June 2014 | Edition No. 10 89269 v2 Take-off Delayed? Kenya’s economy facing headwinds in 2014 with a special focus on delivering primary health care services Take-off Delayed? Kenya’s economy facing headwinds in 2014 with a special focus on delivering primary health care services TABLE OF CONTENTS ABBREVIATIONS AND ACRONYMS .................................................................................................................. i FOREWORD ....................................................................................................................................................... ii ACKNOWLEDGEMENTS ................................................................................................................................... iii MAIN MESSAGES AND KEY RECOMMENDATIONS .......................................................................................... iv EXECUTIVE SUMMARY .................................................................................................................................... v THE STATE OF KENYA’S ECONOMY ................................................................................................................... 1 1. Economic Performance in 2013 .................................................................................................................... 2 1.1 Take-off remains delayed ......................................................................................................................... 2 1.2 Fiscal vulnerabilities are emerging ........................................................................................................ 9 1.3 Monetary policy continues to support economic activity, and the financial sector remains robust ...... 18 1.4 External pressures are subsiding for now but may re-intensify .............................................................. 22 2. Growth Outlook for 2014 - 15 ...................................................................................................................... 27 2.1 Growth prospects remain solid, although the economy is facing headwinds ......................................... 27 2.2 Risks to growth have increased ............................................................................................................... 28 2.3 Good monetary and fiscal policies are critical to maintain growth in the near term and increase ....... 29 it in the longer term SPECIAL FOCUS: ............................................................................................................................................... 33 3. Challenges and Opportunities ...................................................................................................................... 34 3.1 Kenya’s health sector faces many challenges Health outcomes are weak .............................................. 34 3.2 Primary health care is key ....................................................................................................................... 38 3.3 Kenya is well positioned to reform its health sector ................................................................................ 40 3.4 Changes have already improved the delivery of primary health services ............................................... 40 3.5 How can the government address remaining challenges? ..................................................................... 44 REFERENCES ...................................................................................................................................................... 48 ANNEXES ........................................................................................................................................................... 49 List of Figures Figure 1: The gap in per capita GDP between Kenya and its peers narrowed between 1990 and 2012 ..... v Figure 2: The fiscal deficit increased in recent years, pushing up public debt ............................................. vi Figure 1.1: Growth in 2013 would have been higher but for the drought ...................................................... 2 Figure 1.2: Kenya has not grown as rapidly as its regional peers or Sub-Saharan Africa as a whole .............. 3 Figure 1.3: The gap in per capita income between Kenya and its peers narrowed between 1980 and 2012 3 Figure 1.4: GDP growth in Kenya continued to be broad based, driven mainly by industry and services ...... 4 Figure 1.5: Tea and horticulture production were up, coffee down ................................................................ 5 Figure 1.6: Lower rainfall in the fourth quarter reduced hydropower generation and industrial output ...... 5 Figure 1.7: Manufacturing production increased significantly in 2013 before drought set in ........................ 6 Figure 1.8: The mobile money industry continued to boom ........................................................................... 7 Figure 1.9: Slow recovery in the Euro zone and travel advisories reduced tourist arrivals ............................. 7 Figure 1.10: The services sector grew in 2013, but security concerns held back growth in hotels ................. 7 and restaurants Figure 1.11: Consumption spending powered GDP growth in 2013 ............................................................... 8 Figure 1.12: Sound monetary policy helped keep inflation low ....................................................................... 9 Figure 1.13: Food, transport, core, and overall inflation all remained within the Central Bank’s targets ....... 9 Figure 1.14: Kenya’s fiscal deficit remains high ................................................................................................ 10 Figure 1.15: The gap between recurrent and development of the national government narrowed .............. 10 Figure 1.16: Wages and salaries have grown in tandem with GDP .................................................................. 11 Figure 1.17: Tax revenue in all categories increased in 2013/14 ...................................................................... 12 Figure 1.18: VAT revenue in 2013/14 exceeded the target .............................................................................. 13 Figure 1.19: Budget execution rates were much lower for development spending than ............................... 13 for recurrent spending in the first half of 2013 Figure 1.20: Budget execution rates for priority sectors were low in the three quarters of 2013/14 ............. 14 Figure 1.21: Foreign financing of the budget deficit increased in 2013/14 ...................................................... 14 Figure 1.22: Public debt increased, driven by external borrowing ................................................................... 15 Figure 1.23: Private nonbank institutions increased their holdings of Kenyan government securities ........... 15 Figure 1.24: Only two counties met their revenue targets during the first half of 2013/14 ............................ 16 Figure 1.25: Ten counties generated three-quarters of all local revenue in the first half of 2013/14 ............. 17 Figure 1.26: Budget execution rates were well below counties’ own targets .................................................. 18 Figure 1.27: Almost half of all county expenditure went to personnel emoluments ...................................... 18 Figure 1.28: Growth of monetary aggregates slowed but remained below target levels ................................ 19 Figure 1.29: The Central Bank Rate coordinated short-term interest rates, but volatility ............................... 19 in the market was significant Figure 1.30: Lending rates remained sticky downward, but the volume of credit to the private sector grew 20 Figure 1.31: Credit to all sectors of the economy except mining and quarrying rose in 2014 ......................... 20 Figure 1.32: Performance on the Nairobi Securities Exchange (NSE) was weak in the second half of 2013 ... 21 Figure 1.33: The external balance improved, but risks remain ........................................................................ 21 Figure 1.34: Growth in merchandise exports and imports was modest in 2013 ............................................. 22 Figure 1.35: Merchandise exports continue to underperform imports and GDP ............................................ 23 Figure 1.36: Remittance inflows remain strong ................................................................................................ 24 Figure 1.37: Long-term capital inflows declined in 2013, and short-term flows increased ............................. 24 Figure 1.38: The exchange rate was stable and volatility low .......................................................................... 25 Figure 1.39: Appreciation of the trade-weighted exchange rate suggests that Kenya’s .................................. 25 competiveness has declined Figure 1.40: The reserves Kenya has built cushion it from shocks ................................................................... 26 Figure 2.1: Annual GDP growth is projected to remain at about 4.7 percent over the next two years ........ 27 Figure 2.2: Growth in the 1st quarter was low ............................................................................................... 29 Figure B1: Level of real seasonally-adjusted GDP (left scale) and LEAD indicator (right scale) .................... 30 for the period 2006 Q1 – 2014 Q1 Figure B2: Quarterly growth rate of real seasonally-adjusted GDP and LEAD indicator for ......................... 30 the period 2006 Q2 – 2014 Q1 Figure 3.1: Kenya’s maternal mortality rate has fallen since 1990, but the decline has been ....................... 22 much more modest than in some neighboring countries Figure 3.2: Life expectancy in Kenya in 2011 is comparable to that of China in the late 1960s. . . ............... 22 Figure 3.3: . . . and the total fertility rate is comparable to that of Brazil in the Mid 1970s ........................... 35 Figure 3.4: Kenya allocates too little of its budget to health expenditure ...................................................... 35 Figure 3.5: More than 9 percent of Kenyan households reported catastrophic expenditure ........................ 36 on health in 2013, with the figure ranging widely by county Figure 3.6: Kenyan providers can diagnose common health conditions, but many cannot fully treat them 36 Figure 3.7: Health facilities are everywhere but personnel are disproportionately in cities ......................... 37 Figure 3.8: Almost a third of public health providers are absent from their facility ...................................... 38 Figure 3.9: … and 80 percent of those absences are authorized .................................................................... 38 Figure 3.10: Dispensaries have great scope to improve the efficiency of their services than ......................... 39 other types of health care institutions in Kenya Figure 3.11: A comprehensive primary care system requires all of the building blocks .................................. 40 identified by the World Health Organization Figure 3.12: The vast majority of public dispensaries and health centers have Health Facility ...................... 42 Management Committees and work plans Figure 3.13: More than half of Health Care Facility Management Committee members are elected ............ 42 Figure 3.14: The availability of maternal medicines increased under the pull system, ................................... 43 but the availability of pediatric medicines declined Figure 3.15: The proportion of health facilities offering basic emergency obstetric care ranges .................... 44 widely across countries List of Tables Table 1.1: Low rainfall in the fourth quarter caused production of most major food crops to fall .............. 4 Table 1.2: Sources of GDP growth, 2009–13 ................................................................................................. 8 Table 1.3: Spending on all recurrent items except pensions fell ................................................................... 11 Table 1.4: Public sector wage bill, 2012/13–2014/15 ................................................................................... 12 Table 1.5: County revenues and expenditures were well below target in the first half ............................... 17 of 2013/14 (KSh billion) Table 1.6: Asset quality by bank size, April 2013 and April 2004 (percent) .................................................. 22 Table 2.1: Components of GDP growth, 2010–16 ......................................................................................... 27 Table 3.1: Number of registered medical personnel and personnel in training in Kenya, ........................... 38 by profession 2013 Table 3.2: Utilization of outpatient services in Kenya increased between 2003 and 2013 .......................... 39 Table 3.3: Poor Kenyans disproportionately use public health care facilities ............................................... 39 List of Boxes Box 1.1: County governments are now operational ................................................................................... 16 Box 2.1: Estimating GDP Growth based on leading indicators ................................................................... 30 ABBREVIATIONS AND ACRONYMS AMDD Averting Maternal Death and Disability CBK Central Bank of Kenya CBR Central Bank Rate DANIDA Danish International Development Agency GDP Gross Domestic Product HFMC Health Facility Management Committee HSSF Health Sector Services Fund ICT Information Communication and Technology IDA International Development Association IFMIS Integrated Financial Management Information System JKIA Jomo Kenyatta International Airport KSh Kenyan Shilling KEMSA Kenya Medical Supplies Agency KHSSP Kenya Health Sector Strategic and Investment Plan KNBS Kenya National Bureau of Statistics MDGs Millenium Development Goals MEDS Mission for Essential Drugs and Supplies M-health Mobile Health MIA Moi International Airport M-pesa Mobile money MTPII Second Medium Term Plan NEO Net Errors and Omissions NGOs Non-Governmental Organizations NHIF National Hospital Insurance Fund NSE Nairobi Securities Exchange PAYE Pay As You Earn SMS Short Messaging Service Tbill Treasury Bill U.S United States UNFPA United Nations Population Fund UNICEF United Nations International Children’s Emergency Fund VAT Value Added Tax VCT Voluntary Counselling and Testing WHO World Health Organization June 2014 | Edition No. 10 i FOREWORD I t is my pleasure to present the tenth edition of the Kenya Economic Update. Kenya faces many challenges in 2014. Domestic shocks are testing the country’s economic resilience, including coping with difficult security issues, and an inadequate rainfall that threatens to push up food and electricity prices. However, there is also good news. The performance of Kenya’s Eurobond floatation in June exceeded market expectations sending a strong signal that despite its challenges, international investors still have confidence in the Kenyan economy. The World Bank’s latest Country Policy and Institutional Assessment rating—a global exercise which examines key features of an economy’s institutional capacity—gave Kenya has the highest score in Sub-Saharan Africa. And according to the 2014 Economic Survey, Kenya maybe underestimating its economic activity (as has been found recently with other GDP rebasing estimates elsewhere in Africa). Later in the year the results of GDP rebasing being undertaken by Kenya National Bureau of Statistics are expected to be released and will provide new and fresh perspectives on Kenya’s economy. This Kenya Economic Update has three main messages. First, the economy remains strong despite the headwinds it faces in 2014. Kenya’s record of maintaining macroeconomic stability and adhering to credible policies has underpinned its growth in the past; staying this course will help Kenya weather the domestic shocks it faces, allowing it to grow at an annual rate of 4.7 percent in 2014 and 2015. This growth will be powered by aggregate demand, fueled by strong consumption and investment. Second, addressing the fiscal pressures emerging from fiscal expansion is a priority. Given the reduction in fiscal buffers and the fiscal risks linked to the wage bill and devolution, efficiency gains needs to be achieved. This will help address the access and equity challenges such as those in the health sector highlighted in this Kenya Economic Update. Additional spending should be pursued only if they are necessary and careful attention is given to sustainability. Third, Kenya’s health outcomes are not commensurate with its aspirations of achieving middle income status. More needs to be done to improve these outcomes. Global evidence indicates that the best way to improve health outcomes is to improve primary health care. Doing so involves reallocating some of the health budget away from curative care towards preventive and promotive care. As in the past, we are proud to have worked with many Kenyan stakeholders during the preparation of this report. We hope that it will contribute to their discussions of policy issues that will contribute to help Kenya grow, permanently reduce poverty, and bring shared prosperity to all Kenyans. Diariétou Gaye Country Director for Kenya World Bank ii June 2014 | Edition No. 10 ACKNOWLEDGEMENTS This tenth edition of the Kenya Economic Update was prepared by a team led by John Randa and Gandham N.V. Ramana supervised by Apurva Sanghi. The core team consisted of Jane Chuma, Angélique Umutesi, Catherine Ngumbau, Jane Bogoev, Allen Denis, Gerard Kambou, Alberto Gallachi, Barbara Karni, Fred Owegi and Anne Khatimba. The team acknowledges contributions from Robert Waiharo. The report benefitted from insights of several peer reviewers including Sergey Ulatov, Elitza Alexandrova Mileva, Albertus Voetberg, Dinesh Nair, Armando Morales Regio, Kathleen A. Whimp, George Addo Larbi, Jane W. Kiringai, Borko Handjiski and Laban Maiyo. The team also received guidance from Pablo Fajnzylber, Thomas O’Brien and Diariétou Gaye. Partnership with key Kenyan policy makers was instrumental in the production of this report. On June 20, 2014, a draft of the report was presented at the 16th Quarterly Economic Roundtable. The meeting was attended by senior officials from the National Treasury, Ministry of Devolution and Planning, the Central Bank of Kenya, the Kenya Revenue Authority, Kenya Institute of Public Policy Research and Analysis, the International Monetary Fund and the Ministry of Health. June 2014 | Edition No. 10 iii MAIN MESSAGES AND KEY RECOMMENDATIONS Main messages Kenya’s economy remains strong, enabling it to weather the headwinds it faces. Maintenance of macroeconomic stability and adherence to credible policies has underpinned Kenya’s growth in the past. Continuing to adhere to these policies will help the country surmount domestic shocks, allowing it to grow 4.7 percent a year in 2014 and 2015. Addressing the pressures emerging from fiscal expansion is a priority. The large public sector wage bill and devolution have reduced fiscal buffers and increased fiscal risks. Efficiency gains will need to be found to prevent them from derailing growth. Additional expenditures should be incurred only if they are necessary and attention paid to sustainability. Kenya’s health outcomes are not commensurate with its aspirations of achieving middle income status. Global evidence indicates that investing in primary health care is the most cost-effective way to improve health outcomes. As part of the new emphasis on primary care, resources should be reallocated from curative interventions to preventive and promotive care. Key recommendations to stabilize and sustain a robust growth Deepen fiscal consolidation without reducing infrastructure spending. Fiscal buffers could be rebuilt by reducing duplication at the national level of activities being undertaken by county staff; managing and rationalizing the number of national and county staff; and increasing the efficiency of public spending in education and health, two sectors in which public expenditure tracking surveys have identified wastage. Investment on infrastructure—the availability of which determines both a country’s ability to accelerate growth by connecting regions and markets, as well as to widen the distribution of economic opportunities and the benefits of economic development across different regions and socio-economic groups—should not be cut. Achieving more inclusive growth will also be key for enhancing peace and stability, thus complementing the Government’s efforts to addresss partial and income inequality. Expand the engines of growth to include not only consumption but also investments and exports. Over the medium term, Kenya needs to boost productivity and regain its competitiveness. To accelerate its growth rates, Kenya needs to continue investing in infrastructure and human capital, improve the business and regulatory environment, and diversify exports. The challenge is to craft policies that raise productivity and foster job creation, in order to ensure that all engines of the economy contribute to growth. To that end, maintaining Kenya’s good macroeconomic management will be key, but complementary efforts will be needed in order to create a business environment, promote job creation and higher rates of investment in physical and human capital. Key recommendations that can help Kenya improve the delivery of primary health care Focus first on making existing public primary health care facilities operational. Ensure that the non-functional primary health care facilities are operational at the counties. Devolution provides a unique opportunity to strengthen the delivery of primary healthcare services. With counties now responsible for delivering primary health care services, there is renewed hope that some chronic weaknesses-especially inadequate staffing, weak retention, and absenteeism will be addressed. Rather than build new infrastructure, county governments should focus on making existing infrastructure functional. Build on partnerships with faith-based organizations and partner with the private sector. Governors and Chief Executives of health need to look for and take advantage of opportunities to involve all stakeholders (NGOs, faith- based organizations, private sector and donors) that can help fill gaps in the delivery of primary health care services. Optimize the use of fixed facilities. The inpatient services of many health centers are grossly underutilized. The reasons for underutilization should be determined. If it turns out that such services are not needed, counties should consider alternative health care uses for the facilities such as maternal shelters, nutrition rehabilitation etc., and rationalize future infrastructure investments. iv June 2014 | Edition No. 10 EXECUTIVE SUMMARY Growth will remain robust—but Kenya faces by low fiscal deficits and low levels of government strong headwinds in 2014 debt—has allowed Kenya’s peers to start closing the E conomic growth in Kenya remains robust. large income gap that once existed between them Strong economic performance continued in 2013 and Kenya. In order to retain its advantage, Kenya as the economy grew 4.7 percent, an uptick from can accelerate its own agenda of structural reforms 4.6 percent in 2012. Growth was driven by robust that are key to higher and sustainable growth. The consumption spending and public investment in priority should be on reforms aimed at increasing infrastructure, as well as higher industrial and the flexibility of its economy to facilitate the transfer services output. Growth was underpinned by of resources toward the tradable sector, in order to macroeconomic stability, including single-digit increase exports and create jobs. inflation and a stable exchange rate. On the negative side, weak investor confidence resulted in anemic Macroeconomic stability underpinned growth in private investment and subdued GDP growth. And 2013, as lower inflation supported the demand drought in the fourth quarter of 2013 depressed for goods and services. Inflation expectations growth in agriculture and increased electricity were anchored at a lower level as a result of lower prices, driving up production costs and reducing international food and fuel prices and prudent GDP by an estimated KSh 23.8 billion (0.7 percent). monetary policy. Inflation averaged 5.7 percent (7.3 percent for food) in 2013 and 6.9 percent (9.6 Despite its robust performance, Kenya continues percent for food) in the 12 months ending in May to underperform its regional peers. Kenya’s 2014. Industrial output growth rebounded strongly neighbors are catching up in terms of per capita GDP in 2013, partly thanks to stable exchange rates for (Figure 1). Annual real GDP growth in the region most of the year. Economic activity softened in the averaged almost 6.1 percent between 2000 and last quarter of 2013, as inadequate rainfall in key 2012, accelerating the recovery that started in the bread basket zones reduced agricultural output, late 1990s. This strong performance—driven partly reducing GDP by KSh 23.8 billion (0.7 percent). Figure 1: The gap in per capita GDP between Kenya and its peers narrowed between 1990 and 2012 GDP per capita in constant US dollars Index of GDP per capita 1,600 200 GDP per capita (constant 2005 US$) Index of GDP per capita (1999 = 100) 1,400 180 1,200 160 1,000 140 800 120 600 100 400 200 80 0 60 2011 2012 2008 2009 2010 2006 2007 2003 2004 2005 2002 1999 2000 2001 1997 1998 1995 1996 1992 1993 1994 1990 1991 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Burundi Kenya Rwanda Tanzania Uganda Burundi Kenya Rwanda Tanzania Uganda Source: World Development Indicators (World Bank) June 2014 | Edition No. 10 v Executive Summary The ongoing fiscal expansion is widening the fiscal Medium-term growth prospects remain favorable, deficit and raising the public debt-to-GDP ratio. despite emerging challenges. In the base case The fiscal deficit remained high at 6.6 percent of scenario, GDP growth is projected to increase 4.7 GDP, as a result of ambitious public investment percent in both 2014 and 2015. In the optimistic programs and increases in public sector wages. scenario, GDP is projected to increase 5.0 percent Fiscal policy remained expansionary, even though in both 2015 and 2016. Robust domestic demand, growth returned to its trend level. As a result, fiscal underpinned by investment in infrastructure and buffers were reduced, raising Kenya’s vulnerability household consumption, will continue to drive growth to shocks. The debt-to-GDP ratio crossed the 50 during the forecast period. Public consumption will percent threshold in 2014, raising concerns about remain high. A large public sector wage bill, transfers the level of indebtedness and the availability of fiscal from the national government to the counties, and buffers to absorb volatility going forward (Figure 2). recurrent expenditures for social sector projects will Figure 2: The fiscal deficit increased in recent years, pushing up public debt continue to drive public expenditures in 2014 and probably thereafter. External demand for Kenyan 60 10 55.8 51.7 51.8 9 exports and investment flows should revive as the 50.3 global economy strengthens. Despite the increase Fiscal deficit (share of GDP, percent) 50 47.3 Public debt (share of GDP, percent) 45.5 8 40 7.1 7 in exports, however, net exports are expected to 6.6 6 slow GDP growth over the forecast horizon, because 30 5 5.6 demand for imported capital goods is projected to 4 20 3 remain strong. 