State Revenue Forecasting Practices: Accuracy, Transparency, and Political Acceptance
A Volcker Alliance Project Paper
March 18, 2017
ASPA 2017 Annual Conference
Emily Franklin
Public Finance Fellow
Center for State and Local Finance
Andrew Young School of Policy Studies
Georgia State University
[email protected]
Carolyn Bourdeaux
Associate Professor
Director, Center for State and Local Finance
Andrew Young School of Policy Studies
Georgia State University
Alex Hathaway
Public Finance Fellow
Center for State and Local Finance
Andrew Young School of Policy Studies
Georgia State University
Special thanks to the Volcker Alliance for their research support and permission to use
their data in this analysis.
DRAFT: Please do not cite without permission of the authors.
ABSTRACT
This paper will discuss the budget practices around revenue forecasting. Recent research has
discussed how revenue forecasting is not just a matter of accuracy but also is important for
transparency and political acceptance of revenue forecasts as a guide to the budget process. At
the same time, recent research has pointed out there is significant variation in “consensus
forecasting” practices. This paper will look at the diversity of revenue forecasting processes
across the 15 states and assess the extent to which they have proven to be accurate, transparent,
and politically accepted between FY15 and FY16.
INTRODUCTION
The state revenue forecast sets the tenor for budget deliberations in the U.S. states.
Because most states operate under a balanced budget constraint, the revenue forecast establishes
a foundation for fiscal discipline since it sets a cap on state spending. Almost every state has
evolved to have a unique process around revenue estimation and scholars have long debated
whether there are different processes or methodologies that are more accurate, more likely to
lead to broad political acceptance and generally provide a firmer foundation for fiscal discipline.
The academic literature on these different processes is vast and by no means conclusive
regarding best practices.
This paper briefly reviews the literature on revenue forecasting and then draws on a
dataset produced as part of the Volcker Alliance Truth and Integrity in Government Finance
project to examine in detail the revenue forecasting processes in 15 southeastern states. In
particular the paper assesses the process and actors involved in forecasting, the methodological
approach, the accuracy of the forecast, and ultimately, the political acceptance of the forecast.
The analysis draws on the rich detail the researchers have available for each state to explore
some of the more interesting state practices around forecasting.
LITERATURE REVIEW
Forecasting Processes
One of the most vibrant debates in the literature on state revenue forecasting centers
around the process associated with revenue forecasting. Revenue forecasting is roughly divided
into three types: executive, consensus and separate (where the legislative and executive branch
and even the different parties within the legislative branch develop separate forecasts).
1
Perhaps the most widely recommended process is a consensus forecast.2 3 4 5 According
to the National Association of State Budget Officers (NASBO), a consensus revenue forecast is a
“revenue projection developed in agreement through an official forecasting group representing
both the executive and legislative branches.”6 However, these categories mask wide variations,
particularly around consensus forecasting, which can involve a number of different combinations
of legislative and executive policy-makers, including involvement by legislative and executive
staff, elected officials or even elected officials explicitly from opposing political parties as well
as involvement by non-partisan external parties such as academics. A common question is the
extent to which these process differences are linked to accuracy, transparency or more recently,
political acceptance of the forecast.
