Long-Run Effects in Large Heterogenous Panel Data Models with Cross-Sectionally Correlated Errors

46 Pages Posted: 17 Aug 2015

See all articles by Alexander Chudik

Alexander Chudik

Federal Reserve Banks - Federal Reserve Bank of Dallas

Kamiar Mohaddes

University of Cambridge - Judge Business School; University of Cambridge - King's College, Cambridge

M. Hashem Pesaran

University of Southern California - Department of Economics

Mehdi Raissi

International Monetary Fund (IMF) - Fiscal Affairs Department

Multiple version iconThere are 2 versions of this paper

Date Written: 2015-01-01

Abstract

This paper develops a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in large dynamic heterogeneous panel data models with cross-sectionally dependent errors. The asymptotic distribution of the CS-DL estimator is derived under coefficient heterogeneity in the case where the time dimension (T) and the crosssection dimension (N) are both large. The CS-DL approach is compared with more standard panel data estimators that are based on autoregressive distributed lag (ARDL) specifications. It is shown that unlike the ARDL type estimator, the CS-DL estimator is robust to misspecification of dynamics and error serial correlation. The theoretical results are illustrated with small sample evidence obtained by means of Monte Carlo simulations, which suggest that the performance of the CS-DL approach is often superior to the alternative panel ARDL estimates particularly when T is not too large and lies in the range of 30≤T

JEL Classification: C23

Suggested Citation

Chudik, Alexander and Mohaddes, Kamiar and Pesaran, M. Hashem and Raissi, Mehdi, Long-Run Effects in Large Heterogenous Panel Data Models with Cross-Sectionally Correlated Errors (2015-01-01). Globalization and Monetary Policy Institute Working Paper No. 223, Available at SSRN: https://ssrn.com/abstract=2643949 or http://dx.doi.org/10.24149/gwp223

Alexander Chudik (Contact Author)

Federal Reserve Banks - Federal Reserve Bank of Dallas ( email )

2200 North Pearl Street
PO Box 655906
Dallas, TX 75265-5906
United States

Kamiar Mohaddes

University of Cambridge - Judge Business School ( email )

Trumpington Street
Cambridge, CB2 1AG
United Kingdom
+44 (0)1223 766933 (Phone)

HOME PAGE: http://https://www.mohaddes.org/

University of Cambridge - King's College, Cambridge ( email )

King's Parade
Cambridge, CB2 1ST
United Kingdom
+44 (0)1223 766933 (Phone)

HOME PAGE: http://https://www.mohaddes.org/

M. Hashem Pesaran

University of Southern California - Department of Economics ( email )

3620 South Vermont Ave. Kaprielian (KAP) Hall 300
Los Angeles, CA 90089
United States

Mehdi Raissi

International Monetary Fund (IMF) - Fiscal Affairs Department ( email )

700 19th Street, NW
Washington, DC 20431
United States

HOME PAGE: http://https://sites.google.com/site/mehdiraissi/

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