Aid for Trade: Ensuring That the Most Needy Get It

Aid for Trade: Ensuring That the Most Needy Get It Richard Newfarmer International Growth Centre Paris, March 28, 2011 This presentation is based on Elisa Gamberoni and Richard Newfarmer Aid for Trade: Matching Potential Demand with Supply World Bank Policy Research Paper 4991 and Elisa Gamberoni and Richard Newfarmer, Aid for Trade: Do the Most Needy Get It? draft 2011

Key questions: Which countries might have a potential demand for aid for trade, either because of poor trade performance or because of capacity constraints that hamper trade? Is the supply of aid for trade going to countries that have a potential demand for it? Which countries are receiving below average aid for trade relative to their potential demand? Corollary: Which indicators seem most useful for monitoring aid for trade because of their predictive effects on trade performance?

Why do we care about aid for trade? Globalization risky? What do you mean?

Google map to our logic. Which countries have greatest need potential demand? Trade performance 5 Indicators Capacity : Infrastructure, Institutions, incentives Which indicators predict trade level? 5 Indicators Measuring potential demand -- rankings by quintile Indicator 1 2 3 4 5 6 7 8 9 10 Total Country (highest) 1 1 1 1 1 1 1 1 1 1 = 10 : Country (lowest) 5 5 5 5 5 5 5 5 5 5 = 50 Does supply of aid go to countries with the higest demand? Aid for Trade / GDP demand Income p.c., aid effectiveness Which countries have less aid for trade than they might demand?

Caveats Paper does not analyze why a country might receive less aid for trade It might not need it It might have higher priorities It might not use it well The effort here is not to provide answers for individual countries -- but to provide the big picture and to provoke questions at the national level on competitiveness and aid for trade stategy

Potential demand arises from poor trade performance and weak trade capacity Trade performance Several ways to measure.. 1. Growth rate of exports of goods and services

Trade performance varies but 29 low income countries figure in the bottom two quintiles Bosnia Zambia Rwanda Vietnam Mozambique Cambodia Lao PDR Guinea-Bissau Cape Verde Myanmar Burundi Azerbaijan Grenada Ethiopia Armenia Lesotho India Bhutan Bangladesh Mali Georgia Haiti Nicaragua Uganda Angola Congo, DR. Mauritania Ghana Moldova Burkina Faso Bolivia Nepal Pakistan Tanzania Côte d'ivoire Sri Lanka Tajikistan Congo, Rep. Gambia, The Sierra Leone Niger Cameroon Madagascar Honduras Uzbekistan Kenya Nigeria St. Lucia Samoa Kyrgyz Republic C. African.Republic Djibouti Eritrea Benin Zimbabwe Senegal Yemen, Rep. Guinea Guyana Malawi 1 st quintile 2 nd quintile 3 rd quintile 4 th quintile 5 th quintile -15-10 -5 0 5 10 15 Source: Authors calculation. World Bank,WTI Note: Quintile scale are from the entire sample of low and middle income countries

Despite export growth, about half of LICs lost market share Low income countries: Change in market share, 1996-2006 India Viet Nam Nigeria Angola Azerbaijan Equatorial Guinea Sudan Cambodia Bangladesh Chad Yemen Myanmar Zambia Mozambique Georgia Congo Bolivia Ghana Mongolia Nicaragua Armenia Cameroon Ethiopia Mali Cape Verde Haiti Lesotho Tanzania Laos Rwanda Sierra Leone Guinea-Bissau Mauritania Burundi Comoros Kyrgyzstan Burkina Faso Djibouti Maldives Dominica Saint Lucia Niger Madagascar Uganda Central African Gambia Eritrea Honduras Moldova Kenya Benin Malawi Guyana Senegal Guinea Congo DR Uzbekistan Nepal Côte d'ivoire Sri Lanka Papua New Pakistan 1 st quintile 2 nd quintile 3 rd quintile 4 th quintile 5 th quintile Source: Authors calculation. Wolrd Bank,WTI Note: Quintile scale are from the entire sample of low and middle income countries

Potential demand arises from poor trade performance and weak trade capacity Trade performance Several ways to measure.. 1. Growth rate of exports of goods and services 2. Change in global market share 3. Change in competitiveness in existing markets 4. Growth rates of export markets product and geographic markets

