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A Bayesian forecasting approach to constructing regional input output based employment multipliers**An earlier version of this article was presented at the 47th North American Meetings of the RSAI, Chicago, IL. I would like to thank Stephan Weiler and three anonymous referees for helpful comments

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Listed:
  • Rickman, Dan S.

Abstract

A Bayesian mixed estimation framework is used to examine the forecast accuracy of alternative closures of an input output model for the Oklahoma economy. The closures correspond to textbook Type I and Type II multipliers, as well as variations of extended input output and Type IV multipliers. Relative forecast performance of the alternative IO model closures determines which set of multipliers should be used for impact analysis. The exercise reveals differences in forecast accuracy across alternative IO model closures, suggesting that before closures of a particular IO model are adopted, they should be tested for accuracy in predicting the time series data for the regional economy under scrutiny.

Suggested Citation

Handle: RePEc:eee:paresc:v:81:y:2002:i:4:p:483-498
DOI: 10.1111/j.1435-5597.2002.tb01245.x
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JEL classification:

  • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
  • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
  • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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