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Title:Multiple Testing in Growth Econometrics PDF Logo
Authors:Deckers, Thomas
Hanck, Christoph
Issue Date:2010
Series/Report no.:Beiträge zur Jahrestagung des Vereins für Socialpolitik 2010: Ökonomie der Familie - Session: Analysing Macroeconomic Panel Data Sets B2-V3
Abstract:This paper discusses two longstanding questions in growth econometrics which involve multiple hypothesis testing. In cross sectional GDP growth regressions many variables are simultaneously tested for significance. Similarly, when investigating pairwise convergence of output in panel data sets of n countries, n(n-1)/2 tests are performed. We propose to control the false discovery rate (FDR) so as not to erroneously declare variables significant in these multiple testing situations only because of the large number of tests performed. Doing so, we provide a simple new way to robustly select variables in economic growth models. We find that few other variables beyond the initial GDP level are needed to explain growth. We also show that convergence in panels of per capita output using a time series definition with the necessary condition of no unit root in the log per-capita output gap of two economies does not appear to hold.
Subjects:Growth Empirics
Panel Data
Multiple Testing
Convergence
Bootstrap
JEL:O47
C12
C33
Document Type:Conference Paper
Appears in Collections:Jahrestagung des Vereins für Socialpolitik 2010: Ökonomie der Familie

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