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The Effectiveness of Aid to Development. Focus on the Aid-Growth literature.

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par François Defourny
Facultés N-D de la Paix de Namur - Université Catholique de Louvain - Master in International and Development Economics 2005

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7.2. Risky interpretation and sensitivity to model specification

First, Lensink and White (2000) and Guillaumont (1999) indicate that the «aid×policy» interaction term needs to be interpreted carefully. It can mean both that the impact of aid on growth appreciates with the quality of policy, and that the impact of policy on growth increases with the quantity of aid.

29 This indicator has been introduced by Sachs and Warner (1995)

30 CPIA = Country Policy and Institutional Assessment

31 This policy index has been criticised as well. See Dalgaard, Hansen, and Tarp (2004) for three pertinent remarks.

Furthermore, some authors demonstrated the high sensitivity of Burnside and Dollar's results to model specification. Among those, Hansen and Tarp (2001) and Dalgaard and Hansen (2001) modify Burnside and Dollar (1997) regressions in different ways. For example, when they add an «aid²» term to the equation, the «aid×policy» interaction term looses its significance. On the other hand, aid appears to be effective on average, independently from policy variables. They also observe diminishing returns.

For Beynon (2001, p29): «There remain significant unexplained determinants of growth in all these models.» Hansen and Tarp (2001) also argue that there probably exists other unobserved country-level effects that give incorrect explanatory power to the «aid×policy» term. Indeed, if the regression fails to catch fully and properly all the determinants and constraints that influence economic growth, the estimated coefficient of aid will be biased. In this sense, Morrissey (2005, p1) underlines: «As aid is more likely to flow to poor countries that suffer growth-retarding characteristics (that are not specified), there is a greater likelihood of incorrectly drawing the conclusion that aid is ineffective.»

7.3. Other conditioning variables than economic policy

The literature contains a large number of variables, other than economic policy, that are presented to have a significant impact on economic growth. In consequence, there is a high attendant risk that any individual model does suffer from omitted variable bias and inconsistent estimators. As Gunning (2004, p54) says: «The idea is that the effect of aid on growth is conditional on a wide variety of country characteristics, not just on the policies pursued.» We will briefly present the major contributions to the discussion.

For Guillaumont and Chauvet (2001), aid is more effective in economically vulnerable countries32. In those countries, exposed to external shocks, it appears to be more difficult to maintain consistent economic policies. They conclude that aid should be allocated in priority to countries suffering from external shocks, terms of trade difficulties or natural disasters in order to help them to stabilize. Suspend their assistance because of poor policies would be very damaging. In the same sense, Collier and Dehn (2001) say that aid has more impact on growth in countries suffering from extreme fall of export prices.

32 Economical vulnerability can be measured by the instability of the agricultural production, the instability of exports earnings, long-term terms of trade trend and the size of the population.

Bloom and Sachs (1998) and Gallup et al. (1999) all find that geography has a significant impact on growth33. From this, Dalgaard et al. (2004) investigate the aid-growth relationship for countries with part of their territory in the tropical areas. An advantage of this variable is the absence of endogenity worries. On average, aid seems to influence positively growth outside the tropics but not in them. In consequence, Dalgaard et al. (2004) see tropical area as an exogenous «deep determinant» of growth. If we refer to the principle of selectivity of Burnside and Dollar (1997), it would obviously be particularly unfair to penalise tropical countries because of their geographic situation.

The literature contains an extensive variety of other variables that have been found to condition significantly the efficiency of aid. Hence, Svensson (1999) highlights that aid is more effective in places with democratic institutions, whereas Islam (2003) pretends exactly the opposite, namely totalitarian governments reinforce the impact of aid on growth. For Petterson (2004), the degree of fungibility of aid in the recipient country is decisive. Collier and Hoeffler (2002) find out that countries emerging from conflict have larger absorptive capacities.

All these variables plausibly influence the aid-growth relationship and there probably exist others. However, Roodman (2003) find that for most of these studies, the significance of the results were very sensitive to observations and extensions of dataset. In any case, the conditional efficiency of aid seems to be much more complex than suggested by Burnside and Dollar (1997).

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