A Simple Test for Dynamic Causality in Panel Data

Empirical Economics Letters, Vol. 2, No. 6, pp. 209-215, November 2003

7 Pages Posted: 18 Apr 2011 Last revised: 17 Nov 2015

See all articles by David Schimmelpfennig

David Schimmelpfennig

Science & Technology PPQ; Economic Research Service (ERS); USDA Economic Research Service

Colin Thirtle

Imperial College London - TH Huxley School of Environment, Earth Sciences & Engineering; University of Pretoria - Department of Agricultural Economics, Extension and Rural Development

Date Written: April 18, 2003

Abstract

A new panel data test for Granger causality is presented that can be applied to panels with more time series observations than cross-sections. Inconsistency in these models with lagged dependent variables and fixed effects is avoided by differencing and pooling the data. The joint significance tests are also non-standard. The result is a set of homogeneous coefficients, which compare favorably to results from seemingly unrelated regressions under common conditions.

Keywords: Panel Causality, Two-Stage Least Squares

JEL Classification: C33

Suggested Citation

Schimmelpfennig, David and Thirtle, Colin, A Simple Test for Dynamic Causality in Panel Data (April 18, 2003). Empirical Economics Letters, Vol. 2, No. 6, pp. 209-215, November 2003 , Available at SSRN: https://ssrn.com/abstract=1814243

David Schimmelpfennig (Contact Author)

Science & Technology PPQ ( email )

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Economic Research Service (ERS) ( email )

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USDA Economic Research Service ( email )

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Washington, DC 20024-3221
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Colin Thirtle

Imperial College London - TH Huxley School of Environment, Earth Sciences & Engineering ( email )

Prince Consort Road
London, SW7 2BP
United Kingdom

University of Pretoria - Department of Agricultural Economics, Extension and Rural Development

Pretoria 0002
South Africa

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