Accuracy
Because revenue collections are affected by state, national and global economic
conditions, they are difficult to predict. Researchers have looked at both the association of
accuracy with consensus forecasting process as well as whether different techniques of
forecasting produce more accurate results. There is extensive literature showing that combining
independent forecasts increases accuracy.7 Updating revenue forecasts as close to the start of the
fiscal year as possible has also been shown to increase accuracy.8 Some studies have found that
consensus revenue forecasting improves the accuracy of forecasts, though it is not clear why it
improves accuracy. Consensus forecasts may lower the percentage of forecast “misses”.9 10 11 12
One possible reason is the process often involves a number of experts on different parts of the
economy, who can provide a wealth of economic information, as well as ensure the forecasting
method is less politically influenced. In addition, if different forecasts are combined during the
process of forming the official forecast, then accuracy may increase. Voorhees (2004), however,
found less of an effect on accuracy after controlling for frequency of state’s forecasts,
independent expert input and other factors.13 Boyd and Dadayan (2014) agree that consensus
revenue forecasting can help insulate the forecasting process from undue political influences, but
their study did not show that it contributed to the accuracy of the forecast.14
A further dimension to the revenue forecasting debate is the extent to which the forecast
is subject to political influence. Several studies have found forecasting errors increased due to
politically opportunistic behavior when governors have a balanced-budget requirement, when the
forecasting group is linked with the government, or when elected officials have longer term
limits or long-term unified government. The creation of independent groups with knowledge of
the forecasting domain, however, reduces forecasting error because they reduce error due to
human bias or political expediency. 15 16 17 18 In contrast, Mikesell and Ross (2014) found that
the Indiana revenue forecast process (which has not only executive and legislative consensus, but
also Republican and Democrat party representation) outperformed various “naïve” revenue
forecasting processes and had the further benefit of building political consensus around the
forecast. Certain fiscal policies can also predict more transparency around the revenue estimation
process. For example, Rose & Smith (2011) found that states that created budget stabilization
funds (BSFs), with policies governing how much expected surplus would be put into the account
and how much could be taken out and used for other purposes, also decreased their revenue
forecast bias.19
Transparency
The level of transparency surrounding the estimation process is another relevant aspect of
revenue forecasting. The Government Finance Officers Association (GFOA) recommends
governments are upfront about their forecasting philosophies. For instance, some governments
prefer to make “conservative” forecasts, which may make balancing the budget more difficult,
but reduce the risk of a shortfall. Other governments try to make an “objective” forecast, which
seeks to be as close to actual revenue collections as possible. These forecasts make it easier to
balance the budget, but also increase the risk of a shortfall. The GFOA also recommends that
governments clearly present underlying assumptions and methodologies in the final budget
document.20 The Organisation for Economic Co-operation and Development (OECD) and the
International Monetary Fund (IMF) recommend that key economic assumptions be disclosed in
budget documents, as well. Such assumptions can include gross domestic product (GDP)
growth, the employment and unemployment rates, and inflation. Furthermore, an analysis of the
impact of these macroeconomic trends on the budget should be publicly available.21 22 However,
McNichol, Lav and Leachman (2015) found that most states do not clearly tie these
underpinning economic assumptions to the revenue forecast. A few states, such as Alabama, do
not publish these assumptions at all.23
Different factors predict the level of transparency around the revenue forecast. Alt,
Lassen and Rose (2006) provide some anecdotal accounts of states adopting consensus revenue
forecasting in an effort to increase fiscal transparency, such as Delaware and Rhode Island.
These transparency efforts were generally adopted in periods of fiscal stress, split governments
or a recent party turnover in the governor’s office.24
Political Acceptance
Recently, Mikesell and Ross (2014) raised the issue of political contention around the
revenue forecast, pointing out that both the executive and legislative branches need to be
involved in the process in order to build consensus and reduce conflict over the final estimate. 25
Ironically, other researchers have called for de-politicizing the revenue forecasting process for
this very same reason.26 27 28 29 30 There are a number of studies with anecdotal accounts of states
adopting consensus forecasts for political reasons;31 32 33 however, the researchers were unable to
locate a study that looks at this issue on a national scale. States seem to have adopted a mixture
of both approaches. As of 2014, as many as 24 states have adopted some form of consensus
forecast, while 36 include non-government experts in their forecasting process. 18 states have
both a consensus forecast and non-governmental experts in their forecasting body.34
This analysis examines three key aspects of revenue forecasting in 15 southeastern states:
the level of accuracy, the level of transparency, and the level of political acceptance. Though
there is evidence that combined forecasts and independent expert participation increases
accuracy, the verdict is still out on whether or not a consensus forecast increases accuracy.
