Global Poverty Monitoring Technical Note 11 March 2020 PovcalNet Update What’s New Aziz Atamanov, R. Andres Castaneda Aguilar, Tony H. M. J. Fujs, Reno Dewina, Carolina Diaz-Bonilla, Daniel Gerszon Mahler, Dean Jolliffe, Christoph Lakner, Mikhail Matytsin, Jose Montes, Laura L. Moreno Herrera, Rose Mungai, David Newhouse, Minh C. Nguyen, Francisco J. Parada Gomez Urquiza, Ani Rudra Silwal, Diana M. Sanchez Castro, Marta Schoch, David L. Vargas Mogollon, Martha C. Viveros Mendoza, Judy Yang, Nobuo Yoshida and Haoyu Wu March 2020 (Updated January 2021*) Keywords: What’s New; March 2020. Development Data Group Development Research Group Poverty and Equity Global Practice Group GLOBAL POVERTY MONITORING TECHNICAL NOTE 11 Abstract The March 2020 update to PovcalNet involves several changes to the data underlying the global poverty estimates. Some welfare aggregates have been changed for improved harmonization, and some of the CPI, national accounts, and population input data have been revised. This document explains these changes in detail and the reasoning behind them. In addition to the changes listed here, a large number of new country-years have been added, bringing the total number of surveys to more than 1,900. All authors are with the World Bank. Corresponding authors: Christoph Lakner (clakner@worldbank.org) and Minh C. Nguyen (mnguyen3@worldbank.org). The authors are thankful for comments and guidance received from Francisco Ferreira, Haishan Fu, and Carolina Sánchez- Páramo. We would also like to thank the countless Poverty Economists that have provided data and documentation, and patiently answered our questions. Without them the database of household surveys that underpins the World Bank’s global poverty measures would not exist. This note has been cleared by Berk Ozler. *January 2021 update: • The table in Section 7.2 has been corrected. The previous version of the document stated that data for Somalia 2017 had been added. This is not the case. The Global Poverty Monitoring Technical Note Series publishes short papers that document methodological aspects of the World Bank’s global poverty estimates. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Global Poverty Monitoring Technical Notes are available at http://iresearch.worldbank.org/PovcalNet/. Contents 1. Introduction ............................................................................................................................. 2 2. Changes to the welfare aggregates .......................................................................................... 5 2.1. Brazil 2012-2015 ............................................................................................................ 5 2.2. Brazil 2016-2017 ............................................................................................................ 7 2.3. Chile 2006-2017.............................................................................................................. 8 2.4. Honduras 2016 ................................................................................................................ 9 2.5. LIS................................................................................................................................... 9 2.6. Mexico 2016 ................................................................................................................. 10 2.7. Papua New Guinea 1996 ............................................................................................... 10 2.8. EU-SILC ....................................................................................................................... 11 2.9. Uruguay 2000-2017 ...................................................................................................... 11 3. Changes to CPI data .............................................................................................................. 13 4. Changes to National Accounts Data ..................................................................................... 13 5. Comparability database ......................................................................................................... 13 6. Methods for estimating the error from advancing the line-up year ...................................... 14 7. Economy-years added/removed ............................................................................................ 16 7.1. Economy-years removed .............................................................................................. 16 Lesotho 2010 ......................................................................................................................... 16 7.2. Economy-years added ................................................................................................... 16 8. References ............................................................................................................................. 19 9. Appendix 1 – CPI Data sources ............................................................................................ 20 10. Appendix 2 – National Accounts Data Sources ................................................................ 37 1 1. Introduction The March 2020 global poverty update from the World Bank presents new poverty estimates for the reference year 2018, and revises the previously published global and regional estimates from 1981 to 2015. The update includes new surveys that have been received and processed, as well as several changes to the existing data. Some changes reflect improvements in the welfare aggregate based on new harmonization efforts and more available information. This document outlines the changes made to the underlying data by country, and explains the reasons why the changes have been made. Table 1 shows the poverty estimates in 2018 for those regions that have sufficient population coverage. The data available at the time of the March 2020 update do not offer sufficient population coverage in 2018 for South Asia and Sub-Saharan Africa, so we are unable to publish regional poverty estimates for these two regions.1 Furthermore, since these regions account for most of the global poor in recent years, we are also unable to provide a global poverty estimate at this time. As further survey data in these two regions become available, we will update PovcalNet such that we can provide a global poverty estimate in the upcoming Poverty and Shared Prosperity report (to be published in the Autumn of 2020). Table 1. Poverty estimates for reference year 2018, different poverty lines $1.90 $3.20 $5.50 Survey Head- Num- Head- Num- Head- Num- Region coverage count ber of count ber of count ber of (%) ratio poor ratio poor ratio poor (%) (mil) (%) (mil) (%) (mil) East Asia and Pacific 91.9 1.3 28 7.6 159 25.6 532 Europe and Central Asia 87.5 1.2 6 4.5 22 12.1 60 Latin America and the Caribbean 86.6 4.4 28 10.4 66 24.2 154 Middle East and North Africa 50.9 7.2 28 19.8 77 44.8 174 Other High-Income Economies 71.2 0.7 7 0.8 9 1.3 14 South Asia 21.8 n/a n/a n/a n/a n/a n/a Sub-Saharan Africa 36.4 n/a n/a n/a n/a n/a n/a World Total 61.5 n/a n/a n/a n/a n/a n/a Source: PovcalNet 1 Survey coverage is assessed within a two-year window either side of 2018, i.e. including surveys that were conducted between 2016 and 2020 (also see Chen et al., 2018). The estimates for South Asia and Sub-Saharan Africa are not displayed since these regions have a survey coverage less than 40%. 2 East Asia and Pacific has continued on its downward trend, reducing the poverty headcount ratio at the international poverty line from 2.3% in 2015 to 1.3% in 2018, driven by decreases in poverty in China and the Philippines.2 In contrast, spurred by the conflicts in Yemen and Syria, the Middle East and North Africa region has seen a sharp reversal, with the poverty rate increasing from around 2.4% in 2011-2013 to 3.8% in 2015 and 7.2% in in 2018. In Latin America, poverty has largely stagnated, increasing slightly from 4.1% in 2015 to 4.4% in 2018, partially due to an increase in the number of poor in Brazil. Table 2 illustrates the impact of the data updates on global poverty for the reference year 2015. The estimates for 2015 were first published in September 2018, and have since been revised in March 2019 and September 2019. With the new data, the estimate of the global $1.90 headcount ratio increases very slightly, from 9.98% to 10.04% and the number of poor increases from 734 million to 737 million people. This change is largely explained by an increase in the regional poverty estimate for Sub-Saharan Africa, which in turn is explained by the availability of new survey data (e.g. Angola, Sudan and Tanzania etc.). These new surveys improve the precision of the reference year estimates in these countries, which were previously based on extrapolations of earlier surveys. Previously, PovcalNet produced poverty numbers for a new reference year (also referred to as a “line-up year”) with a three-year lag. For example, in 2018, we released global poverty estimates for 2015. There has been a growing interest in timelier poverty estimates to provide a more up-to- date picture of poverty around the world. The main trade-off weighing against improved timeliness is the added imprecision in the lined-up poverty estimates: The closer the line-up year is to the present time, the further we have to extrapolate survey-estimates forward in time. To gauge the relevance of this concern, and determine whether the merits to advancing the line-up by one year outweigh the increase in imprecision, we have tried to quantify the increase in the error we would expect from this. By error we mean the difference between the initially reported global/regional poverty estimates and the “final” poverty estimates once survey data before and after the line-up year have become available (we refer to this as the true estimate, although it is 2 The estimates before 2018 are available in PovcalNet, as well as the R and Stata packages. 3 obviously subject to various errors). The challenge with such an exercise is that we do not yet know the true poverty rate. We used two methods to approximate the increase in the error, as summarized below (section 6). Jointly, the methods suggest that the error in the global poverty headcount rate (at the international poverty line) is likely to increase somewhere in the range of 0- 0.6 percentage points, with 0.15 percentage points being our best guess. We judge this to be small enough to merit advancing the line-up year and are reporting poverty estimates for 2018 with this update. Table 2. Poverty at reference year 2015: Comparison of September 2019 and March 2020 versions $1.90: $1.90: $3.20: $3.20: $5.50: $5.50: Headcount Number of Headcount Number of Headcount Number of ratio (%) poor (mil) ratio (%) poor (mil) ratio (%) poor (mil) Region Sep- Mar- Sep- Mar- Sep- Mar- Sep- Mar- Sep- Mar- Sep- Mar- 19 20 19 20 19 20 19 20 19 20 19 20 East Asia and 2.3 2.3 47 47 12.4 12.5 254 254 34.8 34.9 710 711 Pacific Europe and Central 1.5 1.6 7 8 5.4 5.6 26 27 14.0 14.2 68 69 Asia Latin America and 3.9 4.1 24 25 10.6 10.7 66 66 26.3 26.2 165 162 the Caribbean Middle East and 4.2 3.8 16 14 15.6 15.1 58 55 42.1 41.7 157 154 North Africa Other High-Income 0.7 0.7 7 8 0.9 0.9 10 10 1.5 1.5 16 16 Economies South Asia n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a Sub-Saharan 41.4 42.3 416 420 67.0 68.1 674 676 85.0 86.0 855 853 Africa World Total 10.0 10.0 734 737 26.3 26.4 1936 1937 46.1 46.2 3390 3386 Source: PovcalNet 4 2. Changes to the welfare aggregates 2.1. Brazil 2012-2015 Since 2012, Brazil’s Institute of Geography and Statistics (IBGE) has been undertaking a new survey called the PNAD-Continua (PNADC). Between 2012-2015, the new PNADC was collected in parallel to the traditional PNAD. PNADC incorporates improvements in survey methodology (including improved income questions and larger samples) relative to the PNAD. During this period of overlap, IBGE continued to rely on the PNAD for annual household welfare aggregates and used the quarterly PNADC for employment monitoring. In 2016, the PNAD was discontinued, and IBGE switched to using the income aggregate from the PNADC, without releasing the first four years of PNADC. Until this update, PovcalNet was also using the PNAD from 1981-2015 and the PNADC for 2016-2017. In October 2019, IBGE published the PNADC series for 2012-2018, including the four years that overlap with PNAD. However, the 2012-2015 PNADC data that were released do not contain the variables necessary for imputing the rent of owner-occupiers. While the PNADC is an improvement over the PNAD in terms of survey methodology, the 2012-2015 data were published without dwelling characteristics, home ownership status, or housing rent amount. These are the variables that are used from the Socioeconomic Database for Latin America and the Caribbean (SEDLAC) for the rent imputation model used in other countries of Latin America and the Caribbean (LAC). To create the longest possible time series that is comparable with the new PNADC used from 2016 onwards, the team developed and tested an imputation model that imputes rent into the PNADC for 2012-2015. In brief, the methodology is as follows (further details are available upon request): 1) Adjustments are made to the PNAD to construct an income variable that is more comparable with the PNADC. Since 2012, PNADC uses revised definitions of employment and labor income that are in line with the new guidelines published by the ILO. 5 2) The distribution of imputed rent is calculated in the PNAD for each year 2012 through 2015.3 Distributions are estimated separately for rural and urban populations. 3) Based on the distributions of non-zero household per capita income without rent [ ], 2,000 bins are generated for rural areas and 4,000 bins for urban areas. For both rural and urban areas, one additional bin is generated that includes households with zero income. For each bin, the PNAD is used to estimate the average imputed rent for home owners and the percent of households who are homeowners (where refers to urban or rural, and is the number of the bin). 4) Homeownership and average imputed rent are then allocated to households observed in PNADC, such that each bin matches the and observed in PNAD. The allocation of homeownership is based on the results of a probit model run for each year, separately for urban and rural households.4 Based on this model, households with the highest likelihood of being homeowners are allocated home ownership and receive the average imputed rent among homeowners in that bin. The final welfare aggregate is defined as ̃ = + [1 ] where 1 takes the value 1 if the household is allocated home ownership and 0 otherwise. 5) This methodology was validated through two tests. First, we applied the methodology to the PNAD for which we can compare the original rent imputation methodology and this bin-imputation approach. Key poverty and inequality indicators are very close under the two approaches. Second, a cross-validation technique was used to test whether the model is properly imputing rent. The first validation relies on an “in sample” test, which is vulnerable to overfitting, especially as the number of bins increases. For the second test, the PNAD was divided into two samples: the training sample and the test sample.5 The 3 In the case of Brazil, the value of rent for homeowners is estimated using a quantile regression model. This is described in Atamanov et al. (2018). 4 The variables used are household head’s years of schooling, age, and gender; household composition (number of children in the household, number of household members, and whether a spouse is present), and state fixed effects. The probit estimator was used separately for models of urban and rural areas. 5 Since the imputation model relies on dividing the data into urban and rural areas, the samples were drawn so as to be balanced over rural and urban areas. 6 training sample was used to estimate the imputed rent for each bin. These values were then imputed into the test sample, and this sample was used to estimate the indicators. The results show no evidence of overfitting. The revised data for Brazil uses the PNADC (including the rent imputation as described above) from 2012 to 2015. Poverty headcount $1.90 Poverty headcount $3.20 Gini index year Sept 2019 Mar2020 Sept 2019 Mar 2020 Sept 2019 Mar 2020 2012 3.8 3.8 8.7 9 52.7 53.5 2013 3.8 3.1 8.2 7.9 52.8 52.7 2014 2.8 2.7 6.9 7.1 51.5 52.1 2015 3.4 3.2 8 7.8 51.3 51.9 Note: Table presents poverty and inequality estimates for 2012 – 2015 as reported in this March 2020 release and as reported in our prior release from September 2019. 2.2. Brazil 2016-2017 IBGE released a new version of the 2016 and 2017 datasets in October 2019. The harmonization methodology has remained unchanged. The October 2019 data release changed 1) survey weights for 2012-2018 due to revised population projections, and 2) the identification and treatment of outliers in labor income for 2012-2019. Further details can be found in the technical notes on the IBGE website. In the same release, IBGE also released the 2012-2015 and 2018 datasets for the first time (see above). Poverty headcount $1.90 Poverty headcount $3.20 Gini index year Sept 2019 Mar2020 Sept 2019 Mar 2020 Sept 2019 Mar 2020 2016 4.3 3.9 9.3 8.9 53.7 53.3 2017 4.8 4.5 9.6 9.1 53.3 53.2 Note: Table presents poverty and inequality estimates for 2016 – 2017 as reported in this March 2020 release and as reported in our prior release from September 2019. 7 2.3. Chile 2006-2017 The PovcalNet data for Latin America and the Caribbean are taken from the Socio-Economic Database for Latin America and the Caribbean (SEDLAC). SEDLAC has been developed by the Center for Distributional, Labor and Social Studies (CEDLAS) of the Universidad Nacional de La Plata in Argentina, in partnership with World Bank’s Poverty and Equity Group’s Latin America team. A process of methodological and technical revisions to the SEDLAC project started in 2015, to address several issues presented by users during the preceding five years. Additional changes were made to better align the SEDLAC data with the household survey harmonized by the World Bank for other regions. These revisions of the welfare aggregate represent a move from version 02 of the SEDLAC project, to version 03. For most countries in the region, PovcalNet moved from version 02 to version 03 as part of the April 2018 update. With this update, we are also implementing version 03 for Chile from 2006 onwards. The estimates in 2003 and earlier still use version 02, and are therefore not comparable to the series beginning in 2006. Three specific changes were made to the welfare aggregate for Chile: First, the methodology used for imputing the rental value of owner-occupied housing was improved. It now includes households with a dwelling that has been received as a gift and those that live in usufruct, ceded dwellings. This change has led to increases in incomes for these types of households. The revision to the imputed rent methodology explains most of the change in the Chile series. Second, the new series includes imputations for missing labor incomes, which has become more important due to rising non-response rates over the period. The imputed labor income variable has recently become available in the raw data, and the methodological details will soon become publicly available (to be published by the NSO on their website). Third, the Chilean authorities have released more detailed variables. These variables allowed 1) the exclusion of the scaling up of individual incomes and rents to match National Accounts. 2) improved checks on the elements being included in the income aggregate (this revealed a case of inadvertent double counting in 2015, which led to a small error being corrected). 8 Poverty headcount $1.90 Poverty headcount $3.20 Gini index Year Sept 2019 Mar 2020 Sept 2019 Mar 2020 Sept 2019 Mar 2020 2006 2.4 1.5 7.4 5.5 48.2 47.3 2009 2.6 1.3 6.7 4.1 49.0 47.0 2011 1.6 0.6 4.7 2.6 47.6 46.1 2013 0.9 0.4 2.6 1.4 47.3 45.8 2015 1.3 0.3 3.1 1.1 47.7 44.4 2017 0.7 0.3 1.8 0.7 46.6 44.4 Note: Table presents poverty and inequality estimates for 2006 – 2017 as reported in this March 2020 release and as reported in our prior release from September 2019. 2.4. Honduras 2016 Weights were adjusted according to population projections based on the 2013 Census. This ensures comparability of the 2016 data with the 2014, 2015, 2017 and 2018 surveys. Poverty headcount $1.90 Poverty headcount $3.20 Gini index Year Sept 2019 Mar 2020 Sept 2019 Mar 2020 Sept 2019 Mar 2020 2016 16.0 18.0 30.0 32.9 50.1 51.1 Note: Table presents poverty and inequality estimates for 2016 as reported in this March 2020 release and as reported in our prior release from September 2019. 2.5. LIS We continue to use the Luxembourg Income Study (LIS) for the following seven economies6: Australia, Canada, Germany, Israel, Japan, South Korea, and United States. With this update we have also added data for Taiwan, China. For the countries that use EU-SILC in recent years (typically from the early 2000s), we have added LIS data in the earlier years. This improves the population coverage of our database in the 1980s and 1990s, especially for the economies in the “Other High Income” group. These new data, however, introduce a break in comparability, usually in the early 2000s, when we switch from LIS to EU-SILC. Users should bear this in mind when analyzing country trends, and they are advised 6 The term country, used interchangeably with economy, does not imply political independence but refers to any territory for which authorities report separate social or economic statistics. 9 to use the comparability database that is released together with the global poverty data (see Atamanov et al. 2019, blog, data and Section 5 below). The comparability database accounts for the break between LIS and EU-SILC. More generally, for all LIS surveys, we have added a break whenever the name of the underlying survey changes, given limited information on comparability in the LIS documentation. All LIS data have been downloaded on 6 February 2020. As before, we use disposable income per capita from the LIS data in the form of 400 bins (see Chen et al., 2018 for more details). 2.6. Mexico 2016 Four households in the surveys were classified as non-coherent households due an inconsistency of the income variables, that was not identified previously. These households have very high incomes, so removing them lowers the Gini index considerably, while the poverty measures remain unchanged. Poverty headcount $1.90 Poverty headcount $3.20 Gini index Year Sept 2019 Mar 2020 Sept 2019 Mar 2020 Sept 2019 Mar 2020 2016 2.2 2.2 7.9 7.9 48.3 46.3 Note: Table presents poverty and inequality estimates for 2016 as reported in this March 2020 release and as reported in our prior release from September 2019. 2.7. Papua New Guinea 1996 The previous version of the Papua New Guinea 1996 data included duplicate households. This has now been corrected. Poverty headcount $1.90 Poverty headcount $3.20 Gini index Year Sept 2019 Mar 2020 Sept 2019 Mar 2020 Sept 2019 Mar 2020 1996 53.2 51.0 70.8 73.6 55.4 45.8 Note: Table presents poverty and inequality estimates for 1996 as reported in this March 2020 release and as reported in our prior release from September 2019. 10 2.8. EU-SILC All historical EU-SILC data have been updated to data released in December 2019. The updates for each country-year are documented on the Eurostat website [CIRCABC → Eurostat → EU - SILC →Library → data_dissemination → udb_user_database]. Previous versions of PovcalNet used 400 bins generated from the EU-SILC microdata (similar to how the LIS data are being used, see Chen et al., 2018 for more details). With this update, we are using the full EU-SILC microdata. Pending further research on harmonizing the treatment of negative incomes across our database, we exclude households with negative incomes. In contrast, the World Bank’s Poverty and Equity Portal, as well as its Shared Prosperity Database, include negatives. This can explain some of the differences in the estimates presented in the different databases. 2.9. Uruguay 2000-2017 The thirteenth salary (or Christmas bonus, aguinaldo in Spanish) is now included correctly in the income variable. In the previous version, this component of labor income was included only for individuals interviewed in July and January. In the revised version, it is included for individuals interviewed at any point during the survey. 11 Poverty headcount $1.9 Poverty headcount $3.2 Gini index Year Sept 2019 Mar 2020 Sept 2019 Mar 2020 Sept 2019 Mar 2020 2001 0.4 0.4 2.5 2.4 44.96 44.94 2002 0.5 0.5 3.3 3.1 45.47 45.49 2003 0.7 0.7 4.5 4.3 44.98 44.99 2004 0.8 0.7 5.7 5.6 45.85 45.83 2005 0.7 0.7 4.7 4.6 44.69 44.69 2006 0.5 0.4 3.7 3.5 45.95 45.91 2007 0.3 0.3 2.9 2.9 46.43 46.38 2008 0.2 0.2 1.8 1.7 45.15 45.06 2009 0.2 0.2 1.8 1.7 45.61 45.52 2010 0.1 0.1 1.3 1.3 44.54 44.45 2011 0.1 0.1 1.0 0.9 42.20 42.15 2012 0.1 0.1 1.1 1.0 39.93 39.89 2013 0.2 0.2 0.8 0.8 40.53 40.44 2014 0.1 0.1 0.7 0.7 40.15 40.10 2015 0.1 0.1 0.6 0.6 40.16 40.12 2016 0.1 0.1 0.5 0.5 39.72 39.69 2017 0.1 0.1 0.4 0.4 39.50 39.46 Note: Table presents poverty and inequality estimates for 2001-2017 as reported in this March 2020 release and as reported in our prior release from September 2019. 12 3. Changes to CPI data The baseline source of CPI data has been updated to the IMF’s International Financial Statistics (IFS) as of 4 November 2019. Lakner et al. (2018) provide an overview of the various CPI series that are used in PovcalNet. Table A.1 in the Appendix to this note gives the up-to-date source of the deflator for all countries included in PovcalNet as of the current update. 4. Changes to National Accounts Data The national accounts data used to adjust survey data to reference years have been updated. Methodological details and choice of data sources are available in Prydz et al. (2019). The primary series is national accounts data from WDI February 2020, supplemented with historical data from the Madison Project Database. A full overview of national accounts data used in the update, including special series, is available in Appendix 2. 5. Comparability database Since September 2019, we provide metadata on comparability of poverty estimates within countries over time. The assessment of comparability is country-dependent and relies on the accumulation of knowledge from past and current Bank staff in the countries, as well as close dialogue with national data producers with knowledge of survey design and methodology (see Atamanov et al. 2019, for more information on reasons that break comparability). With this data update, we have also revised the comparability database. Changes in the comparability database arise from the introduction of new years in the database or the revision of previously published data (as documented above). For example, the revision of the Chile series introduces a break in 2006. The introduction of LIS data for the countries that use EU-SILC in later years, also introduces a new break for these countries. As described above, the comparability database accounts for the break between LIS and EU-SILC. More generally, for all LIS surveys, we have added a break whenever the name of the underlying survey changes, given limited information on comparability in the LIS documentation. 13 The updated comparability database can be accessed here: https://datacatalog.worldbank.org/dataset/comparability-over-time-country-level-international- poverty-measures More information on how to use the database is available in Atamanov et al. (2019), this blog and this replication code. 6. Methods for estimating the error from advancing the line-up year As summarized in the Introduction, we use two methods to assess the added imprecision to the global poverty estimates from advancing the line-up year by one year. The first method tries to estimate what the impact of advancing the line-up year by one year would have been if we had done so in the past. Suppose we are in March 2010 and decide whether to use 2007 or 2008 as the line-up year. We can estimate what our estimate of global poverty for 2008 would have been in 2010 by neglecting all data after 2008, which arguably would not have been processed and be ready for a March 2010 update. Next, we can compare that to our current 2008 global estimate of poverty. This will reveal how far off our initial estimate was from the final estimate (which for simplicity we refer to as the “true” estimate here). We can do the same for 2007 and then derive how much the error would have increased if we had reported 2008 poverty numbers rather than 2007 in 2010. We can repeat this exercise for other years. In some years, advancing the line-up year by one year would have increased the error in the global poverty rate by 0.6 percentage points, equivalent to about 3.5% of the actual poverty estimate. Other years it would hardly have mattered. The increased error mostly comes from South Asia and Sub-Saharan Africa, where advancing the line-up year by one year would have increased the error in the regional poverty rates by up to 2 percentage points. The second method gets around the problem that we do not know the difference between the initially reported lined-up estimate and the true estimate by trying to predict these differences for each country. We do so in the following way. For all past surveys in PovcalNet, we take the observed poverty rate and calculate the poverty rate using PovcalNet’s extrapolation method supposing the survey had not been present. The error is the absolute difference between the two. We can use this to get a sense of what has determined the country-level line-up errors in the past. 14 We use a random forest model to predict the errors as a function of the extrapolation time, the poverty rate, mean consumption, the Gini, GDP per capita, whether income/consumption is used, the region, the growth rate between the two surveys, and whether the two surveys are comparable. The poverty rate of the country as well as the extrapolation time between the two surveys matter the most for the error in lined-up poverty rates. We can use the model to predict the error in the lined-up poverty rate for each country for each line-up year under consideration. For example, the model predicts that the absolute difference between the true poverty rate and the extrapolated poverty rate for Namibia is 2.0 percentage points if 2017 is the line-up year and 2.4 percentage points if 2018 is the line-up year. By taking the population weighted average by region and globally we can estimate the impact of increasing the line-up year from 2017 to 2018. Doing so suggests that changing the line-up year from 2017 to 2018 increases the error in the poverty headcount ratio (at the international poverty line) by about 0.15 percentage points globally, and by about 0.3 percentage points in South Asia and Sub-Saharan Africa. 15 7. Economy-years added/removed 7.1. Economy-years removed Lesotho 2010 The data collection of the 2010-11 wave of the CMS/HBS faced several challenges concerning missing values in core consumption items. As an interim solution, a survey-to-survey imputation exercise was carried out to impute household expenditures and estimate poverty in 2010, utilizing the 2002-03 wave of the HBS. For several years, the imputed consumption aggregate has been used in PovcalNet. Since full consumption data were collected in 2017/18 (CMS/HBS 2017/18), the 2010 imputed data have been removed. 7.2. Economy-years added The table below gives the list of new economy-years added to the PovcalNet database. Two new economies have also been added for the first time: Taiwan, China and United Arab Emirates. Economy Years Survey Name Albania 2014-2017 HBS Angola 2018 IDREA Argentina 2018 EPHC Armenia 2018 ILCS Austria 1987, 1994, 1995, 1997, 2000 LIS Austria 2016, 2017 EU-SILC Belarus 2018 HHS Belgium 1985, 1988, 1992, 1995, 1997, 2000 LIS Belgium 2016, 2017 EU-SILC Bolivia 2018 EH Brazil 2018 PNADC Bulgaria 2016, 2017 EU-SILC Canada 1971,1975 LIS Cape Verde 2015 IDRF Colombia 2018 GEIH Costa Rica 2018 ENAHO Croatia 2016, 2017 EU-SILC Cyprus 2016, 2017 EU-SILC Czech Republic 1992, 2002 LIS Czech Republic 2016, 2017 EU-SILC Denmark 1987, 1992, 1995, 2000 LIS Denmark 2016, 2017 EU-SILC Dominican Republic 2017, 2018 ECNFT Ecuador 2018 ENEMDU Egypt 2017 HIECS El Salvador 2018 EHPM 16 Estonia 2016, 2017 EU-SILC Eswatini 2016 HIES Finland 1987, 1991, 1995, 2000 LIS Finland 2016, 2017 EU-SILC France 1978, 1984, 1989, 1994, 2000 LIS France 2016, 2017 EU-SILC Georgia 2018 HIS Germany 1973, 1978, 1981, 1983,1984, 1987, 1989, 2016 LIS Greece 1995, 2000 LIS Greece 2016, 2017 EU-SILC Honduras 2018 EPHPM Hungary 1991, 1994 LIS Hungary 2016, 2017 EU-SILC Iran, Islamic Republic 2017 HEIS of Ireland 1987, 1994, 1995, 1996, 2000 LIS Ireland 2016 EU-SILC Iceland 2015 EU-SILC Italy 1986, 1987, 1989, 1991, 1993, 1995, 1998, 2000 LIS Italy 2016, 2017 EU-SILC Japan 2010, 2013 LIS Kyrgyz Republic 2018 KIHS Lesotho 2017 CMSHBS Lithuania 2016, 2017 EU-SILC Luxembourg 1985, 1991, 1994, 1997, 2000 LIS Luxembourg 2016, 2017 EU-SILC Latvia 2016, 2017 EU-SILC Maldives 2016 HIES Malta 2016, 2017 EU-SILC Mauritius 2017 HBS Mexico 2018 ENIGHNS Moldova 2018 HBS Mongolia 2018 HSES Montenegro 2012-2015 SILC-C Myanmar 2017 MLCS Netherlands 1983, 1987, 1990, 1993, 1999 LIS Netherlands 2016, 2017 EU-SILC North Macedonia 2016, 2017 SILC-C Norway 1979, 1986, 1991, 1995, 2000 LIS Norway 2016, 2017 EU-SILC Panama 2018 EH Paraguay 2018 EPH Peru 2018 ENAHO Poland 1986, 1992, 1995 LIS Poland 2017 EU-SILC Portugal 2016, 2017 EU-SILC Romania 1995, 1997 LIS Romania 2017 EU-SILC Russian Federation 2016, 2017, 2018 HBS 17 São Tomé and Principe 2017 IOF Serbia 2016, 2017 SILC-C Serbia 2018 HBS Sierra Leone 2018 SLIHS Slovakia 1992 LIS Slovakia 2016 EU-SILC Slovenia 1997, 1999 LIS Slovenia 2016, 2017 EU-SILC Spain 1980, 1985, 1990, 1995, 2000 LIS Spain 2016, 2017 EU-SILC Sudan 2014 NHBS Sweden 1967, 1975, 1981, 1987, 1992, 1995, 2000 LIS Sweden 2016, 2017 EU-SILC Switzerland 1982, 1992, 2000, 2002 LIS Switzerland 2016, 2017 EU-SILC Taiwan, China 1981, 1986, 1991, 1995, 1997, 2000, 2005, 2007, 2010, LIS 2013, 2016 Tanzania 2017 HBS Thailand 2018 SES Turkey 2017, 2018 HICES Ukraine 2017, 2018 HLCS United Arab Emirates 2014 HIES United Kingdom 1969, 1974, 1979, 1986, 1991, 1994, 1995, 1999 LIS United Kingdom 2016 EU-SILC United States 1974 LIS Uruguay 2018 ECH Vietnam 2018 VHLSS Zimbabwe 2017 PICES 18 8. References Atamanov, Aziz, Joao Pedro Azevedo, R. Andres Castaneda Aguilar, Shaohua Chen, Paul A. Corral Rodas, Reno Dewina, Carolina Diaz-Bonilla, Dean M. Jolliffe, Christoph Lakner, Kihoon Lee, Daniel Gerszon Mahler, Jose Montes, Rose Mungai, Minh C. Nguyen, Espen Beer Prydz, Prem Sangraula, Kinnon Scott, Ayago Esmubancha Wambile, Judy Yang and Qinghua Zhao., “April 2018 Povcalnet update: what’s new”, World Bank Group Global Poverty Monitoring Technical Note, no. 1., April 2018. https://ideas.repec.org/p/wbk/wbgpmt/1.html. Atamanov, Aziz, R. Andres Castaneda Aguilar, Carolina Diaz-Bonilla, Dean Jolliffe, Christoph Lakner, Daniel Gerszon Mahler, Jose Montes, Laura Liliana Moreno Herrera, David Newhouse, Minh C. Nguyen, Espen Beer Prydz, Prem Sangraula, Sharad Alan Tandon and Judy Yang, “ September 2019 PovcalNet Update: what’s new”, World Bank Group Global Poverty Monitoring Technical Note, no. 10., September 2019. https://ideas.repec.org/p/wbk/wbgpmt/10.html Chen, Shaohua, Dean M. Jolliffe, Christoph Lakner, Kihoon Lee, Daniel Gerszon Mahler, Rose Mungai, Minh C. Nguyen, Espen Beer Prydz, Prem Sangraula, Dhiraj Sharma, Judy Yang and Qinghua Zhao., “September 2018 PovcalNet Update: what's new”, World Bank Group Global Poverty Monitoring Technical Note, no. 2., September 2018. https://ideas.repec.org/p/wbk/wbgpmt/2.html. Devadas, Sharmila, Ibrahim Elbadawi, and Norman V. Loayza. 2019. “ Growth After War in Syria.” Policy Research Working Paper Series 8967, The World Bank. https://ideas.repec.org/p/wbk/wbrwps/8967.html. Gobat, J. Jeanne, and Kristina Kostial. 2016. Syria’s Conflict Economy. International Monetary Fund. Working Paper, WP/16/123, June 2016. https://www.imf.org/en/Publications/WP/Issues/2016/12/31/Syrias-Conflict-Economy- 44033 Lakner, Christoph, Daniel Gerszon Mahler, Minh C. Nguyen, Joao Pedro Azevedo, Shaohua Chen, Dean M. Jolliffe, Espen Beer Prydz and Prem Sangraula., "Consumer Price Indices used in Global Poverty Measurement ", World Bank Group Global Poverty Monitoring Technical Note, no. 4., September 2018. https://ideas.repec.org/p/wbk/wbgpmt/4.html. Prydz, Espen Beer, Dean M. Jolliffe, Christoph Lakner, Daniel Gerszon Mahler, and Prem Sangraula. “ National Accounts Data used in Global Poverty Measurement.” Global Poverty Monitoring Technical Note 8. Washington, DC: World Bank. 2019. https://ideas.repec.org/p/wbk/wbgpmt/8.html. 19 9. Appendix 1 – CPI Data sources Table A1.1 lists the source of CPI used for each economy-year reported in PovcalNet. The columns in the table are defined as follows: • Code: The 3-letter economy code used by the World Bank: https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank- countryand-lending-groups • Economy name: Name of economy • Year(s): Welfare reporting year, i.e. the year for which the welfare has been reported. If the survey collects income for the previous year, it is the year prior to the survey. This is identical to the year variable used in PovcalNet. • CPI period: Common time period to which the welfare aggregates in the survey have been deflated. The letter Y denotes that the CPI period is identical to the year column. When the welfare aggregate has been deflated to a particular month within the welfare reporting year, the month is indicated by a number between 1 and 12, preceded by an M, and similarly with a Q for quarters. The letter W indicates that a weighted CPI is used, as described in equation 1 in Lakner et al. (2018). • CPI source: Source of the deflator used. The source is given by the abbreviation, the frequency of the CPI, and the vintage; e.g. IFS-M-201911 denotes the monthly IFS database version November 2019. For economy-specific deflators, the description is given in the text or further details are available upon rfinterequest. 