effect of TC is close to zero, and the effect of SP aid on public expenditure is close to 1. Full fungibility is rejected across the board, but the null hypothesis of no fungibility cannot be rejected in any of the cases.

Table 5: Disaggregated education and health aid, marginal effects of the log-linear model

||Public education exp.|Public health exp.|
|---|---|---|
|�_βSP_|1.342|1.092|
|_βSP_ ⩽0|0.005|0.006|
|_βSP_ ⩾1|0.750|0.585|
|�_βT C_|0.0522|0.0602|
|_βT C_ ⩽_−_1|0.000|0.000|
|_βT C_ ⩾0|0.632|0.591|

Note: _β_<sup>�</sup> _SP_ and _β_<sup>�</sup> _T C_ are marginal effects, calculated at the sample means, based on the fixed effects estimation of equation (11) in loglinear form. Annual data, 1990-2003. All regressions include time dummies and the standard set of control variables (coefficients not reported) and are estimated with heteroskedasticity-robust standard errors, clustered by country. _βSP_ ⩽ 0 ( _βSP_ ⩾ 1) and _βT C_ ⩽ _−_ 1 ( _βT C_ ⩾ 0) are p-values for the test of full (no) fungibility for sector program aid and technical cooperation, respectively. Source: Author’s analysis based on data described in the text.

As a more direct and arguably superior approach to determine the effects of influential observations, I reestimate equation (11) by eliminating one country at a time. Figure 1 shows the resulting distribution of the estimated SP aid and TC coefficients. The marginal effect of TC is more stable than that of SP aid in both sectors, which is consistent with the more limited variation in SP aid. A small number of countries induce fairly large changes in the effect of SP aid. For instance, when Lesotho is eliminated, the effect of education SP aid decreases to 0.82. When Tonga is excluded, this effect increases to 1.51. In contrast, the distribution of the estimated coefficient of education TC has a substantially smaller range. For health TC, two countries have a sizable influence on the estimated coefficient when they are omitted from the sample, but the remainder of the distribution is substantially narrower.<sup>26</sup> To examine how sensitive the results are to the removal of countries that appear to exert an undue influence on the coefficients of interest, I omit countries for which the absolute value of the _DFBETAi_ influence statistic for SP aid or TC exceeds the size-adjusted cut-off value of 2 _/√N_ (in this case, _N_ is the number of countries) proposed by Belsley, Kuh, and Welsch (1980).<sup>27</sup> This procedure removes 14 countries in the education sector and 5 countries in the health sector.<sup>28</sup> Table 6 presents the results of estimating equation (11) for this reduced sample, and figure 2 shows partial scatter plots of the key relationships in the FE regressions for both the full and reduced samples. The FE results in the reduced sample are similar to those in the full sample. The effect of TC in both sectors remains close to zero, and full fungibility is easily rejected. The effect of education SP aid decreases sharply to 0.83, which is also the size of the nearly unchanged coefficient of health SP aid. However, full fungibility is rejected in both cases. This result suggests that the conclusions from Table 4, namely that the fungibility of education and health SP aid and TC is limited, are not solely driven by the particular experience of a small number of aid recipients.<sup>29</sup> In what follows, I continue to work with this reduced sample.

To interpret the FE coefficients in a causal way requires a potentially strong assumption of strict exogeneity.

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