Regarding transparency, the GFOA and others recommend that states publish detailed
methodologies with underlying macroeconomic assumptions along with their forecasts. There
are anecdotal accounts of consensus forecasting increasing fiscal transparency. An interesting
question is: are states with consensus forecasts more likely to publish detailed forecast
methodologies and underlying macroeconomic assumptions because they are more likely to
involve external experts in making the forecast? Finally, regarding political acceptance and the
revenue forecast, there are a number of studies that describe states’ adoption of consensus
forecasting processes for political reasons; however, we were unable to find a study that looked
at this issue on a national scale. While recognizing the “endogeneity” of a consensus forecast to
inter-party political conflict, a further question of interest is whether there is any evidence that
consensus forecasts are more likely to be accepted as legitimate by policy-makers than a pure
executive forecast or a forecast where the legislative and executive branch each act
independently.
Using data compiled for the Truth and Integrity in Government Finance project by the
Volcker Alliance, this paper examines state revenue forecasting budget practices and the extent
to which they reflect the best practices described above. While the data is limited, the paper also
assesses whether there is any evidence of a relationship between these best practices and the
extent to which the forecast is accurate and viewed as legitimate by different political actors. The
research then draws on some rich contextual detail and case study material available to the
researchers to further examine these issues.
METHODS
The Volcker Alliance’s project involved organizing a group of universities to conduct a
survey of budget and fiscal practices of all fifty states for the fiscal years 2015, 2016 and 2017.
The project was organized around assessing whether and to what extent states are facing
structural deficits and several questions focused on revenue forecasting processes, multi-year
revenue and expenditure forecasts, revenue growth projection rationales, and midyear budget
adjustments. There were 29 questions in total, but, for this paper, the analysis focuses on the data
gathered for the following five questions:
1. Does the state disclose consensus revenue forecasts in budget documents?
2. Does the state disclose multi-year revenue forecasts (at least 3 years) in budget
documents?
3. Does the state disclose multiyear expenditure forecasts (at least 3 years) in budget
documents?
4. Does the state reasonably support revenue growth projections at time of initial
budget?
5. Was there a need for a meaningful (i.e., greater than 1%) midyear budget
adjustment?
Since all states were still in the middle of FY2017 at the time of this analysis, only
FY2015 and FY2016 responses were considered. For the purposes of the project, budget
documents were considered the Governor’s recommended budget, enacted appropriations bills,
as well as supporting documents such as legislative analysis of the budget and presentations or
revenue forecasts produced in tandem with the budget. Consensus revenue forecasts were
defined as forecasts with both executive and legislative participation. Additionally, for five
states, Maryland, Virginia, North Carolina, South Carolina, and Georgia, the analysis draws on
more detailed case study information on the shifts in the revenue estimate during budget
development, adoption and implementation. Because questions of accuracy and transparency
cannot be entirely addressed based on the Volcker project questions, the analysis also
supplements this information with material collected from the National Association of State
Budget Officers (NASBO) Fiscal Survey of the States as well as more in depth reviews of
revenue forecasting and budget documents across all of the states to examine the methodology in
the forecasting process as well as participation in consensus and executive forecasting processes.
RESULTS
Forecasting Processes in the Southeastern States
This section discusses different aspects of the revenue forecasting processes in the
southeastern states, including the number of states with consensus forecasts, types of
membership in the states’ forecasting groups (executive, legislative, non-partisan), and multiyear forecasts.
[Table 1: Forecasting Processes in the Southeastern States]
Table 1 describes the membership of the states’ forecasting groups and whether or not
they include executive, legislative or non-partisan members. Most southeastern states have a
consensus revenue forecast-type process (10 out of 15 states); however, four have executive
driven processes. Only Alabama has a forecast developed separately by the executive and
legislative branches.
