Aid Volatility Research Articles

Herding in Aid Allocation

This paper investigates a claim repeatedly made, but never tested, that aid donors herd. To do so it originally uses methodologies developed in finance to measure herding on financial markets, and adapts them to aid allocation. The motivation for studying herding is to improve our understanding of aid allocation beyond observable determinants. If herding is indeed present, then it is likely to shape aid patterns in a significant way by creating aid darlings, orphans, but also by exacerbating aid volatility. Our approach starts by carefully defining aid to avoid including herding-prone aid, such as humanitarian aid and debt relief, and the sets of donors and recipients. Once this is done, herding is measured by directly applying the indexes used in finance to yearly aid data. Results show herding is indeed present, but that it is small. A second step is to introduce modifications to better match the characteristics of aid allocation. The most important in the paper is to change the time horizon. Unlike traders, aid donors commit to an aid partnership over several years, and yearly variations may contain a large part of randomness. Instead of year-to-year changes, we instead use 3- and 5-year allocations to measure herding. With this modification herding is still found to be present, but also of a larger size. It is now similar to what is traditionally found on financial markets. The next, important step is to acknowledge that aid donors' allocation decisions almost surely follow similar determinants and changes in these determinants generate a lot of co-movements. Herding measures by definition interpret these simultaneous decisions as herding, when they merely reflect common views among donors (think about a natural disaster occurring in a country that dramatically increase aid needs). Herding determinants are carefully estimated and their contributions to herding measures are then removed to obtain an estimate free of the effects of observable variables that affect aid allocation. This procedure shows that, even after taking observable factors into account, herding is still present. It suggests other considerations drive herding behavior.

Herding in Aid Allocation

This paper investigates a claim repeatedly made, but never tested, that aid donors herd. To do so it originally uses methodologies developed in finance to measure herding on financial markets, and adapts them to aid allocation. The motivation for studying herding is to improve our understanding of aid allocation beyond observable determinants. If herding is indeed present, then it is likely to shape aid patterns in a significant way by creating aid darlings, orphans, but also by exacerbating aid volatility. Our approach starts by carefully defining aid to avoid including herding-prone aid, such as humanitarian aid and debt relief, and the sets of donors and recipients. Once this is done, herding is measured by directly applying the indexes used in finance to yearly aid data. Results show herding is indeed present, but that it is small. A second step is to introduce modifications to better match the characteristics of aid allocation. The most important in the paper is to change the time horizon. Unlike traders, aid donors commit to an aid partnership over several years, and yearly variations may contain a large part of randomness. Instead of year-to-year changes, we instead use 3- and 5-year allocations to measure herding. With this modification herding is still found to be present, but also of a larger size. It is now similar to what is traditionally found on financial markets. The next, important step is to acknowledge that aid donors' allocation decisions almost surely follow similar determinants and changes in these determinants generate a lot of co-movements. Herding measures by definition interpret these simultaneous decisions as herding, when they merely reflect common views among donors (think about a natural disaster occurring in a country that dramatically increase aid needs). Herding determinants are carefully estimated and their contributions to herding measures are then removed to obtain an estimate free of the effects of observable variables that affect aid allocation. This procedure shows that, even after taking observable factors into account, herding is still present. It suggests other considerations drive herding behavior.

International Monetary Fund and Aid Displacement

Several recent papers find evidence that global health aid is being diverted to reserves, education, military, or other sectors, and is displacing government spending. This is suggested to occur because ministers of finance have competing, possibly corrupt, priorities and deprive the health sector of resources. Studies have found that development assistance for health routed to governments has a negative impact on health spending and that similar assistance routed to private nongovernmental organizations has a positive impact. An alternative hypothesis is that World Bank and IMF macro-economic policies, which specifically advise governments to divert aid to reserves to cope with aid volatility and keep government spending low, could be causing the displacement of health aid. This article evaluates whether aid displacement was greater when countries undertook a new borrowing program from the IMF between 1996 and 2006. As found in existing studies, for each $1 of development assistance for health, about $0.37 is added to the health system. However, evaluating IMF-borrowing versus non-IMF-borrowing countries reveals that non-borrowers add about $0.45 whereas borrowers add less than $0.01 to the health system. On average, health system spending grew at about half the speed when countries were exposed to the IMF than when they were not. It is important to take account of the political economy of global health finance when interpreting data on financial flows.

