Connecting 2018 to Compete Trade Logistics in the Global Economy The Logistics Performance Index and Its Indicators LPI score, 2012–18 (1 is the lowest score; 5 is the highest score) Connecting to Compete 2018 Trade Logistics in the Global Economy The Logistics Performance Index and Its Indicators Jean-François Arvis The World Bank Lauri Ojala Turku School of Economics, University of Turku Christina Wiederer The World Bank Ben Shepherd Developing Trade Consultants Anasuya Raj The World Bank Karlygash Dairabayeva The World Bank Tuomas Kiiski Turku School of Economics, University of Turku © 2018 The International Bank for Reconstruction and Development/The World Bank 1818 H Street NW Washington, DC 20433 Telephone: 202–473–1000 Internet: www.worldbank.org E-mail: feedback@worldbank.org All rights reserved The findings, interpretations, and conclusions expressed herein are those of the authors and do not necessarily reflect the views of the Executive Directors of the International Bank for Reconstruc- tion and Development/The World Bank or the governments they represent. 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All other queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202–522–2422; e-mail: pubrights@worldbank.org. If you have any questions or comments about this report, please contact: Global Trade and Regional Integration Unit The World Bank Group 1818 H Street NW, Mailstop MC3-300, Washington, DC 20433 USA E-mail: lpi@worldbank.org Web site: www.worldbank.org, www.worldbank.org/trade, or www.lpi.worldbank.org The report was designed, edited, and typeset by Communications Development Incorporated, Washington, DC. Foreword Caroline Freund, Director, Macroeconomics, Trade and Investment Global Practice, The World Bank Group José Luis Irigoyen, Senior Director, Transport and Digital Development Global Practice, The World Bank Group We are happy to present the sixth edition of The exercise may seem a bit repetitive. The Connecting to Compete and the 2018 edition list of best performers does not change very of the Logistics Performance Index (LPI). much over the course of two years. We invite This interdisciplinary World Bank project was the reader to look beyond country rankings and launched just over 10 years ago. The ambition look at the nexus of themes and policies. The lo- was to develop simple comparators of how effi- gistics sector is changing fast, in terms of the ciently supply chains connect firms to markets, nature of demand (for example, e-commerce), or logistics performance. players, use of technology, new risks (cyberse- Since 2007, most of the countries the curity), and policy concerns. Professionals and World Bank Group works with are well aware countries are increasingly concerned with the of the importance of logistics performance for environmental footprint and resilience of sup- growth and integration. The cross-­ cutting na- ply chains. ture of logistics as a policy area is widely rec- We hope this work will appeal to a broad ognized: logistics is not just about connecting and diverse audience: policy makers, practitio- infrastructure but encompasses regulation of ners, and researchers. We are confident readers services, sustainability, and resilience, or trade will find this report and its data useful. facilitation. We see that this regular publication has had Caroline Freund a significant impact in helping countries frame Director their own policies and motivate consistent ap- Macroeconomics, Trade and Investment proaches to interventions and reforms at the Global Practice national level. In some cases, the World Bank The World Bank Group has been asked to provide support, which we did by bringing expertise and tools that address the José Luis Irigoyen country-specific supply chain constraints more Senior Director deeply than the rough indications from the LPI Transport and Digital Development can. The LPI remains unique in providing a Global Practice common referential across countries. The World Bank Group C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y iii Foreword Young Tae Kim, Secretary-General, International Transport Forum at the Organisation for Economic Co-operation and Development Logistics is an elevated priority for many mem- tracing­—­ point to policy actions that can sup- ber countries of the International Transport port the improvement of each individual ele- Forum. Because facilitating trade and trans- ment. International Transport Forum studies port is at the core of stimulating economic have examined the drivers of logistics perfor- development, several countries have developed mance and assessed the development of national comprehensive national logistics strategies. logistics observatories in Chile, Mexico, Turkey, Well-­f unctioning domestic and international and more recently Vietnam. logistics is a precondition of national competi- The LPI is a crucial part of global efforts to tiveness. And fact-based metrics can provide better understand logistics performance in the reliable benchmarks, assess policy impacts, and context of increasingly complex supply chains. compare global advances in logistics. I am sure the 2018 edition of the LPI will be The World Bank Logistics Performance used extensively by governments, international Index (LPI) is a unique benchmarking tool, organizations, private firms, and academia in ef- providing the same measure for more than forts to improve logistics­—­the backbone of the 160 countries. At the International Transport global economy. Forum, we use the LPI as the most important starting point of dialogue with our member Young Tae Kim countries on the drivers of logistics performance. Secretary-General The six components of the LPI­—­customs, infra- International Transport Forum at the structure, ease of arranging shipments, quality Organisation for Economic Co-operation of logistics services, timeliness, and tracking and and Development iv C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Acknowledgements This report was prepared by the World Bank’s (www.fiata.com), especially of Marco Sorgetti, Global Trade and Regional Integration Team FIATA’s former Director General, as well as in the Macroeconomics, Trade and Investment Hans Günther Kersten, FIATA’s current Direc- Global Practice, under the guidance of Car- tor General. National freight forwarding asso- los Felipe Jaramillo (Senior Director), Caro- ciations and a large group of small, medium, and line Freund (Director), and Jose Guilherme large logistics companies worldwide were instru- Reis (Practice Manager). The project leaders mental in disseminating the survey. The survey were Jean-François Arvis (jarvis1@worldbank was designed with Finland’s Turku School of .org) and Christina Wiederer (cwiederer@ Economics, University of Turku (www.utu.fi/ worldbank­ .org). The other authors included en), which has worked with the World Bank to Professor Lauri Ojala (Turku School of Eco- develop the concept since 2007. nomics, University of Turku; lauri.ojala@utu The authors are also grateful to external .fi), Ben Shepherd (Principal, Developing colleagues for their support and contributions Trade Consultants; ben@developing-trade in reaching out to forwarding associations and .com), Anasuya Raj (anasuya.raj14@gmail providing inputs for the report, including Ruth .com), Karlygash Dairabayeva (kdairabayeva@­ Banomyong (Thammasat University, Thai- worldbank.org), and Tuomas Kiiski (tmmkii@ land), Tapio Naula (Oman Logistics Center), utu.fi). and Cesar Lavalle (ILOS Brazil). Daniel Cra- The authors thank Michele Ruta and Luis mer of BlueTundra.com designed, developed, Blancas, the peer reviewers of the report, and and maintained the LPI survey and result other colleagues at the World Bank who pro- websites under the guidance of the core team. vided guidance and inputs to the 2018 edition, Scott Johnson from the World Bank Informa- including Cordula Rastogi, Daniel Saslavsky, tion Solutions Group helped the team distribute Fannie Delavelle, Stéphane Hallegatte, An- the survey. drew Burns, and Inès Zabalbeitia Mugica. As The authors thank the hundreds of employ- in previous years, a team at Communications ees of freight forwarding and express carrier Development­—­led by Bruce Ross-Larson­—­ companies around the world who responded to designed, edited, and typeset the report. the survey. Their participation was central to the The Logistics Performance Index (LPI) sur- quality and credibility of the project, and their vey would not have been possible without the continuing feedback will be essential as we de- support and participation of the International velop and refine the survey and the LPI in years Federation of Freight Forwarders Associations to come. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y v Table of contents Foreword by Caroline Freund and José Luis Irigoyen    iii Foreword by Young Tae Kim    iv Acknowledgments   v Aggregate LPI ranking and scores, 2012–18    x Summary and key findings    1 1. The 2018 Logistics Performance Index    7 Guidelines on how to use the LPI and how to interpret it    8 Features of the 2018 survey    10 Key findings of the 2018 international Logistics Performance Index    10 Logistics performance is strongly correlated with the quality of service    14 Logistics performance is more than income    15 Trends over the past four reports    16 Weighted international LPI scores and ranks 2012–18    16 2. Unbundling logistics performance    19 Infrastructure: A shared concern across performance groups    19 Developing logistics services markets    20 Streamlining border procedures and facilitating trade.    21 Supply chain reliability: A key concern for all countries    27 Logistics trends, reform implementation, and the Logistics Performance 3.  Index   31 The LPI: Stimulating and informing reforms    31 Shifting priorities   31 Managing the complexity of implementation    36 Notes   39  ggregated international LPI results across four editions: 2012, 2014, Appendix 1. A 2016, and 2018   40 Appendix 2. International LPI results for 2018, with bounds     45 Appendix 3. Domestic LPI results, by region and income group    49 Appendix 4. Domestic LPI results, time and distance data    53 Appendix 5. The LPI methodology    59 Appendix 6. Respondent demographics    63 Appendix 7. LPI usage reference list    65 C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y vii References   68 Boxes 1.1 The six components of the international Logistics Performance Index    8 1.2 How precise are LPI scores and ranks?    9 1.3 Logistics performance boosts trade integration, but by just how much?    11 3.1 Use of the LPI in research and policy-making literature    32 3.2 Assessing logistics skills, competencies, and training: A new toolkit    35 3.3 Logistics policy making in Oman    37 Figures S.1 LPI score as a percentage of the best performer, 2012–18    2 S.2 Respondents reporting that shipments are “often” or “nearly always” cleared and delivered as scheduled, by LPI quintile   3 S.3 Cybersecurity threats and preparedness by income    4 1.1 Cumulative distribution of LPI scores, 2018    13 1.2 LPI components score, by LPI quintile, 2018    14 1.3 Change in LPI component score by income group, 2016–18    15 1.4 LPI overperformers and underperformers    16 1.5 LPI score as a percentage of the best performer, 2012–18    16 1.6 Weighted aggregate international LPI score, 2012–18    18 2.1 Respondents rating the quality of trade and transport infrastructure as “improved” or “much improved” since 2015, by LPI quintile   20 2.2 Respondents rating the quality of each infrastructure type as “high” or “very high,” by LPI quintile, 2014–18    20 2.3 Respondents rating the quality of each infrastructure service type as “high” or “very high,” bottom LPI quintile, 2014–18   22 2.4 Median import time and average clearance time, by LPI quintile    23 2.5 Median export lead time, by LPI quintile    24 2.6 Median export lead time, by income group    24 2.7 Respondents rating the quality and competence of quality and inspection agencies as “high” or “very high,” by LPI quintile, 2014–18   25 2.8 Respondents rating the quality and competence of health and sanitary/phytosanitary agencies as “high” or “very high,” by LPI quintile, 2014–18   26 2.9 Red tape affecting import and export transactions, by LPI quintile    26 2.10 Respondents reporting that shipments are “often” or “nearly always” cleared and delivered as scheduled, by LPI quintile   28 2.11 Respondents reporting that shipments are “often” or “nearly always” cleared and delivered as scheduled, by World Bank developing country region   29 2.12 Shipments not meeting company quality criteria, by LPI quintile    29 3.1 Increased use of electronic trading platforms (business to business and business to consumer) by shippers mean that our business volumes have…   33 3.2 Cybersecurity threats in logistics have…    34 3.3 Our firm’s preparedness for cyberthreats has…    34 3.4 The demand for green logistics    34 A6.1 Composition of respondents, by income group    63 A6.2 Composition of respondents, by region    63 viii C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Tables S.1 Top 10 average and lowest 10 average LPI scores, 2007–18    2 1.1 Top 10 LPI economies, 2018    11 1.2 Bottom 10 LPI economies, 2018    11 1.3 Top-performing upper-middle-income economies, 2018    12 1.4 Top-performing lower-middle-income economies, 2018    12 1.5 Top-performing low-income economies, 2018    12 1.6 Deviation on each component from the overall LPI score, by quintile    14 1.7 Respondents reporting an “improved” or “much improved” logistics environment since 2015, by LPI quintile    15 2.1 Respondents rating the quality of each infrastructure type “high” or “very high,” by LPI quintile    19 2.2 Respondents rating the quality of each infrastructure type “high” or “very high,” by World Bank developing country region   21 2.3 Respondents rating the quality and competence of each service provider type “high” or “very high,” by LPI quintile 21 2.4 Difference between respondents rating services “high” or “very high” and those rating infrastructure “high” or “very high,” by World Bank developing country region     22 2.5 Respondents indicating that listed customs procedures are available and being used, by LPI quintile    23 2.6 Respondents rating the quality and competence of three border agencies as “high” or “very high,” by LPI quintile    25 2.7 Respondents reporting that shipments are “often” or “nearly always” delayed, by delay category and LPI quintile    27 3.1 Interaction of LPI performance quintile and logistics priorities    38 A5.1 Methodology for selecting country groups for survey respondents    59 A5.2 Results of principal component analysis for the International LPI 2018    60 A5.3 Component loadings for the International LPI 2018    60 C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y ix Aggregate LPI ranking and scores, 2012–18 This year’s edition of Connecting to Compete features the aggregated 2012–18 results. The methodology is included in appendix 1. The 2018 single-year results can be found in appendix 2. Mean LPI % of Mean LPI % of Mean LPI % of Mean score, highest Mean score, highest Mean score, highest Economy rank 2012–18 performer Economy rank 2012–18 performer Economy rank 2012–18 performer Germany 1 4.19 100.0 Bulgaria 57 3.00 71.7 Moldova 113 2.52 60.1 Netherlands 2 4.07 97.2 Botswana* 58 2.96 70.7 Comoros 114 2.51 60.1 Sweden 3 4.07 97.2 Kuwait 59 2.96 70.6 Guatemala 115 2.51 59.9 Belgium 4 4.05 96.9 Egypt, Arab Rep. 60 2.95 70.5 Armenia 116 2.51 59.9 Singapore 5 4.05 96.6 Malta 61 2.94 70.3 Uzbekistan 117 2.50 59.7 United Kingdom 6 4.01 95.7 Argentina 62 2.93 70.0 Zambia* 118 2.49 59.4 Japan 7 3.99 95.3 Kenya 63 2.93 69.9 Togo 119 2.48 59.4 Austria 8 3.99 95.2 Philippines 64 2.91 69.6 Lao PDR 120 2.48 59.2 Hong Kong SAR, China 9 3.96 94.6 Rwanda 65 2.90 69.3 Nepal 121 2.45 58.6 United States 10 3.92 93.7 Côte d'Ivoire 66 2.89 69.0 Guyana 122 2.45 58.6 Denmark 11 3.92 93.6 Tanzania* 67 2.88 68.8 Azerbaijan* 123 2.45 58.5 Finland 12 3.92 93.5 Serbia 68 2.83 67.7 Georgia 124 2.45 58.5 Switzerland 13 3.91 93.4 Ukraine 69 2.83 67.5 Cameroon 125 2.43 58.1 United Arab Emirates 14 3.89 92.8 Ecuador 70 2.82 67.4 Djibouti 126 2.43 58.1 France 15 3.86 92.2 Colombia 71 2.81 67.1 Trinidad and Tobago* 127 2.41 57.5 Luxembourg 16 3.84 91.8 Uganda* 72 2.79 66.7 Guinea-Bissau 128 2.40 57.4 Canada 17 3.81 90.9 Brunei Darussalam* 73 2.78 66.5 Mongolia 129 2.40 57.3 Spain 18 3.78 90.3 Peru 74 2.78 66.5 Sudan 130 2.40 57.3 Australia 19 3.77 90.0 Uruguay 75 2.78 66.4 Ethiopia* 131 2.40 57.2 Norway 20 3.74 89.3 Jordan 76 2.78 66.3 Kyrgyz Republic 132 2.38 57.0 Italy 21 3.73 89.2 Kazakhstan 77 2.77 66.2 Congo, Rep. 133 2.38 56.7 New Zealand 22 3.68 88.0 Bosnia and Herzegovina 78 2.76 65.8 Fiji 134 2.37 56.7 Korea, Rep. 23 3.65 87.3 Costa Rica 79 2.74 65.4 Venezuela, RB 135 2.37 56.5 Taiwan, China 24 3.65 87.2 Namibia* 80 2.73 65.1 Bolivia 136 2.36 56.5 Ireland 25 3.63 86.8 Iran, Islamic Rep.* 81 2.71 64.8 Madagascar 137 2.35 56.1 Czech Republic 26 3.62 86.4 Lebanon 82 2.71 64.7 Gambia, The* 138 2.34 56.0 China 27 3.60 86.1 Paraguay 83 2.70 64.6 Myanmar 139 2.34 55.9 Portugal 28 3.56 85.1 Malawi* 84 2.69 64.3 Chad 140 2.34 55.9 South Africa 29 3.51 83.8 Russian Federation 85 2.69 64.2 Senegal 141 2.34 55.8 Qatar 30 3.50 83.7 Dominican Republic 86 2.68 64.1 Turkmenistan* 142 2.34 55.8 Poland 31 3.50 83.5 Morocco* 87 2.67 63.8 Congo, Dem. Rep. 143 2.33 55.6 Hungary 32 3.41 81.5 El Salvador 88 2.66 63.6 Papua New Guinea 144 2.31 55.2 Israel* 33 3.39 81.0 Cambodia 89 2.66 63.5 Guinea 145 2.30 54.9 Thailand 34 3.36 80.2 Bahamas, The 90 2.65 63.3 Liberia 146 2.29 54.7 Malaysia 35 3.34 79.9 Mauritius* 91 2.65 63.3 Tajikistan 147 2.29 54.6 Estonia 36 3.30 78.8 Sri Lanka* 92 2.65 63.2 Niger 148 2.29 54.6 Turkey 37 3.29 78.6 Benin 93 2.65 63.2 Yemen, Rep.* 149 2.27 54.3 Iceland 38 3.29 78.6 Montenegro 94 2.65 63.2 Central African Republic* 150 2.26 54.0 Slovenia 39 3.29 78.5 Pakistan 95 2.64 62.9 Bhutan 151 2.25 53.7 Chile 40 3.28 78.4 Burkina Faso 96 2.63 62.9 Cuba 152 2.23 53.4 Panama 41 3.26 77.8 Maldives 97 2.63 62.8 Lesotho 153 2.22 53.0 India 42 3.22 77.0 Albania* 98 2.62 62.5 Burundi 154 2.22 53.0 Lithuania 43 3.20 76.4 Macedonia, FYR 99 2.62 62.5 Libya 155 2.21 52.9 Greece 44 3.19 76.2 Bangladesh* 100 2.60 62.0 Equatorial Guinea* 156 2.21 52.7 Vietnam 45 3.16 75.5 Ghana 101 2.60 62.0 Mauritania 157 2.20 52.5 Oman 46 3.16 75.5 Mozambique* 102 2.59 61.9 Gabon 158 2.19 52.3 Slovak Republic 47 3.14 75.0 Nigeria 103 2.59 61.8 Iraq 159 2.18 52.2 Croatia 48 3.12 74.4 Tunisia 104 2.59 61.8 Angola 160 2.18 52.1 Cyprus 49 3.10 74.0 São Tomé and Principe 105 2.56 61.3 Zimbabwe 161 2.17 51.8 Romania 50 3.10 74.0 Honduras 106 2.56 61.2 Eritrea 162 2.11 50.4 Indonesia 51 3.08 73.6 Algeria 107 2.56 61.1 Syrian Arab Republic 163 2.10 50.2 Saudi Arabia 52 3.08 73.6 Nicaragua* 108 2.56 61.0 Sierra Leone* 164 2.06 49.3 Mexico 53 3.08 73.6 Mali* 109 2.55 60.9 Afghanistan 165 2.04 48.7 Bahrain 54 3.06 73.2 Belarus 110 2.54 60.6 Haiti 166 2.02 48.3 Latvia 55 3.02 72.3 Jamaica 111 2.52 60.3 Somalia* 167 2.00 47.7 Brazil 56 3.02 72.1 Solomon Islands 112 2.52 60.2 * Countries with missing values for one or two editions. For details, see appendix 1. x C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Summary and key findings This sixth edition of Connecting to Compete, Logistics performance matters the Logistics Performance Index (LPI) report, presents the latest worldwide view on trade Not surprisingly, an effective logistics sector logistics performance across more than 160 is now recognized almost everywhere as one countries as seen by logistics professionals. This of the core enablers of development. Previous biennial information on logistics infrastructure, editions of Connecting to Compete have high- service provision, cross-border trade facilitation, lighted how implementing better policies leads and other aspects is invaluable for policy to better logistics performance. Such policies makers, traders, and a wide audience of other cover, for example, regulating services; provid- stakeholders, including researchers and teachers. ing transportation infrastructure; implement- The LPI survey data provide numerical ing controls, especially for international goods; evidence on how easy or difficult it is in these and raising the quality of public–private part- countries to transport general merchandise­ —­ nerships (PPPs). typically manufactured products in unitized The policy focus has evolved since 2007, form. The six main indicators of the interna- when the first LPI report was published. Ini- tional part of the LPI summarize on a five-point tially, logistics policies tended to concentrate scale the assessments of logistics professionals on facilitating trade and removing border bot- worldwide trading with the country. tlenecks. Today, international logistics is in- The domestic part of the LPI indicates the creasingly intertwined with domestic logistics. quality and availability of key logistics services Policy makers and stakeholders deal with a wide within a country, but due to the small number range of policies. Growing concerns include of responses, these data are more informative in spatial planning; skills and resources for train- comparisons by region or income group. ing; the environmental, social, and economic Logistics is understood as a network of sustainability of the supply chain; and the resil- services that support the physical movement ience of the supply chain to disruption or disas- of goods, trade across borders, and commerce ter (physical or digital). within borders. It comprises an array of activities beyond transportation, including warehousing, Gaps in logistics brokerage, express delivery, terminal operations, performance persist and related data and information management. The global turnover generated by these net- Overall, the score profile of the entire set of works exceeds US$4.3 trillion, so a better under- more than 160 countries has remained simi- standing of their operation is no trivial issue.1 lar since the 2007 edition, an indication of the For individual countries, logistics performance robust nature of underlying data.2 The modest is key to economic growth and competitiveness. convergence of scores from 2007 to 2014 was Inefficient logistics raises the cost of doing busi- explained in the 2014 edition by a perceived ness and reduces the potential for both interna- improvement in the trade-supporting infra- tional and domestic integration. The toll can be structure of low- and middle-income countries particularly heavy for developing countries try- and, to less extent, in their logistics services ing to compete in the global marketplace. and customs and border management. This C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 1 Countries that have explanation appeared largely valid for most Figure S.1 LPI score as a percentage of the traditionally dominated countries being ranked. In 2016, however, the highest score by quintile average, gap seemed to widen between the top and the 2012, 2014, 2016, and 2018 the supply chain industry bottom, with the highest average scores ever for Percent 2012 2014 2016 2018 occupy the top 10 rankings: the top 10 countries (4.13 on a scale from 1 to 5) 90 eight in Europe plus and the lowest scores since 2007 for countries at the bottom (1.91; table S.1). 80 Japan and Singapore In 2018, the gap between top and bot- 70 tom performers narrowed again. The average score for the top 10 countries dropped to 4.03, 60 whereas the bottom 10 countries scored an all- time high of 2.08 (figure S.1). 50 High-income countries occupied the top 10 rankings in 2018,3 eight in Europe plus Japan 40 and Singapore­ —­ countries that have tradition- ally dominated the supply chain industry. Ger- 30 Bottom Fourth Third Second Top many is at the top, scoring 4.20. The scores of quintile quintile quintile quintile quintile the following nine countries are in a tight inter- Source: Logistics Performance Index 2012, 2014, 2016, and 2018. val, with Sweden in 2nd with a score of 4.05 and Finland in 10th with a score of 3.97. The bottom 10 countries are mostly low- marginally, with China (26th with a score of income and lower-middle-income countries in 3.61), Thailand (32nd with a score of 3.41), and Africa or isolated areas. Some are fragile econo- South Africa (33rd with a score of 3.38) leading mies affected by armed conflict, natural disas- the group. Romania, Croatia, and Bulgaria also ters, and political unrest. Others are landlocked improved their rankings. Among low-income countries naturally challenged by geography or countries, those in East and West Africa lead in economies of scale in connecting to global sup- this year’s edition. ply chains. Afghanistan ranks 160th with a score 1.95, preceded by Angola (2.05), Burundi Supply chain reliability and service (2.06), and Niger (2.07). quality are strongly associated Among the lower-middle-income countries, with logistics performance large economies such as India (44th with a score of 3.18) and Indonesia (46th with a score of Supply chain reliability is key to logistics per- 3.15) and emerging economies such as Vietnam formance. In a global environment, consignees (39th with a score of 3.27) and Côte d’Ivoire require a high degree of certainty as to when (50th with a score of 3.08) stand out as top per- and how deliveries will take place. Reliability formers. Most of these countries either have ac- is typically much more important than speed, cess to sea or are located close to major trans- and many shippers are willing to pay a premium. portation hubs. In other words, supply chain predictability is a The composition of the top-performing matter not just of time and cost, but also a com- upper-middle-income economies has changed ponent of shipment quality (figure S.2). Table S.1 Top 10 average and lowest 10 average LPI scores, 2007–18 1=lowest; 5=highest 2007 2010 2012 2014 2016 2018 Top 10 average 4.06 4.01 4.01 3.99 4.13 4.03 Lowest 10 average 1.84 2.06 2.00 2.06 1.91 2.08 Source: Logistics Performance Index 2007, 2010, 2012, 2014, and 2016. 