Helping Countries Develop
Chapter

17 Foreign Aid and Consumption Smoothing: Evidence from Global Food Aid

Author(s):
Benedict Clements, Sanjeev Gupta, and Gabriela Inchauste
Published Date:
September 2004
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Author(s)
Sanjeev Gupta, Benedict Clements and Erwin R. Tiongson 

1. Introduction

The debate on aid effectiveness has largely focused on the impact of aggregate “development assistance” on economic growth or economic development more broadly (Easterly, 2001; World Bank, 1998). As a result, relatively little attention has been paid to how well certain components of foreign aid achieve their stated objectives, such as disaster relief, humanitarian assistance, and food aid. In this paper, we focus on one particularly important component of foreign aid—food aid—and evaluate whether it helps stabilize consumption in recipient countries, and whether it has been targeted to those countries most in need.

Aid inflows (including food aid) impact government revenues and economic activity. This is the case when aid flows through the budget and if part or all of the commodity aid is sold in local markets. Wide variations in the receipt of commodity aid can thus lead to volatility in both government revenues and economic activity and make fiscal management more problematic. This paper also seeks to shed light on this issue by empirically assessing whether the timing of food aid has contributed to the volatility of government revenues and economic activity in recipient countries.

The rest of this paper is structured as follows: Section 2 reviews the relevant literature. Section 3 presents the empirical framework and the data sources. Section 4 reports the empirical results and Section 5 concludes.

2. Literature Review

A number of recent papers have also documented a pattern of aid volatility and aid procyclicality with respect to output and fiscal revenues (Gemmell and McGillivray, 1998; and Pallage and Robe, 2001). The procyclicality of aid implies that aid flows cannot stabilize fluctuations in consumption; direct (humanitarian) intervention does not take place when it is needed most. Food aid is usually made available free or on highly concessional terms. Counterpart funds generated by commodity aid including food aid provide critical budget support.

The size of counterpart funds is substantial in many recipient countries (Colding and Pinstrup-Andersen, 2000). Counterpart funds (from food aid, commodity aid, and project aid) accounted for about 30% of government revenue in Mozambique in the early 1990s (Riley, 1992). In Albania, counterpart funds from food aid sales amounted to 5% of government expenditure and 3% of GDP during the same period. In Georgia, revenues from food aid sales accounted for about 15% of total expenditures in the mid-1990s (UNDP, 1996).

Fluctuations in food aid can have important macroeconomic consequences. In particular, the timing of food aid and its sale could be viewed as an “automatic stabilizer” for the economy; when food output in a country falls, government revenues decline and spending increases. Monetization of food aid flows in these circumstances stabilizes flows to the budget in addition to shielding food consumption levels in the country. Furthermore, food aid (including commodities distributed directly to households) is critical for alleviating spending pressures on the budget to offset the adverse consequences of food shortages.

A handful of case studies of individual food aid programs and time series studies of global food aid and world commodity prices suggest that food aid is not effective in addressing transitory food insecurity (Clay et al., 1996), and that food aid and world prices move inversely (Benson, 2000). Therefore, food aid fails to mitigate transitory food insecurity. However, these studies do not provide information on the relationship between food aid and cyclical fluctuations in aggregate domestic food availability by country. With respect to cross-country econometric studies, the literature has examined the cyclicality of either individual food aid programs alone or multilateral food aid programs for small samples of countries. The empirical findings are mixed (Barrett, 2001; Mellor and Pandya-Lorch, 1992; and Trueblood et al., 2001). Evidence on how well food aid is targeted to countries with the greatest need is also mixed (Shapouri and Missiaen, 1990; Diven, 2001; and Barrett, 2001).

