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kpsstest: A command that implements the Kwiatkowski, Phillips, Schmidt, and Shin test with sample-specific critical values and reports p-values

Author

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  • Ali Kagalwala

    (Texas A&M University)

Abstract

Commonly used unit-root tests in time-series analysis—such as the Dickey–Fuller and Phillips–Perron tests—use a null hypothesis that the series con- tains a unit root. Such tests have low power against the alternative—when a time series is near integrated or highly autoregressive—implying that they do poorly in distinguishing such a series from having a unit root. Kwiatkowski et al. (1992, Jour- nal of Econometrics 54: 159–178) introduced the Kwiatkowski, Phillips, Schmidt, and Shin test, in which the null hypothesis is that the series is stationary, to deal with this problem. One shortcoming of the presently available Kwiatkowski, Phillips, Schmidt, and Shin test in Stata is that it uses asymptotic critical values regardless of the sample size. This poses a problem in that researchers—especially social scientists—are often presented with short time series. I introduce kpsstest, a command that extends the previous implementation by including an option for a zero-mean-stationary null hypothesis, generating sample- and test-specific critical values, and reporting appropriate p-values.

Suggested Citation

  • Ali Kagalwala, 2022. "kpsstest: A command that implements the Kwiatkowski, Phillips, Schmidt, and Shin test with sample-specific critical values and reports p-values," Stata Journal, StataCorp LP, vol. 22(2), pages 269-292, June.
  • Handle: RePEc:tsj:stataj:v:22:y:2022:i:2:p:269-292
    DOI: 10.1177/1536867X221106371
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    1. Aleksandra Górna & Alicja Szabelska-Beręsewicz & Marek Wieruszewski & Monika Starosta-Grala & Zygmunt Stanula & Anna Kożuch & Krzysztof Adamowicz, 2023. "Predicting Post-Production Biomass Prices," Energies, MDPI, vol. 16(8), pages 1-16, April.

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