As noted earlier, states define “consensus” in different ways with varying degrees of nonpartisan, staff and elected official participation and even the executive dominated processes have
different external and staff advisement arrangements. In some states, such as Maryland, only
non-partisan staff are involved in the revenue forecasting process, although the process is still
considered consensus because the staff are from the executive as well as the legislative research
offices. Other consensus, staff driven processes include Florida, Kentucky, North Carolina, and
Mississippi. Virginia has an interesting hybrid process with two committees working on the
forecast. The first committee is a staff or “expert” committee, the Joint Advisory Board of
Economists (JABE). This committee works on the detailed methodology behind the forecast and
produces several options for consideration by elected policy-makers. The Governor’s Advisory
Council on Revenue Estimates (GACRE) includes legislative leadership as well as the Governor
and they ultimately vote on the revenue estimate to use.
No southeastern state statutorily requires the participation of both Republican and
Democrat politicians. In Delaware, however, some representation from each party is generally
included. After an initial review, Delaware appears to be the only state to explicitly include
minority party members in its forecasting group, although other states may have multi-party
representation if the legislative majorities in either Chamber are from the opposing party.
All fifteen states include the governor or some other executive membership, such as an
executive budget office, in their forecasting group. Georgia and West Virginia appear to be the
only states that exclusively rely on the Governor and his or her direct staff to develop the
revenue estimate. Oklahoma is an executive driven process but includes leadership from across
the executive branch, including the Lieutenant Governor and Attorney General.
The majority also include some sort of legislative membership, whether elected officials
or professional staff from legislative research offices. Only a very few include parties from
outside government. These include Virginia’s JABE and GARCE and the Delaware forecasting
group, which have citizen appointees and Louisiana and Alabama which have academic
appointees.
Accuracy of Southeastern States’ Revenue Forecasts
This section discusses the accuracy of revenue forecasts in the fifteen southeastern U.S.
states. Table 2 shows midyear adjustments to the budget, forecasting errors and accuracy grades.
[Table 2: Accuracy of Southeastern States’ Revenue Forecasts]
Table 2 shows the response to the Volcker Alliance survey assessment on whether a state
made a mid-year adjustment greater than one percent for FY2015 and FY2016. This is paired
with a fairly objective assessment of forecast accuracy pairing the general fund forecast with the
general fund year-end actual collections from NASBO. The table shows the forecasting error as a
raw percentage, which shows whether the state over or under estimated revenues, and absolute
value, which helps compare the size of the forecast “miss.” To more easily compare the
forecasting errors, we simply assigned a letter grade with errors between 0 and 1 receiving an
“A”, errors between 1 percent and 2 percent a “B”, errors between 2 and 3 percent a “C”, errors
between 3 and 4 a “D”, and errors above 4 percent an “F”. The grades are the same regardless of
whether the error is positive or negative. While an “A” grade signals a more accurate forecast, an
“F” grade signals a less accurate forecast, Willoughby and Guo (2008) considered less than five
percent forecasting error to be a relatively accurate forecast and a Pew-Rockefeller report on
revenue forecasts generally found that the mean forecast error was around 3 percent.35 36 States
with “D”s and “F”s are outside of the average forecast error.
While some important considerations around revenue forecast accuracy will be
considered later, just taking these forecasts at face value, in FY2015, the average forecast error
(the absolute value of the percentage difference between the forecast general fund revenues and
actuals) for the 15 states was two percent. In FY2016, the forecast error was 2.5 percent. This
average suggests the southeastern states on average are beating the forecast errors predicted by
the Pew-Rockefeller report -- even including states that are intentionally low-balling their
forecasts. FY2016 appears to be particularly affected by serious revenue declines in the energy
sector dependent states of Oklahoma, Louisiana, and West Virginia, but also by some large
misses to the positive in Georgia, South Carolina and Tennessee. The standard deviation for the
actual to forecast percentages is 3.72 for 2016 while only 2.58 for 2015.
Drawing on the more detailed data from various case studies suggests some important
considerations when simply taking the difference between forecast and actual revenues at face
value. For instance, in the 2015 legislative session Georgia passed transportation legislation that
increased tax and fee revenues by $870 million in FY2016. However, the state did not add these
new revenues to their budget until the middle of the fiscal year 2016, which makes the error rate
seem like 7.38 percent.
