**Table 3: Marginal effects of school presence or distance based on alternative specifications of distance, probit** **<u>model of school participation, rural children aged 6 to 14.</u>**

||<br>Alte|<br>rnative model|<br>1|Alter|native model 2||Summar|ystatistics|
|---|---|---|---|---|---|---|---|---|
||Average ma<br>to school<br>funct|rginal effect of<br>based on non-<br>ion of distance|distance<br>linear<br>s|Average m<br>presence of a|arginal effects<br>school in the c|of the<br>luster<sup>(a)</sup>|Propo<br>children<br>cluste|rtion of<br>living in<br>rs with:|
||||Joint|||Joint|||
||Primary<br>school|Secondary<br>school|test: p-<br>value|Primary<br>school|Secondary<br>school|test: p-<br>value|Primary<br>school|<br>Seconda<br>ryschool|
|Niger 1992|-0.028**|0.001|0.000|0.193**|-0.084**|0.000|0.528|0.113|
|Niger 1998|-0.058 **|-0.002**|0.000|0.234**|0.121**|0.000|0.665|0.044|
|Mali 1995-96|-0.024 **|0.002|0.000|0.172**|0.037|0.000|0.347|0.042|
|Senegal 1992-93|0.009 *|0.000|0.093|-0.065|-0.013|0.225|0.549|0.100|
|Burkina Faso 1992-93|-0.033 **|0.000*|0.000|0.169**|-0.030|0.000|0.727|0.124|
|Chad 1998|-0.025 **|-0.001**|0.000|0.108**|0.011|0.000|0.535|0.036|
|Benin 1996|-0.058 **|-0.006**|0.000|0.095**|0.031**|0.000|0.858|0.074|
|Morocco1992|-0.051 *|0.001|0.047|0.017|0.012|0.324|0.580|0.055|
|Cộte d’Ivoire 1994|-0.019 **|-0.001|0.022|0.050**|-0.005|0.028|0.896|0.012|
|Tanzania 1991-92|-0.006 **|0.000|0.000|-0.009*|0.001|0.091|0.792|0.024|
|C.A.R. 1994-95|-0.020 **|-0.001**|0.000|0.002**|-0.002|0.013|0.625|0.043|
|Madagascar 1992|-0.058 **|-0.008**|0.000|-0.012*|-0.022*|0.008|0.778|0.107|
|Dominican Rep.1991|-0.003**|-0.003*|0.000|-0.016|-0.002|0.313|0.744|0.076|
|Nigeria 1999|-0.066 **|-0.013**|0.000|0.000|-0.027*|0.046|0.767|0.472|
|Cameroon 1991|-0.035 **|-0.008**|0.000|-0.042|-0.097**|0.000|0.699|0.094|
|India 1992-93|-0.025 *|-0.005**|0.000|-0.022**|-0.006|0.004|0.920|0.282|
|Haiti 1994-95|-0.001 *|-0.004|0.006|-0.037|-0.016|0.421|0.700|0.176|
|Uganda 1995|-0.005|-0.009**|0.000|-0.009|-0.077**|0.000|0.431|0.081|
|Bangladesh 1993-94|-0.001|-0.011**|0.001|-0.043*|-0.009|0.095|0.925|0.382|
|Bangladesh 1996-97|-0.038|-0.002|0.155|-0.051|-0.002|0.252|0.904|0.412|
|Philippines 1993|-0.022 *|-0.003|0.001|-0.019|-0.005|0.365|0.877|0.252|
|India 1998-99|-0.009|-0.005**|0.000|-0.015|-0.014*|0.047|0.905|0.281|
|Zimbabwe 1994|-0.010 **|-0.003|0.000|-0.053*|-0.034|0.010|0.456|0.150|
|Bolivia1993-94|-0.045*|-0.003**|0.001|-0.067*|-0.061*|0.014|0.805|0.173|

_Note_ : Data ordered by average school participation. Selected results from a model that includes child’s age, adults’ education, characteristics of the head of household, and a set of cluster characteristics. *, ** indicate significance of the underlying probit coefficients at the 5, and 1 percent respectively. (a) Reports average change in probability of enrollment resulting from a change in the dummy variable from zero to one. _Source:_ Author’s calculation from DHS data.

The right panel of Figure 3 plots simulated enrollment with a primary and a secondary school in every village against current enrollment. This specification identifies five countries where the impact of building a primary and secondary school in every cluster would be larger than 10 percentage points (Central African Republic, Madagascar, Mali, Niger, and Uganda). For some countries the impact according to this specification is quite large. For example, in Niger (1998) a primary and secondary school in every cluster would raise enrollments from about 15 to 44 percent; and in Cameroon from about 62 to 88 percent.

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