A Bayesian forecasting approach to constructing regional input-output based employment multipliers

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.