Monitoring Cointegrating Polynomial Regressions: Theory and Application to the Environmental Kuznets Curves for Carbon and Sulfur Dioxide Emissions

Knorre, Fabian; Wagner, Martin and Grupe, Maximilian (December 2020) Monitoring Cointegrating Polynomial Regressions: Theory and Application to the Environmental Kuznets Curves for Carbon and Sulfur Dioxide Emissions. IHS Working Paper Series 27, 53 p.

[img]
Preview
Text
ihs-working-paper-2020-knorre-wagner-grupe-monitoring-cointegrating-polynomial-regressions.pdf
Available under License Creative Commons Attribution.

Download (1MB) | Preview
[img] Other (not available to the public)
ua-wp27.pdf - Other
Restricted to Repository staff only

Download (818kB)

Abstract or Table of Contents

This paper develops residual-based monitoring procedures for cointegrating polynomial regressions, i.e., regression models including deterministic variables, integrated processes as well as integer powers of integrated processes as regressors. The regressors are allowed to be endogenous and the stationary errors are allowed to be serially correlated. We consider five variants of monitoring statistics and develop the results for three modified least squares estimators for the parameters of the CPRs. The simulations show that using the combination of self-normalization and a moving window leads to the best performance. We use the developed monitoring statistics to assess the structural stability of environmental Kuznets curves (EKCs) for both CO2 and SO2 emissions for twelve industrialized country since the first oil price shock.

Item Type: IHS Series
Keywords: Cointegrating Polynomial Regression, Environmental Kuznets Curve, Monitoring, Structural Change
Classification Codes (e.g. JEL): C22, C52, Q56
Research Units: Divisions > Former Research Units (until 2020) > Macroeconomics and Economic Policy
IHS general publications
Status: Published
Date Deposited: 08 Jan 2021 10:00
Last Modified: 08 Jan 2021 10:15
URI: https://irihs.ihs.ac.at/id/eprint/5586

Actions (login required)

View Item View Item