Document Type

Working Paper

Date

Winter 2-2019

Keywords

Non-Stationary Panels, Time Trends, Serial Correlation, Wald Type Tests

Language

English

Disciplines

Economic Policy | Economics | Public Affairs, Public Policy and Public Administration

Description/Abstract

This paper studies testing of shifts in a time trend panel data model with serially correlated error component disturbances, without any prior knowledge of whether the error term is stationary or nonstationary. This is done in case the shift is known as well as unknown. Following Vogelsang (1997) in the time series literature, we propose a Wald type test statistic that uses a fixed effects feasible generalized least squares (FE-FGLS) estimator derived in Baltagi, et al. (2014). The proposed test has a Chi-square limiting distribution and is valid for both I (0) and I (1) errors. The finite sample size and power of this Wald test is investigated using Monte Carlo simulations.

ISSN

1525-3066

Additional Information

Working paper no. 213

Source

Local input

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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