The Determinants and Consequences of the Placement of Government Programs in Indonesia
Author(s) -
Mark M. Pitt,
Mark R. Rosenzweig,
Donna Marie Gibbons
Publication year - 1993
Publication title -
the world bank economic review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.542
H-Index - 89
eISSN - 1564-698X
pISSN - 0258-6770
DOI - 10.1093/wber/7.3.319
Subject(s) - socioeconomic status , human capital , cross sectional study , cross sectional data , attendance , public health , government (linguistics) , demography , geography , demographic economics , socioeconomics , economics , population , economic growth , econometrics , medicine , sociology , pathology , linguistics , philosophy , nursing
Most estimates of the consequences of public programs rely on the cross-sectional association between region-specific programs and program outcomes. Such estimates assume that the spatial distribution of programs is random. This article reports estimates of the effects of public programs on basic human capital indicators and the biases in conventional cross-sectional estimates of program effects due to non-random program placement. The estimates are obtained from pooled observations on human capital outcomes, socioeconomic variables, and program coverage at the kecamatan (subdistrict) level. The observations are based on successive sets of Indonesian cross-sectional household and administrative data during 1976-86. The determinants of the spatial allocation of programs in Indonesia in 1976-86 are also estimated. The empirical results indicate that the presence of grade and middle schools in villages has a significant positive effect on the school attendance rates of teenagers. The presence of health clinics in villages also positively affects the schooling of females ages 10-18. However, no evidence is found of any significant effects of the presence of family planning and health programs on either the survival rates of children or on cumulative fertility. The estimates also suggest that the use of cross-sectional data results in substantial biases in the estimates of program effects because of the evident nonrandom spatial allocation of public programs.
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