2 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Figure S.2 Respondents reporting that shipments are “often” or “nearly always” cleared and For the first time, the delivered as scheduled, by LPI quintile perceived improvement Percent of respondents Imports Exports in infrastructure quality 100 is higher in the bottom quintile than in the top 75 50 25 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2018. In the top LPI quintile, just 13 percent of contrast to ICT, rail infrastructure continues shipments fail to meet company quality criteria­ to elicit general dissatisfaction. —­the same proportion as in 2014 and 2016. By Similar patterns emerge when the domestic comparison, two to three times as many ship- LPI data on infrastructure are disaggregated ments in the two bottom quintiles fail to meet by World Bank region, excluding high-income these criteria, and quality criteria in low-per- countries. ICT is rated at the top or very close forming countries tend to be less rigid than in to the top in all regions. high-performing ones. This finding illustrates the persistence of the logistics gap from an over- Delivering good quality services all perspective of supply chain efficiency and is key to successful operations, reliability. and its importance is growing The differing pace of progress is also seen in the ratings of domestic trade and transport The LPI has shown that service quality drives infrastructure, where respondents were asked logistics performance in practically all econo- to assess how much these have improved since mies. Yet developing advanced services, such as 2015. third-party or fourth-party logistics, requires As in previous surveys, satisfaction with following a complex policy agenda, partly infrastructure quality varies by infrastructure because such services cannot be created from type. For the first time, however, the perceived scratch or developed purely domestically. In improvement is higher in the bottom quintile logistics-friendly countries, manufacturers and than in the top, although the difference is traders already outsource much of their basic weaker in the middle of the distribution. logistics operations to third-party providers Respondents in all LPI quintiles are highly and focus on pursuing their core business while satisfied with information and communications managing more complex supply chains issues. technology (ICT) infrastructure. The infra- This handoff is reciprocal: the more that such structure gap continues to narrow, particularly advanced services are available at a reasonable between the top and the bottom, where the rate cost, the more shippers will outsource their of improvement seems noticeably faster. Im- logistics. But the less that reliable and compre- provement in the middle quintiles is on a par hensive services are available, the more shippers with what has been observed previously. In will handle logistics in house. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 3 The 2018 LPI survey Logistics services are provided under very concern worldwide. Resilience is understood confirms that demand different operational environments globally. In as the ability of an organization (or a country) a pattern recurring across years, the quality of to recover from severe disruptions, whether for sustainable supply the services that logistics firms provide is often human caused or natural. For 2018, the LPI chain management perceived as better than the quality of the corre- survey included a question on cybersecurity goes hand in hand with sponding infrastructure that they operate. This resilience. The perceived magnitude of cyber- may be explained partly by who the respondents threats and preparedness to mitigate their logistics performance are­—­ freight forwarders and logistics firms rat- effects go hand in hand (figure S.3). Devel- ing their own services. oping countries lag far behind high-income In a pattern seen across LPI editions, op- countries in both. erations that support international trade, such The 2018 LPI survey confirms that demand as air and maritime transport and supporting for sustainable supply chain management goes services, tend to receive high scores even when hand in hand with logistics performance. This is infrastructure bottlenecks exist. Railroads, on especially true for environmentally sustainable the other hand, have low ratings almost every- services (green logistics). In the top quintile of where. Low-income countries score poorly on LPI performers, 28 percent of respondents in- road freight and warehousing. dicated that shippers often or nearly always Service quality can differ substantially at ask for environmentally friendly options. In similar levels of perceived infrastructure qual- the second-highest quintile, the share drops ity. Even high-quality “hard” infrastructure to 14 percent, and it falls steadily in the third cannot substitute for operational excellence, (9 percent), fourth (7 percent) and fifth (5 per- based on “soft” infrastructure such as profes- cent) quintiles. sional skills and smooth business and adminis- This trend is in line with the increasing trative processes. number of global and national commitments to reduce freight- and logistics-related greenhouse Supply chain resilience and gases, particulate matter, and other harmful sustainability are emerging concerns emissions. Regulatory changes have been imple- mented in all transport modes, and the interna- The resilience of international and domestic tional targets for 2030 and 2050, for example, supply chains has emerged as a growing policy are ever more challenging. Figure S.3 Cybersecurity threats and preparedness by income Cybersecurity threats in logistics have… Our firm’s preparedness for cyber threats has… (Much) decreased Stayed about the same (Much) increased (Much) decreased Stayed about the same (Much) increased Percent of respondents Percent of respondents 100 100 75 75 50 50 25 25 0 0 Low Lower Upper High Low Lower Upper High income middle income middle income income income middle income middle income income Source: Logistics Performance Index 2018. 4 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Pushing the envelope with considerable impact even before hard Countries that introduce of implementation infrastructure projects were completed. The far-reaching changes soft reforms provided a higher and quicker re- appear to be those Implementation of effective policies to improve turn on investment than hard infrastructure. logistics performance is at least as challenging Examples can be found in low- and middle- that treat logistics as today as in 2007­ —­for two reasons. First, the income countries such as India, Lao PDR, integral to the economy scope of implementation has widened from Southern African countries, and Vietnam and the traditional focus on infrastructure and in high-income countries such as Oman. Un- trade facilitation. Sustainability and resilience fortunately, performance may be degraded by receive more attention, and not only by devel- governance weaknesses and economic and so- oped countries, as do skills development and cial turmoil, as for some Arab countries in the training, spatial dimensions of logistics, and 2016 and 2018 LPI reports. Low-performing the specificity of the regulatory and legal frame- countries with serious governance challenges work. In addition to these emerging fields, reg- (conflict-ridden or postconflict countries and ulatory reforms of the logistics services sectors fragile states) are the most in need of attention are critical but remain challenging to imple- from their neighbors and the international ment in many developing countries. Regula- community. tory improvements aim to improve the quality Ultimately, countries that introduce far- of service delivery, building on market mecha- reaching changes appear to be those that treat nisms and private sector participation, in the logistics as integral to the economy. They tend sectors that constitute the core of logistics activ- to combine policy perspectives, such as regula- ities, such as trucking, brokerage, and terminal tory reform, trade facilitation, and trade and or warehousing operations. The broad and cross- investment planning. Seamless interagency co- cutting logistics agenda challenge policy mak- ordination and, above all, strong public–private ers to make sense of which policy measures are dialogue characterize the top performers. They needed, when, and using what resources. offer very positive examples of coordinating and Second, most reforms involve more than facilitating logistics bodies, some of them pub- one agency and many stakeholders, slowing lic–private institutions such as the most famous implementation, or even reversing it if coopera- one, the Dutch Dinalog. tive mechanisms are not sustainable. This prob- lem is well-known in developing countries for Influence of the Logistics transport (for example, transport corridors) and Performance Index trade facilitation (for example, single-window trade facilitation). Since its inception in 2007, the Connecting For consistent and broad reforms and im- to Compete report providing LPI ratings has provements, countries must deal with this com- moved trade logistics firmly onto the policy plexity. But countries in the middle and lower agenda, even for countries that had not previ- tiers of performance are deterred by weaker co- ously considered them. LPI results have also ordination mechanisms and private sector con- been used in many policy reports and docu- stituencies than countries with modern and in- ments prepared by multilateral organizations or novative logistics sectors. Even though logistics the consultants they have engaged. The findings services are provided overwhelmingly by the pri- provide a worldwide general benchmark for the vate sector, public sector actors and institutions logistics industry and for logistics users. play an essential role, without which logistics LPI results have been embraced by the aca- competitiveness is unlikely to improve. demic community, as evidenced by the wide- Administrative reforms can be rapid when spread use of LPI data in research reports, jour- countries with a strong political will align their nal articles, and textbooks. The results have also efforts. In some cases, soft reforms in facilita- been used in teaching, and thousands of theses tion of trade and transport were implemented at all levels have cited the LPI. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 5 Using LPI data requires caution, because demanding regulatory requirements for trad- they are based on a web-based survey aggre- ers and operators are motivated by safety, social, gating the views of the worldwide logistics and environmental, and other reasons. Efficient freight-forwarding community. To avoid overly management and information technology solu- simplistic conclusions, section 1 of Connecting tions in both the private and public sectors are to Compete presents detailed instructions on tools for high-quality logistics. National com- how to use­—­and how not to use­—­LPI data for petitiveness depends on the ability to manage various purposes. logistics in today’s global business environment. More than ever, comprehensive reforms and *    *    * long-term commitments are needed from policy makers and private stakeholders. The current Logistics performance is based largely on reli- LPI data provide a unique and updated refer- able supply chains and predictable service ence for better understanding the impediments delivery for traders. Global supply chains are to trade logistics worldwide and for informing becoming more and more complex. Ever more policy making and business decisions. 6 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 1 SECTION The 2018 Logistics Performance Index This is the sixth edition of Connecting to public–private partnership and dialogue. Previ- Compete, the biennial Logistics Performance ous Connecting to Compete reports have empha- Index (LPI) report. Global logistics is often sized that better policies lead to better logistics referred to as the “physical internet,” as it was performance. in the initial 2007 LPI report. Logistics is a Since the LPI was launched, gaps in perfor- network of services that support the physical mance have persisted between low-­ performing movement of goods, trade across borders, and countries and high-performing ones, mostly in commerce within borders. Logistics encompasses Europe and East Asia, where logistics has de- an array of activities beyond transportation, veloped into an important service sector. The including warehousing, brokerage, express importance of logistics-related policies in en- delivery, and critical infrastructure services hancing performance is more recognized today such as terminals. Competing international than in 2007, and the policy focus has evolved. networks of increasingly multi­ service logistics Initially, logistics policies focused on trade fa- providers offer ever more diversified solutions for cilitation and removal of border bottlenecks. trade, commerce, and manufacturing. Indeed, Today, such international logistics issues are the annual turnover generated by these global difficult to separate from domestic ones. And networks exceeds US$4.3 trillion.4 policy makers and stakeholders deal with a The role of logistics in the global economy wider range of policies, increasingly with safety is better recognized today than it was 10 years and sustainability in mind. Emerging policy ago. Good logistics services reduce the cost of concerns include spatial planning, greening trade. Logistics performance is about how effi- the supply chain, and bolstering the resilience ciently supply chains connect firms to domestic of the supply chain to disruption or disasters and international opportunities. The LPI tries (physical or digital) (see section 3). And skills to capture how logistically accessible, or how and training resources have recently received well connected to the physical internet of global more attention. logistics, a country is. It includes several dimen- The growing scope of logistics performance sions that will be developed in this report. and increasing recognition of its contribution to Logistics is business to business (B2B): its growth and economic integration call for holis- activities are executed primarily by private com- tic policies. More and more countries, especially panies for private companies. For this reason, emerging economies, see logistics as a sector of the LPI relies directly on the knowledge of lo- the economy requiring consistent policy making gistics professionals worldwide (box 1.1). But that cuts across traditional logistics areas. Previ- the performance of logistics in each economy ous LPI reports have referred to many countries depends on the public sector’s interventions having set up national strategies or dedicated or- and policies­ —­that was the main message of ganizations advancing logistics, such as Canada, the initial 2007 LPI report, and it remains true China, France, Indonesia, Morocco, the Neth- today. Public features include regulation; trans- erlands, and Thailand. For the 2018 edition, the portation infrastructure; the implementation examples include Oman (see box 3.3 in section of controls, especially for international goods 3) and India, which in 2017 set up a dedicated (as in trade facilitation); and the quality of logistics body under a Special Secretary. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 7 Box 1.1 The six components of the international Logistics Performance Index The World Bank’s Logistics Performance Index (LPI) analyzes coun- are best positioned to assess how countries perform. Their views tries through six indicators: matter because they directly affect the choice of shipping routes 1. The efficiency of customs and border management and gateways, thereby influencing the decisions of firms to locate clearance. production, choose suppliers, and select target markets. Their par- 2. The quality of trade- and transport-related infrastructure. ticipation is thus central to the LPI’s quality and credibility. 3. The ease of arranging competitively priced international shipments. Input and outcome LPI indicators 4. The competence and quality of logistics services. 5. The ability to track and trace consignments. Customs Timeliness 6. The frequency with which shipments reach consignees within the scheduled or expected delivery time. The components were chosen based on theoretical and empiri- Supply chain Inter- Infra- cal research and on the practical experience of logistics profession- national structure service shipments als involved in international freight forwarding. The figure maps the delivery six LPI indicators onto two main categories: • Areas for policy regulation, indicating main inputs to the sup- Services Tracking ply chain (customs, infrastructure, and services). quality and tracing • Supply chain performance outcomes (corresponding to LPI Areas Service —­ indicators of time, cost, and reliability­ timeliness, interna- delivery for tional shipments, and tracking and tracing). policy performance regulations outcomes The LPI uses standard statistical techniques to aggregate the Time, cost, (inputs) data into a single indicator (see appendix 5 for a detailed description reliability of how the LPI is calculated).a This single indicator can be used to compare countries, regions, and income groups. Because operators on the ground can best assess the vital See the 2018 LPI questionnaire at www.worldbank.org/lpi. aspects of logistics performance, the LPI relies on an online survey of logistics professionals from the companies responsible for mov- a. In all six editions of the LPI (2007, 2010, 2012, 2014, 2016, and 2018), ing goods around the world: multinational freight forwarders and statistical aggregation has produced an overall index close to the simple the main express carriers. Freight forwarders and express carriers average of country scores across the six LPI components. Guidelines on how to use the how easy or difficult they experience trade lo- LPI and how to interpret it gistics along six generic dimensions when deal- ing with eight preselected countries (see box 1.1 Since 2007, LPI findings have become standard and the LPI methodology in appendix 5). As a reference material in numerous studies and pol- survey, the LPI is subject to sampling error, di- icy papers on trade logistics. The LPI has been verging opinions of the respondents, and varia- adopted by several countries as a key perfor- tion of the respondent base from one LPI report mance indicator in their national transport or to the next. The number of evaluations received logistics strategies. It is also used as a subset of per country may also vary a lot. transport or logistics key performance indica- So, it is important to check the confidence tors by the European Union, the Association interval (CI) of a country’s LPI scores before of Southeast Asian Nations, Asia-Pacific Eco- making any deeper judgment: the narrower the nomic Cooperation, and others. (See more in CI, the more reliable the score. Large traders, box 3.1 in section 3). This makes it important such as China, Germany, the United Kingdom, to highlight how best to use the LPI and its and the United States, tend to have a CI at 0.05 indicators to avoid possible misinterpretations score points or below, which is about 1 percent (box 1.2). or less of their scores. By contrast, some smaller First, LPI data are gathered through a traders’ CIs are often closer to 0.5 score points, worldwide survey of logistics professionals on which may be more than 15  percent of their 8 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Box 1.2 How precise are LPI scores and ranks? Although the LPI and its components now offer the most compre- confidence intervals to account for sampling error, a country’s exact hensive and comparable data on country logistics and trade facili- ranking might be less relevant to policy makers than its proxim- tation environments, they have a limited domain of validity because ity to others in a wider performance group or its statistically sig- of the limited experience of survey respondents and, for landlocked nificant improvement. Still, a close examination of the distribution countries and small island states, the dependence of their logistics of changes in ranking indicates that they have behaved similarly on the logistics of other countries. across all six editions of the index. To account for the sampling error created by the LPI’s survey- To provide a bigger, better-balanced picture of country per- based dataset, LPI scores are presented with approximate 80 per- formance, this report publishes the current 2018 results along- cent confidence intervals (see appendix 5). These intervals yield side a composite score of the four latest surveys (2012–18). This upper and lower bounds for a country’s LPI score and rank. Upper approach reduces the noise and random variation from one LPI bounds for LPI ranks are calculated by increasing a country’s LPI survey to another and enhances the comparison of aggregate score to its upper bound while maintaining all other country scores scores for the 167 countries in the 2018 edition. In the aggregate constant and then recalculating LPI ranks. An analogous procedure data for the four latest LPI surveys, 41 countries scored 70 per- is adopted for lower bounds. cent or more of the top performer’s score. For these, the average Confidence intervals must be carefully examined to determine difference per rank position was 0.023 score points. For the next whether a change in score or a difference between two scores is 61 countries scoring 50–69 percent of the top performer’s score statistically significant. An improvement in a country’s performance and occupying ranks 42–102, the average difference per rank was should be considered statistically significant only if the lower bound 0.016 score points. This means that countries at similar perfor- of its 2018 LPI score exceeds the upper bound of its 2016 score. mance levels may have substantially different ranks, especially in Because of the LPI’s limited domain of validity and the need for the middle range. scores. Changes can be statistically significant with aggregate values, the maximum interval of only if the CIs for the scores of two consecutive both score (0.18 score points) and rank changes years do not overlap. (20 rank positions) are about half of what they Second, the overall LPI score is a more tell- are with single-year scores and ranks (0.38 score ing indicator than the LPI rank, because scores points and 37 rank positions) in the interval are more accurate and provide a better basis for covering the LPI reports in 2012, 2014, 2016, comparison over time. Especially for countries and 2018. ranked in the middle range, scores may differ lit- Third, the direction of trade in the interna- tle even if rank positions can be quite far apart: tional LPI is important to the countries being for example, Egypt, ranked 60th, and Bangla- evaluated. In addition, the traded products cov- desh, ranked 100th, both fall within 0.36 score ered could be labeled “general merchandise,” so points, an interval where the average difference the responses provide less information on goods per country is only 0.0088 score points. Thus, that require specific care, such as pharmaceuti- the fluctuation in a country’s rank from one LPI cals, food, and those labeled as dangerous. Fur- report to the next may appear much larger than thermore, the respondents are freight forward- the actual change in its score. ers, express carriers, and logistics providers (by For this reason, the 2018 LPI uses the road, rail, shipping, and air transport). weighted average LPI score as the primary in- Consequently, manufactured products dicator, taking away much of the oscillation in transported in unitized form make up the core scores from one LPI to another. The weighted of trade covered, where freight forwarders are average values of the four most recent LPI sur- typically used as intermediaries. Trade of large veys were provided in appendix 4 in the 2014 volumes of raw materials and energy products and 2016 LPI reports, too. Using the aggregate handled in bulk (such as ores, grain, oil, and gas) values and following their development over is not covered well in the LPI. Such large-volume time provides a more balanced picture of a coun- trade uses either direct industry buyer–seller try’s logistics performance than relying solely on channels or another type of intermediaries, such single-year data. For El Salvador, for instance, as commodity traders or shipping brokers. