DSS News
                     D. J. Power, Editor
               June 9, 2002 -- Vol. 3, No. 12
         A Bi-Weekly Publication of DSSResources.COM

    Check the article by Joe Herlihy at DSSResources.COM


* DSS Wisdom
* Ask Dan! - Can DSS improve state government tax revenue projections?
* Spreadsheet-based DSS Tip - Hide Unused Rows and Columns
* What's New at DSSResources.COM
* DSS News Releases


Check Dan Power's new book, Decision Support Systems: 
Concepts and Resources for Managers. Get information at .


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DSS Wisdom

According to Haynes and Henry (1974) in their book on Managerial 
Economics, "In appraising the basic four-step procedure for forecasting 
-- constructing a model, estimating the parameters, choosing values for 
the exogenous variables, and simulating the future -- several possible 
weak links are obvious. First, there is the possibility of incorrectly 
specifying the model. ... A second possible weakness relates to any 
attempt to extrapolate into the future based on past experience. A 
change in the economy cannot be measured immediately ... A third 
possible weak link in the procedure involves choice of values for 
exogenous variables. ... Perhaps the most important positive feature of 
econometric model forecasting is that it requires the forecaster to 
completely specify the assumptions underlying his forecasts. ... Another 
strength of econometric models is their capability for simulation of a 
great variety of possible environments." (p. 132)

from Haynes, W. W. and W. R. Henry. Managerial Economics: Analysis and 
Cases (3rd edition). Dallas, TX: Business Publications, Inc., 1974.


Ask Dan!
by Daniel J. Power

Can DSS improve state government tax revenue projections?

In the United States, state governments forecast tax revenues, prepare 
spending budgets based on the forecast, and then track and monitor tax 
receipts and expenditures. This past year has been especially difficult 
for the forecasters. Here in Iowa we have experienced major tax revenue 
shortfalls. Rather than raising taxes to meet budgeted needs, our state 
legislature has cut budgets. This Ask Dan! briefly examines why state 
tax revenue projections are so "bad" this year, the revenue estimating 
decision process, and then the role, if any, DSS play and could play in 
tax revenue projections. Web resources have been invaluable for 
collecting information for this Ask Dan!, but I would welcome comments 
from those with "first hand" knowledge of using DSS in revenue 

People in many states in the United States are asking why state tax 
revenue projections are so "bad". One reads many explanations. The 
shortfall is caused by the national recession. The terrorist attacks 
have reduced consumer spending and hence sales taxes. More people are 
unemployed, personal income is down and hence there has been a much 
"higher-than-expected" increase in income tax refunds. There is a 
continuing Medicaid shortfall. And there is a ripple effect theory ... 
an unexpected effect of the federal government's stimulus package and 
changes in depreciation schedules was a major reduction in state 
corporate income taxes. It sounds like part of the blame falls to errors 
in specifying a revenue estimating model. Model-driven DSS should be 
able to assist forecasters in examining impacts of changes in state and 
federal tax laws and the impact of changes in personal income on tax 
refunds and hence the impact on tax revenues.

What about process problems? Here in Iowa we have a 3 person revenue 
estimating board. These "experts" are supposed to take the politics out 
of tax revenue projections. It is not clear however how they arrive at 
their forecasts. A state legislator told me they don't use any decision 
support systems. The revenue numbers continue to fall and the shortfalls 
seem to only get worse. 

Lynn Okamoto, a staff writer for the Des Moines Register, reported May 
8, 2002 the "Off-the-mark revenue estimates over the past year have led 
to criticism of the Revenue Estimating Conference, the three-person 
panel that lawmakers rely upon to determine the size of the state budget 
pie." Iowa Governor, Tom Vilsack, recently replaced his appointee to the 
panel with banker Holmes Foster. Foster noted in an interview with 
Okamoto, "This isn't an exact science. I would characterize it as a very 
intelligent guess." 

What is the revenue estimating decision process? IT DEPENDS! Processes 
vary among the states. In Michigan, a Revenue Estimating Conference is 
held each January and it is a major part of the budget process. 
According to a document at the State of Michigan Web site 
(, during the conference, "national and state 
economic indicators are used to formulate an accurate prediction of 
revenue available for appropriation in the upcoming fiscal year." The 
Web page also notes "The principal participants in the conference are 
the State Budget Director and the Directors of the Senate and House 
Fiscal Agencies or their respective designees. Other participants may 
include the Governor and senior officials from the Department of 
Treasury." A second Revenue Estimating Conference takes place in June of 
each year.

In Florida, the following seven step revenue estimating process is used 

1. The process begins with a national economic forecast.

2. The national economic forecast establishes the basic parameters for 
making a state economic forecast.

3. Once a particular level of state economic activity is agreed upon, 
state revenues can be forecast.

4. Demographic and other relevant data are taken into consideration.

5. The principals use the adopted national and state economic forecasts 
to derive forecasts of state revenue collections.

