Over decades much attention has been devoted to the relationship between foreign aid and economic growth, while few studies have focused on the effects of foreign aid on female empowerment. This despite the fact that empowerment of girls and women is a key driver of development, and often an explicit objective of foreign aid. Using geo-coded data on aid project placement and household-level survey responses, Perrotta Berlin, Bonnier and Olofsgård (2023), show that foreign aid has a modest but robust effect on several dimensions of female empowerment. This is the case for both aid in general and gender-targeted aid, highlighting the potential of foreign aid to reduce gender inequalities. It is also found, though, that the impact is contingent on the context, and that there can even be a backlash in male attitudes towards female empowerment in more traditional communities.
The donor community has long been invested in the empowerment of women and girls, and the 2030 Agenda for Sustainable Development also includes gender equality as an explicit goal. Yet surprisingly little quantitative research has tried to make a broader assessment of the effect of foreign aid on gender equality measures.
This policy brief summarises a study by Perrotta Berlin, Bonnier and Olofsgård (2023) which addresses this question by matching the location of aid projects with geo-coded household surveys in Malawi between 2004 and 2010. Analysing the community-level impact on five different female empowerment indices, the study finds foreign aid to affect positively women’s empowerment across several dimensions. Furthermore, the authors find that gender-targeted aid has an additional impact on an index measuring women’s control over sexuality and fertility-related decisions and an index focusing on violence against women.
When considering areas with patrilineal land inheritance traditions, the results however partly shift, especially in relation to men’s attitudes. This implies that the success of foreign aid and gender-targeted aid in reducing gender inequalities may be conditional on the community context.
Gender Equality and Foreign Aid in Malawi
Malawi is highly dependent on foreign aid. Net official development assistance (ODA) has exceeded 10 percent of gross national income yearly since 1975, reaching as high as 23.5 percent in 2016 (World Bank, WDI database).
In recent years, reforms have been undertaken by the Malawian government to improve gender equality. The minimum legal age of marriage was raised from 15 to 18 through the 2015 Marriage, Divorce and Family Relations Bill, and the 2013 Gender Equality Act strengthened the legislation concerning gender-based violence and included a universal condemnation of all types of gender-based discrimination. Yet, in 2020, Malawi was ranked 116 out of 153 in the World Economic Forum Gender Gap Report and 172 out of 189 in UNDP’s Gender Inequality Index. An area of concern regards the high rates of child marriage, with 9 percent of girls already married at age 15 and 42 percent by the age of 18. Alongside these numbers, 31 percent of women report to have given birth by the age 18.
Another aspect potentially influencing gender equality is the prevalence of matrilinear land tenure systems, particularly in the southern and central parts of the country (as depicted in Figure 1). While previous research has shown that land ownership empowers women and suggested that property rights affect decision power over key decisions, fertility preferences, age of marriage etc., less research has been devoted to analysing the effects on women’s empowerment outcomes in a matrilinear kinship setting. Some recent literature however suggests women in matrilinear societies have greater say in household decisions – including financial ones – and are less accepting of, as well as exposed to, domestic violence (Lowes, 2021; Djurfeldt et al., 2018).
Figure 1. Intensity of matrilineal tenure in Malawi.
Methodology and Data
For the analysis, the authors make use of geo-coded data on aid projects from the Government of Malawi’s Aid Management Platform (AMP) and match it to household-level data from the Malawi Demographic and Health Survey (DHS). The country of Malawi and the period 2004-2010 were chosen in order to maximize data coverage on aid disbursement. Malawi’s AMP covers 80 percent of all aid entering the country during those years, which gives a much more complete picture compared to only focusing on one specific donor.
To identify causal impact, the authors apply a difference-in-differences specification on survey clusters in proximity to aid projects implemented between 2004 and 2010. Proximity was identified as within a 10-kilometer radius from an aid project. Among those, households interviewed in 2004, i.e., prior to the implementation date of any aid project, were considered the control group, and households interviewed in 2010 formed the treatment group. The underlying assumption of parallel pre-treatment trends was confirmed with the use of earlier DHS surveys. The model specification includes individual-level controls (age, ethnicity, household size, a Muslim dummy, years of education and literacy) and also a geographic fixed-effect based on a grid of coordinates.
The analysis distinguishes between the impact of aid in general, and the additional impact of gender-targeted aid. Gender-targeted projects are defined as projects that have any of the words woman, girl, bride, maternal, gender, genital or child, in the title, description or activity list. When estimating the effect of gender-targeted aid the authors control for overall aid intensity in the household’s vicinity. The estimated effect should therefore be interpreted as the additional effect from being exposed to a gender-targeted aid project while keeping the general number of aid projects in the area constant.