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 9 The LPI is best used Fourth, especially in poor countries, tradi- of professional skills and training in the logistics as a snapshot of where tional operators often play a larger role in trade sector. arrangements than international freight for- a country stands on warders. Traditional and international opera- Features of the 2018 survey logistics, and it can serve tors may differ in their interactions with gov- as an entry point to a ernment agencies, and in their service levels. In The 2018 LPI survey employed the same meth- developing countries, international networks odology as the previous five editions of Con- more comprehensive tend to serve large companies, which may have necting to Compete: a standardized ques- assessment of a country’s significantly different service level criteria for tionnaire with two parts, international and logistics performance time, cost, and other aspects from traditional domestic. In the international questionnaire, trading networks. respondents evaluate six indicators of logis- Fifth, for most landlocked countries and tics performance in up to eight of their main small island states, the LPI might reflect access overseas partner countries (see box 1.1 for the problems outside the country assessed, such as six indicators). In the domestic questionnaire, transit difficulties. The rating of a landlocked respondents are asked to provide qualitative and country might not adequately assess its trade quantitative data for the logistics environment facilitation reform efforts, because their success in the country where they work. depends on international transit routes through In 2018, almost 6,000 country assessments its neighbors. were made by logistics professionals. This In summary, individual country data—­ edition covers 160 countries in the international especially rank positions tracked from one LPI and 100 countries in the domestic LPI. The LPI report to the next—should preferably not report provides new insights on cybersecurity be used as the sole indicator, but should be threats in logistics and the use of electronic considered in combination with scores, while trading platforms by shippers. also keeping the size of the CI in mind. Using Given that the LPI captures a broad range the weighted aggregate score and rank data that of factors affecting performance, the results rely on the four latest LPI ratings is also a good show clear benefits, particularly for developing idea, as they provide a more balanced picture. countries, in moving forward on a broad range Furthermore, very few improvements in a of fronts to improve logistics. Evidence suggests country’s operational or regulatory environment that improvements in logistics performance immediately affect the global freight forwarding boost the integration of countries in global and logistics professionals view on that country. trade (box 1.3). However, some negative developments, such as a devastating natural catastrophe or an outbreak Key findings of the 2018 of a serious and wide-spread armed conflict may international Logistics impact a country’s ratings more quickly than any Performance Index positive changes. Put differently: positive changes tend to take more time, while some (extreme) Over the past several years, high-income negative ones might have a more sudden impact. countries, most of which are in Europe, The LPI has been effective at galvanizing occupied the top 10 positions in the LPI interest in and making the case for reform in rankings (table 1.1). Not surprising, since these several countries. It is best used as a snapshot of countries traditionally have been dominant in where a country stands on logistics, and it can the supply chain industry. serve as an entry point to a more comprehensive The composition of the 15 best-performing assessment of a country’s logistics performance. countries has not significantly changed This can entail, for instance, assessments of either. But it is worth highlighting major the different transport modes (road, rail, air, improvements in the LPI scores of Japan, maritime, and inland shipping), internal Denmark, the United Arab Emirates, and New logistics, dwell time studies, and an assessment Zealand since 2012. 10 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Box 1.3 Logistics performance boosts trade integration, but by just how much? The LPI has now been available for several years, which makes it possible to estimate a trade model using more than one year of data. The approach controls for unobservable and observable factors that vary by country and time, as well as by country pair, and isolates the impact of logistics performance. Shepherd (forthcoming) implements such an approach using data for 63 exporters and importers that together account for 93 percent of world GDP and a similar proportion of world trade. Regression results show that a 1 point improvement in a country’s LPI score increases trade by 16 percent, before accounting for relative price effects. He then uses the same model to consider a catch-up scenario, in which all countries narrow the logistics gap between themselves and the leading country by 20 percent, but all other factors remain constant. Total world real GDP (a proxy for economic welfare) would increase by 0.1 percent. Trade effects would be an order of magnitude larger. In relative terms, the largest welfare gains are typi- cally in developing countries such as Cambodia (0.7 percent), Costa Rica (0.4 percent), and Tunisia (0.4 percent). All these welfare impact figures are lower bounds, since they do not take into account intersectoral linkages in production, which are known to produce substantially higher results. Source: Shepherd forthcoming. Table 1.1 Top 10 LPI economies, 2018 2018 2016 2014 2012 Economy Rank Score Rank Score Rank Score Rank Score Germany 1 4.20 1 4.23 1 4.12 4 4.03 Sweden 2 4.05 3 4.20 6 3.96 13 3.85 Belgium 3 4.04 6 4.11 3 4.04 7 3.98 Austria 4 4.03 7 4.10 22 3.65 11 3.89 Japan 5 4.03 12 3.97 10 3.91 8 3.93 Netherlands 6 4.02 4 4.19 2 4.05 5 4.02 Singapore 7 4.00 5 4.14 5 4.00 1 4.13 Denmark 8 3.99 17 3.82 17 3.78 6 4.02 United Kingdom 9 3.99 8 4.07 4 4.01 10 3.90 Finland 10 3.97 15 3.92 24 3.62 3 4.05 Source: Logistics Performance Index 2012, 2014, 2016, and 2018. The bottom 10 countries in the ranking are and emerging economies such as Vietnam stand mostly low-income and lower-middle-income out as top performers. Most either have access to countries in Africa or isolated areas (table 1.2). the sea or are located close to major transporta- These are either fragile economies affected by tion hubs (table 1.4). armed conflict, natural disasters, and political Among low-income countries, countries in unrest or landlocked countries naturally chal- East and West Africa are leading performers in lenged by geography or economies of scale in the 2018 report (table 1.5). connecting to global supply chains. Figure 1.1 displays the cumulative The overall group composition among the distribution of LPI scores. The vertical lines top-performing upper-middle-income econo- represent the boundaries of LPI quintiles: mies has changed marginally, with China, Thai- five groups containing the same number of land, and South Africa leading the group, and countries rated in the LPI. The bottom quintile Croatia and Bulgaria improving in their LPI includes countries with the lowest LPI scores, ranking (table 1.3). while the top quintile includes countries with Among lower-middle-income countries, the highest scores. As in past LPI reports, the large economies such as India and Indonesia range of scores in the third and fourth quintiles C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 11 Table 1.2 Bottom 10 LPI economies, 2018 2018 2016 2014 2012 Economy Rank Score Rank Score Rank Score Rank Score Afghanistan 160 1.95 150 2.14 158 2.07 135 2.30 Angola 159 2.05 139 2.24 112 2.54 138 2.28 Burundi 158 2.06 107 2.51 107 2.57 155 1.61 Niger 157 2.07 100 2.56 130 2.39 87 2.69 Sierra Leone 156 2.08 155 2.03 na na 150 2.08 Eritrea 155 2.09 144 2.17 156 2.08 147 2.11 Libya 154 2.11 137 2.26 118 2.50 137 2.28 Haiti 153 2.11 159 1.72 144 2.27 153 2.03 Zimbabwe 152 2.12 151 2.08 137 2.34 103 2.55 Central African Republic 151 2.15 na na 134 2.36 98 2.57 na is not available. Source: Logistics Performance Index 2012, 2014, 2016, and 2018. Table 1.3 Top-performing upper-middle-income economies, 2018 2018 2016 2014 2012 Economy Rank Score Rank Score Rank Score Rank Score China 26 3.61 27 3.66 28 3.53 26 3.52 Thailand 32 3.41 45 3.26 35 3.43 38 3.18 South Africa 33 3.38 20 3.78 34 3.43 23 3.67 Panama 38 3.28 40 3.34 45 3.19 61 2.93 Malaysia 41 3.22 32 3.43 25 3.59 29 3.49 Turkey 47 3.15 34 3.42 30 3.50 27 3.51 Romania 48 3.12 60 2.99 40 3.26 54 3.00 Croatia 49 3.10 51 3.16 55 3.05 42 3.16 Mexico 51 3.05 54 3.11 50 3.13 47 3.06 Bulgaria 52 3.03 72 2.81 47 3.16 36 3.21 Source: Logistics Performance Index 2012, 2014, 2016, and 2018. Table 1.4 Top-performing lower-middle-income economies, 2018 2018 2016 2014 2012 Economy Rank Score Rank Score Rank Score Rank Score Vietnam 39 3.27 64 2.98 48 3.15 53 3.00 India 44 3.18 35 3.42 54 3.08 46 3.08 Indonesia 46 3.15 63 2.98 53 3.08 59 2.94 Côte d'Ivoire 50 3.08 95 2.60 79 2.76 83 2.73 Philippines 60 2.90 71 2.86 57 3.00 52 3.02 Ukraine 66 2.83 80 2.74 61 2.98 66 2.85 Egypt, Arab Rep. 67 2.82 49 3.18 62 2.97 57 2.98 Kenya 68 2.81 42 3.33 74 2.81 122 2.43 Lao PDR 82 2.70 152 2.07 131 2.39 109 2.50 Jordan 84 2.69 67 2.96 68 2.87 102 2.56 Source: Logistics Performance Index 2012, 2014, 2016, and 2018. 12 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Table 1.5 Top-performing low-income economies, 2018 2018 2016 2014 2012 Economy Rank Score Rank Score Rank Score Rank Score Rwanda 57 2.97 62 2.99 80 2.76 139 2.27 Benin 76 2.75 115 2.43 109 2.56 67 2.85 Burkina Faso 91 2.62 81 2.73 98 2.64 134 2.32 Mali 96 2.59 109 2.50 119 2.50 na na Malawi 97 2.59 na na 73 2.81 73 2.81 Uganda 102 2.58 58 3.04 na na na na Comoros 107 2.56 98 2.58 128 2.40 146 2.14 Nepal 114 2.51 124 2.38 105 2.59 151 2.04 Togo 118 2.45 92 2.62 139 2.32 97 2.58 Congo, Dem. Rep. 120 2.43 127 2.38 159 1.88 143 2.21 na is not available. Source: Logistics Performance Index 2012, 2014, 2016, and 2018. Figure 1.1 Cumulative distribution of LPI scores, 2018 Cumulative density 1.0 Bottom quintile Fourth Third Second quintile Top quintile quintile quintile 0.8 Logistics unfriendly Logistics friendly Partial performers 0.6 Consistent performers 0.4 0.2 0.0 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 LPI score Source: Logistics Performance Index 2018. is similar. This means that country LPI scores • Logistics-unfriendly: Includes countries with are closer to each other and that any change severe logistics constraints, such as the least in the country’s performance (and that of its developed countries (bottom LPI quintile). neighbors) will generate larger changes in the • Partial performers: Includes countries with a ranking relative to countries in other quintiles level of logistics constraints most often seen (see box 1.2). in low- and middle-income countries (third As in previous reports, LPI scores are and fourth LPI quintiles). broken down into four categories, consistent • Consistent performers: Includes countries with the score quintiles, used in all editions of rated better on logistics performance than Connecting to Compete: most others in their income group (second LPI quintile). C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 13 • Logistics-friendly: Includes top-­ performing which also have relatively low quality of logistics countries, most of which are in the high- services. income group (top LPI quintile). In addition, table 1.6 shows which of the six LPI components of the international LPI are Logistics performance is above or below the overall index. A positive entry strongly correlated with indicates that an LPI component score is higher the quality of service than a group’s overall international LPI score, and a negative entry indicates that the compo- Several trends observed in past LPI reports nent score is lower than the group’s overall score. still hold. There are significant differences in Several observations stand out. Customs and bor- LPI performance across LPI components and der agencies continue to underperform compared quintiles (figure 1.2). The timeliness component with other LPI components. As in past reports, seems to outperform the other LPI components except for the top quintile, the quality of trade and is generally viewed as the least problematic. and transport infrastructure score and the qual- On the other hand, the performance of cus- ity of logistics services score are below the overall toms and border agencies, as well as the quality LPI score. Across the three lowest quintiles, the of trade and transport infrastructure, are par- tracking and tracing component is a little below ticularly low in the worst-performing countries, than the overall score, as in past reports. Figure 1.2 LPI components score, by LPI quintile, 2018 LPI score Customs Infrastructure Ease of shipping Quality of logistics Tracking and Timeliness arrangements services tracing 4.5 4.0 3.5 3.0 2.5 2.0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile Source: Logistics Performance Index 2018. Table 1.6 Deviation on each component from the overall LPI score, by quintile Ease of shipping Quality of Tracking and Quintile Customs Infrastructure arrangements logistics services tracing Timeliness Bottom quintile –0.16 –0.19 0.04 –0.05 –0.02 0.34 Fourth quintile –0.14 –0.19 0.01 –0.09 –0.01 0.39 Third quintile –0.20 –0.19 0.02 –0.07 –0.01 0.42 Second quintile –0.24 –0.12 –0.01 –0.07 0.02 0.40 Top quintile –0.18 0.02 –0.19 0.00 0.07 0.31 Source: Logistics Performance Index 2018. Note: All calculations are based on the weighted average score for the LPI and its components over 2012–18. 14 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y In past reports, average country LPI scores Logistics performance is High-income countries, were generally improving. But in 2018, low- more than income on average, surpass income countries experienced a drop in the LPI low-income countries scores for quality of infrastructure, customs There is still a noticeable gap in LPI scores performance, and quality of logistics services, between high- and low-income countries. by 48 percent in as lower-middle-income countries’ scores on High-income countries, on average, surpass their LPI scores these three LPI components improved (figure low-income countries by 48  percent in 1.3).5 Progress can be also tracked on the envi- their LPI scores. Among the 30 top-­ ronment for logistics since the last LPI edition performing countries, 24 are members of the (table 1.7). Contrary to past reports, respon- Organization for Economic Co-operation dents report improved scores for the bottom and Development (OECD), a proportion that two quintiles in ICT infrastructure and in pri- has not changed much since past LPI reports. vate logistics services­ —­possibly due to ICT in- Even so, countries such as China, India, frastructure improvements in the past decade. Rwanda, Thailand, and Vietnam outperform For low-income countries, streamlining border their income group peers (figure 1.4). That clearance procedures and ensuring access to is why income alone cannot explain why physical trade and transport infrastructure will performance varies widely among countries continue to be priority issues. in certain income groups. On the other Figure 1.3 Change in LPI component score by income group, 2016–18 Percentage change Customs Infrastructure Quality of logistics services 3 0 –3 –6 Low income Lower middle income Upper middle income Source: Logistics Performance Index 2016 and 2018. Table 1.7 Respondents reporting an “improved” or “much improved” logistics environment since 2015, by LPI quintile Percent Component Bottom quintile Fourth quintile Third quintile Second quintile Top quintile Customs 61 63 44 68 62 Other border procedures 69 43 36 60 49 Trade and transport infrastructure 65 40 45 66 53 ICT infrastructure 54 69 62 69 67 Private logistics services 55 82 61 69 65 Logistics regulation 57 39 36 53 31 Incidence of corruption 39 34 45 56 35 Source: Logistics Performance Index 2018. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 15 Figure 1.4 LPI overperformers and underperformers LPI score 4.5 Linear regression 4.0 China 3.5 Thailand Vietnam India South Africa Rwanda Indonesia 3.0 Côte d’Ivoire Malawi Benin 2.5 Turkmenistan Papua Guyana Fiji Cuba New Guinea Equatorial Guinea Iraq Gabon 2.0 Bhutan Angola 1.5 5 6 7 8 9 10 11 12 Log of GDP per capita (current US$, 2015) Source: Logistics Performance Index 2018. Note: Fitted values are based on an ordinary least squares regression using data for all countries. Underperformers (black diamonds) are the non-high-income countries with the 10 smallest residuals. Overperformers (black circles) are the non-high-income countries with the 10 largest residuals. Figure 1.5 LPI score as a percentage of hand, the mostly resource-rich countries­—­ the best performer, Angola, Gabon, Equatorial Guinea, Iraq, and 2012–18 Turkmenistan­—­u nderperform their income Percent 2012 2014 2016 2018 group peers. 90 Trends over the past four reports 80 The gap in relative LPI scores­ —­the scores as a 70 percentage of the leading country’s score­ —­ is 60 quite similar to the gap revealed in past edi- tions of Connecting to Compete. The average 50 relative score of the three lowest quintiles was higher than in the past three LPI reports (fig- 40 ure 1.5). In 2018, the worst relative performer is Afghanistan, at 29.6  percent of best per- 30 Bottom Fourth Third Second Top former Germany’s score. In 2016, the worst quintile quintile quintile quintile quintile performer was the Syrian Arab Republic, at Source: Logistics Performance Index 2012, 2014, 2016, and 2018. 19 percent. In 2014, the worst was Somalia, at 25 percent. The correlation between the 2016 and 2018 Weighted international LPI LPI scores is a bit stronger than those between scores and ranks 2012–18 past reports, with 0.93 in scores and 0.90 in rankings (compared with 0.91 in scores and As in the past two reports, the scores of the six 0.86 in rankings between 2012 and 2014). LPI components across the four latest surveys Keep in mind that the data are survey-based and were used to provide a bigger and better- thus are prone to sampling errors. Statistically balanced picture of a country’s performance. significant changes are revealed only if the This approach is believed to reduce the noise and confidence intervals for the 2016 and 2018 random variation across different LPI surveys, scores do not overlap. and thus enhances the comparison of the 167 16 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y countries. In the 2018 report, the four previous As in 2010–16, all OECD countries are in Despite some convergence scores on each component were weighted as the top third. In the previous 2007–14 LPI ag- since the 2007 LPI, the follows: 6.7 percent for 2012, 13.3 percent for gregate, all European Union member states were logistics gap between 2014, 26.7 percent for 2016, and 53.3 percent in the top third. Bulgaria fell narrowly outside for 2018 (so the more recent data carry more this category in the aggregate LPI scores for high- and low-income weight). This method is identical to the one used 2012–18 (3.0, ranked 57th) and 2010–16 (2.96, countries persists in the 2014 and 2016 reports, which used the ranked 62th). Romania, by contrast, rose from a data for the prior four LPI reports. 2010–16 score of 3.05, ranked 56th, to a 2012– The opportunity to use weighted values 18 score of 3.09, ranked 50th. is important because an individual country’s In the aggregate international LPI for 2012– score and, consequently, its rank can oscillate a 18, Somalia again scores the lowest at 2.00, lot, even though the change might not be sta- ranked 167th (it scored 1.67 in 2010–16 and tistically significant. That happened to several 1.62 in 2007–14). Despite some convergence countries’ scores in 2014–16, especially those since the 2007 LPI, the logistics gap between with a wide confidence interval, indicating dis- high- and low-income countries persists. As agreement among the respondents. The effect in the previous surveys, the countries with tends to be amplified if the number of observa- the weakest performance in 2018 are least tions is low, as is frequent in smaller countries. developed countries or small island countries, Large traders, such as China, Germany, the some also conflict-ridden. Haiti occupies the United Kingdom, and the United States had second-­ lowest rank with a score of 2.02 (it confidence intervals of 0.05 score points or less scored 1.96 in 2010–16 and 2.24 in 2007– in 2018, 1 percent or less of their corresponding 14). Other countries that score the lowest on LPI scores. By contrast, Yemen, with a confi- logistics include Afghanistan with a score of dence interval of 0.44, Iceland with 0.42, Niger 2.04 (2.15 in 2010–16 and 2.10 in 2007–14), with 0.41, and Malta with 0.39 had the largest Sierra Leone with 2.06 (2.04 in 2010–16 and confidence intervals, more than 13 percent of 2.06 in 2007–14), and the Syrian Arab Republic their scores. with 2.10 (1.94 in 2010–16 and 2.31 in 2007– In the aggregate 2012–18 LPI, Germany 14). Broadly speaking, the converging countries­ scores highest at 4.19 (4.17 for the aggregate —­ranking, roughly, from 40th to 120th­—­have 2010–16 LPI and 4.10 for 2007–14), followed scores separated by only a few decimal points. by the Netherlands 4.07 (4.12 for 2010–16 Thus, some large changes in rank might be and 4.05 for 2007–14), Sweden 4.07 (4.08 witnessed in this middle ground, even though for 2010–16 and 3.95 for 2007–14), Belgium the underlying score changes are marginal. 4.05 (4.06 for 2010–16 and 4.0 for 2007–14), and Singapore 4.05 (4.10 in 2010–16 and 4.06 Changes in countries’ in 2007–14). Germany and the Netherlands LPI scores 2016–18 continue to dominate the top three, while Singapore fell from third to fifth. Of the 28 Changes in the LPI score reflect negative or European Union member states, 15 are among positive private sector perceptions of logistics the top 30 countries, and of the 34 OECD performance. The LPI score is thus not purely a members, 24 are among the top 30. The non- metric of current performance. It incorporates OECD economies in the top 30 are Singapore expectations, trends, and the perceived pace of (5th) Hong Kong, SAR, China (9th), United improvement. This can create a rebound effect Arab Emirates (14th), Taiwan, China (24th), from one survey to the next. For example, a China (27th), South Africa (29th), and Qatar country with large positive changes in one (30th). All but two of the top 30 are high- survey may be adjusted downward the next income countries; the other two, China time because positive changes were perceived as and South Africa, are upper-middle-income happening more slowly than anticipated during countries. the preceding survey. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 17 Table 1.8 Number of countries with positive and negative changes in LPI scores, 2016–18 Change in LPI score, 2016-18 Low income Lower middle income Upper middle income High income Positive and statistically significant 1 4 0 0 Positive (not statistically significant) 11 18 23 14 No change 0 0 1 0 Negative (not statistically significant) 10 16 13 32 Negative and statistically significant 1 3 2 5 Source: Logistics Performance Index 2016 and 2018. Note: The 2018 LPI includes 160 countries, of which 6 were not included in the 2016 edition and are thus not included in this table. Twelve countries had different income classifications in 2018 than in 2016; in all cases the 2018 classification was used. Differences in scores were rounded to two positions after the decimal point. The LPI score depends primarily on performance of internal logistics and domestic industry perceptions of relative performance. commerce corridors linking economic centers Even a country that is making improvements across provincial or state boundaries. And can see its score affected by the perceived impact survey respondent demographics can affect a or speed of improvements in other countries. perception-based survey such as the LPI. Planned improvements to a country’s logistics Score changes from one edition of the LPI environment can temporarily lower a country’s to the next should be interpreted with care. LPI score. For example, even if relocation from However, negative trends across all years, not an old port to a new one is managed efficiently, just two, may be something to worry about­ —­ it is likely that the logistics industry will expect especially when a country’s score changes by or experience disruptions in supply chains more than 20%. Connecting to Compete always during the adjustment. includes the statistical confidence interval for LPI assessments may also be influenced by each country’s International LPI (see appendix respondents’ own experiences and the types of 2). Statistically significant changes occur only cargo they handle. Logistics for oil, gas, mining, if the confidence intervals for the 2018 and or industrial projects are likely to be smoother 2016 scores do not overlap. Table 1.8 gives an and more homogeneous worldwide than exports overview of the number of countries in the of goods for local consumption, which go 2018 index whose LPI score changed, either through traditional logistics and distribution negatively or positively. channels. For large countries with sizable While the finding is not statistically domestic markets and associated domestic significant, it is noteworthy that slightly more logistics systems­ —­ such as China and India­ —­ low- and middle-income countries had LPI the LPI is biased toward the performance of the scores rise (34) than fall (30) between 2016 main import gateways. It does not capture the and 2018. 