2 10 1 Inflationary pressures are building. Inadequate 0 0 rainfall could create macroeconomic instability in 2011/12 2012/13 2013/14 2014. The extent of the effect remains unclear, Public debt to GDP (net) Fiscal deficit Public debt to GDP (gross) but higher food and electricity prices are expected Source: Quarterly Economic and Budgetary Review (National Treasury) to raise inflation above its target level, putting macroeconomic stability, private investment, and The World Bank projects that Kenya’s GDP will grow projected growth at risk. 4.7 percent a year in 2014 and 2015, supported by stronger global economic activity among its trading Several risks threaten growth. Drought (or erratic partners. The projections assume that the impact rainfall) could reduce agricultural production, of inadequate rainfall and the insecurity caused by leading to higher food and electricity prices as terrorist activity will be limited. The economy grew by well as inflationary pressures, the tightening of just 2.7 percent in the first quarter of 2014, mainly as global monetary conditions could reverse capital a result of delayed rain in the bread basket areas of flows, and the domestic security situation could the Rift Valley and increased insecurity. These shocks deteriorate further. Strong inflationary pressures caused the Bank to reduce its growth projection for have been emerging since April, driven partly by 2014 by 0.5 percentage points since the last Kenya unfavorable bad weather. Unreliable electricity Economic Update. The new projections reflect the supply (exacerbated by low rainfall) continues to effects of the drought, the deteriorating security impose high costs on enterprises. These effects situation, the low level of budget execution, and could dampen household consumption and reduce tighter global credit as the U.S. Federal Reserve domestic demand. Increased volatility in financial winds down its expansive monetary policy. markets and capital flows could slow growth by vi June 2014 | Edition No. 10 Executive Summary raising domestic interest rates and inflation. A . . . but universal health coverage is attainable worsening security situation would have a severe if the right polices are implemented effectively D effect on the tourism sector and instill fear among evolution of health care to the counties has the current and potential investors across sectors. potential to improve health outcomes. Under Kenya’s new constitution, operational aspects of the Addressing the fiscal pressures emerging from fiscal delivery of health care services have been devolved expansion is a priority for the authorities. Given the to newly created county governments; the national reduction of fiscal buffers and the fiscal risks linked to government is now responsible only for policy the wage bill and devolution, a strong emphasis on making and regulation. The new constitution also achieving efficiency gains, is warranted particularly guarantees equitable access to health services to all. in order to address the access and equity challenges in the health sector. Additional expenditures should Direct funding of lower-level hospitals—through be pursued only if they are sustainable. the Health Sector Services Fund—has already improved services. In 2010 the Ministry of Health Health care for many Kenyans introduced direct funding to dispensaries and health is inadequate . . . centers, through the Health Sector Services Fund D espite economic growth over the past decade, health care outcomes in Kenya remain weak. Rates of maternal mortality and stunting among (HSSF). This funding mechanism currently covers more than 3,000 facilities and will be expanded to about 6,000 by 2015. Two years after its launch, children have barely changed, and the incidence of the HSSF has already improved the quality and non-communicable diseases is rising. quantity of services, community participation, and governance. Supporting increased utilization Catastrophic health-related spending continues has been the shift from a kit-based “push” supply to push Kenyan households into poverty. The system to a demand-based “pull” system as well as proportion of households reporting catastrophic the implementation of a human resources strategic spending on health fell from 11.4 percent in 2007 plan that has deployed more than 3,000 nurses to to 9.4 percent in 2013, according the most underserved areas. to preliminary results of the 2013 household healthcare utilization Kenya’s quest for universal access is and expenditure survey. But this Two years after its achievable but expensive. Investing figure still means that health-related launch, the HSSF has in comprehensive primary health expenditure pushed hundreds of already improved the care is a cost-effective way to thousands of Kenyan families into quality and quantity of achieve universal health coverage. poverty last year alone. Improving services, community The sector must be consolidated, access to primary care would participation, and and further strengthened, and contribute to achievement of the governance the recently introduced systems twin goals of the World Bank Group— need to be expanded at all levels, to eliminate extreme poverty and especially through the primary promote shared prosperity—because the poor tend health care pyramid. Health care spending needs to benefit most from primary health care and out- to be reallocated away from curative care toward of-pocket health care expenditures are an important preventive and promotive care. A multisectoral, cause of poverty. multidisciplinary, and holistic approach is June 2014 | Edition No. 10 vii Executive Summary necessary that increases the number of health staff for health insurance through the National Health in all disciplines, establishes an effective supply chain Insurance Fund. system for drugs and laboratory services, ensures improved transport services and infrastructure, and Creation of a comprehensive primary health care provides adequate water and sanitation. system depends on several factors, including: • good policies and legislation at the national and The health care system needs to be more county level that emphasize participation by communities and individuals; equitable. Seventy percent of health costs in Kenya • participatory approaches to planning and go to hospital and specialist care, which benefit management; just 30 percent of the population (Logie and others • health literacy, especially among women, which 2010). Greater equitability could be achieved by has been found to reduce both maternal and allocating more funds to primary health care and by child morbidity and mortality; and ensuring access to health insurance by the poor. The • appreciation by the community of good-quality World Bank is supporting the Ministry of Health in services, which increases utilization. implementing the phased introduction of subsidies viii June 2014 | Edition No. 10 The State of Kenya’s Economy The State of Kenya’s Economy 1. Economic performance in 2013 E conomic activity remained robust in Kenya. GDP grew 4.7 percent, up from 4.6 percent in 2012, supported by strong domestic demand, particularly higher household consumption as well as investment and consumption. Investment demand was flat, with gross fixed capital formation rising by 2.8 percent of GDP and inventory stocks falling by the same margin. Continued strong macroeconomic management kept inflation down and reduced growth volatility. Growth continued to be constrained by structural bottlenecks, most of them associated with the country’s business environment, and by weak external demand from trading partners. 1.1 Take-off remains delayed The industry and services sectors, which were less Growth in 2013 was robust but below expectations affected by poor rainfall than the agriculture and power sectors, were the main drivers of growth. K enya’s economy grew 4.7 percent in 2013, despite political uncertainty during an election year and a weak global environment. This growth The macroeconomic environment was stable. Inflation remained in single digits, as inflationary was the highest ever in an election year and expectations continued to be anchored at a lower represented a modest increase over 2012, when level. Portfolio flows into Kenya’s money and output rose 4.6 percent. The economy built on the equities markets helped the Kenya shilling remain momentum generated in the last quarter of 2012 by stable despite the high current account deficit growing 5.2 percent in the first half of 2013. Output and political uncertainty in an election year. The slowed in the second half, growing just 4.3 percent peaceful general elections and smooth transfer of (4.6 percent in the third quarter and 3.9 percent power in March reduced political uncertainty in the in the fourth quarter) (Figure 1.1). The slower second half of 2013, further stabilizing the shilling. growth reflected a combination of factors, including implementation of the Value Added Tax (VAT) Growth of 4.3 percent in the second half of the law, which tempered consumption, and a severe year was the lowest level since 2009, when Kenya drought in the last quarter of 2013, which reduced was hit with quadruple shocks. Challenges in agricultural production and electricity generation. implementing the budget during the transition Figure 1.1: Growth in 2013 would have been higher but for the drought Annual GDP growth, 2010-13 Quarterly GDP growth, 2011-13 7 6 5.7 5.8 5.2 5.2 6 5.0 5 4.6 4.7 Annual GDP growth (percent) 4.5 4.6 5 4.6 4.7 4.0 3.9 4.4 4 3.8 3.4 4 Percent 3 3 2 2 1 1 0 0 1 2 3 4 1 2 3 4 1 2 3 4 2010 2011 2012 2013 2011 2012 2013 Source: Kenya National Bureau of Statistics 2 June 2014 | Edition No. 10 The State of Kenya’s Economy Figure 1.2: Kenya has not grown as rapidly as its regional peers or Sub-Saharan Africa as a whole Average growth in selected countries in East Africa, 2003-13 Annual growth in Kenya and Sub-Saharan Africa excluding South Africa, 1998-2013 8 8 6.9 7.0 7.2 7 7 5.8 6.0 6 6 Percent growth Annual growth (percent) 5 4.6 5 4.7 4 4 3.6 3 3 2 2 1 1 0 0 1998 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 /2002 Burundi Kenya SSA excl. Tanzania Uganda Rwanda ZAF Kenya Sub-Saharan Africa excluding South Africa Source: Kenya National Bureau of Statistics and Global Economic Prospects (World Bank) period and drought significantly contributed to of 4.4 percent between 2009 and 2013 was lower reduced growth in the second half. The drought in than in Uganda (5.1 percent), Tanzania (6.7 percent), the fourth quarter of 2013 slowed growth in the and Rwanda (6.9 percent) (Figure 1.2). agriculture and electricity and water sectors. As a result, agricultural GDP fell from 6.2 percent in the Real GDP per capita in Kenya is the highest in the second half of 2012 to 0.8 percent in 2013, and the region, but the gap is narrowing, as a result of growth of GDP from electricity and water declined faster GDP growth in most other countries in Sub- from 11.0 percent to 2.3 percent. The drought alone Saharan Africa since the 1990s (Figure 1.3). As a reduced GDP by 0.7 percent (KSh 23.8 billion). result of increased domestic demand and good macroeconomic policies, GDP per capita more than Kenya’s economy remains resilient, despite the doubled in Rwanda and Uganda between 1990 perennial shocks that have caused it to lag its and 2012 (measured in constant 2005 dollars). peers. Sound macroeconomic policies have enabled In Rwanda, which was recovering from the 1994 Kenya’s economy to achieve more balanced growth genocide, per capita GDP rose from US$ 575 in 1995 in recent years, despite various domestic and to US$ 1,167 in 2012. Uganda’s real GDP per capita external shocks. Nevertheless, average real growth increased from US$ 568 in 1990 to US$ 1,165 in Figure 1.3: The gap inper capita income between Kenya and its peers narrowed between 1980 and 2012 GDP per capita in constant U.S. dollars Index of GDP per capita GDP per capita (constant 2005U.S. dollars) 1,600 200 Index of GDP per capita (1999 = 100) 1,400 180 1,200 160 1,000 140 800 120 600 400 100 200 80 0 60 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Burundi Kenya Rwanda Tanzania Uganda Burundi Kenya Rwanda Tanzania Uganda Source: World Development Indicators (World Bank) June 2014 | Edition No. 10 3 The State of Kenya’s Economy 2012. In contrast, Kenya’s real GDP per capita stood Figure 1.4: GDP growth in Kenya continued to be broad based, driven mainly by industry and services at US$ 1,522 in 2012, up from US$ 1,421 in 1990, an increase of just 6 percent over a period of more than 7 6.7 two decades. 6 5.8 Annual growth (percent) 5.3 5.5 5.3 5 4.8 All production sectors experienced growth 4.2 K 4 enya’s economic growth continues to be broad 3.4 3.2 3.0 3 based, driven by all main sectors. For the second 2.0 year in a row, all main sectors of the economy 2 1.5 contributed to GDP growth in 2013 (Figure 1.4). 1 Agriculture output expanded 3.0 percent, down 0 from 4.2 percent in 2012. The sector’s performance 2011 2012 2013 deteriorated sharply in the fourth quarter, as Agriculture Manufacturing Other industries Services insufficient rain caused growth in agricultural output Source: Kenya National Bureau of Statistics to fall 0.2 percent, down from 5.7 percent in the fourth quarter of 2012. Tea production increased 17 and 11 percent of GDP, grew 4.8 percent in 2013, up percent in 2013, rebounding from 2012, when annual from 3.2 percent in 2012. “Other industry,” (which production fell 2 percent. Other major crops did not comprises mainly construction [56 percent] and perform as well (Figure 1.5). Output of maize, Kenya’s electricity and water [36 percent]) grew 5.8 percent. staple crop, declined 2 percent, with the number of This growth was constrained by inadequate rainfall bags produced falling from 39.7 million in 2012 to in the fourth quarter and problems in the lands 38.9 million in 2013. Production of millet declined office that affected title registration of leases, land 12.5 percent, beans 10.3 percent, and sorghum titles and construction. 5.3 percent (Table 1.1). Horticulture production increased 4 percent, rebounding considerably from Inadequate water for hydro power generation led 2012, when output fell 5 percent. to lackluster growth of the electricity and water subsector in the fourth quarter. Electricity prices Production in the industrial sector increased in (and therefore production costs) rose, as higher- 2013, mainly as a result of the stable exchange priced thermal power was used to make up for rate, low inflation, and, until the fourth quarter, the shortfall in hydropower. The worst-affected lower electricity prices. Manufacturing, which industries were construction and mining and the contributes 60 percent of total industrial production quarrying subsectors (Figure 1.6). Domestic sugar Table 1.1: Low rainfall in the fourth quarter caused production of most major food crops to fall Percent Crop Unit 2009 2010 2011 2012 2013 change 2012/13 Maize Millions of bags 27.1 35.8 34.4 39.7 38.9 –2.0 Beans Millions of bags 5.2 4.3 6.4 6.8 6.1 –10.3 Sorghum Millions of bags 1.1 1.8 1.8 1.9 1.8 –5.3 Millet Millions of bags 0.6 0.6 0.8 0.8 0.7 –12.5 Wheat Millions of tonnes 0.1 0.2 0.1 0.2 0.2 19.5 Potatoes Millions of tonnes 2.6 2.7 1.6 1.5 2.1 40.0 Source: Kenya National Bureau of Statistics Note: Production data are not cumulative 4 June 2014 | Edition No. 10 The State of Kenya’s Economy Figure 1.5: Tea and horticulture production were up, coffee down Coffee production 50 Cumulati ve in metric tonnes, thousands 40 30 20 10 0 2012 2013 Tea production Horticulture exports 500 250 Cumulati ve in metric tonnes, thousands Cumulati vein metric tonnes, thousands 400 200 300 150 200 100 100 50 0 0 2012 2013 2012 2013 Source: Kenya National Bureau of Statistics production expanded 21.5 percent, despite high Services experienced buoyant growth, thanks operational costs and competition from cheap to a stable macroeconomic environment. imported sugar (Figure 1.7). Galvanized sheet Improved access to private sector credit buoyed production grew 19.3 percent; soft drink production activity in wholesale and retail trade and financial 12.8 percent; and cement production 9.0 percent, intermediation, which helped increase output in up from 3.6 percent in 2012. the services sector. The major drivers of growth Figure 1.6: Lower rainfall in the fourth quarter reduced hydropower generation and industrial output Domestic electricity generation Growth of selected industrial subsectors, by quarter, 2013 Local electricity generation (million of KWh) 450 16 400 350 11 Annual growth (percent) 300 250 6 200 150 100 1 50 Q1 Q2 Q3 Q4 0 -4 Jan Mar May Jul Sept Nov Jan Mar May Jul Sept Nov Jan Mar May Jul Mar Sept Nov Jan -9 2011 2012 2013 2014 Hydro Geo thermal Thermal Mining and quarrying Manufacturing Electricty and water Construction Source: Kenya National Bureau of Statistics June 2014 | Edition No. 10 5 The State of Kenya’s Economy Figure 1.7: Manufacturing production increased significantly in 2013 before drought set in Sugar Soft drinks 700 410 600 400 Thousands of metric tonnes 390 500 Millions of liters 380 400 370 300 360 200 350 100 340 0 330 2012 2013 2012 2013 310 Galvanized sheet 5.1 Cement 300 5.0 Thousands of metric tonnes Thousands of metric tonnes 290 4.9 280 4.8 270 4.7 260 4.6 250 240 4.5 230 4.4 2012 2013 2012 2013 Source: Kenya National Bureau of Statistics were financial intermediation and transport and 64—have mobile phone subscriptions. The number communication. Financial intermediation grew of Internet users grew 31 percent, rising from 16.3 7.2 percent in 2013, up from 6.5 percent in 2012, million in 2012 to 21.3 million in 2013. Penetration as commercial banks provided more credit to of Internet subscriptions increased 55 percent, from the private sector following optimism after the 8.5 million in 2012 to 13.2 million in 2013. general election, as demand rose. Transport and communication expanded 6.0 percent, up from 4.7 The ICT sector is a source of employment and a percent in 2012. This subsector was driven mainly facilitator of daily financial transactions. The mobile by transport expansion, as more vehicles were money transfer industry has been booming: the needed during the electioneering period (new number of customers grew 21.5 percent in 2013, vehicle registration rose 28.4 percent in 2013), and from 21.4 million to 26.0 million, and the value of by the ongoing massive infrastructure construction. transactions rose 23.5 percent to KSh 182.5 billion at New regulations on minibuses also contributed to the end of December 2013 (Figure 1.8). The number improved performance. of agents increased 50 percent, from 62,300 in December 2012 to 93,689 December 2013. The information and communication technology (ICT) subsector skyrocketed in 2013. The economy Security threats hurt the tourism sector. Hotels continued to reap benefits from the use of modern and restaurants remained a dragon growth, partly technology in service delivery. Some 31.3 million because security threats depressed tourist arrivals Kenyans—71 percent of the total population and (Figures 1.9 and 1.10). The number of tourist arrival more than 120 percent of people between 15 and at both Jomo Kenyatta International Airport (JKIA) 6 June 2014 | Edition No. 10 The State of Kenya’s Economy Figure 1.9: Slow recovery in the Euro zone and travel advisories Figure 1.8: The mobile money industry continued to boom for Kenya reduced tourist arrivals Mobile money payments 130 200 Number of tourist arrival (thousands) 180 120 160 172.8 140 110 120 100 115.0 100 80 90 60 65.6 40 80 20 26.1 0 70 Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov Jan 60 2010 2011 2012 2013 2014 50 Number of Customers (millions) Transactions (millions) Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Value of transactions (billions of KSh) Agents (thousands) 2012 2013 Source: Central Bank of Kenya and Kenya National Bureau of Statistics Source: Kenya National Bureau of Statistics and Moi International Airport (MIA) fell throughout The economy ran on one engine in 2013 A the year, particularly during the peak season of ggregate demand softened in 2013, as a result June–September. The downturn in the first quarter of the collapse of growth in net investment reflected security uncertainties during the general expenditure and lower growth in private elections. The expected recovery in the peak consumption. Aggregate demand declined from season was disrupted by a fire at JKIA in August. 6.7 percent in 2012 to 4.1 percent in 2013. The drop Slow recovery in the Euro area, which accounts was attributed to the much slower increase in gross for more than 20 percent of total passengers who fixed capital formation, which grew 11.5 percent land at JKIA, also hurt the sector. For the year as in 2012 and just 2.3 percent growth in 2013. The a whole, the number of tourist arrivals decreased weighted growth of investment expenditure to 11.0 percent, tourism earnings fell 2.1 percent, GDP fell from 2.6 percent in 2012 to less than and bed-night occupancy dropped 3.8 percent, 0.03 percent in 2013. Private final consumption leading to a 4.5 percent contraction of the hotel expenditure fell from 5.8 percent (unweighted) to and restaurant sector. 4.5 percent over the same period. Figure 1.10: The services sector grew in 2013, but Domestic consumption remained the main driver of security concerns held back growth in hotels and restaurants growth in 2013 (Figure 1.11). Consumption (private and public) grew 4.9 percent, down from 5.4 percent Wholesale and retail trade in 2012 (Table 1.2). It was the only source of GDP Financial intermediation growth. Private consumption rose 4.5 percent, down Transport and communication from 5.8 percent in 2012. The lower rate of growth Education of consumption is attributed to slower growth in Public administration food and beverages, which grew 8 percent, down Real estate, renting, business services from 14 percent in 2012, probably as a result of the Other services new VAT law and enforcement of anti–drunk driving Hotels and restaurants regulations. Public final consumption grew 9.6 -5 -3 -1 1 3 5 7 9 percent, up from 5.7 percent in 2012. The increase Annual growth (percent) reflected election spending and the establishment of 2013 2012 new offices that were created after the election. Source: Kenya National Bureau of Statistics June 2014 | Edition No. 10 7 The State of Kenya’s Economy Figure 1.11: Consumption spending powered GDP growth in 2013 Lending rates declined in 2013, as a result of the stable macroeconomic environment, but political 8 uncertainties related to the general elections 6 delayed new ventures and investments during the 5.8 4.7 4.4 4.6 first half of the year. In the second half of the year, 4 the transitional challenges of implementing the Percentage points 2 2.7 budget prolonged investors’ wait, as they remained cautious about the new political environment. In 0 the face of low investments, companies met market demand by destocking their inventories. -2 -4 2009 2010 2011 2012 2013 The increase in net exports was one of the main Consumption Net investment Net exports GDP growth (percent) contributions to GDP growth in 2013. A sharp Source: Kenya National Bureau of Statistics reduction in imports helped reduce the negative impact of imports on GDP growth (see Figure 1.11). Investment activities slowed significantly in 2013, The growth of imports of goods and services declined as companies drew down their inventories. In significantly, to 2.8 percent in 2013, down from 11.6 anticipation of the general election, most investors percent in 2012, as investors ran down inventories played a wait and see attitude, by investing less in built up before the election. Low international oil capital equipment in 2013 than they did in 2012. prices reduced the import bill, and good rains in As a result, the contribution of net investments to the first half of the year reduced the need for food growth weakened significantly. Real gross fixed imports. The reduction in imports slightly narrowed capital formation grew 2.3 percent in 2013, down the gap between exports and imports, neutralizing from 11.5 percent in 2012. The growth collapse the effect of a negative net export balance that had is explained by the tepid growth of investment been restraining overall economic growth. However, expenditure in transport equipment (which grew exports deteriorated, as a result of subdued global 2.1 percent, down from 27.0 percent in 2012) demand from both the region and traditional market and other machinery equipment (which grew in Europe, with global demand for Kenyan goods and 0.4 percent, down from 11.4 percent in 2012). services rising just 2.8 percent in 2013, down from Table 1.2: Sources of GDP growth, 2009–13 (percentage points, except where otherwise indicated) Item 2009 2010 2011 2012 2013 GDP growth (percent) 2.7 5.8 4.4 4.6 4.7 Consumption 4.4 6.6 3.0 5.4 4.9 Government 0.5 0.9 0.7 0.8 1.4 Private 3.9 5.7 2.3 4.6 3.5 Net investment 1.3 1.2 3.7 2.6 0.0 Gross fixed capital formation 0.7 1.8 3.1 3.0 0.6 Change in inventories 0.6 –0.6 0.6 –0.4 –0.6 Exports –2.6 4.3 2.5 1.7 0.8 Imports 1.1 2.5 6.4 5.2 1.3 Discrepancies 0.8 –3.8 1.6 0.1 0.3 Source: Kenya National Bureau of Statistics 8 June 2014 | Edition No. 10 The State of Kenya’s Economy 6.0 percent in 2012. Poor performance of exports Figure 1.12: Sound monetary policy helped keep inflation low reflected low commodity prices on international 20 markets. The volume of production of major exports 18 crops, including tea and horticulture, rose. 16 14 Inflation remained subdued 12 I 10 Percent nflation was in the single-digits throughout 2013. 8 The average overall consumer price index (CPI) 6 rose 5.7 percent, down from 9.6 percent in 2012. 4 The steep decline reflected three main factors: low 2 domestic food prices, effective monetary policy, and 0 stable oil prices. 4 0 0 1 1 3 12 12 2 -1 -1 t-1 -1 -1 12 -1 -1 n- v- b ay ar g p r n- Oc Au Fe Ap No Se Ju M M Ja Central Bank Rate Core inflation Domestic food prices were low throughout the Source: Kenya National Bureau of Statisticsand Central Bank of Kenya year, despite inadequate rain during October– December. Average retail prices fell 11.4 percent Both domestic and international oil prices were low for maize and 4.6 percent for beans. Average food and stable. As a result, transport inflation fell, from inflation stood at 7.3 percent, down from 10.5 7.8 percent in 2012 to 4.8 percent in 2013. percent in 2012. Food prices did rise in September, following implementation of the VAT Act of 2013, 1.2 Fiscal vulnerabilities are emerging which taxes some food-related items, but the spike The overall fiscal deficit remains high I was short-lived. ncreased spending has weakened Kenya’s fiscal position since 2011/12. After the March 2013 Monetary policy was sound and sustainable. elections, which ushered in the devolved system of Despite a reduction in the central bank rate (CBR), government, government expenditure experienced from 9.5 percent in the first quarter of 2013 to 8.5 a significant uptick to accommodate the new county percent throughout the rest of the year, there was no sign of demand-pull inflation (Figures 1.12 and governments’ expenditure and finance the pre- 1.13). Nonfood nonfuel inflation fell from 9.5 percent election promises under the Jubilee Government in 2012 to 4.8 percent in 2013. manifesto. According to the latest Quarterly Budget Figure 1.13: Food, transport, core, and overall inflation all remained within the Central Bank’s targets 30 Food, transport, core and overall inflation rates, April 2010 - April 2014 25 Inflation rate (percent) 20 15 10 5 0 12 2 12 2 0 10 0 1 11 13 3 11 13 1 3 14 4 -1 1 -1 -1 -1 -1 1 -1 -1 b- g- v- g- b- g- b- g- v- b- ay ay v ay ay v ay No Au No No No Fe Au Au Au Fe Fe Fe M M M M M Food inflation Transport Inflation Core Inflation Overall Inflation Source: Kenya National Bureau of Statistics June 2014 | Edition No. 10 9 The State of Kenya’s Economy Contribution of food, energy, and core inflation to overall inflation rate, May 2010 - May 2014 100 80 60 Percent 40 20 0 0 0 10 10 11 1 1 1 11 11 12 2 2 2 12 12 13 3 3 3 13 13 14 4 4 -1 l-1 -1 -1 l-1 -1 -1 l-1 -1 -1 l-1 -1 -1 p- v- n- p- v- n- p- v- n- p- v- n- ay ar ay ar ay ar ay ar ay Ju Ju Ju Ju No No No No Ja Ja Ja Ja Se Se Se Se M M M M M M M M M Food Energy Core Source: Kenya National Bureau of Statistics and Economic Review, spending increased from 30.9 spending narrowed, reflecting Kenya’s desire to percent of GDP in 2012/13 to 36.7 percent of GDP in reorient government spending toward capital 2013/14 (Figure 1.14). Revenue reforms, particularly spending (Figure 1.15). Development spending the VAT Act of September 2013, improved the overall increased from 8.5 percent of GDP in 2012/13 to balance, but expenditure increased more than 11.2 percent in 2013/14, and recurrent expenditure revenue collections. As such, the overall deficit declined from 22.1 percent of GDP to 19.8 percent remained high, at an estimated 6.6 percent of GDP of GDP. As a share of total spending, development in June 2014, down from 7.1 percent of GDP in spending increased from 27.8 percent in 2012/13 June 2013. to 36.1 percent in 2013/14, and recurrent spending declined from 72.2 percent to 63.9 percent.3 This Development spending (most of which is capital trend is expected to continue in the medium term, spending) by the national government increased, as infrastructure is among the priorities of the while recurrent spending declined. The gap Second Medium Term Plan (MTPII), launched in between recurrent expenditure and development October 2013. Figure 1.15: The gap between recurrent and development Figure 1.14: Kenya’s fiscal deficit remains high of the national government narrowed 36 25 20 26 Percent of GDP 15 Percent of GDP 16 10 6 5 -4 1999/00 - 2010/11 2011/12 2012/13 2013/14 0 -14 20 00 20 01 20 2 20 03 20 04 20 5 20 06 20 7 20 08 20 09 20 0 20 11 20 12 20 3 4 /0 /0 /0 /1 /1 /1 / / / / / / / / / 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 19 Government revenue Government expenditure Primary balance, cash basis Overall balance, including grants (cash basis) Recurrent expenditure Development expenditure Source: Quarterly Budget and Economic Review, March 2014 (National Treasury) Source: Quarterly Budget and Economic Review, March 2014 (National Treasury). Note: Figures for 2013/14 are estimates 1 The total budget here includes development and recurrent spending only. Some government expenditures (such as county transfers and spending on the judiciary, parliament, and drought relief) fall into neither category. 