_ANNEX 3. DETERMINANTS OF NET ENROLLMENT RATE IN INDONESIA_ The following specification is aimed to examine demand and supply side factors in the determination of education outcomes.

_Ri_ = α+ β 1 _E_ 1 + β 2 _E_ 2 + β 3 _S_ + +β 4 _GRDP_ + β 5 _Po_ + β 6 _R_ + β 7 _A_ + β 8 _Sc_ + β 9 _D_ + β 10 _K_ + β 11 _L_ + _ui_ Where: i = District i = 1...N, N=409 R = Net enrollment rates E1 = Log of education spending per population in school age (total education spending per number of children aged between 7 and 18 years).<sup>41</sup> E2 = Log average district education spending (per population in school age) from 2001 to 2003 S= Education personnel spending as share of total education spending (ratio of personnel spending to total education spending) GRDP= Log of Gross Regional Product per capita Po = Poverty head count R = Remote area (Geometric average of the distance from village to the closer adjacent district) A = Road Access (% of villages with access to paved roads) Sc = No of primary and secondary schools per square kilometer D = Disaster (0-1) variable indicating whether the district has been hit by any kind of disaster during last year

- K  = Dummy for urban/rural districts (=1 for urban)

- L= Percent of population in school age working

# _Sources_

Net enrollment and percent of population in school age that work were computed based on the National Socio- Economic Survey (Susenas) 2005. Education spending and the share of salaries in total education spending are taken from the SIKD (sub-national budgets) dataset, and from the distribution of central government spending on DAK and Dekonsentrasi as reported by the MoF. Gross domestic product per district is drawn from figures released by the National Statistics Bureau (BPS). The remaining variables are computed based in Podes 2005.

# _Econometric Models_

Models 1, 2 and 3 estimate the specification linearly by ordinary least squares; whereas model 4 estimates a Logit model. The latter due to the fractional nature of the dependent variable. Model 3 and 4 control for province-level unobserved effects by including province dummies (fixedeffects). The province level coefficients are not reported for exposition simplicity.

Regression results confirm the role of public spending as a determinant of enrollment rates. The coefficient for public education spending is positive and statistically significant in all of the estimated models and specifications. Given the linear-log functional form used in the estimation, a one percent increase in education spending would increase the net enrollment rate by 0.02 percentage points, with a point elasticity of 0.02 * (1/Net enrollment of district i). The elasticity of education expenditures resulting from the Logit model (column 4) is on the same range as the linear models (approximately.03). There are lags built into all models with spending in education (per potential student) preceding the impact on enrollment by 1 year and the average of district spending by lag from 2 to 4 years (2001-2003). Yet, the average district spending (per population in school age) from 2001-2003 is not statistically significant in any of the estimated models.

> 41 Population in school age is used to proxy for per capita spending (as opposed to the number of actual students) in order to avoid endogeneity (i.e. an increase in net enrollment, reflecting a higher number of actual students, would also increase the denominator of a spending “per student” variable).

31