interpretation is that the SFD has the strongest impact when its efforts complement other projects, rather than when it operates alone. It is not entirely clear why this should be so, but it is possible that there are threshold effects at work: for instance, providing potable water to half a village may be helpful, but if the SFD then steps in and supplements such efforts, thereby ensuring everyone has potable water, it may be that only then are the effects on health appreciable.

**Table 13.** **<u>Summary of Effects of SFD Interventions in Road Maintenance and Improvement</u>**

|||SFD inte<br>inter<br>|rvention 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|<br>Kernel|Regres-<br>sion|Nearest<br>Neighbor|Kernel|Regres-<br>sion|Nearest<br>Neighbor|<br>Kernel|
|Spending on<br>transportation|65.8|-12.94***<br>(-6.76)|-5.93*<br>(-1.90)|-11.57***<br>(-4.20)|2.92<br>(0.86)|-4.40<br>(-0.60)|1.34<br>(0.25)|-17.79**<br>(-7.78)|-12.41**<br>(-2.38)|-16.68***<br>(-6.32)|
|% road utilization|0.15|-0.001<br>(-0.10)|-0.006<br> (-0.28)|0.01<br>(0.95)|-0.30**<br>(-2.08)|0.06<br>(0.20)|0.002<br>(0.14)|0.008<br>(0.82)|0.005<br>(0.21)|0.01<br>(0.74)|
|Employment rate|0.95|0.01***<br>(2.99)|0.01<br>(1.32)|0.01***<br>(2.70)|-0.01<br>(-1.38)|-0.01<br>(-0.85)|-0.002<br>(-0.20)|0.02***<br>(4.17)|0.01<br>(1.58)|0.02***<br>(2.90)|
|Farm-income†|68.5|27.8***<br>(6.68)|29.7***<br>(2.93)|20.9***<br>(2.84)|36.2***<br>(4.85)|35.3<br>(1.56)|37.9**<br>(2.30)|23.8***<br>(4.72)|14.0<br>(1.01)|15.2*<br>(1.82)|
|Non-farm<br>income†|54.6|-10.0*<br>-1.89|-6.1<br>-0.65|-11.4**<br>-2.08|22.48**<br>2.12|35.62<br>1.62|16.06<br>0.93|-20.4***<br>-3.48|-19.8**<br>-2.22|-22.1***<br>-3.63|
|Under-5<br>mortalityrate|19.9|-3.68<br>(-1.17)|-16.22<br>(-1.44)|-4.80<br>(-1.20)|-1.38<br>(-0.24)|2.74<br>(0.27)|-1.54<br>(-0.24)|-4.97<br>(-1.31)|-13.08<br>(-1.07)|-5.81<br>(-1.21)|
|Enrollment rate,<br>school|0.91|0.01<br>(1.24)|0.02<br>(1.21)|0.01<br>(0.92)|-0.002<br>(-0.16)|-0.02<br>(-0.56)|-0.004<br>(-0.18)|0.01<br>(1.42)|0.01<br>(0.39)|0.01<br>(1.02)|
|Poverty rate|3.8|0.01<br>(0.05)|-1.07<br>(-1.46)|-0.15<br>(-0.33)|0.66*<br>(1.67)|1.79<br>(1.29)|0.84<br>(0.96)|-0.36<br>(-1.23)|-0.68<br>(-0.79)|-0.38<br>(-0.77)|

_Notes:_ Numbers in parentheses are t-statistics, * significant at 10% level, ** significant at 5% level, *** significant at 1% level. † All coefficients shown here should be multiplied by 1,000. 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.

# _Microcredit_

The SFD does not lend directly to households, but since 1991 it has spent LE 1,062 million to support microcredit, channeling both working capital and grants to financial intermediaries that in turn do provide microcredit. SFD support for microcredit has gone to productive family associations (33%), NGOs (31%), and the PBDAC (20%), as well as to village banks (9%), and occasionally to commercial banks (2%) or other lenders (5%).

However, it is not possible to link individual loans with the activities of the SFD, so the approach that we take in this section is to estimate the impact of microcredit in general. Our working assumption is that if microcredit has an impact, then SFD support for microcredit has an impact. This is not a trivial assumption; if SFD support for microlending simply displaces other support for microlending, then SFD _Impact Evaluation: Egyptian Social Fund for Development_ _Version of June 29, 2009_ _Page 21 of 36_