clear where SFD projects are undertaken in conjunction with other interventions (comparing C vs. E); when SFD-only areas are compared with areas lacking any project, the effects of SFD projects are either not statistically significant or counterintuitive (in the case of renal disease). It is curious that sanitation projects are not associated with lower household spending on health; one might have expected better sanitation facilities to improve health and so reduce such spending. Better health might then be associated with higher productivity and incomes, and a lower poverty rate.

**Table 12.** **<u>Summary of Effects of SFD Interventions in Sanitation</u>**

|||SFD int<br>inter<br>|ervention vs<br>vention[A<br>|. no SFD<br>vs. B]<br>|SFD int<br>interve<br>|ervention on<br>ntion at all[<br>|ly vs. no<br>D vs. F]<br>|SFD inter<br>other inter<br>|vention wit<br>ventions on<br>|h others vs.<br>ly [C vs. E]<br>|
|---|---|---|---|---|---|---|---|---|---|---|
||Mean|Regres-<br>sion|Nearest<br>Neighbor|Kernel|Regres-<br>sion|Nearest<br>Neighbor|Kernel|Regres-<br>sion|Nearest<br>Neighbor|<br>Kernel|
|Access: sewer-<br>age network|0.52|0.04<br>(1.57)|0.12<br>(1.02)|0.11<br>(1.47)|0.01<br>(0.25)|0.11<br>(0.70)|0.07<br>(0.66)|0.06*<br>(1.81)|0.27*<br>(1.94)|0.16*<br>(1.80)|
|Spending on<br>sanitation|4.41|-1.47**<br>(-2.49)|-2.26<br>(-1.50)|-1.82<br>(-1.41)|0.003<br>(0.00)|-0.048<br>(-0.01)|-0.53<br>(-0.29)|-2.30***<br>(-2.81)|-1.60<br>(-0.67)|-3.07***<br>(-3.28)|
|Prevalence: renal|0.54|0.22*|0.11|0.20|0.99***|0.71|0.88**|-0.39**|-0.23|-0.44***|
|disease||(1.96)|(0.30)|(0.82)|(6.59)|(0.94)|(2.17)|(-2.45)|(-0.44)|(-4.01)|
|Prevalence:|0.09|-0.04|0.003|-0.04|-0.09|-0.51|-0.11***|0.09|0.19|0.03|
|bilharzia||(-0.62)|(0.03)|(-0.50)|(-1.57)|(-1.21)|(-4.52)|(0.83)|(1.03)|(0.17)|
|Spending on|99.1|0.79|24.25|9.83|3.20|19.96|10.09|6.59|8.72|9.55|
|health||(0.14)|(1.30)|(0.66)|(0.42)|(0.82)|(0.63)|(0.74)|(0.22)|(0.40)|
|Poverty rate|3.6|-0.80***<br>(-2.62)|-1.86<br>(-1.52)|-1.21*<br>(-1.66)|-0.15<br>(-0.34)|-1.43<br>(-1.02)|-0.97<br>(-0.86)|-1.07***<br>(-2.57)|-0.91<br>(-0.64)|-1.54*<br>(-1.80)|

_Notes:_ Numbers in parentheses are t-statistics, * significant at 10% level, ** significant at 5% level, *** significant at 1% level. All results are derived by first estimating a propensity score equation, and then confining the regression, nearest-neighbor matching, or kernel matching, to the region of common support. _Source:_ Authors’ calculations based on HIECS and community survey 2004/2005.

Over the period 1991-2007, the SFD spent over LE 500 million on building and maintaining rural roads. As expected, these projects were associated with substantial reductions in household spending on transportation, by about LE 13 (compared to a mean of LE 66). The economic effects of these projects are quite strong: they raised the employment rate, and they increased farm income by almost half, presumably by lowering the cost of acquiring inputs and of delivering farm output to market. Only in the case where SFD-only areas are compared with no-project areas do roads also raise non-farm income; in the other comparisons non-farm income fell, perhaps as a result of greater competition from outsiders as areas become more accessible, or possibly because the increased attractiveness of farming led some people to cut back on non-farm activities. More surprisingly, there was no clear impact of the road projects on the poverty rate. A plausible explanation is that opening up villages to the outside world may raise incomes on average, but expose some vulnerable members of society to new economic pressures.

There is an interesting pattern that runs through Tables 9 to 13: as a general rule, SFD interventions have a stronger measurable effect when the comparison is between areas where there are SFD interventions alongside other projects (case C) and areas where there are only other projects (case E). A reasonable _Impact Evaluation: Egyptian Social Fund for Development_ _Version of June 29, 2009_ _Page 20 of 36_