Abstract
Across the 50 states, there is significant variation in forecasting practices, which makes them difficult to compare and assess. This study looks at the diversity of the state-level revenue forecasting processes between FY2015 and FY2017, with a particular focus on the type of process, the level of political involvement, and the extent to which state forecasts have proven to be accurate and transparent. Additionally, case analyses of several states demonstrate that revenue forecasts exist within institutional and political frameworks that can significantly influence the accuracy and transparency of the publicly reported forecasts.
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Notes
- 1.
Percent Error = (At – Ft) / At
Mean Percent Error = ∑[(At – Ft) / At]
Mean Absolute Percent Error = |∑[(At – Ft) / At]|
where A = actual general fund collections, F = official forecast of general fund collections, and t = the fiscal year.
- 2.
The reader should be wary in comparing errors across states. The portfolio of funds that comprise each state’s general fund can be very different. For example, some states have transportation funds separate from the general fund where they deposit revenues from highway tolls and other transportation-related revenues. Other states put these revenues into the general fund. States can also have different tax structures, which impacts their revenues because different sources of revenue have different levels of volatility. For example, some states do not have income taxes. Finally, the reader should be aware that the general fund forecasts and actual collections are based on NASBO survey numbers, which do not account for post-publication tax base or rate changes, administration collection changes, or changes to the general fund structure.
- 3.
Interview with Director of Georgia Office of Planning and Budget.
- 4.
Interview with Executive Budget Office official, South Carolina Department of Administration.
- 5.
Interview with Director of Tennessee Budget Analyst Agency.
- 6.
Interview with Staff Director, Virginia House Appropriations Committee.
- 7.
Interview with Budget Director, Virginia House of Delegates.
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Appendices
Appendix 1: General Fund Forecast to Actual Differences and Midyear Adjustments
State by forecasting type | FY2015 percent error | FY2015 midyear adjustment? | FY2016 percent error | FY2016 midyear adjustment? | FY2017 percent error | State mean percent error | State mean absolute percent error (MAPE) |
|---|---|---|---|---|---|---|---|
Consensus | Â | Â | Â | Â | Â | Â | Â |
Connecticut | −1.0% | Yes | −2.3% | Yes | 0.1% | −1.1% | 1.1% |
Delaware | 0.2% | – | 0.2% | – | −2.5% | −0.7% | 0.9% |
Florida | 1.4% | – | −0.6% | – | 0.5% | 0.4% | 0.8% |
Hawaii | 5.7% | – | 4.0% | – | −2.2% | 2.5% | 4.0% |
Indiana | 0.3% | – | −1.0% | – | −2.0% | −0.9% | 1.1% |
Iowa | −0.4% | – | −3.7% | – | −3.5% | −2.6% | 2.6% |
Kansas | −0.8% | Yes | −8.6% | Yes | −8.6% | −6.0% | 6.0% |
Kentucky | 1.3% | – | 2.8% | – | 0.0% | 1.3% | 1.3% |
Louisiana | −3.0% | Yes | −8.6% | Yes | 0.0% | −3.9% | 3.9% |
Maine | 2.5% | – | 1.3% | – | 2.3% | 2.0% | 2.0% |
Maryland | −0.4% | Yes | −0.8% | – | −2.5% | −1.2% | 1.2% |
Massachusetts | 0.3% | Yes | −0.4% | – | 0.9% | 0.3% | 0.6% |
Michigan | 3.7% | Yes | 1.3% | – | 0.4% | 1.8% | 1.8% |
Mississippi | 1.4% | – | 0.7% | Yes | 3.2% | 1.8% | 1.8% |
Missouri | 1.4% | – | 1.3% | – | −3.0% | −0.1% | 1.9% |
Nebraska | 2.0% | – | −3.9% | Yes | −3.1% | −1.7% | 3.0% |
Nevada | −1.7% | Yes | 4.9% | – | 4.5% | 2.6% | 3.7% |