A number of important issues remain unresolved in the empirical literature on food aid. First, because food aid is typically provided by a number of donors, evaluating the performance of individual programs in responding to food shortages can be misleading. An evaluation of the performance of global food aid would be more appropriate. Second, the cyclical properties of food aid with respect to revenues and overall deficit have not been examined. Because food aid can provide additional revenue and because food shortages can be symptoms of a more fundamental economic downturn, the magnitude and direction of co-movements between food aid and measures of economic activity provide useful information. Third, recent research has found that the results of business cycle studies are sensitive to the choice of filter (Canova, 1999). This implies that the robustness of results from empirical studies of food aid should be tested against various filtering techniques and model specifications. Fourth, the literature on food aid has noted a change in the composition of food aid toward emergency aid, raising the question of whether its cyclical properties have also changed. Finally, while the literature has noted that foreign aid is not necessarily progressive, the issue of whether this also applies to global food aid per se has yet to be settled.

3. Methodology and Data

Methodology

This paper employs two strategies for assessing the cyclical properties of foreign aid with respect to domestic food availability in recipient countries: (1) the calculation of correlation coefficients between food aid and domestic food availability detrended by the Hodrick-Prescott filter; and (2) a two-step Tobit regression of food aid on a measure of relative shortfalls in consumption and a measure of absolute shortfalls in consumption. As explained below, the second strategy also provides a test for the progressivity of food aid distribution.

Hodrick-Prescott Filter

First, following the literature, we measure business cycles as deviations from trend. We detrend nonconcessional food availability using the Hodrick and Prescott (1997) filter, which for a series x extracts the growth component xg and the cyclical component xc = xxg by minimizing the following loss function:

where λ is a weight that reflects the relative variance of growth and cyclical components. For annual data, λ = 100 by convention.1 The logarithm of x is used to calculate percentage deviations from trend. The correlations between global food aid and the cyclical component of domestic food availability are calculated contemporaneously, and with leads and lags up to two years. For comparison, we also calculate the correlations between food aid and the cyclical components of log per capita income as a measure of economic activity and a proxy for consumption shortfalls.

Two-Step Estimation

The empirical literature on food aid and consumption smoothing has examined how food aid flows respond to shortfalls in food availability by first measuring food availability in terms of deviations from a trend (Mellor and Pandya-Lorch, 1992; Shapouri and Rosen, 2001), and then examining the statistical relationship between food aid and such deviations. We use the same two-step estimation procedure, but adopt the specification in Barrett (2001); and Barrett and Heisey (2002). Their method has the added feature of providing a measure of progressivity (that is, whether food aid flows are, on average, targeted toward countries with greater absolute shortfalls in food availability).

The first step requires estimating the growth rate in nonconcessional food availability (NA) using a logarithmic trend regression for each country in the sample:

where εnt captures the deviations around the trend nonconcessional NA. NA is measured using the FAO data as the sum of domestic food production (PROD) plus total food imports (IM).

The second step involves the regression of food aid per capita (FA) on εnt and the level of NA. Because FA is a nonnegative variable often taking zero value, the relationship is estimated using a panel data Tobit specification:

where i is the index of the recipient country, t is the year, and r is region.2 In Eq. (3a), β1 is a measure of the stabilization effect of food aid and β2 is the measure of progressivity, controlling for fixed effects of regions and years (as captured by the dummy variables D and Y for regions and years, respectively). The method thus distinguishes relative shortfalls (εnt) from absolute shortfalls (NA) in food availability. In particular, β1 < 0 indicates that global food aid is countercyclical, β1 > 0 indicates that it is procyclical, and β1 = 0 indicates that it is acyclical. The sign of β2 on the other hand, indicates whether food aid is progressive. β2 > 0 would indicate the progressivity of global food aid.

Barrett and Heisey (2002) note two possible sources of bias in the estimation of Eqs. (3a) and (3b): (1) omitted variables bias, and (2) endogeneity bias due to reverse causality between food aid (FA) and food availability (NA), through commercial imports (IM = NAPROD).

First, control for lagged food aid may be required because a number of studies note that food aid flows are persistent. In particular, Diven (2001) finds a strong incremental trend in food aid “programming,” where policymakers appear to use shipments from the previous year as a starting point for marginal adjustments. Evidence from micro data confirms some spatial inertia in food aid allocations as well, which means that food aid allocation to certain regions persist (Clay et al., 1996; and Jayne et al., 2002), for various reasons including significant fixed costs in food aid operations.