10 June 2014 | Edition No. 10 The State of Kenya’s Economy Recurrent spending of the national government percent of GDP in 2013/14, after some national civil declined significantly in 2013/14, as a result of the servants’ pay was transferred to the counties. reclassification of spending for devolved functions (Table 1.3). Increased spending in 2012/13 reflected Figure 1.16: Wages and salaries have grown in tandem with GDP the cost of wages and salaries of constitutional 140 9 offices set by the new constitution, higher domestic 8 120 interest payments on domestic borrowing to finance 7 the budget following shortfalls in revenue targets, 100 Percent of GDP 6 and the expenses associated with the 2013 elections. 80 KSh Billion 5 The estimated drop in recurrent spending in 2013/14 60 4 was driven purely by reclassification of spending of 3 40 counties for devolved functions. 2 20 1 Nominal wage and salary spending rose between 0 0 4* 20 /01 20 /02 20 /03 20 /04 20 /05 20 /06 20 /07 20 /08 20 /09 20 /10 20 /11 20 /12 20 /13 2009/10 and 2013/14, but the increase was in line /1 00 01 02 03 04 05 06 07 08 09 10 11 12 13 20 with economic activities. The nominal wage bill of Real wages and salaries Wages and salaries (percent of GDP) the national government increased by more than Source: Quarterly Budget and Economic Review, March 2014 (National Treasury). 58 percent between 2009/10 and 2013/14,rising Note: Figures for 2013/14 are estimate from US$ 173 billion (7.0 percent of GDP) to US$ 274 billion (7.6 percent of GDP), an average growth The total public sector wage bill remains high. rate of 14.5 percent a year (Figure 1.16). In real According to preliminary data released by the terms, wages rose by an annual average rate of 5.1 National Treasury, Kenya’s total public sector wage bill percent—somewhat faster than GDP, which grew (excluding semi-autonomous government agencies) at 4.5 percent a year. The larger increases in wages increased in 2013/14, rising from KSh 323 billion (9.0 observed in the last two years were driven mainly by percent of GDP) in 2012/13 to KSh 366 billion (9.1 the establishment of the new constitutional offices percent of GDP), and the county government wage created to smooth implementation of the 2010 bill increased by about KSh 50 billion (Table 1.4). constitution and by absorption of the former local As a result of devolution, the national government authorities’ staffs into county governments. Under wage bill declined by KSh 7 billion as some national the old system, local civil servants were not paid staff (including doctors) were transferred from the by exchequer funds. Under the new system, they national to county payrolls. The staff rationalization are paid by county governments, which depend on program that was to have followed devolution has transfers from the national government. Wages at yet to be implemented at the national level. As a the national level are estimated to have fallen to 6.8 result, some services are being delivered by both Table 1.3: Spending on all recurrent items except pensions fell (percent of GDP) Item 2009/10 2010/11 2011/12 2012/13 2013/14 Total recurrent spending 20.8 21.3 20.0 22.1 19.8 Wages and salaries 7.0 7.1 6.7 7.6 7.2 Interest payments 2.6 2.7 2.5 3.4 3.0 Domestic interest 2.3 2.5 2.2 3.1 2.7 Foreign interest 0.3 0.3 0.3 0.3 0.3 Pensions 1.2 0.9 0.8 0.7 0.8 Operation and maintenance/other 10.0 10.5 10.0 10.4 8.8 Source: Quarterly Budget and Economic Review, March 2014 (National Treasury) June 2014 | Edition No. 10 11 The State of Kenya’s Economy Table 1.4: Public sector wage bill, 2012/13–2014/15 (KSh million, except where otherwise indicated) 2012/13 2013/14 2014/15 Item Preliminary Budget Revised budget Projected National government 291,831 263,020 284,804 297,618 Constitutional and state 9,727 9,727 9,727 9,922 governments County governments 21,596 71,247 71,247 80,672 (devolved and local authorities)a Subtotal 323,154 343,994 365,778 388,212 Percent of GDP 9.0 8.6 9.1 8.6 Salaries through transfers to semi-autonomous government 141,797 146,051 146,051 150,433 agenciesb Total 464,951 490,045 511,829 538,645 Nominal GDP 3,600,761 4,016,372 4,016,372 4,498,337 Percent of GDP 12.9 12.2 12.7 12.0 Source: Rotich 2014, based on data from National Treasury a. County governments generate their own revenue and do not rely fully on the national exchequer for funds b. Agencies that receive no exchequer funds (including the Central Bank of Kenya and the Kenya Revenue Authority, which contribute a large portion of the wage bill in this category) have been lumped with agencies that rely 100 percent on the exchequer. Their inclusion in this category thus overestimates the wage bill levels of government. Including wages of semi- by the fact that tax bands were set almost a decade autonomous government agencies, the wage-bill ago. As a result, income taxpayers have crept into increased to more than 12.9 percent of GDP. higher brackets than they would have had the bands been updated. Pension spending increased in 2013/14, as pensioners affected by the 2009 increase in the Income tax collections increased from 9.6 percent retirement age (from 55 to 60) retired. Pension of GDP in 2011/12 to 10.4 in 2012/13 and an payments grew 18 percent in nominal terms, from estimated 11.4 percent in 2013/14 (Figure 1.17). KSh 27 billion in 2012/13 to an estimated KSh 31.8 As a result, total revenue in the first half of 2013/14 billion in 2013/14. rose to 10.7 of GDP, up from 9.5 percent in the first Figure 1.17: Tax revenue in all categories increased in 2013/14 Government revenue rose R evenue and tax collections remain strong. Tax 12 revenue increased from 21.1 percent of GDP in 10 2011/12 to 21.6 percent in 2012/13 and an estimated 25.9 percent in 2013/14. The increase was driven by 8 increases in other revenue (which rose 1.8 percent Percent of GDP 6 of GDP), income tax (1.0 percent), import duty (0.8 percent), and the value added tax (0.6 percent) and 4 by the new railway tax. The income tax remained 2 the major source of tax revenue, thanks to better monitoring and collection of pay as you earn (PAYE) 0 1999/00 -2010/11 2011/12 2012/13 2013/14* at the national level and enhanced tax collection Import Duty Excise Duty VAT Income Tax from corporations and enhanced collection from Source: Quarterly Budget and Economic Review, March 2014 (National Treasury). rental income. PAYE growth has been driven partly Note: Figures for 2013/14 are estimates 12 June 2014 | Edition No. 10 The State of Kenya’s Economy half of 2012/13. Achieving fiscal year targets will Revenues from the new railway levy exceeded require resilient economic growth and continuous targets. The 1 percent levy on all imports, efforts to close loopholes in tax administration. implemented in August 2013, funds railway transport infrastructure. Revenues from the levy far exceeded VAT collections exceeded targets. The new law the target, generating an estimated KSh 20.5 billion reduced the number of items exempt from VAT from in 2013/14, equivalent to 2 percent of GDP. more than 400 to just 40, increasing VAT revenue. VAT collections of KSh 110.7 billion in the first half Budget execution continues to be weak W of 2013/14 exceeded the target of KSh 106.8 billion eak execution of the budget, especially (Figure 1.18). As of February 2014, year-on-year development spending, remains a challenge. growth was 26 percent. For the fiscal year as a Allocations to development spending increased whole, VAT revenues were estimated to have risen in recent years, but low execution rates relative to from 5.1 percent of GDP in 2012/13 to an estimated recurrent expenditure remain a significant challenge 5.4 percent in 2013/14. that jeopardizes attainment of Vision 2030 goals. Execution rates for recurrent spending averaged Figure1.18: VAT revenue in 2013/14 exceeded the target about 90 percent over the past five years. In Nominal VAT revenue collection contrast, just 61 percent of development spending 200 was appropriated. 180 160 140 Budget utilization of both recurrent spending and development spending were low, but the rate for KSh billion 120 100 development spending was much lower. Transitional 80 challenges, including the merger of 44 ministries into 60 40 18, and slow procurement processes reduced the 20 absorption rate. The overall budget execution rate 0 stood at 72.6 percent at the end of the third quarter Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun of 2013/14, up from 71.6 percent in the first half 2010/11 2011/12 2012/13 2013/14 (Figure 1.19). The lower rate of execution was mainly Source: Central Bank of Kenya the result of weak appropriation of development spending (46.8 percent). The execution rate for the Figure 1.19: Budget execution rates were much lower for development spending than for recurrent spending at the end of quarter three in March 2014 Budget execution rate as at the end of the third quarter Overall budget execution rates, end quarter three, 2009 -2014 100 100 90 80 80 78.9 70 60 Percent Percent 60 47.3 46.8 50 40 87.5 71.6 72.6 40 20 30 20 0 10 March 2009 - March 2013 March 2014 March 2012 0 March 2009 - March 2013 March 2014 Recurrent expenditure Development expenditure March 2012 Source: Quarterly Budget and Economic Review, March 2014 (National Treasury) June 2014 | Edition No. 10 13 The State of Kenya’s Economy recurrent budget increased from 90.2 percent at the 4.2 percent of GDP in 2010/11 to an estimated 6.6 end of March 2012 to 92.0 percent at the end of percent of GDP in fiscal 2013/14. To reduce pressure March 2013. on domestic lending rates, the government issued a US$ 2 billion Eurobond in June 2014, with proceeds Budget execution rates differ widely across slated for infrastructural projects in energy and ministries and sectors. The worst execution in the roads. As a result, deficit financing from domestic second quarter of 2013/14 was in the environmental sources fell from 4.7 percent of GDP in 2012/13 to protection, water, and natural resources sectors an estimated 0.6 percent in 2013/14, with foreign (48.1 percent) and the energy, infrastructure, and ICT financing increasing from 2.4 percent to 5.9 percent sectors (51.0 percent) (Figure 1.20). Low execution (Figure 1.21). rates have been associated with weaknesses in timely reporting, monitoring, and tracking systems. Public debt rose, but Kenya’s debt distress rating Another challenge includes the practice of allocating remains low. Gross public debt increased from KSh funds to projects that are still at the preparatory 1,793 billion (49.8 percent of GDP) at the end of stage in the budget estimates. December 2012 to KSh 2,113 billion (52.6 percent) at The Single Treasury account being put in place will Figure 1.21: Foreign financing of the budget deficit increased in 2013/14 improve budget execution. On July 1, 2014, the Sources of deficit financing system of individual ministerial bank accounts at 8 Partly funded by Euro-bond of US$ 1.5 - 2 billion the Central Bank of Kenya—the source of delays in 7 Partly funded by syndicated project implementation—will be replaced by a Single 6 0.9 loan of US$ 600 billion Treasury Account, which will pool all ministerial 2.4 Percent of GDP 5 funds. The new system will reduce delays in 4 executing development projects caused by revenue 6.2 1.0 3 3.5 shortfalls of individual ministries and cut down on 4.7 5.9 unnecessary government borrowing. 2 3.2 1 2.0 0.6 Higher deficits have increased the level of 0 2009/10 2010/11 2011/12 2012/13 2013/14 public debt Domestic financing Foreign financing K enya has been leveraging its ability to borrow in order to run increasingly large fiscal deficits in the past few years. Deficit financing rose from Source: The National Treasury Source: Quarterly Economic and Budgetary Review, March 2014 (National Treasury) Figure 1.20: Budget execution rates for priority sectors were low in the three quarters of 2013/14 Education Governance, Justice, Law and Order 160 Energy, Ingrastructure and ICT National Security 91.4 Public Administration and International General, Economic and Commercial Affairs 89.4 National Security Education 81.6 Agriculture, Rural and Urban Development Social Protection, Culture and Recreation 67.6 Governance, Justice, Law and Order Agriculture, Rural and Urban Development 60.7 Environmental Protection, Water and Natural Resources Public Administration and International 59.9 Health Health 56.2 Social Protection, Culture and Recreation Energy, Ingrastructure and ICT 51.0 General, Economic and Commercial Affairs Environmental Protection, Water 48.1 and Natural Resources 0 100 200 300 0 20 4 0 60 80 100 120 1 4 0 160 180 KSh Billion Target March 2014 Actual March 2014 Budget implementati on rate (end of March 2014) Source: Quarterly Budget and Economic Review, March 2014 (National Treasury) 14 June 2014 | Edition No. 10 The State of Kenya’s Economy the end of December 2013. By the end of the fiscal a short four months after they were established (see year, gross debt was estimated to have reached 55.8 Box 1). By January 2014 the national government percent of GDP. Netting out government deposits, had transferred payroll responsibility for more public debt increased from 45.3 percent of GDP than 70,000 staff previously engaged by national at the end of December 2012 to 46.5 percent at ministries. As of June 2014, most county governments the end of December 2013 and an estimated 51.8 had county public service boards, county executives, percent by the end of the fiscal year (Figure 1.22). and senior sector officials in place. Most of Kenya’s public external debt remains on concessional terms, although its commercial The first county budgets were prepared without the component increased to about 15 percent by June benefit of good information. Counties did not know 2014 with the Eurobond taken into account. the cost of staff they would inherit, nor what would be involved in realizing their full revenue potential. Private nonbank financial institutions increased According to the Controller of Budget’s biannual their holdings of government paper. Their share implementation report, counties overstated of domestic debt increased from 11.4 percent of revenues (and correspondingly, expenditure) by a GDP at the end of December 2012 to 13.2 percent total of about KSh 36 billion. Inadequate capacity, of GDP at the end of December 2013 (Figure 1.23). delays in setting regulations that were meant to act Commercial banks’ share remained constant during as a guide to the whole budget formulation process, this period. A large proportion of domestic debt held lack of experience using standard reporting systems, by nonbank financial institutions is an indication of and other challenges caused counties to miss both broader investment options for the private sector, revenue and expenditure targets. which reduce the volatility of interest rates.4 Shortfalls in revenue collection also reflect a County governments are now operational variety of administrative hiccups and cyclical G iven the radical nature of Kenya’s “big bang” fluctuations. County revenue collections were less devolution, implementation has proceeded than 50 percent of annual targets in all but two surprisingly quickly. County governments were counties(—Samburu and West Pokot) (Figure 1.24). required to enact their first full budgets by June 2013, The consolidated county budget for 2013/14 was set Figure 1.23: Private nonbank institutions increased their holdings Figure1.22: Public debt increased, driven by external borrowing of Kenyan government securities 70 Domestic debt by creditors 30 60 24.0 50 53.7 25 51.8 48.3 47.3 47.8 Percent of GDP Percent of GDP 44.9 45.5 40 42.2 20 30 15 20 10 10 0 5 4 7/ 00 9 0 11 2 9 4 Q3 3/1 /0 /1 /1 /0 /1 00 20 / March March March March March March 08 09 10 11 08 13 08 1 -2 99/ 20 20 20 20 20 20 20 2009 2010 2011 2012 2013 2014 19 External debt Domestic debt Total public debt (net) Commercial banks Non-banks Total domestic debt Source: Quarterly Economic and Budgetary Review, March 2014 (National Treasury). Source: Quarterly Budget and Economic Review, March 2014 (National Treasury) Note: Figures for 2013/14 are estimates 4 By developing a domestic money market, Kenya is also better placed to attract international financial investments because of improved policies and stable macroeconomic environment. June 2014 | Edition No. 10 15 The State of Kenya’s Economy Box 1:1 County governments are now operational Kenya’s county governments ‘took off’ in March 2013, following peaceful elections which ushered in one of the world’s most revolutionary devolution endeavors. Through the 2010 constitution, major political and administrative powers were transferred to 47 counties, which replaced previously existing local government administrations, provinces and district units. Each county comprises an elected Governor and a Senator, a County Assembly, nominated County Executive Committee (CEC) members and two autonomous boards managing county public and county assembly services. The counties are now delivering services in agriculture, health (including promotion of primary health care), transport, and trade development and regulation among other functions, with health being the biggest, cost wise, based on estimates by the National Treasury. The functions were handed over to counties within six months of their establishment, contrary to earlier plans for a phased transfer. The counties have been assigned two tax bases—property rates and entertainment tax—and they are also able to raise own-source revenues from trade and liquor licenses, in addition to fees and charges for services rendered. The primary financing for counties comes from their equitable share of revenue raised nationally, which constitutionally, should not fall below 15 percent of the last audited revenues approved by Parliament. This share is decided annually, and then allocated among counties based on a criteria determined by the Senate. In the first year of devolution, counties’ equitable share equaled approximately 7 percent of the country’s GDP, with the aggregate transfer expected to grow nearly 20 percent in the second year. In general, counties are responsible for preparing their own budgets which, like those of the national government, should contain estimates of revenue and expenditures as well as proposals for financing any deficit and proposals for borrowing. Figure 1.24: Only two counties met their revenue targets during the first half of 2013/14 Ratio of local revenue collection for the first half versus the annual target West Pokot Samburu Homa Bay Tharaka-Nithi Nandi Marsabit Kericho Baringo Nyeri Taita/Taveta Siaya Elgeyo/Marakwet Bomet Nyamira Nairobi City Kajiado Nyandarua Isiolo Narok Tana River Makueni Wajir Vihiga 50 percent Busia Meru Machakos Kitui Embu Migori Kirinyaga Turkana Murang’a Nakuru Trans Nzoia Garissa Kwale Uasin Gishu Kilifi Laikipia Kisii Mandera Kisumu Kiambu Mombasa Bungoma Kakamega Lamu 0 10 20 30 40 50 60 Percent Source: Office of the Controller of Budget 16 June 2014 | Edition No. 10 The State of Kenya’s Economy Figure 1.25: Ten counties generated three-quarters Not unexpectedly, budget execution rates were of all local revenue in the first half of 2013/14 well below target. The delay in releasing funds from Local revenue collection in the first half 4 the national coffers affected budget execution. By 4.5 December 2013, county government had received 3 three out of six exchequer releases. As a result, 3.5 counties spent only KSh 41 billion in the first half of KSh billion 2 the fiscal year, just 14.9 percent of total expenditure 2.5 for the year as a whole. The highest rates were in 1 Nairobi County (31.6 percent) and Bomet County 1.5 (27.1 percent). The lowest rates were in Mandera 0 Country (5.5 percent) and Lamu County (7.5 percent) (Figure 1.26). ’a u lifi u ru bu sa s k bi ko ro sh m g iro ba ku Ki am an su Na ha Gi Na Na om ur Ki Ki ac sin M M M Ua Counties’ expenditure of development funds during Source: Office of the Controller of Budget the first half of the year was in line with that of the at KSh 275.8 billion, financed by KSh 194.3 billion of national government. Infrastructural development transfers from the national government (comprising was among the key priorities for the new county the “equitable share” and a small conditional grant governments: development allocations for 2013/14 for level 5 hospitals) and counties’ own revenues accounted for 40.7 percent (KSh 112.2 billion) of the of KSh 67.8 billion (Table 1.5). During the first half total budget. In the first half of 2013/14, however, just of the fiscal year, counties collected only KSh 9 4.3 percent of the budgeted amount (KSh 4.8 billion) billion, just 13.3 percent of projected revenue for was spent on development. This burn rate was well the year as a whole. The shortfall reflected deferral below the target of 50 percent but not inconsistent of property rates and business license receipts into with the national government development budget the third quarter, delays in passing county finance burn rate of 15.8 percent for the first half of the laws, and the weakness of the (manual) financial year, according to the Controller of Budget. Weak management systems in place. Some shortfalls in implementation of the budget reflected delays in reported revenues may reflect revenues being spent disbursements (particularly in the first quarter, when before being transferred to county revenue funds, the County Allocation of Revenue Act of 2013 was especially during the period before national transfers not approved on time); delays approving the county were available, when counties used the funds collected integrated development plans on which county to pay essential expenditure like wages. development spending must be based; and the lead Table 1.5: County revenues and expenditures were well below target in the first half of 2013/14 (KSh billion) Annual budget Actual as of end Item 2013/14 December-2013 Revenue Transfers from national government (equitable share) 210.0 66.5 Local revenue 67.8 9.0 Total revenue 277.8 75.5 Expenditure Recurrent 163.7 36.3 Development 112.2 4.8 Total expenditure 275.8 41.0 Source: Office of the Controller of Budget June 2014 | Edition No. 10 17 The State of Kenya’s Economy Figure 1.26: Budget execution rates were well below counties’ own targets Nairobi 31.6 Bomet 27.1 Elgeyo/Marakwet 26.8 Kericho Narok Machakos Homa Bay Baringo Trans Nzoia Tharaka -Nithi Laikipia Busia Mombasa Marsabit Nakuru Samburu Kitui Kilifi Turkana Migori Nyeri Nyamira Kajiado Wajir Kiambu Kisii Kirinyaga Murang’a Vihiga Nyandarua Nandi Taita/Taveta Meru Embu Garissa Siaya Tana River Uasin Gishu Makueni West Pokot Kisumu Kwale Isiolo Kakamega Bungoma Lamu 7.5 Mandera 5.5 0 5 10 15 20 25 30 Overall implementation rates as at the end of December 2013, percent Source: Office of the Controller of Budget Note: Orange bars represent counties that were provincial headquarters were located with better systems time in setting up procurement plans and processes Figure 1.27: Almost half of all county expenditure went to personnel emoluments in counties for the first time. Counties total expenditure as at December 2013 Development Personnel emoluments (wages, salaries, and KSh 4.8 billion allowances) accounted for the largest share of county expenditures. In the first half of 2013/14, expenditure on personnel emoluments represented Personnel emoluments KSh 19.6 billion 54.0 percent of counties’ total recurrent expenditure and 47.8 percent of their total expenditure (Figure Operations and maintainance 1.27). The large share reflects the fact that counties KSh 14.4 billion Debt repayment both inherited staff from the old local authority and pending billls KSh 2.2 billion system and recruited new staff. Recurrent KSh 36.3 billion 1.3 Monetary policy continues to support economic Source: Office of the Controller of Budget activity, and the financial sector remains robust Note: Figures are as of December 31, 2013 T he Central Bank of Kenya maintained its accommodative monetary policy stance to support economic performance. The CBR was economic activities. This objective was achieved by increasing the volume as opposed to the price of credit. Long-term rates remained sticky, at 17.08 retained at 8.5 percent for the 12 months ending May percent, a reduction of only 298 basis points since 2014 to allow the market time to continue lowering the height of the 2011 crisis. In contrast, the CBR interest rates to encourage more lending to boost declined by 950 basis points. Private credit growth 18 June 2014 | Edition No. 10 The State of Kenya’s Economy Figure 1.28: Growth of monetary aggregates slowed but remained below target levels Monetary aggregates, Target versus actual levels of reserve money, Target versus actual levels of M3X, 40 January 2007 - February 2014 January 2012 - May 2014 January 2012 - May 2014 35 30 30 30 25 Annual growth (percent) Annual growth (percent) 25 Annual growth (percent) 20 20 20 15 15 10 10 10 5 5 0 0 0 5 Jan-07 Jun-07 Nov-07 Apr-08 Jul-09 Dec-09 May-10 Oct-10 Mar-11 Aug-11 Jan-12 Jun-12 Nov-12 Apr-13 Sep-08 Feb-09 Sep-13 Feb-14 Jan-12 Mar-12 May-12 Jul-12 Sep-12 Nov-12 Jan-13 Mar-13 May-13 Jul-13 Sep-13 Nov-13 Jan-14 Mar-14 May-14 Mar-11 May-11 Jun-11 Nov-11 Jan-12 Mar-12 May-12 Jun-12 Nov-12 Jan-13 Mar-13 May-13 Sep-11 Sep-12 Jun-13 Sep-13 Nov-13 Jan-14 Mar-14 May-14 -10 Reserve money M0 M3 Reserve money target Actual reserve money Money supply (M3X) Money supply (M3X) target M1 M2 Source: Central Bank of Kenya more than doubled between April 2013 and April 1.29 shows, it has managed to stop the interbank 2014 (see the previous Kenya Economic Update 9). and repo rates from overshooting during liquidity shortages, which have become common in recent The Central Bank has kept monetary aggregates years, as a result of poor cash management and the within the targets it set to control inflation. buildup of government deposits at the Central Bank. Monetary aggregates remained below the targets set, partly as a result of the buildup of government Volatility in short-term market interest rates points deposits (Figure 1.28). Reserve money grew 18.1 to lingering concerns about liquidity in the banking percent (against the target of 24.8) percent) in the system linked to implementation of the budget. 