Estimating IPAT Models Using Panel Data

Tobias Eibinger (), Beate Deixelberger () and Hans Manner ()
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Tobias Eibinger: University of Graz, Austria
Beate Deixelberger: University of Graz, Austria
Hans Manner: University of Graz, Austria

No 2024-01, Graz Economics Papers from University of Graz, Department of Economics

Abstract: This paper addresses econometric challenges arising in panel data analyses related to IPAT (environmental Impact of Population, Affluence and Technology) models and other applications typically characterized by a large-N and large-T structure. This poses specific econometric complexities due to nonstationarity and cross-sectional error correlation, potentially affecting consistent estimation and valid inference. We provide a concise overview of these complications and how to deal with these with appropriate tests and models. Moreover, we apply these insights to empirical examples based on the IPAT identity, offering insights into the robustness of previous findings. Our results suggest that using standard panel techniques can lead to biased estimates, incorrect inference, and invalid model adequacy tests. This can potentially lead to flawed policy conclusions. We provide practical guidance to practitioners for navigating these econometric issues.

Keywords: IPAT models; Nonstationary panel data; Cross-sectional dependence; Panel cointegration; GHG emissions; Common correlated effects. (search for similar items in EconPapers)
JEL-codes: C18 C33 Q54 R49 (search for similar items in EconPapers)
Date: 2024-01
New Economics Papers: this item is included in nep-ecm and nep-env
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