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Feasible Estimation in Cointegrated Panels

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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
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    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. repec:cup:etheor:v:10:y:1994:i:1:p:95-115 is not listed on IDEAS
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.

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    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

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