Additionally, Georgia annually adds a one percent of net revenue increase each year to
K-12 education in the mid-year budget out of the revenue shortfall reserve. The state essentially
pre-funds this by lowballing the revenue estimate in order to force the state to reserve this
amount the year prior. Finally, Georgia’s governor publicly committed to building a $2 billion
reserve fund before he left office in 2018. Georgia’s reserve is replenished from any surplus
year-end funds, so the Governor has further low-balled the revenue estimate to force sufficient
surpluses to rebuild the reserve. None of this is explicit in any budget documents so there is no
way to know what the “true” underlying state forecast actually is. While Georgia does not win
points for transparency, the state’s overly conservative revenue estimates do not necessarily
reflect poor forecasting capacity, but an intentional effort to significantly underestimate the
revenues.
Of the other southeastern states, South Carolina and Tennessee also appear to be similarly
substantially underestimating revenues. Like Georgia, South Carolina has certain designated
current year uses for prior year reserves, in their case a reserve for capital outlay. The state
actually uses this capital outlay reserve as a first resort rainy day fund prior to tapping their
revenue shortfall reserve. However, according to a budget official, South Carolina does not make
conservative revenue estimates in order to replenish this fund, but to avoid mid-year budget cuts
and year-end deficits.1
On the other end of the spectrum, six of the fifteen states over-projected their revenues,
and four over projected by greater than one percent in FY2015. Not surprisingly, these four
states were also forced to make negative mid-year adjustments of greater than one percent.2
Louisiana, Oklahoma and West Virginia were affected by unanticipated declines in the energy
sectors, and in FY2016 face even more dramatic overestimates of revenues; however, Virginia is
an anomaly. In 2016, the state gets an A for its revenue forecast, and is the only state to swing
from an F to an A. The challenge in Virginia is that the state appears to have intentionally gone
into FY2015, the second year in its biennium, knowing that it would overshoot its revenue
1
Interview with Executive Budget Office official, South Carolina Department of Administration
Two other states also recorded making mid-year adjustments greater than one percent, even though revenues
were tracking “to the good.” Arkansas’s mid-year adjustments are actually pre-planned. As part of the budget
process, the state adopts a set of mid-year spending priorities if the state is on track to make budget. If the
revenues track below estimate, these second tier priorities are put on hold for the fiscal year. Georgia actually is
similar in that it has a pre-planned mid-year adjustment for K-12 growth out of the revenue shortfall reserve,
which is required to be one percent of prior year revenues. Additionally, in FY2016 the state added in the tax
revenues from the transportation tax. Depending on whether one counts these adjustments, then the state also
made a greater than one percent mid-year adjustment like Arkansas. Tennessee continues to be an anomaly.
2
estimate. According to one account, the state had to formally overshoot its revenue estimate in
order to access its reserves.3 The state statute stipulates that the state can only access the revenue
shortfall reserve “if the general fund revenues appropriated exceed the forecast by more than two
percent.” Despite passing an adjusted FY2015 budget in June of 2014 and making significant
provision for an anticipated shortfall, the legislature did not formally lower the revenue estimate
until after an August 2014 revised revenue estimate (which in turn, was legally triggered by
problems with the FY2014 revenue estimate). The legislature then formally inserted the reserves
into the revised budget in December of 2014. In detail, the state ended the regular Session
without a budget due to a budget impasse, and the impasse continued into a Special Session. By
May, it was clear that the state would not meet its forecast for FY2014, which, on July 1st, would
legally trigger a new forecast for the FY2014-16 biennial budget period. Because the state did
not want to use a revised forecast in adopting its new budget, the impasse ended, and a budget
was adopted based on the old revenue forecast from December 2013. Now the forecast would not
be revised until after the start of the new fiscal year, allowing the state to reopen the newly
adopted budget and use the Revenue Stabilization Fund. Virginia’s constitution does not allow
the use of the Revenue Stabilization Fund in building a budget, which is why it was imperative to
adopt the new budget using the December 2013 revenue estimate.4
Given these variations in managing the revenue estimate, the metric of “forecast error”
may be something of a misnomer for many states. Rather than reflecting any lack of internal
capacity or methodological problems, forecasting error at the state level may be more
appropriately characterized as a problem of transparency or strategies for management of legal
and institutional arrangements. Revenue forecasts to some degree have a unique role in the
3
4
Interview with Budget Director, Virginia House of Delegates.