18 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 2 SECTION Unbundling logistics performance The international Logistics Performance Index Survey respondents in top-quintile coun- (LPI) provides insights into the drivers of over- tries rated their infrastructure far more highly all logistics performance. To unbundle the sur- than those in other quintiles did (table 2.1). Dif- vey results, it is necessary to refer to the domestic ferences among the other four quintiles are less LPI. This section is based on the domestic LPI, striking, especially for roads and rail. The differ- where surveyed logistics professionals assess the ence between the top and bottom is smallest in logistics environments in countries where they ICT, suggesting that developing countries may work. It contains more detailed information have been investing heavily in modern technol- on countries’ logistics environments, processes, ogies, perhaps even leapfrogging intermediate and institutions and looks at the logistics con- stages of performance. Of course, ICT cannot straints within countries, not just at gateways replace other hard infrastructure, which re- such as ports or borders. It analyzes countries quires a renewed focus. by four major determinants of overall logistics Though still a constraint in developing performance: infrastructure, services, border countries, infrastructure seems to be improv- procedures, and supply chain reliability. Unless ing. Since the previous LPI survey, respondents otherwise stated, data are from the 2018 survey from countries in all performance quintiles rather than aggregate data for 2012–18. generally perceive improvements in trade and transport infrastructure (figure 2.1). For the Infrastructure: A shared concern first time since the survey began, the perception across performance groups of improvement is higher in the bottom quintile than in the top one, though lower in the middle. Infrastructure is a major concern across all LPI If this pattern persists, it would be consistent performance groups except the top performers, with some closing of the logistics gap discussed but survey respondents signal improvements. in section 1. The quality of information and communications It is also possible to compare respondents’ technology (ICT) is consistently rated higher ratings of infrastructure with the ratings in than physical transportation infrastructure. previous LPI reports. Table 2.1 shows clear evi- dence of increasing satisfaction with port infra- structure, since scores in 2018 are higher than in Table 2.1 Respondents rating the quality of each infrastructure type “high” or “very high,” by LPI quintile previous years, as they were in 2016 compared with 2014 in most quintiles. Although for other Percent of respondents types of infrastructure the picture is mixed and Warehousing and LPI quintile Ports Airports Roads Rail transloading ICT varies by quintile, these results together with Bottom quintile 26 30 17 17 21 34 respondents’ observations of improvement (see Fourth quintile 23 13 10 9 23 44 figure 2.1) clearly suggest that governments are Third quintile 33 39 20 12 27 48 aware of the importance of infrastructure qual- Second quintile 57 41 37 11 37 52 ity for logistics performance and are working Top quintile 63 67 57 37 62 75 successfully to improve it. Satisfaction with infrastructure quality var- ICT is information and communications technology. Source: Logistics Performance Index 2018. ies by infrastructure type. As in previous years, C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 19 ICT is consistently rated Figure 2.1 Respondents rating the quality of reports, elicits general dissatisfaction. In the higher than physical trade and transport infrastructure bottom quintile, infrastructure of all kinds fails as “improved” or “much improved” to satisfy­—­an exception to the pattern in other infrastructure across since 2015, by LPI quintile quintiles of variation by infrastructure type. performance quintiles, Percent of respondents Similar patterns emerge when the domestic and rail infrastructure and LPI data on infrastructure are disaggregated 80 by World Bank region, excluding high-income services are rated lowest countries (table 2.2). The highest ratings are 60 for ICT in all regions except the Middle East and North Africa, and Latin America and the Caribbean, where ICT ratings are very close to 40 the highest. Ratings for other types of infra- structure vary more widely by region, but two features stand out. First, satisfaction with road 20 and rail infrastructure is especially low in Latin America and the Caribbean, as in previous sur- 0 veys, and also in South Asia, as in 2016. Second, Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest (low (average (high (highest satisfaction with rail infrastructure is low in all performance) performance) performance) performance) performance) regions, as was the case for all LPI quintiles. Source: Logistics Performance Index 2018. Developing logistics respondents in all LPI quintiles are most satis- services markets fied with ICT infrastructure. As in 2016, there is evidence of a narrowing infrastructure gap, The quality and competence of core logistics particularly between the top quintile and the service providers are two other important parts bottom one, where the rate of improvement in of a country’s overall performance. Respondents 2018 seems noticeably faster than in 2016; im- in all LPI quintiles are nearly always more sat- provement in the middle quintiles is on a par isfied with service providers than with infra- with that in earlier reports. Rail infrastruc- structure quality (table 2.3, compared with ture, by contrast, but also in line with previous table 2.1). Just as for infrastructure, for service Figure 2.2 Respondents rating the quality of each infrastructure type as “high” or “very high” by LPI quintile, 2014–18 Percent 2018 2016 2014 80 60 40 20 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2014, 2016, and 2018. 20 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Table 2.2 Respondents rating the quality of each infrastructure type “high” or “very high,” by World Bank developing country region Percent of respondents Warehousing and Region Ports Airports Roads Rail transloading ICT East Asia and Pacific 33 36 33 10 33 43 Europe and Central Asia 14 22 21 20 23 48 Latin America and Caribbean 26 23 9 0 6 26 Middle East and North Africa 70 53 45 12 56 69 South Asia 18 14 7 10 7 37 Sub-Saharan Africa 45 39 17 13 30 47 ICT is information and communications technology. Source: Logistics Performance Index 2018. Table 2.3 Respondents rating the quality and competence of each service provider type “high” or “very high,” by LPI quintile Percent of respondents Maritime Warehousing, Trade and Road Rail Air transport transloading, Freight Customs transport Consignees LPI quintile transport transport transport and ports and distribution forwarders brokers associations or shippers Bottom quintile 28 19 37 44 33 32 14 24 22 Fourth quintile 30 9 39 46 21 38 26 19 26 Third quintile 36 24 58 40 39 45 45 32 22 Second quintile 38 26 49 53 49 59 36 42 38 Top quintile 78 41 70 71 69 78 68 56 52 Source: Logistics Performance Index 2018. providers there is a quality gap between the top develop transport-related infrastructure, so that LPI quintile and the other four quintiles. service markets reforms can bring maximum For countries in all LPI quintiles, freight benefits to users. forwarders are rated highly, typically at or close As for infrastructure performance, it is pos- to the strongest scores among service providers sible to compare service performance over LPI (see table 2.3).6 Ratings for the other service pro- years. Figure 2.3 shows performance in the vider types vary more widely across all quintiles­ bottom quintile, where improvements are par- —­ though rail transport service provision, like ticularly important, over 2014–18. Across most rail infrastructure, consistently receives low rat- types of service provider, respondent satisfac- ings (see table 2.3). Rail transport aside, in the tion has clearly increased. The bottom quintile top-performing countries, service providers of is particularly important, as underdeveloped all types are rated as being of high quality and logistics services markets are often a key con- competence, though the scores for consignees straint on performance. But figure 2.3 suggests or shippers and for trade and transport associa- that even in challenging environments, govern- tions are lower than for most other types. ments and the private sector can move toward A ratings gap between services and infra- higher performance in a fairly short time. For structure appears generally across World Bank other quintiles, results are more variable. regions (table 2.4). It is particularly stark for air transport in Europe and Central Asia and Latin Streamlining border procedures America and the Caribbean, for road transport and facilitating trade in Latin America and the Caribbean and Sub-­ Saharan Africa, and for warehousing in Sub-­ The survey collects a set of indicators related Saharan Africa. These data suggest a need to to the time to trade, the ease of clearance at C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 21 Table 2.4 Difference between respondents rating services “high” or “very high” and those rating infrastructure “high” or “very high,” by World Bank developing country region Percentage points Warehousing, Maritime transport transloading, and Region and ports Air transport Road transport Rail transport distribution East Asia and Pacific 9 9 3 0 4 Europe and Central Asia 9 18 16 2 6 Latin America and Caribbean 21 18 12 5 11 Middle East and North Africa 0 –9 8 3 –7 South Asia 6 10 1 –8 4 Sub-Saharan Africa 5 12 16 14 16 Source: Logistics Performance Index 2018. Figure 2.3 Respondents rating the quality of each infrastructure service type as “high” or “very high,” bottom LPI quintile, 2014–18 Percent of respondents 2018 2016 2014 50 40 30 20 10 0 Road Rail Air Maritime W/H, transload, Freight Customs Trade and Consignees transport transport transport and ports distr. forwarders brokers transport assoc. or shippers Source: Logistics Performance Index 2014, 2016, and 2018. the border, and the experience with red tape. Import and export time Breakdowns of these data by region and The time to complete trade transactions is a income group are in appendix 3, and for time useful outcome measure of logistics perfor- and distance by country in appendix 4. These mance. The median import lead time for port indicators provide contrasting insight into the and airport supply chains, as measured for the depth of implementation of trade and trans- LPI, is generally lower in higher performing portation reforms. The principles of trade groups (figure 2.4).7 It takes nearly three times facilitation are widely accepted­ —­for instance, as long to import in the bottom quintile as in automated submission is the norm in all per- the top quintile. This substantial gap is similar formance groups. But lead times to import or to the one in 2016. But unlike previous reports, clear goods or amounts of red tape still dif- this year’s does not show a consistent relation- ferentiate much between the bottom three ship between time and performance quintile. quintiles and the two top performance tiers: Instead, results for the third quintile, par- for the bottom three clearance times are three ticularly the land supply chain, seem anoma- times as much and paperwork twice as much as lously high. These relationships will need to be for the top two. inspected closely in future years to see whether 22 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Figure 2.4 Median import time and average clearance time, by LPI quintile Customs procedures are becoming more similar Days Import lead time (ports and airports) Import lead time (land) 12 worldwide: even the bottom quintile countries 10 tend to adopt core 8 Average clearance time without physical inspection customs best practices Average clearance time with physical inspection 6 4 2 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2018. the issue is sampling error or changes in respon- on arrival (see figure 2.4). Although the time dent demographics, or concrete issues of perfor- to clear goods through customs is a small frac- mance that need to be addressed. tion of total import time for all LPI quintiles, it Importing by land takes longer than im- rises sharply if goods are physically inspected, porting by air or sea in all LPI quintiles except even in high-performing countries. Core cus- the bottom one­ —­ possibly another anomalous toms procedures are similar across quintiles. result. The correlation between land distance But physical inspection is far more prevalent in and import lead time suggests that geographic low-performing countries, which may even sub- hurdles­—­ in addition to infrastructure, service ject the same shipment to repeated inspections provision, and other logistics issues­—­are impor- by multiple agencies (table 2.5). Countries with tant in determining a country’s ability to con- low logistics performance need to cut red tape, nect with world markets. physical inspections, and excessive and opaque Besides geography and speed en route, the procedural requirements. efficiency of border processes affects import lead Export supply chains typically have a much times. The time for border processes can be re- lighter procedural burden than import supply duced at all stages, but especially clearing goods chains, so lead times are shorter for exports Table 2.5 Respondents indicating that listed customs procedures are available and being used, by LPI quintile Percent of respondents, unless otherwise indicated Customs procedure Bottom quintile Fourth quintile Third quintile Second quintile Top quintile Online processing of customs declaration 76 94 83 92 95 Requirement that a licensed customs broker be used for clearance 100 81 57 86 67 Choice of location of final clearance 63 67 81 74 75 Release with guarantee pending final clearance 61 52 50 69 64 Physical inspection of import shipments (percent of shipments) 33 29 20 17 9 Multiple physical inspections of import shipments 18 11 11 3 5 Source: Logistics Performance Index 2018. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 23 than for imports (figure 2.5). Export lead times low-income countries and the rest than between for overall logistics performance have generally middle- and high-income countries. Many low- declined, but not for land supply chains in the income countries have long export lead times, third and fourth quintiles, an anomalous re- hurting their export competitiveness and ability sult that will need to be monitored in future to trade internationally. reports. The familiar logistics gap between Unlike lead times, customs procedures are income groups appears again for export lead becoming more similar worldwide (see table times, which are nearly four times as long for 2.5). Even the bottom quintile countries tend low- as for high-income countries (figure 2.6). to adopt core customs best practices. That gap is far wider than in previous editions, Even as customs procedures gradually im- perhaps due to a different locational composi- prove, customs is not the only agency in border tion of survey respondents. Export times for management in many countries, and the other land supply chains differ much more between agencies constrain supply chain performance. Figure 2.5 Median export lead time, by LPI quintile Days Export lead time (ports and airports) Export lead time (land) 14 12 10 8 6 4 2 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2018. Figure 2.6 Median export lead time, by income group Days Export lead time (ports and airports) Export lead time (land) 20 15 10 5 0 Low income Lower middle income Upper middle income High income Source: Logistics Performance Index 2018. 24 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Table 2.6 Respondents rating the quality and competence of three border agencies as “high” or “very high,” by LPI quintile Percent of respondents Customs Quality/standards Health/sanitary and LPI quintile agencies inspection agencies phytosanitary agencies Bottom quintile 15 26 25 Fourth quintile 15 23 21 Third quintile 32 32 21 Second quintile 44 43 39 Top quintile 76 58 55 Source: Logistics Performance Index 2018. In 2018, the performance gap between customs among all agencies­ —­ standards, transport, vet- and other border agencies is narrower than in erinary, and health/SPS­ —­is critical to reform. previous LPI reports, and even reversed in the So is introducing modern approaches to regula- fourth quintile (table 2.6). Previous editions tory compliance. stressed that for many countries, the key to Whereas customs performance has re- improving border agency performance may lie mained constant across the board since the 2014 with reforms to agencies other than customs. LPI report, quality and standards/inspection There is evidence that some countries have been agencies have improved considerably in lower moving forward on this agenda, though the data quintiles. Figures 2.7 and 2.8 show a clear trend will need to be monitored in future years to see toward greater satisfaction with them. whether the trend continues. It remains important to look beyond cus- Red tape toms when designing trade facilitation reforms. Indicators for red tape show a continuing lack Fewer inspection procedures are required for of border coordination, resulting in a burden products that are not perishable or time sensi- on private logistics operators similar to the tive. Health and sanitary and phytosanitary one in previous editions. In countries in the (SPS) agencies have been slow to automate, al- bottom quintile, operators typically deal with though that may be changing. Cooperation around twice as many government agencies and Figure 2.7 Respondents rating the quality and competence of quality and inspection agencies as “high” or “very high,” by LPI quintile, 2014–18 Percent 2018 2016 2014 60 40 20 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2014, 2016, and 2018. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 25 Figure 2.8 Respondents rating the quality and competence of health and sanitary/ phytosanitary agencies as “high” or “very high,” by LPI quintile, 2014–18 Percent of respondents 2018 2016 2014 60 40 20 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2014, 2016, and 2018. documentary requirements operators as coun- place great weight on such simplification. Still, tries in the top quintile (figure 2.9). Countries steps in other aspects of border management in the top quintile typically require two sup- and, more generally, soft and hard trade-related porting documents for trade transactions, and infrastructure are also needed. those in the bottom, four to five­ —­ a persistent The World Trade Organization (WTO) logistics gap in the previous and current LPIs. Agreement on Trade Facilitation (TFA) can Simplifying documentation for imports and help in two areas. First, its standards are sub- exports has long been high on the trade facilita- ject to the WTO’s binding trade disciplines, tion agenda, prompting initiatives to bring bor- unlike previous conventions, although devel- der agencies together and create a single window oping countries remain free to select which for trade. The World Bank and International Fi- parts of the TFA will become immediately nance Corporation’s Doing Business indicators binding, which will be deferred, and which Figure 2.9 Red tape affecting import and export transactions, by LPI quintile Number of procedures Import agencies Export agencies Import documents Export documents 5 4 3 2 1 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2014, 2016, and 2018. 26 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y will apply only once technical assistance is re- consistent with the lower prevalence of most Predictable, reliable supply ceived. Second, to support this framework, the kinds of delays in the bottom quintile than in chains are central to good TFA strengthens the delivery of technical assis- the middle ones. It is hoped that this important logistics performance; tance and capacity-building support for devel- change reflects catching up, and monitoring the oping and least developed countries. Many of trend in future reports will be important. highly uncertain lead the agreement’s measures are relatively straight- Despite clear improvements, delays and un- times can disrupt forward to implement, while others, such as in- expected costs are more common in bottom production and exporting troducing national single-window systems, can quintile countries than the top performers, un- be quite complex and will require sustained ef- dermining overall supply chain performance. fort from governments. Worse, across LPI quintiles the incidence of delays is generally increasing, except in the low- Supply chain reliability: A key est quintile in some cases. The general pattern concern for all countries suggests that supply chain predictability is an acute commercial problem but may be moving Logistics performance is strongly associated in the right direction in the lowest-performing with supply chain reliability and predictable countries. shipment delivery. The causes of delays identi- Predictable, reliable supply chains are cen- fied in the survey are more worrisome in the tral to good logistics performance. Indeed, three bottom performance quintiles than in highly uncertain lead times can disrupt pro- the top performers or even the second quintile. duction and exporting, forcing firms to adopt Some causes of delays or unreliability are en- costly strategies such as express shipping or dogenous to a country’s supply chain: the qual- sharply higher inventories, eroding competi- ity of service and the cost and speed of clearance tiveness within global and regional value chains processes are examples. But other causes, such that use just-in-time production. Although as dependence on indirect maritime routes, lie firms can adopt strategies, such as building in outside the domestic supply chain and are not redundancies to deal with disruptions affecting under a country’s control. one supplier, countries that want their firms to The LPI details possible causes of delay not join, and move up in, global and regional value directly related to how domestic services and chains must provide the conditions for predict- agencies perform (table 2.7). Again, the con- able, reliable supply chains. trast is striking between the top and bottom An additional reason for policy makers LPI quintiles, especially in three areas: informal to focus greater attention on supply chain re- (corrupt) payments, compulsory warehousing, liability and predictability is the emerging and preshipment inspection. The first two over- networked structure of global and regional lap with the problems identified in previous LPI trade, linked in part to the rise of value chains. reports. Since the 2016 report, reported delays In a network, small disruptions at one link can in the bottom quintile declined considerably, spread rapidly and sometimes unpredictably to Table 2.7 Respondents reporting that shipments are “often” or “nearly always” delayed, by delay category and LPI quintile Percent of respondents Compulsory Preshipment Maritime Informal LPI quintile warehousing inspection transshipment Theft payments Bottom quintile 26 20 11 8 13 Fourth quintile 27 21 13 5 30 Third quintile 23 27 14 14 22 Second quintile 14 13 18 5 13 Top quintile 5 5 6 2 3 Source: Logistics Performance Index 2018. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 27 In the top quintile, most other links. The efficiency gains associated with importance of low-performing countries taking respondents report networked production models thus come with steps to improve predictability and reliability of increased systemic risk, because the structure supply chains, to continue narrowing this part that import and export itself can be vulnerable to small shocks affect- of the logistics gap. shipments “always” or ing crucial links. Countries that cannot pro- The fourth LPI quintile has the largest dif- “nearly always” arrive vide the conditions for developing predictable ference between on-schedule arrival rates for ex- and reliable supply chains will become increas- ports and those for imports (see figure 2.10), as on schedule, but in the ingly disconnected from world markets, where in the previous LPI report. The bottom quintile bottom quintile, only networked production models are common. has a substantially narrower gap. A lower rate around half as many do Low-­ performing countries need greater policy of favorable survey responses for imports sug- attention to improve their connectivity and to gests that supply chain unreliability discrimi- stem any further marginalization in the global nates in practice (if not in law) against foreign trading system. goods. As traditional trade barriers continue Supply chain reliability and predictability to fall around the world, policies contributing are further reflected in a key performance met- to such other barriers become ever larger deter- ric from the domestic LPI, timeliness of clear- minants of performance and trade outcomes. ance and delivery (figure 2.10). Given that the So, addressing the causes of unexpected delays­ frequency of delays tends to rise with declining —­ including unpredictability in clearance, in- logistics performance, it is unsurprising that land transit delays, and low service reliability­—­ the timeliness of clearance and delivery gener- should be an important part of logistics reform ally suffers as one moves down the LPI quintiles. in low-performing countries. In the top quintile, most respondents report The patterns for supply chain reliability are that import and export shipments “always” or more striking in some World Bank regions than “nearly always” arrive on schedule, but in the others (figure 2.11). The geographic predictabil- bottom quintile, only around half as many do. ity gap may influence competitiveness and the However, compared with the 2016 LPI report, spread of regional supply chains and produc- performance in the low and middle quintiles tion networks. However, caution is appropriate is noticeably improved, so some convergence is in approaching figure 2.11 because the data vary taking place. This finding again highlights the considerably from one year to another, in part Figure 2.10 Respondents reporting that shipments are “often” or “nearly always” cleared and delivered as scheduled, by LPI quintile Imports Exports Respondents reporting that shipments are “often” or “nearly always” cleared and delivered as scheduled, by LPI quintile 100 75 50 25 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2018. 28 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Figure 2.11 Respondents reporting that shipments are “often” or “nearly always” cleared and delivered as scheduled, by World Bank developing country region Percent of respondents Imports Exports 100 75 50 25 0 East Asia Europe and Latin America Middle East and South Sub-Saharan and Pacific Central Asia and Caribbean North Africa Asia Africa Source: Logistics Performance Index 2018. due to differences in response patterns across meet company quality criteria. However, perfor- countries. mance in the bottom quintile has improved no- Supply chain quality is not just a matter of ticeably since the 2016 LPI, while the result for time and cost. A further consideration­ —­for the fourth quintile appears anomalous­ —­it has private sector operators and their clients­ —­ is the highest percentage failing to meet company shipment predictability, which varied widely quality criteria. This finding again illustrates in the 2018 LPI, as in previous reports (figure that the logistics gap is real but perhaps narrow- 2.12). In the top LPI quintile, just 13 percent of ing from an overall perspective of supply chain shipments fail to meet company quality criteria­ efficiency and reliability. —­ the same proportion as previously. Twice as The most important quality criterion many shipments in the bottom quintile fail to in freight forwarding is delivery within the Figure 2.12 Shipments not meeting company quality criteria, by LPI quintile Percent 40 30 20 10 0 Bottom quintile Fourth quintile Third quintile Second quintile Top quintile (lowest performance) (low performance) (average performance) (high performance) (highest performance) Source: Logistics Performance Index 2018. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 29 promised time window. Almost as important tolerated, in high-performing countries than is the absence of errors in cargo composition or in low-performing countries. The shipment documentation. The window of acceptable qual- quality gap only partly reflects these differing ity is much narrower, and errors are much less expectations. 30 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Logistics trends, reform 3 implementation, and the SECTION Logistics Performance Index The global logistics landscape displays positive Shifting priorities trends, even though disparities remain between the top performers and many developing coun- Global logistics has changed in big ways since tries. In developing countries, the logistics the first LPI report. The 2008–09 trade crunch agenda appears even more prominent today that ended an era of fast growing international than it was in 2007, as interventions expand trade put pressure on traditional actors. And with changes in demand, changes in industry, new players and new business models, such as and the increasingly central role of sustainabil- e-commerce, have emerged. Technology and ity-related concerns. Often motivated by the new concerns about supply chain resilience Logistics Performance Index, national gov- drive industry changes and reshape the policy ernments and regional groups are promoting agenda. reform. And international organizations­ —­the Organisation for Economic Co-operation and Megatrends and policies Development (OECD), the United Nations A recent publication by the World Economic Conference on Trade and Development, the Forum, prepared by leading experts, identified World Bank, and regional development banks­ eight megatrends likely to drive the future of —­are supporting them. logistics: 1. Logistics skill shortages. The LPI: Stimulating and 2. Restructuring global value chains. informing reforms 3. Supply risk and recovery (resilience). 4. Digital transformation of supply chains. Since their inception, the LPI and its concep- 5. Sustainability of supply chains. tual framework have motivated comprehensive 6. E-commerce driving demand chains. reforms, as in India and Oman (for Oman, see 7. Logistics property and infrastructure. box 3.3 below). Since 2016, India has empha- 8. Collaborative business models.10 sized logistics among its high-priority economic Most of these trends are directly relevant reforms to meet challenges of large country size, for the logistics policy agenda. So, the 2018 LPI congested hubs, and internal barriers to trading survey asked about the drivers of change for good and services. To complement the ground- freight forwarding services. Most respondents breaking unification of the sales tax across across country income groups see the demand states, the government of India appointed a for services growing, fueled by the expansion of Special Secretary for logistics, in charge of cross- e-commerce (figure 3.1). cutting policies and coordination. And in 2018, the government commissioned a subnational The importance of skill development for LPI, applying the World Bank LPI concept.8 logistics The LPI and related datasets produced at Despite extensive mechanization and auto- the World Bank9 are widely used as inputs for mation, logistics remains a people business. analytical policy work and in academic research Logistics at an operational level is labor- in areas such as transportation, operations re- intensive, with many blue-collar workers (such search, and trade (box 3.1). as truck drivers and warehouse operators) and C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 31 Box 3.1 Use of the LPI in research and policy-making literature Since its launch in 2007, the LPI has established itself as an impor- the Asian Development Bank, the African Development Bank, the tant source of global trade and transport facilitation and logistics Inter-American Development Bank, the United Nations Economic performance indicators for policy makers, academics, logistics Commission for Europe, the United Nations Commission on Trade practitioners, and traders. It is also used by advocacy groups. Al- and Development, and the United Nations Economic and Social most 90 research or policy-making publications since 2008 have Commission for Asia and the Pacific­ —­ include the LPI as a regular used LPI data (see figure), in addition to several textbooks and many element in their trade and transport publications. In addition, large materials and theses. and small consultancies and several logistics firms, regularly in- clude LPI data in their reports. Use of LPI in the research and Thematically, the use of LPI can broadly be arranged into two policy making literature, 2008–18 main categories: trade and transport facilitation and supply chain management, transport, and logistics competitiveness (see table). Number of articles and reports In more than 40 publications, LPI data are the main empirical evi- 100 dence, and an almost equal number use the data as a reference. Most of the publications are academic papers that may address both categories. A non-exhaustive list of the references is in ap- 75 pendix 7. Thematic division of use of LPI in the research and 50 policy making literature Trade economics, SCM/logistics/transport and trade and transport competitiveness issues on 25 facilitation and similar national or industry levels Total Main empirical 27 14 41 data 0 2008 2010 2012 2014 2016 2018 Major reference 21 13 34 Source: World Bank staff calculations. data Minor 2 11 13 reference The LPI is also a component in various trade and transport in- Total 50 38 88 dicators, such as the World Economic Forum Enabling Trade Index, first published in 2008, and the European Union Transport Score- a. The World Economic Forum’s Enabling Trade Index has used the LPI three board, launched in 2014.a Almost all multilateral agencies­ —­such as times, and the European Union Transport Scoreboard twice. administrative clerks. The quality, training, and years. Respondents in developing countries see retention of these employees is a major factor in the most severe skill shortage at the managerial logistics performance. Lower-quality service level­—­for example, in filling senior supply chain hurts production and international trade. Yet management positions. In developed countries, human resources, often overlooked or taken for the most severe shortage is for a qualified blue- granted, depend not only on the policies of com- collar workforce, such as truck drivers. panies but also on national initiatives to educate Reasons for the shortages include the low and train people for logistics occupations. prestige and status of operational logistics In 2017, the World Bank and the Kühne workers. The sector offers comparatively low Logistics University published a report on salaries, leading to an inferior position in the skills, competencies, and training in the logis- war for talent. Many developing countries, even tics sector.11 It highlighted a general perception if they suffer from high unemployment, have a that qualified logistics-related labor is in short limited supply of skilled labor. Logistics devel- supply at all levels in both developed and devel- opments, particularly in information technol- oping countries, suggesting that the problem ogy, demand new competencies that the work- is likely to remain or worsen over the next five force does not possess. Developing countries 32 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Figure 3.1 Increased use of electronic • Regulation of freight and logistics services, In the current era of trading platforms (business to including customs brokerage and trucking. globalization, extended business and business to • Setting and harmonizing competency stan- consumer) by shippers mean that supply chains have created our business volumes have… dards for different jobs.
 • Raising skill levels in state-owned logistics more interdependence, (Much) decreased Stayed about enterprises (typically ports and railways). and commerce and Percent of respondents (Much) increased the same • Investing in human capital as a compo- 100 production have been nent of the development of logistics and freight 
infrastructure. disrupted by natural events 75 As part of its country work, the World Bank and man-made disasters recently began to offer a comprehensive assess- ment of skills and competencies at the national 50 level to support logistics improvements (box 3.2). It pinpoints labor skills and constraints in 25 logistics jobs and suggests priorities for inter- vention to upgrade skills. 0 Supply chain resilience Low Lower Upper High income middle income Commerce and production have been dis- middle income income Source: Logistics Performance Index 2018. rupted by natural events and man-made disasters, such as civil wars or, recently, cyber­ lag behind developed ones in training budgets, disasters. In the current era of globalization, course content, and the quality of the educa- extended supply chains have created more tional experience and training provider. Voca- interdependence. Local events create dis- tional schools for logistics jobs are lacking. And turbances much beyond the area directly training­ —­ —­ if there is any­ is limited to short- affected when supply chains are interrupted term, on-the-job instruction by colleagues dur- with no backup. In 2010, the eruptions of the ing daily operations. This failure disproportion- ­ Eyjafjallajökull volcano in Iceland grounded ally affects the young, an untapped reservoir of most European air transportation for weeks apprentices. and broke the air cargo export supply chains National governments and international of many African developing countries for sev- agencies have traditionally paid more attention eral weeks. In 2011, the tsunami in Japan and to infrastructure and trade facilitation than to the floods in Thailand disrupted trade by strik- fostering quality services and a skilled work- ing key nodes of global value chains. In such force. Employees are hired by private companies, severe events, supply chain links can take a and their training is largely a private responsi- long time to rebuild and may even be perma- bility. But governments play an important role nently altered. directly by regulating or providing training­ —­ The resilience of international and domes- and indirectly by facilitating private initiatives. tic supply chains is thus emerging as a policy Developing countries need a major expansion of concern, requiring measures by government logistics training and skill development initia- agencies and private companies, as in Canada, tives. Public interventions promoting logistics Japan, the Nordic countries, and the United competence include the following: States. • Education and training by public institu- In mid-2017, cyberattacks on global tions, or financial support to training. providers created significant physical supply • Education policy and curricula develop- chain disruption for weeks, so the 2018 LPI ment. survey included a question on the importance • Advocacy, public–private dialogue, and of resilience in cybersecurity. The perceived multi-stakeholder collaboration. magnitude of cyberthreat and preparedness C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 33 to respond go hand in hand, and developing (figure 3.4). This trend is good news, as logis- countries lag behind (figures 3.2 and 3.3). tics has a fairly large footprint not only on the economy but also on the environment. Environmental sustainability of logistics This edition of Connecting to Compete, like Asking for green logistics? the three previous editions, included a question Emissions from all logistics activities are hard on the demand for environmentally friendly to measure, but transport offers a good proxy: international logistics. The results are consis- 23 percent of all energy-related emissions can be tent: Environmentally friendly supply chains attributed to transport,12 and about 7 percent are associated with higher logistics performance of global CO2 emissions can be attributed to freight transport,13 which is estimated to have Figure 3.2 Cybersecurity threats in logistics emitted 3.2 gigatons of CO2 in 2015.14 This have… number is estimated to rise in the next decades, with a higher growth in emerging economies (Much) decreased Stayed about Percent of respondents (Much) increased the same than in Europe. 100 In top-quintile countries, 28  percent of respondents indicated in 2018 that shippers often or nearly always ask for environmentally 75 friendly shipping options­ —­in emission levels and choices of routes, vehicles, and schedules (down from 34  percent in 2016). The share 50 drops to 14 percent in second-quintile coun- tries, and then steadily declines in the third 25 (9 percent), fourth (7 percent) and fifth (5 per- cent) quintiles (see figure 3.4). The picture is slightly more balanced for re- 0 Low Lower Upper High spondents answering that shippers “sometimes” income middle income middle income income ask for environmentally sustainable shipping Source: Logistics Performance Index 2018. options, ranging from 27  percent in the top quintile and 21  percent in the bottom one. Figure 3.3 Our firm’s preparedness for cyberthreats has… Figure 3.4 The demand for green logistics (Much) decreased Stayed about Often or nearly always Sometimes Percent of respondents (Much) increased the same Percent of respondents Hardly ever or rarely 100 100 75 75 50 50 25 25 0 0 Low Lower Upper High Bottom Fourth Third Second Top income middle income middle income income quintile quintile quintile quintile quintile Source: Logistics Performance Index 2018. Source: Logistics Performance Index 2018. 34 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Box 3.2 Assessing logistics skills, competencies, and training: A new toolkit In 2017, to support logistics service improvements, the World Bank interviews, each assessment area is assigned a maturity level on introduced the “Logistics skills, competencies, and training tool- a scale from 1 to 5 (from minimal capacity to global best practice). kit,” which was co-developed with the Kühne Logistics University. An assessment report is then prepared, with recommendations The toolkit systematically evaluates logistics skill requirements, as- for policy responses. sesses whether they are being met by current training and educa- To test the toolkit, a pilot study was performed in 2017 in Togo, tion, and suggests priority areas for intervention to upgrade logistics a small, Sub-­ Saharan economy located between Benin and Ghana. skills. It has a population of around 7.8 million, nearly 60 percent younger The toolkit assesses 20 areas, tailoring the assessment to than 25. Because Togo exports phosphates, cocoa, coffee, and interviewees not knowledgeable about every area (see table). cotton, logistics is a key to economic prosperity. The toolkit en- The toolkit mainly relies on qualitative data obtained from abled a useful scan of the skills and competencies in logistics, and interviews with logistics stakeholders, such as shippers, re- provided valuable policy insights on how to address educational cruitment agencies, educational institutions, professional asso- and training needs. ciations, logistics service providers, and government ministries dealing with transport and professional training. Following the Source: World Bank 2017b. Areas assessed by the logistics skills, competencies, and training toolkit Recruitment of operative Skill level of existing operative Recruitment of administrative Skill level of existing logistics staff logistics employees logistics staff administrative employees Demand Recruitment of logistics Skill level of existing logistics Skill level of logistics Recruitment of logistics managers supervisors supervisory employees managers currently in post Availability of vocational Quality of vocational Availability of logistics education Quality of logistics education education in logistics education in logistics by private training providers by private training providers Supply Availability of logistics Quality of logistics education Availability of in-house training Quality of in-house training education by universities by universities Certification of logistics skills Role of associations Attractiveness of logistics industry Availability of recruitment services Higher costs and fewer choices for shipping are named, they influence several of the 17 SDGs: likely the chief culprits for the discrepancy be- 7, affordable and clean energy; 9, industry, in- tween higher and lower performing countries, novation, and infrastructure; 11, sustainable as are fears of adding transit time in an already cities and communities; 12, responsible con- long and unpredictable supply chain. sumption and production; and 13, climate action. Reducing the logistics footprint Several organizations focused on specific Decarbonization measures can curb the detri- modes of transport (road, rail, air, and mari- mental effect of freight transport. They include time, including seaports) reference the SDGs. improved asset utilization in logistics (such as They include the International Civil Aviation for storage and handling), higher energy effi- Organization in its 2030 Agenda for Sustain- ciency of road and rail freight, low-carbon able Development through promoting sustain- energy for ships (such as biofuels), fuel efficiency able air transport.16 For maritime shipping, in air cargo, and modal shifts (a moving higher the International Maritime Organization for- proportion of freight to modes with lower car- mulates maritime policies and in April 2018 bon intensity). 15 adopted an initial strategy to halve emissions Climate change mitigation also features in from maritime transport by 2050 from the the United Nations Sustainable Development 2008 level.17 Goals (SDGs) adopted in September 2015. In addition, the worldwide port industry While transport and logistics are not explicitly launched its SDG initiative called the World C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 35 While the development of Ports Sustainability Program in March 2018.18 competitiveness), environmentally (air pollu- connecting infrastructure The road transport industry is recognizing the tion and noise), and socially (quality of life and SDG, too: its primary organization, the Inter- health). Hence, the sharper focus on urban lo- remains a central national Road Transport Union, is promoting gistics and the spatial planning of logistics facili- concern, middle-income the agenda among its members and in coopera- ties, as in logistics centers and zones. countries have to deal tion with relevant bodies, such as the United Nations Economic Commission for Europe.19 Managing the complexity with an increasingly Other international bodies that have green of implementation complex set of policies logistics and transport on their agenda include the International Energy Agency (IEA) and the The initial focus of logistics related reform International Transport Forum (ITF), both emphasized building connecting infrastructure linked to the OECD. 20 The IEA’s guidance and facilitating trade at the border. That tradi- for countries to reduce dependence on oil and tional agenda remains important for developing greenhouse gas emissions runs under the theme, countries, especially for low logistics performers “Avoid, Shift, Improve.” Its recent transport (see section 2), and is still at the core of interven- policy reports include “The Future of Trucks,” tions of international organizations. Connecting which highlights how improved efficiency and infrastructure in developing countries is a high alternative truck fuels can help meet environ- priority of development partners. It is also tar- mental objectives, 21 and the “Global EV Out- geted by the major connectivity initiatives such look 2017,” which features recent developments as the Belt and Road. Trade facilitation good of electric vehicles as well as market and policy practices have been spelled out in documents and implications.22 conventions by specialized international organi- The ITF launched its “Decarbonizing zations such as the United Nations Economic Transport” initiative in 2016, with the goal Commission for Europe and the World Cus- of achieving zero transport emissions around toms Organization since the 1970s. Regulatory 2050. At the heart of the project are tools to en- reforms of the logistics services sectors are also able decisionmakers to select the most fitting key to logistics performance, as advocated in pre- CO2 reduction measures. The initiative focuses vious editions of Connecting to Compete. Regula- on assessing the impacts of CO2 reducing mea- tory improvements aim to enhance the quality of sures, not on advocating specific measures. service delivery, building on market mechanisms Country-level examples include the Nordic and private sector participation. These reforms countries­ —­ Denmark, Finland, Iceland, Nor- are nevertheless challenging to implement in way, and Sweden­ —­ which have embraced the many developing countries. They deal with sec- goal of being fossil free by 2050.23 While 87 per- tors such as trucking, brokerage, and terminal or cent of electricity generated across the Nordic warehousing operations, which in many places countries is already carbon-free, several chal- operate with limited efficiency and with barriers lenges remain: the variability of wind energy in to modernization or entry of new services. Denmark, the reliance on biomass and forestry The emerging policy areas, such as resilience products in Finland, and the investments in oil and urban logistics, are at least as relevant to de- and hydropower in Norway. veloping countries as to developed countries. The logistics footprint is also spatial, requir- The network nature of logistics means that stan- ing large land areas for facilities such as ware- dards and business models applicable in high- houses, and transport connections to and from performing countries will soon appear in lower- them. Logistics not only competes for space performing countries. with industry and commerce, but also gener- ates traffic in high-density areas. With grow- Managing logistics as a sector of the ing urbanization in developing countries, rap- economy idly increasing urban freight transport has a big Countries aiming at improving their logistics impact economically (inefficiencies and urban performance must see logistics as a cross-cutting 36 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y policy concern. The work crosses administrative develop and refine national strategies. Morocco boundaries of transportation, commerce, infra- set up a dedicated agency in 2013 to promote structure, industry, finance, and the environ- the logistics sector. Dinalog in the Netherlands­ ment. And it requires mechanisms to involve —­a partnership of the private sector, academia, the private sector (box 3.3). and government agencies with shared funding­ The complexity of the agenda is likely to —­ develops strategy, promotes innovation, con- challenge countries in the second and third LPI solidates knowledge and data, and facilitates performance tiers most. Their policy-­ making investments.24 has to reconcile the need for consistency and Another question is the legal and regulatory depth of reforms with a set of priorities wider status of logistics as a sector of the economy. than those facing top performers, which are far- Logistics encompasses specific activities, cre- ther along, or countries in the two bottom tiers, ates new concerns because of its footprint, and which can focus on fewer issues. brings new types of services. Very specific logis- National logistics bodies exist in several tics regulations apply to services, to movements countries. They help address the cross-cutting of goods, and to facilities and assets. But tradi- nature of logistics, set common strategies, in- tional transport, commerce, urban, and fiscal sure consistency across sectors, and address gaps provisions rarely consider logistics as an activ- not crossed by other agencies. China has a large ity or service. Many countries with an emerging government-related Federation of Logistics and modern logistics sectors are promoting a frame- Purchasing. Association of Southeast Asian work law to clarify the status of logistics and Nations countries have consultative bodies to to improve consistency with other regulatory Box 3.3 Logistics policy making in Oman In response to declining hydrocarbon revenues and a rising need along four pillars: markets, trade facilitation, human capital, and to diversify away from oil, Oman is improving its logistics perfor- technology applications. mance. In the first Connecting to Compete in 2007, it ranked 48th, Continuous interaction between the public and private sec- and in 2018, 43rd. tors rapidly built trust among stakeholders. The logistics sector Given that Oman was an international logistics hub in the 16th has grown faster (10 percent from 2016 to 2017) than the overall century, and wanting to capitalize on Oman’s geographical position, economy (8 percent), and the awareness of logistics has increased. the Omani government started work on a National Logistics Strat- The next step under the National Logistics Strategy is to estab- egy in December 2013. The government was particularly interested lish Oman as an international logistics hub. Oman is not aiming to in how to profit from Oman’s political environment and its previous directly challenge the United Arab Emirates, especially in air freight, investments in infrastructure. but to act as a complementary second hub. Oman’s Liner Ship- Oman’s National Logistics Strategy 2040 (SOLS 2040) was de- ping Connectivity Index has improved in recent years (63.6 in 2017), veloped in consultation with 65 specialists from the private sector, slightly ahead of Saudi Arabia (59.5), but still behind the United Arab government, and academia. It was approved in February 2015 and Emirates (73.7). Significant shares of Omani imports and exports are confirmed as a part of a five-year plan (2016–20) in the National Pro- routed through the UAE ports of Jebel Ali and Sharjah. The Omani gram for Enhancing Economic Diversification (Tanfeedh). Oman’s government plans to further develop a 2,244 km rail network to link strategy targets the five sectors with the most growth potential: Oman to the GCC rail network and to connect Oman’s major ports, manufacturing, tourism, mining, fisheries, and transport and logis- industrial areas, and free zones at Sohar, Salalah, and Duqm. Oman tics. It aims to boost investment, create job opportunities, and in- hopes to reduce shipping times to the Upper Gulf by 2–10 days by crease their contribution to GDP. offering significantly lower costs.a SOLS 2040 identifies the need for integrated development of Source: Al-Futaisi and Salem 2015; UNCTAD 2017; http:// transport and distribution and of supporting soft infrastructure. The www.tanfeedh.gov.om/en/news-National-programme-Tanfeedh-to approach requires integrating transport modes and infrastructure, -enhance.php; https://www.isc.hbs.edu/resources/courses/ depots, terminals, ports, customs and legal procedures, finance moc-course-at-harvard/Documents/pdf/student-projects/UAE_ and insurance, information technology, security, and such interme- TransportLogisticsCluster_2007.pdf. diaries as freight forwarders. The implementation of SOLS 2040 was entrusted to the Oman Logistics Center, a focal agency for simplify- a. Based on a benchmark voyage direct from Singapore to Suez with no Mid- ing, harmonizing, and automating government logistics processes dle East call. Ports Benchmarking Study 2014, Mercator International LLC. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 37 Table 3.1 Interaction of LPI performance quintile and logistics priorities • • • Very important  • • Important  • Less important Lowest performer Fourth Third Second Best performer Transportation infrastructure ••• ••• •• •• •• Trade and transport facilitation ••• ••• •• • • Service markets and regulations •• ••• ••• • • Skills •• ••• ••• ••• • Green logistics • • •• •• ••• Urban logistics • •• ••• ••• ••• Spatial planning • • •• •• •• Resilience •• •• •• •• •• Dedicated logistics body • • ••• ••• •• Specific legal framework • • •• •• • National data system •• •• ••• ••• ••• areas. Greece and Morocco have done so re- Transforming the massive raw data on individ- cently. Despite limited experience, a framework ual movements into relevant decision-oriented legal instrument should be carefully evaluated. dashboards is a major technical and organiza- tional challenge, with limited experience so far Informing reforms with data and few established methodologies or guide- Data are essential for motivating, designing, and lines. Exceptions include South Africa and monitoring policy changes. Logistics observa- Canada, which have performance-monitoring tories, implemented in Asia, Europe, and Latin systems for their internal logistics networks America, typically rely on national surveys and based on micro-­ logistics data.26 And Finland’s the maintenance of a few key performance indi- large-scale biennial national logistics surveys are cators based on existing data.25 in the public domain.27 One of the biggest changes since the 2007 Connecting to Compete is a quantum shift of *    *    * country-specific logistics data from scarce to abundant. The automation of supply chain pro- More advanced economies deal with a broader cessing and the spread of tracking and tracing array of policies addressing the performance almost globally provide micro-level data on and externalities of domestic supply chains logistics that can be used to evaluate not only than lower logistics performers. Table 3.1 sum- international gateways and corridors but also marizes how logistics priorities connect with supply chain connectivity within countries. logistics performance. 38 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Notes 1 Boston Consulting Group 2016. 10 WEF 2017. 2 This section uses single-year results for 2018 rather than 11 McKinnon and others 2017. the aggregated 2012–18 LPI. 12 ITF 2016b. 3 The ranking of countries by LPI score uses the weighted 13 ITF 2016a. aggregate value of the scores from the four most recent LPI surveys, with greatest weight given to 2018. This 14 McKinnon 2018, p. 9. reduces the noise and random variation across different 15 McKinnon 2018, p. 15 editions of LPI surveys to provide a more balanced 16 ICAO n.d. picture. 17 IMO 2018. 4 Boston Consulting Group 2016. 18 World Ports Sustainability Program, available at: 5 In 2018, the number of respondents from low-Income https://www.wpspevent.org/home countries was smaller than in 2016 (but close to the 19 IRU 2017. number in 2014). This may have generated more “noise” in the 2018 data, so the findings should be treated with 20 Not all OECD members are members of the IEA or the caution. ITF. Both organizations can have members that are not members of the OECD. 6 The respondents in the LPI survey are freight forwarders and express carriers, so the quality and competence of 21 IEA 2017a. these service providers are assessed by their peers. 22 IEA 2017b. 7 Lead time to import is the median time for shipments from 23 European Commission DG (Directorate-General) port of discharge to arrival at the consignee. Environment News Alert Service 2017. 8 See https://economictimes.indiatimes.com/news/ 24 See http://www.dinalog.org. economy/policy/government-ropes-in-deloitte-to-rank- 25 ITF 2016. states-on-logistics/articleshow/59552798.cms. 26 Arvis and others 2016. 9 The World Bank–UNESCAP International Trade Costs database is available at http://databank.worldbank.org/ 27 In English at https://blogit.utu.fi/logistiikkaselvitys/ data/reports.aspx?source=escap-world-bank en/225-2/. -international-trade-costs. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 39 Aggregated international LPI APPENDIX 1 results across four editions: 2012, 2014, 2016, and 2018 International Logistics quality Tracking and Mean Mean % of Customs Infrastructure shipments and competence tracing Timeliness LPI LPI highest Missing Economy rank score performer Rank Score Rank Score Rank Score Rank Score Rank Score Rank Score values Germany 1 4.19 100.0 1 4.09 1 4.38 4 3.83 1 4.26 1 4.22 1 4.40 Netherlands 2 4.07 97.2 3 3.97 2 4.23 6 3.76 2 4.12 7 4.08 6 4.30 Sweden 3 4.07 97.2 4 3.95 3 4.22 2 3.88 5 4.04 11 4.02 4 4.32 Belgium 4 4.05 96.9 13 3.74 10 4.03 1 3.97 3 4.10 4 4.11 2 4.40 Singapore 5 4.05 96.6 2 4.00 5 4.14 8 3.72 4 4.08 8 4.05 3 4.34 United Kingdom 6 4.01 95.7 8 3.85 7 4.09 10 3.69 7 4.04 5 4.10 5 4.32 Japan 7 3.99 95.3 5 3.91 4 4.19 14 3.61 8 4.03 9 4.03 9 4.24 Austria 8 3.99 95.2 14 3.71 8 4.07 5 3.78 6 4.04 2 4.13 11 4.22 Hong Kong SAR, China 9 3.96 94.6 9 3.85 11 4.02 3 3.85 10 3.94 13 3.95 13 4.18 United States 10 3.92 93.7 11 3.76 6 4.10 23 3.54 11 3.93 3 4.13 16 4.14 Denmark 11 3.92 93.6 7 3.88 17 3.89 16 3.59 9 3.98 14 3.94 8 4.26 Finland 12 3.92 93.5 6 3.89 14 3.95 21 3.56 14 3.88 6 4.10 15 4.17 Switzerland 13 3.91 93.4 12 3.75 9 4.07 20 3.57 12 3.92 10 4.02 12 4.20 United Arab Emirates 14 3.89 92.8 17 3.66 13 3.98 7 3.76 16 3.83 16 3.89 10 4.23 France 15 3.86 92.2 18 3.63 12 4.00 15 3.60 17 3.82 12 3.99 14 4.17 Luxembourg 16 3.84 91.8 16 3.67 18 3.84 11 3.68 15 3.83 22 3.78 7 4.27 Canada 17 3.81 90.9 15 3.70 16 3.91 28 3.45 13 3.90 15 3.91 21 4.03 Spain 18 3.78 90.3 21 3.57 22 3.79 9 3.72 18 3.78 21 3.78 19 4.04 Australia 19 3.77 90.0 10 3.76 15 3.92 31 3.40 19 3.76 19 3.83 22 4.00 Norway 20 3.74 89.3 19 3.62 19 3.84 27 3.48 20 3.75 18 3.83 25 3.96 Italy 21 3.73 89.2 23 3.44 20 3.82 22 3.55 23 3.68 17 3.84 18 4.09 New Zealand 22 3.68 88.0 20 3.58 21 3.79 36 3.27 21 3.69 24 3.73 17 4.10 Korea, Rep. 23 3.65 87.3 24 3.43 23 3.75 29 3.43 26 3.63 23 3.75 24 3.96 Taiwan, China 24 3.65 87.2 25 3.42 25 3.67 24 3.54 24 3.68 27 3.67 27 3.93 Ireland 25 3.63 86.8 22 3.45 26 3.50 25 3.53 22 3.69 20 3.79 30 3.85 Czech Republic 26 3.62 86.4 26 3.34 29 3.38 12 3.65 25 3.65 26 3.68 23 3.98 China 27 3.60 86.1 30 3.28 24 3.73 18 3.57 27 3.58 28 3.63 29 3.86 Portugal 28 3.56 85.1 32 3.24 35 3.23 17 3.59 28 3.54 25 3.69 20 4.03 South Africa 29 3.51 83.8 29 3.29 28 3.39 26 3.53 33 3.42 30 3.56 31 3.85 Qatar 30 3.50 83.7 35 3.18 27 3.43 13 3.62 31 3.46 31 3.53 34 3.78 Poland 31 3.50 83.5 31 3.26 40 3.17 19 3.57 29 3.49 33 3.49 26 3.94 Hungary 32 3.41 81.5 36 3.18 32 3.31 35 3.29 36 3.27 29 3.61 32 3.82 Israel 33 3.39 81.0 27 3.32 31 3.33 61 2.93 32 3.44 32 3.50 28 3.89 2012 Thailand 34 3.36 80.2 37 3.13 41 3.17 32 3.40 35 3.29 35 3.38 36 3.75 Malaysia 35 3.34 79.9 38 3.06 33 3.30 30 3.43 34 3.34 38 3.32 46 3.60 Estonia 36 3.30 78.8 28 3.30 43 3.13 41 3.19 42 3.15 46 3.20 33 3.80 Turkey 37 3.29 78.6 47 2.94 30 3.36 40 3.19 37 3.23 36 3.37 39 3.68 Iceland 38 3.29 78.6 40 3.02 39 3.18 55 3.00 30 3.48 34 3.38 38 3.72 Slovenia 39 3.29 78.5 34 3.21 34 3.25 44 3.16 41 3.17 40 3.30 41 3.65 Chile 40 3.28 78.4 33 3.23 45 3.09 37 3.24 47 3.09 39 3.30 37 3.73 Panama 41 3.26 77.8 44 2.95 42 3.14 33 3.35 38 3.20 43 3.25 42 3.63 40 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Appendix 1  Aggregated international LPI results International Logistics quality Tracking and Mean Mean % of Customs Infrastructure shipments and competence tracing Timeliness LPI LPI highest Missing Economy rank score performer Rank Score Rank Score Rank Score Rank Score Rank Score Rank Score values India 42 3.22 77.0 43 2.97 48 3.01 38 3.24 39 3.18 37 3.33 50 3.57 Lithuania 43 3.20 76.4 41 3.02 49 3.00 54 3.03 45 3.10 42 3.25 35 3.78 Greece 44 3.19 76.2 49 2.88 36 3.19 48 3.13 52 3.02 41 3.25 40 3.67 Vietnam 45 3.16 75.5 51 2.86 54 2.92 45 3.15 40 3.17 44 3.23 47 3.60 Oman 46 3.16 75.5 52 2.82 37 3.18 34 3.29 50 3.06 60 2.96 44 3.61 Slovak Republic 47 3.14 75.0 46 2.94 44 3.09 42 3.19 43 3.13 57 3.02 54 3.45 Croatia 48 3.12 74.4 42 3.01 47 3.02 56 2.99 44 3.10 55 3.08 51 3.51 Cyprus 49 3.10 74.0 39 3.04 53 2.94 53 3.04 58 2.93 59 2.98 43 3.62 Romania 50 3.10 74.0 58 2.73 58 2.86 46 3.15 53 3.01 48 3.19 45 3.61 Indonesia 51 3.08 73.6 62 2.69 61 2.81 51 3.08 48 3.07 45 3.23 49 3.59 Saudi Arabia 52 3.08 73.6 60 2.70 38 3.18 52 3.05 57 2.94 47 3.19 56 3.43 Mexico 53 3.08 73.6 54 2.78 56 2.90 50 3.09 49 3.06 51 3.14 52 3.49 Bahrain 54 3.06 73.2 50 2.88 57 2.89 49 3.09 51 3.03 50 3.16 66 3.31 Latvia 55 3.02 72.3 48 2.93 46 3.03 57 2.97 59 2.92 56 3.06 69 3.25 Brazil 56 3.02 72.1 85 2.52 51 2.99 65 2.89 46 3.10 49 3.17 53 3.47 Bulgaria 57 3.00 71.7 55 2.77 64 2.71 43 3.16 54 2.96 63 2.93 57 3.43 Botswana 58 2.96 70.7 45 2.95 59 2.85 73 2.82 75 2.71 77 2.81 48 3.60 2018 Kuwait 59 2.96 70.6 57 2.75 50 3.00 62 2.91 63 2.81 66 2.88 59 3.39 Egypt, Arab Rep. 60 2.95 70.5 65 2.67 55 2.91 59 2.94 55 2.95 64 2.91 67 3.30 Malta 61 2.94 70.3 56 2.77 52 2.95 64 2.91 61 2.85 61 2.95 71 3.24 Argentina 62 2.93 70.0 90 2.49 60 2.81 63 2.91 62 2.82 52 3.13 58 3.41 Kenya 63 2.93 69.9 67 2.66 67 2.68 70 2.86 60 2.88 53 3.11 61 3.35 Philippines 64 2.91 69.6 70 2.62 71 2.67 39 3.20 64 2.80 58 3.01 83 3.11 Rwanda 65 2.90 69.3 64 2.68 76 2.60 47 3.14 69 2.77 73 2.83 64 3.31 Côte d'Ivoire 66 2.89 69.0 68 2.66 69 2.67 58 2.96 56 2.95 62 2.95 85 3.11 Tanzania 67 2.88 68.8 69 2.66 63 2.72 66 2.89 65 2.80 69 2.85 62 3.34 2018 Serbia 68 2.83 67.7 82 2.53 78 2.59 67 2.89 68 2.78 68 2.86 63 3.32 Ukraine 69 2.83 67.5 95 2.46 105 2.38 81 2.77 70 2.76 54 3.08 55 3.45 Ecuador 70 2.82 67.4 63 2.69 74 2.62 72 2.82 77 2.70 67 2.87 75 3.22 Colombia 71 2.81 67.1 89 2.50 81 2.58 60 2.93 66 2.79 70 2.84 80 3.17 Uganda 72 2.79 66.7 53 2.78 96 2.45 74 2.82 78 2.70 86 2.69 68 3.27 2012, 2014 Brunei Darussalam 73 2.78 66.5 61 2.70 77 2.59 84 2.74 84 2.64 75 2.82 78 3.18 2012, 2014 Peru 74 2.78 66.5 74 2.59 91 2.46 68 2.88 87 2.62 85 2.72 60 3.36 Uruguay 75 2.78 66.4 73 2.60 82 2.57 80 2.78 67 2.79 74 2.83 91 3.10 Jordan 76 2.78 66.3 87 2.51 65 2.70 86 2.74 83 2.67 79 2.79 70 3.24 Kazakhstan 77 2.77 66.2 78 2.57 79 2.59 87 2.73 89 2.60 78 2.81 65 3.31 Bosnia and Herzegovina 78 2.76 65.8 71 2.62 85 2.52 89 2.70 74 2.73 82 2.75 77 3.20 Costa Rica 79 2.74 65.4 88 2.50 97 2.45 77 2.79 81 2.67 65 2.88 92 3.09 Namibia 80 2.73 65.1 72 2.60 62 2.74 93 2.68 86 2.64 107 2.55 81 3.14 2018 Iran, Islamic Rep. 81 2.71 64.8 96 2.46 70 2.67 94 2.68 72 2.76 95 2.63 95 3.07 2014 Lebanon 82 2.71 64.7 98 2.45 75 2.61 82 2.77 103 2.52 72 2.83 98 3.05 Paraguay 83 2.70 64.6 80 2.53 87 2.50 101 2.66 76 2.70 105 2.56 73 3.23 Malawi 84 2.69 64.3 76 2.58 83 2.56 103 2.61 71 2.76 92 2.65 105 2.99 2016 Russian Federation 85 2.69 64.2 131 2.25 73 2.64 105 2.59 73 2.74 88 2.67 74 3.23 C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 41 Appendix 1  Aggregated international LPI results International Logistics quality Tracking and Mean Mean % of Customs Infrastructure shipments and competence tracing Timeliness LPI LPI highest Missing Economy rank score performer Rank Score Rank Score Rank Score Rank Score Rank Score Rank Score values Dominican Republic 86 2.68 64.1 102 2.43 102 2.39 83 2.77 93 2.59 71 2.84 99 3.03 Morocco 87 2.67 63.8 114 2.36 80 2.58 75 2.80 92 2.59 104 2.57 93 3.09 2014 El Salvador 88 2.66 63.6 105 2.40 113 2.31 76 2.79 82 2.67 94 2.63 88 3.10 Cambodia 89 2.66 63.5 94 2.47 120 2.26 69 2.87 106 2.50 93 2.64 82 3.13 Bahamas, The 90 2.65 63.3 59 2.72 84 2.56 100 2.66 105 2.51 102 2.58 118 2.87 Mauritius 91 2.65 63.3 86 2.51 68 2.68 137 2.35 79 2.69 84 2.72 106 2.98 2016 Sri Lanka 92 2.65 63.2 77 2.57 104 2.39 108 2.57 85 2.64 81 2.77 113 2.93 2016 Benin 93 2.65 63.2 93 2.48 94 2.45 98 2.66 107 2.50 101 2.58 79 3.17 Montenegro 94 2.65 63.2 91 2.49 93 2.46 92 2.68 97 2.55 108 2.55 84 3.11 Pakistan 95 2.64 62.9 104 2.41 100 2.43 79 2.79 80 2.69 112 2.52 112 2.93 Burkina Faso 96 2.63 62.9 101 2.44 89 2.48 78 2.79 96 2.56 126 2.42 97 3.06 Maldives 97 2.63 62.8 97 2.46 72 2.64 104 2.59 115 2.42 103 2.57 96 3.07 Albania 98 2.62 62.5 118 2.33 123 2.24 85 2.74 95 2.56 111 2.52 72 3.24 2014 Macedonia, FYR 99 2.62 62.5 115 2.36 86 2.51 96 2.66 90 2.60 113 2.52 100 3.01 Bangladesh 100 2.60 62.0 120 2.33 109 2.36 99 2.66 94 2.56 89 2.67 108 2.97 2012 Ghana 101 2.60 62.0 103 2.41 92 2.46 102 2.63 104 2.51 100 2.58 109 2.95 Mozambique 102 2.59 61.9 100 2.45 130 2.22 71 2.86 120 2.38 96 2.62 107 2.98 2012, 2018 Nigeria 103 2.59 61.8 145 2.15 88 2.50 118 2.52 100 2.54 83 2.73 86 3.10 Tunisia 104 2.59 61.8 130 2.27 117 2.27 115 2.53 113 2.45 80 2.78 76 3.20 São Tomé and Principe 105 2.56 61.3 83 2.52 114 2.30 130 2.44 99 2.55 90 2.66 116 2.90 Honduras 106 2.56 61.2 123 2.30 112 2.32 97 2.66 91 2.60 97 2.61 121 2.85 Algeria 107 2.56 61.1 127 2.28 95 2.45 113 2.54 101 2.53 91 2.65 117 2.89 Nicaragua 108 2.56 61.0 84 2.52 99 2.44 111 2.54 98 2.55 115 2.49 129 2.77 2012, 2018 Mali 109 2.55 60.9 136 2.22 116 2.28 95 2.66 117 2.40 76 2.81 119 2.87 2012 Belarus 110 2.54 60.6 126 2.29 103 2.39 124 2.47 102 2.53 124 2.44 87 3.10 Jamaica 111 2.52 60.3 99 2.45 106 2.36 114 2.53 110 2.48 120 2.48 123 2.81 Solomon Islands 112 2.52 60.2 66 2.66 125 2.23 151 2.24 88 2.61 131 2.37 102 3.00 Moldova 113 2.52 60.1 122 2.31 131 2.21 90 2.69 123 2.36 133 2.36 90 3.10 Comoros 114 2.51 60.1 75 2.58 119 2.27 123 2.47 129 2.32 87 2.67 132 2.74 Guatemala 115 2.51 59.9 116 2.35 118 2.27 126 2.46 125 2.35 117 2.49 89 3.10 Armenia 116 2.51 59.9 107 2.39 101 2.39 110 2.55 112 2.45 128 2.38 122 2.84 Uzbekistan 117 2.50 59.7 147 2.13 98 2.44 134 2.38 109 2.49 110 2.54 101 3.01 Zambia 118 2.49 59.4 129 2.27 115 2.29 88 2.72 111 2.46 154 2.18 110 2.94 2012 Togo 119 2.48 59.4 119 2.33 127 2.23 106 2.58 130 2.29 114 2.50 111 2.93 Lao PDR 120 2.48 59.2 111 2.37 128 2.23 116 2.52 114 2.45 119 2.48 130 2.77 Nepal 121 2.45 58.6 140 2.19 132 2.20 131 2.40 122 2.36 106 2.56 104 2.99 Guyana 122 2.45 58.6 92 2.48 134 2.17 138 2.35 121 2.36 109 2.55 127 2.79 Azerbaijan 123 2.45 58.5 81 2.53 66 2.69 109 2.56 153 2.14 153 2.18 146 2.62 2016, 2018 Georgia 124 2.45 58.5 109 2.38 108 2.36 132 2.38 139 2.27 130 2.37 114 2.92 Cameroon 125 2.43 58.1 128 2.27 111 2.36 119 2.51 108 2.50 132 2.37 152 2.56 Djibouti 126 2.43 58.1 124 2.29 90 2.47 141 2.33 154 2.14 121 2.46 115 2.91 Trinidad and Tobago 127 2.41 57.5 106 2.40 107 2.36 127 2.46 134 2.28 142 2.27 139 2.65 2012, 2014 Guinea-Bissau 128 2.40 57.4 138 2.21 160 1.94 117 2.52 131 2.29 98 2.60 124 2.80 Mongolia 129 2.40 57.3 132 2.25 142 2.12 128 2.45 145 2.23 149 2.21 94 3.07 Sudan 130 2.40 57.3 148 2.13 139 2.14 121 2.49 116 2.41 122 2.45 134 2.73 42 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Appendix 1  Aggregated international LPI results International Logistics quality Tracking and Mean Mean % of Customs Infrastructure shipments and competence tracing Timeliness LPI LPI highest Missing Economy rank score performer Rank Score Rank Score Rank Score Rank Score Rank Score Rank Score values Ethiopia 131 2.40 57.2 79 2.54 140 2.13 112 2.54 119 2.39 145 2.24 158 2.49 2018 Kyrgyz Republic 132 2.38 57.0 110 2.38 126 2.23 157 2.20 147 2.21 116 2.49 126 2.79 Congo, Rep. 133 2.38 56.7 151 2.07 141 2.12 107 2.58 142 2.25 129 2.38 125 2.80 Fiji 134 2.37 56.7 113 2.37 110 2.36 148 2.27 136 2.27 136 2.32 138 2.65 Venezuela, RB 135 2.37 56.5 160 1.94 124 2.24 120 2.49 128 2.32 123 2.44 133 2.74 Bolivia 136 2.36 56.5 134 2.24 138 2.16 122 2.48 146 2.21 140 2.29 131 2.75 Madagascar 137 2.35 56.1 121 2.32 137 2.16 154 2.22 141 2.25 125 2.42 136 2.70 Gambia, The 138 2.34 56.0 149 2.08 161 1.90 91 2.68 144 2.23 118 2.48 150 2.60 2016 Myanmar 139 2.34 55.9 137 2.21 145 2.11 155 2.22 133 2.28 135 2.33 120 2.86 Chad 140 2.34 55.9 143 2.15 121 2.26 136 2.35 118 2.39 141 2.28 151 2.58 Senegal 141 2.34 55.8 125 2.29 122 2.24 129 2.44 137 2.27 151 2.19 153 2.56 Turkmenistan 142 2.34 55.8 133 2.25 129 2.23 135 2.36 150 2.20 137 2.32 143 2.63 2012 Congo, Dem. Rep. 143 2.33 55.6 135 2.23 152 2.04 149 2.26 126 2.34 127 2.41 141 2.65 Papua New Guinea 144 2.31 55.2 112 2.37 144 2.11 145 2.29 159 2.11 134 2.36 147 2.61 Guinea 145 2.30 54.9 108 2.39 166 1.80 133 2.38 138 2.27 99 2.59 166 2.30 Liberia 146 2.29 54.7 153 2.04 150 2.06 156 2.22 143 2.24 157 2.15 103 2.99 Tajikistan 147 2.29 54.6 154 2.02 133 2.17 143 2.32 132 2.29 143 2.26 142 2.65 Niger 148 2.29 54.6 146 2.14 146 2.10 146 2.28 140 2.26 139 2.29 145 2.62 Yemen, Rep. 149 2.27 54.3 150 2.08 151 2.05 142 2.33 135 2.27 144 2.24 144 2.63 2016 Central African Republic 150 2.26 54.0 117 2.35 135 2.17 150 2.25 156 2.13 150 2.21 161 2.46 2016 Bhutan 151 2.25 53.7 141 2.16 159 1.98 164 2.12 124 2.36 138 2.31 155 2.54 Cuba 152 2.23 53.4 144 2.15 148 2.09 144 2.30 151 2.20 155 2.18 160 2.46 Lesotho 153 2.22 53.0 139 2.20 153 2.02 162 2.14 158 2.12 148 2.22 149 2.60 Burundi 154 2.22 53.0 163 1.90 157 2.00 147 2.28 127 2.33 147 2.23 154 2.55 Libya 155 2.21 52.9 156 2.00 136 2.17 158 2.18 148 2.21 166 1.90 128 2.78 Equatorial Guinea 156 2.21 52.7 158 1.99 164 1.82 125 2.46 160 2.11 158 2.14 137 2.66 2012 Mauritania 157 2.20 52.5 142 2.16 147 2.09 161 2.15 162 2.06 156 2.18 156 2.54 Gabon 158 2.19 52.3 157 1.99 149 2.07 153 2.23 155 2.13 163 2.06 148 2.61 Iraq 159 2.18 52.2 162 1.90 158 2.00 140 2.33 166 1.98 160 2.13 135 2.73 Angola 160 2.18 52.1 166 1.79 156 2.01 139 2.33 157 2.13 159 2.14 140 2.65 Zimbabwe 161 2.17 51.8 155 2.01 155 2.01 163 2.13 149 2.20 152 2.19 162 2.45 Eritrea 162 2.11 50.4 152 2.05 162 1.89 165 2.12 152 2.19 162 2.09 165 2.31 Syrian Arab Republic 163 2.10 50.2 167 1.70 143 2.12 166 2.09 165 2.00 146 2.23 157 2.50 Sierra Leone 164 2.06 49.3 164 1.82 154 2.02 160 2.15 167 1.96 161 2.10 164 2.31 2014 Afghanistan 165 2.04 48.7 161 1.91 163 1.83 159 2.18 163 2.02 167 1.76 159 2.48 Haiti 166 2.02 48.3 159 1.96 165 1.81 167 1.98 164 2.02 164 1.96 163 2.37 Somalia 167 2.00 47.7 165 1.81 167 1.69 152 2.24 161 2.07 165 1.94 167 2.18 2012 Source: Logistics Performance Index 2012, 2014, 2016 and 2018. Note: The LPI index is a multidimensional assessment of logistics performance, rated on a scale from 1 (worst) to 5 (best). The six core components captured by the LPI survey are rated by respondents on a scale of 1–5, where 1 is very low or very difficult and 5 is very high or very easy, except for question 15, where 1 is hardly ever and 5 is nearly always. The relative LPI score is obtained by normalizing the LPI score: Percentage of highest performer = 100 × [LPI – 1] / [LPI highest – 1]. Thus, the best performer has the maximum relative LPI score of 100 percent. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 43 Appendix 1  Aggregated international LPI results Methodology for computing the aggregated International LPI Scores of the six components across the four most recent LPI surveys were used to generate a “big picture” to better indicate countries’ logistics performance. This approach reduces random variation from one LPI survey to another and enables the comparison of 167 countries. Each year’s scores in each component were given weights: 6.7 percent for 2012, 13.3 percent for 2014, 26.7 percent for 2016, and 53.3 percent for 2018. In this way, the most recent data carry the highest weight. We compute aggregated the score over 2018, 2016, 2014, and 2012 in the following way. First, we fill missing values, according to: Score14 = Score12 if Score 14 is missing Score16 = Score14 if Score 16 is missing Score18 = Score16 if Score 18 is missing Then: Score16 = Score18 if Score 16 is still missing Score14 = Score16 if Score 14 is still missing Score12 = Score14 if Score 12 is missing For example, the following table: Score18 Score16 Score14 Score12 a1 a2 a3 . b1 . b3 . . c2 . c4 . . d3 d4 e1 e2 . . would be extrapolated in this way: Score18 Score16 Score14 Score12 a1 a2 a3 a3 b1 b3 b3 b3 c2 c2 c4 c4 d3 d3 d3 d4 e1 e2 e2 e2 Second, we weight the values in the following way: Consolidated score = 8w*Score18 + 4w*Score16 + 2w*Score14 + w*Score12 So that: w = 0.067, 2w = 0.133, 4w = 0.267, 8w = 0.533. 44 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 2 APPENDIX International LPI results for 2018, with bounds Logistics International quality and Tracking and LPI rank LPI score Customs Infrastructure shipments competence tracing Timeliness % of Lower Upper Lower Upper highest Economy Rank bound bound Score bound bound performer Rank Score Rank Score Rank Score Rank Score Rank Score Rank Score Germany 1 1 1 4.20 4.16 4.25 100.0 1 4.09 1 4.37 4 3.86 1 4.31 2 4.24 3 4.39 Sweden 2 2 12 4.05 3.90 4.20 95.4 2 4.05 3 4.24 2 3.92 10 3.98 17 3.88 7 4.28 Belgium 3 2 12 4.04 3.92 4.16 94.9 14 3.66 14 3.98 1 3.99 2 4.13 9 4.05 1 4.41 Austria 4 2 14 4.03 3.88 4.17 94.5 12 3.71 5 4.18 3 3.88 6 4.08 7 4.09 12 4.25 Japan 5 2 10 4.03 3.96 4.09 94.5 3 3.99 2 4.25 14 3.59 4 4.09 10 4.05 10 4.25 Netherlands 6 2 11 4.02 3.95 4.09 94.3 5 3.92 4 4.21 11 3.68 5 4.09 11 4.02 11 4.25 Singapore 7 2 15 4.00 3.86 4.13 93.6 6 3.89 6 4.06 15 3.58 3 4.10 8 4.08 6 4.32 Denmark 8 2 17 3.99 3.82 4.16 93.5 4 3.92 17 3.96 19 3.53 9 4.01 3 4.18 2 4.41 United Kingdom 9 3 11 3.99 3.93 4.05 93.3 11 3.77 8 4.03 13 3.67 7 4.05 4 4.11 5 4.33 Finland 10 1 21 3.97 3.68 4.26 92.7 8 3.82 11 4.00 16 3.56 15 3.89 1 4.32 8 4.28 United Arab Emirates 11 2 15 3.96 3.86 4.05 92.3 15 3.63 10 4.02 5 3.85 13 3.92 13 3.96 4 4.38 Hong Kong SAR, China 12 7 17 3.92 3.83 4.01 91.2 9 3.81 15 3.97 8 3.77 12 3.93 15 3.92 15 4.14 Switzerland 13 7 17 3.90 3.80 4.00 90.6 16 3.63 9 4.02 20 3.51 11 3.97 5 4.10 13 4.24 United States 14 12 17 3.89 3.83 3.94 90.1 10 3.78 7 4.05 23 3.51 16 3.87 6 4.09 19 4.08 New Zealand 15 2 23 3.88 3.63 4.12 89.8 13 3.71 13 3.99 27 3.43 8 4.02 16 3.92 9 4.26 France 16 14 17 3.84 3.79 3.90 88.8 19 3.59 12 4.00 17 3.55 17 3.84 12 4.00 14 4.15 Spain 17 12 18 3.83 3.74 3.92 88.4 17 3.62 19 3.84 6 3.83 18 3.80 19 3.83 20 4.06 Australia 18 14 26 3.75 3.60 3.90 85.9 7 3.87 16 3.97 40 3.25 21 3.71 20 3.82 21 3.98 Italy 19 18 22 3.74 3.68 3.80 85.6 23 3.47 18 3.85 21 3.51 24 3.66 18 3.85 17 4.13 Canada 20 14 27 3.73 3.56 3.89 85.2 18 3.60 21 3.75 30 3.38 14 3.90 21 3.81 22 3.96 Norway 21 12 30 3.70 3.45 3.94 84.2 21 3.52 24 3.69 26 3.43 23 3.69 14 3.94 24 3.94 Czech Republic 22 17 28 3.68 3.53 3.83 83.7 30 3.29 26 3.46 10 3.75 20 3.72 24 3.70 16 4.13 Portugal 23 16 30 3.64 3.44 3.85 82.6 35 3.17 32 3.25 7 3.83 22 3.71 23 3.72 18 4.13 Luxembourg 24 18 30 3.63 3.45 3.81 82.2 20 3.53 25 3.63 31 3.37 19 3.76 29 3.61 26 3.90 Korea, Rep. 25 20 29 3.61 3.49 3.74 81.6 25 3.40 22 3.73 33 3.33 28 3.59 22 3.75 25 3.92 China 26 23 27 3.61 3.55 3.66 81.4 31 3.29 20 3.75 18 3.54 27 3.59 27 3.65 27 3.84 Taiwan, China 27 18 31 3.60 3.42 3.78 81.2 22 3.47 23 3.72 24 3.48 30 3.57 25 3.67 35 3.72 Poland 28 20 33 3.54 3.35 3.73 79.3 33 3.25 35 3.21 12 3.68 29 3.58 31 3.51 23 3.95 Ireland 29 20 37 3.51 3.28 3.74 78.4 26 3.36 29 3.29 28 3.42 26 3.60 28 3.62 33 3.76 Qatar 30 19 41 3.47 3.21 3.74 77.3 38 3.00 27 3.38 9 3.75 31 3.42 30 3.56 36 3.70 Hungary 31 28 39 3.42 3.25 3.59 75.6 27 3.35 30 3.27 43 3.22 38 3.21 26 3.67 32 3.79 Thailand 32 29 37 3.41 3.29 3.53 75.3 36 3.14 41 3.14 25 3.46 32 3.41 33 3.47 28 3.81 South Africa 33 30 39 3.38 3.25 3.51 74.2 34 3.17 36 3.19 22 3.51 39 3.19 35 3.41 34 3.74 Chile 34 31 41 3.32 3.21 3.43 72.4 32 3.27 34 3.21 38 3.27 43 3.13 44 3.20 31 3.80 Slovenia 35 28 49 3.31 3.08 3.55 72.3 24 3.42 31 3.26 47 3.19 50 3.05 40 3.27 38 3.70 Estonia 36 28 50 3.31 3.06 3.56 72.2 28 3.32 44 3.10 39 3.26 40 3.15 43 3.21 30 3.80 Israel 37 30 47 3.31 3.13 3.49 72.1 29 3.32 28 3.33 75 2.78 34 3.39 32 3.50 48 3.59 Panama 38 31 47 3.28 3.12 3.43 71.1 45 2.87 42 3.13 34 3.31 35 3.33 36 3.40 46 3.60 Vietnam 39 31 48 3.27 3.11 3.44 71.0 41 2.95 47 3.01 49 3.16 33 3.40 34 3.45 40 3.67 Iceland 40 23 72 3.23 2.80 3.65 69.5 54 2.77 37 3.19 72 2.79 25 3.61 37 3.35 37 3.70 Malaysia 41 31 55 3.22 3.00 3.44 69.4 43 2.90 40 3.15 32 3.35 36 3.30 47 3.15 53 3.46 Greece 42 34 51 3.20 3.04 3.37 68.9 47 2.84 38 3.17 35 3.30 48 3.06 45 3.18 42 3.66 C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 45 Appendix 2  International LPI results for 2018, with bounds Logistics International quality and Tracking and LPI rank LPI score Customs Infrastructure shipments competence tracing Timeliness % of Lower Upper Lower Upper highest Economy Rank bound bound Score bound bound performer Rank Score Rank Score Rank Score Rank Score Rank Score Rank Score Oman 43 31 59 3.20 2.93 3.47 68.6 44 2.87 39 3.16 36 3.30 49 3.05 66 2.97 29 3.80 India 44 40 49 3.18 3.10 3.26 68.0 40 2.96 52 2.91 44 3.21 42 3.13 38 3.32 52 3.50 Cyprus 45 31 64 3.15 2.85 3.45 67.2 37 3.05 55 2.89 50 3.15 53 3.00 48 3.15 45 3.62 Indonesia 46 31 64 3.15 2.85 3.45 67.2 62 2.67 54 2.89 42 3.23 44 3.10 39 3.30 41 3.67 