TY - JOUR
T1 - Response surface models for OLS and GLS detrending-based unit-root tests in nonlinear estar models
AU - Otero, Jesús
AU - Smith, Jeremy
PY - 2017/1/1
Y1 - 2017/1/1
N2 - In this article, we calculate response surface models for a large range of quantiles of the Kapetanios, Shin, and Snell (2003, Journal of Econometrics 112: 359–379) and Kapetanios and Shin (2008, Economics Letters 100: 377–380) tests for the null hypothesis of a unit root against the alternative—that the series of interest follows a globally stationary exponential smooth transition autoregressive process. The response surface models allow estimation of finite-sample critical values and approximate p-values for different combinations of the number of observations, T, and the lag order in the test regression, p. The latter can be either specified by the user or optimally selected using a data-dependent procedure. We present the new commands kssur and ksur and illustrate their use with an empirical example.
AB - In this article, we calculate response surface models for a large range of quantiles of the Kapetanios, Shin, and Snell (2003, Journal of Econometrics 112: 359–379) and Kapetanios and Shin (2008, Economics Letters 100: 377–380) tests for the null hypothesis of a unit root against the alternative—that the series of interest follows a globally stationary exponential smooth transition autoregressive process. The response surface models allow estimation of finite-sample critical values and approximate p-values for different combinations of the number of observations, T, and the lag order in the test regression, p. The latter can be either specified by the user or optimally selected using a data-dependent procedure. We present the new commands kssur and ksur and illustrate their use with an empirical example.
UR - https://www.scopus.com/pages/publications/85029837682
UR - https://www.scopus.com/pages/publications/85029837682#tab=citedBy
U2 - 10.1177/1536867X1701700310
DO - 10.1177/1536867X1701700310
M3 - Research Article
AN - SCOPUS:85029837682
SN - 1536-867X
VL - 17
SP - 704
EP - 722
JO - Stata Journal
JF - Stata Journal
IS - 3
ER -