20 Table A1.1. Source of temporal deflator used in PovcalNet Code Economy Name Survey Year(s) CPI period Source HBS 2000 W IFS-M-201911 IBEP-MICS 2008 W IFS-M-201911 AGO Angola IDREA 2018 W IFS-M-201911 EWS 1996 Y IFS-M-201911 2002- LSMS 2012 Y IFS-M-201911 2014- HBS 2017 Y IFS-M-201911 ALB Albania SILC-C 2017 (prev. year)Y IFS-M-201911 ARE United Arab Emirates HIES 2014 W IFS-M-201911 1980- CEDLAS May 25 EPH 1987 Y 18 1991- 2002 M9 NSO 2003- EPHC-S2 2018 M7-M12 NSO 2007- ARG Argentina - urban 2014 M7-M12 Private estimates ARM Armenia ILCS ALL Y IFS-M-201911 HIS-LIS 1981 Y IFS-A-201911 IDS-LIS 1985 Y IFS-A-201911 1989- SIH-LIS 2014 Y IFS-A-201911 2004- AUS Australia SIH-HES-LIS 2010 Y IFS-A-201911 1987- MC-LIS 1995 Y IFS-M-201911 1994- ECHP-LIS 2000 Y IFS-M-201911 2004- AUT Austria EU-SILC 2018 (prev. year)Y IFS-M-201911 ALZ 1995 Y IFS-M-201911 2001- HBS 2005 Y IFS-M-201911 AZE Azerbaijan HSMTSA 2008 Y IFS-M-201911 EDCM 1992 Y IFS-M-201911 EP 1998 W IFS-M-201911 QUIBB 2006 Y IFS-M-201911 BDI Burundi ECVMB 2013 W IFS-M-201911 1985- SEP-LIS 1997 Y IFS-M-201911 PSBH-ECHP- 1995- LIS 2000 Y IFS-M-201911 2004- BEL Belgium EU-SILC 2018 (prev. year)Y IFS-M-201911 21 QUIBB 2003 Y IFS-M-201911 EMICOV 2011 W IFS-M-201911 BEN Benin 2015 Y IFS-M-201911 EP-I 1994 W IFS-M-201911 EP-II 1998 Y IFS-M-201911 2003- ECVM 2009 Y IFS-M-201911 BFA Burkina Faso EMC 2014 Y IFS-M-201911 1983- HHES 1985 W WEO-A-201910 1988- 1991 W IFS-A-201911 1995 W Survey 2000- BGD Bangladesh HIES 2016 Y Survey HBS 1989 Y IFS-A-201911 1992- 1994 Y IFS-M-201911 1995- IHS 2001 Y IFS-M-201911 2003- MTHS 2007 Y IFS-M-201911 2007- BGR Bulgaria EU-SILC 2018 (prev. year)Y IFS-M-201911 2001- LSMS 2004 Y WEO-A-201910 2007- BIH Bosnia and Herzegovina HBS 2015 Y IFS-M-201911 FBS 1988 Y Previous WDI/IFS 1993- 1995 Y IFS-M-201911 1998- BLR Belarus HHS 2018 Y IFS-M-201911 1993- LFS 1999 Y WEO-A-201910 HBS 1995 Y WEO-A-201910 BLZ Belize SLC 1996 Y WEO-A-201910 Bolivia EPF 1990 W IFS-M-201911 Bolivia - urban EIH 1992 M11 IFS-M-201911 ENE 1997 M11 IFS-M-201911 ECH 1999 M10 IFS-M-201911 2000 M11 IFS-M-201911 2001- EH 2005 M11 IFS-M-201911 ECH 2004 M10 IFS-M-201911 2006- BOL Bolivia EH 2016 M10 IFS-M-201911 22 2017- 2018 M11 IFS-M-201911 1981- PNAD 2015 M9 IFS-M-201911 2012- BRA Brazil PNADC-E1 2018 Y IFS-M-201911 BTN Bhutan BLSS ALL Y Previous WDI/IFS 1985- HIES 2002 W IFS-M-201911 CWIS 2009 W IFS-M-201911 BWA Botswana BMTHS 2015 W IFS-M-201911 EPCM 1992 W IFS-M-201911 2003- CAF Central African Republic ECASEB 2008 Y IFS-M-201911 1971- SCF-LIS 1997 Y IFS-M-201911 1998- SLID-LIS 2010 Y IFS-M-201911 CAN Canada CIS-LIS 2013 Y IFS-M-201911 SIWS-LIS 1982 Y IFS-M-201911 NPS-LIS 1992 Y IFS-M-201911 2000- IES-LIS 2002 Y IFS-M-201911 2007- CHE Switzerland EU-SILC 2018 (prev. year)Y IFS-M-201911 CASEN 1987 Y IFS-M-201911 1990- CHL Chile 2017 M11 IFS-M-201911 1981- China - rural CRHS-CUHS 2011 Y Special 1981- China - urban 2011 Y Special 2012- China - rural CNIHS 2016 Y Special 2012- CHN China - urban 2016 Y Special 1985- EPAM 1988 W IFS-M-201911 EP 1992 W IFS-M-201911 1995- CIV Côte d'Ivoire ENV 2015 Y IFS-M-201911 ECAM-I 1996 Y IFS-M-201911 ECAM-II 2001 Y IFS-M-201911 ECAM-III 2007 Y IFS-M-201911 CMR Cameroon ECAM-IV 2014 Y IFS-M-201911 COD Congo, Dem. Rep. E123 ALL W IFS-M-201911 COG Congo, Rep. ECOM ALL Y IFS-M-201911 23 1980- ENH 1988 Y IFS-M-201911 1989- Colombia - urban 1991 M11 IFS-M-201911 1992- 2000 M11 IFS-M-201911 2001- ECH 2005 M11 IFS-M-201911 2008- COL Colombia GEIH 2018 M11 IFS-M-201911 EIM 2004 Y IFS-M-201911 COM Comoros EESIC 2013 Y IFS-M-201911 IDRF 2001 W IFS-M-201911 QUIBB 2007 W IFS-M-201911 CPV Cabo Verde IDRF 2015 Y IFS-M-201911 1981- ENH 1986 Y IFS-M-201911 EHPM 1989 Y IFS-M-201911 1990- 2009 M7 IFS-M-201911 2010- CRI Costa Rica ENAHO 2018 M7 IFS-M-201911 CYP Cyprus EU-SILC ALL (prev. year)Y IFS-M-201911 CM 1988 Y Previous WDI/IFS 1992- MC-LIS 2002 Y IFS-M-201911 CM 1993 Y IFS-M-201911 2005- CZE Czech Republic EU-SILC 2018 (prev. year)Y IFS-M-201911 1973- LIS 1983 Y IFS-M-201911 1981 Y IFS-M-201911 1984- DEU Germany 2016 Y IFS-M-201911 2002- EDAM 2013 Y IFS-M-201911 DJI Djibouti 2017 M5 IFS-M-201911 1987- LM-LIS 2000 Y IFS-M-201911 2004- DNK Denmark EU-SILC 2018 (prev. year)Y IFS-M-201911 1986- ENGSLF 1989 Y IFS-M-201911 ICS 1992 M6 IFS-M-201911 ENFT 1996 M2 IFS-M-201911 DOM Dominican Republic 1997 M4 IFS-M-201911 24 2000- 2016 M9 IFS-M-201911 2017- ECNFT-Q03 2018 Y IFS-M-201911 EDCM 1988 Y IFS-M-201911 ENMNV 1995 Y IFS-M-201911 DZA Algeria ENCNVM 2011 W IFS-M-201911 EPED 1987 Y IFS-M-201911 Ecuador ECV 1994 M6-M10 IFS-M-201911 Ecuador - urban EPED 1995 M11 IFS-M-201911 1998 M6 IFS-M-201911 (prev. year)M10- ECV 1999 M9 IFS-M-201911 EPED 2000 M11 IFS-M-201911 2003- ECU Ecuador ENEMDU 2018 M11 IFS-M-201911 1990- HIECS 2012 W IFS-M-201911 2015 Y IFS-M-201911 EGY Egypt, Arab Rep. 2017 W IFS-M-201911 1980- HBS-LIS 1990 Y IFS-M-201911 1995- ECHP-LIS 2000 Y IFS-M-201911 2004- ESP Spain EU-SILC 2018 (prev. year)Y IFS-M-201911 HIES 1988 Y Previous WDI/IFS 1993- 1998 Y IFS-M-201911 2000- HBS 2004 Y IFS-M-201911 2004- EST Estonia EU-SILC 2018 (prev. year)Y IFS-M-201911 Ethiopia - rural HICES 1981 W IFS-M-201911 1995- 2010 W IFS-M-201911 ETH Ethiopia 2015 M12 IFS-M-201911 1987- IDS-LIS 2000 Y IFS-M-201911 2004- FIN Finland EU-SILC 2018 (prev. year)Y IFS-M-201911 FJI Fiji HIES ALL W IFS-M-201911 1978- HBS-LIS 2000 Y IFS-M-201911 2004- FRA France EU-SILC 2018 (prev. year)Y IFS-M-201911 25 Micronesia, Fed. Sts. - urban CPH 2000 Y IFS-A-201911 2005- FSM Micronesia, Fed. Sts. HIES 2013 Y IFS-A-201911 GAB Gabon EGEP ALL Y IFS-M-201911 1969- FES-LIS 1995 Y IFS-M-201911 1994- FRS-LIS 1999 Y IFS-M-201911 2005- GBR United Kingdom EU-SILC 2017 (prev. year)Y IFS-M-201911 1996- SGH 1997 Y IFS-M-201811 1997- HIS 2004 Y IFS-M-201811 2005- GEO Georgia 2018 Y IFS-M-201911 GLSS-I 1987 W IFS-M-201911 GLSS-II 1988 W IFS-M-201911 GLSS-III 1991 W IFS-M-201911 GLSS-IV 1998 W IFS-M-201911 GLSS-V 2005 W Survey GLSS-VI 2012 W Survey GHA Ghana GLSS-VII 2016 W Survey ESIP 1991 Y WEO-A-201910 EIBC 1994 W WEO-A-201910 EIBEP 2002 W WEO-A-201910 2007- GIN Guinea ELEP 2012 Y IFS-M-201911 HPS 1998 Y IFS-M-201911 HIS 2003 W IFS-M-201911 2010- GMB Gambia, The IHS 2015 W IFS-M-201911 ILJF 1991 Y IFS-M-201911 ICOF 1993 Y IFS-M-201911 ILAP-I 2002 Y IFS-M-201911 GNB Guinea-Bissau ILAP-II 2010 Y IFS-M-201911 1995- ECHP-LIS 2000 Y IFS-M-201911 2004- GRC Greece EU-SILC 2018 (prev. year)Y IFS-M-201911 ENSD 1986 W IFS-M-201911 1989 Y IFS-M-201911 ENIGF 1998 M8 IFS-M-201911 GTM Guatemala ENCOVI 2000 M6-M11 IFS-M-201911 26 2006- 2014 M7 IFS-M-201911 GLSMS 1992 W WEO-A-201910 GUY Guyana 1998 Y IFS-M-201911 Honduras - urban ECSFT 1986 Y IFS-M-201911 EPHPM 1989 Y IFS-M-201911 1990- 1993 M5 IFS-M-201911 1994 M9 IFS-M-201911 1995- HND Honduras 2018 M5 IFS-M-201911 1988- HBS 2010 Y IFS-M-201911 2010- HRV Croatia EU-SILC 2018 (prev. year)Y IFS-M-201911 ECVH 2001 M5 IFS-M-201911 HTI Haiti ECVMAS 2012 M10 IFS-M-201911 1987- HBS 2007 Y IFS-M-201911 1991- HHP-LIS 1994 Y IFS-M-201911 THMS-LIS 1999 Y IFS-M-201911 2005- HUN Hungary EU-SILC 2018 (prev. year)Y IFS-M-201911 1984- SUSENAS 1999 Y IFS-M-201911 2000- 2007 M2 IFS-M-201911 2008- IDN Indonesia 2018 M3 IFS-M-201911 India - rural NSS 1983 Y Special India - urban 1983 Y Special 1987- India - rural NSS-SCH1 2011 W Special 1987- IND India - urban 2011 W Special SIDPUSS-LIS 1987 Y IFS-M-201911 1994- LIS-ECHP-LIS 2000 Y IFS-M-201911 2004- IRL Ireland EU-SILC 2017 (prev. year)Y IFS-M-201911 1986- SECH 1998 Y CBI 2005- IRN Iran, Islamic Rep. HEIS 2017 Y CBI M11-(next IHSES 2006 year)M12 COSIT IRQ Iraq 2012 Y COSIT 27 ISL Iceland EU-SILC ALL (prev. year)Y IFS-M-201911 ISR Israel HES-LIS ALL Y IFS-M-201911 1986- SHIW-LIS 2000 Y IFS-M-201911 2004- ITA Italy EU-SILC 2018 (prev. year)Y IFS-M-201911 SLC 1988 M9 IFS-M-201911 1990- M11-(next 1993 year)M3 IFS-M-201911 1996 M5-M8 IFS-M-201911 1999 M6-M8 IFS-M-201911 2002- JAM Jamaica 2004 M6 IFS-M-201911 HEIS 1986 W IFS-M-201911 1992- 1997 Y IFS-M-201911 2002- JOR Jordan 2010 W IFS-M-201911 JPN Japan JHPS-LIS ALL Y IFS-M-201911 HBS 1988 Y Previous WDI/IFS 1993- 2017 Y IFS-M-201911 KAZ Kazakhstan LSMS 1996 Y IFS-M-201911 WMS-I 1992 Y NSO WMS-II 1994 Y NSO WMS-III 1997 Y NSO 2005- KEN Kenya IHBS 2015 W NSO PMS 1988 Y Previous WDI/IFS HBS 1993 Y Previous WDI/IFS 1998- 2003 Y IFS-M-201911 2004- KGZ Kyrgyz Republic KIHS 2018 Y IFS-M-201911 KHM Cambodia CSES ALL Y IFS-M-201911 KIR Kiribati HIES 2006 Y IFS-M-201911 KOR Korea, Rep. HIES-FHES-LIS ALL Y IFS-M-201911 LECS 1997 W IFS-M-201911 2002- LAO Lao PDR 2012 W Survey LBN Lebanon HBS 2011 (next year)M5 IFS-M-201911 CWIQ 2007 Y IFS-M-201911 2014- LBR Liberia HIES 2016 Y IFS-M-201911 LSMS 1995 Y IFS-M-201911 LCA St. Lucia SLC-HBS 2016 M1 IFS-M-201911 28 LFSS 1985 Y IFS-M-201911 HIES 1990 W IFS-M-201911 SES 1995 W IFS-M-201911 