Generalizing the Bayesian Vector Autoregression Approach for Regional Interindustry Employment Forecasting

Mark Partridge and Dan Rickman

Journal of Business & Economic Statistics, 1998, vol. 16, issue 1, 62-72

Abstract: The Bayesian vector autoregression (BVAR) employment-forecast approach is generalized using data for the state of Georgia. This study advances previous regional BVAR approaches by (1) incorporating regional input-output coefficients, (2) using the coefficients both to specify the prior means in one model and to weight the variances of a Minnesota-type prior in a second model, and (3) including final-demand effects and links to national and world economies. Out-of-sample forecasts produced by the generalized BVAR models are compared to forecasts produced from an autoregressive model, an unconstrained VAR model, and a Minnesota BVAR model.

Date: 1998
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Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:16:y:1998:i:1:p:62-72

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