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Response surface models for OLS and GLS detrending-based unit-root tests in nonlinear ESTAR models

Author

Listed:
  • Jesús Otero

    (Universidad del Rosario)

  • Jeremy Smith

    (University of Warwick)

Abstract

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 ob- servations, 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.

Suggested Citation

  • Jesús Otero & Jeremy Smith, 2017. "Response surface models for OLS and GLS detrending-based unit-root tests in nonlinear ESTAR models," Stata Journal, StataCorp LP, vol. 17(3), pages 704-722, September.
    • Handle: RePEc:tsj:stataj:y:17:y:2017:i:3:p:704-722
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    Citations

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    Cited by:

    1. Huthaifa Alqaralleh & Ahmad Al-Majali & Abeer Alsarayrh, 2021. "Analyzing the Dynamics Between Macroeconomic Variables and the Stock Indexes of Emerging Markets, Using Non-linear Methods," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(3), pages 193-204, May.
    2. Mishra, Bibhuti Ranjan & Pradhan, Ashis Kumar & Tiwari, Aviral Kumar & Shahbaz, Muhammad, 2019. "The dynamic causality between gold and silver prices in India: Evidence using time-varying and non-linear approaches," Resources Policy, Elsevier, vol. 62(C), pages 66-76.
    3. Mohammad Ajmal Hameed & Mohammad Mafizur Rahman & Rasheda Khanam, 2024. "Asymmetric effects of long-term war on human resource development in Af…ghanistan: evidence from NARDL approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(5), pages 4807-4832, October.
    4. Clement Olalekan Olaniyi & James Temitope Dada & Nicholas Mbaya Odhiambo & Xuan Vinh Vo, 2023. "Modelling asymmetric structure in the finance-poverty nexus: empirical insights from an emerging market economy," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 453-487, February.
    5. Sebastian Kripfganz & Daniel C. Schneider, 2020. "Response Surface Regressions for Critical Value Bounds and Approximate p‐values in Equilibrium Correction Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1456-1481, December.
    6. Dulal Chandra Pattak & Farian Tahrim & Mahdi Salehi & Liton Chandra Voumik & Salma Akter & Mohammad Ridwan & Beata Sadowska & Grzegorz Zimon, 2023. "The Driving Factors of Italy’s CO 2 Emissions Based on the STIRPAT Model: ARDL, FMOLS, DOLS, and CCR Approaches," Energies, MDPI, vol. 16(15), pages 1-21, August.
    7. Christopher A. Hartwell, 2021. "Market Behavior in the Face of Political Violence: Evidence from Tsarist Russia," JRFM, MDPI, vol. 14(9), pages 1-13, September.
    8. Khanday, Ishfaq Nazir & Tarique, Md., 2023. "Does income inequality respond asymmetrically to financial development? Evidence from India using asymmetric cointegration and causality tests," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).

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