HIES 2002 Y IFS-M-201911 2006- 2012 W IFS-M-201911 LKA Sri Lanka 2016 Y IFS-M-201911 HBS 1986 W WEO-A-201910 NHECS 1994 W WEO-A-201910 HBS 2002 W IFS-M-201911 CMSHBS 2010 Y IFS-M-201911 LSO Lesotho 2017 M8 IFS-M-201911 HBS 1988 Y Previous WDI/IFS 1993- 2008 Y IFS-M-201911 2005- LTU Lithuania EU-SILC 2018 (prev. year)Y IFS-M-201911 1985- PSELL-LIS 1991 Y IFS-M-201911 PSELL-ECHP- 1994- LIS 2000 Y IFS-M-201911 2004- LUX Luxembourg EU-SILC 2018 (prev. year)Y IFS-M-201911 HBS 1988 Y Previous WDI/IFS 1993- 2009 Y IFS-M-201911 2005- LVA Latvia EU-SILC 2018 (prev. year)Y IFS-M-201911 ECDM 1984 W IFS-M-201911 ENCV 1990 W IFS-M-201911 1998- ENNVM 2006 W IFS-M-201911 2000- MAR Morocco ENCDM 2013 W IFS-M-201911 1988- HBS 1992 Y Previous WDI/IFS 1997- MDA Moldova 2018 Y IFS-M-201911 EB 1980 Y IFS-M-201911 EPM 1993 W IFS-M-201911 1997- 2010 Y IFS-M-201911 MDG Madagascar ENSOMD 2012 Y IFS-M-201911 2002- HIES 2009 W IFS-M-201911 MDV Maldives 2016 Y IFS-M-201911 29 1984- ENIGH 2014 M8 IFS-M-201911 2016- MEX Mexico ENIGHNS 2018 M8 IFS-M-201911 1998- HBS 2008 Y IFS-M-201911 2010- MKD North Macedonia SILC-C 2018 (prev. year)Y IFS-M-201911 EMCES 1994 Y IFS-A-201911 EMEP 2001 W IFS-M-201911 ELIM 2006 Y IFS-M-201911 MLI Mali 2009 W IFS-M-201911 MLT Malta EU-SILC ALL (prev. year)Y IFS-M-201911 MPLCS 2015 M1 IFS-M-201911 MMR Myanmar MLCS 2017 Q1 IFS-M-201911 2005- HBS 2014 Y IFS-M-201911 2013- MNE Montenegro SILC-C 2016 (prev. year)Y IFS-M-201911 1995- LSMS 1998 Y IFS-M-201911 LFS 2002 Y IFS-M-201911 LSS 2007 W IFS-M-201911 2010- MNG Mongolia HSES 2018 Y IFS-M-201911 NHS 1996 W WEO-A-201910 IAF 2002 W WEO-A-201910 2008- MOZ Mozambique IOF 2014 W WEO-A-201910 EPCV 1987 Y IFS-M-201911 EP 1993 Y IFS-M-201911 EPCV 1995 W IFS-M-201911 2000- MRT Mauritania 2014 Y IFS-M-201911 HBS 2006 W IFS-M-201911 2012- MUS Mauritius 2017 Y IFS-M-201911 IHS-I 1997 W IFS-M-201911 IHS-II 2004 W Survey IHS-III 2010 W Survey MWI Malawi IHS-IV 2016 M04 Survey 1984- HIS 2007 Y IFS-M-201911 2009 W IFS-M-201911 2012- MYS Malaysia 2014 Y IFS-M-201911 30 2016 W IFS-M-201911 NHIES 1993 W WEO-A-201910 2003- NAM Namibia 2015 W IFS-M-201911 1992- ENBCM 2007 W IFS-M-201911 EPCES 1994 W IFS-M-201911 ENCVM 2005 Y IFS-M-201911 2011- NER Niger ECVMA 2014 Y IFS-M-201911 NCS 1985 W IFS-M-201911 1992- 1996 Y IFS-M-201911 2003- NGA Nigeria LSS 2018 W IFS-M-201911 EMNV 1993 M2 NSO 1998 M6 NSO 2001 M6 IFS-M-201911 2005- 2009 M8 IFS-M-201911 NIC Nicaragua 2014 M8-M10 IFS-M-201911 1983- AVO-LIS 1990 Y IFS-M-201911 1993- SEP-LIS 1999 Y IFS-M-201911 2005- NLD Netherlands EU-SILC 2018 (prev. year)Y IFS-M-201911 1979- IDS-LIS 2000 Y IFS-M-201911 2004- NOR Norway EU-SILC 2018 (prev. year)Y IFS-M-201911 MHBS 1984 W IFS-M-201911 LSS-I 1995 W IFS-M-201911 LSS-II 2003 W IFS-M-201911 NPL Nepal LSS-III 2010 W IFS-M-201911 HIES 1987 Y IFS-M-201911 1990- 1998 W IFS-M-201911 IHS2 1996 W IFS-M-201911 PIHS 2001 W IFS-M-201911 2004- PAK Pakistan PSLM 2015 W IFS-M-201911 1979- EMO 1989 Y IFS-M-201911 1991 M7 IFS-M-201911 1995- PAN Panama EH 2018 M7 IFS-M-201911 31 ENNIV 1985 W IFS-M-201911 1994 Y IFS-M-201911 1997- ENAHO 2002 Q4 IFS-M-201911 2003 M5-M12 IFS-M-201911 2004- PER Peru 2018 Y IFS-M-201911 PHL Philippines FIES ALL Y IFS-M-201911 HIES 1996 Y IFS-A-201911 PNG Papua New Guinea 2009 W IFS-A-201911 1985- HBS 1987 Y IFS-A-201911 HBS-LIS 1986 Y IFS-A-201911 1989- HBS 2016 Y IFS-M-201911 1992- HBS-LIS 1999 Y IFS-M-201911 2005- POL Poland EU-SILC 2018 (prev. year)Y IFS-M-201911 PRT Portugal EU-SILC ALL (prev. year)Y IFS-M-201911 EH 1990 M7 IFS-M-201911 1995 M8-M11 IFS-M-201911 EIH 1997 (next year)M2 IFS-M-201911 EPH 1999 M9 IFS-M-201911 EIH 2001 M3 IFS-M-201911 EPH 2002 M11 IFS-M-201911 2003 M9 IFS-M-201911 2004 M10 IFS-M-201911 2005 M11 IFS-M-201911 2006 M12 IFS-M-201911 2007- 2008 M10 IFS-M-201911 2009 M11 IFS-M-201911 2010- PRY Paraguay 2018 M10 IFS-M-201911 2004- PECS 2011 Y IFS-M-201911 PSE West Bank and Gaza 2016 W IFS-M-201911 HBS 1989 Y Milanovic (1998) MC 1992 Y IFS-M-201911 HIS 1994 Y IFS-M-201911 1995- IHS-LIS 1997 Y IFS-M-201911 1998- ROU Romania IHS 2000 Y IFS-M-201911 32 1999- HBS 2016 Y IFS-M-201911 2007- EU-SILC 2018 (prev. year)Y IFS-M-201911 RLMS 1988 Y Previous WDI/IFS 1993- HBS 2018 Y IFS-M-201911 RUS Russian Federation RLMS 2001 Y IFS-M-201911 ENBCM 1984 W IFS-M-201911 EICV-I 2000 W IFS-M-201911 EICV-II 2005 W IFS-M-201911 EICV-III 2010 (next year)M1 IFS-M-201911 EICV-IV 2013 (next year)M1 IFS-M-201911 RWA Rwanda EICV-V 2016 (next year)M1 IFS-M-201911 NBHS 2009 Y IFS-M-201911 SDN Sudan 2014 M11 IFS-M-201911 EP 1991 W IFS-M-201911 ESAM 1994 W IFS-M-201911 ESAM-II 2001 Y IFS-M-201911 ESPS-I 2005 W IFS-M-201911 SEN Senegal ESPS-II 2011 W IFS-M-201911 SLB Solomon Islands HIES ALL Y IFS-M-201911 HEEAS 1989 W WEO-A-201910 SLIHS 2003 W WEO-A-201910 2011- SLE Sierra Leone 2018 Y IFS-M-201911 EHPM 1989 Y IFS-M-201911 M10-(next 1991 year)M4 IFS-M-201911 1995- 1999 Y IFS-M-201911 2000- 2007 M12 IFS-M-201911 2008- SLV El Salvador 2018 M11 IFS-M-201911 LSMS 2002 Y IFS-M-201911 2003- HBS 2018 Y IFS-M-201911 2013- SRB Serbia EU-SILC 2018 (prev. year)Y IFS-M-201911 SSD South Sudan NBHS 2009 Y IFS-M-201911 IOF 2000 W IFS-M-201911 2010- STP São Tomé and Principe 2017 Y IFS-M-201911 SUR Suriname EHS 1999 Y IFS-M-201911 33 1992- MC-LIS 1996 Y IFS-M-201911 2004- HBS 2009 Y IFS-M-201911 2005- SVK Slovak Republic EU-SILC 2017 (prev. year)Y IFS-M-201911 1987- IES 1993 Y IFS-M-201911 1997- HBS-LIS 1999 Y IFS-M-201911 1998- HBS 2003 Y IFS-M-201911 2005- SVN Slovenia EU-SILC 2018 (prev. year)Y IFS-M-201911 LLS-RD-LIS 1967 Y IFS-M-201911 1975- HIS-LIS 2000 Y IFS-M-201911 2004- SWE Sweden EU-SILC 2018 (prev. year)Y IFS-M-201911 1994- HIES 2000 W IFS-M-201911 2001 Y IFS-M-201911 2009- SWZ Eswatini 2016 W IFS-M-201911 HES 1999 W IFS-M-201911 HBS 2006 W IFS-M-201911 SYC Seychelles 2013 Y IFS-M-201911 SYR Syrian Arab Republic HBS 2004 Y IFS-M-201911 ECOSIT-II 2003 Y IFS-M-201911 TCD Chad ECOSIT-III 2011 Y IFS-M-201911 TGO Togo QUIBB ALL Y IFS-M-201911 THA Thailand SES ALL Y IFS-M-201911 TLSS 1999 Y WEO-A-201910 2003- 2007 Y Survey HBS 2004 Y Survey TLSS 2009 Y IFS-M-201911 TJK Tajikistan HSITAFIEN 2015 Y IFS-M-201911 TKM Turkmenistan LSMS 1998 Y WEO-A-201910 TLSS 2001 Y WEO-A-201910 2007- TLS Timor-Leste TLSLS 2014 Y IFS-M-201911 TON Tonga HIES ALL Y IFS-M-201911 SLC 1988 Y IFS-M-201911 TTO Trinidad and Tobago PHC 1992 Y IFS-M-201911 TUN Tunisia HBCS 1985 Y IFS-A-201911 34 1990 Y IFS-M-201911 1995- LSS 2000 Y IFS-M-201911 2005- NSHBCSL 2015 W IFS-M-201911 TUR Turkey HICES ALL Y IFS-M-201911 TUV Tuvalu HIES 2010 Y WEO-A-201910 TWN Taiwan, China FIDES-LIS ALL Y WEO-A-201910 HBS 1991 W IFS-A-201911 2000 W IFS-M-201911 2007 Y IFS-M-201911 2011- TZA Tanzania 2018 W IFS-M-201911 HBS 1989 Y WEO-A-201910 NIHS 1992 W WEO-A-201910 1996- 1999 W IFS-M-201911 2002- UGA Uganda UNHS 2016 W IFS-M-201911 HS 1988 Y Previous WDI/IFS 1992- 1993 Y IFS-M-201911 1995- HIES 1996 Y IFS-M-201911 HBS 1999 Y IFS-M-201911 2002- UKR Ukraine HLCS 2018 Y IFS-M-201911 1981- Uruguay ENH 1989 Y IFS-M-201911 1992- Uruguay - urban ECH 2005 (prev. year)M12 IFS-M-201911 2006- URY Uruguay 2018 (prev. year)M12 IFS-M-201911 1974- CPS-LIS 2000 Y IFS-M-201911 2004- USA United States CPS-ASEC-LIS 2016 Y IFS-M-201911 UZB Uzbekistan HBS ALL Y WEO-A-201910 1981- EHM 1989 Y NSO 1992- VEN Venezuela, RB 2006 M12 NSO VLSS 1992 W WEO-A-201910 1998 W IFS-M-201911 2002- VNM Vietnam VHLSS 2018 M1 IFS-M-201911 VUT Vanuatu HIES 2010 Y IFS-A-201911 35 2002- HIES 2008 Y IFS-M-201911 WSM Samoa 2013 W IFS-M-201911 XKX Kosovo HBS ALL Y IFS-M-201911 HBS 1998 Y IFS-M-201911 2005 W IFS-M-201911 YEM Yemen, Rep. 2014 Y IFS-M-201911 KIDS 1993 Y IFS-M-201911 HIES 1996 Y IFS-M-201911 2000 W IFS-M-201911 2005- IES 2010 (next year)M6 IFS-M-201911 LCS 2008 W IFS-M-201911 ZAF South Africa 2014 (next year)M6 IFS-M-201911 1991- HBS 1993 Y IFS-M-201911 LCMS-I 1996 Y IFS-M-201911 LCMS-II 1998 Y IFS-M-201911 LCMSIII 2002 W IFS-M-201911 LCMS-IV 2004 W IFS-M-201911 LCMS-V 2006 W IFS-M-201911 LCMS-VI 2010 Y IFS-M-201911 ZMB Zambia LCMS-VII 2015 Y IFS-M-201911 ICES 2011 Y IFS-M-201911 ZWE Zimbabwe PICES 2017 Y IFS-M-201911 36 10.Appendix 2 – National Accounts Data Sources This appendix provides details of national accounts data used in aligning estimates to reference years (see Prydz et al, 2019 for methodological details). The primary source of national accounts data in this update is the February 2020 version of the World Development Indicators. For historical data this is supplemented with the Madison Project Database (MDP), 2018 version, for years prior to 2000. In addition, the following special economy series are used: • Angola: GDP data for the year 2019 is used from WEO October 2019, since they are not available in WDI. • Djibouti: GDP data from May 2018 WDI is used from 1990 to 2015. From 1987 to 1989, September 2006 WDI is used. From 2016 to 2018, the IMF’s World Economic Outlook (WEO) October 2019 is used. • India 2011-2015: As before, the reference year estimates for India from 2012 to 2015 are based on a method which adjusts HFCE growth by incorporating findings of a poverty imputation for 2014.5. Growth rates in national accounts are adjusted to match the results from the poverty imputation. The method is described in greater detail in Chen et al (2018) and Newhouse and Vyas (2018). • Iran: GDP from February 2020 WDI is used until 2017. For 2018, WEO October 2019 is used. • Liberia: GDP from October 2019 WDI is used from 2001 to 2018. For the earlier years, November 2018 WDI is used. • South Sudan: GDP from December 2017 WDI is used until 2015. From 2016 onwards, WEO October 2019 is used. • Syrian Arab Republic: The GDP series for the Syrian Arab Republic has been revised and updated to 2018. The availability of growth estimates in a conflict setting such as Syria is scarce, so we are forced to combine several sources: WDI June 2016 is used up to 2007. It is then linked with growth rates (in real per capita GDP) based on the WEO October 2019 (2008-2010), Gobat and Kostial (2016) (2011-2015) and Devadas et al. (2019) (2016- 2018). • Taiwan, China: GDP from WEO October 2019 is used. 37 A complete overview is available in Table A2.1 (GDP per capita) and Table A2. 