A Data-Pooling Approach to Estimate Employment Multipliers for Small Regional Economies

The level of residentiary employment in areas such as counties is an important component of rural development, environmental, and energy impact analysis. Volatile employment changes lead to migration, population, and wage changes. This study demonstrates a procedure for estimating disaggregated and lagged economic base multipliers for short to intermediate term forecasting models. Using an application of pooled cross-section/time-series data, a covariance model and an error components model are demonstrated for Northern Great Plains coal development. The only sector identified as having a consistent time lag was mining, and this lag was estimated to be 1 year.