Aid Volatlity: Is it a Problem in Tuvalu?

Empirical evidence on aid volatility shows that it adversely impacts recipient countries. For instance, high aid volatility results in uncompleted projects, affects fiscal planning, and decreases the economic and social value of aid. Given these impacts of aid volatility, this study seeks to find out whether aid volatility is a problem in Tuvalu – a small country in the Pacific that is highly dependent on foreign aid. The study, the first of its type in Tuvalu, looks at the volatility of aid relative to other government revenues, and aid volatility by donor, type, and sector in the country. Furthermore, the study tries to identify the causes and costs of aid volatility and how to deal with it. The findings reveal that although aid volatility, at the coefficient of variation (CV) of 0.49, is lower than the volatility of most revenue sources to the government of Tuvalu (fisheries licence, dot TV, TTF), it is much higher than domestic (tax) revenue which has a CV of 0.20 and aid volatility of other aid dependent countries. Moreover, by breaking down aid by donor, type, and sector; it is found that aid from donors funding projects (including capital projects) is more volatile than aid from donors whose aid goes more into budget support and routine programs such as scholarships. Accordingly, volatility is higher in project aid than budget support and program aid. Moreover, it is revealed that multilateral aid is less volatile than bilateral aid. The main causes of aid volatility in the country relate to the lack of effective aid agreements between Tuvalu and its donor partners, late disbursements in committed aid from donors, the focus of aid on individual projects instead of programs, and administrative problems in Tuvalu. The major costs of aid volatility in the country link to uncompleted projects, high transaction costs, ‘Dutch disease’, and fiscal planning problems. The study therefore argues that aid volatility is a problem in Tuvalu. Thus, to deal with the aid volatility problem, Tuvalu needs to strengthen ‘reserve funds’ such as the Tuvalu Trust Fund (Account B) to buffer for any disruptions in aid disbursements, provide sound policy and institutional climate in the country, target aid to budget support and programs instead of specific projects, and implement large infrastructural projects in phases.

Growth effect of aid and its volatility: An individual country study in South Asian economies

This paper empirically investigates the growth effect associated with aid and its volatility during the period 1995-2008 in the case of five South Asian economies. The aid is classified into short impact, long impact and humanitarian aid. We obtained results for each of the country by employing two-stage least squares method. The results suggest that gross aid is positively associated with growth rate where as its volatility negatively effects growth rate South Asian countries. Short impact and long impact aid positively effect on growth rate whereas respective aid volatilities have negative affects on all the economies, excluding at least one country in each case. Humanitarian aid and its volatility have mixed results. Thus, we come to a conclusion that, aid and aid volatility have strong association with growth rate in the South Asian countries, but varies considerably from country to country in terms of magnitude of effect and in relation to the growth rates.

Economic Growth and the Volatility of Foreign Aid

Foreign aid’s effectiveness in promoting economic growth remains mired in controversy.We examine the impact of the volatility of aid on economic growth, controlling for the level of aid. A four-year panel analysis is conducted encompassing 155 countries over the period 1966-2001. We find that once the volatility of aid is controlled for, aid has a positive impact on economic growth. Correspondingly, volatility of aid flows is found to be negatively related to growth. We found no significant link between investment and foreign aid, but a positive correlation between aid and consumption and a negative link between aid volatility and consumption. But our results also indicate that aid has become a source of volatility rather than insuring against it, and in that way may have become inimical to economic growth. Key Words: foreign aid, volatility, economic growth JEL codes: O4, O11, O19

Donors and domestic politics: Political influences on foreign aid effort

The vast majority of scholarship on foreign aid looks at either the effectiveness of foreign aid or why particular countries receive aid from particular donors. This paper takes a different approach: what are the domestic sources of support for foreign aid? Specifically, how does the donor's domestic political and economic environment influence ‘aid effort’? This paper uses a time-series cross-sectional data set to analyze the influence of changes in political and economic variables. As governments become more conservative, their aid effort is likely to fall. Domestic political variables appear to influence aid effort, but only for aid to low income countries and multilaterals while aid effort to middle income countries in unaffected. This suggests that models solely emphasizing donor economic and international strategic interests as determinants of donor aid policy may be mis-specified. These results also suggest sources of aid volatility that might influence recipient growth prospects.