2 (HFCE per capita). Legend Tables A2.1 and A2.2 Code – World Bank economy/country code Sources (See beginning of Appendix for details) Cov – Coverage M – Madison Project Dataset N – National W – World Development Indicators, U – Urban February 2020 R – Rural S – Special Country Series 38 Table A2.1. Gross Domestic Product (GDP) per capita GDP Coverage 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Code AGO N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ALB N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ARE N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ARG N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ARM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W AUS N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W AUT N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W AZE N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BDI N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BEL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BEN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BFA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BGD N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BGR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BIH N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BLR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BLZ N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BOL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BRA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BTN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BWA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CAF N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CAN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CHE N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CHL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CHN R W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CHN U W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CIV N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CMR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W COD N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W COG N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W COL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W COM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CPV N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CRI N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CYP N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CZE N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W DEU N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W DJI N W W W W W W S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S DNK N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W DOM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W DZA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ECU N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W EGY N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ESP N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W EST N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ETH N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W FIN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W FJI N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W 39 FRA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W FSM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GAB N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GBR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GEO N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GHA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GIN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GMB N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GNB N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GRC N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GTM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GUY N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W HND N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W HRV N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W HTI N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W HUN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W IDN R W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W IDN U W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W IND R W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W IND U W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W IRL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W IRN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W S IRQ N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ISL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ISR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ITA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W JAM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W JOR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W JPN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W KAZ N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W KEN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W KGZ N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W KHM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W KIR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W KOR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W LAO N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W LBN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W LBR N S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S LCA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W LKA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W LSO N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W LTU N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W LUX N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W LVA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MAR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MDA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MDG N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MDV N W W W W W W W W W W W W W W W W W W W W W W W W MEX N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MKD N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MLI N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MLT N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MMR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MNE N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MNG N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MOZ N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W 40 MRT N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MUS N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MWI N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MYS N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W NAM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W NER N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W NGA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W NIC N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W NLD N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W NOR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W NPL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PAK N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PAN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PER N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PHL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PNG N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W POL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PRT N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PRY N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PSE N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ROU N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W RUS N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W RWA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SDN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SEN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SLB N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SLE N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SLV N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SRB N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SSD N S S S S S S S S S S S STP N W W W W W W W W W W W W W W W W W W SUR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SVK N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SVN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SWE N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SWZ N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SYC N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SYR N S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S TCD N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W TGO