Advanced

Finite-sample distribution of a recursively mean-adjusted panel data unit root test

Jönsson, Kristian LU (2007) In Journal of Statistical Computation and Simulation 77(4). p.293-303
Abstract
In this paper, we investigate the finite-sample distribution of the recursively mean-adjusted panel data unit root test of Shin et al. [Shin, D. W., Kang, S. and Oh, M.-S., 2004, Recursive mean adjustment for panel unit root tests. Economics Letters, 84, 433-439.]. More precisely, we provide response surface parameters that can be used to calculate small-sample critical values for the test. Furthermore, we supply standardizing moments that can be used to calculate a test statistic that has an asymptotic standard normal distribution. The asymptotic standard normal distribution, which follows when the cross-sectional dimension increases, enables easy calculation of critical values and p-values. Hence, it is of interest to study how large the... (More)
In this paper, we investigate the finite-sample distribution of the recursively mean-adjusted panel data unit root test of Shin et al. [Shin, D. W., Kang, S. and Oh, M.-S., 2004, Recursive mean adjustment for panel unit root tests. Economics Letters, 84, 433-439.]. More precisely, we provide response surface parameters that can be used to calculate small-sample critical values for the test. Furthermore, we supply standardizing moments that can be used to calculate a test statistic that has an asymptotic standard normal distribution. The asymptotic standard normal distribution, which follows when the cross-sectional dimension increases, enables easy calculation of critical values and p-values. Hence, it is of interest to study how large the cross-sectional dimension has to be in order for the normal approximation to be valid for inference. By performing a Monte Carlo simulation, we find that the normal approximation works well, at conventional significance levels, even when the cross-sectional dimension is as small as 2. We also supply critical values and moments for the panel unit root test that can be used when the baseline model is augmented to account for serially correlated disturbances. Finally, we investigate the finite-sample size and power properties of the test and find that the test performs well even when disturbances display serial correlation. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
recursive mean adjustment, serial, Monte Carlo simulation, correlation, panel data, unit root test
in
Journal of Statistical Computation and Simulation
volume
77
issue
4
pages
293 - 303
publisher
Taylor & Francis
external identifiers
  • wos:000245077400002
  • scopus:33947432343
ISSN
1563-5163
DOI
10.1080/10629360600570988
language
English
LU publication?
yes
id
8fe26212-72c8-49f4-9675-8de22df7def0 (old id 671618)
date added to LUP
2007-12-12 16:27:16
date last changed
2017-01-01 07:05:23
@article{8fe26212-72c8-49f4-9675-8de22df7def0,
  abstract     = {In this paper, we investigate the finite-sample distribution of the recursively mean-adjusted panel data unit root test of Shin et al. [Shin, D. W., Kang, S. and Oh, M.-S., 2004, Recursive mean adjustment for panel unit root tests. Economics Letters, 84, 433-439.]. More precisely, we provide response surface parameters that can be used to calculate small-sample critical values for the test. Furthermore, we supply standardizing moments that can be used to calculate a test statistic that has an asymptotic standard normal distribution. The asymptotic standard normal distribution, which follows when the cross-sectional dimension increases, enables easy calculation of critical values and p-values. Hence, it is of interest to study how large the cross-sectional dimension has to be in order for the normal approximation to be valid for inference. By performing a Monte Carlo simulation, we find that the normal approximation works well, at conventional significance levels, even when the cross-sectional dimension is as small as 2. We also supply critical values and moments for the panel unit root test that can be used when the baseline model is augmented to account for serially correlated disturbances. Finally, we investigate the finite-sample size and power properties of the test and find that the test performs well even when disturbances display serial correlation.},
  author       = {Jönsson, Kristian},
  issn         = {1563-5163},
  keyword      = {recursive mean adjustment,serial,Monte Carlo simulation,correlation,panel data,unit root test},
  language     = {eng},
  number       = {4},
  pages        = {293--303},
  publisher    = {Taylor & Francis},
  series       = {Journal of Statistical Computation and Simulation},
  title        = {Finite-sample distribution of a recursively mean-adjusted panel data unit root test},
  url          = {http://dx.doi.org/10.1080/10629360600570988},
  volume       = {77},
  year         = {2007},
}