IDEAS home Printed from https://ideas.repec.org/p/lie/wpaper/91.html
   My bibliography  Save this paper

The Factor Analytical Approach in Trending Near Unit Root Panels

Author

Listed:
  • Milda Norkute

    (Bank of Lithuania, Vilnius University)

  • Joakim Westerlund

    (Lund University, Deakin University)

  • Ovidijus Stauskas

    (Lunk University)

Abstract

In this study, we re-visit the factor analytical (FA) approach for (near unit root) dynamic panel data models, whose asymptotic distribution has been shown to be normal and well centered at zero without the need for valid instruments or correction for bias. It is therefore very appealing. The question is: Does the appeal of FA, which so far has only been documented for fixed effects panels, extends to panels with incidental trends? This is an important question, because many persistent variables are trending. The answer turns out to be negative. In particular, while consistent, the asymptotic normality of FA breaks down when there is an exact unit root present, which limits its applicability.

Suggested Citation

  • Milda Norkute & Joakim Westerlund & Ovidijus Stauskas, 2021. "The Factor Analytical Approach in Trending Near Unit Root Panels," Bank of Lithuania Working Paper Series 91, Bank of Lithuania.
  • Handle: RePEc:lie:wpaper:91
    as

    Download full text from publisher

    File URL: https://www.lb.lt/uploads/publications/docs/32251_31978b95c71b0d6db64acfc1fc9d3164.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Andrews, Donald W. K., 1987. "Asymptotic Results for Generalized Wald Tests," Econometric Theory, Cambridge University Press, vol. 3(3), pages 348-358, June.
    2. Moon, Hyungsik R. & Phillips, Peter C.B., 2000. "Estimation Of Autoregressive Roots Near Unity Using Panel Data," Econometric Theory, Cambridge University Press, vol. 16(6), pages 927-997, December.
    3. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    4. Moon, Hyungsik Roger & Perron, Benoit & Phillips, Peter C.B., 2007. "Incidental trends and the power of panel unit root tests," Journal of Econometrics, Elsevier, vol. 141(2), pages 416-459, December.
    5. Moon, H.R.Hyungsik Roger & Perron, Benoit, 2004. "Testing for a unit root in panels with dynamic factors," Journal of Econometrics, Elsevier, vol. 122(1), pages 81-126, September.
    6. Hayakawa, Kazuhiko & Pesaran, M. Hashem, 2015. "Robust standard errors in transformed likelihood estimation of dynamic panel data models with cross-sectional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 188(1), pages 111-134.
    7. Hyungsik Roger Moon & Peter C. B. Phillips, 2004. "GMM Estimation of Autoregressive Roots Near Unity with Panel Data," Econometrica, Econometric Society, vol. 72(2), pages 467-522, March.
    8. Hyungsik R. Moon & Peter C. B. Phillip, 1999. "Maximum Likelihood Estimation in Panels with Incidental Trends," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 711-747, November.
    9. Westerlund, Joakim & Larsson, Rolf, 2015. "New tools for understanding the local asymptotic power of panel unit root tests," Journal of Econometrics, Elsevier, vol. 188(1), pages 59-93.
    10. Hyungsik R. Moon & Peter C.B. Phillips, 1999. "Maximum Likelihood Estimation in Panels with Incidental Trends," Cowles Foundation Discussion Papers 1246, Cowles Foundation for Research in Economics, Yale University.
    11. Jinyong Hahn & Guido Kuersteiner, 2002. "Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects when Both "n" and "T" Are Large," Econometrica, Econometric Society, vol. 70(4), pages 1639-1657, July.
    12. Hsiao, Cheng & Hashem Pesaran, M. & Kamil Tahmiscioglu, A., 2002. "Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods," Journal of Econometrics, Elsevier, vol. 109(1), pages 107-150, July.
    13. Peter C. B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Econometrica, Econometric Society, vol. 67(5), pages 1057-1112, September.
    14. Norkutė, Milda & Westerlund, Joakim, 2021. "The factor analytical approach in near unit root interactive effects panels," Journal of Econometrics, Elsevier, vol. 221(2), pages 569-590.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yanbo Liu & Peter C. B. Phillips & Jun Yu, 2023. "A Panel Clustering Approach To Analyzing Bubble Behavior," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(4), pages 1347-1395, November.
    2. Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
    3. Felix Chan & Les Oxley, 2023. "A pulse check on recent developments in time series econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 3-6, February.
    4. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.