Figure 2. Map of aid projects and household clusters from 2004 and 2010 survey waves in Malawi.
To capture female empowerment, the authors make use of thousands of responses to DHS survey waves from 2004 and 2010. From these responses, the authors construct four different indices. Two of these are modelled on indices used in different contexts by Haushofer and Shapiro (2016) and Jayachandran et al. (2023). The former captures experiences of violence together with men’s and women’s attitudes towards violence, and some measures of decision making and control over household resources. The more recent index by Jayachandran et al. (2023) focuses on female agency and includes questions on women’s participation in decisions on large household purchases and daily expenditures, decisions on family visits, and decisions concerning their own healthcare.
To also capture questions related to sexual and fertility preferences, often regarded as measures of female empowerment, the authors construct two additional indices. The women’s attitudes index is based on responses to questions about whether the respondent is able to refuse sexual intercourse with her husband and ask him to use a condom, age at first marriage, and age at first childbirth, among others. The men’s attitudes index is based on questions about whether the respondent thinks it is justified to use violence to force intercourse, if a woman is justified to refuse intercourse, as well as fertility and child spacing preferences. In addition, all four indices are weighted and combined into an aggregated general index.
Considering all aid projects, the authors find that being exposed to an aid project in the 2004 to 2010 window has a significant positive impact on the agency index, the female attitude index and the combined general index (12, 11 and 31 percent of their respective means). When considering gender-targeted aid, the authors found the exposure to at least one such project to increase the women’s attitude index by 7 percent and the general index by 17 percent of their respective means. The impact is present for both a narrower and a wider exposure area, and quite persistent over time.
When breaking down the analysis for areas with matrilineal versus patrilineal land tenure systems the results diverge. In communities where the share of matrilineal ethnic groups exceeds the mean of 73 percent, the results are largely in line with those in the full sample. In patrilineal communities (< 73 percent matrilineal households), the results are however vastly different. Aid projects in general, and gender-targeted aid in particular, affect negatively the men’s attitudes index. In addition, gender-targeted aid seems to have no additional impact on the other indices.
In the paper underlying this brief, the authors study the effect of foreign aid on female empowerment, a frequent but understudied objective often set by donors. Looking at geo-coded aid projects in Malawi, the authors estimated such projects to positively impact girl’s and women’s empowerment across several indices. This is true for aid in general, and for some indices even more so when considering gender-targeted aid. Some of the positive results disappear or even change sign, though, in patrilineal communities, displaying the significance of pre-existing community norms for the effectiveness of development investments. Aid even generates a backlash when it comes to men’s attitudes towards women’s sexual and fertility preferences in these communities.
The takeaway from the study lies in foreign aid’s potential to empower women in targeted communities. This however hinges on pre-existing norms in recipient communities – something that aid donors should be aware of.
The authors emphasize the need for more research to better understand the role of pre-existing norms in the uptake of aid, to distinguish direct effects from aid from potential spillovers, and to understand what type of aid projects deliver the best outcomes in terms of female empowerment.
- Djurfeldt, A. A., E. Hillbom, W. O. Mulwafu, P. Mvula, and G. Djurfeldt. (2018). “The family farms together, the decisions, however are made by the man” -Matrilineal land tenure systems, welfare and decision making in rural Malawi. Land use policy 70, 601-610.
- Haushofer, J. and J. Shapiro. (2016). The short-term impact of unconditional cash transfers to the poor: experimental evidence from Kenya. The Quarterly Journal of Economics, 131(4), 1973-2042.
- Jayachandran, S., M. Biradavolu, and J. Cooper. (2023). Using machine learning and qualitative interviews to design a five-question survey module for women’s agency. World Development 161, 106076.
- Lowes, S. (2021). Kinship structure, stress, and the gender gap in competition. Journal of Economic Behavior & Organization 192, 36-57.
- Perrotta Berlin, M., Bonnier, E., and A. Olofsgård. (2023). Foreign Aid and Female Empowerment. SITE Working Paper Series, No. 62.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
This brief provides an overview of the discussion on the relative merits of grants and loans in the literature on foreign aid, including a short section on debt relief initiatives. These claims are then tested against the context of Ukrainian post-war reconstruction, and it is argued that the case for providing grants is very strong. This argument is based on the magnitude of the investments needed, the need to create a long-run sustainable economy, the road towards a future EU membership, and the global value of a democratic and prosperous Ukraine as a bulwark against autocratic forces.