Sources of export growth: competitiveness or demand growth? Gaining competitiveness in slow growing markets Competitiveness effect Gaining competitiveness in fast growing markets + - Azerbaijan, Bangladesh, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Burkina Faso, Cambodia, Chad, Comoros, Djibouti, Ghana, Haiti, India, Kenya, Kiribati, Laos, Mali, Mauritania, Mozambique, Rwanda, Samoa, Sierra Leone, Solomon Is, Sri Lanka, Tajikistan, Togo, Uzbekistan, Vanuatu, Viet Nam. ++ Angola, Armenia, Cape Verde, Congo, Equatorial Guinea, Georgia, Myanmar. Losing competitiveness in slow growing markets -- Burundi, Cameroon, Central Afr. Rep., Côte d'ivoire, Congo D. R., Dominica Eritrea, Ethiopia, Gambia, Grenada, Guinea, Guinea-Bissau, Guyana, Honduras, Liberia, Madagascar, Malawi, Maldives, Moldova, Nepal, Nicaragua, Pakistan, Papua New Guinea, Saint Lucia, Saint Vincent, Sao Tome and P., Senegal, Somalia, Sudan, Tanzania, Tonga, Uganda, Zambia, Zimbabwe. Source: Authors calculations based on International Trade Center, Trade Performance indicator +- Kyrgyzstan, Mongolia, Niger, Nigeria, Yemen. Demand Losing competitiveness in fast growing markets

Dependence on a few exports exposes countries to terms of trade shocks Terms of trade volatility 30 Developing Countries: Terms of trade volatility (1996-2006) 25 20 15 10 5 0 0 10 20 30 40 50 60 70 80 90 100 Concentration Index Source: Authors calculation based on World Bank, Wolrd Development Indicators and World Trade Indicators

Concentration Index average 1996-2006 Low income countries India Bosnia and Herzegovina Djibouti Georgia Viet Nam Pakistan Sri Lanka Madagascar Nicaragua Moldova, Rep.of Bolivia Senegal Nepal Kenya Honduras Zimbabwe Tanzania, United Rep. of Myanmar Togo Lao People's Democratic Republic Armenia Kyrgyzstan Grenada Guyana Côte d'ivoire Bhutan Uganda Uzbekistan Eritrea Cambodia Gambia Mongolia Saint Vincent and the Grenadines Bangladesh East Timor Papua New Guinea Lesotho Ghana Dominica Niger Cape Verde Maldives Cameroon Mozambique Haiti Vanuatu Saint Lucia Rwanda Ethiopia Central African Republic Tonga Tajikistan Democratic Republic of the Congo Zambia Malawi Sudan Guinea Azerbaijan Benin Solomon Is Kiribati Burkina Faso Guinea-Bissau Mauritania Samoa Mali Burundi Sierra Leone Comoros Congo Equatorial Guinea Yemen Sao Tome and Principe Angola Nigeria 1 st quintile 2 nd quintile 3 rd quintile 4 th quintile 5 th quintile 0 20 40 60 80 100 Source: Authors calculation. Wolrd Bank,WTI Note: Quintile scale are from the entire sample of low and middle income countries

Besides trade performance, potential demand should include trade capacity Objective: Find capacity indicators that predict trade levels How? Literature: Infrastructure, Institutions, Incentives But many measures of each of these how can we select? So we analyzed bilateral trade levels using a gravity model to find out which were most powerful of predictors trade levels

What capacity indicators influence bilateral trade? A gravity model permits us to hold other factors constant Controls? GDP of home country GDP of partner Distance FTA, WTO membership Trade = 200 U K Trade = 50 S Capacity indicators? Infrastructure Institutions Incentives Trade = 100 T

Besides trade performance, potential demand should include trade capacity Objective: Find indicators that predict trade levels Infrastructure 1. Quality of infrastructure and information technology LPI (2) Institutions 2. Quality of customs LPI (3) 3. Time to export Doing Business Incentives 4. Peak tariffs (# of lines 3x average tariff level) 5. Tariff overall restrictiveness index - OTRI

Infrastructure, institutions and incentives influence trade Effects of 1% change in infrastructure, institution, and incentive on exports Infrastructure Institutions Incentives Transport and IT Time to export Customs efficiency Trade restictions Tariff peak Control variables (selected) b WTO FTA a a Distance GDP of importer -3 0 Change in exports % Note: Marginal effects calculates at the average of the sample. a represents the change passing from zero to one. The rest of the variables refers to change of 1 percentage point. b Other control variables are listed in the Annex.

Infrastructure, institutions and incentives influence trade Effects of 1% change in infrastructure, institution, and incentive on exports Infrastructure Institutions Incentives Transport and IT Time to export Customs efficiency Trade restictions Tariff peak Control variables (selected) b WTO FTA a a Distance GDP of importer -3-2 -1 0 1 2 3 4 5 Change in exports % Note: Marginal effects calculates at the average of the sample. a represents the change passing from zero to one. The rest of the variables refers to change of 1 percentage point. b Other control variables are listed in the Annex.