12 months ending April 2014, up from 9.6 percent Interbank rates fluctuated by as much as 25 percent the previous year. M1 grew 14.2 percent, down from in the first quarter of 2014 (see Figure 1.29). Such 17.8 percent; M3X grew 14.1 percent, down from volatility makes commercial banks risk averse to 17.3 percent. lending; if they do lend, they cover the risk by raising long-term rates. However, the 91-day Treasury bill The CBR has remained an effective tool for rate was relatively stable, averaging 9.2 percent in coordinating interest rates at the short end of the the second half of 2013 and falling sharply in March market. The CBR appears to be acting as the upper 2014, when government payments started flowing. bound of the repo and interbank rates. As Figure Figure 1.29: The Central Bank Rate coordinated short-term interest rates, but volatility in the market was significant Short-term interest rates, February 2010 - February 2014 Daily Interbank interest rate volatility 35 30 30 25 Volatility (percent) 25 20 20 15 15 10 10 5 5 0 0 M 11 M 12 M 13 M 14 No 10 No 11 No 12 No 13 Fe 10 Fe 11 Fe 12 Fe 13 Au 10 Au 11 Au 12 Au 13 4 -1 b- b- b- b- g- g- g- g- v- v- v- v- - - - - ay ay ay ay ay Jan-12 Mar-12 May-12 Jul-12 Sep-12 Nov-12 Jan-13 Mar-13 May-13 Jul-13 Nov-13 Jan-14 Mar-14 May-14 Sep-13 Jun-14 M Interbank 91 - Day Tbill Central bank rate Source: Central Bank of Kenya June 2014 | Edition No. 10 19 The State of Kenya’s Economy Figure 1.30: Lending rates remained sticky downward, but the volume of credit to the private sector grew Long-term interest rates, March 2010 - March 2014 Growth in credit to the private sector, January 2011 - April 2014 30 40 25 35 Long-term interest rate (percent) Annual growth (percent) 30 20 25 15 20 15 10 10 5 5 0 0 Mar-14 Mar-07 Jul-07 Nov-07 Mar-08 Jul-08 Nov-08 Mar-09 Jul-09 Nov-09 Mar-10 Jul-10 Nov-10 Mar-11 Jul-11 Nov-11 Mar-12 Jul-12 Nov-12 Mar-13 Jul-13 Nov-13 Jan-11 Mar-11 May-11 Jul-11 Sep-11 Nov-11 Jan-12 Mar-12 May-12 Jul-12 Sep-12 Nov-12 Jan-13 Mar-13 May-13 Jul-13 Sep-13 Nov-13 Jan-14 Mar-14 Deposit Savings Lending Overdraft Source: Central Bank of Kenya Lending rates continued to be sticky downward, result, interest spreads (lending minus deposit rates) despite the continued accommodative policy exceeded 10 percent (equivalent to a real spread of stance of the Central Bank (Figure 1.30). The about 3 percent after taking account of inflation of delayed transmission mechanism from the lower about 7 percent). CBR did not materialize, as lending rates did not fall as anticipated. Between December 2012 and April Credit to the private sector increased significantly, 2014, lending rates fell just 144 basis points—about despite the lack of change in lending rates. As half the 250 basis point decline in the CBR rate. The political uncertainty declined after the March 2013 reasons for low transmission mechanism have not general elections and the economy continued to changed since the last Kenya Economic Update. The stabilize following the macroeconomic instability liquidity challenges in the banking system brought of 2011, the demand for and supply of loans about by slow payment of government contracts kept increased. Private sector credit growth almost money markets rates high, choking the transmission doubled between 2013 and 2014, increasing 23.9 of a lower CBR to lower lending rates. Deposit rates percent in the 12 months ending April 2014, up remained stable, declining by just 33 basis points from 10.5 percent in the same period the previous over the 16 months ending in April 2014. As a year. The increase was much larger than the Central Figure 1.31: Credit to all sectors of the economy except mining and quarrying rose in 2014 Unweighted percentage change in private credit, by sector, Weighted percentage change in private credit, by sector, April 2013 - April 2014 April 2013 - April 2014 Business services Private households Transport and communication Real estate Private households Trade Real estate Business services Finance and insurance Manufacturing Trade Transport and communication Manufacturing Consumer durables Consumer durables Agriculture Agriculture Finance and insurance Mining and quarrying Building and construction Building and construction Mining and quarrying Other activities Other activities -30 -20 -10 0 10 20 30 40 50 60 -3 -2 -1 0 1 2 3 4 5 6 Change in volume of credit to private sector (percent) Change in volume of credit to private sector (percent) 2014 2013 2014 2013 Source: Central Bank of Kenya 20 June 2014 | Edition No. 10 The State of Kenya’s Economy Figure 1.32: Performance onthe Nairobi Securities Exchange (NSE) Private credit uptake increased in all sectors of was weakin the second half of 2013 7,000 18,000 the economy, signaling broad optimism in 2014. 16,000 This optimism can be seen in the high level of 6,000 14,000 credit growth in business services (51.0 percent), Dow Jones Industrial average 5,000 transport and communication (45.4 percent), private NSE index (1966 = 100) 12,000 4,000 10,000 households (35.2 percent), real estate (33.2 percent), 3,000 8,000 consumer durables (21.8 percent), and trade (24.5 2,000 6,000 percent) (Figure 1.31). The construction boom is not 4,000 reflected in credit numbers, because most buildings 1,000 2,000 in Nairobi are financed through equity and pension 0 0 funds. Credit to the production sector was lower Feb-07 Aug-07 Feb-08 Aug-08 Feb-09 Aug-09 Feb-10 Aug-10 Feb-11 Aug-11 Feb-12 Aug-12 Feb-13 Aug-13 Feb-14 than might have been expected. NSE 20-share index Dow Jones Industrial average Source: Central Bank of Kenya The quality of assets deteriorated marginally at most banks, as a result of delays in government Bank target of 19.7 percent for the period. In the payments to contractors. The share of gross absence of any inflationary threat, the Central Bank nonperforming loans in total loans increased, from was comfortable allowing private credit growth to 4.30 percent in February 2013 to 4.66 percent in April increase, in order to stimulate economic growth. 2014 (Table 1.6). The deterioration in the quality of Commercial bank lending reached KSh 317 billion loans was driven mainly by large banks, the source of in the 12 months ending April 2014, up from KSh most finance for large government contractors. The 126 billion the previous year. The main beneficiary ratio of nonperforming loans to total loans of large sectors of this increase were private households banks increased 0.64 percent, from 4.35 percent to (21.3 percent), real estate (17.3 percent), trade 4.99 percent in the 12 months ending April 2014. (17.0 percent), and business services (16.4 This change was much larger than the change for percent). Other sectors in which commercial medium-size banks (among which the figure rose bank lending rose included manufacturing (12.3 by 11 basis points) or small banks (among which it percent), transport and telecommunication (10.7 declined by 10 basis points). The average share of percent), agriculture (2.7 percent), and building net nonperforming loans in total loans rose 104 and construction (1.0 percent).5 basis points, from 1.47 percent to 2.51 percent. This Figure 1.33: The external balance improved, but risks remain 15 40 30 10 20 10 5 Percent of GDP Percent of GDP 0 0 -10 -20 -5 -30 -40 -10 -50 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 (Apr) 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 (Apr) 2014 2014 -15 Current account Short-term flows (including NEO) Exports (fob) Nonfactor services Imports (non-oil) Oil Imports Other flows Overall balance Balance of Trade Balance of Trade (non-oil) Source: Nairobi Security Exchange June 2014 | Edition No. 10 21 The State of Kenya’s Economy Table 1.6: Asset quality by bank size, February 2013 and February 2004 (percent) Change Quality measure/bank size February 2013 February 2014 (a positive number indicates deterioration) Gross non-performing loans/total loans Total 4.03 4.83 0.80 Large banks 3.69 5.32 1.63 Medium-size banks 3.14 3.77 0.63 Small banks 6.19 6.44 0.25 Net non-performing loans/total loans Total 0.97 2.64 1.67 Large banks 1.09 2.96 1.87 Medium-size banks 1.08 1.65 0.57 Small banks 3.80 4.92 1.12 Source: Central Bank of Kenya change was also driven by large banks, among which The overall balance of payments remained in asset quality fell by 93 basis points. surplus in 2013. The balance of payment declined to US$ 0.7 billion in 2013, down from US$ 1.3 billion in The performance of the Nairobi Securities Exchange 2012, mainly as a result of the reduction in long-term (NSE) was weak, with its index declining 2.5 percent capital flows (Figure 1.33). Official medium- to long- in the 12 months ending May 2014 (Figure 1.32). term flows declined by US$ 555 million, while private During the same period, the Dow Jones Industrial long-term flows declined by US$ 171 million in 2013. Index rose 10.6 percent. Between December 2013 By April 2014, the overall balance of payment stood and May 2014, the NSE 20-share index declined 0.9 at a surplus of US$ 581 million (US$ 200 million more percent. In addition to depressed economic activity, than in December 2013). the poor performance of the equities market may reflect investors switching their portfolios to reap the Improvements in the external sectors are high returns in the fixed income securities markets. temporary; threats to Kenya’s external vulnerability remain. Improvement in Kenya’s external balance 1.4 External pressures are subsiding for now but is likely to be temporary, because the inherent may re-intensify K Figure 1.34: Growth in merchandise exports and imports was modest in enya’s external position is improving. The 12 80 month current account deficit declined from 70 its peak of 10.9 percent of GDP in December 2013 60 and 9.8 percent in April 2014. In dollar terms, it 50 declined from US$ 4.7 billion in 2013 to US$ 4.3 Annual growth (percent) 40 billion in April 2014. Imports as a percent of GDP 30 declined marginally, from 38.9 percent in the 12 20 months ending in April 2013 to 38.4 percent in the 10 12 months ending in April 2014. Exports of goods 0 declined by 0.5 percent of GDP in the same period -10 from 13.8 percent to 13.4 percent; exports of 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 (Apr) 2014 -20 nonfactor services rose by 1.1 percent of GDP, and Exports of goods and non-factor services Imports (CIF) Services current transfers increased by 0.4 percent of GDP. Source: Central Bank of Kenya 22 June 2014 | Edition No. 10 The State of Kenya’s Economy Figure 1.35: Merchandise exports continue to underperform imports and GDP Exports of goods and nonfactor services, 2000 - 2014 Exports coverage of imports, 2000 - 2014 30 100 25 80 20 Percent of GDP 60 Percent 15 40 10 20 5 0 0 00 01 02 03 04 05 06 07 08 09 10 11 12 13 01 02 03 04 05 06 07 08 09 10 11 12 (A 014 00 (A 014 13 ) 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 ) pr 20 pr 2 2 Exports of goods Exports of nonfactor services Ratio of exports plus nonfactor services to imports Exports of goods and nonfactor services Ratio of exports to imports Source: Central Bank of Kenya structural weaknesses of the external account have have continued to deteriorate in the 12 months not been dealt with. A healthier improvement would ending April 2014. The growth of merchandise have been driven by an increase in exports or a exports declined 3.1 percent, with tea (falling 8.5 reduction in nonessential imports. Exports continue percent and), chemicals (-11.3 percent). Exports in to underperform, as a result of the weak business other sectors, including horticulture (5.6 percent) environment, and the significant drop in imports in and raw material exports (11.4 percent) rose. 2013 seems temporary. The importance of export growth becomes particularly salient in the context of The potential of Kenya’s exports to finance Kenya’s large current account deficit and significant its imports continues to decline. The share of external vulnerability. Weather-induced shocks, merchandise exports in GDP—which measures the a pick-up in government capital spending, and an ability of the economy to finance foreign goods— increase in private sector credit pose risks for further continued to drop, falling from a peak of 18.5 deterioration of the current account. percent in 2005 to 13.3 percent in 2013 (Figure 1.35). However, exports of nonfactor services as a Exports continue to perform poorly, as a result share of GDP increased, from a low of 2.6 percent of the weak business environment and subdued of GDP in 2001 to a high of 10.5 percent in 2013. foreign demand. Tepid external demand for Kenya’s Merchandise exports as a share of imports declined exports reflected subdued global demand and lower from a peak of 64.4 percent in 2002 to 35.5 percent commodity prices (Figure 1.34). On the supply side, in 2013. Adding nonfactor services exports, which the poor business environment constrains firms have been growing very rapidly, increases this figure from competing in international markets. Exports of to 62.5 percent, but it is still much lower than the goods declined 5.8 percent in 2013. Coffee exports peak of 82.3 percent achieved in 2003. fell 29.0 percent (an even sharper decline than the 21.0 percent drop in 2012), and exports of chemicals Imports growth slowed significantly in 2013. fell 14.0 percent. Tea, Kenya’s main export grew a Imports rose just 2.0 percent in 2013, down from mere 1.3 percent, down from 4.0 percent in 2012. 12.9 percent in 2012. The tepid growth reflected Raw material export grew 9.7 percent in 2013 and declines in imports of oil, which fell 6 percent, and; horticulture 6.7 percent. Exports of goods and machinery and transport equipment, which fell 3.1 nonfactor services grew 3.7 percent, down from percent, after increasing 28.8 percent growth in 2012. 17.3 percent in 2012. Services exports grew 2.5 The decline in essential capital imports reflected the percent, down from 10.7 percent in 2012. Exports poor performance of the economy and investors’ June 2014 | Edition No. 10 23 The State of Kenya’s Economy Figure 1.36: Remittance inflows remain strong Diaspora Remittances 1,400 3.5 140 1,200 3.0 120 1,000 2.5 Monthly (US$ Million) 100 Percent of GDP 800 2.0 US$ Million 80 60 600 1.5 40 400 1.0 20 200 0.5 0 0 0 De 04 Ju 4 Fe 5 Se 6 Ap 6 No 7 Ja 7 08 Au 9 M 09 Oc 0 M 0 De 11 Ju 1 Se 2 Ap 3 4 Ju 1 4 r- 1 Fe 5 Se 06 Ap 06 No 07 Ja 07 Ja 8 Au 9 M 09 Oc 10 M 0 De 11 Fe 2 Se 13 Ap 13 0 l- 0 0 0 r- 0 0 0 -1 t- 1 1 l- 1 1 - l- 0 0 0 t- 1 1 r-1 - c- l-1 b- p- v- n- n- g- c- p- ay ar ay b- p- r- v- n- n- g- - - c- b- p- ar ay Ja Ju M Monthly 12-months average 12 month Cumulative Percent of GDP Source: Central Bank of Kenya jitteriness about undertaking new projects without foreign exchange in Kenya. Remittances have played a clear path ahead. Imports of chemicals rose 9.8 a crucial role in stabilizing the exchange rate during percent, up from 6.6 percent in 2012, and imports periods of volatility and diversifying foreign exchange of manufactured imports increased 14.0 percent, up inflows. In 2013 remittances reached US$ 1.29 from 2.3 percent in 2012. Other imports increased billion (2.9 percent of GDP), a 10.2 percent nominal 10.5 percent compared to 22.6 percent in 2012. increase over the 2012 level of US$ 1.17 billion. In the In the 12 month ending April 2014, gross imports 12 months ending April 2014, remittances reached declined 1.5 percent driven mainly by oil imports US$ 1.33 billion, a 12.0 percent increase over the which declined by 1.3 percent), chemicals (-7.8 same period the previous year (Figure 1.36). Average percent), machinery and equipment (-7.1 percent), monthly remittances increased from US$ 97.6 million and oil imports (–1.3 percent). in December 2012 to US$ 107.5 million in December 2013 and US$110.9 million in April 2014. The boom Remittances now a major source of external finance in remittances reflects both improved data collection continued to increase faster than the economy. They by the Central Bank of Kenya, the ease with which now exceed foreign direct investment as a source of the diaspora can now send remittances to Kenya via commercial banks for investment purposes, and Figure 1.37: Long-term capital inflows declined in 2013, improved economic activity in North America (the and short-term flows increased source of 50 percent of remittances) and Europe 6 (the source of 27 percent). 5 4 The financing of the current account remains vulnerable to external factors, as long-term capital Billions of dollars 3 2 inflows remain low. The financial account increased 1 from US$ 5.3 billion (13.1 percent of GDP) in 2012 0 to US$ 3.9 billion (12.2 percent of GDP) in 2013, -1 mainly as a result of the reduction in long-term capital inflows. Net long-term financing (official and (A 1 4 13 00 01 02 03 04 05 06 07 08 09 10 11 12 ) 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 pr private flows) declined US$ 726 million from US$ Capital account Financial account Official, medium and long-term Short term (including por tfolio flows) Private, medium and long-term 1.1 billion (2.6 percent of GDP) in 2012 to US$ 334 Net errors and omissions (NEO) Source: Central Bank of Kenya 24 June 2014 | Edition No. 10 The State of Kenya’s Economy Figure 1.38: The exchange rate was stable Exchange rate versus the dollar, pound, and euro, Volatility of the shilling against the dollar, 180 January 2008 - May 2014 January 2011 - June 2014 4 Period of excess 160 3.5 KSh per unit of foreign currency 140 3 120 Exchange rate market stable 2.5 without excess volatility Percent 100 80 2 60 1.5 40 1 20 0.5 0 0 Jan-11 Mar-11 May-11 Jul-11 Nov-11 Jan-12 Mar-12 May-12 Jul-12 Nov-12 Jan-13 Mar-13 May-13 Jul-13 Mar-14 May-14 Sep-11 Sep-12 Sep-13 Nov-13 Jan-14 Jul-05 Apr-07 Feb-06 Sep-06 Nov-07 Jun-08 Jan-09 Aug-09 Mar-10 Oct-10 Mar-11 Dec-11 Jul-12 Apr-14 Feb-13 Sep-13 U.S. dollar British pound Euro Source: Central Bank of Kenya million (0.8 of GDP) in 2013 (Figure 1.37). Short-term capital and financial account in 2013, a significant flows increased by 6.2 percent, from US$ 2.4 billion increase from the 61 percent share in 2012. By April in 2012 to US$ 2.6 billion in 2013. Short-term flows 2014, the figure had declined to 77 percent. Long- including net errors and omissions increased from term flows (both official and private) constituted 6 US$ 3.4 billion in 2012 to US$ 5.0 billion in 2013. percent of the combined capital and capital account, down from 19 percent in 2012. This figure increased Short-term flows still dominate the capital and to 12 percent in April 2014. Short-term flows financing account of Kenya’s balance of payments. (including net errors and omissions) constituted Short-term flows have been largely portfolio flows, 11.3 percent of GDP in 2013, up from 8.4 percent in because yields on shilling-dominated assets have 2012. This figure fell to 8.6 percent in April 2014. Net been very attractive in the fixed-income and equity long-term flows declined from 2.6 percent of GDP in markets. Short-term flows (including errors and 2012 to 0.8 percent in 2013 and 1.3 in the 12 months omissions) constituted 91 percent of the combined ending April 2014. Figure 1.39: Appreciation of the trade-weighted exchange rate suggests that Kenya’s competiveness has declined Index of exchange rate, July 2000 - April 2014 Volatility of exchange rate, December 1999 - April 2014 150 30 Percentage change in exchange rate 140 25 Depreciation 130 20 Index (January 2003 = 100) 120 15 10 110 5 100 0 90 -5 80 -10 70 -15 Appreciation 60 -20 Jan-10 Apr-10 Jul-10 Oct-10 Jan-11 Apr-11 Jul-11 Oct-11 Jan-12 Apr-12 Jul-12 Oct-12 Jan-13 Apr-13 Jul-13 Oct-13 Jan-14 Apr-14 Oct-00 Jul-01 Apr-02 Jan-03 Oct-03 Oct-06 Oct-09 Jul-04 Apr-05 Jan-06 Jul-07 Apr-08 Jan-09 Jul-10 Apr-11 Jan-12 Oct-12 Jul-13 -25 Nominal effective exchange rate Real effective exchange rate Nominal effective exchange rate Real effective exchange rate Source: Central Bank of Kenya 6 The volatility of the shilling experienced in May 2014 is a short-term phenomenon driven by fears of poor performance by the tourism sector as a result of travel advisories and increased activity by Al Shabaab in some parts of Kenya. Although tourism brings in considerable foreign exchange and directly employs more than 100,000 people, the sector’s contribution to GDP is minimal. June 2014 | Edition No. 10 25 The State of Kenya’s Economy The exchange rate remains stable. The Kenya shilling Kenya has built up adequate international reserves remained stable in 2013 and the first quarter of 2014, to cushion shocks. Under the International thanks to several factors (Figure 1.38). First, inflation Monetary Fund’s Extended Credit Facility program, remained within the Central Bank’s targets of 3–7 which it successfully completed, Kenya increased percent. Second, despite political uncertainty its international reserves. These reserves cushion it in 2013, short-term funds continued to flow in, from the numerous shocks it regularly faces. Gross attracted by higher yields in the money markets. reserves increased 18.5 percent, from US$ 7.2 billion Third, the current account improved significantly, at the end of 2012 to US$ 8.6 billion at the end of reducing the volatility of the exchange rate. Fourth, 2013. Official reserves increased 15.1 percent, from international oil and food prices were stable. As US$ 5.7 billion (3.8 months of import cover) in a result, the exchange rate averaged KSh 86.1 to 2012 to US$6.6 billion (4.5 months of import cover) the dollar in 2013, up from KSh 84.5 in 2012, a in 2013 and US$ 6.6 billion (4.6 months of import nominal depreciation of 1.9 percent. In the first cover) in April, 2014 (Figure 1.40). quarter of 2014, the exchange rate averaged KSh 86.3 to the dollar.6 Figure 1.40: The reserves Kenya has built cushion it from shocks 7 5.0 The trade-weighted exchange rate points to a loss 6 4.3 4.5 4.4 4.5 4.1 4.0 of competiveness by Kenya. The strong shilling 3.9 3.7 Reserves (US$ Billion) 5 3.4 3.5 combined with lower inflation in Kenya’s trading 3.0 4 partner economies continues to erode Kenya’s 2.5 competiveness. In 2013 the effective exchange 3 2.0 rate appreciated 5.7 percent. By April 2014, the 2 1.5 annual increase reached 1.0 percent. The trade- 1 1.0 0.5 weighted shilling has been appreciating in real 0 0 terms since March 2013 (Figure 1.39). The loss of 2008 2009 2010 2011 2012 2013 2014 competitiveness this appreciation reflects can be (Apr) Official reserves Months of import cover mitigated by improving the business climate. Source: Central Bank of Kenya 26 June 2014 | Edition No. 10 The State of Kenya’s Economy 2. Growth Outlook for 2014 - 15 T he World Bank projects that Kenya’s GDP will grow at 4.7 percent a year in 2014 and 2015—0.5 percentage points lower than its earlier projections. The economy is estimated to have grown 2.7 percent in the first quarter of 2014. The new projections reflect negative shocks, particularly the effects of the drought, the deteriorating security situation, the government’s fiscal policy, and tighter global credit as the U.S. Federal Reserve winds down its expansive monetary policy. Improvement in the ability of both national and county-level governments to execute the budget will be key to growth. Annual growth of 4.7 percent is predicated on continuation of a stable macroeconomic environment, uptick of investment in both public and private sectors and robust aggregate demand. The government’s reform program to improve the ease of doing business in Kenya is pivotal in achieving faster growth in the medium term. Figure 2.1: Annual GDP growth is projected to remain at about 4.7 percent over the next two years 2.1 Growth prospects remain solid, although Growth outlook 2014 - 2015 the economy is facing headwinds 5.2 G DP is projected to grow 4.7 percent a year in 2014 and 2015. GDP is projected to grow 4.7 percent a year in 2014 and 2015. On the positive 5.0 4.8 side, the economies of Kenya’s trading partners are Percent 4.6 improving, large investments are being made in Kenyan infrastructure, and consumption is projected 4.4 to be strong. On the negative side,the rains arrived 4.2 late and the security situation has deteriorated, which is hurting the tourism sector and instilling fear 4.0 2011 2012 2013 2014 2015 in both existing and prospective investors. These Baseline Pessimistic Optimistic developments caused the World Bank to revise it Source: Central Bank of Kenya projections downward by 0.5 percentage points since the last Kenya Economic Update. of 2014 remained subdued, mainly as a result of delayed rain in the bread basket areas of the Rift Growth in 2014 will be powered by aggregate Valley and increased insecurity. Stronger growth is demand, fueled by strong consumption and expected in the next 18 months, as the execution investment (Table 2.1). Growth in the first half rates of development spending improve and the global economy strengthens. Table 2.1 Components of GDP growth, 2010–16 (Annual percentage increase) Item 2010 2011 2012 2013 2014 2015 2016 GDP 5.8 4.4 4.6 4.7 4.7 4.7 5.3 Private consumption 7.2 3.0 5.5 4.0 6.6 6.4 6.0 Government consumption 6.3 5.2 9.3 4.6 3.4 3.3 3.2 Gross fixed investment 7.7 12.6 11.5 15.6 8.2 8.0 5.2 Gross domestic expenditure 6.7 5.8 6.8 6.5 6.1 6.8 6.6 Exports of goods and non-factor services 17.5 6.6 4.7 6.4 9.2 8.0 7.8 Imports of goods and non-factor services 6.1 15.6 12.5 9.6 6.6 6.4 6.0 Note: Figures for 2014–16 are projections June 2014 | Edition No. 10 27 The State of Kenya’s Economy In the base case scenario, GDP growth is projected forcing rapid adjustment. The main channels of to remain steady, at about 4.7 percent in 2014 transmission include pressures on interest rates and and 2015, supported by a rebound in investment exchange rates, which could strain some banks and growth (Figure 2.1). In this scenario, the recovery financial institutions, reduce domestic demand, and of credit flows supports a (private and public) reignite inflation, increasing borrowing costs and investment-led recovery in the second half of 2014. creating refinancing risk for governments. Reduced The government learns from the experience of liquidity and the repricing of risk increase both the 2013/14, accelerates budget implementation, and central bank and commercial lending rates. manages to keep spending on track. The successful Eurobond issued in June 2014 eases pressure on The World Bank estimates that the Kenyan economy government domestic borrowing, as more credit is grew 2.7 percent in the first quarter of 2014. This made available for the private sector. Government growth is much lower than the 5.7 percent growth spending on large infrastructure projects and the in first quarter of 2013. Poor performance in the related forward linkages spur growth, but the first quarter was driven by inadequate rainfall, related increase in import demand widens the which affected electricity generation and increased current account deficit in 2014, moderating the electricity prices,as well as by slower growth of positive effect. M0 and lower tourist arrivals (see box 2.1 for a description of the model used to estimate first- In the optimistic scenario, GDP grows 4.8 percent in quarter GDP based on high-frequency leading 2014 and 5.0 percent in 2015. Under this scenario, indicators). investment is stronger than in the baseline. Government infrastructure programs start spurring 2.2 Risks to growth have increased economic activity and inflows of foreign direct investment increase, not only in the oil and gas sectors but in other sectors of the economy as T he risks to Kenya’s economic outlook are similar to those highlighted in the December 2013 Update. Domestic factors pose the greatest threats well. Macroeconomic stability is sustained, with to growth, but external risks are also significant. the negative effects of agriculture shocks milder Four main risks—weather-related shocks, the than in the other scenarios. The muted impact of deteriorating security situation, the government’s increased investment on growth in 2014/15 reflects fiscal policy, and tighter global credit—could the purchase of imported equipment, as a result of threaten the growth outlook for 2014 and 2015. which the growth in imports overwhelms exports. The current account deficit is projected to increase Weather-related shock resulting from inadequate from 7.7 percent of GDP in 2013 to an average of rainfall in 2014 could create macroeconomic 8.2 percent in 2014 and 2015. instability. The extent of the effect of inadequate rainfall on agricultural and electricity generations In the pessimistic scenario, growth is expected to remains unclear, but inflationary pressures from fall to 4.4 percent in both 2014 and 2015. In this higher food and electricity prices could threaten scenario, macroeconomic instability drags growth macroeconomic stability, private investment, and down, as the negative effects of inadequate rainfall projected growth. The response of the Central Bank reduce agricultural production and hurt industry to higher inflation will determine the impact of the through higher electricity prices. The tightening drought on growth. A sharp increase in the central of global financial conditions causes short-term bank rate to double digits would choke growth; a capital flows to dry up, creating volatility in the modest increase would have only a minimal effect exchange rate, and inflationary pressures emerge, on growth. 