One topic in the discussion on the post-war reconstruction of Ukraine is to what extent foreign support should come as loans or grants. The case at hand regards reconstruction in the aftermath of a military invasion by an aggressive neighbor. Therefore, Ukrainian reconstruction is sometimes compared to the Marshall Plan, the US package to help rebuild Europe after World War II. But this choice is also part of the more general discussion on foreign aid, comparing concessional loans (loans with lower interest rates than the market rate) with grants (financial transfers with no expectation of repayment), not least since many aid receiving countries have been highly indebted. What are then the arguments in favor of one or the other in the foreign aid literature? And how should we think about this in the context of the Ukraine crisis?
The Case for Loans
From a donor perspective, loans could be preferred from a purely financial viewpoint, as long as they are repaid. This must be put into the perspective of the purpose of foreign aid, though. If the purpose is to increase the welfare of the poor, and if loans cause macroeconomic imbalances that eventually lead to a debt crisis, using loans for aid will defeat its purpose. It is thus important, even from a donor perspective, to differentiate between the pure financial costs and the effectiveness and efficiency of foreign aid in relation to the stated goals. Yet, the paradigm on which development banks such as the World Bank motivate their strategy is that, even from an effectiveness perspective, loans may outperform grants. In their model, the bank has a broad portfolio of investments across multiple countries prioritized in order of the social rate of return. By lending out money, the bank can invest the returns from the most prioritized project into the second-most prioritized project, most likely in a different country. If the money instead had been given as a grant, the best possible outcome is that the receiving country can now invest the returns in the next best project within that country. This argument thus relies on the assumption that development banks can continually identify the most promising recipients among their wide portfolio of alternatives.
It has also been argued that grants may reduce incentives to raise tax revenues, and encourage government consumption over investments, as there is no need to generate net revenues to repay the debt (e.g., Clements et al. 2004; Djankov et al. 2004). From a donor perspective, it can also be argued that the monitoring of grants may be weaker because donors have no direct financial interest in the success of a project if it is financed by a grant. The disciplining effect of loans, though, relies on the absence of moral hazard problems. If receiving governments expect debt to be forgiven anyway when it is perceived as unsustainable and counterproductive to the country’s development, loans may be no better.
Based on arguments such as those above, part of the literature suggests that concessional loans are more likely than grants to promote growth in recipient countries, at least in good institutional environments. Cordella and Ulku (2007) look into this in detail and develop a model linking the degree of concessionality, for a given level of foreign aid (i.e. the extent to which finances are on preferential terms compared to market rates), to the receiving country’s economic growth rate, in a world where default is possible. Concessionality varies from 100 percent grants to 100 percent loans on market terms. The model suggests that a country with better policies and stronger institutions has a higher absorptive capacity for investments, meaning it can handle a lower level of concessionality (i.e., more loans, fewer grants) without going into default. They also argue that the immediate incentives for default on a loan are higher for a poorer and more indebted country as the cost of servicing the loan is higher. This would motivate relatively more grants and fewer loans to countries that are poor and highly indebted. Taking this to the data, they find in consistence with their theory that for any given level of total assistance, the impact on growth is increasing with the degree of concessionality for poor countries with weak policy and institutional environments, whereas this matters less for richer countries with better policies and stronger institutions. Looking at the level of indebtedness, the results are inconclusive.
The Case for Grants
The arguments above generally favor loans over grants, but it is of course crucial to also consider the risks and consequences of excessive debt burdens and sovereign default. Perhaps the most dramatic example of the potential consequences of shouldering a country with an excessive debt burden comes from Germany after the end of World War I. The economic struggles and sense of humiliation that followed have been argued to have contributed to German grievances leading up to World War II. Less dramatic but still with significant implications is the “lost decade” affecting Latin American middle-income countries in the 1980s. The combination of cheap credit from oil-exporting countries and the sudden dramatic increase of international interest rates following US policies in the early 1980s resulted in unsustainable levels of commercial loans. This crisis led to a US initiative, the Brady Plan, by which bank loans were consolidated and partially backed by the US government.
Excessive lending is often the result of distorted incentives. Within development banks, there are widely recognized internal incentives to get projects “through the door” (e.g., Briggs 2021). This “aid pushing” happens for both grants and loans, but the consequences can be more detrimental for loans if this leads to unsustainable debt levels. Similarly, there is evidence of defensive lending, where countries receive loans simply to be able to repay previous loans. Birdsall et al. (2003) find that donors lent more to African countries with bad policies if they had a large existing debt. On the other side, recipient country governments with short-term horizons and in environments with weak institutional checks and balances do not necessarily internalize the full costs of excessive lending. Due to these incentives on both sides, loans too often reach unsustainable levels, with debt to GDP ratios and debt to net export revenues becoming increasingly alarming.
