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Estimating Short and Long Run Relationships: A Guide to the Applied Economist

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  • Bhaskara Rao

    (University of the South Pacific)

Abstract

Many applied economists face problems in selecting an appropriate technique to estimate short and long run relationships with the time series methods. This paper reviews three alternative approaches viz., general to specific (GETS), vector autoregressions (VAR) and the vector error correction models (VECM). As in other methodological controversies, definite answers are difficult. It is suggested that if these techniques are seen as tools to summarize data, as in Smith (2000), often there may be only minor differences in their estimates. Therefore a computationally attractive technique is likely to be popular.

Suggested Citation

  • Bhaskara Rao, 2005. "Estimating Short and Long Run Relationships: A Guide to the Applied Economist," Econometrics 0508013, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpem:0508013
    Note: Type of Document - pdf; pages: 28. Useful to the applied economists.
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    References listed on IDEAS

    as
    1. Kevin D. Hoover & Stephen J. Perez, 1999. "Data mining reconsidered: encompassing and the general-to-specific approach to specification search," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 167-191.
    2. Pesaran, M.H. & Shin, Y., 1995. "An Autoregressive Distributed Lag Modelling Approach to Cointegration Analysis," Cambridge Working Papers in Economics 9514, Faculty of Economics, University of Cambridge.
    3. Peter C. B. Phillips & Bruce E. Hansen, 1990. "Statistical Inference in Instrumental Variables Regression with I(1) Processes," Review of Economic Studies, Oxford University Press, vol. 57(1), pages 99-125.
    4. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    5. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    6. Mohsen Bahmani-Oskooee & Hafez Rehman, 2005. "Stability of the money demand function in Asian developing countries," Applied Economics, Taylor & Francis Journals, vol. 37(7), pages 773-792.
    7. Alogoskoufis, George & Smith, Ron, 1991. "On Error Correction Models: Specification, Interpretation, Estimation," Journal of Economic Surveys, Wiley Blackwell, vol. 5(1), pages 97-128.
    8. Hendry, David F. & Pagan, Adrian R. & Sargan, J.Denis, 1984. "Dynamic specification," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 18, pages 1023-1100, Elsevier.
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    10. 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.
    11. Harvey, Andrew, 1997. "Trends, Cycles and Autoregressions," Economic Journal, Royal Economic Society, vol. 107(440), pages 192-201, January.
    12. Pesaran, M.H. & Smith, R., 1992. "The Interaction Between Theory and Observation in Economics," Cambridge Working Papers in Economics 9223, Faculty of Economics, University of Cambridge.
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    More about this item

    Keywords

    Var; Cointegration; General to Specific Approach;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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