28 June 2014 | Edition No. 10 The State of Kenya’s Economy The deteriorating security situation is dampening of fiscal vulnerabilities that has been reliant on growth prospects. Al Shabaab terrorists escalated portfolio inflows to finance high fiscal and current their activity in Kenya in 2014, killing innocent account deficits poses significant risks to Kenya’s civilians and instilling fear among the general macroeconomic stability. public. The terrorism threat is compounded by a perception of increased criminal activity and The winding down of the liquidity injection into lawlessness in urban areas. A number of countries the global economy by the U.S. Federal Reserve have issued travel advisories, and some tourists may cause volatility in Kenya’s exchange rate and were evacuated from the coast as a result of terror increase domestic interest rates. Because more threats, diminishing the allure of Kenya as a tourist than 70 percent of its capital and financial account destination. International media coverage of these is made up of short-term flows, Kenya is susceptible events hurt tourism,is a major foreign exchange to any reversal of capital flows when global liquidity earner. Visit arrivals and hotel occupancy rates tightens. Such reversals could lead to significant have plunged, and a number of hotels in Mombasa deterioration of domestic financial conditions and have closed. Escalating security concerns and the slow economic activity. Increased volatility could perceived lack of an effective government response hurt investment and growth. may deter foreign investors from doing business not only in certain counties perceived as dangerous but 2.3 Good monetary and fiscal policies are critical to in Kenya as a whole. maintain growth in the near term and increase it in the longer term M The government’s expansionary fiscal policy is onetary policy will come under intense weakening Kenya’s fiscal position and leaving pressure in 2014. Kenya faces both domestic it vulnerable to shocks. Fiscal vulnerability has risks and the external risk of tighter credit. The increased, driven by heavy infrastructure spending, drought that began in the last quarter of 2013 and leaving Kenya with limited room to maneuver in the the delayed rain in the first half of 2014 will increase face of shocks. The overall fiscal deficit for 2013/14 food and electricity prices, causing inflation to rise. is about 7 percent. The high yields on government The monetary authorities will come under pressure securities continue to attract short-term flows, to anchor inflation expectations, as inflationary which are financing the current account. The buildup pressure build up. Figure 2.2: Growth in the first quarter of 2014 was low 3 7 6 2 5 1 Projections 4 0 Projections 3 -1 2013Q1 2013Q2 2013Q3 2013Q4 2014Q1 2 2013Q1 2013Q2 2013Q3 2013Q4 2014Q1 Actual GDP Projection 1 Projection 2 Actual GDP Projection 1 Projection 2 Source: World Bank Staff forecasts Note: Projections of quarterly seasonally adjusted GDP growth projections (left figure) and annual GDP growth (right figure) June 2014 | Edition No. 10 29 The State of Kenya’s Economy Box 2.1: Estimating GDP Growth based on leading indicators Quarterly GDP data in Kenya are published with a delay of at least 90 days, as is the practice in other countries. Leading indicators can help compensate for this delay by providing estimates based on current economic activity. Such estimates can benefit monetary and fiscal policy makers, especially in situations in which a rapid policy reaction is needed. The LEAD indicator is based on monthly data that are published in a timely manner. LEAD estimates may over- or underestimate GDP growth, for a variety of reasons. A change could occur in a sector of the economy that is not directly related to any of the input variables in the LEAD indicator, for example, or it could have an effect that occurs only with a considerable time lag. Another shortcoming of the methodology is the limited ability to model shocks to variables, which can be done mainly through manual intervention of the series rather than by intervening through the residuals of the model, as is the case with dynamic factor models based on the Kalman filter technique. The methodology used to construct the LEAD indicator for Kenya is based on the paper by Opoku-Afari and Dixit (2012). Technical details are included in annex A. The variables used to estimate GDP in the first quarter of 2014 included imports of industrial supplies and machinery, major export products, the number of tourists and passengers arrivals, cement consumption, electricity consumption, electricity hydropower production, the Nairobi Securities Exchange index, registration of commercial vehicles, registration of saloon vehicles, value added tax revenues, personal income tax revenues, government expenditures, and monetary sector indicators. Almost all of these indicators were found to be highly positively correlated with GDP for the period studied. The model evaluation was based on several criteria, including correlations between GDP and the LEAD indicator and the correlation and closeness of the quarterly growth rates. Results of the final model are shown in figures B2.1 and B2.2. Figure B1: Level of real seasonally-adjusted GDP (left scale) and Figure B2: Quarterly growth rate of real seasonally-adjusted GDP LEAD indicator (right scale) for the period 2006 Q1 – 2014 Q1 and LEAD indicator for the period 2006 Q2 – 2014 Q1 450000 120 7 115 430000 110 5 410000 105 390000 3 100 370000 95 1 350000 90 85 -1 330000 80 310000 75 -3 290000 70 2013Q4 2013Q1 2013Q2 2013Q3 2012Q3 2012Q4 2012Q1 2012Q2 2011Q4 2011Q1 2011Q2 2011Q3 2010Q4 2010Q1 2010Q2 2010Q3 2009Q3 2009Q4 2008Q4 2009Q1 2009Q2 2008Q2 2008Q3 2007Q4 2008Q1 2007Q2 2007Q3 2006Q3 2006Q4 2007Q1 -5 2014Q1 2012Q3 2012Q4 2013Q1 2013Q2 2013Q3 2013Q4 2011Q4 2012Q1 2012Q2 2011Q3 2010Q4 2011Q1 2011Q2 2009Q3 2009Q4 2010Q1 2010Q2 2010Q3 2009Q1 2009Q2 2007Q4 2008Q1 2008Q2 2008Q3 2008Q4 2007Q3 2006Q2 2006Q3 2006Q4 2007Q1 2007Q2 Quarterly GDP_SA Quarterly Lead Indicator Difference in growth rates Quarterly growth LEAD indicator Quarterly growth GDP_SA Source: World Bank calculations Source: World Bank calculations 30 June 2014 | Edition No. 10 The State of Kenya’s Economy Tightening monetary policy will delay economic volatility in the money and capital markets. Lower pick-up. Kenya’s commercial banks are quick to raise debt levels would calm these fears and bring Kenya’s their interest rates when the central bank rate rises debt levels closer to those of its peers. but tend not to lower their rates when the central bank rate falls. The government will therefore be Addressing the fiscal pressures emerging under pressure to control lending interest rates. from fiscal expansion is now a priority for the Stung by accusations of inaction in 2011, which led to authorities. Given the reduction in fiscal buffers a sharp increase in inflation, the Central Bank might and the fiscal risks linked to the wage bill and be pressured to be overzealous in raising interest devolution, a strong emphasis on efficiency rates sharply in 2014, even though the source of gains is warranted. Officials need to ensure that inflation is the supply side. additional expenditures are made only if they are both necessary and sustainable. Such caution is The Central Bank has the instruments and buffers to particularly important if Kenya is to address the cushion short-term shocks. Should global financial access and equity challenges in the health sector. conditions tighten, the monetary authorities could allow the shilling to depreciate without Fiscal consolidation is necessary to rebuild buffers. administrative manipulation. With more than $6 The high level of public debt has eaten into Kenya’s billion in international foreign exchange reserves, fiscal space. Fiscal adjustment and consolidation the Central Bank can cushion shocks to the exchange will be necessary to achieve the medium-term rate in the short term. The goal would not be to debt targets of 45 percent of GDP. The authorities defend a particular level of the shilling but to allow have taken measures to enhance revenues. Fiscal an orderly depreciation if necessary. policy now needs to switch to rebuilding fiscal buffers. Emphasis should be on cutting recurrent Kenya’s growth is still dependent on fiscal expenditure across a range of programs and sectors, activity. The ability of both national and county- including public administration. Revenue measures level governments to execute the budget is key to should include revisiting tax measures such as the growth: slow absorption of funds, as in 2013/14, capital gains tax. stifles aggregate demand and economic activity. In addition, larger budget allocations to county Fiscal consolidation should be possible without government could crowd out financing of national reducing infrastructure spending. Fiscal buffers could functions, which would have to be financed by be rebuilt by reducing duplication at the national level additional borrowing, creating macroeconomic of activities being undertaken by county staff and by instability. managing and rationalizing the number of national and county staff; implementing the Civil Servants It has become increasingly difficult for the Pension Act, to reduce the contingent liability of the government to expand much needed capital government; and increasing the efficiency of public expenditure while keeping debt at a sustainable spending in education and health, where wastage level. Kenya’s fiscal deficit grew faster than GDP public expenditure tracking surveys have identified over the past two years. As a result, the net public waste. Ring-fencing investment in infrastructure— debt to GDP ratio inched toward the 50 percent which determines the ability to connect regions threshold. Even though the deterioration in the fiscal and markets, develop alternatives, and widen balance is linked to infrastructure spending, which the distribution of economic opportunities across increases investment and production, higher levels different socioeconomic zones and groups—will be of debt could raise fears among private investors key for enhancing medium-term prospects. about the government’s ability to pay, resulting in June 2014 | Edition No. 10 31 The State of Kenya’s Economy Kenya needs to preserve the macroeconomic Sources of growth must be broad based, not stability that has underpinned its growth. Action skewed toward consumption alone. Kenya has a in two areas is required: putting in place a credible high consumption to GDP ratio (94 percent), a low fiscal consolidation program that preserves the investment to GDP ratio (27 percent), a low export investment program but reduces duplication and to GDP ratio (28 percent), and a negative net export waste in recurrent spending and ramping up the ratio (–20 percent). To achieve annual growth level of growth to Kenya’s potential in order to create rate of 8–10 percent by 2017, as envisioned by more jobs and reduce poverty. the Vision 20130 and MTP 2 Kenya would have to raise the investment Growth levels are inadequate to to GDP ratio to more than 30 reduce poverty. Economic growth Kenya has a high percent. Doing so would require needs to accelerate to absorb consumption to GDP the savings to GDP ratio to increase Kenya’s burgeoning labor force ratio (94 percent), a faster than the consumption to and reduce poverty. The average low investment to GDP GDP ratio. The increased savings growth rate of 4.9 percent for ratio (27 percent), a low would finance domestic investment 2010–13 (4.6 percent for 2003–13) export to GDP ratio (28 projects. The economy would also is higher than in the last years of the percent) and a negative need to rely more on exports to Moi administration (2.3 percent), finance the growth in imports. net export ratio but it will not allow Kenya to attain (–20 percent) the upper-middle-income status to which it aspires. 32 June 2014 | Edition No. 10 The State of Kenya’s Economy Special Focus: Improving Primary Health Care Services in Kenya’s New Devolved System June 2014 June 2014 | | Edition Edition No. No. 10 10 3 iii Special Focus 3. Challenges and Opportunities K enya’s health sector faces many challenges. Health outcomes are weak and public spending too low, forcing households to bear a large share of health care costs. As a result, just falling ill drives hundreds of thousands of Kenyan households into poverty every year. The key to improving outcomes lies in better primary health care. Under Kenya’s new devolved system of government, responsibility for delivering health care services lies with county governments. A series of actions on their part increase the efficiency and effectiveness of the system, improve health outcomes, and move Kenya toward its goal of achieving universal health coverage. This special focus of the Kenya Economic Update significant share of hospital admissions. Mortality identifies some the challenges facing Kenya’s health from noncommunicable diseases is above the global system. It examines how reforms have already average (624 versus 573 deaths per 100,000), as is improved primary care and suggests ways in which the number of deaths from injuries (116 versus 78 Kenya can build on its devolved system of delivering deaths per 100,000). The average life expectancy of primary health services to achieve the government’s a person born in Kenya in 2011 is virtually identical goal of providing universal health coverage. to that of a person born in China in the late 1960s (Figure 3.2); the total fertility rate (the number of 3.1 Kenya’s health sector faces many challenges births per woman) in Kenya in 2011 is comparable Health outcomes are weak to that of Brazil in the early 1970s (Figure 3.3). These K enya’s health outcomes are inconsistent with its aspiration to become a middle-income country. High levels of maternal mortality and stunting among figures clearly highlight the urgent need to fast- track strategies and evidence-based interventions for improving these important health outcomes. For children have remained more or less unchanged over optimizing the gains, such health sector interventions the past two decades (Figure 3.1). Meanwhile, the need to be complemented by improvements in burden of noncommunicable diseases is beginning women’s education, and access to water and to rise, with such illnesses now contributing a sanitation, roads, and transport. Figure 3.1: Kenya’s maternal mortality rate has fallen since 1990, but the decline has been much more modest Figure 3.2: Life expectancy in Kenya in 2011 is comparable than in some neighboring countries to that of China in the late 1960s. . . 1,400 1400 80 Maternal deaths per 100,000 live births 75 1,200 70 Life expectancy at birth (years) 1,000 65 800 61.08 60 600 490 55 400 50 400 200 45 320 40 0 19 0 63 19 6 69 19 2 75 19 8 81 19 4 87 19 0 60 19 3 96 20 9 02 20 5 20 8 11 Kenya Tanzania Uganda Burundi Rwanda 6 6 7 7 8 9 9 9 0 0 19 19 19 19 19 19 19 19 20 1990 1995 2000 2005 2013 China Kenya Source: World Health Organization Source: World Development Indicators (World Bank) 34 June 2014 | Edition No. 10 Special Focus Figure 3.3: . . . and the total fertility rate is comparable to that of Brazil in the Mid 1970s HIV. The inability of the government to increase 9 its contribution to these important disease control 8 programs and effectively complement donor- 7 supported initiatives could create a high level of contingent liabilities when donor funding declines. Ferti lity rate (birth per woman) 6 5 4 Every year, health-related expenditures push 3 Kenyan households into poverty. The proportion 2 of sampled households reporting catastrophic 1 spending on health fell from 11.4 percent in 2007 0 to 9.4 percent in 2013, according to preliminary 60 63 66 69 72 75 78 81 84 87 90 60 93 96 99 02 05 08 11 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 20 20 20 20 results of the 2013 household healthcare utilization Brazil Kenya and expenditure survey (Figure 3.5). But this figure Source: World Development Indicators (World Bank) still means that health-related expenditure pushed hundreds of thousands of Kenyan households into Public spending is inadequate and inefficient, poverty in 2013 alone. Improving access to primary forcing households to bear too much of the care would contribute to achievement of the twin financial burden of illness goals of the World Bank Group—to eliminate K enya’s spending on health is not commensurate with its disease burden, and reliance on donor financing exposes it to a high risk of contingent extreme poverty and share prosperity—because the poor tend to benefit most from primary health care and out-of-pocket health care expenditures are an liabilities. Public expenditures on health remain low important cause of poverty. (4.1–6.8 percent of total government expenditure during the past decade) (Figure 3.4). They have Elimination of charges for public primary health increasingly been crowded out by donors who are care and maternity services at all public facilities keen to support Kenya’s efforts to control priority is expected to increase access. The new policy, communicable diseases. Over the past decade, announced in 2013, reflects the government’s strong for example, Kenya has been totally dependent on commitment to achieving universal health coverage donors for the supply of free condoms, and donors and eliminating the need for payment at the point of fund a large share of antiretroviral treatment of service delivery for essential health services. Figure 3.4: Kenya allocates too little of its budget to health expenditure 7 3 6.0 Percent of total government expenditure 6 5.8 5.3 5.4 2 5.0 5 4.6 4.7 4.5 Percent of GDP 4.3 4.1 4.1 2 4 1 3 2 1 1 0 0 Total health expenditure Public health services Source: Kenya National Bureau of Statistics 2014 June 2014 | Edition No. 10 35 Special Focus Figure 3.5: More than 9 percent of Kenyan households reported catastrophic expenditure on health in 2013, with the figure ranging widely by county 25 of household reporting catastrophic health 20 15 National average = 9.4 percent expenditures 10 9.32 5 0 Kilifi Kwale Isiolo West Pokot Nyeri Marsabit Kericho Nyandarua Narok Laikipia Tana River Samburu Vihiga Bungoma Uasin Gishu Kakamega Kiambu Makueni Turkana Busia E. Marakwet Kajiado Kisii Migori Bomet Embu Kirinyaga Baringo Muranga Nyamira Mombasa Meru Homa Bay Taita Taveta Siaya Tharaka Nithi Kitui Trans-Nzoia Nairobi Kisumu Nakuru Lamu Nandi Source: Kenya National Bureau of Statistics 2013 Medical personnel are capable, but many facilities nurses, and other medical professionals are lured are understaffed and personnel are too highly away from public facilities, many moving abroad to concentrated in and around urban areas take advantage of better opportunities. New and K enyan health providers are much more better incentives by county governments to recruit knowledgeable than providers in many other and retain health care personnel would help address countries in the region, according to the 2012 Public this problem (Table 3.1).1 Expenditure Tracking Survey. Nearly 80 percent of health staff could correctly diagnose five common Uneven geographical distribution of health health conditions (Figure 3.6). Their ability to fully care personnel affects the quality of care. The manage the conditions was much lower. government has strived to post doctors across Kenya faces an acute shortage of competent health Kenya. But most physicians prefer to work in urban care providers. Thousands of Kenyan physicians, areas, especially Nairobi, Mombasa Kisumu, and Eldoret. As a result, despite the broad geographic Figure 3.6: Kenyan providers can diagnose common health conditions, distribution of health care facilities, medical but many cannot fully treat them professionals are clustered disproportionately 90 86 82 around cities (Figure 3.7). 81 80 72 70 Scope for increasing efficiency exists M Percent of providers 60 54 ost service providers in Kenya have adequate 50 47 46 inputs, but provider effort is low. Some 95 40 percent of health facilities have access to sanitation. 28 30 However, almost a third (29 percent) of public health 20 care providers are absent, with the highest absentee 10 rates in large urban health centers (Figure 3.8). Some 0 80 percent of these absences are approved and Doctors Clinical officers Nurses Midwives Correct diagnosis Full treatment hence within management’s power to influence. Source: Kenya Institute for Public Policy Research and Analysis 2013 1 The head counts by counties during October and November 2013 revealed that many of the medical staff on the books may not actually be present in public facilities for much of the time. 36 June 2014 | Edition No. 10 Special Focus Figure 3.7: Health facilities are everywhere but personnel are disproportionately in cities South Sudan Ethiopia ( ! ! ( ( ! ( ! ( ! ( ( ! ! ( ! ( ! ( ! ((! ! !! ( ( ! ( ! ( ( ! ( ! ! ( ! ( ( ! ( ! ! ( ( ! ! ( ! ( ( ! ! ( ( ! ( ! ! ( ! ( ! ( ! ( ! ( ( ! ( ! ( ! ( ! ! ( ( ! ! ( ( ! ( ! ( ! 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(( ! ! (! ! ( (! ! ((! ! (!( ! ( ! ( (! ! (! (! (! ( ! ! (! ( (! ! !(! !((((! ! ( ( ! ! ( ( ! (! (!(! ( ! (! ( ! ( ! ! ( ! ! (! ( ! ( ( ! ! ( ( ! ! ( (! (! ! ( ( (! ! (! ( ! ( ! ( ! ( ( ! ! ( ( ! (! ! ( ! (!(! ( ! ( ( ! ! ( (! ! ( ! ( ! ( ! ( ! ( ! (! ( ! ( ! ( ( ( ! ( ! ! (! ( ! ( ! ( ! ! ( ! ( ! (!(! ( ! ( ! ( ! ( ( ! (! ! ( ( ! ! ( ! ( ( ! ( ! ! ( ! ( ! ( ( ! ( !!( ! ! ( ( !( ! ( ( ! ( ! ( ! ! ( Kilometers ( ! ! ( 40 20 0 40 80 120 160 ( ! ! ( ( ! ( ! ( ! ! ( ! ( ! ( ( ! (! ( !( ( ( ( ! ( ! ! ( ( ( ! (! !! ! ! ! ( (! ! ( ( ! (! ! ( Tanzania ! ( ( ! ! (! (! !( ! ( ! ( ( ! ( ( ! ( ! Health facilities (primary care) Poverty ( ! ( ! Dispensaries and clinics < 40 % ( ! ( ! ( ! (! ! ! ((! (! (! (!( ( ! (( !! ( ! Health centers and maternity homes 41 - 60 % ! ( ( !! ( ( ! 61 - 80 % ( ! > 81 % ( ! Source: Ministry of Health 2014 June 2014 | Edition No. 10 37 Special Focus Table 3.1: Number of registered medical personnel and personnel in training in Kenya, by profession 2013 Registered medical personnel Number of medical Type of personnel Number per 100,000 Total number personnel in training people Doctors 8,682 21 3,457 Dentists 1,045 3 291 Pharmacists 2,202 5 826 Pharmaceutical technologists 6,204 15 434 BSC nurses 1,873 4 2,736 Registered nurses 37,907 91 2,708 Enrolled nurses 26,841 64 279 Clinical officers 13,216 32 1,125 Public health officers 8,637 21 568 Public health technicians 5,969 14 0 Source: Kenya National Bureau of Statistics 2014 Weak service delivery and absenteeism are the public providers took just 44 percent of the correct major problems facing public hospitals. Kenyan health treatment actions needed to manage maternal and providers are knowledgeable, but their knowledge neonatal complications. is not getting translated into service delivery: only 40 percent of health care professionals are able to provide Technical efficiency is high at health centers and full treatment. About a third of health staff are absent low at dispensaries (Figure 3.10). The low efficiency on any given day, and more than 80 percent of such of dispensaries partly reflects the fact that many are absences are authorized (Figure 3.9). located in sparsely populated communities. Provider knowledge is weak, albeit stronger than 3.2 Primary health care is key S in many other countries. Only 58 percent of public trong evidence suggests that provision of health providers could correctly diagnose at least primary health care is critical to improving health four of five very common conditions (such as diarrhea outcomes. Selective scaling up of primary health with dehydration and malaria with anemia), and care services was a common feature among the 30 Figure 3.8: Almost a third of public health providers are absent from their facility Figure 3.9: … and 80 percent of those absences are authorized 40 37.6 Other approved absence 51.0 35 Absence from Facility, percent Official mission 19.8 30 29.2 28.3 27.5 Training and seminar attendance 10.1 25 20.9 Sick and maternity leave 7.1 20 15 Not specific 5.4 10 Unapproved absence 3.4 5 3.2 On strike 0 0 10 20 30 40 50 60 All Public Private Rural Public Urban Public Percent Source: Kenya Institute for Public Policy Research and Analysis 2013 Source: Kenya Institute for Public Policy Research and Analysis 2013 38 June 2014 | Edition No. 10 Special Focus low- and middle-income countries that achieved Table 3.2: Utilization of outpatient services in Kenya the largest average annual reductions in under-five increased between 2003 and 2013 mortality and increases in skilled birth attendance Percent of people Average number of reporting illness (Rohde and others 2008). The family health program Year visits per capita that did not seek in Brazil, for example, helped reduce infant mortality care by 13 percent within five years (Macink and others 2003 1.9 22.8 2007). (Brazil continues to emphasize primary 2007 2.6 16.7 health care, even though it has already achieved 2013 3.1 12.7 steep declines in maternal and child mortality rates, Source: Kenya National Bureau of Statistics 2013 thanks to an effective primary care to district hospital referral system). load (63.5 percent), cost-effectiveness (50.8 percent), Figure 3.10: Dispensaries have great scope to improve the efficiency drug supply (49.4 percent), and patient satisfaction of their services than other types of health care institutions in Kenya (12.7 percent) (Varatharajan and others 2004). 90 The preliminary results of Kenya’s 2013 Household 82 80 80 Healthcare Utilization and Expenditure Survey show 73 70 that sustained focus on primary care helped double Technical efficiency (percent) 60 outpatient utilization between 2003 and 2013, 50 47 raising the number of per capita outpatient visits 40 from 1.7 to 3.1 (Table 3.2). 30 Expenditure on public health facilities 20 enhances equity, because low-income groups 10 disproportionately use such facilities. The public 0 Referral District Health centers Dispensaries sector is the primary source of both inpatient and hospitals hospitals outpatient care for the poorest two asset quintiles, Source: Kioko 2013 accounting for about two-thirds of all visits by them (Table 3.3). Inpatient care is less pro-poor than outpatient care, with a marginally higher Primary health care is cost-effective. Hospitals and share of the richest quintile using from the public specialist care consume 70 percent of health costs sector (43 percent for inpatient versus 36 percent but serve only 30 percent of the population (Logie for outpatient). Improving the delivery of primary and others 2010). A study in India found that a 2 health care services would thus help Kenya achieve percent increase in resource allocation for primary its Vision 2030 and constitutional mandates. health care was associated with increases in patient Table 3.3: Poor Kenyans disproportionately use public health care facilities (percent of total visits) Asset Public Faith-based Private Other quintile Outpatient Inpatient Outpatient Inpatient Outpatient Inpatient Outpatient Inpatient Lowest 66 66 8 18 21 14 5 2 Second 65 65 7 17 25 16 3 2 Middle 63 63 9 22 25 14 3 1 Fourth 53 52 10 22 34 24 3 2 Highest 36 43 9 13 49 43 6 1 Source: Kenya National Bureau of Statistics 2013 June 2014 | Edition No. 10 39 Special Focus To be effective, the approach to comprehensive Figure 3.11: A comprehensive primary care system requires all of the building blocks identified by the World Health Organization primary health care needs to be multi-sectoral, multidisciplinary, and holistic. A comprehensive System building block Objective/outcome system requires many components, including an adequate number of health staff in all disciplines, • Service delivery • Improved health an effective supply chain system for drugs and • Human resources (level and equity) laboratory services, adequate transport services and • Information • Greater responsiveness infrastructure, and sufficient water and sanitation • Medical products, vaccines, • Protection of social and (Figure 3.11). Factors contributing to the successful and technologies financial risks • Financing • Improved efficiency implementation of a comprehensive primary health • Leadership and governance care system include: • good policies and legislation at the national and county level for the equitable implementation of cost-effective health care interventions that Source: de Savigny and Taghreed 2009 emphasize participation by communities and referral facilities throughout the Horn of Africa. individuals (Black 1990); Faith-based organizations operate facilities in the • participatory approaches to planning and most remote areas of the country. These facilities management; are well integrated with the service delivery systems • health literacy, especially among women, which of the health ministries, which second health staff has been found to reduce both maternal and to them and provide them with drugs and essential child morbidity and mortality (Black 1990); and health commodities. Private franchises are rapidly • appreciation by the community of good-quality increasing to provide good-quality health in rural services, which increases utilization. Kenya. The Kenya Medical Supplies Agency (KEMSA) partners with the private sector to deliver essential 3.3 Kenya is well positioned to reform medicines, and the National Hospital Insurance Fund its health sector (NHIF) partners with the private sector to provide K enya is particularly innovative at developing home-grown solutions to reducing poverty. It is also more open than many other countries to health services. 