    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. Norkutė, Milda & Westerlund, Joakim, 2021. "The factor analytical approach in near unit root interactive effects panels," Journal of Econometrics, Elsevier, vol. 221(2), pages 569-590.
    2. Skrobotov, Anton (Скроботов, Антон) & Turuntseva, Marina (Турунцева, Марина), 2017. "Testing the Hypothesis of a Unit Root for Independent Panels [Тестирование Гипотезы О Наличии Единичного Корня Для Независимых Панелей]," Working Papers 021707, Russian Presidential Academy of National Economy and Public Administration.
    3. Erik Hjalmarsson, 2005. "Estimation of average local-to-unity roots in heterogenous panels," International Finance Discussion Papers 852, Board of Governors of the Federal Reserve System (U.S.).
    4. Seung C. Ahn & Gareth M. Thomas, 2023. "Likelihood-based inference for dynamic panel data models," Empirical Economics, Springer, vol. 64(6), pages 2859-2909, June.
    5. Westerlund, Joakim, 2015. "The effect of recursive detrending on panel unit root tests," Journal of Econometrics, Elsevier, vol. 185(2), pages 453-467.
    6. Phillips, Peter C.B. & Sul, Donggyu, 2007. "Bias in dynamic panel estimation with fixed effects, incidental trends and cross section dependence," Journal of Econometrics, Elsevier, vol. 137(1), pages 162-188, March.
    7. Moon, H.R.Hyungsik Roger & Perron, Benoit, 2004. "Testing for a unit root in panels with dynamic factors," Journal of Econometrics, Elsevier, vol. 122(1), pages 81-126, September.
    8. Hyungsik Roger Moon & Peter C. B. Phillips, 2004. "GMM Estimation of Autoregressive Roots Near Unity with Panel Data," Econometrica, Econometric Society, vol. 72(2), pages 467-522, March.
    9. Yanbo Liu & Peter C. B. Phillips & Jun Yu, 2023. "A Panel Clustering Approach To Analyzing Bubble Behavior," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(4), pages 1347-1395, November.
    10. Robinson, Peter M. & Velasco, Carlos, 2018. "Inference on trending panel data," Journal of Econometrics, Elsevier, vol. 206(2), pages 282-304.
    11. Joakim Westerlund & Jörg Breitung, 2013. "Lessons from a Decade of IPS and LLC," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 547-591, August.
    12. Westerlund, Joakim & Larsson, Rolf, 2015. "New tools for understanding the local asymptotic power of panel unit root tests," Journal of Econometrics, Elsevier, vol. 188(1), pages 59-93.
    13. Moon, Hyungsik Roger & Perron, Benoit & Phillips, Peter C.B., 2007. "Incidental trends and the power of panel unit root tests," Journal of Econometrics, Elsevier, vol. 141(2), pages 416-459, December.
    14. Hayakawa, Kazuhiko, 2016. "Improved GMM estimation of panel VAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 240-264.
    15. Bai, Jushan & Kao, Chihwa & Ng, Serena, 2009. "Panel cointegration with global stochastic trends," Journal of Econometrics, Elsevier, vol. 149(1), pages 82-99, April.
    16. Westerlund, Joakim & Breitung, Jörg, 2009. "Myths and Facts about Panel Unit Root Tests," Working Papers in Economics 380, University of Gothenburg, Department of Economics.
    17. Kruiniger, Hugo, 2009. "Gmm Estimation And Inference In Dynamic Panel Data Models With Persistent Data," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1348-1391, October.
    18. Westerlund, Joakim & Larsson, Rolf, 2012. "Testing for a unit root in a random coefficient panel data model," Journal of Econometrics, Elsevier, vol. 167(1), pages 254-273.
    19. Karavias, Yiannis & Tzavalis, Elias, 2012. "On the Local Power of Fixed T Panel Unit Root Tests with Serially Correlated Errors," MPRA Paper 43131, University Library of Munich, Germany.
    20. Yiannis Karavias & Elias Tzavalis, 2016. "Local Power of Fixed-T Panel Unit Root Tests With Serially Correlated Errors and Incidental Trends," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(2), pages 222-239, March.

    More about this item

    Keywords

    Dynamic panel data models; Unit root; Factor analytical method.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:lie:wpaper:91. 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: Aurelija Proskute (email available below). General contact details of provider: https://edirc.repec.org/data/lbanklt.html .

    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.