IDEAS home Printed from https://ideas.repec.org/p/bdr/borrec/474.html
   My bibliography  Save this paper

Cointegration Vector Estimation By Dols For A Three-Dimensional Panel

Author

Listed:
  • Luis F. Melo
  • John J. León
  • Dagoberto Saboyá

Abstract

This paper extends the asymptotic results of the dynamic ordinary least squares (DOLS) cointegration vector estimator of Mark and Sul (2003) to a three-dimensional panel. We use a balanced panel of N and M lengths observed over T time periods. The cointegration vector is homogenous across individuals but we allow for individual heterogeneity using different short-run dynamics, individual-specific fixed effects and individual-specific time trends. Both individual effects are considered for the first two dimensions. This paper was motivated by the three-dimensional panel cointegration analysis used to estimate the total factor productivity for Colombian regions and sectors during 1975-2000 by Iregui, Melo and Ramírez (2007). They used the methodology proposed by Marrocu, Paci and Pala (2000); however, hypothesis testing is not valid under this technique. The methodology we are currently proposing allows us to estimate the long-run relationship and to construct asymptotically valid test statistics in the 3D-panel context.

Suggested Citation

  • Luis F. Melo & John J. León & Dagoberto Saboyá, 2007. "Cointegration Vector Estimation By Dols For A Three-Dimensional Panel," Borradores de Economia 474, Banco de la Republica de Colombia.
    • Handle: RePEc:bdr:borrec:474
    DOI: 10.32468/be.474
    as

    Download full text from publisher

    File URL: https://doi.org/10.32468/be.474
    Download Restriction: no
    File URL: https://libkey.io/10.32468/be.474?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ana María Iregui B. & Luis Fernando Melo V. & María Teresa Ramírez G., 2007. "Productividad regional y sectorial en Colombia: un análisis utilizando datos de panel," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 25(53), pages 18-65, January.
    2. R. Pala & E. Marrocu & R. Paci, 2000. "Estimation of total factor productivity for regions and sectors in Italy. A panel cointegration approach," Working Paper CRENoS 200016, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    3. Peter C. B. Phillips & Mico Loretan, 1991. "Estimating Long-run Economic Equilibria," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 407-436.
    4. Stock, James H & Watson, Mark W, 1993. "A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems," Econometrica, Econometric Society, vol. 61(4), pages 783-820, July.
    5. Banerjee, Anindya, et al, 1986. "Exploring Equilibrium Relationships in Econometrics through Static Models: Some Monte Carlo Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 253-277, August.
    6. repec:cup:etheor:v:7:y:1991:i:1:p:1-21 is not listed on IDEAS
    7. Kremers, Jeroen J M & Ericsson, Neil R & Dolado, Juan J, 1992. "The Power of Cointegration Tests," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 325-348, August.
    8. Saikkonen, Pentti, 1991. "Asymptotically Efficient Estimation of Cointegration Regressions," Econometric Theory, Cambridge University Press, vol. 7(1), pages 1-21, March.
    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. Hasanov, Fakhri J. & Shannak, Sa'd, 2020. "Electricity incentives for agriculture in Saudi Arabia. Is that relevant to remove them?," Energy Policy, Elsevier, vol. 144(C).
    2. Denise Côté & Doug Hostland, 1996. "An Econometric Examination of the Trend Unemployment Rate in Canada," Staff Working Papers 96-7, Bank of Canada.
    3. Hussein, Khaled A., 1998. "International capital mobility in OECD countries: The Feldstein-Horioka 'puzzle' revisited," Economics Letters, Elsevier, vol. 59(2), pages 237-242, May.
    4. G. Everaert, 2007. "Estimating Long-Run Relationships between Observed Integrated Variables by Unobserved Component Methods," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/452, Ghent University, Faculty of Economics and Business Administration.
    5. Valerie Herzberg & George Kapetanios & Simon Price, 2003. "Import prices and exchange rate pass-through: theory and evidence from the United Kingdom," Bank of England working papers 182, Bank of England.
    6. Davidson, James, 2002. "A model of fractional cointegration, and tests for cointegration using the bootstrap," Journal of Econometrics, Elsevier, vol. 110(2), pages 187-212, October.
    7. Chen, Shyh-Wei & Shen, Chung-Hua, 2015. "Revisiting the Feldstein–Horioka puzzle with regime switching: New evidence from European countries," Economic Modelling, Elsevier, vol. 49(C), pages 260-269.
    8. Ho, Tsung-Wu, 2003. "A re-examination of the unbiasedness forward rate hypothesis using dynamic SUR model," The Quarterly Review of Economics and Finance, Elsevier, vol. 43(3), pages 542-559.
    9. Zivot, Eric, 2000. "The Power Of Single Equation Tests For Cointegration When The Cointegrating Vector Is Prespecified," Econometric Theory, Cambridge University Press, vol. 16(3), pages 407-439, June.
    10. Everaert Gerdie, 2011. "Estimation and Inference in Time Series with Omitted I(1) Variables," Journal of Time Series Econometrics, De Gruyter, vol. 2(2), pages 1-28, January.
    11. David Neto, 2023. "Penalized leads-and-lags cointegrating regression: a simulation study and two empirical applications," Empirical Economics, Springer, vol. 65(2), pages 949-971, August.
    12. Ekaterini Panopoulou, 2005. "A Resolution of the Fisher Effect Puzzle: A Comparison of Estimators," Money Macro and Finance (MMF) Research Group Conference 2005 18, Money Macro and Finance Research Group.
    13. Choi, In & Kurozumi, Eiji, 2012. "Model selection criteria for the leads-and-lags cointegrating regression," Journal of Econometrics, Elsevier, vol. 169(2), pages 224-238.
    14. Scheiblecker, Marcus, 2013. "Between cointegration and multicointegration: Modelling time series dynamics by cumulative error correction models," Economic Modelling, Elsevier, vol. 31(C), pages 511-517.
    15. Norah Al-Ballaa, 2005. "Test for cointegration based on two-stage least squares," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(7), pages 707-713.
    16. 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.
    17. Suzanne McCoskey & Chihwa Kao, 1997. "A Monte Carlo Comparison of Tests for Cointegration in Panel Data," Econometrics 9712002, University Library of Munich, Germany.
    18. Masih, Rumi & Masih, Abul M. M., 2000. "A Reassessment of Long-Run Elasticities of Japanese Import Demand," Journal of Policy Modeling, Elsevier, vol. 22(5), pages 625-639, September.
    19. Canarella, Giorgio & Miller, Stephen M., 2017. "Inflation targeting and inflation persistence: New evidence from fractional integration and cointegration," Journal of Economics and Business, Elsevier, vol. 92(C), pages 45-62.
    20. Clostermann, Jörg & Seitz, Franz, 2005. "Are bond markets really overpriced: The case of the US," Arbeitsberichte – Working Papers 11, Technische Hochschule Ingolstadt (THI).

    More about this item

    Keywords

    Cointegration; Dynamic OLS estimation; panel data in three dimensions.;
    All these keywords.

    JEL classification:

    • 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

    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:bdr:borrec:474. 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: Clorith Angélica Bahos Olivera (email available below). General contact details of provider: https://edirc.repec.org/data/brcgvco.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.