3.4 Changes have already improved the delivery private sector participation in the delivery of public of primary health services goods. M-pesa, which addresses the challenge Kenya’s new constitution guarantees rights of rural banking, also provided a platform for to health care and devolves responsibility for M-health (mobile health)—the use of mobile delivering health care to the counties devices to support the practice of medicine and public health. Health workers now send weekly reports on communicable diseases by SMS instead K enya’s new constitution guarantees rights to health care. These rights include the right to the highest attainable standard of health, including the of mail. These weekly reports of integrated disease surveillance and response data help the authorities right to life, reproductive health, and other attributes control communicable diseases, such as cholera of good health, as well as the right to emergency and measles. treatment. Children have the right to basic nutrition and health care; people with disabilities have the right The health sector is vibrant. Kenya has several to reasonable access to health facilities, materials, pharmaceutical companies. Kenyan hospitals and devices; and minorities and marginalized groups offering specialized services are widely used as have the right to reasonable levels of health services. 40 June 2014 | Edition No. 10 Special Focus The constitution devolves the operation of health partners were posted to the most underserved services to county governments. Under the new provinces, and the ministry of health seconded staff constitution, which creates equally powerful central to faith-based organizations. and county governments, the operational aspects of service delivery have been devolved to the counties; Beneficiary assessment surveys indicate increased the national government is now responsible only user satisfaction with primary health care centers. for policy making and regulation. Counties have the The citizen’s report card exercise conducted by freedom to organize their own sectors, including Family Care International in October 2012 in Kitui health, and distribute resources among them as they and Nakuru counties noted improvements in service deem necessary. delivery. A majority of the 599 clients interviewed stated that the overall quality of service, waiting Actions by the center have made a difference time, cleanliness, and state of the health centers had T he split into two ministries of improved during the previous year. health in 2007 helped improve Kenya’s focus on primary health Public expenditure studies also care. The break-up of the Ministry The World Bank indicate improvement. A public of Health into the Ministry of Public is supporting the expenditure tracking survey covering Health and Sanitation and the Ministry of health in randomly selected health facilities Ministry of Medical Services helped implementing a phased showed that 95 percent of sampled the government focus on primary introduction of health public health centers and 76 percent health care. The ministries have of public dispensaries received HSSF insurance subsidies since been re-merged. The significant grants in 2013 and that 92 percent to the poor through of sampled public health centers and gains made in primary health care the National Health provision during the split should not 69 percent of public dispensaries Insurance Fund had annual operational plans in be eroded. place (Kenya Institute for Public Policy Research and The government launched the Health Sector Analysis 2013). The difference between the figures Services Fund (HSSF) in 2010. The goal of the HSSF for health centers and dispensaries could reflect the is to improve the equitable supply of good-quality fact that public dispensaries were included for the health care by dispensaries and health centers, the first time in 2012. The results of both surveys are very facilities closest to communities. This initiative was encouraging, given that HSSF systems were measured a direct policy response by the Ministry of Health to barely a year after their introduction in more than evidence that its mechanisms were not guaranteeing 3,000 facilities countrywide. sufficient or predictable funding to those facilities, adversely affecting the quality, quantity, and scope of The HSSF has the potential to initiate a process of their services. Funded by the government of Kenya, change that could go well beyond its initial scope of the World Bank, and Danida, the HSSF originally improving the management and accountability of provided direct cash transfers from the national level resources. Implementation in thousands of facilities to dispensaries and health centers that meet the across the country of a funding mechanism that qualifications to register with it (Danida has since puts the community in a management role has the begun providing funds directly to counties). potential to yield desirable outcomes other than improving the health status of Kenyans. It could Economic stimulus package funds were used to stimulate communities to create and foster direct fund hiring by counties. Under the new devolved social accountability systems mechanisms; explore system, districts hired more than 3,000 nurses. In the possibilities of contracting out services to addition, contract staff provided by development nongovernmental organizations and community/self- June 2014 | Edition No. 10 41 Special Focus help groups closest to the community; and facilitate Primary health services are responding to needs horizontal linkages with other sectors important of local community. The HSSF system, under which to health, such as social services and education, citizen representatives to work together with health by including them in planning and implementing staff to plan and manage the facility using facility- relevant local projects. generated evidence, has the potential to improve the responsiveness of primary health services to Ensuring access to health insurance by the poor communities’ needs. is essential to reducing inequities and achieving universal health care. The Bank is supporting Almost all (98 percent) primary health facilities the Ministry of health in implementing a phased have Health Facility Management Committees, introduction of health insurance subsidies to the and more than half of their members are elected poor through the National Health Insurance Fund. (Figures 3.12 and 3.13). In more than 80 percent of sampled public primary health facilities, the Local communities are more involved L ocal communities in Kenya identify health priorities, help manage health facilities, and participate in planning and implementing Figure 3.12: The vast majority of public dispensaries and health centers have Health Facility Management Committees and work plans 120 initiatives that address them. They participate in 99.6 98.2 facility management by electing representatives to 100 91.2 the Health Facility Management Committee (HFMC), 80 whose secretary is the head of the facility. The HFMC 69 Percent is responsible for planning, managing, and reporting 60 on all aspects of the facility’s activities. As of 2011, 40 the HSSF was funding 787 health centers and 2,427 dispensaries. Since its inception in 2011, it has 20 disbursed KSh 1.695 billion (about US$20 million). 0 The government plans to expand the fund to cover Public dispensaries Public health centers all government and faith-based primary health care Work plan Health facility management committee facilities that meet its criteria, doubling the current Source: Kenya Institute for Public Policy Research and Analysis 2013 number of facilities by 2015. Figure 3.13: More than half of Health Care Facility Management Committee members are elected 100 90 Percent of committee members 80 70 60 50 40 30 20 10 0 All Public (all) Public Public health Public Public rural Public urban Private dispensaries centers hospitals (non-profit) Elected Appointed by local leadership Appointed based on recommendation of the Ministry of Health No community members Source: Central Bank of Kenya 42 June 2014 | Edition No. 10 Special Focus committees reported meeting every quarter (Kenya All public primary health care facilities in Kenya Institute for Public Policy Research and Analysis are now covered by the “pull” system of supplying 2013). More than three-fourths of the facilities (77 essential medicines and medical supplies. This percent) reported disclosing financial information system is a demand-based approach for ensuring to the public; facilities that did not submit quarterly the reliable availability of health commodities at financial reports were 20 percent less likely to all service delivery points within a health system. receive funds, suggesting that the HSSF program Under this system, facilities order their supplies has put in place some internal controls. The survey and commodities based on actual need rather than identified the need to strengthen financial record receiving centrally determined numbers of medicine keeping at the facility level, as more than a quarter of kits (the “push” system). Under the push system, dispensaries and about 10 percent of health centers commodities where distributed to all facilities, from did not keep proper records. dispensaries to hospitals, as kits, whose contents were assembled based on the type of facility, the The supply of essential medicines and medical patient load, disease patterns, and prescribing and supplies has improved dispensing practices. Coming up with the right mix S everal of donor partners, including the World of commodities and distributing them in the right Bank, invested heavily in strengthening quantities in a timely manner proved very difficult. governance and reforming the management of Both supplying agency and recipients were unhappy the supply chain. These efforts are paying off: well- with the system. functioning modalities of financing, procurement, and distribution are now in place. New resource Early assessments suggest marginal improvements allocation criteria for rural health facilities were in the availability of essential medicines, especially developed in 2011–12. Drawing rights are now for maternal health (Figure 3.14). Under the pull allocated at two levels—national to district and system, nearly two-thirds of facilities had essential district to health facilities. Allocation from the drugs, and supply was marginally better, according national to the district level is based on (a weighted to a Public Expenditure Tracking Survey conducted average of) the district’s workload, population, in 2012. At most facilities, the supply of essential number of rural health facilities, and poverty index. medicines for children was better than the supply for Allocation from the district to the facility is based maternal care, although the pull system seemed to primarily on the facility’s workload. have improved the supply of drugs for maternal care (the supply of pediatric drugs declined). The government, in partnership with development Figure 3.14: The availability of maternal medicines increased under the pull system, but the availability of pediatric medicines declined partners, is supplying medicines and medical 90 supplies. The Kenya Medical Supplies Authority 81 80 77 (KEMSA) is supplying facilities with commodities Percent of faciliti es stocked with 70 68 procured with funds provided by the government 62 61 and the International Development Association essenti al medecines 60 48 (IDA) through the Kenya Heath Sector Strategic and 50 Investment Plan (KHSSP). The Ministry of Health 40 reimburses KEMSA based on documented evidence 30 of supply to primary health facilities (proof of 20 deliveries) using government and Danida funding. 10 Reimbursement to KEMSA aims at establishing a 0 pool of funds for supplying essential medicines and All drugs Maternal drugs Push system Pull system Pedriatic drugs medical supplies to primary health care facilities. Source: Kenya Institute for Public Policy Research and Analysis 2013 June 2014 | Edition No. 10 43 Special Focus Reform of the supply of essential medicines has offering basic emergency obstetric care varies been pro-poor. The per capita value of supplies widely across counties, however (Ministry of Health provided by KEMSA was higher in districts with the 2013) (Figure 3.15).3 Basic emergency obstetric largest proportions of the poor (75 percent) than in care is much easier to offer than comprehensive districts in which about a quarter of the population emergency obstetric care, which requires specialists, was living below poverty line (KSh 99 versus KSh 86) equipment, blood storage, and an operation theater. (World Bank 2011). However, it cost KEMSA more to ship supplies to poorer districts (which tend to 3.5 How can the government address be more remote) than to better-off districts; part remaining challenges? of the increased expenditure thus reflected higher Reforms undertaken in recent years improved shipping costs. Determining drawing rights based on health care, but challenges remain S utilization trends could be disadvantageous to poorer hortfalls of nurses, clinical officers, and laboratory districts with dispersed populations. Although the technicians are still a problem, particularly in study advises caution in drawing policy conclusions, rural communities and densely populated urban it identifies the need for budgeting higher transport slums The number of medical personnel per patient costs for poorer districts and linking supply chains is very low (see Table 3.1). to community strategies in poorer districts where communities are more widely dispersed with limited Other challenges also need to be addressed. They transport to access fixed health facilities. include: the inadequate supply of basic emergency obstetric services; financial constraints (including The policy of offering free maternity services at all the timely availability of funds at the point of service public health facilities is a step in the right direction delivery); low usage of health services as a result of A ttended birth is known to reduce maternal deaths; it is therefore an important intervention for achieving the MDG4 target of reducing the social, economic, and cultural barriers that affect demand; and lack of effective oversight mechanisms to reduce misuse (over reporting and unnecessary under-five mortality rate by two-thirds between referrals to higher-level facilities that offer larger 1990 and 2015. The proportion of health facilities reimbursements) fostered by perverse incentives. Figure 3.15: The proportion of Kenyan health facilities offering basic emergency obstetric care ranges widely across counties 100 basic emergency obstetric care (percent) 90 Proportion of health facilities offering 80 70 60 50 40 30 20 10 0 Kilifi West Pokot Nyandarua Kwale Kakamega Isiolo Uasin Gishu Bungoma Marsabit Narok Bomet Kajiado Samburu Makueni Vihiga Nyeri Tana River Kericho Laikipia Kiambu Kisumu Kitui Wajir Trans-Nzoia Mandera Kirinyaga Nakuru Baringo Busia Tharaka Nithi Siaya Muranga E. Marakwet Nairobi Homa Bay Taita Taveta Mombasa Turkana Meru Kisii Embu Nyamira Machakos Garissa Lamu Migori Nandi Source: Ministry of Health 2013 3 Basic emergency obstetric care includes antibiotics and uterotonic drugs, anti-convulsants for eclampsia and preeclampsia, manual removal of the placenta, removal of retained products, assisted vaginal delivery, and basic neonatal resuscitation (WHO and others 2009). 44 June 2014 | Edition No. 10 Special Focus Structures, functions, and the roles of different Various actions could reap benefits K stakeholders need to be defined enya could realize quick wins in its new devolved T he HSSF is improving the quality of primary care. Already, facilities that respect basic rules in the management and reporting of the resources health system by taking the following actions: 1. Focus first on making existing public primary health care facilities operational. County fact provided can access a fairly predictable resource sheets suggest that more than 10 percent of base. Health commodities are more readily primary health care facilities are nonfunctional; available, major staff gaps have been largely filled, the real situation appears to be even worse. results-based financing schemes are on the way to be instituted countrywide, and the network is Devolution provides a unique opportunity to functional. strengthen the delivery of primary healthcare services. With counties now responsible for A review of structures and functions of healthcare delivering primary health care services, there is a facilities under the new devolved system is renewed hope that some chronic weaknesses— needed. The HSSF was created before the devolved especially staffing and retention of staff—will government set-up was put in place. It needs to be be addressed. By the end of the first year of reviewed and revised so that it works optimally under devolution, some improvements in services the new system. With the help of policy makers from were already visible. The governor of Mandera, both the national and county governments, the HSSF for example, had made all 52 primary health care needs to determine whether it should fund all four facilities in the county operational. All primary levels of service delivery in all counties. health care facilities in the county now have maternity units, and all wards have ambulances. The roles of the national and county governments Kakamega County is focusing on improving and donors in the new system need to be thrashed out. The HSSF is funded by the government of Kenya, maternal and newborn health services. Other the World Bank, and Danida. The government and counties have also made progress, which has the Bank will continue to provide their funds to the not yet been systematically documented. national government. Danida is now providing its Many counties, for example, have conducted share directly to counties. audits of human resources to weed out ghost workers. Closer oversight is expected to reduce A comprehensive framework for managing absenteeism. conditional grants is needed, to support the 2. Improve access to basic emergency obstetric Ministry of Health in exercising an appropriate care. A majority of Kenyan women give birth at oversight role. In 2013/14 the national government home without a skilled birth attendant. Given provided almost KSh 10 billion in conditional grants the risks of unattended births, it is vital that to counties in order to “fund” free primary and resources be re-allocated to obstetric care. maternity services and compensate 12 counties for Before new infrastructure is developed, counties the spillovers costs associated with operating level 5 referral hospitals. Clear conditions are needed need to ensure that all primary health centers to focus county health managers’ attention on the and dispensaries with maternity wards offer results that counties are expected to achieve with basic emergency obstetric care. The governors those funds, provide accountability for their use, and chief executives of health need to give and ensure that funding flows are integrated with priority to addressing existing gaps, including mainstream county systems instead of through by coordinating support from partners. Most inefficient parallel systems. primary health centers have 20–30 beds that are June 2014 | Edition No. 10 45 Special Focus underutilized. Some of these beds could be used 6. Use the Health Sector Services Fund to as maternity waiting beds, especially in counties continuously improve facility performance and where road connectivity is poor and ambulances enhance accountability to both the community cannot reach all households and the county. Performance accountability 3. Build on partnerships with faith-based remains the cornerstone of the devolved health organizations, and partner with the private system in Kenya. Counties need to ensure that sector. Governors and chief executives of the Health Facility Management Committees health need to look for and take advantage of (HFMCs) participate actively and regularly in the opportunities to involve all sector stakeholders facility management cycle, “own” annual facility (donors, NGOs, faith-based organizations, and plans, set realistic targets, and receive support others) that can help to address gaps in planning from qualified staff to help them implement and managing relevant activities. Faith-based activities and measure their achievements in organizations are already complementing public a fair manner. The experiences of the results- health facilities, and the Ministry of Health has based financing pilot in Samburu County suggest been seconding staff and providing essential that objective assessment of performance medicines to more than 600 dispensaries run through regular supportive supervision enhances by such organizations. Counties need to sustain motivation of providers and supervisors and build on this well-established relationship. and improves retention (Population Council Kenya also has a vibrant private sector, which 2013). Introducing performance management is rapidly expanding to rural areas through measures through results based financing franchised networks. It is important to leverage provides the opportunity to focus on the key such networks for delivering public goods, deliverables of the system and ensures that there especially reproductive, maternal, newborn, is a coordinated thrust to delivery of results. and child health services, by including both 7. Ensure that communities “own” health facilities faith-based and private facilities under the free and dispensaries. HFMCs draw their legitimacy maternity care initiative. Such a mechanism and mandate primarily from the community. could operate through the existing coverage of Social participation plays a vital role in health, maternity care offered by the National Hospital health system coverage, performance, and Insurance Fund (NHIF). accountability. It is therefore vital that counties 4. Fast track capacity improvements within establish clear regulations and guidelines on a decentralized structure: By bringing the the composition, roles, responsibilities, powers, management closer to service delivery, capacities, and resources delegated to the decentralization provides opportunities for HFMCs. Policy makers also need to ensure that continuous course correction, and enables HFMCs remain nonpartisan entities protecting improved community engagement and service community interests and that the community utilization. receives regular feedback on technical 5. Optimize the use of fixed facilities. The inpatient performance and financial accountability. Report services of a large number of Level 3 facilities to higher levels within the county health system are grossly underutilized. The reasons for this progress, challenges, and needs as they are underutilization should be determined. If it turns expressed by the community. out that the facilities are not needed, counties 8. Rationalize hospital infrastructure. Building should consider alternative uses for them new infrastructure for each county when service (maternal shelters, nutrition rehabilitation, VCT). delivery could be strengthened by re-energizing 46 June 2014 | Edition No. 10 Special Focus existing infrastructure or establishing strategic 10. Develop flexible strategies. Given the varied partnerships with faith based organizations, needs and capacities of counties and the complex does not make sense. The efficient and effective and evolving relationship between counties and utilization of new county referral hospitals can the central government, no single strategy can be achieved only when lower-level facilities improve the delivery of primary health care and the referral system function properly. services across Kenya. It is therefore important Recognizing the importance of rationalizing to develop flexible strategies built on shared hospital infrastructure, Brazil and countries common principles that are demand driven, in Central Asia created hospital networks that focused on outcomes, and co-financed from optimize efficiency. Clusters of counties in Kenya domestic resources. Kenyan innovativeness and need to develop networks of hospitals that entrepreneurship can find ways to quickly scale provide good-quality referral back-up to primary up appropriate and locally relevant solutions. care facilities. 11. Improvements in the health sector will need 9. Ensure the delivery of essential medicines and to come from productivity and efficiency gains, medical supplies. All counties in Kenya have not a larger budget. In the immediate future, entered into memoranda of understanding with budget increases for all sectors are constrained KEMSA or the Mission for Essential Drugs and by the fiscal expansion of the past few years Supplies (MEDS), the agency that handles pooled and the budgetary pressure associated with procurement for faith-based organizations. implementing the new constitution’s county These agreements will yield economies of scale reforms. Initially, therefore, more than ever and increase the quality of essential medicines. before, quality improvements in the health A quick analysis of the ordering pattern between sector will have to come from productivity and January and March 2014 suggests that only efficiency gains. Demonstrating value for money three counties allocated less than 30 percent and the effectiveness of existing health spending of their orders for primary health care facilities. will strongly bolster the sector’s chances of Although more analysis needs to be done, these attracting a larger budget allocation once current preliminary figures suggest that counties are budgetary pressures ease. committing to sustaining the delivery of primary health care services. June 2014 | Edition No. 10 47 REFERENCES ▪ Black, R. E. 1990. “Prevention in Developing Countries.” Journal of General Internal Medicine 5 (5 Suppl): 132–35. ▪ Bloomberg. 2014. “Markets: Dow Jones Industrial Average.” http://www.bloomberg.com/quote/INDU:IND deSavigny, Don, and Adam Taghreed, eds. 2009. “Systems Thinking for Health Systems Strengthening.” Geneva: World Health Organization. ▪ Family Care International. 2012. “Direct Facility Funding and Quality of Care: Assessing Perceptions and Building Evidence for Advocacy,” October. ▪ Kenya Institute of Public Policy Research and Analysis. 2013. “Kenya Public Expenditure Tracking and Service Delivery Indicators Survey.” Nairobi. ▪ Kenya National Bureau of Statistics. 2013. “Household Healthcare Utilization and Expenditure in Kenya.” Nairobi. ———. 2014. Economic Survey. Nairobi. ▪ Kioko, U. 2013. “Health Sector Efficiency in Kenya: Implication for Fiscal Space.” Report to the World Bank. Nairobi. ▪ Logie, D. E., M. Rowson, N. M. Mugisha, and B. McPake. 