A VAR Forecasting Model of a Regional Economy: Its Construction and Comparative Accuracy

Terrence W. Kinal · Jonathan B. Ratner

51 citations0/0 files storedInternational Regional Science Review

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Forecasting Techniques and Applications Monetary Policy and Economic Impact Regional Economic and Spatial Analysis

Abstract

The usefulness of the vector autoregression (VAR) approach to forecasting regional economies is explored. A VAR model and a Bayesian VAR (BVAR) model of selected New York State economic variables are constructed using monthly data. Their predictions about these variables are compared with ARIMA and transfer function model forecasts. Overall, the accuracy of BVAR matches or exceeds that of the other techniques. Thus, a previous suggestion that BVAR is promising, as a forecasting tool and as a benchmark for regional forecasts, is supported.

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1980Macroeconomics and Reality 2000Forecasting Economic Time Series 1983Forecasting and Conditional Projection Using Realistic Prior Distributions 1984Forecasting and conditional projection using realistic prior distributions 1977Forecasting Economic Time Series 1982Policy Analysis with Econometric Models 1974Time series analysis and simultaneous equation econometric models 1981Relative Shocks, Relative Price Variability, and Inflation

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1992Co‐integration, error correction and improved medium‐term regional VAR forecasting 2013Macroeconomic surprises and stock returns in South Africa 2016A small-scale DSGE-VAR model for the Romanian economy

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