New Mexico | −0.1% | – | −10.4% | Yes | −7.9% | −6.1% | 6.1% |
New York | 7.3% | – | 2.0% | – | −1.5% | 2.6% | 3.6% |
North Carolina | 2.1% | – | 2.2% | – | −0.3% | 1.4% | 1.5% |
Rhode Island | 4.1% | – | 3.3% | – | 1.2% | 2.8% | 2.8% |
South Carolina | 4.3% | – | 3.1% | – | 0.0% | 2.5% | 2.5% |
Tennessee | 4.0% | – | 7.0% | – | 4.3% | 5.1% | 5.1% |
Utah | 7.3% | – | 2.4% | – | 0.0% | 3.2% | 3.2% |
Vermont | −0.3% | Yes | 0.4% | Yes | −0.2% | 0.0% | 0.3% |
Virginia | −4.9% | Yes | 0.9% | – | −2.7% | −2.2% | 2.8% |
Washington | 2.7% | – | 3.2% | – | 2.5% | 2.8% | 2.8% |
Wyoming | −17.0% | – | −77.1% | – | −2.9% | −32.3% | 32.3% |
Mean | 0.8% |  | −2.7% |  | −0.8% | −0.9% | 3.6% |
Median | 1.3% |  | 0.8% |  | −0.1% | 0.4% | 2.5% |
Executive | Â | Â | Â | Â | Â | Â | Â |
Alaska | −50.1% | Yes | −43.2% | Yes | 13.9% | −26.5% | 35.7% |
Arkansas | 0.2% | – | 3.4% | – | 0.0% | 1.2% | 1.2% |
Georgia | 3.5% | Yes | 6.9% | Yes | 1.7% | 4.0% | 4.0% |
Minnesota | 3.6% | – | 1.2% | Yes | −0.8% | 1.4% | 1.9% |
North Dakota | 2.1% | – | −31.3% | Yes | −0.5% | −9.9% | 11.3% |
Oklahoma | −2.0% | Yes | −9.1% | Yes | −5.5% | −5.5% | 5.5% |
Oregon | 2.4% | – | −2.1% | – | 0.9% | 0.4% | 1.8% |
Texas | 4.9% | – | −5.9% | – | −4.6% | −1.9% | 5.1% |
West Virginia | −1.4% | Yes | −4.6% | Yes | 0.0% | −2.0% | 2.0% |
Mean | −4.1% |  | −9.4% |  | 0.6% | −4.3% | 7.6% |
Median | 2.1% |  | −4.6% |  | 0.0% | −1.9% | 4.0% |
Separate | Â | Â | Â | Â | Â | Â | Â |
Alabama | −0.2% | – | −0.7% | – | 0.3% | −0.2% | 0.4% |
Arizona | 2.1% | – | 6.7% | – | 1.1% | 3.3% | 3.3% |
California | 6.0% | – | 0.4% | – | −1.3% | 1.7% | 2.6% |
Colorado | 2.1% | – | −2.8% | Yes | 0.9% | 0.0% | 1.9% |
Idaho | 3.2% | – | 2.0% | – | 1.1% | 2.1% | 2.1% |
Illinois | −0.4% | Yes | – | Yes | −1.6% | −0.7% | 0.7% |
Montana | 2.9% | – | −6.7% | Yes | −5.8% | −3.2% | 5.1% |
New Hampshire | −2.2% | – | 6.4% | – | 4.8% | 3.0% | 4.5% |
New Jersey | 1.7% | Yes | −2.1% | – | −0.7% | −0.4% | 1.5% |
Ohio | 2.3% | – | −2.6% | – | −2.9% | −1.1% | 2.6% |
Pennsylvania | 5.6% | – | – | Yes | −5.0% | 0.2% | 3.6% |
South Dakota | −0.8% | – | 0.3% | – | −1.7% | −0.7% | 0.9% |
Wisconsin | −1.2% | Yes | −0.7% | – | −1.0% | −1.0% | 1.0% |
Mean | 1.6% |  | 0.0% |  | −0.9% | 0.2% | 2.3% |
Median | 2.1% |  | −0.7% |  | −1.0% | −0.2% | 2.1% |
TOTAL | Â | Â | Â | Â | Â | Â | Â |
Mean | 0.1% |  | −3.2% |  | −0.6% | −1.2% | 4.0% |
Median | 1.4% |  | 0.2 |  | −0.2% | 0.0% | 2.5% |
Appendix 2: States Without a Reasonable Rationale and GF Forecast to Actual
State | FY2015 PE | RR? | FY2016 PE | RR? | FY2017 PE | RR? | State PE | State APE |
|---|---|---|---|---|---|---|---|---|
Consensus | ||||||||
Iowa | −0.4% | No | −3.7% | No | −3.5% | No | −2.6% | 2.6% |
Kansas | −0.8% | No | −8.6% | No | −8.6% | No | −6.0% | 6.0% |
Missouri | 1.4% | No | 1.3% | No | −3.0% | No | −0.1% | 1.9% |
Virginia | −4.9% | No | 0.9% | – | −2.7% | – | −2.2% | 2.8% |
Executive | ||||||||
Georgia | 3.5% | No | 6.9% | No | 1.7% | No | 4.0% | 4.0% |
Separate | ||||||||
Alabama | −0.2% | No | −0.7% | No | 0.3% | No | −0.2% | 0.4% |
Illinois | −0.4% | – | N/A | No | −1.6% | No | −0.7% | 0.7% |
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Franklin, E., Bourdeaux, C., Hathaway, A. (2019). State Revenue Forecasting Practices: Accuracy, Transparency, and Political Participation. In: Williams, D., Calabrese, T. (eds) The Palgrave Handbook of Government Budget Forecasting. Palgrave Studies in Public Debt, Spending, and Revenue. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-18195-6_8
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