6. For the General Revenue Fund, separate forecasts are made for each 
major tax source.

7. The forecasts for each separate tax source are debated, and a 
consensus forecast is agreed upon.

In Tennessee, the "revenue estimating process generally starts twelve 
months before a fiscal year begins. Revenue collections are tracked on a 
monthly basis, and this information, along with specific long-run 
forecasts of individual sectors of the economy, is used to form the 
basis for the next fiscal year's estimated revenue collections. 
Preliminary estimates are supplied to the Department of Finance and 
Administration in mid-summer by the Department of Revenue and the 
University of Tennessee Center for Business and Economic Research. Tax 
estimates are recalculated in October and November and refined in 
December and January for inclusion in the Governor's Budget Document 

According to a web page at the State of Tennessee Web site, their 
revenue estimating process incorporates the "Good Practices in Revenue 
Estimating" endorsed by the National Association of State Budget 
Officers and the Federation of Tax Administrators. The web page notes 
this "requires the use of national and state economic forecasts, 
development of an official revenue estimate, monitoring and monthly 
reporting on revenue collections, and revision of estimates when 

In Rhode Island, a Revenue Estimating Conference develops a consensus 
forecast (cf., 

In general, estimators are supposed to take into account state tax law 
changes, federal tax law changes, and updated economic factors. In some 
U.S. states, the revenue estimating authority is in the executive branch 
(e.g., Treasurer, Comptroller, or revenue collection agency). In other 
states, authority has been placed in a consensus conference process.

What role, if any, do Decision Support Systems play in tax revenue 
projections? The Federation of Tax Administrators 
( holds an annual Revenue Estimation and Tax 
Research Conference. At the 2001 conference in Minneapolis, the agenda 
included working sessions on Dynamic Estimation and Modeling, Data 
Base/Blurring Techniques, Tax Expenditure Reporting/Estimation 
Techniques, and Revenue Forecasting. Michael Lipsman of the Iowa 
Department of Revenue and Finance presented a paper titled "Hunting for 
Leading Indicators: The Iowa Experience". Reece Womack, Oklahoma Tax 
Commission, presented "A Survey on the Use of Multivariate Time series 
Analysis in State Revenue Forecasting." William Witzleben, New York 
Dept. of Taxation and Finance, presented "Corporate Tax Simulations -- 
Modeling and Distributional Analysis." From what I can tell some tax 
administrators are using data and models to support revenue estimating. 
The sophistication of the DSS is however unclear.

The American Economics Group ( sells a 
software product called RevCast™ for State and Local Government Revenue 
Forecasting. Their marketing materials claim it can help prepare 
accurate monthly forecasts of taxes and other revenue, link revenue 
expectations to forecasts of the regional economy, track monthly revenue 
against target forecast ranges, receive early warning of revenue 
shortfalls or surpluses and reduce revenue-estimating volatility. 
RevCast™ sounds almost too good to be true. If you are using the 
product, let me know how it is working.

What's going wrong with the processes, models, and Decision Support 
Systems? Some possibilities ... the forecasters and decision makers may 

1) making consensus estimates based on limited information.

2) relying too much on simple moving average forecasts.

3) using simplistic revenue models that need major revisions or 
incorrectly specifying the revenue model (cf., Haynes and Henry, 1974).

4) using incorrect data or data that is outdated.

5) failing to recognize the economy has fundamentally changed (cf., Haynes 
and Henry, 1974).

6) reading tea leaves instead of using a crystal ball; perhaps they need 
Crystal Ball 2000 (the Excel add-in at

Building a new model-driven Decision Support System or improving current 
DSS won't eliminate the current revenue shortfalls ... all Decision 
Support Systems can do is give decision makers better, more timely 
estimates so they can prepare better budgets, respond faster to changes 
in the economy and tax laws, and hopefully reduce the impact of future 
revenue shortfalls or make proactive changes to reduce any shortfalls. 
As Haynes and Henry (1974) note, "forecasting is both an art and a 
science (p. 135)." Let's not forget the science of forecasting.


American Economics Group at

Haynes, W. W. and W. R. Henry. Managerial Economics: Analysis and Cases 
(3rd edition). Dallas, TX: Business Publications, Inc., 1974.

Michigan.Gov Office of the Governor FAQ, "What is the purpose of the 
Revenue Estimating Conference?", at URL,1431,7-103-786-2659--F,00.html

O'Kain, S. "Consensus Estimating Process - Overview," presented at 2001 
Florida Government Finance Officers Association Annual Conference,

Okamoto, L. "New, lower revenue estimate keeps budget nightmare alive." 
Des Moines Register newspaper, 05/08/2002,

State of Tennessee, "State Tax Revenues", at URL


Spreadsheet-based DSS Tip

Hide Unused Rows and Columns 

Users can get lost navigating the more than 16 million cells in an Excel 
worksheet. For practical and aesthetic reasons hide the unused rows and 
columns. Rodney Powell in a posting at explained 
the steps to "hide" rows: 

1. Select the row header just beneath the used area of your spreadsheet, 
where you want to start hiding rows. 

2. Press Ctrl + Shift + Down Arrow. This will highlight everything from 
your selected row through the bottom of the worksheet. 

3. From the worksheet's Format menu, choose Row, then Hide. 

Follow the same basic steps to hide columns. Check


What's New at DSSResources.COM

06/02/2002 Posted article by Herlihy, J. "Simulation software: A 
powerful way to improve organizational decision making", 
DSSResources.COM, 06/02/2002, URL


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