2010. “Affordable Primary Health Care in Low Income Countries: Can It Be Achieved?” African Journal of Primary Health Care & Family Medicine 1 (2): 1–3. ▪ Macinko, J., B. Starfield, and T. Erinosho. 2009. “The Impact of Primary Healthcare on Population Health in Low- and Middle- Income Countries.” Journal of Ambulatory Care Management 32 (2): 150–71. ▪ Macinko, J., de Souza, M.F.M., Guanais, F. C. and C.C.S. Simoes. 2007. “Going to scale with community-based primary care: An analysis of the family health program and infant mortality in Brazil, 1999–2004.” Social Science and Medicine 65: 2070–80. ▪ Ministry of Health. 2013. “Kenya Service Availability and Readiness Assessment Mapping.” Nairobi. ———. 2014. Health Facilities List. http://www.ehealth.or.ke/. ▪ Ministry of Public Health and Sanitation. 2012. “Aide-Memoire: Joint Danida and World Bank Implementation Support Mission to Kenya Health Sector Support Program.” February 12–20. ▪ Nairobi Securities Exchange. 2014. “Market Statistics.” https://www.nse.co.ke/ ▪ Office of the Controller of Budget. 2014. “County Budget Implementation Review Report.” Half Year, Fiscal Year 2013/2014, February. Nairobi. ▪ Opoku-Afari, M. and S. Dixit. 2012. “Tracking Short-Term Dynamics of Economic Activity in Low-Income Countries in the Absence of High-Frequency GDP Data.” IMF Working Paper. WP/12/119. ▪ Population Council. 2013. “Evaluation of Performance-Based Finance Pilot in Samburu County, Kenya, Qualitative Research Findings.” Nairobi. ▪ Rohde, J., S. Cousens, M. Chopra, V. Tangcharoensathien, R. Black, Z. A. Bhutta, and J. E. Lawn. 2008. “30 Years after Alma-Ata: Has Primary Health Care worked in Countries?” Lancet 372 (9642) 950–61. ▪ Rotich, H. 2014. “Wage Bill Trends, Current Situation and its Impact on Growth and Development. Presentation to the National Debate on Wage Bill Sustainability.” March. Nairobi. ▪ The National Treasury. 2014. “Quarterly Economic and Budgetary Review. Third Quarter 2013/2014 May.” Nairobi. ▪ WHO (World Health Organization). 2014. “Trends in Maternal Mortality: 1990 to 2013.” Estimates by WHO, UNICEF, UNFPA, the World Bank, and the United Nations Population Division. Geneva. ▪ WHO (World Health Organization), UNICEF (United Nations Children’s Fund), UNFPA (United Nations Population Fund), and AMDD (Averting Maternal Death and Disability). 2009. “Monitoring Emergency Obstetric Care: Handbook.” Geneva: WHO. ▪ World Bank. “World Development Indicators.” Washington, DC: World Bank. ▪ World Bank. “Global Economic Prospects.” Washington, DC: World Bank. ▪ Varatharajan, D., Thankappan, R. and S. Jayapalan. 2004. “Health Policy and Planning 19(1): 41–51.” 48 June 2014 | Edition No. 10 ANNEXES ANNEX 1 Leading economic indicator for Kenya – Technical note – Objective This note explains the process of construction of a Leading economic indicator (LEAD) based on high frequency data for estimating the change of GDP in the current period. Due to the worldwide practice of applying various compound methods of collecting and calculating GDP data, the GDP vintages are published with a delay of around 90-days. Consequently, the construction of the LEAD indicator should help in avoiding this delay by giving approximate indication about the current developments of the economic activity. The main purpose of LEAD is to provide real-time information about the pulse of the Kenyan economy. This information would be of benefit to monetary and fiscal policy makers, especially in situations when a prompt policy reaction is expected. The index complements existing forecasting tools that are used by the Kenyan authorities, and can be used as an input to short- and medium-term forecasting. Having real time information on economic activity brings twofold benefits to policy makers. First, the GDP estimates will allow monetary and fiscal institutions to make more informed policy decisions. Second, it will also be of use to policy makers as an input in preparing macroeconomic projections. For example, they will get additional input indicator for predicting the state of the current economic activity that may be important for closing the initial data conditions in computing the projections. Model description The LEAD indicator is based on monthly frequency data that are published on timely manner. The major data input for this indicator are the leading indicators published by the Kenya National Bureau of Statistics (KNBS), the monetary aggregates published by the Central Bank of Kenya (CBK) and the value added tax (VAT) data by the Treasury of Kenya. In selection of the leading variables, it should be taken into account that the variables are published in timely manner, in similar time period and at least with monthly frequency. The leading variables should share common stochastic component with the GDP variable, which means that they should be correlated with the business cycle in the country. According to this, a broader set of leading variables was considered: • Imports of industrial supplies and machinery and equipment serve as a proxy for the industrial production activity. These variables are included in the model with a one period lag because a certain time period is needed since the import of industrial supplies and the machinery and equipment till the period they are utilized in the industrial production which is directly reflected in the value added of the economic activity. • Major export products of Kenya: horticulture, tea and coffee. These products combine substantial proportion of overall exports of Kenya and directly determine the economic activity in the country. 50 June 2014 | Edition No. 10 Annexes • Tourists and passengers arrivals at the two most frequent airports in Kenya: Jomo Kenyatta International Airport and MOI International Airport. The tourism of Kenya has a relatively high contribution to the overall value added and thus, tourists and/or passenger arrivals from these two airports serve to capture the tourism activity in the country. • Cement consumption is used as an indicator for the construction activity in Kenya. For example, greater cement consumption should indicate expansion of construction activity that is positively associated to the expansion of the business activities through building new production capacities. Greater cement consumption can also be associated with greater household consumption through building new dwellings and the complementary purchases of necessary appliances. The cement consumption variable is included with one period lag due to the time period needed from purchasing cement till the projects starts building. • Total electricity consumption is also seen as an indicator for expansion of business activities in Kenya because electricity is the major energy source for production processes, transportation and similar business related activities. • Electricity hydropower production is included as a rough indicator for the weather conditions in Kenya that directly affects agricultural production. Agricultural production is important contributor in the overall value added in Kenya which engages greatest proportion of the labor force through formal and informal side of the labor market. More electricity hydropower production may indicate favorable weather conditions for agricultural production and reverse. As extreme case may also be excessive electricity production through hydropower when there are floodings in the country, but this is considered a rare event in Kenya. • Nairobi Stock Exchange Index (NSE 20) as an indicator for the financial markets activity that is expected to be positively correlated with the business cycle in the country. • Registration of commercial vehicles (buses, station wagons, vans and pick-ups) are essential part of the transportation services and are considered to be positively associated with the business activities in the country. • Registration of saloon vehicles reflects part of the household consumption. • Value Added Tax (VAT) total is included as an indicator for the final purchases in Kenya. In absence of any indicator for the retail sales in Kenya this can be a good proxy. In addition, a disaggregated data for VAT are used such as VAT of local as indicator for domestic consumption and VAT of imports as indicator for imported goods for the business activities. • Personal income tax is included as an indicator for the developments of the labor markets. The personal income tax captures both, employment changes in the labor market as well as changes in the wages. • Government expenditures as an indicator for the government consumption. • Monetary sector indicators: credit to private sector or one of the monetary aggregates M0, M1, M2, M3 or quasi-money. These indicators are important because they capture the credit and deposit activity in the country that is directly related to the consumption (personal and investment). In addition, monetary sector indicators also capture part of the changes in monetary policy stance that is transmitted in the short- to medium-term in the real economic activity in the country. June 2014 | Edition No. 10 51 Annexes A more technical details about the leading indicators used are presented in the table below: Table 1: Details about the leading indicators Variable Value Source Imports of industrial supplies KSh million KNBS Imports of machinery and equipment KSh million KNBS Exports of horticulture Metric tonnes KNBS Exports of tea Metric tonnes KNBS Tourists arrivals at JKI and MOI International Airports. Number of people KNBS Passengers arrivals at JKI and MOI International Airports. Number of people KNBS Cement consumption Metric tonnes KNBS Total electricity consumption Kw/H KNBS Electricity production hydropower Kw/H KNBS NSE 20 Index value with base KNBS year Registration of buses, station wagons and vans and pick-ups and Number of vehicles KNBS saloon vehicles VAT total, VAT locals, VAT imports KSh million Treasury Personal income tax KSh million Treasury Government expenditures KSh million Treasury Credit to private sector KSh million Central Bank of Kenya M0, M1, M2, M3, quasi-money KSh million Central Bank of Kenya Imports KSh million Central Bank of Kenya Exports KSh million Central Bank of Kenya Net exports = exports-imports KSh million Central Bank of Kenya Source: World Bank, Global Economic Prospects The methodology of construction of the LEAD indicator is based on the research paper by Opoku-Afari and Dixit (2012).6 Accordingly, the following multi-step procedure is performed: 1. All variables used are expressed in real terms. The variables that were originally in nominal terms were converted into real terms by using the CPI as a deflator. 2. The variables are seasonally adjusted using the common “Census X-12” additive method due to their seasonal patterna 3. In order to capture the co-movement between the changes in the leading indicators and the economic activity -and to alleviate the problem of stock versus flow variables- monthly changes of the selected components are calculated by using the symmetric percentage change formula. This approach allows equal treatment for both negative and positive changes in the series, i.e. a percentage increase in a variable X followed by the same percentage decrease would leave the level of X at its original value. The symmetric percentage change is presented as follows; 6 The title of the paper is: “Tracking Short-Term Dynamics of Economic Activity in Low-Income Countries in the Absence of High-Frequency GDP Data”, IMF Working Paper No. 12/119. 52 June 2014 | Edition No. 10 Annexes 4. The inverted standard deviation of each of the series is calculated: ; where is the standard deviation of the variable which is used later on with step 5 as a main input for calculating the weights of each of the variables. The reason for calculating the inverted standard deviations is to penalize for the volatility of the variables. For example, a higher volatility of the variable will result in higher standard deviation and thus, lower inverted standard deviation. This will assign lower weight of the variable in the index. In other words, the inverted standard deviation penalizes the volatility of the variable by assigning lower weight in the overall index. 5. Normalized weights for each series are computed based on the sum of the already calculated inverted standard deviations of each of the series with step 4. Normalized weight indicates that the sum of the inverted standard deviations equals to one. This is presented with the formula: where is the calculated weight for each variable, is the inverted standard deviation of the respective variable. 7. The calculated symmetric percentage changes of the variables from step 3 are multiplied by their respective normalized weigh calculated with step 6. 8. The overall index is calculated by summing the weighed symmetric percentage changes of the variables. The index is then re-based according to a base year (in this case as a base year is selected 2010).7 A first step in assessing the degree of association of the included leading indicators with the real seasonally adjusted GDP, is computing correlation coefficients presented below: Table 2: Correlation coefficients between the seasonally adjusted real GDP and each of the leading indicators presented in Table 1. All of them are in real terms and seasonally adjusted CEMENT_CONSUMP_SA 0.97077*** QUASI-MONEY 0.96238*** CREDIT_R_SA 0.989738*** NET_EXPORTS -0.903217*** ELECTR_CONS_SA 0.975541*** NSE_20_R_SA -0.727127*** ELECTR_PRODHYDRO_SA 0.560358*** PASSENGERS_SA 0.793754*** EXPORTS_R_SA 0.648545*** TEA_VOL_SA 0.512647*** GOV_EXPEND_R_SA 0.837017*** TOURISTS_SA 0.597356*** HORTICULTURE_SA 0.499155*** VAT_IMPORTS_R_SA 0.75867*** IMPORTS_R_SA 0.880957*** VAT_LOCALS_R_SA 0.261651*** INCOME_TAX_R_SA 0.933238*** VAT_TOTAL_R_SA 0.629121*** IND_SUPPLIES_R_SA 0.847942*** VEHICLES_COMERC_SA 0.903139*** M0_R_SA 0.733498*** VEHICLES_SALOON_SA -0.409995*** M1_R_SA 0.912844*** COFFE_VOL_SA -0.1353 M2_R_SA 0.97152*** Source: authors’ calculations based on data from KNBS, CBK and Treasury M3_R_SA 0.982396*** *** indicates statistical significance at 1 percent level MACHINERY_EQ_R_SA 0.889453*** 7 The dynamics of the index does not depend from the selection of the base year. June 2014 | Edition No. 10 53 Annexes Model results As expected, almost all leading indicators are highly positively correlated with GDP. The correlation is in the majority of cases above 0.8 and is statistically significant at 1 percent level. Exceptions are the exports of coffee, registration of vehicles – saloon and NSE 20. For all the three variables was estimated a negative correlation with GDP and it was statistically significant for the NSE and saloon vehicle registration. The negative correlation between the NSE 20 index and GDP could be explained by the fact that stock market prices are forward looking, i.e. they are a result of expectations about the future that may be different from the current economic trends. It may also be due to the structure of the stock exchange market in Kenya which includes several companies, such as financial institutions, who serve the regional market. Accordingly, their business cycles are not determined solely by the Kenyan economic activity so changes in the share value of these companies may not correlate with the Kenyan business cycle. The data sample used ranges from 2005: M01 to 2014:M03. The model evaluation was done according to several criteria such as correlation between the levels of GDP and LEAD indicator and most importantly, by the correlation and closeness of their quarterly growth rates. By conducting various iterations of the model through including, excluding some of the variables and by various combinations of them, the final model was selected. The final model includes the following leading indicators: cement consumption with one period lag, electricity consumption, electricity production hydropower, imports of industrial supplies and imports of machinery and equipment with one period lag, number of tourist arrivals at the two largest airports in Kenya, registration of commercial vehicles (busses, vans, pick-ups and station wagons), VAT total, reserve money M0 and net exports. The calculated weights with steps 5 and 6 (mentioned before) of each of the variables in the LEAD indicator and the LEAD indicator without outliers are presented in Table 3 (later on in the text). Table 3: calculated weights of each of the variables included in the LEAD indicator and the LEAD indicator without outliers Weight in the LEAD indicator Variable: Weight in the LEAD indicator without outliers M0 0.34 0.43 electricity consumption 0.21 0.19 electricity production 0.09 0.08 hydropower cement consumption 0.08 0.07 imports of industrial supplies 0.07 0.06 number of tourist arrivals 0.05 0.04 VAT 0.05 0.04 registration of commercial 0.04 0.04 vehicles imports of machinery and 0.04 0.03 equipment net exports 0.04 0.03 54 June 2014 | Edition No. 10 Annexes The narrower M0 aggregate is selected in the model instead of broader monetary aggregates such as M2 or M3 because it provides best fit of the model. This might be explained with the argument that currency in circulation is the major component of the M0 aggregate unlike the wider monetary aggregates that are dominated by deposits that in the short-run do not fluctuate to the same extent as the currency in circulation (the former especially holds for the time deposits). Currency in circulation plays important role in Kenya’s payments because they are still mainly done on cash basis, although money to deposit ratio has been declining in recent years due to increased financial intermediation mainly driven by mobile-based banking transactions M-pesa (Andrle et al. 2013). Therefore, the fluctuations in economic activity that are reflected through sales and other cash transactions will be directly shown in the M0 aggregate, while not necessarily in the wider monetary aggregates due to their more stable structure. Additional explanation why M0 aggregate may provide better fit is because it captures part of the changes in the monetary policy stance. Those changes in the monetary policy stance are reflected immediately in the banks’ reserves that are also part of M0, whereas they are not part of the broader monetary aggregates. Banks’ reserves are important factor because the major instruments for controlling the liquidity in the money market by the CBK (the repo operations and cash reserve requirements), directly affect banks’ reserves. Consequently, the monetary policy conduct of the CBK is characterized as: “Monetary policy is in principle based on modified monetary aggregate framework. Reserve money targets are declared as de jure operational target…..” (Andrle et al. 2013), p. 20. Moreover, the empirical evidence points that changes in the monetary policy stance are at least to some extent transmitted to the real economic activity in the short-run through reserve money and this provides greater correlation of M0 aggregate with the real economic activity (Andrle et al. 2013). The results from the final model suggest that the correlation and the goodness of fit (R2 coefficient) between the levels of GDP and LEAD indicator are estimated as quite high - 0.94 and 0.89, respectively. The correlation between the annual and quarterly rates of growth is calculated at 0.81 and 0.52, respectively. The R2 coefficient calculated for the annual and quarterly growth rates between GDP and LEAD indicator are estimated at 0.66 and 0.27, respectively. The figures of the levels of GDP and LEAD indicator and their quarterly and annual growth rates are presented below: Figure 1: Level of real seasonally-adjusted GDP (left scale) and LEAD indicator (right scale) for the period 2006 Q1 – 2014 Q1 450000 120 430000 115 110 410000 105 390000 100 370000 95 350000 90 85 330000 80 310000 75 290000 70 20 4 Q1 20 1 20 2 20 3 20 1 20 2 20 3 20 4 20 3 20 4 20 4 20 1 20 2 20 3 20 1 20 2 20 2 20 3 20 4 20 3 20 4 20 1 20 4 20 1 20 2 20 1 20 2 20 3 20 2 20 3 20 4 Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q 13 14 13 13 13 12 12 12 11 11 12 11 11 10 10 10 10 09 09 09 08 08 08 09 08 07 07 07 06 06 07 06 20 Quarterly GDP_SA Quarterly Lead Indicator Source: authors’ calculations based on the data from KNBS, CBK and Treasury June 2014 | Edition No. 10 55 Annexes Figure 2: Quarterly contribution of the variables included in the LEAD indicator (in percent) 100 90 80 70 60 Percent 50 40 30 20 10 0 20 Q2 Q1 20 Q1 20 Q3 20 Q4 20 Q1 20 Q2 20 Q3 20 Q4 20 Q2 20 Q3 20 Q4 20 Q1 20 Q2 20 Q3 20 Q4 20 Q1 20 Q1 20 Q2 20 Q3 20 Q4 20 Q2 20 Q3 20 Q4 20 Q1 20 Q2 20 Q3 20 Q4 20 Q2 20 Q3 20 Q4 20 Q1 13 13 14 11 12 12 12 12 13 13 10 10 10 10 11 11 11 09 09 09 09 07 07 07 08 08 08 08 06 06 06 07 20 CEMENT_CONSUMP_SA_LAG ELECTR_CONS_SA ELECTR_PRODHYDRO_SA IND_SUPPLIES_R_SA_LAG MACHINERY_EQ_R_SA_LAG TOURISTS_SA VEHICLES_COMERC_SA VAT_TOTAL_R_SA INVERSE_NETEXPORTS_R_SA M0_R_SA Source: authors’ calculations based on the data from KNBS, CBK and Treasury. The level of LEAD indicator closely coincides with the movements of the level of GDP throughout the whole period with some exceptions. For example, exceptions are the periods 2007:Q1-2008:Q1 and 2010:Q2- 2011:Q2 where the LEAD indicator grows more intensively than the GDP mainly due to the increase of positive contribution of M0 aggregate and electricity consumption in both periods (Figure 2). Another exception is the 2009:Q2-2009:Q4 period when the level of the LEAD indicator falls more sharply than the GDP mainly due to the fall in contribution of the M0 monetary aggregate and electricity production hydropower. The more intensive increase of the LEAD indicator compared to the GDP during first period (2007:Q1- 2008:Q1), was characterized with a greater electricity consumption due to the expansion of almost all economic activities in the country. Concurrent with this, the reserve money growth was caused by the increased cash outside the banks due to higher number of transactions in the country as a results of the expansion of the economic activity and accumulation of commercial banks’ reserves according to which Figure 3: Quarterly growth rate of real seasonally-adjusted GDP and LEAD indicator for the period 2006 Q2 – 2014 Q1 7 5 3 1 1 -3 -5 Q3 Q4 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q4 Q1 Q2 Q3 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 12 12 13 13 13 13 12 12 10 11 11 11 11 09 09 09 09 10 10 10 07 07 07 08 08 08 08 06 06 07 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 Difference in growth rates Quarterly growth LEAD indicator Quarterly growth GDP_SA Source: Authors’ calculations based on the data from KNBS, CBK and Treasury. 56 June 2014 | Edition No. 10 Annexes the CBK had to revise the growth target of the M0 aggregate (source: CBK Annual Report 2008). During the second period: 2009:Q2-2009:Q4, the LEAD indicator fell more steeply compared to the GDP due to the shrinkage of the M0 aggregate, which was a result of the accumulation of government deposits that negatively affected liquidity on markets. Accordingly, this accumulation of government deposits led to appropriate reaction by the CBK mainly in the second half of 2010 by injecting liquidity through reverse repo operations in order to mitigate the liquidity shortages on the markets. This reaction by the CBK was the major reason for the growth of the reserve money in Kenya in 2010:Q2-2011:Q2 period (CBK Annual Report 2011). The quarterly growth rates of GDP and LEAD indicator series are presented in Figure 3. The data suggest that they overlap in the most recent period (2012:Q4-2013:Q3) and their difference is marginal. However, a greater difference can be noticed in the afore-mentioned periods where the levels of GDP and LEAD indicator diverge the most, which is expected. What is most important about the LEAD indicator is how well it captures the turning points in the economic activity (growth versus slow-down and vice versa). From Figures 1 and 3, it can be noticed that in most of the period the turning points are captured quite accurately suggesting that the LEAD indicator may be useful tool for analyzing the economic activity in Kenya for the current period because the GDP data is published with a delay of 90 days. In order to further improve the fit of the LEAD indicator, additional exercise has been conducted by identifying and removing the outliers from the variable that has greatest weight in the LEAD indicator, which in this case it is the M0 aggregate. The rationale for identifying and removing the outliers from M0 variable is because any temporary excessive movements of the M0 aggregate will be strongly reflected in the overall LEAD indicator, which was the case during the three periods mentioned before: 2007:Q1-2008:Q1; 2009:Q2-2009:Q4 and 2010:Q2-2011:Q2. Consequently, this has reduced the predictive power of the index over those periods. Figure 4: quarterly growth rates of seasonally-adjusted GDP, LEAD indicator and LEAD indicator with removed outliers 7 5 3 1 -1 -3 -5 Q1 20 2 20 3 20 4 20 4 20 1 20 1 20 2 20 3 20 3 20 4 20 4 20 1 20 2 20 1 20 2 20 3 20 4 20 1 20 2 20 3 20 3 20 4 20 2 20 3 20 4 20 1 20 1 20 2 20 3 20 4 Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q 13 14 13 13 13 12 12 12 12 11 11 11 11 10 10 10 09 10 09 09 09 08 08 07 08 08 07 07 06 06 07 20 Quarterly growth LEAD indicator with removed outliers Quarterly GDP growth Quarterly growth of LEAD indicator Source: Authors’ calculations based on the data from KNBS, CBK and Treasury June 2014 | Edition No. 10 57 Annexes The identification of the outliers has been applied on the monthly symmetric changes of the M0 variable (described with step 3 earlier in the text), instead of its levels because M0 is a stock variable that has an increasing long-term trend. For example, any temporary excessive increase of the level of the M0 aggregate in the earlier period of the sample may be lower or equal to its stock level later on in the sample period and thus, it may not be identified as an outlier. The same conclusion holds if there is any excessive fall of the level of the M0 aggregate in the later period of the sample because this fall of the level may be lower or equal to the M0 stock value in the beginning of the sample period. The identification of the outliers has been done according to the commonly applied approach in the empirical literature by setting a benchmark for the minimum and maximum values of the monthly changes of the index. The minimum and maximum points have been defined on the basis of the median value of the sample minus/plus one standard deviation. The observations that are lower/higher than this minimum-maximum benchmark have been replaced with the defined minimum and maximum of the sample. By removing the outliers of the M0 variable, variability has decreased and the weight of the M0 variable has increased from 0.34 to 0.43. The newly computed weight with removal of the outliers are presented in Table 3. What is most important with this version of the LEAD indicator is that the correlation between the quarterly growth rates of GDP and LEAD indicator has increased to 0.62 compared to 0.58 previously, and the differences between the quarterly growth rates have been reduced. In the same manner, the R2 has also increased marginally from 0.33 to 0.38. The comparison of the series - quarterly GDP growth, the LEAD indicator with removed outliers and the original LEAD indicator (Figure 4), suggests that the LEAD indicator with removed outliers more closely matches the quarterly GDP growth rates and the differences in the growth rates has been reduced at the extreme points in the periods: 2007:Q1-2008:Q1; 2009:Q2-2009:Q4 and 2010:Q2-2011:Q2. Furthermore, in the most recent period starting from 2012:Q4; the difference between the quarterly growth rates between GDP and LEAD indicator without outliers has almost disappeared. This may be a good sign for Figure 5: Quarterly seasonally-adjusted GDP growth projections (left figure) and annual GDP growth projections (right figure), in percent 3 7 6 2 5 1 4 Projections Projections 0 3 1 2 2013Q1 2013Q2 2013Q3 2013Q4 2014Q1 2013Q1 2013Q2 2013Q3 2013Q4 2014Q1 Actual GDP Projection 1 Projection 2 Actual GDP Projection 1 Projection 2 Source: authors’ calculations based on the data from KNBS, CBK and Treasury 58 June 2014 | Edition No. 10 Annexes the improvement of the fit of the model, which may provide a more accurate prediction of the current GDP. Projections for 2014:Q1 The projections based on most recent data