Interview with Staff Director, Virginia House Appropriations Committee.
budget process that goes beyond accuracy around expected revenues. For instance, in Georgia,
the balanced budget requirements are tied to the revenue forecast. Since the executive
unilaterally sets the forecast, the forecast is used as a policy lever to bound legislative
expenditures rather than as a device to actually communicate anticipated revenues. As noted in
the literature, a further confounding factor is that some states explicitly adopt an accuracy
approach, while others explicitly try to undershoot the estimate.
Given that many of the D and F scoring states either face problems like difficult to
predict energy prices or have revenue forecasts that do not accurately reflect their actual revenue
expectations, it is difficult to assess the relationship between forecasting process (e.g., consensus,
etc.) and outcome. A brief look at the states that appear to produce forecasts that are intended to
accurately reflect expected revenues shows no evidence of any clear linkage between a
consensus forecast and accuracy of the forecast. The states that received A or B grades in
FY2015 and FY2016 include Alabama, Arkansas, Delaware, Florida, Maryland and Mississippi;
however, these include a mix of forecast process types. Four out of the six have a consensus
process, but the committees working on the process are quite varied. Arkansas has an executive
forecast and Alabama has a “separated” process. Obviously, a more sophisticate quantitative
analysis is warranted, but as noted above, such an analysis would need to carefully consider
actual revenue expectations relative to the reported revenue forecast.
Transparency of Southeastern States’ Revenue Forecasts
This section discusses the extent to which the assumptions and methodology
underpinning the state revenue forecast are not explained, explained at a high level, but without a
clear connection to the forecast, and explained at a high level and clearly linked to the final
forecast.
[Table 3: Transparency of Southeastern States’ Revenue Forecasts]
In order to create Table 3, the researchers looked at the official revenue forecasting
documents for each of the fifteen southeastern states, searching specifically for information on
general macroeconomic trends in the forecasting document. Such trends could include housing
starts, employment rates, and US gross domestic product (GDP). The researchers wanted to see
if states were following best practice as recommended by GFOA and others by linking these
macroeconomic trends to the forecast. For instance, the state might link the income tax forecast
to personal income forecasts. If the document did not contain such information, the state received
an “X” in the column labeled “No Macroeconomic Information Explaining the Forecast”. If the
forecasting document did contain information on macroeconomic trends, but did not make clear
connections between those trends and the state forecast, the state received an “X” in the column
labeled “General Macroeconomic Trends without a Clear Link to the Forecast”. Finally, if the
state did clearly link the forecast to general macroeconomic trends, then it received an “X” in the
column labeled “Detailed Methodology with Direct Links to the Forecast”.
Four of the 15 states received an “X” in the first column, “No Macroeconomic
Information Explaining the Forecast”. These states only included a chart with the forecast
numbers, with no explanation of how these estimates were reached. Nine of the fifteen states
received an “X” in the second column, “General Macroeconomic Trends Without a Clear Link to
the Forecast”. These states included narrative about macroeconomic trends with a general
description of how they may affect the state economy; however, they did not detail their
methodology for how these trends brought them to their forecast number.