Aid, Volatility, and Growth Again: When Aid Volatility Matters and When it Does Not

AbstractIn previous papers the authors have argued that aid is likely to mitigate the negative effects of external shocks on economic growth (i.e. that aid is more effective in countries which are more vulnerable to external shocks). Recently an important debate has emerged about the possible negative effects of aid volatility itself. However, the cushioning effect of aid may involve some volatility in aid flows, which then is not necessarily negative for growth. In this paper the authors examine to what extent the time profile of aid disbursements may contribute to an increase or a decrease of aid effectiveness. They first show that aid, even if volatile, is not clearly as pro‐cyclical as is often argued, and, even if pro‐cyclical, is not necessarily destabilizing. They measure aid volatility by several methods and assess pro‐cyclicality of aid with respect to exports, thus departing from previous literature, which usually assess pro‐cyclicality of aid with respect to national income or fiscal receipts. The stabilizing/destabilizing nature of aid is measured by the difference in the volatility of exports and the volatility of the aid plus export flows. Then, in order to take into account the diversity of shocks to which aid can respond, they consider the effect of aid on income volatility and again find that aid is making growth more stable, while its volatility reduces this effect. They finally show through growth regressions that the higher effectiveness of aid in vulnerable countries is to a large extent due to its stabilizing effect.

Aid and the Soft Budget Constraint

The author applies the theory of the soft budget constraint to explain some stylized facts regarding the outcomes and practice of international aid, including ineffectiveness, white elephants, and volatility. The soft budget constraint can also make aid counterproductive. Nonetheless, actual aid institutions may be constrained optimal responses to soft budgets and commonly suggested reforms such as improved donor coordination in aid, focus on fewer countries and projects, and less volatility of aid may lower the effectiveness of aid. The soft budget is also consistent with conservative project selection and the recent focus on “ownership.”

Aid volatility and poverty traps

This paper studies the impact of aid volatility in a two-period model where production may occur with either a traditional or a modern technology. Public spending is productive and “time to build” requires expenditure in both periods for the modern technology to be used. The possibility of a poverty trap induced by high aid volatility is first examined in a benchmark case where taxation is absent. The analysis is then extended to account for self insurance (taking the form of a first-period contingency fund) financed through taxation. An increase in aid volatility is shown to raise the optimal contingency fund. But if future aid also depends on the size of the contingency fund (as a result of a moral hazard effect on donors' behavior), the optimal policy may entail no self insurance.

Reforming Aid: Toward More Predictable, Performance-Based Financing for Development

We explore ways of mitigating the costs of aid volatility: in particular, we show that these can be dramatically reduced by a flexible pre-commitment rule which adjusts flows in the case of drastic improvements or deteriorations in country performance ratings. Such a system can further reduce variability with only minor efficiency costs. Our simulations suggest that a buffer stock of the order of 50–100% of annual aid-financed spending might enable a corrective feedback loop, with the necessary buffer depending on the size and variability of aid flows. Our proposed mechanism is similar in principle to natural resource funds, which have worked well in some countries but not in others; we briefly discuss some issues in design and implementation.

Aid Volatility, Policy and Development

We build on Bulir and Hamann's analysis of aid volatility (2003, 2005), showing that the conclusions reached depend on the dataset used. Their argument that the poorest countries have the highest volatility appears not to be correct. The impact of volatility on growth is negative overall, but differs between positive and negative volatility. The mix between `responsive´ components of aid, e.g. programme aid, and `proactive´ components, e.g. technical assistance, is important. Finally, we conclude that measures which increase trust between donor and recipient, and reductions in the degree of donor `oligopoly´, reduce aid volatility without obviously reducing its effectiveness.

Introduction: The Volatility of Overseas Aid

Summary Evidence is mounting that the pattern of overseas aid through time, of which its volatility (or instability) is a key dimension, has an important influence on its effectiveness. The three papers in this Special Section examine the extent of this influence, and how it may be possible to control volatility in the interests of more effective aid.

