Econometrics for Grumblers: A New Look at the Literature on Cross-Country Growth Empirics

Since the seminal contribution of Gregory Mankiw, David Romer and David Weil (1992), the growth empirics literature has used increasingly sophisticated methods to select relevant growth determinants in estimating cross-section 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' (Abramowitz, 1956).  The central theme of this survey is an investigation of this choice of specification against the background of pertinent data properties when the units of observations are countries or regions and the time-series dimension of the data becomes substantial.  We present two general empirical frameworks for cross-country productivity analysis and demonstrate that they encompass the 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 is important for reliable empirical analysis.  This idea is developed against the background of the pertinent time-series and cross-section properties of macro panel data.