Interpreting Tests of the Convergence Hypothesis

Andrew Bernard and Steven Durlauf

No 159, NBER Technical Working Papers from National Bureau of Economic Research, Inc

Abstract: This paper provides a framework for understanding the cross- section and time series approaches which have been used to test the convergence hypothesis. First, we present two definitions of convergence which capture the implications of the neoclassical growth model for the relationship between current and future cross-country output differences. Second, we identify how the cross-section and time series approaches relate to these definitions. Cross-section tests are shown to be associated with a weaker notion of convergence than time series tests. Third, we show how these alternative approaches make different assumptions on whether the data are well characterized by a limiting distribution. As a result, the choice of an appropriate testing framework is shown to depend on both the specific null and alternative hypotheses under consideration as well as on the initial conditions characterizing the data being studied.

JEL-codes: C1 (search for similar items in EconPapers)
Date: 1994-06
Note: EFG
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Citations: View citations in EconPapers (32)

Published as Bernard, Andrew B. and Steven N. Durlauf. "Interpreting Tests Of The Convergence Hypothesis," Journal of Econometrics, 1996, v71(1&2,Mar/Apr), 161-173.

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Related works:
Journal Article: Interpreting tests of the convergence hypothesis (1996)
Working Paper: Interpreting Tests of the Convergence Hypothesis (1994)
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