N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W THA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W TJK N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W TKM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W TLS N W W W W W W W W W W W W W W W W W W W TON N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W TTO N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W TUN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W TUR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W TUV N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W TWN N S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S TZA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W UGA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W UKR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W URY N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W USA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W UZB N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W 41 VEN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W VNM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W VUT N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W WSM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W XKX N W W W W W W W W W W W W W W W W W W W YEM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ZAF N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ZMB N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ZWE N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W 42 Table A2.2. Household Final Consumption Expenditures (HFCE) per capita HFCE Code Coverage 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 AGO N W W W W W W W W W W W W W W W W ALB N W W W W W W W W W W W W W W W W W W W ARE N W W W W W W W W W W W W W W W W W W ARG N W W W W W W W W W W W W W W W W W W W W W W W W W W ARM N W W W W W W W W W W W W W W W W W W W W W W W W W AUS N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W AUT N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W AZE N W W W W W W W W W W W W W W W W W W W W W BDI N W W W W W W W W W W W W W W W W W W W W W W BEL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BEN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BFA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BGD N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BGR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BIH N W W W W W W W W W W W W W BLR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BLZ N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BOL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BRA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W BTN N W W W W W W W W W W W W W W W W W W W BWA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CAF N W W W W W W W W W W CAN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CHE N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CHL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CHN R W W W W W W W W W W W W W W W W W W W W W W W W CHN U W W W W W W W W W W W W W W W W W W W W W W W W CIV N W W W W W W W W W W W CMR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W COD N W W W W W W W W W W W W W W W W W W W W W W W W W W COG N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W COL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W COM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CPV N W W W W W W W W W W W W CRI N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CYP N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W CZE N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W DEU N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W DJI N DNK N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W DOM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W DZA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ECU N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W EGY N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ESP N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W EST N W W W W W W W W W W W W W W W W W W W W W W W W W W ETH N FIN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W FJI N 43 FRA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W FSM N GAB N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GBR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GEO N W W W W W W W W GHA N W W W W W W W W W W W W W GIN N W W W W W W W W W W W W W GMB N W W W W W W W W W W W W W W W GNB N W W W W W W W W W W W W W W W W W W W GRC N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GTM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W GUY N W W W W W W W W W HND N W W W W W W W W W W W W W W W W W W W HRV N W W W W W W W W W W W W W W W W W W W W W W W W HTI N W W W W W W W W W HUN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W IDN R W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W IDN U W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W IND R W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W S S S S S S S IND U W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W S S S S S S S IRL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W IRN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W IRQ N W ISL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ISR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ITA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W JAM N W W W W W W W W W W W W JOR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W JPN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W KAZ N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W KEN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W KGZ N W W W W W W W W W W W W W W W W W W W W W W W W W W KHM N W W W W W W W W W W W W W W W W W W W W W W W W W W KIR N KOR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W LAO N W W W W W W W W W W W W W W W W W LBN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W LBR N S S S S S S S S S S S S S S S S S LCA N W LKA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W LSO N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W LTU N W W W W W W W W W W W W W W W W W W W W W W W W LUX N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W LVA N W W W W W W W W W W W W W W W W W W W W W W W W MAR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MDA N W W W W W W W W W W W W W W W W W W W W W W W W MDG N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MDV N MEX N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MKD N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MLI N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MLT N W W W W W W W W W W W W W W W W W W W MMR N W MNE N W W W W W W W W W W W W W MNG N W W W W W W W W W MOZ N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W 44 MRT N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MUS N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W MWI N W W W W W W W W W W W W W W W W MYS N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W NAM N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W NER N W W W W W W W W W W W W W NGA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W NIC N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W NLD N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W NOR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W NPL N W W W W W W W W W W W W W W W W W W PAK N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PAN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PER N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PHL N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PNG N POL N W W W W W W W W W W W W W W W W W W W W W W W W PRT N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PRY N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W PSE N W W W W W W W W W W W W W W W W W W W W W W W W W ROU N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W RUS N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W RWA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SDN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SEN N SLB N SLE N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SLV N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SRB N W W W W W W W W W W W W W W W W W W W W W W W W SSD N S S S S S S S S STP N SUR N W SVK N W W W W W W W W W W W W W W W W W W W W W W W W W W SVN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SWE N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SWZ N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W SYC N W SYR N TCD N W W W W W W W W W W W W TGO N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W THA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W TJK N W W W W W W W W W W W W W W W W W W W W W TKM N W TLS N W W W W W W W W W W W W W W W W W W TON N W TTO N TUN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W TUR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W TUV N TWN N TZA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W UGA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W UKR N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W URY N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W USA N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W UZB N W W W W W W W W W 45 VEN N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W VNM N W W W W W W W W W W W W W W W W W W W W W W W W W VUT N W W W W W W W W W W W WSM N XKX N W W W W W W W W W W W W W YEM N ZAF N W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W ZMB N W ZWE N W W W W W W W W W W HFCE 46