Assistant Professor of Economics, University of California at San Diego
Cubberley Conference Room 114
Empirical studies of the relationship between school inputs and test scores typically do not account for the fact that households will respond to changes in school inputs. We present a dynamic household optimization model relating test scores to school and household inputs, and test its predictions in two very different low-income country settings – Zambia and India. We measure household spending changes and student test score gains in response to unanticipated as well as anticipated changes in school funding. Consistent with the optimization model, we find in both settings that households offset anticipated grants more than unanticipated grants. We also find that unanticipated school grants lead to significant improvements in student test scores but anticipated grants have no impact on test scores. Our results suggest that naïve estimates of public education spending on learning outcomes that do not account for optimal household responses are likely to be considerably biased if used to estimate parameters of an education production function.