About 60% of LDCs figure in the bottom two quintiles of infrastructure rankings for all developing countries 100% 80% 60% 40% Passing from the fourth quintile to the third quintile raise trade by 35% 20% 0% LDC Other low income Middle Income Source: Authors calculation based on World Bank, LPI Indicators

Quantifying potential demand adding it up Trade performance 1 Growth of exports 2 Change in market share 3 Competitiveness in existing markets 4 Demand structure 5 Concentration- diversification Capacity 6 Infrastructure 7 Customs 8 Time to export 9 Tariff peaks 10 Overall tariff restrictiveness Score every country on 10 dimensions 1 for highest quintile to 5 for lowest quintile Least demand (best score) = 10. to highest need for aid for trade = 50

Potential demand for aid for trade Countries in the bottom two quintiles Congo Lesotho Tanzania Moldova Gabon Colombia Vanuatu Laos Haiti Gambia Zambia Uganda Sudan Mauritius Kyrgyzstan Saint Vincent and the Sao Tome and Principe Burundi Paraguay Mali Guinea Ethiopia Burkina Faso Solomon Is Yemen Syrian Arab Republic Comoros Rwanda Papua New Guinea Niger Madagascar Micronesia Fiji Nepal Eritrea Tajikistan Namibia Uzbekistan Jamaica Congo DR Benin Somalia Samoa Malawi East Timor Central African Sierra Leone Guyana Source: Authors calculation based on data from ITC and World Bank.

Does potential demand match supply? Aid for trade (GDP) is determined by potential demand, p.c. income, and aid effectiveness Supply of aid for trade /GDP BIH GEO ARM NIC VUT SLB Good news: positive correlation Other news: many countries underserved VNM LBR MOZ IND DMA MNG TMP STP MRT LCA BOL AZE LAO CAF CMR KGZ BEN KHM HTI TON CPV ZMB COG COM LKA MDA PNGTJK SEN KEN BTN GNB GRD HND GIN AGO SDN KIR BFA YEM LSO GMB GHA ETH RWA NPL BDI PAK MLI MWI UZB BGD TZA DJI MDG CIVNGA SLE NER UGA ZAR MDV ERI GNQ GUY TGO TCD Potential demand for aid for trade Source: Authors calculation based on 2006 cross section regression

Conclusions Aid for trade potential demand outstrips current supply While trade performance of developing countries as a group has been strong, many countries are performing below average and many countries are vulnerable to a slowing global economy Particular at risk are those with poor trade performance slow growth, declining market shares, and concentrated exports and those with poor infrastructure, institutions and export incentives While aid for trade supply is broadly correlated with potential demand, still, several countries that have the highest potential demand are receiving less- than- average levels of aid for trade.

Conclusions A corollary about indicators Several indicators of trade performance are readily available from the World Trade Indicators, the International Trade Center, and the WTO s Trade Profiles Indicators of trade capacity also are available, and several are strong predictors of future trade performance Infrastructure -- Logistics Performance Index (used here), the Limao- Venables index, and the communication index Trade-related institutions -- customs component of the LPI and the time to export index of the Doing Business. Incentives to exports include the tariff peak index and the OTRI But indicator gaps still remain, particularly on NTBs, implementation of FTAs, and services restrictions. The international community has to invest more in filling these gaps.

Selected References For details to this presentation, see Elisa Gamberoni and Richard Newfarmer Aid for Trade: Matching Potential Demand with Supply World Bank, Sept 15, 2008 Collier, P. and D. Dollar (2002), Aid allocation and poverty reduction, European Economic Review, Vol. 46 (8), pp. 1475-1500. Djankov, S., Freund, C. and S. Pham Cong (2006), Trading on time, Policy Research Working Paper 3909, The World Bank. Francois J. and M. Manchin (2007), Institutions, Infrastructure, and Trade, IIDE Discussion Papers 2007-401, Institute for International and Development Economics. Hoekman B. and A. Nicita (2008), Trade Policy, Trade Costs and Developing Country Trade. Jansen, M. (2004), Income volatility in small and developing economies: export concentration matters, World Trade Organization Publication. Limao, N. and Venables, A. J. (1999), Infrastructure, geographical disadvantage, and transport costs, Policy Research Working Paper 2257, The World Bank. Nordas, H. and R. Piermartini (2004), Infrastructure and Trade, WTO Staff Working Paper, World Trade Organization. Turnovsky, S.J. and P. Chattopadhyay (2003), "Volatility and Growth in Developing Economies: Some Numerical Results and Empirical Evidence", Journal of International Economics 59. Wilson, J. S., Mann, C. L. and T. Otsuki (2004), Assessing the potential benefit of trade facilitation: A global perspective, Policy Research Working Paper 3224, The World Bank.