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The Role of "Leads" in the Dynamic OLS Estimation of Cointegrating Regression Models

Author

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  • Kazuhiko Hayakawa
  • Eiji Kurozumi

Abstract

In this paper, we consider the role of "leads" of the first difference of integrated variables in the dynamic OLS estimation of cointegrating regression models. We demonstrate that the role of leads is related to the concept of Granger causality and that in some cases leads are unnecessary in the dynamic OLS estimation of cointegrating regression models. Based on a Monte Carlo simulation, we find that the dynamic OLS estimator without leads substantially outperforms that with leads and lags; we therefore recommend testing for Granger noncausality before estimating models.

Suggested Citation

  • Kazuhiko Hayakawa & Eiji Kurozumi, 2006. "The Role of "Leads" in the Dynamic OLS Estimation of Cointegrating Regression Models," Hi-Stat Discussion Paper Series d06-194, Institute of Economic Research, Hitotsubashi University.
  • Handle: RePEc:hst:hstdps:d06-194
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    References listed on IDEAS

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    1. Park, Joon Y, 1992. "Canonical Cointegrating Regressions," Econometrica, Econometric Society, vol. 60(1), pages 119-143, January.
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    3. Peter C. B. Phillips & Mico Loretan, 1991. "Estimating Long-run Economic Equilibria," Review of Economic Studies, Oxford University Press, 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. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    6. Saikkonen, Pentti, 1991. "Asymptotically Efficient Estimation of Cointegration Regressions," Econometric Theory, Cambridge University Press, vol. 7(01), pages 1-21, March.
    7. Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-552, September.
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    Cited by:

    1. Laura Policardo & Lionello F. Punzo & Edgar J. Sánchez Carrera, 2016. "Brazil and China: Two Routes of Economic Development?," Review of Development Economics, Wiley Blackwell, vol. 20(3), pages 651-669, August.
    2. Bu, Ruijun & Cheng, Jie & Hadri, Kaddour, 2016. "Reducible diffusions with time-varying transformations with application to short-term interest rates," Economic Modelling, Elsevier, pages 266-277.
    3. Hadri, Kaddour & Kurozumi, Eiji & Rao, Yao, 2013. "Novel Panel Cointegration Tests Emending for Cross-Section Dependence with N Fixed," Discussion Papers 2013-12, Graduate School of Economics, Hitotsubashi University.
    4. Akama, Erick, 2016. "International tourism receipts and economic growth in Kenya 1980 -2013," MPRA Paper 78110, University Library of Munich, Germany.
    5. Adom, Philip Kofi, 2017. "The long-run price sensitivity dynamics of industrial and residential electricity demand: The impact of deregulating electricity prices," Energy Economics, Elsevier, vol. 62(C), pages 43-60.
    6. Risso, W. Adrián & Punzo, Lionello F. & Carrera, Edgar J. Sánchez, 2013. "Economic growth and income distribution in Mexico: A cointegration exercise," Economic Modelling, Elsevier, vol. 35(C), pages 708-714.
    7. 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.
    8. James J. Forest & Paul Turner, 2013. "Alternative estimators of cointegrating parameters in models with nonstationary data: an application to US export demand," Applied Economics, Taylor & Francis Journals, vol. 45(5), pages 629-636, February.
    9. Skrobotov Anton & Eiji Kurozumi, 2016. "Confidence Sets for the Break Date in Cointegrating Regressions," Working Papers wpaper-2016-268, Gaidar Institute for Economic Policy, revised 2016.
    10. Hasanov, Fakhri J. & Bulut, Cihan & Suleymanov, Elchin, 2016. "Do population age groups matter in the energy use of the oil-exporting countries?," Economic Modelling, Elsevier, vol. 54(C), pages 82-99.

    More about this item

    Keywords

    Cointegration; dynamic ordinary least squares estimator; Granger causality;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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