With increased recognition of the costs of development of unsustainable levels of official lending, debt negotiations targeting highly indebted low-income countries have become common. These negotiations have often taken place through the Paris Club (a group of 22 high or upper-middle income creditor nations, including Russia) or through the HIPC (Highly Indebted Poor Countries) initiative (e.g. Birdsall et al. 2002). These debt reduction agreements have been continuously renegotiated, offering more and more generous conditions including debt forgiveness, rescheduling of existing loan terms, and more focus on grants in the portfolios of official financing.
Of particular relevance for this note, though, are the discussions around these initiatives that illustrate the different arguments made in favor of, or against, debt relief. As brought up in Birdsall et al. (2002), critique against the HIPC initiatives came from both sides. On the one hand, some argued that debt forgiveness was just more aid “down the rathole”, encouraging irresponsible policies by receiving governments (e.g. Easterly 2001), and fuelled by commercially motivated bilateral donors and multilateral institutions with misguided bureaucratic incentives. In order for aid to be effective, much more stringent conditionality was needed, and if that didn’t work, stricter selectivity in terms of which governments to partner with. On the other hand, others argued that the initiatives did not go far enough (e.g. Sachs, 2002). The economic arguments largely relied on concepts of a poverty trap, impossible to escape under conditions of a heavy debt burden requiring scarce foreign exchange to be used for debt service and discouraging investments. These countries were perceived as particularly vulnerable to adverse economic shocks, and as such, in need of insurance mechanisms that wouldn’t burden them with claims hampering their ability to prosper looking forward. But there was also a moral dimension, with blame focused on the creditor side, arguing that citizens of poor nations could not be burdened by debt issued for political reasons by creditors looking the other way when receiving rulers used proceeds for personal purposes.
Financing Post-war Recovery
The discussion above relates to foreign aid in general. The situation of financing post-war recovery is more specific, but past examples may give some points of reference. It should be noted, however, that every situation is unique in terms of the level of destruction, preconditions for a quick recovery, the political ramifications, and the risk of a resurgence of violence. And all these factors matter for the ability and willingness of foreign actors to step in and help.
An often-made reference in conjunction with Ukrainian recovery plans is the Marshall Plan, also known as the European Recovery Plan following World War II. Through this plan, financed by the US, initially 16 countries in Europe were getting “help to self-help” at an amount corresponding to roughly 10,5 percent of the countries’ GDP at the time (roughly about $13 billion, or $138 billion in 2019 dollars). The resources were spent differently across receiving countries, depending on the level of physical destruction. Importantly, grants accounted for as much as 90% of the total resources (Becker et al. 2022). More generally, grants usually account for a more significant share of aid flows when it comes to post-war reconstruction. This is natural, as a large share of the funding typically goes to humanitarian relief, and war-torn countries tend to be saddled with debt and a low capacity to raise domestic revenues in the short to medium term given the destruction of the war.
The common reference to the Marshall Plan in the context of Ukraine is probably partly geographically motivated: it is another war in Europe. But there are also other reasons, such as the direct unprovoked aggression by one of the world’s leading military powers, and the potential ramifications for world peace and the existing world order. The Marshall plan was motivated by the desire to avoid the mistakes from the peace agreements after WWI, and to help create a unified western Europe as a bulwark against further communist expansion from the Soviet Union. There are similar arguments to be made for the case of Russia’s war on Ukraine.
Implications for Ukraine Reconstruction
According to World Bank statistics, the total external debt stock of Ukraine in 2020 was $130 billion in current values, or 81,4 % of Gross National Income (GNI). This is already quite high, but the war has of course completely upended the situation and the IMF argued that Ukraine was facing debt sustainability issues already by the beginning of March 2022. Public finances are in the short run facing double pressure from a steep fall in revenues as economic activity drops and the ability to raise taxes is eroded, and an increase in expenditures on defence and humanitarian relief. Looking ahead, estimates of the Ukrainian costs of the war range between $440 and $1 000 billion by end of March 2022, but there is of course high uncertainty, and the bill is increasing for each day that the war goes on (Becker et al. 2022). This could be compared to the 2021 estimate of Ukraine’s GDP at around $165 billion. Even in the most optimistic scenarios, the rebuilding effort will be very costly, and will require massive amounts of foreign capital.
The sheer amount of effort needed in itself speaks to the need for grant financing. Rebuilding will require both public and private capital, and attracting new investments will necessitate an economic environment that is perceived as stable, dynamic, and conducive to long-term growth. As in the discussion on debt forgiveness for low-income countries above, such new investments are unlikely to materialize if the debt situation is deemed unsustainable. Furthermore, arguments in favor of loans over grants on grounds of fostering domestic macroeconomic responsibility and reducing moral hazard problems, fall flat when a country is invaded by an aggressive neighbor. Ukraine has had its share of bad politics, but the current situation is not caused by poor policies, lack of reform, or irresponsible lending under the assumption of future bailouts.
