IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v219y2022ics0165176522002968.html
   My bibliography  Save this article

Quantile unit root inference for panel data with common shocks

Author

Listed:
  • Yang, Jisheng
  • Wei, Jinbao
  • Cai, Biqing

Abstract

This paper proposes new quantile unit root tests for panel data with common shocks, whose critical values can be simulated based on our asymptotic theory. The Monte Carlo simulation results indicate that our tests perform well in finite sample. An application for real effective exchange rates (REERs) suggests that the Purchasing Power Parity (PPP) hypothesis holds for higher quantiles but does not hold for lower ones, and the asymmetric dynamics of REERs provide a plausible explanation for the PPP puzzle.

Suggested Citation

  • Yang, Jisheng & Wei, Jinbao & Cai, Biqing, 2022. "Quantile unit root inference for panel data with common shocks," Economics Letters, Elsevier, vol. 219(C).
    • Handle: RePEc:eee:ecolet:v:219:y:2022:i:c:s0165176522002968
    DOI: 10.1016/j.econlet.2022.110809
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176522002968
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2022.110809?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Matthew Harding & Carlos Lamarche & M. Hashem Pesaran, 2020. "Common correlated effects estimation of heterogeneous dynamic panel quantile regression models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 294-314, April.
    2. Nikolaou, Kleopatra, 2008. "The behaviour of the real exchange rate: Evidence from regression quantiles," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 664-679, May.
    3. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    4. Galvao Jr., Antonio F., 2009. "Unit root quantile autoregression testing using covariates," Journal of Econometrics, Elsevier, vol. 152(2), pages 165-178, October.
    5. Pesaran, M. Hashem & Vanessa Smith, L. & Yamagata, Takashi, 2013. "Panel unit root tests in the presence of a multifactor error structure," Journal of Econometrics, Elsevier, vol. 175(2), pages 94-115.
    6. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    7. Lundbergh, Stefan & Terasvirta, Timo, 2006. "A time series model for an exchange rate in a target zone with applications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 579-609.
    8. Roger Koenker & Zhijie Xiao, 2004. "Unit Root Quantile Autoregression Inference," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 775-787, January.
    9. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    10. Maddala, G S & Wu, Shaowen, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 631-652, Special I.
    11. Lee, Hsiu-Yun & Lai, Hung-Pin, 2011. "A structural threshold model of the exchange rate under optimal intervention," Journal of International Money and Finance, Elsevier, vol. 30(6), pages 931-946, October.
    12. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
    13. Haiqi Li & Sung Y. Park, 2018. "Testing for a unit root in a nonlinear quantile autoregression framework," Econometric Reviews, Taylor & Francis Journals, vol. 37(8), pages 867-892, September.
    14. Li, Haiqi & Zheng, Chaowen, 2018. "Unit root quantile autoregression testing with smooth structural changes," Finance Research Letters, Elsevier, vol. 25(C), pages 83-89.
    15. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cem Ertur & Antonio Musolesi, 2017. "Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 477-503, April.
    2. Acikgoz, Senay & Ben Ali, Mohamed Sami, 2019. "Where does economic growth in the Middle Eastern and North African countries come from?," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 172-183.
    3. Tolga Omay & Mübariz Hasanov & Yongcheol Shin, 2018. "Testing for Unit Roots in Dynamic Panels with Smooth Breaks and Cross-Sectionally Dependent Errors," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 167-193, June.
    4. Dina Azhgaliyeva, 2013. "What Makes Oil Revenue Funds Effective," International Conference on Energy, Regional Integration and Socio-economic Development 6023, EcoMod.
    5. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2022. "Which are the long-run determinants of US outward FDI? Evidence using large long-memory panels," Working Papers 2022.08, International Network for Economic Research - INFER.
    6. Chakraborty, Saptorshee Kanto & Mazzanti, Massimiliano, 2020. "Energy intensity and green energy innovation: Checking heterogeneous country effects in the OECD," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 328-343.
    7. Asta Ndongo & Ibrahima Thione Diop, 2021. "Economic and Monetary Integration in ECOWAS Countries: A Panel VAR Approach to Identify Macroeconomic Shocks," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 7(2), pages 61-87, December.
    8. Chi Lau & Ka Fung & Lee Pugalis, 2014. "Is health care expenditure across Europe converging? Findings from the application of a nonlinear panel unit root test," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 4(2), pages 137-156, December.
    9. Ayhan KULOĞLU & Eyyup ECEVİT, 2017. "The Relationship Between Health Development Index And Financial Development Index: Evidence From High Income Countries," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 2(2), pages 83-95.
    10. Selien De Schryder and Gert Peersman, 2015. "The U.S. Dollar Exchange Rate and the Demand for Oil," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    11. Kristofer Månsson & Ghazi Shukur & Pär Sjölander, 2013. "Testing for panel unit roots in the presence of spatial dependency," Applied Economics, Taylor & Francis Journals, vol. 45(29), pages 4152-4159, October.
    12. Jaroslava Hlouskova & Martin Wagner, 2006. "The Performance of Panel Unit Root and Stationarity Tests: Results from a Large Scale Simulation Study," Econometric Reviews, Taylor & Francis Journals, vol. 25(1), pages 85-116.
    13. T. Gries & M. Redlin, 2020. "Trade and economic development: global causality and development- and openness-related heterogeneity," International Economics and Economic Policy, Springer, vol. 17(4), pages 923-944, October.
    14. Joakim Westerlund & Johan Blomquist, 2013. "A modified LLC panel unit root test of the PPP hypothesis," Empirical Economics, Springer, vol. 44(2), pages 833-860, April.
    15. Eleftherios Thalassinos & Marta Kadłubek & Le Minh Thong & Tran Van Hiep & Erginbay Ugurlu, 2022. "Managerial Issues Regarding the Role of Natural Gas in the Transition of Energy and the Impact of Natural Gas Consumption on the GDP of Selected Countries," Resources, MDPI, vol. 11(5), pages 1-22, April.
    16. Pedroni, Peter L. & Vogelsang, Timothy J. & Wagner, Martin & Westerlund, Joakim, 2015. "Nonparametric rank tests for non-stationary panels," Journal of Econometrics, Elsevier, vol. 185(2), pages 378-391.
    17. Djaballah Mustapha, 2020. "The Relationship Between the Financial Innovation and the Money Supply: Empirical Study on the Maghreb Countries," Economics and Business, Sciendo, vol. 34(1), pages 168-178, February.
    18. Valérie Mignon & Christophe Hurlin, 2005. "Une synthèse des tests de racine unitaire sur données de panel," Économie et Prévision, Programme National Persée, vol. 169(3), pages 253-294.
    19. Fateh Belaïd, Sabri Boubaker, Rajwane Kafrouni, 2020. "Carbon emissions, income inequality and environmental degradation: the case of Mediterranean countries," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 17(1), pages 73-102, June.
    20. Nazlioglu, Saban & Karul, Cagin, 2017. "A panel stationarity test with gradual structural shifts: Re-investigate the international commodity price shocks," Economic Modelling, Elsevier, vol. 61(C), pages 181-192.

    More about this item

    Keywords

    Common shocks; Panel data; Purchasing power parity; Quantile regression; Unit root test;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • F31 - International Economics - - International Finance - - - Foreign Exchange

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolet:v:219:y:2022:i:c:s0165176522002968. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.