Abstract
This paper provides a survey and synthesis of econometric tools that have been employed to study economic growth. While these tools range across a variety of statistical methods, they are united in the common goals of first, identifying interesting contemporaneous patterns in growth data and second, drawing inferences on long-run economic outcomes from cross-section and temporal variation in growth.
We describe the main stylized facts that have motivated the development of growth econometrics, the major statistical tools that have been employed to provide structural explanations for these facts, and the primary statistical issues that arise in the study of growth data. An important aspect of the survey is attention to the limits that exist in drawing conclusions from growth data, limits that reflect model uncertainty and the general weakness of available data relative to the sorts of questions for which they are employed.Keywords
identification, estimation, parameter heterogeneity, model uncertainty, nonlinearities, convergence, growth determinants
JEL classification: C2, C3, O1, O2, O3
The totality of our so-called knowledge or beliefs, from the most causal matters of geography and history to the profoundest laws of atomic physics... is a manmade fabric which impinges on experience only along the edges... total science is like a field of force whose boundary conditions are experience... A conflict with experience on the periphery occasions readjustments in the interior of the field. Reevaluation of some statements entails reevaluation of others, because of their logical interconnections... But the total field is so underdetermined by its boundary conditions, experience, that there is much latitude of choice as to what statements to reevaluate in the light of any single contrary experience.
W.VO. Quine[311]
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