It should also be noted that both the Ukrainian government and representatives of the European Union (EU) have emphasized the long-term ambition that Ukraine should join the EU. This will not be possible, however, unless the country’s economy is in order, including a sustainable debt level, according to EU requirements for all joining members. Were Ukraine to shoulder excessive levels of debt at this moment it would thus jeopardize this ambition. And not least, Ukraine is fighting for its survival, but the war is also part of a wider emerging struggle between democratic and authoritarian forces over the future world order. The result of the war is of great significance for all democratic countries, though it’s the people of Ukraine that are facing the immediate horrific consequences. It is thus in our common interest to rebuild a prosperous and democratic Ukraine also as a bulwark against further authoritarian ambitions to change the existing world order. A Ukraine saddled with an unsustainable debt burden runs completely counter to the interests of the democratic world.
The Marshall Plan was successful in its goal “to permit the emergence of political and social conditions in which free institutions can exist”. This allowed for economic and political cooperation to take roots in western Europe, also contributing to political stability and prosperity. This cooperation expanded further east after 1989 with the inclusion of new member states into the European Union, largely solidifying a move towards market-based democracy in the region (despite some recent setbacks, primarily in Hungary). Let us build on these successful examples. The current situation offers an opportunity to bring an additional 44 million people into the European umbrella of peaceful cooperation in the near future. This ambition would become much more difficult, though, if Ukraine was saddled with an excessive debt burden.
- Becker, Torbjörn, Barry Eichengreen, Yuriy Gorodnichenko, Sergei Guriev, Simon Johnson, Tymofiy Mylovanov, Kenneth Rogoff, and Beatrice Weder di Mauro. (2022). “A Blueprint for the Reconstruction of Ukraine” Rapid Response Economics 1, CEPR Press.
- Birdsall, Nancy, John Williams, and Brian Deese. (2002). “Delivering on Debt Relief: From IMF Gold to a New Aid Architecture”, Peterson Institute for International Economics, Washington DC.
- Birdsall, Nancy, Stijn Claessens, and Ishac Diwan. (2003). “Policy Selectivity Forgone: Debt and Donor Behavior in Africa” World Bank Economic Review 17 (3): 409–35.
- Briggs, R. C. (2021). “Why does aid not target the poorest” International Studies Quarterly 65 (3), 739-752.
- Benedict Clements, Sanjeev Gupta, Alexander Pivovarsky, and Erwin R. Tiongson. (2004). “Foreign Aid: Grants versus Loans” Finance and Development, September, pp. 46–49.
- Cordella, Tito and Hulya Ulku. (2007). “Grants vs. Loans” IMF Staff Papers, 54(1), 139-162.
- Djankov, Simeon, Jose G. Montalvo, and Marta Reynal- Querol. (2004). “Helping the Poor with Foreign Aid: The Grants vs. Loans Debate” World Bank, Washington, D.C.
- Easterly, William. (2001). “Debt Relief”, Foreign Policy 126, 20-26.
- Sachs, Jeffrey. (2002). “Resolving the Debt Crisis of Low-Income Countries” Brookings Papers on Economic Activity 1, Brookings Institution Press.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
The short answer is: quite a lot, but different parts of the literature offer different recommendations. The problem is that these different recommendations are partly in conflict, and that political and bureaucratic incentives may reinforce these frictions when putting aid policy into practice. It follows that reforms aiming at improving aid effectiveness have to find a way to deal with this conflict and also balance the tendency of institutional sclerosis within bureaucratic agencies against short sighted incentives of politicians.
The currently predominant field of development economics focuses on impact evaluation of different economic and social interventions. These studies are all micro-oriented, looking at the impact on the level of the individual or household, rather than at the nation as a whole. One example is evaluations of the effects of different interventions on school participation, such as conditional cash transfers, free school meals, provision of uniforms and textbooks, and de-worming. Other well-known studies have looked at educational output, moral hazard versus adverse selection on financial markets, how to best allocate bed-nets to prevent malaria, and the role of information in public goods provision and health outcomes.
