System Estimation of Panel Data Models under Long-Range Dependence

Yunus Emre Ergemen ()
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Yunus Emre Ergemen: Aarhus University and CREATES, Postal: Department of Economics and Business Economics, Fuglesangs Allé 4, 8210 Aarhus V, Denmark

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: A general dynamic panel data model is considered that incorporates individual and interactive fixed effects allowing for contemporaneous correlation in model innovations. The model accommodates general stationary or nonstationary long-range dependence through interactive fixed effects and innovations, removing the necessity to perform a priori unit-root or stationarity testing. Moreover, persistence in innovations and interactive fixed effects allows for cointegration; innovations can also have vector-autoregressive dynamics; deterministic trends can be featured. Estimations are performed using conditional-sum-of-squares criteria based on projected series by which latent characteristics are proxied. Resulting estimates are consistent and asymptotically normal at standard parametric rates. A simulation study provides reliability on the estimation method. The method is then applied to the long-run relationship between debt and GDP.

Keywords: Long memory; factor models; panel data; endogeneity; fixed effects; debt and GDP (search for similar items in EconPapers)
JEL-codes: C32 C33 (search for similar items in EconPapers)
Pages: 47
Date: 2016-01-13
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (3)

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