Second, food aid flows may have an effect, both lagged and contemporaneous, on commercial food imports by the recipient, as some imports are displaced by food aid. There is thus some reverse causality between food aid and food availability, via food imports. Though an argument could be made that food aid flows may also depress production, there is no evidence that food aid (FAit) has any contemporaneous effect on domestic food production (PRODit) (Barrett, 2002).

To correct for these biases, Barrett and Heisey (2002) suggest reestimating Eqs. (3a) and (3b) as follows:

where εpit is a measure of fluctuations in domestic food production as in Eq. (2), FAit−1 is lagged food aid, and PRODit is a measure of domestic food production per capita. PRODit may be treated as exogenous. The sign of ϕ1 indicates the cyclical properties of global food aid.

Modifications

To test the robustness of the results to the choice of filters, we employ other filtering or detrending techniques in both procedures. In addition to the Hodrick-Prescott filter, we employ linear and quadratic detrending. In particular, we decompose a data series into a cyclical component and a linear function of time:

This is similar to Eq. (2), where an OLS regression yields residuals (εt) that are the cyclical component of the series (ct). The quadratic trend adds a second term to equation (5):

We also use an approximation of the band-pass filter developed by Christiano and Fitzgerald (1999). This filters both high frequency “noise” and low frequency “trends,” thus leaving fluctuations within a specified band at typical business cycle frequencies (1.5 to 8 years).

Using the new filtering procedures, one possible modification to the two-step method would be to estimate εnt as deviations from a nonlinear trend (εntN) rather than from a linear time trend implied by equation (2). Eq. (3a), for example, is then estimated as

A test of the null hypothesis β1 = 0 versus the alternate hypothesis β1 < 0 is again a direct test of the procyclicality of global food aid. A similar procedure may be applied to Eqs. (4a) and (4b).

Data

This paper uses comprehensive data on global food aid flows over 30 years, 1970–2000, covering some 150 recipient countries. Global food aid data are drawn from the WFP’s Food Aid Flows (various issues) and the Food and Agriculture Organization’s (FAO) FAOSTAT database. Data on population, domestic food production, and total food imports are from the FAOSTAT database. All food data are measured in volumes (metric tons). We proxy total food production, food imports, and global food aid using cereal volumes. All series are measured in per capita terms.

Data for GDP per capita, total government revenue (in percent of GDP), and overall deficit (in percent of GDP) are from the World Economic Outlook (WEO) database. The data generally cover the 1970-2000 period, though the period may vary across countries.

4. Results

Correlations

Table 1 provides the summary information on the correlations between global food aid and cyclical fluctuations in nonconcessional food availability, by region.3 The estimates are based on food availability up to two periods in leads and lags, using linear and quadratic detrending as well as the band-pass and Hodrick-Prescott filters (not reported). The results indicate that food aid is overwhelmingly acyclical across all regions. Some 100 out of the 150 countries in the sample have correlation coefficients less than zero. However, these are mostly within the intervals judged not significantly different from zero. At the most, only in 28 countries is food aid significantly countercyclical. The results are invariant to the choice of filter.

Table 1.Cyclical Properties of Food Aid(Unweighted averages; comovement with domestic nonconcessional food availability)
Linear DetrendingQuadratic Detrending
Sample

Size
Two-

period

lag
One-

period

lag
Zero

lag
One-

period

lead
Two-

period

lead
Two-

period

lag
One-

period

lag
Zero

lag
One-

period

lead
Two-

period

lead
Asia27.0−0.03−0.03−0.060.00−0.100.00−0.08−0.030.01−0.06
Middle East and North Africa16.00.06−0.04−0.040.100.10−0.05−0.050.000.080.02
Sub-Saharan Africa48.00.030.01−0.020.01−0.06−0.030.000.010.040.02
Transition24.0−0.08−0.060.000.07−0.060.030.200.10−0.21−0.26
Western Hemisphere33.00.06−0.06−0.11−0.030.010.030.010.08−0.06−0.06
Others5.0−0.09−0.13−0.09−0.07−0.12−0.04−0.01−0.010.050.00
Sources: FAO database; WFP database; and authors’ calculations.
Sources: FAO database; WFP database; and authors’ calculations.

