Conditional growth models: 3rd generation studies

Much of the research on the impact of aid on economic growth conducted since the late 1990s falls within the third generation of studies. This group of studies is premised on the fundamental determinants of growth and analyses cross-national variation in economic growth by focusing on the role of institutions (legal, socio-political and economic) in both donor’s as well as recipient’s aid allocation policies and how these affect economic growth. Furthermore, this generation is motivated by the availability of better data from developing countries as well as progress in conducting more sophisticated econometric analysis that allows for estimation of changes across and within countries over time.

13_{See also Boone (1996), McGillivray and Morrissey (2000), Isopi and Mavrotas (2009) and Feyzioglu} et al. (1996)

This wave of studies became more popular especially since the publication of the World

Bank study ’Assessing Aid (1998)’ which recommended a rethinking of aid and gave

prominence to the concept of aid conditionality/selectivity in an attempt to improve the policy environment in aid-receiving countries. The main feature of this generation of aid effectiveness literature was the idea that there exists an interaction between aid and institutions/policies in the recipient nations that is crucial in making aid effective i.e. aid is seen to work in good policy countries and not work in bad policy ones. The implicit

conclusion of the World Bank Report and the paper by Burnside and Dollar (1997)14 _on

which the Report is based, is that aid is very fungible and so aid can only reduce poverty through economic growth if there are good policies in place.

The third generation also places explicit emphasis on understanding and addressing endo- geneity of aid which arises, as already alluded to earlier, from reverse causality. Endogene- ity of aid poses a significant challenge when analysing the impact of foreign aid as it makes estimating the response of growth to variation in foreign aid difficult. The fundamental problem is that aid is allocated to countries based on individual country characteristics, rather than being a random allocation. This not only makes simple correlations in the econometric analysis uninformative, but they also render regression approach highly prob- lematic that even a systematic approach to choosing control variables will not solve the identification problem.

In the econometric analysis, measures of economic policy, political and institutional vari- ables in the regression analysis were introduced alongside the traditional macroeconomic growth controls. In the literature, these policies include fiscal performance, market liber- alization, trade openness, monetary policies etc. The studies used panel data estimation for a number of years covering a large number of countries; the data usually includes many indicators of trade and economic activity for developing countries. The use of panel data also gave the new growth models the convenience of accounting for country specific

effects (Roodman (2007a) and Moreira (2005)).

A typical third generation regression equation takes the form:

gi(t) =α+gdpi(t−1) +s(i)t+βa0i(t) +ζzi0t+ωai(t)zi(t) +γjc0i(t) +µi(t) (2.2.1)

14_{A later version of this research was published as Burnside and Dollar (2000) in the American Eco-} nomic Review, hence for the remainder of the thesis we will be citing the published version.

where, other than the notation already used in the regression models of the first two generations,gdpi(t−1) is initial GDP,a0i(t) is a vector of aid variables including aid itself

(as a share of GDP/GNI), the square of aid and in other studies different lags of aid.

zi0(t) is a vector of conditional variables,15 the most commonly used in the literature being

policy index (measures of macroeconomic policies that affect output growth). ai(t)zi(t) is

the interaction term included as another way of capturing non-linearity in the aid-growth relationship other than introduction of a squared aid term.

Aside from the controls included in the second generation models, this generation of studies includes as explanatory variables (treated to be exogenous) factors such as ini- tial income levels, measures of institutional quality, measures of ethnic fractionalisation, measures of the frequency of assassinations, interaction between ethnic fractionalisation and assassinations, M2 as a fraction of GDP (in some studies including lags of M2),

geographical region dummies etc. In equation (2.2.1), these are captured byc0_i(t).

Boone (1996) stimulated the conditional aid effectiveness debate; using panel data for 91 countries covering the period 1971-1990, the study investigated the impact of aid on investment, consumption and measures of well-being and examined whether aid effective- ness was conditional on the political regime. His results indicated that foreign aid leads to increases in government consumption rather than increasing investment or benefiting the poor, and also that there was no evidence to suggest that the impact aid varies with different forms of regime.

In perhaps the most cited work of this generation (about 4517 citations according to Google Scholar (as of Oct 2016)), Burnside and Dollar (2000) conducted panel growth regressions using data for the period1970 -1993 from 56 aid receiving developing countries, examining the relationship between foreign aid, policies and growth of per capita GDP and found that aid has a significant and robust positive relationship with growth in countries that have good fiscal, monetary and trade policies. In response to early critics of Burnside and Dollar (2000) study, in Burnside and Dollar (2004), they used a different dataset focusing mainly on the 1980s and 1990s for 42 low income countries and found

15_{Unlike the earlier generations, this group of studies also explored potential non-linearities in the} aid-growth nexus, so that the regression analysis includes a quadratic aid term. There are strong reasons behind the expectation of non-linearity between aid and growth; in the literature the most cited include recipient country’s limited absorption capacities (Hadjimichael et al. (1995)) while Durbarry et al. (1998) further refers to the optimal borrowing and the incidence of Dutch disease problems

similar results: that aid has a robust causal effect on growth of output per capita in economies where there is a good policy environment.

Some of the strongest aid critics in recent times such as Easterly (2003, 2008) and Moyo (2009) maintain that due to the lack of accountability in the aid delivery mechanism as well as rampant corruption in the recipient countries, foreign aid has done more bad than good. It has left recipient countries in a vicious cycle that fosters corruption, interference in the rule of law, establishment of civil institutions and protection of civil liberties. This creates an environment where foreign investment is untenable and coupled with low domestic savings, it retards growth, reduces job opportunities and hence escalating poverty. Thus they argue against the findings of the third generation studies; that even in economies with good policy environment, there is little evidence to suggest that aid has had a positive effect on the growth of per capita output.

Cross-country analysis remains the popular approach to estimating the growth effects of aid flows in developing countries. Despite this, the literature has long recognised the ap- propriateness of country-specific studies over cross-country studies in analysing the growth effects of aid (Pack and Pack (1990); White (1992)). There is growing recommendations in recent literature suggesting that better results on the determinants of economic growth can better be achieved by conducting detailed single country analysis (Rodrik (2003)). Cassen (1994) and Lloyd et al. (2001) discussed and concluded that using single-country approach, rather than cross-country approach, in analysing macroeconomic effects of aid on growth might be a more appropriate strategy and could lead to more robust evidence on the causal relationship between foreign aid and economic growth.