An Open Systems Model of Local Government Forecasting

Abstract

Local governments use single source forecasts to inform decision making, which can constrain their ability to prepare for and respond to financial uncertainty. This unique context may have increased the challenges faced by governments at the local level through economic downturns such as the Great Recession. Given this concern, which has yet to be addressed in the literature, this article develops an open systems model of local government forecast accuracy, which can be tested across any type of local government. This article tests the model with a panel of special purpose governments at the local level, specifically school districts in Pennsylvania, from 2003 through 2013. Estimation of the model with longitudinal analysis shows that government forecasters at the local level consider internal and external factors when forecasting own-source and intergovernmental revenue streams. In particular, a mix of institutional, financial, and political factors are associated with forecast accuracy. Forecasters at the local level also considered the role of economic shocks, as evidenced by decreased expectations for own-source revenue through the Great Recession. Collectively, these findings demonstrate that they consider a complex and multifaceted information set, which includes both internal and external determinant factors of forecast accuracy at the local level. These factors can prove critical to increasing forecast accuracy in context of the financial uncertainty experienced through the Great Recession.