Tobit Regressions

Baseline Regressions

Table 2 presents the results of the Tobit regression of Eqs. (3a) and (3b). For the sample as a whole, the results indicate that global food aid follows a significantly progressive distribution. This means that food aid has been responsive to absolute shortfalls in nonconcessional food availability across countries.

Table 2.Baseline Tobit Regression Results for All Countries: Linear Detrending1
(1)(2)(3)(4)
β1 (cyclically)0.0136***0.0096**0.0118**0.0079*
(2.92)(2.03)(2.52)(1.66)
β2 (progressivity)−0.0422***−0.0241***−0.0425***−0.0246***
(−8.53)(−3.69)(−8.61)(−3.78)
Regional dummiesNoYesNoYes
Year dummiesNoNoYesYes
LR statistic79.05171.36120.44213.41
P-value0.000.000.000.00
Number of observations3,7203,7203,7203,720
Source: See text.(***), (**), and (*) denote significance at the 1, 5, and 10 percent level, respectively.

Specification varies from one column to the next, depending on the inclusion or exclusion of regional or year dummies.

Source: See text.(***), (**), and (*) denote significance at the 1, 5, and 10 percent level, respectively.

Specification varies from one column to the next, depending on the inclusion or exclusion of regional or year dummies.

An equally interesting result is the progressivity of food aid flows among low-income countries (not reported). In fact, the relationship between per capita income and food aid is negative and significant, but the coefficient size is small (−0.03). Food aid to these low-income countries appears to have been triggered by absolute shortfalls in consumption.

However, the preliminary results from Tobit regressions further confirm that, on average, food aid flows have not generally been responsive to fluctuations in food availability. In fact, there is evidence that food aid disbursements have been procyclical rather than countercyclical.

Accounting for bias arising from the absence of lagged food aid and the endogeneity of commercial food imports, as noted above, lagged food aid and domestic production (PROD)—to proxy nonconcessional food availability (NA)—are added to the baseline regressions, following Eqs. (4a) and (4b). The regression results in Table 3 confirm that for the sample as a whole, global food aid is generally progressive and responds to absolute gaps across countries.

Table 3.Modified Tobit Regression Results: Linear Detrending
All

Countries
All

Countries
All

Countries
Most

Food-Insecure1
Low-

Income2
Sub-Saharan

Africa
φ1 (cyclicality)−0.0012−0.0029−0.0033−0.007**−0.0107***−0.004***
(−0.49)(−1.17)(−1.28)(−2.21)(−7.16)(3.10)
φ2 (progressivity)−0.0392***−0.0192***−0.0195***0.017−0.0084**−0.021***
(−8.05)(−3.22)(−3.28)(1.04)(−2.01)(−4.05)
Food aid (t−1)0.3705***0.3779***0.3765***0.66***0.6684***0.89***
(69.02)(55.62)(53.07)(20.88)(25.26)(65.47)
Regional dummiesNoYesYesYesYesNo
Year dummiesNoNoYesYesYesYes
LR statistic460.24527.95568.42471.45659.781980.25
P-value0.000.000.000.000.000.00
Number of observations3,5583,5583,5589008101,310
Source: See text.(***), (**), and (*) denote significance at the 1, 5, and 10 percent level, respectively.

Bottom quartile of countries ranked by average nonconcessional food availability during 1970-2000.

Bottom quartile of countries ranked by average per capita income during 1970-2000.

Source: See text.(***), (**), and (*) denote significance at the 1, 5, and 10 percent level, respectively.

Bottom quartile of countries ranked by average nonconcessional food availability during 1970-2000.

Bottom quartile of countries ranked by average per capita income during 1970-2000.