What has sparked the academic interest in these types of impact evaluations is the application of a methodology well known from clinical trials and first introduced in the field of economics by labor economists, randomized field experiments. The purpose of impact evaluation is to establish the causal effect of the program at hand. Strictly speaking this requires an answer to the counterfactual question; what difference does it make for the average individual if he is part of the program or not. Since an individual cannot be both part of, and not part of, the program at the same time, an exact answer to that question cannot be reached. Instead evaluators must rely on a comparison between individuals participating in the program and those that do not, or a before and after comparison of program participants. The challenge when doing this is to avoid getting the comparison contaminated by unobservable confounding factors and selection issues. For instance, maybe only the most school motivated households are willing to sign up for conditional cash transfer programs, so a positive correlation between program involvement and school participation may all be due to a selection bias (these households would have sent their children to school anyway). In this case participation is what economists refer to as “endogenous”, individual characteristics that may impact the outcome variable may also drive participation in the program.
To get around this problem, the evaluator would want strictly “exogenous” variation in the participation in the program, i.e. individuals should not get an opportunity to self-select into participation or not. The solution to this problem is to select a group of similar individuals/households/villages and then randomize participation across these units. This creates a group of participants in the program (the “treated”, using the language of clinical studies) and a group of non-participants (the “control group”) who are not only similar in all observable aspects thought to possibly affect the outcome, but who are also not given the opportunity to self-select into the program based on unobservable characteristics. Based on this methodology, the evaluator can then estimate the causal effect of the program. Exactly how that is done varies, but in the cleanest cases simply by comparing the average outcome in the group of treated with that in the group of controls.
So what has this got to do with aid policy? A significant part of aid financing goes of course to projects to increase school participation, give the poor access to financial markets, eradicate infectious diseases, etc. Both the programs evaluated by randomization, and the randomization evaluations themselves, are often financed by aid money. The promise of the randomization literature is thus that it offers a more precise instrument to evaluate the effectiveness and efficiency of aid financed projects, and also helps aid agencies in their choice of new projects by creating a more accurate knowledge bank of what constitutes current best practices. This can be particularly helpful since aid agencies often are under fire for not being able to show what results their often generous expenditures generate. Anyone who has followed the recent aid debate in Sweden is familiar with this critique, and the methodology of randomization is often brought forward as a useful tool to help estimate and make public the impact of aid financed development projects.
Limits to Randomization
Taken to the extreme, the “randomization revolution” suggests that to maximize aid effectiveness all aid should be allocated to clearly defined projects, and only to those projects that have been shown through randomization to have had a cost-effective causal effect on some outcome included in the aid donors objective (such as the millennium development goals). Yet, most aid practitioners would be reluctant to ascribe to such a statement. Why is that? Well, as is typically the case there are many potential answers. The cynic would argue that proponents of aid are worried that a true revelation of its dismal effects would decrease its political support, and that aid agencies want to keep their relative independence to favor their own pet projects. Better evaluation techniques makes it easier for politicians and tax payers to hold aid agencies accountable to their actions, and principal-agency theory suggests that governments then should put more pressure on agencies to produce verifiable results.
There are other more benevolent reasons to be skeptical to this approach, though, and these reasons find support in the more macro oriented part of the literature. In recent papers studying cross national differences in economic growth and development almost all focus is on the role of economic and political institutions. The term “institutions” has become a bit of a catch-phrase, and it sometimes means quite different things in different papers. Typically, though, the focus lies on formal institutions or societal norms that support a competitive and open market economy and a political system with limited corruption, predictability and public legitimacy. Critical components include protection of property rights, democracy, honest and competent courts, and competition policy, but the list can be made much longer. Also this time the recent academic interest has been spurred by methodological developments that have permitted researchers to better establish a causal effect from institutions to economic development. Estimating cleanly the effect of institutions on the level or growth rate of GDP is complicated since causality is likely to run in both directions, and other variables, such as education, may cause both. What scholars have done is to identify historical data that correlates strongly with historic institutions and then correlated the variation in current institutions that can be explained by these historical data with current day income levels. If cross national variation in current institutions maps closely to cross national variation in historical institutions (“institutional stickiness”) and if current day income levels, or education rates, do not cause historical institutions (which seems reasonable) then the historical data can be used as a so called “instrument” to produce a cleaner estimate of the causal effect of institutions.
Note that randomization and instrumentation are trying to solve the same empirical challenge. When randomization is possible it will be superior if implemented correctly (because perfect instruments only exist in theory), but there is of course a fairly limited range of questions for which randomized experiments are possible to design. In other cases scholars will have to do with instrumentation, or other alternatives such as matching, regression discontinuity or difference-in-difference estimations to better estimate a causal effect.
A second insight from this literature is that what constitutes successful institutions is context specific. Certain economic principles may be universal; incentives work, competition fosters efficiency and property rights are crucial for investments. However, as the example of China shows, what institutions are most likely to guarantee property rights, competition and the right incentives may vary depending on norms and historical experiences among other things. Successful institutional reforms therefore require a certain degree of experimentation for policy makers to find out what works in the context at hand. To just implement blueprints of institutions that have worked elsewhere typically doesn’t work. In other words, institutions must be legitimate in the society at hand to have the desired effect on individual behavior.
