Forecasting Industry Employment for a Resource-Based Economy Using Bayesian Vector Autoregressive Models
AbstractBayesian vector autoregressive (BVAR) models are developed to forecast industry employment for a resource-based economy. Two different types of input-output (I-O) information are used as priors: (i) a reduced-form I-O relationship and (ii) an economic-base version of the I-O information. Out-of-sample forecasts from these two I-O-based BVAR models are compared with forecasts from an autoregressive model, an unconstrained VAR model, and a BVAR model with a Minnesota prior. Results indicate most importantly that overall the model version with economic base information performs the best in the long run.
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Bibliographic InfoArticle provided by Southern Regional Science Association in its journal Review of Regional Studies.
Volume (Year): 40 (2010)
Issue (Month): 2 ()
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Forecast; Forecasting; Input Output;
Find related papers by JEL classification:
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
- R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
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