Furthermore, the sign of ϕ1 suggests that food aid is countercyclical for the sample as a whole but insignificant. We run the modified Tobit regressions for selected subsamples: the food-insecure (defined as the bottom quartile of countries ranked by nonconcessional food availability) and low-income countries (defined as the bottom quartile of countries ranked by per capita income). The results suggest that for the most food-insecure and low-income countries, food aid has been disbursed countercyclically. We further test whether this holds for sub-Saharan Africa given the absence of correlation between business cycles in donor countries and in sub-Saharan Africa. The results indicate that food aid is significantly progressive and countercyclical in Africa.

The results in Table 3 imply that food aid covers a minuscule amount of food needs. In particular, food aid covers only about 7 kilograms out of every contemporaneous metric ton shortfall in food-insecure countries. This confirms previous findings in the literature that food aid mitigates consumption shortfall in some countries, but is far from sufficient to cover the entire consumption shortfall (Barrett and Heisey, 2002, and Lavy, 1992).

Finally, the coefficient on lagged food aid (φ3) is relatively large across specifications and significant, confirming previous findings that there is a persistence or inertia in food aid distributions.

Other Filters

The regression results reported in Tables 2 and 3 are based on the linear detrending technique. We reestimate Eqs. (4a) and (4b) and substitute measures of transitory shortfalls in food availability using the quadratric trend, band pass filter, and the Hodrick-Prescott filter for the sample as a whole. The results are generally invariant to the choice of filter.4

Food Aid in the 1990s

Have food aid flows become more countercyclical over time? To test changes over time, we divide the sample into 10-year periods. As indicated in Table 4, food aid is consistently progressive; if anything, there is some evidence that it has become more progressive over time. In contrast, the responsiveness of food aid flows to transitory shortfalls in consumption has varied over time. In terms of decades, it was significantly countercyclical over the 1980s. Contrary to expectations, food aid has not become countercyclical in recent years. Dividing the sample into 15-year periods and 20-year periods reinforces these findings. The results hold for a linearly detrended measure of food availability and are robust to other measures of cyclical fluctuations. An expansion of the regression equation to include dummy variables for the 1980s and the 1990s and their interaction with other independent variables also indicates that food aid is consistently progressive but has not become more countercyclical over time.5 There is some evidence that the incremental trend in food aid has become weaker over time, as the coefficient estimates for lagged food aid suggest.

Table 4.Modified Tobit Regression Results: Food Aid Flows Over Time(Linear detrending)
10-Year Periods15-Year Periods20-Year Periods
1971-801981-901991-20001971-851986-20001971-901981-2000
φ1 (cyclicality)−0.0002−0.0048***0.0027−0.0030***0.0036−0.0030***−0.0027
(−0.15)(−2.67)(0.38)(−3.24)(0.76)(−2.66)(−0.74)
φ1 (progressivity)−0.0144***−0.0154***−0.0369***−0.0162***−0.0393***−0.0157***−0.0433***
(−5.06)(−4.18)(−2.98)(−6.15)(−4.56)(−6.51)(−6.31)
Food aid (t−1)0.8176***0.9104***0.1436***0.88***0.3158***0.8818***0.3155***
(43.61)(45.93)(4.08)(55.36)(11.32)(63.65)(53.45)
Regional dummiesNoNoNoNoNoNoNo
Year dummiesNoNoNoNoNoNoNo
LR statistic1118.661222.3626.561780.0095.592309.19229.59
P-value0.000.000.000.000.000.000.00
Number of observations1,1891,1861,1831,7841,7742,2572,369
Source: See text.(***), (**), and (*) denote significance at the 1, 5, and 10 percent level, respectively.
Source: See text.(***), (**), and (*) denote significance at the 1, 5, and 10 percent level, respectively.

Food Aid and Fiscal Variables

Previous studies suggest that counterpart funds generated by monetized food aid account for a significant share of the government budget in some countries. Using the same econometric framework as in Eqs. (3) and (4), we now examine how food aid moves with relative and absolute revenue shortfalls. We use the Hodrick-Prescott filter to detrend the revenue series and estimate relative revenue shortfalls.