Coming back to aid policy, the lesson from this part of the literature is that for aid to contribute to economic and social development, focus should be on helping partner country governments and civic society to develop strong economic and political institutions. And since blueprints don’t work, it is crucial that this process involves domestic involvement and leadership in order to guarantee that the institutions put in place are adapted to the context of the partner country at hand, and has legitimacy in the eyes of both citizens and decision makers. Indeed, institution building is also a central part of aid policy. This sometimes takes an explicit form such as in financing western consultants with expertise in say central banking reform or how to set up a well-functioning court system. But many times it is also implicit in the way the money is disbursed, through program support rather than project support (where the former is more open for the partner country to use at their own priorities), through the partner country’s financial management systems and recorded in the recipient country budget. Also in the implementation of projects there is an element of institution building. By establishing projects within partner government agencies and actively involving its employees, learning and experience will contribute to institutional development.
Actual aid policy often falls short of these ambitions, though. Nancy Birdsall has referred to the impatience with institution building as one of the donors’ “seven deadly sins”. The impatience to produce results leads to insufficient resources towards the challenging and long term work of creating institutions in weak states, and the search for success leads to the creation of development management structures (project implementation units) outside partner country agencies. The latter not only generates no positive spill-overs of knowledge within government agencies, but can often have the opposite effect when donors eager to succeed lure over scarce talent from government agencies. The aid community is aware of these problems and has committed to improve its practices in the Paris declaration and the Accra Agenda, but so far progress has been deemed as slow.
Micro or Macro?
So, I started out saying that there is a risk that these two lessons from the literature may be in conflict if put into practice for actual aid policy. Why is that? At a trivial level, there is of course a conflict over the allocation of aid resources if we interpret the lessons as though the sole focus should be on either institutional development or best practice social projects respectively. However, most people would probably agree that there is a merit to both. In theory it is possible to conceive of an optimal allocation of aid across institutional support and social project support, in which the share of resources going to project support is allocated across projects based on best practices learned from randomized impact evaluations. In practice, however, it’s important to consider why these lessons from the literature haven’t been implemented to a greater extent already. After all, these are not completely new insights. Political economy and the logic of large bureaucratic organizations may be part of the answer. Once these factors are considered, a less trivial conflict becomes apparent, showing the need to think carefully about how to best proceed with improving the practices of aid agencies.
As mentioned above, one line of criticism against aid agencies is that they have had such a hard time to show results from their activities. This is partly due to the complicated nature of aid in itself, but critics also argue that it is greatly driven by current practices of aid agencies. First of all there is a lack of transparency; information about what decisions are made (and why), and where the money is going is often insufficient. This problem sometimes becomes acute, when corruption scandals reveal the lack of proper oversight. Secondly, money is often spent on projects/programs for which objectives are unclear, targets unspecified, and where the final impact of the intervention on the identified beneficiaries simply can’t be quantified. This of course limits the ability to hold agencies accountable to their actions, so focus instead tends to fall on output targets (have all the money been disbursed, have all the schools been built) rather than the actual effects of the spending. So why is this? According to critics, a reason for this lack of transparency and accountability is that it yields the agencies more discretion in how to spend the money. Agencies are accused of institutional inertia, programs and projects keep getting financed despite doubts about their effectiveness because agency staff and aid contractors are financially and emotionally attached.
In this context, more focus on long run, hard to evaluate institutional development may be taken as an excuse for continuing business as usual. Patience, a long run perspective and partner country ownership is necessary, but it cannot be taken as an excuse for not clearly specifying verifiable objectives and targets, and to engage in impact evaluation. It is also important that a long term commitment doesn’t have to imply an unwillingness to abandon a program if it doesn’t generate the anticipated results. It is of course typically much harder to design randomized experiments to evaluate institutional development than the effect of say free distribution of bed-nets. But it doesn’t follow that it is always impossible, and, more importantly, it doesn’t preclude other well founded methods of impact evaluation. The concern here is thus that too much emphasis on the role of institutional development is used as an excuse for not incorporating the main lesson from the “randomization revolution”, the importance of the best possible impact evaluation, because actual randomization is not feasible.
The concern discussed above is based on the implicit argument that aid agencies due to the logic of incentives and interests within bureaucratic institutions may not always do what is in their power to promote development, and that this is made possible through lack of transparency and accountability. The solution would in that case seem to be to increase accountability of aid agencies towards their politicians, the representatives of the tax payers financing the aid budget. That is, greater political control of aid policy would improve the situation.