Turkey 47 40 51 3.15 3.05 3.24 67.0 58 2.71 33 3.21 53 3.06 51 3.05 42 3.23 44 3.63 Romania 48 40 55 3.12 3.01 3.23 66.2 80 2.58 51 2.91 48 3.18 47 3.07 41 3.26 39 3.68 Croatia 49 34 65 3.10 2.84 3.37 65.7 39 2.98 46 3.01 58 2.93 45 3.10 61 3.01 47 3.59 Côte d'Ivoire 50 38 63 3.08 2.86 3.30 65.0 51 2.78 56 2.89 45 3.21 37 3.23 49 3.14 71 3.23 Mexico 51 43 60 3.05 2.90 3.20 64.1 53 2.77 57 2.85 51 3.10 52 3.02 62 3.00 49 3.53 Bulgaria 52 40 64 3.03 2.84 3.23 63.5 42 2.94 64 2.76 41 3.23 55 2.88 59 3.02 65 3.31 Slovak Republic 53 34 82 3.03 2.69 3.36 63.3 50 2.79 48 3.00 52 3.10 41 3.14 64 2.99 86 3.14 Lithuania 54 38 74 3.02 2.76 3.28 63.0 46 2.85 66 2.73 74 2.79 54 2.96 50 3.12 43 3.65 Saudi Arabia 55 44 66 3.01 2.83 3.19 62.8 66 2.66 43 3.11 56 2.99 57 2.86 46 3.17 67 3.30 Brazil 56 48 64 2.99 2.85 3.12 62.0 102 2.41 50 2.93 61 2.88 46 3.09 51 3.11 51 3.51 Rwanda 57 38 86 2.97 2.66 3.29 61.7 64 2.67 65 2.76 29 3.39 60 2.85 86 2.75 61 3.35 Colombia 58 49 74 2.94 2.77 3.11 60.6 75 2.61 72 2.67 46 3.19 56 2.87 53 3.08 81 3.17 Bahrain 59 48 76 2.93 2.75 3.12 60.4 63 2.67 68 2.72 55 3.02 58 2.86 60 3.01 68 3.29 Philippines 60 51 77 2.90 2.73 3.07 59.5 85 2.53 67 2.73 37 3.29 69 2.78 57 3.06 100 2.98 Argentina 61 57 72 2.89 2.80 2.98 58.9 98 2.42 62 2.77 59 2.92 68 2.78 58 3.05 58 3.37 Ecuador 62 52 79 2.88 2.72 3.05 58.8 48 2.80 69 2.72 80 2.75 70 2.75 55 3.07 75 3.19 Kuwait 63 44 108 2.86 2.54 3.18 58.1 56 2.73 45 3.02 98 2.63 67 2.80 96 2.66 59 3.37 Iran, Islamic Rep. 64 43 114 2.85 2.50 3.20 57.9 71 2.63 63 2.77 79 2.76 62 2.84 85 2.77 60 3.36 Serbia 65 50 96 2.84 2.59 3.09 57.5 78 2.60 74 2.60 57 2.97 80 2.70 76 2.79 62 3.33 Ukraine 66 52 91 2.83 2.62 3.04 57.2 89 2.49 119 2.22 68 2.83 61 2.84 52 3.11 56 3.42 Egypt, Arab Rep. 67 45 115 2.82 2.48 3.17 57.0 77 2.60 58 2.82 73 2.79 63 2.82 89 2.72 74 3.19 Kenya 68 55 91 2.81 2.62 3.01 56.7 67 2.65 79 2.55 99 2.62 64 2.81 56 3.07 79 3.18 Malta 69 42 125 2.81 2.41 3.21 56.7 60 2.70 53 2.90 89 2.70 66 2.80 75 2.80 98 3.01 Latvia 70 56 90 2.81 2.62 3.00 56.5 49 2.80 49 2.98 81 2.74 81 2.69 77 2.79 113 2.88 Kazakhstan 71 56 90 2.81 2.63 2.99 56.5 65 2.66 81 2.55 84 2.73 90 2.58 83 2.78 50 3.53 Bosnia and Herzegovina 72 56 91 2.81 2.62 3.00 56.5 69 2.63 97 2.42 66 2.84 65 2.80 70 2.89 72 3.21 Costa Rica 73 58 90 2.79 2.63 2.95 56.0 70 2.63 84 2.49 76 2.78 79 2.70 67 2.96 83 3.16 Paraguay 74 56 98 2.78 2.58 2.99 55.7 68 2.64 80 2.55 91 2.69 76 2.72 101 2.61 55 3.45 Russian Federation 75 63 89 2.76 2.65 2.87 54.9 97 2.42 61 2.78 96 2.64 71 2.75 97 2.65 66 3.31 Benin 76 58 109 2.75 2.54 2.96 54.7 82 2.56 83 2.50 83 2.73 98 2.50 87 2.75 57 3.42 Montenegro 77 60 106 2.75 2.56 2.93 54.5 83 2.56 75 2.57 92 2.68 74 2.72 105 2.58 63 3.33 Mauritius 78 55 116 2.73 2.45 3.01 54.1 59 2.70 59 2.80 151 2.12 59 2.86 63 3.00 99 3.00 Lebanon 79 56 119 2.72 2.43 3.00 53.6 106 2.38 73 2.64 70 2.80 104 2.47 74 2.80 77 3.18 Brunei Darussalam 80 60 114 2.71 2.51 2.91 53.3 73 2.62 89 2.46 113 2.51 77 2.71 88 2.75 80 3.17 Macedonia, FYR 81 58 119 2.70 2.44 2.97 53.3 91 2.45 87 2.47 67 2.84 72 2.74 100 2.64 96 3.03 Lao PDR 82 60 115 2.70 2.47 2.93 53.1 74 2.61 91 2.44 85 2.72 83 2.65 69 2.91 117 2.84 Peru 83 60 115 2.69 2.48 2.91 52.9 86 2.53 111 2.28 65 2.84 110 2.42 108 2.55 54 3.45 Jordan 84 64 112 2.69 2.52 2.86 52.7 88 2.49 70 2.72 119 2.44 93 2.55 84 2.77 76 3.18 Uruguay 85 63 114 2.69 2.50 2.87 52.6 87 2.51 94 2.43 82 2.73 78 2.71 82 2.78 109 2.91 46 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Appendix 2  International LPI results for 2018, with bounds Logistics International quality and Tracking and LPI rank LPI score Customs Infrastructure shipments competence tracing Timeliness % of Lower Upper Lower Upper highest Economy Rank bound bound Score bound bound performer Rank Score Rank Score Rank Score Rank Score Rank Score Rank Score Maldives 86 61 119 2.67 2.44 2.89 52.0 105 2.40 71 2.72 94 2.66 125 2.29 104 2.60 64 3.32 Dominican Republic 87 66 115 2.66 2.49 2.84 51.9 103 2.41 105 2.36 77 2.77 108 2.44 65 2.97 101 2.98 Albania 88 64 115 2.66 2.46 2.86 51.8 114 2.35 110 2.29 69 2.82 92 2.56 95 2.67 73 3.20 São Tomé and Principe 89 66 115 2.65 2.47 2.84 51.6 57 2.71 106 2.33 121 2.42 84 2.65 81 2.78 97 3.01 Djibouti 90 61 130 2.63 2.37 2.90 51.1 113 2.35 60 2.79 118 2.45 135 2.25 72 2.85 85 3.15 Burkina Faso 91 61 133 2.62 2.34 2.90 50.6 100 2.41 95 2.43 60 2.92 106 2.46 124 2.40 95 3.04 Armenia 92 73 122 2.61 2.42 2.80 50.2 81 2.57 86 2.48 95 2.65 97 2.50 113 2.51 111 2.90 Honduras 93 76 116 2.60 2.45 2.76 50.1 125 2.24 88 2.47 93 2.66 75 2.72 93 2.68 118 2.83 Sri Lanka 94 63 135 2.60 2.32 2.87 49.9 79 2.58 85 2.49 112 2.51 109 2.42 78 2.79 122 2.79 Cameroon 95 73 129 2.60 2.38 2.81 49.8 90 2.46 76 2.57 63 2.87 87 2.60 118 2.47 142 2.57 Mali 96 63 136 2.59 2.30 2.88 49.7 133 2.15 109 2.30 88 2.70 107 2.45 54 3.08 119 2.83 Malawi 97 61 138 2.59 2.28 2.89 49.5 94 2.43 126 2.18 105 2.55 82 2.68 94 2.67 102 2.97 Cambodia 98 75 129 2.58 2.38 2.78 49.3 109 2.37 130 2.14 71 2.79 111 2.41 111 2.52 84 3.16 Uzbekistan 99 75 129 2.58 2.38 2.77 49.3 140 2.10 77 2.57 120 2.42 88 2.59 90 2.71 91 3.09 Bangladesh 100 68 134 2.58 2.34 2.82 49.2 121 2.30 100 2.39 104 2.56 102 2.48 79 2.79 107 2.92 El Salvador 101 82 118 2.58 2.45 2.70 49.2 120 2.30 114 2.25 86 2.71 91 2.56 117 2.47 90 3.10 Uganda 102 73 133 2.58 2.34 2.81 49.2 76 2.61 124 2.19 78 2.76 99 2.50 123 2.41 110 2.90 Belarus 103 78 125 2.57 2.41 2.74 49.2 112 2.35 92 2.44 134 2.31 85 2.64 109 2.54 78 3.18 Solomon Islands 104 60 143 2.57 2.23 2.91 49.1 52 2.77 120 2.21 142 2.20 73 2.73 126 2.37 87 3.12 Tunisia 105 75 129 2.57 2.38 2.76 49.0 107 2.38 133 2.10 115 2.50 123 2.30 71 2.86 70 3.24 Ghana 106 65 138 2.57 2.29 2.85 48.9 92 2.45 90 2.44 109 2.53 95 2.51 106 2.57 115 2.87 Comoros 107 60 144 2.56 2.20 2.91 48.6 72 2.63 113 2.25 116 2.49 138 2.21 68 2.93 120 2.80 Kyrgyz Republic 108 73 138 2.55 2.29 2.80 48.3 55 2.75 103 2.38 138 2.22 114 2.36 99 2.64 106 2.94 Morocco 109 79 133 2.54 2.35 2.73 48.1 115 2.33 93 2.43 103 2.58 101 2.49 112 2.51 114 2.88 Nigeria 110 64 144 2.53 2.21 2.86 47.9 147 1.97 78 2.56 110 2.52 112 2.40 92 2.68 92 3.07 Zambia 111 84 130 2.53 2.36 2.69 47.7 129 2.18 108 2.30 54 3.05 103 2.48 158 1.98 94 3.05 Bahamas, The 112 85 130 2.53 2.37 2.69 47.6 61 2.68 98 2.41 114 2.50 130 2.27 110 2.52 125 2.75 Jamaica 113 79 135 2.52 2.32 2.72 47.4 99 2.42 107 2.32 107 2.53 94 2.54 116 2.48 121 2.79 Nepal 114 77 138 2.51 2.28 2.75 47.3 122 2.29 123 2.19 129 2.36 105 2.46 98 2.65 89 3.10 Congo, Rep. 115 65 151 2.49 2.12 2.85 46.4 123 2.27 138 2.07 64 2.87 127 2.28 125 2.38 103 2.95 Moldova 116 92 137 2.46 2.30 2.62 45.5 124 2.25 141 2.02 90 2.69 122 2.30 142 2.21 82 3.17 Algeria 117 85 143 2.45 2.21 2.69 45.2 138 2.13 96 2.42 122 2.39 113 2.39 103 2.60 124 2.76 Togo 118 78 150 2.45 2.16 2.74 45.2 119 2.31 116 2.23 111 2.52 134 2.25 120 2.45 112 2.88 Georgia 119 84 146 2.44 2.19 2.69 45.1 95 2.42 102 2.38 124 2.38 132 2.26 139 2.26 105 2.95 Congo, Dem. Rep. 120 104 138 2.43 2.28 2.57 44.6 108 2.37 132 2.12 127 2.37 100 2.49 114 2.51 133 2.69 Sudan 121 91 141 2.43 2.23 2.62 44.6 136 2.14 125 2.18 102 2.58 96 2.51 115 2.51 139 2.62 Pakistan 122 98 140 2.42 2.26 2.58 44.3 139 2.12 121 2.20 97 2.63 89 2.59 136 2.27 136 2.66 Chad 123 75 156 2.42 2.07 2.76 44.3 134 2.15 104 2.37 125 2.37 86 2.62 127 2.37 138 2.62 Trinidad and Tobago 124 93 143 2.42 2.22 2.61 44.2 96 2.42 101 2.38 101 2.59 129 2.27 135 2.27 144 2.53 Guatemala 125 93 143 2.41 2.22 2.61 44.2 132 2.16 122 2.20 130 2.33 136 2.25 122 2.42 88 3.11 Turkmenistan 126 97 141 2.41 2.23 2.59 44.0 111 2.35 117 2.23 136 2.29 120 2.31 107 2.56 130 2.72 Gambia, The 127 84 153 2.40 2.11 2.69 43.8 141 2.08 155 1.82 87 2.71 142 2.21 73 2.81 131 2.71 Madagascar 128 97 146 2.39 2.19 2.59 43.4 118 2.32 128 2.16 146 2.19 118 2.33 102 2.61 128 2.73 C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 47 Appendix 2  International LPI results for 2018, with bounds Logistics International quality and Tracking and LPI rank LPI score Customs Infrastructure shipments competence tracing Timeliness % of Lower Upper Lower Upper highest Economy Rank bound bound Score bound bound performer Rank Score Rank Score Rank Score Rank Score Rank Score Rank Score Guinea-Bissau 129 86 153 2.39 2.11 2.67 43.3 144 2.01 159 1.78 108 2.53 126 2.28 80 2.78 116 2.86 Mongolia 130 100 148 2.37 2.17 2.58 42.9 127 2.22 135 2.10 117 2.49 140 2.21 152 2.10 93 3.06 Bolivia 131 113 146 2.36 2.19 2.52 42.4 117 2.32 129 2.15 106 2.54 139 2.21 148 2.13 127 2.74 Guyana 132 114 145 2.36 2.20 2.52 42.4 84 2.55 137 2.09 148 2.17 137 2.24 121 2.44 137 2.65 Fiji 133 94 154 2.35 2.10 2.60 42.2 101 2.41 99 2.40 149 2.16 119 2.31 132 2.31 143 2.54 Tajikistan 134 108 151 2.34 2.12 2.56 41.8 150 1.92 127 2.17 133 2.31 116 2.33 131 2.33 104 2.95 Mauritania 135 108 153 2.33 2.11 2.55 41.6 128 2.20 112 2.26 145 2.19 144 2.19 119 2.47 134 2.68 Equatorial Guinea 136 82 160 2.32 1.93 2.70 41.2 151 1.91 151 1.88 62 2.88 133 2.25 149 2.13 126 2.75 Myanmar 137 115 154 2.30 2.10 2.50 40.5 131 2.17 143 1.99 144 2.20 128 2.28 143 2.20 108 2.91 Syrian Arab Republic 138 115 155 2.30 2.08 2.51 40.5 154 1.82 82 2.51 126 2.37 124 2.29 128 2.37 148 2.44 Lesotho 139 107 159 2.28 1.99 2.56 39.9 110 2.36 145 1.96 140 2.21 154 2.03 129 2.37 132 2.70 Yemen, Rep. 140 80 160 2.27 1.82 2.71 39.5 104 2.40 131 2.12 141 2.21 131 2.26 146 2.16 151 2.43 Senegal 141 115 159 2.25 2.01 2.50 39.1 130 2.17 118 2.22 128 2.36 149 2.11 150 2.11 145 2.52 Venezuela, RB 142 130 156 2.23 2.08 2.38 38.4 156 1.79 134 2.10 123 2.38 141 2.21 133 2.29 141 2.58 Liberia 143 115 159 2.23 1.97 2.49 38.4 152 1.91 149 1.91 155 2.08 148 2.14 155 2.05 69 3.25 Somalia 144 117 159 2.21 1.97 2.45 37.8 145 2.00 157 1.81 100 2.61 121 2.30 140 2.23 157 2.20 Guinea 145 126 159 2.20 1.99 2.41 37.5 93 2.45 160 1.56 132 2.32 152 2.07 91 2.70 160 2.04 Cuba 146 128 159 2.20 2.00 2.39 37.4 143 2.03 139 2.04 137 2.27 143 2.20 147 2.15 147 2.46 Iraq 147 137 159 2.18 2.04 2.31 36.7 153 1.84 140 2.03 131 2.32 159 1.91 144 2.19 129 2.72 Papua New Guinea 148 128 159 2.17 1.95 2.40 36.7 116 2.32 144 1.97 150 2.15 160 1.88 138 2.26 150 2.44 Bhutan 149 129 159 2.17 1.95 2.39 36.5 135 2.14 150 1.91 160 1.80 115 2.35 130 2.35 146 2.49 Gabon 150 117 160 2.16 1.87 2.45 36.3 148 1.96 136 2.09 153 2.10 151 2.07 153 2.07 135 2.67 Central African Republic 151 116 160 2.15 1.81 2.48 35.9 126 2.24 148 1.93 135 2.30 157 1.93 151 2.10 156 2.33 Zimbabwe 152 128 160 2.12 1.84 2.40 35.0 146 2.00 154 1.83 156 2.06 147 2.16 137 2.26 152 2.39 Haiti 153 140 159 2.11 1.95 2.27 34.7 142 2.03 147 1.94 157 2.01 145 2.19 154 2.05 149 2.44 Libya 154 136 160 2.11 1.89 2.32 34.6 149 1.95 115 2.25 159 1.99 153 2.05 160 1.64 123 2.77 Eritrea 155 130 160 2.09 1.79 2.38 34.0 137 2.13 152 1.86 154 2.09 146 2.17 145 2.17 159 2.08 Sierra Leone 156 137 160 2.08 1.85 2.31 33.7 155 1.82 156 1.82 147 2.18 156 2.00 134 2.27 154 2.34 Niger 157 116 160 2.07 1.66 2.48 33.4 157 1.77 142 2.00 158 2.00 150 2.10 141 2.22 155 2.33 Burundi 158 139 160 2.06 1.85 2.28 33.2 159 1.69 146 1.95 139 2.21 117 2.33 156 2.01 158 2.17 Angola 159 142 160 2.05 1.85 2.25 32.7 160 1.57 153 1.86 143 2.20 155 2.00 157 2.00 140 2.59 Afghanistan 160 155 160 1.95 1.79 2.11 29.6 158 1.73 158 1.81 152 2.10 158 1.92 159 1.70 153 2.38 Note: The LPI index is a multidimensional assessment of logistics performance, rated on a scale from 1 (worst) to 5 (best). The six core components captured by the LPI survey are rated by respondents on a scale of 1–5, where 1 is very low or very difficult and 5 is very high or very easy, except for question 15, where 1 is hardly ever and 5 is nearly always. The relative LPI score is obtained by normalizing the LPI score: Percentage of highest performer = 100 × [LPI – 1] / [LPI highest – 1]. Thus, the best performer has the maximum relative LPI score of 100 percent. Source: Logistics Performance Index 2018. 48 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 3 APPENDIX Domestic LPI results, by region and income group Percent of respondents, unless otherwise indicated. Data for regional averages include low- and middle-income countries only. Region Income group Europe Latin Middle East and America East and Sub- Lower Upper Response Asia and Central and North South Saharan Low middle middle High Question categories Pacific Asia Caribbean Africa Asia Africa income income income income Question 17: Level of fees and charges High or very high 35 53 60 47 56 65 71 63 39 35 Port charges Low or very low 8 6 3 3 8 3 2 2 9 18 High or very high 30 59 54 34 61 60 64 59 40 35 Airport charges Low or very low 11 10 13 27 7 10 9 6 19 9 High or very high 39 31 69 15 63 44 51 53 36 25 Road transport charges Low or very low 14 17 11 50 7 4 2 8 24 31 High or very high 15 50 29 6 46 19 27 29 26 31 Rail transport rates Low or very low 28 17 15 71 8 21 11 30 24 17 Warehousing/transloading High or very high 26 30 44 25 39 32 45 37 25 31 service charges Low or very low 23 20 4 40 14 4 2 8 23 32 High or very high 17 34 19 20 48 9 23 22 18 21 Agent fees Low or very low 32 23 21 33 24 18 18 19 29 25 Question 18: Quality of infrastructure Low or very low 38 49 54 21 38 31 52 39 35 15 Ports High or very high 33 14 26 70 18 45 26 26 42 66 Low or very low 22 21 37 10 61 35 60 31 16 9 Airports High or very high 36 22 23 53 14 39 25 22 42 65 Low or very low 30 43 50 11 75 42 62 42 33 14 Roads High or very high 33 21 9 45 7 17 13 12 30 58 Low or very low 59 53 68 58 64 54 60 64 53 37 Rail High or very high 10 20 0 12 10 13 3 6 19 34 Warehousing/ Low or very low 21 19 27 20 55 18 38 30 10 10 transloading facilities High or very high 33 23 6 56 7 30 14 17 37 61 Low or very low 31 21 27 15 13 21 33 27 14 5 Telecommunications and IT High or very high 43 48 26 69 37 47 35 36 52 75 Question 19: Quality and competence of service Low or very low 19 33 27 8 45 10 17 26 20 8 Roads High or very high 36 37 21 54 8 33 18 25 44 74 Low or very low 50 44 69 46 56 38 38 58 46 24 Rail High or very high 11 22 5 16 2 26 17 13 19 45 Low or very low 14 14 11 4 4 12 14 12 10 6 Air transport High or very high 45 40 41 44 24 51 34 39 52 74 Low or very low 11 23 9 5 23 15 26 16 8 6 Maritime transport High or very high 42 23 47 69 24 50 36 41 46 71 Warehousing/transloading Low or very low 14 25 9 29 39 1 5 23 10 4 and distribution High or very high 37 29 18 49 12 46 32 24 42 70 Low or very low 6 23 8 13 29 2 5 18 7 6 Freight forwarders High or very high 47 43 22 64 39 55 39 36 53 79 Low or very low 30 20 31 23 57 25 33 35 20 12 Customs agencies High or very high 39 27 15 22 14 36 24 24 33 72 C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 49 Appendix 3  Domestic LPI results, by region and income group Region Income group Europe Latin Middle East and America East and Sub- Lower Upper Response Asia and Central and North South Saharan Low middle middle High Question categories Pacific Asia Caribbean Africa Asia Africa income income income income Quality/standards Low or very low 25 26 36 8 63 20 35 31 21 6 inspection agencies High or very high 24 25 15 59 12 34 20 25 31 62 Health/sanitary and Low or very low 29 41 60 16 64 35 46 43 39 10 phytosanitary agencies High or very high 19 18 4 52 7 31 20 16 24 61 Low or very low 11 17 21 6 49 13 23 24 8 10 Customs brokers High or very high 50 36 14 56 18 28 19 28 40 66 Low or very low 15 35 41 32 46 29 42 36 22 15 Trade and transport associations High or very high 33 29 13 45 13 31 19 21 37 58 Low or very low 19 24 7 13 14 12 20 19 8 10 Consignees or shippers High or very high 32 18 9 39 17 35 20 23 29 52 Question 20: Efficiency of processes Hardly ever 6 13 10 17 14 15 21 13 7 3 Clearance and delivery of or rarely imports as scheduled Often or nearly 62 71 62 49 37 45 46 48 69 87 always Hardly ever 1 13 7 2 34 18 19 15 6 1 Clearance and delivery of or rarely exports as scheduled Often or nearly 77 67 78 83 53 60 58 65 78 88 always Hardly ever 8 22 28 20 55 16 33 24 14 5 Transparency of or rarely customs clearance Often or nearly 57 60 37 70 22 60 40 48 63 84 always Hardly ever 12 15 26 12 57 23 45 19 14 5 Transparency of other or rarely border agencies Often or nearly 52 53 27 56 21 47 30 42 51 79 always Hardly ever Provision of adequate 14 27 47 29 44 27 39 31 26 10 or rarely and timely information on regulatory changes Often or nearly 61 47 25 69 24 39 23 45 48 69 always Hardly ever Expedited customs 10 18 28 23 55 23 35 26 16 10 or rarely clearance for traders with high compliance levels Often or nearly 56 52 28 61 17 31 19 39 50 73 always Question 21: Sources of major delays Often or nearly 13 13 24 18 47 30 44 25 11 5 Compulsory warehousing/ always transloading Hardly ever 37 38 36 39 22 44 34 28 49 68 or rarely Often or nearly 10 17 19 32 39 24 30 27 11 7 always Preshipment inspection Hardly ever 58 51 28 37 20 25 21 30 49 72 or rarely Often or nearly 12 16 13 10 44 10 10 23 10 7 always Maritime transshipment Hardly ever 44 38 41 45 17 34 26 27 52 51 or rarely Often or nearly 4 16 7 1 21 5 0 14 8 2 Criminal activities always (such as stolen cargo) Hardly ever 68 70 49 75 36 74 75 53 69 85 or rarely 50 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Appendix 3  Domestic LPI results, by region and income group Region Income group Europe Latin Middle East and America East and Sub- Lower Upper Response Asia and Central and North South Saharan Low middle middle High Question categories Pacific Asia Caribbean Africa Asia Africa income income income income Often or nearly 13 16 25 11 35 29 21 33 14 3 Solicitation of informal always payments Hardly ever 45 68 33 68 25 34 28 33 61 86 or rarely Question 22: Changes in the logistics environment since 2015 Much worsened or worsened 10 8 17 26 20 16 14 26 5 5 Customs clearance procedures Improved or much improved 66 51 57 56 46 65 56 55 64 63 Much worsened Other official clearance or worsened 10 10 18 18 22 9 8 21 8 5 procedures Improved or much improved 55 40 45 52 36 57 54 47 48 55 Much worsened Trade and transport or worsened 9 12 22 14 26 10 10 24 7 5 infrastructure Improved or much improved 56 56 54 52 29 44 29 48 60 60 Much worsened Telecommunications or worsened 7 9 14 1 0 10 14 7 9 1 and IT infrastructure Improved or much improved 58 71 50 77 43 64 51 63 63 72 Much worsened or worsened 1 9 13 5 24 0 0 10 7 4 Private logistics services Improved or much improved 60 64 66 67 42 64 51 66 65 72 Much worsened or worsened 7 18 7 23 29 9 10 17 9 14 Regulation related to logistics Improved or much improved 52 39 48 47 25 47 38 41 52 36 Much worsened Solicitation of informal or worsened 6 25 10 16 34 26 26 21 14 2 payments Improved or much improved 38 37 47 50 25 45 48 32 48 43 Question 23: Developments since 2015 Much decreased Demand for traditional freight or decreased 13 20 13 30 28 14 10 13 27 5 forwarding as a commercial service Increased or much increased 47 49 51 50 28 50 45 46 51 46 Increased use of electronic trading Much decreased platforms (business to business and or decreased 2 9 7 8 2 8 3 5 12 0 business to consumer) by shippers Increased or mean that business volumes have much increased 63 46 45 51 28 49 60 51 47 45 Much decreased or decreased 18 20 3 23 15 17 9 9 19 19 Cybersecurity threats in logistics Increased or much increased 22 39 40 37 24 42 66 46 26 36 Much decreased Firm’s preparedness or decreased 11 10 3 7 1 13 1 3 11 16 for cyber threats Increased or much increased 47 50 45 62 30 43 78 58 43 26 C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 51 Appendix 3  Domestic LPI results, by region and income group Region Income group Europe Latin Middle East and America East and Sub- Lower Upper Response Asia and Central and North South Saharan Low middle middle High Question categories Pacific Asia Caribbean Africa Asia Africa income income income income Question 24: Export time and distance Distance (kilometers) 508.35 461.75 468.04 577.22 112.13 618.05 150.70 612.90 458.82 353.02 Port or airport supply chain Lead time (days) 2.36 4.83 4.72 2.81 3.43 9.37 2.42 4.72 4.45 10.35 Distance (kilometers) 893.34 1,348.99 430.52 699.71 848.13 1,377.22 593.71 1,059.78 940.82 1,163.99 Land supply chain Lead time (days) 6.88 8.00 4.16 4.07 7.71 16.22 4.33 6.71 7.44 17.80 Question 25: Import time and distance Distance (kilometers) 137.19 499.72 147.42 539.87 235.61 684.06 174.67 486.33 239.47 659.91 Port or airport supply chain Lead time (days) 3.47 3.60 5.48 4.54 4.31 6.81 2.64 5.29 3.83 6.91 Distance (kilometers) 468.98 1,574.14 595.27 739.79 566.81 955.95 624.00 1,125.82 741.75 719.68 Land supply chain Lead time (days) 6.56 8.24 5.80 5.03 6.77 8.33 5.13 7.98 7.11 5.56 Question 26: Percentage of shipments meeting quality criteria % of shipments 83 79 86 76 65 68 86 81 74 70 Question 27: Number of agencies Imports 3.31 2.57 3.37 3.56 5.69 4.43 2.12 3.14 3.76 4.79 Exports 3.16 2.89 3.16 2.92 6.05 4.21 1.93 3.03 3.57 4.76 Question 28: Number of forms Imports 4.56 3.68 3.38 4.27 5.32 4.90 2.41 3.68 4.53 5.14 Exports 4.17 4.01 3.34 3.23 4.69 4.76 2.02 3.60 4.10 5.21 Question 29: Clearance time (days) Without physical inspection 1.20 2.75 1.71 1.60 1.58 2.89 0.73 2.36 1.88 2.34 With physical inspection 2.57 2.86 3.35 2.95 3.02 4.64 1.60 3.16 3.64 3.86 Question 31: Physical inspection % of import shipments 22 15 21 43 29 34 10 21 28 32 Question 32: Multiple inspections % of shipments physically inspected 13 9 3 9 6 18 5 9 12 13 Question 33: Customs Can customs declarations be submitted and processed % yes 92 92 75 80 90 86 97 85 89 82 electronically and online? Does customs code require importer to use a licensed % yes 78 72 86 82 91 88 64 78 82 92 customs broker to clear goods? Are you or your customer able to choose the location of the final % yes 79 84 95 61 37 55 74 86 72 45 clearance of the goods for imports? Can goods be released pending final clearance against an % yes 53 57 52 75 58 60 69 56 67 46 accepted guarantee? Note: Responses are calculated at the country level and then averaged by region and income group. Source: Logistics Performance Index 2018. 52 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 4 APPENDIX Domestic LPI results, time and distance data Question 24: Export time and distance Question 25: Import time and distance Port or airport supply chaina Land supply chainb Port or airport supply chainc Land supply chainb Distanced Lead time Distance Lead time Distance Lead time Distance Lead time Economy (kilometers) (days) (kilometers) (days) (kilometers) (days) (kilometers) (days) Albania 300 10 25 14 Argentina 117 4 265 4 49 5 517 8 Armenia 300 7 300 25 Australia 75 1 75 1 Austria 332 2 496 3 344 3 486 3 Azerbaijan 1,025 3 2,646 7 43 2 296 4 Belarus 75 2 25 8 43 2 1,581 7 Belgium 160 2 245 3 186 3 216 3 Benin 75 14 75 10 75 3 Bolivia 52 3 304 6 75 6 968 8 Brazil 276 5 366 5 240 5 352 5 Brunei Darussalam 25 1 25 1 25 1 25 1 Bulgaria 438 2 1,136 3 276 2 1,256 3 Burkina Faso 750 5 300 2 Burundi 25 18 750 750 3 Cameroon 150 5 2,092 13 474 6 1,581 11 Canada 161 4 766 3 188 5 Chile 300 3 300 3 China 337 2 707 6 328 6 784 4 Colombia 237 2 43 5 Congo, Rep. 3,500 18 Côte d'Ivoire 36 4 1,250 14 36 4 306 16 Czech Republic 300 7 750 3 474 5 300 3 Denmark 43 3 75 2 52 3 75 3 Dominican Republic 1,250 6 2,000 18 Egypt, Arab Rep. 349 2 792 5 452 5 554 6 Estonia 75 2 968 4 75 2 1,250 4 Ethiopia 750 60 750 25 750 10 750 14 Finland 230 2 785 5 172 3 553 5 France 261 2 673 3 177 3 439 3 Gabon 3,500 25 3,500 25 Georgia 300 2 1,225 4 300 2 775 3 Germany 212 2 569 2 350 2 559 3 Ghana 296 1 1,620 1 296 1 25 2 Greece 219 3 841 3 302 3 783 7 Guatemala 150 4 300 5 Haiti 25 1 25 1 Hong Kong SAR, China 300 2 750 2 474 2 India 246 3 569 6 203 3 812 8 Indonesia 171 2 297 3 277 4 277 4 Iran, Islamic Rep. 1,581 3 1,250 5 Italy 269 3 541 5 210 4 519 5 Japan 25 2 25 3 C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 53 Appendix 4  Domestic LPI results, time and distance data Question 24: Export time and distance Question 25: Import time and distance Port or airport supply chaina Land supply chainb Port or airport supply chainc Land supply chainb Distanced Lead time Distance Lead time Distance Lead time Distance Lead time Economy (kilometers) (days) (kilometers) (days) (kilometers) (days) (kilometers) (days) Kazakhstan 2,000 10 3,500 18 Kenya 298 4 203 3 429 4 483 4 Kuwait 75 2 150 2 43 3 75 4 Lao PDR 25 2 750 3 25 2 750 3 Latvia 25 1 2,000 46 25 1 3,500 53 Lithuania 150 2 1,581 4 43 2 1,581 4 Luxembourg 96 2 471 3 101 2 393 3 Macedonia, FYR 300 1 300 2 Madagascar 300 1 75 1 Malawi 750 4 3,500 88 1,250 14 Malaysia 75 2 75 4 43 2 75 4 Malta 25 1 25 1 Mauritius 52 1 66 2 Mexico 3,500 5 300 5 Mongolia 1,250 14 1,250 14 Morocco 159 2 523 2 292 3 631 2 Mozambique 75 3 75 5 Myanmar 88 3 683 4 106 4 579 5 Namibia 25 3 3,500 25 300 4 3,500 25 Nepal 61 1 1,486 10 133 2 582 5 Netherlands 48 2 265 1 99 1 453 2 Nigeria 64 3 61 6 87 2 426 4 Norway 75 1 75 1 75 2 Oman 198 2 320 3 157 2 256 3 Pakistan 66 4 489 7 306 8 306 7 Panama 75 3 300 2 75 2 75 2 Papua New Guinea 3,500 2 3,500 2 75 2 75 2 Paraguay 25 3 Peru 39 2 512 2 84 4 75 1 Philippines 36 1 25 2 Poland 75 1 750 4 300 1 750 5 Portugal 141 3 1,601 3 157 3 1,738 6 Qatar 25 10 25 7 75 7 Romania 203 2 835 3 482 2 1,249 4 Russian Federation 306 3 3,500 3 2,646 5 2,092 9 Rwanda 2,000 6 2,000 7 Saudi Arabia 235 4 940 5 232 5 483 7 Senegal 296 1 25 1 300 7 Serbia 75 2 909 4 300 2 777 4 Singapore 30 2 33 1 29 2 33 2 Slovenia 300 1 256 2 300 3 474 3 Spain 143 2 298 2 101 3 326 2 Sri Lanka 75 6 300 4 Sweden 474 1 1,025 1 300 3 1,025 5 Switzerland 36 3 750 3 52 2 300 2 Taiwan, China 75 1 75 2 54 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Appendix 4  Domestic LPI results, time and distance data Question 24: Export time and distance Question 25: Import time and distance Port or airport supply chaina Land supply chainb Port or airport supply chainc Land supply chainb Distanced Lead time Distance Lead time Distance Lead time Distance Lead time Economy (kilometers) (days) (kilometers) (days) (kilometers) (days) (kilometers) (days) Tanzania 51 4 776 7 51 4 326 5 Thailand 300 4 300 18 300 5 300 18 Tunisia 219 4 784 5 166 5 1,034 6 Turkey 252 3 1,267 6 332 3 1,087 6 Uganda 750 3 750 5 3,500 14 1,250 6 United Arab Emirates 89 2 249 2 107 2 119 2 United Kingdom 147 2 562 4 197 3 429 3 United States 275 2 612 5 263 2 483 4 Uzbekistan 429 16 1,647 16 750 3 3,129 23 Venezuela, RB 209 15 422 7 162 12 750 3 Vietnam 43 2 477 9 56 3 131 5 a. From the point of origin (the seller’s factory, typically located either in the capital city or in the largest commercial center) to the port of loading or equivalent (port/airport), and excluding international shipping (EXW to FOB). b. From the point of origin (the seller’s factory, typically located either in the capital city or in the largest commercial center) to the buyer’s warehouse (EXW to DDP). c. From the port of discharge or equivalent to the buyer’s warehouse (DAT to DDP). d. Aggregates of the distance indicator for port and airport. Source: Logistics Performance Index 2018. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 55 Appendix 4  Domestic LPI results, time and distance data Question 31: Question 32: Question 26: Question 29: Physical Multiple % of shipments Clearance time (days)a inspection inspection meeting quality Question 27: Question 28: criteria Number of agencies Number of forms Without With % of % of shipments physical physical import physically Economy % of shipments Imports Exports Imports Exports inspection inspection shipments inspected Afghanistan 8 8 8 6 Albania 87 3 4 4 3 13 14 6 18 Argentina 75 5 4 4 3 2 4 36 6 Australia 93 2 2 1 1 1 2 1 1 Austria 86 2 2 2 2 0 1 2 2 Azerbaijan 61 3 4 5 8 2 2 50 6 Belarus 57 3 4 4 4 1 1 6 1 Belgium 82 1 1 2 2 1 1 3 1 Benin 88 3 2 5 2 5 6 18 6 Bolivia 83 3 3 2 3 3 7 30 1 Brazil 82 4 4 5 4 2 5 8 5 Brunei Darussalam 88 1 1 1 1 0 1 6 18 Bulgaria 86 2 2 3 3 1 1 7 3 Burkina Faso 88 5 5 3 5 3 5 3 1 Burundi 40 5 3 4 4 4 7 18 3 Cameroon 40 5 8 9 9 2 5 37 18 Canada 57 2 2 3 1 1 4 2 1 Chile 93 5 5 5 5 1 1 3 1 China 81 3 3 4 4 1 2 3 1 Colombia 96 3 3 5 3 2 2 3 1 Côte d'Ivoire 51 5 4 6 4 2 6 30 6 Czech Republic 88 1 1 2 2 1 1 1 1 Denmark 92 1 1 1 1 1 2 1 1 Dominican Republic 97 2 2 3 3 1 1 50 1 Egypt, Arab Rep. 81 6 5 6 5 2 4 40 14 Estonia 93 3 3 1 1 0 1 3 Ethiopia 97 4 6 7 11 1 0 75 75 Finland 93 1 1 2 1 0 1 2 1 France 79 2 2 2 2 1 1 3 2 Gabon 83 1 1 6 5 7 7 50 50 Georgia 62 2 2 2 2 1 1 3 1 Germany 95 1 1 1 1 1 1 2 2 Ghana 61 1 1 1 1 7 10 35 50 Greece 95 2 2 3 3 1 2 2 1 Guatemala 87 4 3 4 4 1 1 42 3 Haiti 100 1 1 1 2 1 3 1 1 Hong Kong SAR, China 95 3 3 4 3 1 2 75 1 India 77 3 3 3 3 1 2 19 3 Indonesia 73 4 3 5 3 1 7 8 2 Iran, Islamic Rep. 69 3 2 4 2 1 3 75 7 Italy 90 2 2 3 2 1 2 3 2 Japan 93 3 2 1 1 1 1 1 1 Kazakhstan 93 4 6 5 8 10 5 18 50 Kenya 53 6 4 6 4 3 4 66 39 Kuwait 62 4 3 9 3 2 1 75 4 Lao PDR 93 3 3 4 4 2 3 18 1 56 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y Appendix 4  Domestic LPI results, time and distance data Question 31: Question 32: Question 26: Question 29: Physical Multiple % of shipments Clearance time (days)a inspection inspection meeting quality Question 27: Question 28: criteria Number of agencies Number of forms Without With % of % of shipments physical physical import physically Economy % of shipments Imports Exports Imports Exports inspection inspection shipments inspected Latvia 89 3 2 2 2 0 1 4 11 Lithuania 97 3 3 2 2 0 1 6 2 Luxembourg 89 2 2 2 2 1 1 3 2 Macedonia, FYR 93 1 1 4 3 1 1 35 6 Madagascar 40 11 11 11 11 2 4 6 3 Malawi 40 3 2 5 6 6 10 75 1 Malaysia 69 2 2 2 2 0 1 4 1 Malta 93 1 1 1 1 1 1 3 1 Mauritius 66 8 5 4 2 1 3 16 3 Mexico 93 2 2 2 2 1 2 6 1 Mongolia 88 2 11 11 1 1 75 75 Morocco 82 3 3 3 3 1 2 13 5 Mozambique 88 2 2 3 3 1 2 35 3 Myanmar 66 4 4 6 6 2 3 28 6 Namibia 90 3 3 2 3 2 4 11 1 Nepal 59 9 9 9 8 1 1 75 10 Netherlands 82 2 1 1 1 0 0 2 1 Nigeria 93 6 6 6 6 2 3 56 21 Norway 93 1 1 2 2 1 2 1 1 Oman 67 4 3 3 2 1 2 36 4 Pakistan 83 4 4 2 2 2 5 17 4 Panama 93 3 3 3 3 1 1 6 3 Papua New Guinea 97 5 5 2 2 1 3 6 3 Paraguay 3 3 4 4 3 3 1 1 Peru 88 5 5 3 3 2 4 15 4 Philippines 87 4 4 6 6 2 2 30 1 Poland 73 2 1 3 3 1 2 3 1 Portugal 82 3 2 3 3 1 2 6 2 Qatar 1 2 3 3 2 7 75 75 Romania 86 2 2 4 5 1 2 8 5 Russian Federation 69 3 3 2 2 2 4 22 4 Rwanda 85 3 2 3 3 2 2 4 3 Saudi Arabia 69 3 3 3 3 2 3 25 9 Senegal 59 3 5 4 3 1 2 35 18 Serbia 95 3 3 3 3 1 1 8 5 Singapore 94 2 2 1 1 0 1 2 2 Slovenia 96 3 3 2 2 0 1 4 2 Spain 75 2 2 2 2 1 2 4 2 Sri Lanka 40 4 4 4 2 4 6 6 Sweden 97 2 2 3 3 1 2 2 1 Switzerland 91 1 1 2 2 0 1 3 1 Taiwan, China 83 2 2 3 3 1 1 1 1 Tanzania 75 7 7 6 6 2 3 70 10 Thailand 93 3 3 2 2 1 1 35 35 Tunisia 74 3 3 5 3 2 3 45 10 Turkey 77 3 3 4 4 1 2 12 6 C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 57 Appendix 4  Domestic LPI results, time and distance data Question 31: Question 32: Question 26: Question 29: Physical Multiple % of shipments Clearance time (days)a inspection inspection meeting quality Question 27: Question 28: criteria Number of agencies Number of forms Without With % of % of shipments physical physical import physically Economy % of shipments Imports Exports Imports Exports inspection inspection shipments inspected Uganda 59 3 4 3 3 3 5 6 35 United Arab Emirates 86 3 2 4 3 1 1 10 3 United Kingdom 90 2 1 2 2 1 2 2 1 United States 91 3 2 4 3 2 3 3 1 Uzbekistan 78 3 3 4 4 1 1 1 1 Venezuela, RB 50 6 7 6 7 3 6 50 7 Vietnam 83 3 2 3 2 1 3 10 3 a. Time taken between the submission of an accepted customs declaration and notification of clearance. Source: Logistics Performance Index 2018. 58 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 5 APPENDIX The LPI methodology Because logistics has many dimensions, mea- Constructing the international LPI suring and summarizing performance across countries is challenging. Examining the time The first part of the LPI survey (questions 10–15) and costs associated with logistics processes­—­ provides the raw data for the international LPI. port processing, customs clearance, transport, Each survey respondent rates eight overseas mar- and the like­ —­i s a good start, and in many kets on six core components of logistics perfor- cases this information is readily available. But mance. The eight countries are chosen based on even when complete, this information can- the most important export and import markets not be easily aggregated into a single, consis- of the country where the respondent is located, tent, cross-country dataset, because of struc- on random selection, and­ —­ for landlocked tural differences in countries’ supply chains. countries­ —­on neighboring countries that form Even more important, many critical elements part of the land bridge connecting them with of good logistics­ —­ such as process transpar- international markets. The method used to select ency and service quality, predictability, and the group of countries rated by each respondent reliability­—­cannot be assessed using only time varies by the characteristics of the country where and cost information. the respondent is located (table A5.1). Table A5.1 Methodology for selecting country groups for survey respondents Respondents from Respondents from Respondents from low‑income countries middle‑income countries high‑income countries Three most important export partner countries + The most important import partner country Five most important export + partner countries Respondents from Four countries randomly, one Two countries randomly from a + coastal countries from each country group: list of five most important export Three most important a. Africa partner countries and five most import partner countries b. East Asia and important import partner countries Central Asia + c. Latin America Four countries randomly, one d. Europe less Central from each country group: Asia and OECD a. Africa Three most important b. East Asia and export partner countries Central Asia + c. Latin America The most important import d. Europe less Central Four most important export partner country Asia and OECD partner countries + + + Two land-bridge countries Two countries randomly Respondents from from the combined country Two most important import + landlocked countries groups a, b, c, and d partner countries Two countries randomly, one + from each country group: Two land-bridge countries a. Africa, East Asia and Central Asia, and Latin America b. Europe less Central Asia and OECD Source: Authors. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 59 Respondents take the survey online. For the sample size of country i so far, and N is the total 2018 edition, the survey was open between Sep- sample size. tember 2017 and February 2018. The web en- The international LPI is a summary indica- gine for 2018 was the same as the new engine tor of logistics sector performance, combining put in place in 2012. It incorporates the Uni- data on six core performance components into a form Sampling Randomized (USR) approach single aggregate measure. Some respondents did to gain the most possible responses from under- not provide information for all six components, represented countries. Because the survey en- so interpolation is used to fill in missing values. gine relies heavily on a specialized country se- The missing values are replaced with the coun- lection methodology for survey respondents try mean response for each question, adjusted based on high trade volume between countries, by the respondent’s average deviation from the the USR can help countries with lower trade country mean in the answered questions. volumes rise to the top during country selection. The six core components are: The 2017–18 survey engine builds a set of • The efficiency of customs and border manage- countries for the survey respondents that are ment clearance, rated from “very low” (1) to subject to the rule set (see table A5.1). After “very high” (5) in survey question 10. 200 surveys, the USR is introduced into the • The quality of trade and transport infrastruc- engine’s process for country selection. For each ture, rated from “very low” (1) to “very high” new survey respondent, the USR solicits a re- (5) in survey question 11. sponse from a country chosen at random but • The ease of arranging competitively priced with non-uniform probability­ —­with weights shipments, rated from “very difficult” (1) to chosen to evolve the sampling toward uniform “very easy” (5) in survey question 12. probability. Specifically, a country i is chosen • The competence and quality of logistics serv- with a probability (N – ni) / 2 N, where ni is the ices, rated from “very low” (1) to “very high” (5) in survey question 13. • The ability to track and trace consignments, Table A5.2 Results of principal component analysis for the International LPI 2018 rated from “very low” (1) to “very high” (5) in survey question 14. Component Eigenvalue Difference Proportion Cumulative • The frequency with which shipments reach 1 5.53535 5.36359 0.9226 0.9226 consignees within scheduled or expected de- 2 0.17175 0.0648739 0.0286 0.9512 livery times, rated from “hardly ever” (1) to 3 0.106876 0.0292183 0.0178 0.9690 “nearly always” (5) in survey question 15. 4 0.0776582 0.00796402 0.0129 0.9819 The LPI is constructed from these six indica- 5 0.0696941 0.0310184 0.0116 0.9936 tors using principal component analysis (PCA), 6 0.0386757 na 0.0064 1.0000 a standard statistical technique used to reduce Source: World Bank staff analysis. the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores on questions 10–15, averaged across all respondents provid- Table A5.3 Component loadings for the ing data on a given overseas market. Scores are International LPI 2018 normalized by subtracting the sample mean and Component Weight dividing by the standard deviation before con- Customs 0.4072 ducting PCA. The output from PCA is a single Infrastructure 0.4130 indicator­—­the LPI­—­that is a weighted average International shipments 0.3961 of those scores. The weights are chosen to maxi- Logistics quality and competence 0.4166 mize the percentage of variation in the LPI’s Tracking and tracing 0.4106 original six indicators that is accounted for by Timeliness 0.4056 the summary indicator. Full details of the PCA procedure are in ta- Source: World Bank staff analysis. bles A5.2 and A5.3. The first line of table A5.2 60 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y shows that the first (principal) eigenvalue of the s is the estimated standard error of each coun- correlation matrix of the six core indicators is try’s LPI score, and t is Student’s t-distribution. greater than one­ —­ a nd much larger than any As a result of this approach, confidence inter- other eigenvalue. Standard statistical tests, such vals and low-high ranges for scores and ranks are as the Kaiser Criterion and the eigenvalue scree larger for small markets with few respondents, plot, suggest that a single principal component since these estimates are less certain. be retained to summarize the underlying data. The high and low scores are used to calculate This principal component is the international upper and lower bounds on country ranks. The LPI. Table A5.2 shows that the international upper bound is the LPI rank a country would LPI accounts for 92 percent of the variation in receive if its LPI score were at the upper bound the six components. of the confidence interval rather than at the cen- To construct the international LPI, normal- ter. The lower bound is the LPI rank a country ized scores for each of the six original indicators would receive if its LPI score were at the lower are multiplied by their component loadings (table bound of the confidence interval rather than at A5.3) and then summed. The component load- the center. In both cases, the scores of all other ings represent the weight given to each original countries are kept constant. indicator in constructing the international LPI. The average confidence interval on the 1–5 Since the loadings are similar for all six, the in- scale is 0.2, or about 7 percent of the average ternational LPI is close to a simple average of the country’s LPI score. Because of the bunching of indicators. Although PCA is re-run for each ver- LPI scores in the middle of the distribution, the sion of the LPI, the weights remain very steady confidence interval translates into an average from year to year. There is thus a high degree of of 16 rank places, using upper and lower rank comparability across the various LPI editions. bounds as calculated above. Caution must be taken when interpreting small differences in Constructing the LPI scores and rankings. confidence intervals Despite being the most comprehensive data source for country logistics and trade facilita- To account for the sampling error created by the tion, the LPI has two important limitations. LPI’s survey-based methodology, LPI scores are First, the experience of international freight for- presented with approximate 80 percent confi- warders might not represent the broader logistics dence intervals. These intervals make it possible environment in poor countries, which often rely to provide upper and lower bounds for a coun- on traditional operators. And the international try’s LPI score and rank. To determine whether and traditional operators might differ in their a change in score or a difference between two interactions with government agencies­ —­ a nd scores is statistically significant, confidence inter- in their service levels. Second, for landlocked vals must be examined carefully. For example, a countries and small-island states, the LPI might statistically significant improvement in a coun- reflect access problems outside the country as- try’s performance should not be concluded unless sessed, such as transit difficulties. The low rating the lower bound of the country’s 2018 LPI score of a landlocked country might not adequately re- exceeds the upper bound of its 2016 score. flect its trade facilitation efforts, which depend To calculate the confidence interval, the on the workings of complex international transit standard error of LPI scores across all respon- systems. Landlocked countries cannot eliminate dents is estimated for a country. The upper and transit inefficiencies with domestic reforms. lower bounds of the confidence interval are then t(0.1, N–1)S Constructing the domestic LPI ± , LPI database N where LPI is a country’s LPI score, N is the The second part of the LPI survey instrument is number of survey respondents for that country, the domestic LPI, in which respondents provide C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 61 qualitative and quantitative information on the offering choices in a dropdown menu. When a logistics environment in the country where they response indicates a single value, the answer is work. coded as the logarithm of that value. When a Questions 17–22 ask respondents to choose response indicates a range, the answer is coded one of five performance categories. In question as the logarithm of the midpoint of that range. 17, for example, they can describe port charges For example, export distance can be indicated as in their country as “very high,” “high,” “aver- less than 50 kilometers, 50–100 kilometers, 100– age,” “low,” or “very low.” As in the international 500 kilometers, and so forth­ —­ so a response of LPI, these options are coded from 1 (worst) to 50–100 kilometers is coded as log(75). Full de- 5 (best). Appendix 3 displays country averages tails of the coding matrix are available on request. of the percentage of respondents rating each as- Country scores are produced by exponen- pect of the logistics environment as 1–2 or 4–5. tiating the average of responses in logarithms Question 23 referred to the use of electronic across all respondents for a given country. This platforms in logistics and to cyberthreats. method is equivalent to taking a geometric aver- With a few exceptions, questions 24–35 age in levels. Scores for regions, income groups, ask respondents for quantitative information and LPI quintiles are simple averages of the rel- on their countries’ international supply chains, evant country scores. 62 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 6 APPENDIX Respondent demographics Operators on the ground are best placed to Figure A6.1 Composition of respondents, assess the vital aspects of logistics performance. by income group The LPI thus uses a structured online survey of Number of respondents logistics professionals at multinational freight Low income forwarders and at the main express carriers. The 28 2018 LPI data are based on a survey conducted between September 2017 and February 2018, Lower middle income answered by 869 respondents at international 154 High income logistics companies in 108 countries. OECD 289 Geographic dispersion of respondents Upper middle income 354 High income Among the respondents, 62  percent are in non-OECD 44 either low income countries (3  percent) or middle-income countries (59  percent). The Source: Logistics Performance Index 2018. overall number is similar to the 2016 LPI, but this year there are relatively many more contri- Figure A6.2 Composition of respondents, butions from upper-middle-income countries. by region The lack of representation of low income coun- tries is due to their more marginal role in world Number of respondents trade, and the difficulty of communicating Middle East & South Asia North Africa 38 effectively with operators on the ground (fig- 39 ure A6.1). Sub- Among developing countries, all regions are Saharan Africa 58 well represented, especially Latin America and East Asia High income Caribbean (figure A6.2). Increasing involve- & Pacific 75 333 ment of local associations and operators will hopefully help build response rates in the future Europe & Central Asia in other regions. 134 Latin America & Caribbean Respondents’ positions 192 in their companies Note: World Bank regions do not include high-income countries, so they are The LPI assesses both large companies and included as a separate category. Source: Logistics Performance Index 2018. small and medium enterprises. Large companies (those with 250 employees or more) account for around 29 percent of responses, which is higher Knowledgeable senior company members than in 2016. Most of the responses are thus are important to the survey. The 2018 respon- from small and medium enterprises. dents include senior executives (43  percent, C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 63 fewer than in 2016), area or country managers companies with business models based on full- (13 percent), and department managers (19 per- container or full-trailer load transport (24 per- cent). These groups of professionals have over- cent) or on customer-tailored logistics solutions sight of, or are directly involved in, day-to-day (14  percent). These shares have converged as operations, not only from company headquar- compared to 2016. ters but also from country offices. The relative Among all respondents, 35  percent deal seniority of respondents has slightly decreased with multimodal transport, 25  percent with from 2016 to 2018. Two-thirds of respon- maritime transport, and 13  percent with air dents are at corporate or regional headquar- transport. These last two numbers are similar ters (39 percent) or at country branch offices to the 2016 ones, while the number of respon- (26 percent). The rest are at local branch offices dents dealing with multimodal transport has (10 percent) or independent firms (25 percent). gone down. In 2018, 6 percent of respondents 43 percent of respondents are involved in handle domestic trade, and 53 percent deal with providing a large range of logistics services as exports or imports. their main line of work. Such services include Finally, 26 percent work with most of the warehousing and distribution, customer-tai- world’s regions, while others concentrate their lored logistics solutions, courier services, bulk work in Europe (34 percent), Asia (19 percent), or break-bulk cargo transport, and less- than- the Americas (14 percent), Africa (4 percent), or full-container, full-container, or full-trailer the Middle East (3 percent). Hardly any work load transport. 38 percent of respondents are at with Australia and the Pacific (3 respondents). 64 C O N N E C T I N G T O C O M P E T E 2 0 18 T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 7 APPENDIX LPI usage reference list Abbade, Eduardo Botti. 2017. “Availability, Access and Utilization: Social Commission for Asia and the Pacific and the Organisation for Identifying the Main Fragilities for Promoting Food Security in Economic Co-operation and Development. Developing Countries.” World Journal of Science, Technology and EC (European Commission). 2014. EU Transport Scoreboard. Brussels: Sustainable Development 14 (4): 322–35. EC. Akhavan, Mina. 2017. “Evolution of Hub Port-Cities into Global Logistics Edirisinghe, Lalith. 2013. “Cross-Border Logistics Performance in Sri Centres: Lessons from the Two Cases of Dubai and Singapore.” Lanka: The Way Forward.” Paper presented at the International International Journal of Transport Economics 44 (1): 25–47. Research Conference on Business & Information. Al-Futaisi, H. E. Dr. Ahmed Mohammed Salem. 2015. Sultanate of ¸ Ekici, Sule Önsel, Özgür Kabak, and Füsun Ülengin. 2016. “Linking to Oman Logistics Strategy 2040. Muscat, Oman: Ministry of Transport Compete: Logistics and Global Competitiveness Interaction.” Transport and Communications. Policy 48: 117–28. Andreji´c, Milan M., and Milorad J. Kilibarda. 2016. “Measuring Global Erkan, Birol. 2014. “The Importance and Determinants of Logistics Logistics Efficiency Using PCA-DEA Approach.” Tehnika – Saobra´caj Performance of Selected Countries.” Journal of Emerging Issues in 63: 733–40. Economics, Finance and Banking 3: 1237–54. Au, K. F., and Chan M. H. Eve. 2010. “The Impact of Social, Economic Felipe, Jesus, and Utsav Kumar. 2012. “The Role of Trade Facilitation in Variables and Logistics Performance on Asian Apparel Exporting Central Asia.” Asia, Eastern European Economics 50 (4): 5–20. Countries.” In Innovations in Supply Chain Management for Fonseca, J. M., and N. Vergara. 2015. Logistics in the horticulture supply Information Systems: Novel Approaches, edited by John Wang, chain in Latin America and the Caribbean: Regional report based 204–16. Hershey, NY: Business Science Reference. on five country assessments and findings from regional workshops. Çemberci, Murat, Mustafa Emre Civelek, and Neslihan Canbolat. 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Climate Vulnerability Assessment: Making Fiji Climate reports.aspx?source=escap-world-bank-international-trade-costs. Resilient. Washington, DC: World Bank. http://documents.worldbank. C O N N E C T I N G T O C O M P E T E 2 0 18  T R A D E L O G I S T I C S I N T H E G L O B A L E C O N O M Y 69 What is the Logistics Performance Index? Based on a worldwide survey of global freight forwarders and express carriers, the Logistics Performance Index is a benchmarking tool developed by the World Bank that measures performance along the logistics supply chain within a country. Allowing for comparisons across 167 countries, the index can help countries identif y challenges and opportunities and improve their logistics performance. The World Bank conducts the survey every two years. Reliable logistics is indispensable to integrate global value chains—and reap the benefit of trade opportunities for growth and poverty reduction. The ability to connect to the global logistics web depends on a country’s infrastructure, service markets, and trade processes. Government and the private sector in many developing countries should improve these areas—or face the large and growing costs of exclusion. This is the sixth edition of Connecting to Compete, a report summarizing the findings from the new dataset for the Logistics Performance Index (LPI) and its component indicators. The 2018 LPI also provides expanded data on supply chain performance and constraints in more than 100 countries, including information on time, distance and reliability, and ratings on domestic infrastructure quality, services, and border agencies. The 2018 LPI encapsulates the firsthand knowledge of movers of international trade. This information is relevant for policymakers and the private sector seeking to identify reform priorities for “soft” and “hard” trade and logistics infrastructure. Findings include: • Gaps in logistics performance between the bottom and top performers persist. • Supply chain reliability and service quality are strongly associated with logistics performance. • Infrastructure and trade facilitation initiatives still play an important role in assuring basic connectivity and access to gateways for most developing countries. • The logistics policy agenda continues to broaden, with growing focus on supply chain resilience, cyber security, environmental sustainability, and skills shortages.