The results are provided in Table 5. The columns marked “Balance” and “Revenue” indicate coefficient estimates from a regression of food aid on (absolute and relative) shortfalls in general government fiscal balances and general government revenues, respectively. The results suggest that countries that have the largest revenue shortfall or largest overall fiscal deficit receive proportionately more aid. Food aid thus responds to absolute shortfalls in domestic resources and may provide critical budget support, to the extent that monetized food aid generates counterpart funds and non-monetized food aid alleviates spending pressures. However, food aid is not statistically associated with relative shortfalls in government revenue or the government fiscal balance. This reinforces the findings from previous sections: food aid responds to measures of absolute, but not relative, need.

Table 5.Tobit Regression Results: Fiscal Variables(Hodrick-Prescott filter)
All CountriesAid-Dependent Countries1Low-Income Countries2
BalanceRevenueBalanceRevenueBalanceRevenue
φ1 (cyclicality)0.0002*0.00010.00020.00010.00010.00003
(1.78)(1.30)(1.47)(1.24)(0.83)(0.92)
φ2 (progressivity)−0.0002**−0.00012**−0.0003**−0.0001**−0.0002**0.0001
(−5.13)(−3.20)(−3.88)(−2.41)(−2.03)(1.24)
Food aid (M)0.83**0.85**0.82**0.84**0.67**0.67**
(59.30)(60.84)(44.10)(45.20)(19.93)(19.67)
Regional dummiesYesYesYesYesYesYes
Year dummiesYesYesYesYesYesYes
LR statistic2378.712366.291349.581340.44427.99426.45
P-value0.000.000.000.000.000.00
Number of observations2,4142,4141,3821,382500500
Source: See text.(**), (**), and (*) denote significance at the 1, 5, and 10 percent level, respectively.

Bottom quartile of countries ranked by average aid per capita during 1970-2000.

Bottom quartile of countries ranked by average per capita income during 1970-2000.

Source: See text.(**), (**), and (*) denote significance at the 1, 5, and 10 percent level, respectively.

Bottom quartile of countries ranked by average aid per capita during 1970-2000.

Bottom quartile of countries ranked by average per capita income during 1970-2000.

The results in Table 5 are based on aggregate food aid. Because counterpart funds are generated from the sale of commodities provided through aid, a more accurate measure would be an analysis of the component that is sold in local markets.6 Data on the volume of food aid sold, by country, are available from WFP for 1988 onward. They indicate that, on average, the share of sold food in aggregate food aid has fallen from about 45% to 30%.

Using these data and employing the same econometric framework utilized above, we examine the impact of food aid volume sold in local markets on relative and absolute revenue shortfalls and the overall budget deficit. The results are reported in Table 6. They suggest that food aid has benefited countries with large overall deficits.7 The magnitude is much larger than reported in Table 5 using aggregate food aid. However, there is no measurable association between food aid sold on local markets and revenue shortfall, whether in absolute or relative terms.

Table 6.Tobit Regression Results: Food Aid Sales and Fiscal Variables, 1989-2000(Hodrick-Prescott filter)
All CountriesMost Food-Insecure1Aid-Dependent Countries2
BalanceRevenueBalanceRevenueBalanceRevenue
φ1 (cyclicality)−0.044−0.166−0.070.05−0.26−0.48
(−0.27)(−1.09)(−0.39)(0.29)(−0.67)(−1.14)
φ2 (progressivity)−0.18**0.05−0.24***−0.02−0.30*0.24
(2.28)(0.97)(−3.55)(−0.49)(−1.87)(1.55)
Food aid (t-1)0.83***0.83***0.68***0.84***0.76***0.76***
(31.20)(30.71)(11.18)(15.72)(13.54)(13.51)
Regional dummiesYesYesYesYesYesYes
Year dummiesYesYesYesYesYesYes
LR statistic721.23715.62194.60180.35212.31209.24
P-value0.000.000.000.000.000.00
Number of observations940940231231265265
Source: See text.(***), (**), and (*) denote significance at the 1, 5, and 10 percent level, respectively.

Bottom quartile of countries ranked by average nonconcessional food availability during 1970-2000.