Unfortunately, things aren’t quite that easy, which brings us to the concern with letting the ability to evaluate projects with randomized experiments being a prerequisite for aid financing. We have already touched upon the problem that programs for institutional development are hard to design as randomized experiments. It follows that important programs may not be implemented at all, and that aid allocation becomes driven by what is feasible to evaluate rather than by what is important for long run development. But there is also an additional concern that has to do with the political incentives of aid. The impatience with institution building is often blamed on political incentives to generate verifiable success stories. This is driven by the need to motivate aid, and the government policies more generally, in the eyes of the voters. It follows that politicians in power often have a rather short time horizon, that doesn’t square well with the tedious and long run process of institution building. Putting aid agencies under tighter control of elected politicians may therefore possibly solve the problem outlined above, but it may also introduce, or reinforce, another problem, the impatience with institution building.
Unfortunately, the perception that randomization makes it possible to more exactly define what works and what doesn’t, may have further unintended consequences if politicians care more about short term success than long term development. We know from principal-agent theory that the optimal contract gives the agent stronger incentives to take actions that contribute to a project if it becomes easier to evaluate whether the project has been successful or not. Think now of the government as the principal and the aid agency as the agent, and consider the case when the government has a bias towards generating short run success stories. In this case the introduction of a new technology that makes it easier to evaluate social projects (i.e. randomization) will make the government put stronger incentives on the aid agency to redirect resources towards social projects and away from institutional development. This would not be a problem if the government had development as its only objective, because then the negative consequences on effort at institution building would be internalized in the incentive structure. But in a second best world where politics trump policy, the improved technology may have perverse and unintended consequences. Greater political control will lead to less focus on institutional development than what is desired from a development perspective. A very benevolent (naïve?) interpretation of the motivation behind aid agencies’ tendencies to design social projects such that their effects are hard to quantify could thus be that it decreases the political pressure to ignore institutional development.
The challenge to heed the two lessons from the literature thus goes beyond the mere conflict of whether to allocate the resources to institutional development or to best practice social projects once political economy and bureaucratic incentives are considered. Improved agency accountability may be necessary to avoid “institutional sclerosis” in the name of institution building and make sure that best practices are followed, but too much political meddling may lead to short sightedness and a hunt for marketable success stories. It is even possible, that the “randomization revolution” may make matters worse, if it becomes an excuse for neglecting the tedious and long term process of institution building and reinforces the political pressure for short term verifiable results.
What is then the best hope for avoiding this conflict of interest? That is far from a trivial question, but maybe the best way to make sure that agency accountability towards their political principals doesn’t lead to impatience with institution building is to form a broad-based political consensus around the objectives, means and expectations of development aid. The pedagogical challenge to convince tax payers that aid helps and that they need to be patient remains, but at least the political temptation to accuse political opponents of squandering tax payers money without proven effects and to pretend to have the final solution for how to make aid work, should be mitigated. But until then the best bet is probably to stay skeptical to anyone claiming to have the final cure for aid inefficiency, and to allow some trust in the ability of experienced practitioners to do the right thing.
Recommended Further Reading
- Acemoglu, D., S. Johnson and J.A. Robinson (2001) “The Colonial Origins of Comparative Development: An Empirical Investigation“, American Economic Review 91(5), 1369-1401.
- Banerjee, A. (Ed.) (2007), “Making Aid Work”, MIT Press.
- Bannerjee, A. and E. Duflo (2008), “The Experimental Approach to Development Economics”, NBER Working Paper 14467.
- Birdsall, N. (2005), “Seven Deadly Sins: Reflections on Donor Failings”, CGD Working Paper 50.
- Birdsall, N. and H. Kharas (2010), “Quality of Official Development Assistance Assessment”, Working Paper, Brookings and CGD.
- Duflo, E., R. Glennerster and M. Kremer (2007), “Using Randomization in Development Economics Research: A Toolkit”, CEPR Discussion Paper 6059.
- Easterly, W. (2002), “The Cartel of Good Intentions: The problem of Bureaucracy in Foreign Aid”, Journal of Economic Policy Reform, 5, 223-50.
- Easterly, W. and T. Pfutze (2008), “Where Does the Money Go? Best and Worst Practices in Foreign Aid”, Journal of Economic Perspectives, 22, 29-52.
- Knack, S. and A. Rahman (2007), “Donor fragmentation and bureaucratic quality in aid recipients”, Journal of Development Economics, 83(1), 176-97.
- Rodrik, D. (2008), “The New Development Economics: We Shall Experiment, but how Shall We Learn?”, JFK School of Government Working Paper 55.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.