The Allocation of Aid for Trade: What Does the Cross-National Evidence Tell Us? Yiagadeesen (Teddy) Samy & Jane Imai The Norman Paterson School of International Affairs Carleton University May 2010
Outline of Presentation Motivation The AFT initiative: a brief history Theoretical framework Empirical model and data used Empirical results Conclusions
Motivation Emerging consensus: developing countries need to be financially supported to cover the costs associated with trade liberalization such as preference erosion, trade facilitation and capacity building, and the implementation of trade agreements The OECD divides aid for trade (AFT) into TRTA/CB, trade-related infrastructure, and productive capacity building The WTO identifies four areas of focus: 1) trade policy and regulation 2) economic infrastructure 3) productive capacity building 4) adjustment assistance
Motivation Is AFT achieving these objectives? Is it targeting the countries that need it the most? In this paper we examine AFT allocation over the period We augment an aid allocation model with trade-related and infrastructure variables. We find that although AFT is significantly related to recipient needs, political factors and government effectiveness, it could be better targeted towards trade infrastructure and the trading environment (i.e. VOI)
The AFT Initiative: A Brief History Long-standing debate on relative importance of aid and trade and their impact on development –Aid more valuable than trade because it represents a direct resource flow (Thirlwall 1976) –Trade generates benefits such as economies of scale and spillover effects (Yeats 1982) –Greater focus on social development in 1990s; less emphasis on investments in infrastructure and trade –Millennium Development Goal to cut global poverty in half
The AFT Initiative: A Brief History Conclusion of Uruguay Round (1994) led to a greater need for resources, but cost issues not addressed in the WTO Doha Declaration (2001) called for improved market access and balanced trade rules Attention increasingly turned to supply side constraints and the need for active intervention Launch of Aid for Trade Initiative in Hong Kong (2005); OECD and the Paris Declaration on Aid Effectiveness
The AFT Initiative: A Brief History The analysis of aid for trade allocation is timely and critical because: –AFT can have a real impact on livelihoods –Donors’ aid commitments must be maintained –Biases in aid allocation, particularly bilateral aid, can be confirmed –It can help improve the delivery of aid and its impact on development
Theoretical Framework Simple extension of Dudley and Montmarquette (1976) A single donor allocates its aid to ‘r’ recipient countries Utility function of donor is given by (1) where X is the only other good consumed besides aid, M is the subjective impact of AFT to recipient countries (that is, benefits to donor as a result of giving aid)
Theoretical Framework Impact function is given by (2) where n i = population of recipient country i, A i is aid received by recipient country i, y i is per capita income of recipient country i and Z i is a vector of other characteristics affecting aid’s impact on country i.
Theoretical Framework We expect that The impact function is given by (3) and
Theoretical Framework Assuming there are no savings in this model, the donor will allocate its national income between good X and aid as follows (4) The donor maximizes U subject to (4), and taking into account (2) and (3) Setting up the Lagrangian for this maximization problem and taking the first-order conditions yields the following:
Theoretical Framework (5) In equilibrium, MRS’s are the same across recipients so that (6) Re-arranging equation (6) yields (7)
Theoretical Framework Taking the log transformation of equation (7) and suppressing subscripts yields (8) where
Empirical Model and Data Used Aid allocation studies: –Alesina and Dollar (2000): donor interests, political factors, recipient needs –Neumayer (2003a, b): political and civil rights are significant but human rights have a limited role at best –Alesina and Weder (2002); Dollar and Levin (2002): aspects of governance such as level of corruption, institutions, policies.
Empirical Model and Data Used Model estimated –based on equation (8); BAFT and MAFT estimated separately –control for recipient needs, country size, political factors, quality of institutions and policies –VOI: to evaluate whether AFT is being properly targeted; variables related to infrastructure and trading environment –dependent and independent variables averaged over three year periods with a one year lag
Empirical Model and Data Used AFT obtained from the OECD’s Creditor Reporting System (CRS) database; zeros treated as missing observations Income, population, trade openness and infant mortality data from World Development Indicators (WDI) Political variables from Freedom House Government effectiveness data from Worldwide Governance Indicators by Kaufmann et al. (2009)
Empirical Model and Data Used VOI from International Road Federation, WDI and UNCTAD Ratio of bilateral to multilateral AFT is 8:1 (2006) Large amounts of AFT allocated to the biggest countries (e.g. China, India)
Empirical Model and Data Used Table 1 Summary Statistics Variable Name Number of Obs’ns MeanMedianStandard Deviation Bilateral AFT (US$ m) Multilateral AFT (US$ m) GDP per capita (US$) Infant Mortality Population (m) Democracy (Freedom House) Openness Government Effectiveness Road Reliability of Electricity Telephone Mainlines Internet Users Trade Taxes (% Tax Revenue) Export Concentration
Empirical Model and Data Used Figure 1 Evolution of AFT (Bilateral and Multilateral, ) Source: OECD CRS Database
Empirical Results Estimation with and without country fixed effects Equation estimated separately for bilateral and multilateral AFT Summary of results: –Without fixed effects (bilateral AFT): a 1% decrease in income per capita leads to an increase of % in AFT find evidence of middle income bias in AFT allocation and some bias towards countries with smaller populations
Empirical Results Summary of results: –Without fixed effects (bilateral AFT) (cont’d) the threshold at which the relationship between income per capita and AFT reverses occurs anywhere between a per capita income level of US$797 to US$917 population bias for countries with <5m democracy and government effectiveness highly significant no evidence that VOI are being targeted
Empirical Results
Summary of results: –With fixed effects (bilateral AFT): a 1% decrease in income per capita leads to an increase of % in AFT evidence of middle income bias in AFT allocation disappears but significant inverse relationship between population size and bilateral AFT democracy and government effectiveness remain highly significant no evidence that VOI are being targeted
Empirical Results
Summary of results: –Without fixed effects (multilateral AFT): income per capita is highly significant and multilaterals are responding to physical need as well population size does not matter: less strategic government effectiveness remains highly significant and twice as big in magnitude, but democracy no longer significant no evidence that VOI are being targeted –With fixed effects (multilateral AFT): when estimation is possible, no evidence that VOI are being targeted
Empirical Results Sensitivity (for bilateral AFT) –Excluding outliers (US$>200m, that is, about three times the mean) did not change the results –By excluding high- and upper-middle income countries, the signs and significance of income per capita, democracy and government effectiveness did not change –Some evidence that VOI related to infrastructure are more significantly related to AFT allocation than before
Empirical Results
Conclusions AFT is similar to general aid allocation when one considers variables such as income per capita, democracy and the quality of government institutions and policies There are differences between bilateral and multilateral AFT allocation: different emphasis on recipient needs, strategic difference No significant evidence that VOI are being targeted
Conclusions More work needed in terms of: –Better data on VOI, across countries and over time –Examining further how different categories of AFT are allocated –Examining bilateral AFT by individual donors to see whether there are differences in behaviour