vintages of the leading indicators for the first quarter of 2014 indicate that the quarterly GDP growth will slow-down and enter into negative territory estimated between -0.6% and -0.5%. The quarterly GDP slow-down can be explained mostly with the unexpected drought at the end of last three months of 2013 that is transmitted to lower electricity production hydropower in the first quarter of 2014. Additional factors that affect the economic slow-down are lower quarterly growth of M0 and tourist arrival. According to these estimates, the annual growth rate in the first quarter of 2014 is estimated between 2.8% and 2.6% which again indicates a slow-down of the economic growth. Conclusion and possible next steps This exercise has produced a composite leading indicator for Kenya that estimates quarterly GDP movement based on ten leading variables. The usefulness of this indicator is that it is composed of monthly frequency data that are published regularly and in timely manner and accordingly, it can be utilized by the policy makers in predicting the current stage of the economic activity. This can be helpful for preparing the medium term projections because the final estimated point of this indicator may be used as initial condition in starting the projection process, having in mind that the quarterly GDP data are published with a delay of up to three months. The application of this model requires continual update and reassessment of the variables included and their weights, at least once a year, due to the dynamic economic environment in Kenya. In future, this work can be extended by utilizing Dynamic Factor Models based on Stock and Watson methodology and/or principal component analysis. June 2014 | Edition No. 10 59 Annexes Annex 2: Macroeconomic environment 2009 2010 2011 2012 2013 GDP growth Rates (percent) 2.7 5.8 4.4 4.6 4.7 Agriculture -2.5 6.3 1.5 4.2 2.97 Industry 2.8 5.4 2.9 4.6 5.2 Services 5.1 5.5 5.3 5.5 5.3 Fiscal Framework (percent of GDP)* Total revenue 21.8 23.9 24.0 23.1 23.2 Total expenditure 26.6 29.5 29.1 29.1 30.4 Grants 0.8 1.3 0.7 0.5 0.6 Budget deficit (including grants) -5.2 -7.1 -4.3 -5.6 -6.9 Total debt (net) 42.2 44.9 48.3 45.5 47.3 External Account (percent of GDP) Exports (fob) 14.7 16.1 16.9 15.4 13.3 Imports (cif) 33.5 38.2 43.2 41.5 37.1 Balance of trade -12.7 -14.3 -18.8 -17.1 -13.9 Current account balance -5.4 -7.7 -9.7 -10.6 -7.7 Financial and capital account 8.0 8.2 9.6 13.7 9.3 Overall balance 2.5 0.5 -0.1 3.1 1.6 Prices Inflation (average) 10.5 4.1 14.0 9.6 5.7 Exchange rate (average KSh/$) 77.4 79.2 88.8 84.5 86.1 Source: World Bank, based on data from Kenya National Bureau of Statistics, International Monetary Fund and Central Bank of Kenya * End of FY in June (e.g 2009 = 2008/2009) Annex 3: GDP growth rates for Kenya SSA and EAC (2008-2012) 2009 2010 2011 2012 2013 2009-2013 Kenya 2.7 5.8 4.4 4.6 4.7 4.4 SSA (excluding South Africa) 4.0 6.0 4.9 4.1 6.0 5.0 Uganda 7.2 5.9 6.7 3.4 6.2 5.9 Tanzania 6.0 7.0 6.3 6.5 7.1 6.6 Rwanda 4.1 7.2 8.6 7.7 7.0 6.9 Source: World Bank, Global Economic Prospects 60 June 2014 | Edition No. 10 Annexes Annex 4: Kenya annual GDP GDP, current prices GDP, 2001 constant GDP/capita, current GDP growth Years prices prices KSh Billions KSh Billions US$ Percent 2003 1142 1042 440 2.8 2004 1274 1090 462 4.6 2005 1416 1156 524 6.0 2006 1623 1229 612 6.3 2007 1834 1315 721 7.0 2008 2108 1357 786 1.5 2009 2376 1394 768 2.7 2010 2570 1475 787 5.8 2011 3047 1541 800 4.4 2012 3404 1611 943 4.6 2013 3798 1686 994 4.7 Source: World Bank, based on data from Kenya National Bureau of Statistics and World Bank Development Indicators Annex 5: Broad sectors growth (half year, percent) Year Half Agriculture Industry Services GDP H1 -2.7 4.6 7.0 4.0 2009 H2 -2.3 1.1 3.3 1.6 H1 4.6 4.7 2.9 3.7 2010 H2 7.8 6.0 8.2 7.8 H1 1.9 3.5 5.1 4.2 2011 H2 1.2 2.3 5.4 4.6 H1 1.8 3.6 5.6 4.1 2012 H2 6.2 5.5 5.4 4.9 H1 5.7 7.2 4.9 5.2 2013 H2 0.8 3.3 5.7 4.3 Source: World Bank, based on data from Kenya National Bureau of Statistics Agriculture = Agriculture and forestry + Fishing ‘Industry = Mining and quarrying + Manufacturing + Electricity ans water + Construction ‘Services = Wholesale and retail trade + Hotels and restaurants + Transport and communication + Financial intermediation + Real estate, renting and business services + Public administration + Education + Other services + FISIM June 2014 | Edition No. 10 61 62 Annex 6: Quartely growth rates (percent) June 2014 | Edition No. 10 AGRICULTURE INDUSTRY SERVICES GDP Years Quarters Q/Q-1 Q/Q-4 (Q:Q-3)/ Q/Q-1 Q/Q-4 (Q:Q-3)/ Q/Q-1 Q/Q-4 (Q:Q-3)/ Q/Q-1 Q/Q-4 (Q:Q-3)/ (Q-4:Q-7) (Q-4:Q-7) (Q-4:Q-7) (Q-4:Q-7) 2010 1 -9.9 5.9 -0.7 -0.7 4.4 2.1 5.9 0.2 2.6 -1.9 1.4 1.6 2 -9.2 3.3 0.9 4.2 5.0 2.9 2.7 5.7 3.1 1.5 6.1 2.6 3 25.0 8.6 4.0 2.2 7.2 5.1 8.8 6.1 3.1 10.7 7.2 4.0 4 4.5 6.9 6.3 -0.8 4.8 5.4 -6.6 10.5 5.5 -1.8 8.3 5.8 2011 1 -15.7 0.1 4.9 0.0 5.6 5.7 1.5 5.8 7.0 -4.9 5.0 6.7 2 -5.7 4.0 5.0 0.2 1.5 4.7 1.4 4.4 6.6 0.0 3.4 6.0 3 20.6 0.2 2.8 1.3 0.7 3.1 9.6 5.3 6.4 11.3 4.0 5.2 4 6.5 2.2 1.5 2.2 3.8 2.9 -6.4 5.5 5.3 -0.7 5.2 4.4 2012 1 -16.1 1.7 1.9 -0.8 2.9 2.3 1.6 5.7 5.2 -6.2 3.8 4.1 2 -5.4 2.0 1.5 1.4 4.2 2.9 1.2 5.5 5.5 0.7 4.5 4.4 3 26.2 6.7 3.2 0.8 3.6 3.6 9.2 5.1 5.4 11.5 4.6 4.5 4 5.6 5.7 4.2 5.9 7.4 4.6 -5.9 5.7 5.5 -0.1 5.2 4.6 2013 1 -15.2 6.9 5.4 0.0 8.3 5.9 0.4 4.5 5.2 -5.8 5.7 5.0 2 -7.5 4.5 6.0 -0.7 6.0 6.4 1.8 5.2 5.1 -0.3 4.7 5.0 3 22.4 1.4 4.5 3.6 9.0 7.7 8.5 4.5 5.0 11.4 4.6 5.0 4 4.3 0.2 3.0 -4.9 -2.1 5.2 -3.6 7.0 5.3 -0.7 3.9 4.7 Source: World Bank, based on data from Kenya National Bureau of Statistics Annexes Annexes Annex 7: Inflation Year Month Overall inflation Food inflation Energy inflation Core inflation January 18.3 24.6 17.3 12.1 February 16.7 22.1 14.8 12.1 March 15.6 20.3 13.0 12.0 April 13.1 16.2 11.1 11.0 May 12.2 14.6 10.0 11.3 June 10.1 10.5 9.0 10.7 2012 July 7.7 6.6 7.4 9.7 August 6.1 3.6 6.7 9.0 September 5.3 2.9 6.0 8.3 October 4.1 1.4 5.0 7.0 November 3.3 1.7 3.1 5.5 December 3.2 1.7 2.8 5.5 January 3.7 2.4 3.9 5.2 February 4.5 4.0 4.6 4.9 March 4.1 2.9 5.3 4.8 April 4.1 3.6 4.3 4.6 May 4.1 4.3 3.5 4.1 June 4.9 6.5 3.5 4.1 2013 July 6.0 8.4 4.6 4.4 August 6.7 9.7 5.3 4.3 September 8.3 12.6 5.7 5.4 October 7.8 12.0 4.8 5.4 November 7.4 10.7 5.1 5.5 December 7.1 10.4 5.1 5.1 January 7.2 10.1 5.5 5.4 February 6.9 9.1 5.6 5.5 2014 March 6.3 8.3 4.7 5.4 April 6.4 8.1 5.9 5.3 May 7.3 8.9 8.1 5.6 Source: World Bank, based on data from Kenya National Bureau of Statistics June 2014 | Edition No. 10 63 Annexes Annex 8: Tea production and exports Production Price Exports Exports value Year Month MT KSh/Kg MT KSh million January 36,205 250 35,382 9,145 February 18,412 245 37,656 9,123 March 17,859 251 31,280 9,415 April 18,118 256 26,816 7,804 May 37,383 264 25,060 6,445 June 30,197 279 29,148 7,770 2012 July 24,306 288 28,054 7,813 August 31,920 288 30,996 8,798 September 33,549 280 30,689 8,771 October 40,235 272 33,167 9,448 November 39,977 277 38,681 10,840 December 41,401 281 30,067 8,463 January 45,390 284 40,190 11,383 February 38,503 271 34,585 10,071 March 33,368 241 32,534 8,619 April 38,230 210 33,662 8,012 May 39,600 215 40,936 9,463 June 30,530 209 37,783 8,515 2013 July 26,229 212 43,761 9,911 August 26,338 208 36,175 8,236 September 32,800 191 34,082 7,635 October 44,283 174 33,532 6,977 November 35,463 187 40,054 7,834 December 41,719 212 38,741 7,991 January 44,970 236 38,652 8,784 2014 February 33,774 203 33,514 7,317 March 33,336 187 37,642 7,938 Source: Kenya National Bureau of Statistics. 64 June 2014 | Edition No. 10 Annexes Annex 9: Coffee production and exports Production Price Exports Exports value Year Month MT KSh/Kg MT KSh million January 4,770 544 3,094 1,454 February 6,505 369 3,668 1,937 March 3,317 389 5,069 2,550 April 4,801 342 4,625 2,369 May 5,472 303 4,924 2,275 June 3,884 258 4,887 2,098 2012 July 3,086 298 5,727 2,397 August 3,948 277 4,484 1,712 September 4,474 265 4,421 1,596 October 2,924 263 4,482 1,690 November 1,794 272 4,110 1,453 December 1,075 308 2,223 740 January 3,938 344 2,790 1,062 February 4,825 320 3,955 1,429 March 4,074 327 3,179 1,188 April 6,038 279 3,986 1,362 May 4,482 230 5,164 1,790 June 2,307 207 5,238 1,778 2013 July 830 251 4,652 1,556 August 3,411 297 4,741 1,409 September 2,442 286 4,802 1,436 October 1,580 239 3,899 1,303 November 1,882 256 3,808 1,153 December 2,133 274 2,675 862 January 2,850 293 3,169 1,055 February 5,382 399 3,078 1,118 2014 March 6,212 456 4,584 1,532 April 6,611 392 Source: Kenya National Bureau of Statistics. June 2014 | Edition No. 10 65 Annexes Annex 10: Horticulture exports Exports Exports value Year Month MT KSh million January 14,974 8,721 February 16,053 6,726 March 18,967 6,515 April 17,408 6,317 May 17,027 6,013 June 15,271 6,227 2012 July 17,349 7,813 August 15,869 5,825 September 16,506 7,567 October 19,708 11,368 November 18,347 7,742 December 18,250 9,036 January 18,398 9,071 February 21,576 9,198 March 19,814 7,061 April 19,790 5,228 May 17,135 5,924 June 15,181 6,996 2013 July 15,193 4,971 August 15,005 6,304 September 17,589 5,036 October 20,292 9,118 November 17,689 7,290 December 16,165 7,182 Source: Kenya National Bureau of Statistics. 66 June 2014 | Edition No. 10 Annexes Annex 11: Local electricity generation by source Hydro Geo-thermal Thermal Total Year Month KWh million KWh million KWh million KWh million January 330 129 169 627 February 332 125 159 616 March 293 134 194 620 April 273 124 175 572 May 323 132 159 615 June 342 129 147 618 2012 July 358 119 168 646 August 348 122 176 645 September 358 119 168 646 October 360 129 166 654 November 372 121 159 652 December 369 130 148 647 January 377 129 169 675 February 333 113 160 606 March 348 135 163 645 April 345 152 140 637 May 377 159 133 668 June 378 162 131 671 2013 July 386 158 157 701 August 377 158 182 717 September 377 153 175 705 October 385 151 211 746 November 358 151 222 731 December 347 161 198 705 January 339 179 226 742 February 270 145 257 673 2014 March 287 171 279 737 April 308 170 240 717 Source: Kenya National Bureau of Statistics June 2014 | Edition No. 10 67 Annexes Annex 12: Soft drinks, sugar, galvanized sheets and cement production Soft drinks Sugar Galvanized sheets Cement Year Month litres (thousands) MT MT MT January 34,317 53,852 22,940 350,615 February 32,009 49,480 19,655 378,453 March 37,363 52,342 21,507 397,009 April 29,331 44,914 20,892 360,540 May 24,359 40,503 22,197 381,026 June 27,391 45,111 17,180 396,951 2012 July 22,073 41,607 21,411 398,458 August 24,458 37,058 23,040 399,873 September 31,113 32,503 23,268 382,141 October 32,540 30,123 20,473 421,579 November 31,497 31,886 21,969 415,866 December 33,067 34,651 21,283 357,212 January 32,756 49,046 25,528 393,921 February 36,014 50,036 22,874 380,032 March 42,499 43,647 26,297 367,673 April 27,450 39,151 26,010 365,579 May 27,851 36,529 23,866 414,161 June 31,362 49,512 26,147 422,519 2013 July 28,909 61,802 25,007 454,288 August 28,143 58,687 27,398 432,938 September 36,474 50,303 25,051 453,542 October 35,258 52,751 27,588 487,594 November 36,777 54,752 26,421 464,834 December 43,534 53,994 22,965 422,048 January 40,443 23,748 449,386 2014 February 41,853 23,985 441,918 March 43,109 445,337 Source: Kenya National Bureau of Statistics 68 June 2014 | Edition No. 10 Annexes Annex 13: Tourism arrivals Year Month JKIA MIA TOTAL January 83,450 28,134 111,584 February 80,405 24,636 105,041 March 75,668 19,965 95,633 April 72,023 7,531 79,554 May 71,287 4,830 76,117 June 90,972 5,934 96,906 2012 July 108,136 12,671 120,807 August 108,869 17,771 126,640 September 90,153 13,312 103,465 October 95,911 12,942 108,853 November 83,122 16,135 99,257 December 92,365 23,290 115,655 January 85,838 26,446 111,984 February 48,970 24,031 73,001 March 52,103 17,850 69,953 April 61,685 6,739 68,424 May 69,751 4,772 74,523 June 91,083 6,692 97,775 2013 July 112,332 11,480 123,812 August 33,749 2,334 57,083 September 83,986 11,721 95,707 October 89,045 12,362 101,407 November 81,242 19,068 100,310 December 103,514 25,159 128,673 January 65,533 19,853 65,388 2014 February 50,270 18,334 68,604 March 76,561 15,041 91,602 Source: Kenya National Bureau of Statistics June 2014 | Edition No. 10 69 Annexes Annex 14: New vehicles registration All body types Year Month (number) January 13,730 February 12,693 March 13,066 April 8,257 May 16,652 June 15,091 2012 July 22,577 August 16,970 September 12,003 October 15,449 November 14,867 December 11,689 January 20,997 February 16,928 March 17,061 April 20,203 May 25,070 June 23,527 2013 July 23,223 August 15,224 September 15,749 October 15,803 November 15,995 December 12,398 January 15,411 February 17,779 2014 March 15,629 April 12,789 Source: Kenya National Bureau of Statistics 70 June 2014 | Edition No. 10 Annexes Annex 15: Exchange rate Year Month USD UK pound Euro January 86.3 133.9 111.4 February 83.2 131.4 110.1 March 82.9 131.2 109.6 April 83.2 133.2 109.6 May 84.4 134.3 108.0 June 84.8 132.0 106.5 2012 July 84.1 131.2 103.5 August 84.1 132.1 104.2 September 84.6 136.3 108.8 October 85.1 136.8 110.3 November 85.6 136.8 109.9 December 86.0 138.8 112.8 January 86.9 138.8 115.5 February 87.4 135.5 116.9 March 85.8 129.4 111.3 April 84.2 128.8 109.6 May 84.1 128.7 109.2 June 85.5 132.4 112.8 2013 July 86.9 131.9 113.7 August 87.5 135.5 116.5 September 87.4 138.5 116.7 October 85.3 137.3 116.3 November 86.1 138.6 116.2 December 86.3 141.4 118.2 January 86.2 142.0 117.5 February 86.3 142.8 117.8 2014 March 86.5 143.8 119.6 April 86.7 145.1 119.8 May 87.4 147.3 120.1 Source: Central Bank of Kenya June 2014 | Edition No. 10 71 Annexes Annex 16: Interest rates Short-term Long -term Interbank 91-Treasury Central Average Savings Overall Interest bill bank rate deposit weighted rate spread Year Month rate lending rate January 19.0 21.0 18.0 7.7 1.6 19.5 11.9 February 18.0 20.0 18.0 8.0 1.7 20.3 12.3 March 24.0 18.0 18.0 8.0 1.7 20.3 12.3 April 16.0 16.0 18.0 9.0 1.6 20.2 11.2 May 17.0 11.0 18.0 8.4 1.6 20.1 11.7 June 17.0 10.0 18.0 7.9 1.5 20.3 12.4 2012 July 13.7 12.0 16.5 8.3 1.7 20.2 11.9 August 9.0 10.9 13.0 7.8 1.6 20.1 12.3 September 7.0 7.8 13.0 7.4 1.6 19.7 12.3 October 9.1 9.0 13.0 6.9 1.6 19.0 12.2 November 7.1 9.8 11.0 6.7 1.6 18.7 12.1 December 5.8 8.3 11.0 6.8 1.6 18.1 11.3 January 5.9 8.1 9.5 6.5 1.7 18.1 11.6 February 9.0 8.4 9.5 6.3 1.6 17.8 11.6 March 8.8 9.9 9.5 6.5 1.4 17.7 11.2 April 7.9 10.4 8.5 6.4 1.5 17.9 11.5 May 7.2 9.5 8.5 6.5 1.5 17.5 10.9 June 7.2 6.2 8.5 6.7 1.7 17.0 10.3 2013 July 8.0 5.9 8.5 6.6 1.6 17.0 10.4 August 9.0 10.0 8.5 6.4 1.7 17.0 10.6 September 7.8 9.6 8.5 6.5 1.6 16.9 10.3 October 10.7 9.7 8.5 6.4 1.6 17.0 10.6 November 10.8 9.9 8.5 6.6 1.6 16.9 10.3 December 9.1 9.5 8.5 6.6 1.6 17.0 10.3 January 10.6 9.3 8.5 6.6 1.6 17.0 10.5 February 9.1 9.2 8.5 6.6 1.5 17.1 10.5 2014 March 6.6 9.0 8.5 6.6 1.6 16.9 10.3 April 7.6 8.8 8.5 6.5 1.5 16.7 10.2 May 7.8 8.8 8.5 Source: World Bank, based on data from Central Bank of Kenya 72 June 2014 | Edition No. 10 Annex 17: Credit to private sector Total Annexes private Manufactur- Building Transport sector Finance and Mining and Private Consumer Business Other Year Month Agriculture ing Trade and con- and com- Real estate annual insurance quarrying households durables services activities struction munication growth rates January February 26.0 21.1 22.2 26.3 65.2 31.1 22.9 39.4 28.3 17.4 19.2 -0.5 40.2 March 24.0 16.6 30.5 24.0 54.4 36.3 28.4 36.7 18.0 17.4 19.9 -5.0 23.7 April 22.6 14.5 29.7 27.4 59.4 25.0 19.3 29.0 37.9 15.7 -7.4 -5.7 47.6 May 21.8 14.3 26.9 25.4 51.8 28.7 17.9 29.7 10.0 13.0 16.3 0.0 25.0 June 16.1 10.1 23.4 21.4 49.9 10.3 10.0 27.8 1.8 7.0 14.7 -5.1 16.2 2012 July 13.5 3.6 19.0 10.5 36.7 -2.9 10.7 26.4 3.3 7.7 13.7 -1.3 27.0 August 11.9 3.9 14.8 7.8 35.2 -2.7 16.2 26.2 -10.4 8.1 12.5 0.5 21.7 September 7.7 0.7 7.3 3.2 27.8 -4.3 20.3 24.8 -13.7 6.0 8.0 0.9 8.8 October 7.1 3.7 3.6 2.8 32.5 -2.6 21.9 22.7 -24.0 5.4 4.5 2.2 11.0 November 9.1 6.7 10.2 4.8 37.0 -10.3 15.4 21.1 -23.8 7.6 6.7 8.2 15.0 December 10.4 8.1 15.8 10.6 36.2 -13.3 9.3 17.9 -0.9 8.2 9.4 7.5 10.8 January 12.0 13.3 16.9 9.0 33.6 -11.3 29.9 16.9 5.2 7.3 9.8 23.1 10.0 February 11.6 8.0 15.1 10.1 22.4 -12.9 -2.6 17.3 8.6 14.0 8.3 24.5 11.0 March 11.2 11.0 12.6 10.2 23.9 -15.3 -9.5 15.8 4.3 11.0 6.7 24.0 19.6 April 10.5 4.2 11.6 7.6 17.5 -12.1 -2.4 13.9 -17.7 16.5 8.2 27.1 16.9 May 9.5 2.0 4.9 7.3 13.2 -13.2 4.2 14.0 -9.8 24.8 7.7 37.4 -0.4 June 12.7 1.9 5.5 10.3 11.1 -7.2 11.0 -1.2 -16.0 27.1 13.5 45.5 34.8 2013 July 13.5 6.5 6.4 11.0 9.6 6.3 -0.8 17.5 -13.4 27.3 13.6 36.0 7.3 August 16.2 3.6 9.6 15.4 11.4 9.8 -3.5 16.9 17.4 26.6 13.3 42.1 10.9 September 17.4 -0.5 6.8 20.3 13.5 13.1 -12.4 14.7 18.8 32.9 18.3 35.5 15.0 October 18.0 -3.1 8.8 24.4 11.8 11.1 -25.2 16.6 19.5 26.5 25.0 41.3 16.7 November 20.0 2.9 13.6 23.2 10.2 14.7 -16.8 18.4 18.5 27.7 24.7 41.3 21.6 December 20.1 2.0 7.3 19.9 2.3 18.1 -8.5 22.5 11.0 29.8 18.1 52.6 27.0 January 20.5 -1.1 12.8 18.6 0.1 23.1 -13.6 23.3 -16.3 35.6 20.2 50.1 24.6 June 2014 | Edition No. 10 2014 February 21.5 3.4 16.8 20.2 5.4 31.2 12.1 24.0 -14.0 30.9 20.4 48.1 15.1 73 Source: Central Bank of Kenya Annexes Annex 18: Money aggregate Growth rates Broad money Money Money Year Reserve money (yoy) supply (M2) (M1) (M0) January 10.6 5.3 13.0 17.2 February 11.2 5.7 12.5 10.4 March 11.5 1.4 13.1 23.2 April 13.0 6.1 8.1 14.7 May 12.5 1.7 10.6 13.2 June 13.1 0.6 6.6 16.7 2012 July 13.9 2.3 3.6 15.6 August 15.0 4.1 5.7 8.4 September 14.3 6.3 5.4 9.7 October 15.8 5.6 3.8 6.7 November 18.1 9.3 7.7 14.0 December 17.2 14.1 7.8 15.1 January 18.2 16.1 11.5 12.2 February 17.0 15.5 17.6 23.9 March 15.8 17.8 16.0 11.5 April 18.5 20.0 13.6 9.5 May 17.8 21.9 14.9 18.9 June 15.6 20.7 16.6 11.7 2013 July 13.9 18.5 15.5 10.3 August 13.8 17.5 15.7 23.8 September 13.0 16.6 12.1 12.1 October 11.3 13.0 13.8 22.7 November 10.9 14.9 13.3 13.3 December 11.1 10.9 10.5 9.2 January 13.7 13.6 10.6 10.3 2014 February 15.0 14.4 5.0 9.9 Source: Central Bank of Kenya 74 June 2014 | Edition No. 10 Annexes Annex 19: Mobile payments Number of Number of Value of Year Month Number of agents customers transactions transactions (Millions) (Millions) (Millions) January 52315 18.8 40.2 114.1 February 53685 18.8 41.8 116.7 March 55726 19.2 45.8 126.1 April 56717 19.5 44.4 117.4 May 59057 19.7 48.0 128.4 June 61313 19.8 47.9 124.0 2012 July 63165 19.6 49.4 129.3 August 64439 19.4 49.7 131.4 September 67301 19.7 48.9 130.7 October 70972 20.0 51.9 137.7 November 75226 20.3 53.6 139.0 December 76912 21.1 56.0 150.2 January 85548 21.4 53.4 142.7 February 88393 21.8 53.5 141.1 March 93211 22.3 52.4 134.4 April 96319 23.0 56.0 142.6 May 100584 23.5 60.3 158.8 June 103165 23.8 60.0 152.5 2013 July 105669 24.3 62.7 162.8 August 108559 23.9 64.7 168.1 September 110432 24.0 63.4 165.6 October 111697 24.4 68.3 175.3 November 112947 24.9 68.7 175.2 December 113130 25.3 69.1 182.5 January 114107 25.8 67.1 178.5 2014 February 115015 26.1 65.6 172.8 Source: Central Bank of Kenya June 2014 | Edition No. 10 75 Annexes Annex 20: Nairobi stock exchange (20 share index) and the Dow Jones (New York) Year Month NSE (1966 = 100) Dow Jones January 3225 12,633 February 3304 12,952 March 3367 13,212 April 3547 13,214 May 3651 12,393 June 3704 12,880 2012 July 3832 13,009 August 3866 13,091 September 3972 13,437 October 4147 13,096 November 4084 13,026 December 4133 13,104 January 4417 13,861 February 4519 14,054 March 4861 14,579 April 4765 14,840 May 5007 15,116 June 4598 14,910 2013 July 4788 15,500 August 4698 14,810 September 4793 15,130 October 4993 15,546 November 5101 16,086 December 4927 16,577 January 4856 15,699 February 4933 16,322 2014 March 4946 16,458 April 4949 16,581 May 4882 16,717 Source: Kenya National Bureau of Statistics 76 June 2014 | Edition No. 10 Annexes Annex 21: Nominal and real exchange rate NEER REER Year Month 2003=100 2003=100 January 119 67 February 116 66 March 115 65 April 115 65 May 115 65 June 115 65 2012 July 114 65 August 114 66 September 116 67 October 117 67 November 117 67 December 118 67 January 119 66 February 119 67 March 116 64 April 114 63 May 113 63 June 115 63 2013 July 116 64 August 117 65 September October 117 64 November 115 63 December 116 63 January 116 63 February 116 62 2014 March 117 62 April 117 62 Source: Central Bank of Kenya June 2014 | Edition No. 10 77 78 Annex 22: Fiscal position Actual (percent of GDP) 2005/06 2006/07 2007/08 2008/09 2009/10 2010/11 2011/12 2012/13 2013/14* Revenue and grants 21.8 22.5 23.3 22.6 25.1 24.6 23.6 24.1 30.0 Total revenue 20.5 21.6 22.0 21.8 23.9 24.0 23.1 23.6 28.1 Tax revenue 18.7 19.7 20.2 20.4 21.9 21.9 21.1 21.6 25.9 Income tax 7.2 7.2 8.0 8.2 8.8 9.3 9.6 10.4 11.4 June 2014 | Edition No. 10 VAT 5.0 5.6 5.7 5.7 6.0 6.2 5.4 5.1 5.7 Import duty 1.4 1.6 1.7 1.6 1.7 1.7 1.6 1.6 2.4 Excise duty 3.3 3.3 3.2 3.1 3.0 2.9 2.4 2.4 2.5 Other revenues 1.8 2.0 1.7 1.7 2.4 1.9 2.0 2.1 3.9 Appropriation-in-aid 1.8 1.9 1.8 1.4 1.9 2.1 2.0 2.0 2.2 Grants 1.3 0.9 1.3 0.8 1.3 0.7 0.5 0.6 2.0 Expenditure and net lending 25.2 24.3 27.3 26.6 29.5 29.1 29.1 30.9 36.6 Recurrent 20.2 17.8 20.6 19.5 20.8 21.3 20.0 22.1 19.7 Wages and salaries 7.4 7.4 7.4 6.9 7.0 7.1 6.7 7.6 7.2 Interest payments 2.7 2.5 2.4 2.3 2.6 2.7 2.5 3.4 3.0 Development and net lending 4.5 4.7 6.7 7.2 8.7 7.9 9.1 8.5 11.2 Deficit (commitment basis) Excluding grants -4.7 -2.7 -5.2 -4.8 -5.7 -5.2 -6.0 -7.3 -8.5 Including grants -3.4 -1.8 -3.9 -4.0 -4.4 -4.5 -5.6 -6.7 -6.6 Financing 2.4 2.1 -0.4 5.2 7.1 4.3 5.4 7.1 6.6 Foreign 0.1 -0.1 0.3 1.8 0.9 1.0 3.5 2.4 5.9 Domestic borrowing 2.3 2.2 -0.7 3.4 6.2 3.2 2.0 4.7 0.6 Public debt to GDP (net) 46.7 42.6 39.5 42.2 44.9 48.3 45.5 47.3 51.8 External debt 28.4 23.3 22.6 24.2 23.2 25.9 23.4 23.0 26.7 Domestic debt 23.6 23.5 21.9 23.3 26.9 27.4 26.0 28.7 29.1 Source: National Treasury, 2014 *Printed estimates Annexes Annex 23: 12-months cumulative balance of payments Annexes 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014* 1. CURRENT ACCOUNT -133 -253 -511 -1034 -1973 -1671 -2512 -3330 -4254 -3405 -3151 Balance of trade -1007 -1397 -2226 -2996 -4260 -3892 -4642 -6440 -6895 -6131 -5881 2. MERCHANDISE ACCOUNT -1906 -2488 -3817 -4936 -6444 -5768 -7169 -9007 -10541 -10503 -10499 2.1 Exports (fob) 2726 3462 3516 4132 5048 4528 5225 5807 6181 5856 5773 Coffee 89 128 138 166 155 201 209 222 269 192 188 Tea 456 561 656 693 924 892 1159 1153 1199 1215 1155 Horticulture 416 433 509 607 763 692 725 678 695 741 747 Manufactured goods 292 350 422 513 625 526 608 729 700 705 653 Other 1473 1990 1792 2153 2580 2216 2525 3026 3318 3003 3029 20 13 -2 2.2 Imports (cif) 4632 5950 7333 9069 11492 10296 12395 14814 16722 16358 16272 Oil 1119 1341 1745 1919 3051 2192 2673 4081 4081 3838 3806 Chemicals 746 833 1004 1156 1446 1324 1603 1947 2076 2279 2316 Manufactured goods 687 779 1065 1435 1589 1411 1774 2250 2302 2624 2577 Machinery and 1119 1783 2252 2800 3063 3065 3808 3686 4748 4600 4539 transport equipment Other 961 1214 1267 1759 2343 2304 2537 2848 3251 2900 2911 3. SERVICES 1773 2234 3306 3902 4470 4097 4657 5676 6286 7097 7348 3.1 Non-factor services 898 1091 1591 1940 2184 1876 2527 2566 3645 4372 4618 3.2 Income account -127 -109 -70 -143 -45 -38 -158 7 -164 -73 -72 3.3 Current transfers account 1001 1253 1785 2106 2331 2259 2288 3103 2804 2798 2802 of which 382 408 574 611 609 642 891 1171 1291 1307 remittances 4. CAPITAL & FINANCIAL 250 560 1186 1888 1505 2451 2675 3288 5515 4090 4375 ACCOUNT 4.1 Capital account 145 188 211 267 294 290 154 235 235 170 152 4.2 Financial account 105 372 975 1621 1210 2161 2522 3053 5280 3920 4223 4.2.1.1 Official, medium and -195 -216 -202 -16 106 466 308 340 1147 1187 589 June 2014 | Edition No. 10 long-term 79 80 4.2.1.2 Private, medium and -20 458 38 592 72 44 176 35 -87 -250 -175 long-term 4.2.1.2.3 Direct -7 -55 -11 438 153 127 106 107 107 254 351 June 2014 | Edition No. 10 investment (FDI) 4.2.1.3 Commercial banks -122 -202 -156 -5 15 494 61 -213 854 49 686 (net) 4.2.2 Short term and net 442 332 1296 1050 1017 1158 1977 2891 3366 3538 3123 errorsand omissions (NEO) Short term (including 443 568 714 1032 995 577 1130 1678 2429 2561 2564 portfolio flows) Net errors and -1 -236 582 18 22 581 847 1213 937 977 559 omissions (NEO) 5. OVERALL BALANCE 117 306 675 854 -469 781 163 -43 1261 685 1223 Memo: Gross reserves 2078 2534 3331 4557 4641 5064 5123 6045 7160 8483 8352 Official 1519 1799 2415 3355 2875 3847 4002 4248 5702 6560 6679 Commercial banks 560 735 916 1202 1765 1217 1121 1797 1458 1923 1673 Imports cover (calender 3.4 3.2 3.5 4.0 2.7 4.1 3.5 3.1 3.8 4.5 4.63 year) Import cover (36 4.1 4.0 3.9 4.8 3.4 4.1 3.9 3.7 4.3 4.6 4.61 months imports) GDP market price (KShs m) 1274328 1415724 1622434 1833511 2107589 2375971 2570334 3047392 3403534 3797988 3987887 GDP market price (US$ m) 15688 19397 23302 28964 27053 30716 32440 34313 40265 44100 46305 Source: Central Bank of Kenya. * Cumulative 12 months to February Annexes Annexes Annex 24: Growth Outlook 2013 2014* 2015* 2016* BASELINE GDP 4.7 4.7 4.7 4.1 Private consumption 6.0 6.6 6.4 6.0 Government consumption 3.5 3.4 3.3 3.2 Gross fixed investment 1.5 8.2 8.0 5.2 Exports of goods and nonfactor services 5.2 6.1 6.8 6.6 Imports of goods and nonfactor services 3.6 9.2 8.0 7.8 HIGH CASE SCENARIO GDP 4.7 4.8 5.0 4.0 Private consumption 6.0 6.6 6.4 5.9 Government consumption 3.5 3.4 3.3 3.1 Gross fixed investment 1.5 8.5 8.8 5 Exports of goods and nonfactor services 5.2 6.1 6.8 6.6 Imports of goods and nonfactor services 3.6 9.0 9.0 7.9 LOW CASE SCENARIO GDP 4.7 4.4 4.4 4.2 Private consumption 6.0 6.6 6.4 6.1 Government consumption 3.5 3.4 3.3 3.2 Gross fixed investment 1.5 6.2 5.0 5 Exports of goods and nonfactor services 5.2 6.1 6.8 6.6 Imports of goods and nonfactor services 3.6 8.5 8.0 7.8 Source: World Bank. * Projections June 2014 | Edition No. 10 81 Take-off Delayed? Kenyan economy facing headwinds in 2014 with a special focus on delivering primary health care services Economic activity remained robust in Kenya in 2013. GDP grew 4.7 percent in 2013, up from 4.6 percent in 2012, supported by strong domestic demand, particularly higher household consumption as well public investment and public consumption. Continued strong macroeconomic management kept inflation down and reduced growth volatility. Growth continued to be constrained by structural bottlenecks, most of them associated with the country’s business environment, and by weak external demand from trading partners. The special focus of this Update identifies some of the challenges facing Kenya’s health system. It examines how reforms have already improved primary care and suggests how Kenya can build on its devolved system of delivering primary health services to achieve the government’s goal of providing universal health coverage. Under Kenya’s new devolved system of government, responsibility for delivering health care services lies with county governments. A series of actions on their part could improve health outcomes, increase the efficiency and effectiveness of the system, and move Kenya toward its goal of achieving universal health coverage. The report has three main messages: First, the economy remains strong despite the headwinds it faces in 2014. Kenya’s record of maintaining macroeconomic stability and adhering to credible policies has underpinned its growth in the past;staying this course will help Kenyaweather the domestic shocks it faces, allowing it to grow at an annual rate of 4.7 percent in 2014 and 2015. Second, addressing the fiscal pressures emerging from fiscal expansion is a priority. Given the reduction in fiscal buffers and the fiscal risks linked to the wage bill and devolution, efficiency gains needs to be achieved. Additional spending should be pursued only if they are necessary and careful attention is given to sustainability. Third, Kenya’s health outcomes are not commensurate with its aspirations of achieving middle income status. More needs to be done to improve these outcomes. Global evidence indicates that the best way to improve health outcomes is to improve primary health care. Doing so involves reallocating some of the health budget away from curative care towards preventive and promotive care. The World Bank Join the conversation! Delta Center Menengai Road, Upper Hill KENYA ECONOMIC UPDATE P. O. Box 30577 – 00100 Nairobi, Kenya @KEconomicUpdate Telephone: +254 20 2936000 Fax: +254 20 2936382 Website: www.worldbank.org/kenya Produced by Poverty Reduction and Economic Management Unit Africa Region Design by Robert Waiharo