Empirical Results

The regression results in Table 5.3 show that food aid distributed between t-1 and t-5 is positively and significantly related to children’s height: a one standard deviation increase in lagged food aid is associated with a 0.12 (model 3) to 0.18 (model 1) standard deviation increase in the percentage of children that do not suffer from stunting.¹⁰² Food aid therefore seems to be better than its reputation. Despite all the criticism, food aid distributions since the mid-1990s have made a significant contribution to alleviating hunger and thereby reducing the probability of being stunted for children in recipient countries.

The weight of children in recipient countries is not significantly correlated to food aid that was provided between the time of birth and one year prior to the time of observation (Table 5.4).¹⁰³ The coefficient for contemporary food disbursements is negative and significant (model 1 of Table 5.4). However, it might be misleading to assume that food aid has a negative impact on children’s weight. The negative and significant outcome might be put down to reverse causality effects as food aid is more likely to be given to countries with a high percentage of underweight children.

102 The deeper lags of food aid serve as control variables but are not of interest for our interpretation, as we only want to explain the impact on children’s well-being. Children’s height cannot be directly influenced by food aid that is given prior to their birth. However, earlier food aid flows might have a significant impact on prior generations and thereby on the offspring’s height and are thus controlled for.

Trying to interpret these variables would be highly speculative. As mentioned above, autocorrelation of error terms and multicollinearity was rejected by statistical tests. Therefore, including several lags of food aid does not pose a statistical problem here. However, we also tested specifications where we only included one of the lagged food aid variables (not shown here), which did not change the results.

103 Deeper lags were not included in the regression, as weight is a measure that acts rather promptly in contrast to height that might need longer periods to catch up and might be predetermined by previous generations’ well-being. To make the regressions comparable, we also included deeper lags in regressions not shown in this table, which did not lead to changes in our variable of interest (Tables available from the author).

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Table 5.3: Food aid’s impact on (no) stunting, fixed effects estimates

Notes: P-values in parentheses, ***, **, * significant on the 1, 5, and 10%-level. Country and time fixed effects and probability weights applied in every specification.Standard errors are heteroskedasticity and cluster-robust.

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Table 5.4: Food aid’s impact on (no) underweight, fixed effects estimates

(1) (2)

Food aid -3.055**

(0.013)

Food aid Lag 1-5 -0.758 0.559

(0.330) (0.257)

Health expenditure of gov. -0.0111 -0.021

(0.912) (0.837)

Political rights 0.002 0.003

(0.516) (0.421)

Intra state war -0.004 -0.004

(0.714) (0.759)

HIV -0.137 -0.187

(0.578) (0.497)

Infant mortality -1.283 -1.566*

(0.122) (0.051)

GDP p.c. (log) 0.009 0.016

(0.705) (0.481)

Agricultural Land -0.088 -0.125

(0.513) (0.441)

Immunisation (measles) -0.068 -0.048

(0.147) (0.303)

Prenatal care 0.131*** 0.119***

(0.003) (0.005)

Rural population 0.101 0.010

(0.645) (0.956)

Constant 0.706*** 0.717***

(0.004) (0.004)

Time FE? Yes Yes

Country FE? Yes Yes

N 153 153

Within-R2 0.644 0.605

Notes: P-values in parentheses, ***, **, * significant on the 1, 5, and 10%-level respectively, probability weights as well as country and time fixed effects applied in every specification. Standard errors are heteroskedasticity and cluster-robust.

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Admittedly, the same argument goes for populations with a high share of stunted children and yet we do not find significant negative effects of contemporary food aid on stunting (Table 5.3, model 1). A tentative explanation for this could be that – as weight reacts more quickly to external influences than height – a high proportion of underweight children indicates that a country is currently facing a severe food crisis and donors react promptly by providing emergency aid. A high share of stunted children, on the other hand, tends to point to persistent food insecurity. One could therefore assume that donors react differently to short-term food crises, often triggered by external shocks, and persistent nutritional shortages in a recipient country. The question whether the negative and significant coefficient of contemporary food aid indicates that there is reverse causality or whether food aid has indeed a negative impact on nutritional outcomes in the short run cannot be answered in this study due to the above-mentioned statistical restrictions.

If all food aid donors have the same (developmental) goals in providing food aid, then the effects of food aid on well-being are uniform. If, however, different donors are giving aid for different reasons, then the effect of food aid on stunting and malnutrition might also vary, depending on who provided it. Table 5.5 shows the results for the regression analysis that evaluates the efficiency of U.S. food aid in comparison with other donors. U.S. food aid provides neither better nor worse results than other donors’

food provisions when it comes to children’s heights (models 1 to 3 of Table 5.5). Only contemporary U.S. food aid performs significantly worse. Again, this coefficient should be handled with caution, as it might simply reflect that the U.S. is giving more food aid to countries that currently have a high percentage of stunted children (and therefore react to generally bad nutritional conditions and not only to natural disasters). There is no significantly different effect of U.S. food aid on the percentage of underweight children (model 4 of Table 5.5). Likewise, no better or worse performance compared to other donors can be found for multilateral donors: Table 5.6 shows that multilateral aid has neither a significantly different impact on stunting (models 1 to 3) nor on underweight (model 4).

A factor that also seems to be crucial for the well-being of children is prenatal care.

Throughout every regression and specification in Tables 5.3 to 5.6, prenatal care has a

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positive and significant impact on the outcome variable. As already mentioned above, maternal health and nutrition can affect the offspring’s health to a great extent. The results confirm that prenatal care – by improving maternal health during pregnancy – has a positive effect on the child’s physical development. Apparently, the availability of good medical care during pregnancy is a crucial determinant for the offspring’s health.

To sum up, there seems to be some positive impact of food aid on children’s height for the post-1995 period (or at least a positive relation). However, a positive correlation between food aid and the weight of children, which reacts more quickly to external influences than height, could not be found. Moreover, the frequently discussed statement that U.S. aid is less effective than food aid provided by other donors, particularly multilateral organisations, could not be confirmed here.