ECONOMETRICS FOR GRUMBLERS: A NEW LOOK AT THE LITERATURE ON CROSS-COUNTRY GROWTH EMPIRICS

Since the seminal contribution of N. Gregory Mankiw, David Romer and David N. Weil in 1992 the growth empirics literature has used increasingly sophisticated methods to select relevant growth determinants in estimating cross-section growth regressions. The vast majority of empirical approaches, however, limit cross-country heterogeneity in production technology to the specification of total factor productivity, the 'measure of our ignorance'. In this survey, we present two general empirical frameworks for cross-country growth and productivity analysis and demonstrate that they encompass the various approaches in the growth empirics literature of the past two decades. We then develop our central argument, that cross-country heterogeneity in the impact of observables and unobservables on output as well as the time-series properties of the data are important for reliable empirical analysis.