Bottom quartile of countries ranked by average aid per capita during 1970-2000.

Source: See text.(***), (**), and (*) denote significance at the 1, 5, and 10 percent level, respectively.

Bottom quartile of countries ranked by average nonconcessional food availability during 1970-2000.

Bottom quartile of countries ranked by average aid per capita during 1970-2000.

5. Discussion and Policy Implications

The empirical evidence examined in this paper suggests that global food aid has been allocated to where it is most needed. Based on data covering a large sample of recipient countries during 1970-1999, the evidence suggests that countries with larger absolute shortfalls in food availability have received more aid. Food aid has also been countercyclical within countries with the greatest need. The results are robust to various specifications and filtering techniques.

Food aid has nonetheless fallen short of its objectives. For the sample of food-insecure countries for which food aid has been countercyclical, quantities have not been enough to stabilize consumption. For other recipient countries, food aid has not been significantly countercyclical. Thus, in these countries, food aid does not function as a social safety net. In addition, the responsiveness of food aid flows to transitory shortfalls in consumption has varied over time. In terms of decades, it was significantly countercyclical over the 1980s, but not significantly countercyclical over the 1990s. With respect to fiscal variables, food aid has benefited countries with large overall fiscal deficits. However, there is no measurable association between food aid sold on local markets and revenue shortfall, whether in absolute or relative terms.

The acyclicality of food aid has two implications for macroeconomic and fiscal management. First, to the extent that recipient governments rely on counterpart funds as a revenue source and food aid is not disbursed in a countercyclical manner, the instability of budgetary revenues is not alleviated. Second, shortfalls in food supply increase demands on the government budget for programs to shield the consumption of the population. In the absence of counterpart funds from food aid, the government will have to rely on domestic resources to fund such programs. Falling revenues and rising demand for budgetary programs are likely to complicate macroeconomic management for the food aid-receiving countries. In the circumstances, the “automatic stabilizer” benefits of countercyclical food are largely not met.

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Reprinted from the Review of Development Economics, Vol. 8, Sanjeev Gupta, Benedict Clements, and Erwin R. Tiongson, “Foreign Aid and Consumption Smoothing: Evidence from Global Food Aid,” ©2004, with permission from Blackwell.The authors wish to thank Abbassian Abdolreza, Rina Bhattacharya, Aleš Bulíř, Chris Barrett, Paul Cashin, Bikas Joshi, Menachem Katz, Noureddine Krichene, Wojciech Maliszewski, Srobona Mitra, Paulo Neuhaus, Stéphane Pallage, Michel A. Robe, Tobias Roy, Ratna Sahay, George Simon, Shahla Shapouri, Thierry Tressel, Luis Valdivieso, Mario Zejan, and an anonymous referee for helpful comments on an earlier draft. George Simon and Giampiero Lucarini (WFP) generously provided data on food aid.
1Given the uncertainty about the nature of business cycles in developing countries, we recognize that there could be a case for using different values of λ to assess the robustness of the results. Instead, we opt to use alternative detrending techniques (as described below) as a robustness test. In addition, recent research indicates that traditional values for λ are appropriate for most countries (Marcet and Ravn, 2001).
2Given our interest in assessing whether food aid responds to food needs across (as well as within) countries, country fixed effects are not included.
3Country-level results (not reported) are available on request from the authors. The correlations between food aid and the cyclical components of log per capita income—a proxy for consumption shortfalls—show similar patterns (not reported).
4The results are available from the authors upon request.
5Results are available from the authors upon request. The 1970s act as the base period in this analysis. Using dummy variables for the 1980s and 1970s, with the 1990s as the base period, yields qualitatively similar results.
6However, non-monetized food aid is also critical for alleviating spending pressures on the budget. In this respect, aggregate food aid (rather than just the volume of food sold in local markets) may be a more accurate measure.
7It can be argued that fiscal balances are jointly determined with food aid flows, as recipient governments incur new expenses associated with food aid agreements. However, given the very small share of food needs covered by contemporaneous food aid, this is not likely to have an impact on the empirical results.

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