Estimating Ipat Models Using Panel Data

31 Pages Posted: 15 Jun 2023

See all articles by Tobias Eibinger

Tobias Eibinger

University of Graz

Beate Deixelberger

University of Graz

Hans Manner

University of Graz

Abstract

This paper addresses econometric challenges arising in panel data analyses related to IPAT (environmental Impact of Population, Affluence and Technology) models. Panel data in this context is often characterized by a large-N and large-T structure. This poses specific econometric complexities due to nonstationarity and cross-sectional error correlation, 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 complexities.

Keywords: Nonstationary panel data, Cross-sectional dependence, Panel cointegration, GHG emissions, IPAT, Common correlated effects

Suggested Citation

Eibinger, Tobias and Deixelberger, Beate and Manner, Hans, Estimating Ipat Models Using Panel Data. Available at SSRN: https://ssrn.com/abstract=4479922 or http://dx.doi.org/10.2139/ssrn.4479922

Tobias Eibinger (Contact Author)

University of Graz ( email )

Universitaetsstrasse 15 / FE
A-8010 Graz, 8010
Austria

Beate Deixelberger

University of Graz ( email )

Universitaetsstrasse 15 / FE
A-8010 Graz, 8010
Austria

Hans Manner

University of Graz ( email )

Universitaetsstrasse 15 / FE
A-8010 Graz, 8010
Austria

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
39
Abstract Views
239
PlumX Metrics