Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (Bace) Approach

54 Pages Posted: 29 May 2000 Last revised: 18 Oct 2010

See all articles by Gernot Doppelhofer

Gernot Doppelhofer

University of Cambridge - Faculty of Economics and Politics; CESifo (Center for Economic Studies and Ifo Institute)

Ronald I. Miller

NERA Economic Consulting

Xavier Sala-i-Martin

Columbia University, Graduate School of Arts and Sciences, Department of Economics

Date Written: June 2000

Abstract

This paper examines the robustness of explanatory variables in cross-country economic growth regressions. It employs a novel approach, Bayesian Averaging of Classical Estimates (BACE), which constructs estimates as a weighted average of OLS estimates for every possible combination of included variables. The weights applied to individual regressions are justified on Bayesian grounds in a way similar to the well-known Schwarz criterion. Of 32 explanatory variables we find 11 to be robustly partially correlated with long-term growth and another five variables to be marginally related. Of all the variables considered, the strongest evidence is for the initial level of real GDP per capita.

Suggested Citation

Doppelhofer, Gernot and Miller, Ron I. and Sala-i-Martin, Francesc Xavier, Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (Bace) Approach (June 2000). NBER Working Paper No. w7750. Available at SSRN: https://ssrn.com/abstract=214976

Gernot Doppelhofer

University of Cambridge - Faculty of Economics and Politics ( email )

Austin Robinson Building
Sidgwick Avenue
Cambridge, CB3 9DD
United Kingdom

CESifo (Center for Economic Studies and Ifo Institute)

Poschinger Str. 5
Munich, DE-81679
Germany

Ron I. Miller

NERA Economic Consulting ( email )

1166 Avenue of the Americas, 34th Floor
New York, NY 10036
United States

Francesc Xavier Sala-i-Martin (Contact Author)

Columbia University, Graduate School of Arts and Sciences, Department of Economics ( email )

420 W. 118th Street
New York, NY 10027
United States
212-854-7055 (Phone)

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