Year of Publication
2013
College
Martin School of Public Policy and Administration
Date Available
8-13-2014
Abstract
The LFUCG currently forecasts their revenues internally and has their forecasts validated by the Center for Business and Economic Research (CBER) at the University of Kentucky. However, it does not have a well-developed method of forecasting franchise fee revenue. They are not alone, as the literature on revenue forecasting that finds that between 50 and 75 percent of local governments rely on informal, judgmental approaches to forecast revenue instead of more formal, quantitative techniques. However, the literature also indicates that these judgmental approaches are less accurate.
Inspired by a study of St. Petersburg, Florida by Gianakis et al., and in an effort to find the best forecasting method for Lexington’s franchise fee revenue, this capstone analyzes three different forecasting strategies: unsophisticated methods, Holt-Winters multiplicative method, and multiple regression using robust standard errors.
Results showed that a simple 12 month lag was the most consistently accurate method, while multiple regression showed promising results, especially for years where there were no unexpected shocks to the system. The results for multiple regression were hindered by a small number of observations and a missing forecast for February 2012. It is recommended that the LFUCG use a simple 12 month lag, revising using projections about natural gas prices and weather trends. Suggestions for future studies include developing a model to predict natural gas prices, and heating- and cooling-degree-days.
Recommended Citation
Banta, Ian K., "Developing a Best Practice Model for Forecasting Annual Franchise Fee Revenue: The Case of the Lexington-Fayette Urban-County Government" (2013). MPA/MPP/MPFM Capstone Projects. 33.
https://uknowledge.uky.edu/mpampp_etds/33
