Municipal Government Revenue Forecasting: Issues of Method and Data |
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| Authors: | Carmen Cirincione Gustavo A. Gurrieri Bart van de Sande |
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| Affiliation: | Assistant Professor at the Department of Political Science, University of Connecticut, U-24 341 Mansfield Rd., Storrs, CT 06269-1024. E-mail address: .;Information Systems Manager at the Center for Survey Research and Analysis at the University of Connecticut, U-24 341 Mansfield Rd., Storrs, CT 06269-1024. E-mail address: .;VF Jeanswear, Greensboro, NC. |
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| Abstract: | In this article the authors investigate the impact of the choice of time series method, the length of the data stream used to estimate the model, and the frequency of the data on forecasting accuracy for own source, non-tax general fund revenue for six Connecticut municipalities. The authors find that exponential smoothing models are generally the most accurate. They also conclude that local government officials should rely on bimonthly rather than monthly or quarterly data and retain, in a readily usable format, more than three years of data. |
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