Measuring the Cost of Aid Volatility

Flows of official development assistance (ODA) to recipient countries have been highly volatile and this reduces their value. At the macro level, empirical evidence suggests that volatile ODA can negatively impact growth through several channels. At the micro level, volatility can affect fiscal planning and the level and composition of investment. This working paper develops a simple financial metric that policy makers can use to estimate (and reduce) the cost of aid volatility. Unlike other estimates, our measure does not depend on parameter estimates from cross-country regressions, nor on country-specific model simulations. We treat aid flows as the uncertain return on an unobserved asset of global goodwill held by developing countries. We then calculate the certainty equivalent value of the volatile aid flows as well as an associated dead weight loss, using a capital asset pricing model. Our measure of the deadweight loss per dollar provided in aid permits a comparison of costs across donors and over time. We find that the costs of volatility rose steadily until 2002, and have since fallen. Aid volatility is similar for low and middle income countries; weak states and strong states; aid dependent and low-aid countries; and across regions. Aid volatility differs substantially, however, by donor. We infer that donor policies contribute to volatility and that they should make reducing volatility a strong priority.

Volatility of Development Aid: From the Frying Pan into the Fire?

Summary The paper, building on the authors’ previous analysis, examines the relative volatility of aid flows into developing countries and their domestic revenue, using new data, and three alternative measures of aid instability (relative volatility vis-a-vis fiscal revenue, unpredictability of aid disbursement relative to commitments, and failure of aid to smooth fluctuations in aggregate income). It finds that the volatility of aid flows is still much greater than that of domestic revenue and that this difference is not decreasing. Especially in very poor, aid-dependent countries, this high volatility of inflows makes the macroeconomy hard to manage. Further, the influence of aid has been procyclical and not countercyclical: aid has failed to act either as a stabilizing force or as an insurance mechanism. We argue that, to counter these unwelcome trends, donors need to be able to respond more speedily and effectively to large adverse shocks, and their conditionalities need to become more flexible—possibilities explicitly discussed elsewhere in this Special Section.

Aid Volatility and Donor–Recipient Characteristics in ‘Difficult Partnership Countries’

One factor limiting aid effectiveness is its volatility. We examine aid volatility in 66 countries over 1975–2004, paying particular attention to the characteristics of ‘difficult partnership countries’ and making a distinction between sector aid and total aid. We explore whether weak recipient institutions and policies are associated with greater volatility, allowing for differences in donor characteristics. Institutional quality and macroeconomic stability affect the stability of all kinds of aid, as does reliance on a small number of donors. However, the relative importance of these effects varies across different aid types.

The dynamic implications of foreign aid and its variability

The paper examines the effects of aid and its volatility on consumption, investment, and the structure of production in the context of an intertemporal two-sector general equilibrium model, calibrated using data for aid-dependent countries in Africa. A permanent flow of aid mainly finances consumption rather than investment—consistent with the historical failure of aid inflows to translate into sustained growth. Large aid flows are associated with higher real exchange rates and smaller tradable sectors because aid is a substitute for tradable consumption. Aid volatility results in substantial welfare losses, providing a motivation for recent discussions of aid architecture stressing the need for greater predictability of aid. These results are also consistent with evidence from cross-country regressions of manufactured exports, presented later in the paper.

Does Aid Improve Public Service Delivery?

The expected increase in aid to Africa will put a big challenge for public service delivery. This paper provides an analysis of the effects of the volume and volatility of aid on education, health, water and sanitation outcomes, taking also into account the institutions related to public service delivery, including freedom of press, corruption, and decentralization, using a simultaneous equation model. Overall the share of Official Development Assistance (ODA) that is provided for education and health seems to have a positive impact on outcomes in these sectors, whereas total aid seems to be negatively associated. Aid volatility is associated with better outcomes in sanitation, water, and infant mortality, contrary to expectations.

Volatility of Development Aid: An Update

The positive impact of foreign aid is limited by the erratic behavior of aid flows. The introduction in 1999 of various initiatives anchored in IMF Poverty Reduction Strategy Papers aimed at strengthening coordination among donors, improving the design of financial support programs, and improving domestic records of policy implementation should have led to an improvement in the time series properties of aid flows. We find no evidence of any fundamental changes in the way aid has been delivered during 2000–03. If anything, aid volatility has worsened somewhat and the information value of long-term lending commitments has declined. We take these results to mean that the main causes of the volatility and unpredictability of aid, and the broader issue of macroeconomic instability in low-income countries, may not have been addressed in a systematic manner by the donor community.

The macroeconomic impact of aid volatility

We analyse the impact of aid volatility on GDP/GNP shares of expenditure. Given the level of aid, positive and negative volatility reduce investment and government expenditure shares. But the former reduces import share and the latter increases consumers' expenditure share.