IDEAS home Printed from https://ideas.repec.org/p/hhs/lunewp/2003_012.html
   My bibliography  Save this paper

Feasible Estimation in Cointegrated Panels

Author

Listed:

Abstract

In this paper we propose a simple procedure for data dependent determination of the number of lags and leads to use in feasible estimation of cointegrated panel regressions. Results from Monte Carlo simulations suggests that the feasible estimators considered enjoys excellent precision in terms of root mean squared error and reasonable power with effective size hovering close to the nominal level. The good performance of the feasible estimators is verified empirically through an application to the long run money demand.

Suggested Citation

  • Westerlund, Joakim, 2003. "Feasible Estimation in Cointegrated Panels," Working Papers 2003:12, Lund University, Department of Economics, revised 10 Nov 2003.
    • Handle: RePEc:hhs:lunewp:2003_012
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    as
    1. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220, National Bureau of Economic Research, Inc.
    2. Nelson C. Mark & Masao Ogaki & Donggyu Sul, 2005. "Dynamic Seemingly Unrelated Cointegrating Regressions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 797-820.
    3. Mark, Nelson & Sul, Donggyu, 2002. "Panel Dynamic OLS Cointegration Vector Estimation and Long-Run Money Demand," Working Papers 172, Department of Economics, The University of Auckland.
    4. Nelson C. Mark & Donggyu Sul, 2003. "Cointegration Vector Estimation by Panel DOLS and Long‐run Money Demand," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(5), pages 655-680, December.
    5. repec:cup:etheor:v:10:y:1994:i:1:p:95-115 is not listed on IDEAS
    6. Donggyu Sul & Peter C. B. Phillips & Chi‐Young Choi, 2005. "Prewhitening Bias in HAC Estimation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(4), pages 517-546, August.
    7. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-966, July.
    8. Shin, Yongcheol, 1994. "A Residual-Based Test of the Null of Cointegration Against the Alternative of No Cointegration," Econometric Theory, Cambridge University Press, vol. 10(1), pages 91-115, March.
    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. Christian Dreger & Hans-Eggert Reimers & Barbara Roffia, 2007. "Long-Run Money Demand in the New EU Member States with Exchange Rate Effects," Eastern European Economics, Taylor & Francis Journals, vol. 45(2), pages 75-94, April.
    2. José M. Alonso & Judith Clifton & Daniel Díaz-Fuentes, 2015. "Did New Public Management Matter? An empirical analysis of the outsourcing and decentralization effects on public sector size," Public Management Review, Taylor & Francis Journals, vol. 17(5), pages 643-660, May.
    3. Dreger, C. & Reimers, H.E., 2005. "Health Care Expenditures in OECD Countries: A Panel Unit Root and Cointegration Analysis," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(2), pages 5-20.

    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. Matteo Mogliani, 2010. "Residual-based tests for cointegration and multiple deterministic structural breaks: A Monte Carlo study," Working Papers halshs-00564897, HAL.
    2. Chi-Young Choi & Ling Hu & Masao Ogaki, 2005. "Structural Spurious Regressions and A Hausman-type Cointegration Test," RCER Working Papers 517, University of Rochester - Center for Economic Research (RCER).
    3. Gerdtham, Ulf-G. & Lothgren, Mickael, 2000. "On stationarity and cointegration of international health expenditure and GDP," Journal of Health Economics, Elsevier, vol. 19(4), pages 461-475, July.
    4. Breitung, Jörg & Pesaran, Mohammad Hashem, 2005. "Unit roots and cointegration in panels," Discussion Paper Series 1: Economic Studies 2005,42, Deutsche Bundesbank.
    5. Joëts, Marc & Mignon, Valérie, 2012. "On the link between forward energy prices: A nonlinear panel cointegration approach," Energy Economics, Elsevier, vol. 34(4), pages 1170-1175.
    6. Choi, Chi-Young & Hu, Ling & Ogaki, Masao, 2008. "Robust estimation for structural spurious regressions and a Hausman-type cointegration test," Journal of Econometrics, Elsevier, vol. 142(1), pages 327-351, January.
    7. Christis Katsouris, 2023. "Limit Theory under Network Dependence and Nonstationarity," Papers 2308.01418, arXiv.org, revised Aug 2023.
    8. Vasco Gabriel, 2003. "Tests for the Null Hypothesis of Cointegration: A Monte Carlo Comparison," Econometric Reviews, Taylor & Francis Journals, vol. 22(4), pages 411-435.
    9. Valérie Mignon & Christophe Hurlin, 2007. "Une synthèse des tests de cointégration sur données de panel," Économie et Prévision, Programme National Persée, vol. 180(4), pages 241-265.
    10. Masakatsu Okubo, 2011. "The Intertemporal Elasticity of Substitution: An Analysis Based on Japanese Data," Economica, London School of Economics and Political Science, vol. 78(310), pages 367-390, April.
    11. Frauke Dobnik, 2013. "Long-run money demand in OECD countries: what role do common factors play?," Empirical Economics, Springer, vol. 45(1), pages 89-113, August.
    12. Campo Robledo, Jacobo, 2011. "Sostenibilidad fiscal: una aproximación con datos panel para 8 países Latinoaméricanos [Fiscal sustainability: A data panel approach for eight Latin American countries]," MPRA Paper 33091, University Library of Munich, Germany.
    13. Rapach, David E. & Wohar, Mark E., 2004. "Testing the monetary model of exchange rate determination: a closer look at panels," Journal of International Money and Finance, Elsevier, vol. 23(6), pages 867-895, October.
    14. Muñoz, Sònia, 2004. "Real effects of regional house prices: dynamic panel estimation with heterogeneity," LSE Research Online Documents on Economics 24704, London School of Economics and Political Science, LSE Library.
    15. Ana Iregui & Jesús Otero, 2011. "Testing the law of one price in food markets: evidence for Colombia using disaggregated data," Empirical Economics, Springer, vol. 40(2), pages 269-284, April.
    16. Fernando Arias & David Delgado & Daniel Parra & Hernán Rincón-Castro, 2016. "Gross Capital Flows and their long-term Determinants for Developing Economies: A Panel Co-integration Approach," Borradores de Economia 932, Banco de la Republica de Colombia.
    17. Kuo, Biing-Shen, 1998. "Test for partial parameter instability in regressions with I(1) processes," Journal of Econometrics, Elsevier, vol. 86(2), pages 337-368, June.
    18. Robert A. Amano & Simon van Norden, 1995. "Unit Root Tests and the Burden of Proof," Econometrics 9502005, University Library of Munich, Germany.
    19. Holly, Sean & Pesaran, M. Hashem & Yamagata, Takashi, 2010. "A spatio-temporal model of house prices in the USA," Journal of Econometrics, Elsevier, vol. 158(1), pages 160-173, September.
    20. Frauke Dobnik, 2011. "OLong-run Money Demand in OECD Countries – Cross-Member Cointegration," Ruhr Economic Papers 0237, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.

    More about this item

    Keywords

    Panel Cointegration Estimation; Monte Carlo Simulation;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

    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:hhs:lunewp:2003_012. 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: Iker Arregui Alegria (email available below). General contact details of provider: https://edirc.repec.org/data/delunse.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.