This week we conclude our series on property taxes by introducing our method for forecasting municipal property tax base if you want to build your own property tax forecast. We have used these variables to build models to support municipal budgeting and they should be helpful for any community in North Texas.

Components of the Tax Base

When doing the forecast you will get more accurate results by creating separate forecasts for the three major categories of property tax base: commercial real property, residential real property and business personal property. Many economic indicators are logical predictors of property tax base, but the following have consistently been statistically significant and contribute to more accurate forecasts.

Variables for Forecasting Commercial Real Property

Three indicators have been effective in forecasting commercial real property. The first is historical commercial real property tax base. This information can come from old budget documents or from your central appraisal district. The second variable is total commercial construction. This can also be obtained from the appraisal district for past years, but another good source may be your municipal building inspection permit data. One or the other may be significant for your community. The final variable is a national statistic, annual gross domestic product (GDP.) This indicator picks up the overall national business cycle, which can have an impact on commercial finance and employment trends which, in turn, influence local demand for real estate and drive up or depress local property values.

Variables for Forecasting Residential Real Property

We find four variables are significant predictors of residential property tax base. The first is historical residential tax base. The second is municipal population. This can come from the Texas Demographic Center. You may need to do your own estimates to obtain the most recent annual values. The third variable is your property tax rate. The final indicator is a national statistic and a subset of the gross domestic product called residential investment. This indicator represents the national housing business cycle and has proven to be a statistically significant predictor of residential tax base in the DFW area.

Variables for Forecasting Business Personal Property

For most cities, business personal property is the smallest of the three tax base categories, but we found it is the most complicated to forecast. We have settled on five indicators that are necessary to predict it. The first is historical business personal property. The second is the Texas Business Cycle Index, which is compiled by the Federal Reserve Bank of Dallas. The third variable is the vacancy rate for retail real estate. You can obtain this from one of the commercial real estate data vendors. A second real estate variable, and the fourth in our model, is total occupied commercial inventory (office, industrial and retail). Finally, annual gross domestic product is also important.

Running the Forecast

We have been using this mix of indicators for many years to track local tax base performance. The art of forecasting means experimenting with various functional forms of these and other variables until you find the equations that do the best job of explaining your city’s historical tax base change. It is best if you build the forecast model in a statistical software program like Eviews or STATA. Once you have finalize the forecast models you can transfer them to Excel to do sensitivity analysis and run scenarios. If you want to learn more about our process let us know. You can use our contact form.

Next week we begin a series on measuring economic wellbeing and how and why economists developed widely used indicators like gross domestic product.