Article ID: | iaor20041931 |
Country: | United States |
Volume: | 15 |
Issue: | 3 |
Start Page Number: | 339 |
End Page Number: | 353 |
Publication Date: | Jan 2003 |
Journal: | Journal of Public Budgeting, Accounting and Financial Management |
Authors: | Payne James E., Schwendeman Ken |
Keywords: | management, time series & forecasting methods |
Given the absence of a formal forecasting model of property insurance surtax revenue for the state of Kentucky, this paper presents the in-sample and out-of-sample forecasts of four models: Holt linear trend algorithm, autoregressive model, linear trend/autoregressive model, and economic activity model based on annual fiscal year data from 1984 to 2001. The Holt linear trend algorithm and the linear trend/autoregressive model were reasonably close in their respective forecasting performance for both the in-sample and out-of-sample forecast horizons. However, the linear trend/autoregressive model exhibited some evidence of instability for the period 1992 to 1994. With respect to the out-of-sample forecasts, the Holt linear trend algorithm provided a better fit to the actual surtax data. Moreover, as time passes and additional data on the surtax become available, the models presented can easily be updated and re-evaluated.