Local government revenue forecasting
Using regression and econometric revenue forecasting in a medium-sized city
Bibliographic Data
| ID | 20201180 |
|---|---|
| Authors | J Wong (0000-0002-4771-361X, Wichita State University, corresponding author), John D Wong |
| Year | 1995 |
| Volume | 7 |
| Issue | 3 |
| Pages | 315-335 |
| Publication date | 1995-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Public Budgeting Accounting & Financial Management (JOURNAL) |
| Journal identifiers | ISSN: 1096-3367 • E-ISSN: 1945-1814 |
| Publisher | Emerald (PUBLISHER) |
| DOI | 10.1108/jpbafm-07-03-1995-b001 |
| OpenAlex | W2332634355 |
| Language | EN |
| Citations received | 1 |
| References cited | 5 |
Fiscal stress has forced local governments to pay increasing attention to revenue trends and has increased the importance of financial forecasting in local government. After reviewing the role of revenue forecasting in financial planning and discussing the use of regression and econometric analysis in revenue forecasting, this article applies this technique to forecast several key revenue components in a medium-sized city. Three general conclusions may be drawn: (1) systematic revenue forecasting and long-range planning are necessities, not luxuries, (2) risk aversion to "technical" revenue forecasting can be overcome, and (3) the implementation of a systematic revenue forecasting system does not require a battery of "rocket scientists." As municipal revenue bases come to rely less on relatively stable property taxes and more on less stable sources such as sales taxes, fees, and charges, the use of a regression and econometric based model should prove increasingly fruitful
Business · Demand forecasting · Econometric model · Econometrics · Economics · Government revenue · Operations management · Regression analysis · Revenue · Revenue assurance · Revenue model · Computer Science · Forecasting Techniques and Applications · Housing Market and Economics · Finance
| Unique citing works | 1 |
|---|---|
| Citations per year | 0,05 |
| Citation span | 2006 - 2006 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |