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

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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)

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B. Bhaskara Rao Professor

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.

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Paper provided by EconWPA in its series Econometrics with number 0508013.

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Length: 28 pages
Date of creation: 13 Aug 2005
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Handle: RePEc:wpa:wuwpem:0508013

Note: Type of Document - pdf; pages: 28. Useful to the applied economists.
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Find related papers by JEL classification:
C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: 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

This paper has been announced in the following NEP Reports:

NEP-ALL-2005-11-09 (All new papers)
NEP-ECM-2005-11-09 (Econometrics)
NEP-ETS-2005-11-09 (Econometric Time Series)

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Other versions:
- 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.
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