Search

A limitation of most empirical cross-country studies that focus on determinants of gross domestic product (GDP) is that they fail to distinguish explicitly between inputs used in production and conditions that facilitate production. For example, physical capital, human capital, and labor are production inputs, whereas the quality of institutions, macroeconomic stability, and market quality are conditions that facilitate production. This article takes this distinction seriously and uses a stochastic frontier approach to study factors affecting economic performance. A panel data set of 71 countries for the 1980-98 periods is used to estimate a production frontier with physical capital, human capital, and labor as inputs. The article also analyzes what drives productive efficiency, using the institutional framework, macroeconomic stability, market quality, and urbanization as possible explanatory factors. Urbanization turns out to be an important determinant, with the rule of law, inflation rate, and market quality also affecting productive efficiency.

To improve the likelihood of reaching the Millennium Development Goals (MDGs), or more generally to improve their social indicators, countries (or states and provinces within countries) basically have two options: increasing the inputs used to "produce" the outcomes measured by the MDGs, or increasing the efficiency with which they use their existing inputs. The four papers presented in this study look at whether improvements in efficiency could bring gains in outcomes. The first two papers use world panel data in order to analyze country level efficiency in improving education, health, and GDP indicators (GDP is related to the MDGs because a higher level of income leads to a reduction in poverty). The other two papers use province and state level data to analyze within-country efficiency in Argentina and Mexico for "producing" good education and health outcomes. Together, the four papers suggest that apart from increasing inputs, it will be necessary to improve efficiency in order to reach the MDGs. While this conclusion is hardly surprising, the analysis helps to quantify how much progress could be achieved through better efficiency, and to some extent, how efficiency itself could be improved.