Only Virginia and Florida received an “X” in the third column, “Detailed Methodology
with Direct Links to the Forecast”. These states clearly linked the forecast numbers with these
trends or included detail on their methodology for how the macroeconomic trends brought them
to their forecast. For example, Florida’s estimate of revenue from the ad valorem tax is directly
linked to new construction and other important variables that affect that source of revenue. All of
these statistics are available online, so it is fairly easy to see how the ad valorem revenue
estimate was arrived at by the revenue estimating group. Virginia includes its revenue source
calculations in “The Economic Outlook and Revenue Forecast,” prepared by the Virginia
Department of Taxation for one of its forecasting groups, the Governor’s Advisory Council on
Revenue Estimates. These calculations show directly how the estimate for each revenue source
was developed.5
While the results of the analysis are interesting from a normative perspective, there is no
clear interrelationship between accuracy, consensus forecasts or transparency around the
methods that went into the forecast. Both Florida and Virginia have consensus forecasts. Florida
received a “B” accuracy grade in fiscal year 2015 and an “A” in 2016. Virginia received an “F”
in fiscal year 2015, but an “A” in fiscal year 2016; however, as noted earlier, it does not appears
that the revenue forecast in the budget actually reflected revenue expectations. That being said,
Virginia did struggle during the FY2015 year to arrive at a solid forecast, significantly
downgrading a forecast that ultimately turned out to be close to what the state had initially
predicted prior to the start of the fiscal year. But the state also did a significant and public
analysis of how the revenue forecast missed and what steps the state would take going forward to
avoid such errors. By way of contrast, Alabama does not include the macroeconomic
assumptions underlying its forecast, but it received “A” ’s in both years studied. Generally, most
5
It is pretty clear from Table 3 that different universities evaluating this question for the Volcker Alliance used
different decision criteria when assessing whether states provided a reasonable rationale for their revenue
estimates. Because the GFOA and others consider linking macroeconomic trends to the forecast to be best
practice, the Volcker Alliance might consider using these decision rules when answering Question 4 (“Does the
state reasonably support revenue growth projections at time of initial budget?”).
states seem comfortable providing general economic trends and then a forecast that is loosely
associated with these trends. This holds for executive states and consensus forecasting states.
However, the rigor around the Virginia and Florida processes is certainly appealing, and a more
expanded analysis of rigor, transparency and accuracy is warranted.
Political Acceptance of Southeastern States’ Revenue Forecasts
A further issue raised in Mikesell and Ross (2014) is political acceptance surrounding the
revenue forecasts in the southeastern states. The analysis looked in detail at five states, four of
which had some form of consensus forecast, and one of which had an executive forecast. While
it is difficult to prove a negative, there was no obvious evidence of the revenue estimate being
challenged in any of the states, even those with some intense partisan political conflict such as
occurred in Maryland and Virginia – certainly not in the open way that is visible at the national
level. The case studies of Maryland, Virginia, North Carolina, South Carolina and Georgia all
included a review of the revenue estimates as they moved across through the budget approval
process and all executive and legislative documents in the years studied mapped directly back to
the formal revenue estimate. In the case of Maryland and Virginia, where the legislature and
Governor were in different parties, the legislature did reverse a number of the Governor’s
proposed initiatives and newspaper articles as well as some budget documents reflect significant
conflict.6
Additionally, based on an initial review of news articles from the fiscal years 2015 to
2017, the researchers did not find any evidence of contested forecasts in any of the southeastern
states and conversations with researchers on the other southeastern teams found no evidence of a
contested estimate, although Alabama may bear further scrutiny. Further research on revenue
6
Add citations from Maryland 90 Day Summary and articles from VA about Medicaid expansion conflict and
possibly the session summaries.
estimation during highly charged periods such as the Great Recession may shed further light on
whether different processes are more effective at building consensus; additionally other regions
of the country may have different insights.
CONCLUSION
The state revenue forecast is an important aspect of the budget-forming process. In a
balanced budget environment, the forecast establishes a critical constraint on expenditures.
Because forecasts are affected by global, national and state economic conditions, revenue
collections are notoriously difficult to forecast. As Dadayan and Boyd (2014) found, states are
having a hard time making accurate forecasts even after the end of the recession.37 While
accuracy is important, it is also important that the revenue forecast is transparent and politically
acceptable. As Mikesell and Ross (2014) commented, revenue “forecast accuracy is irrelevant if
the budget process does not respect the forecast as a resource constraint.”38 In other words, a
forecasting process that lacks transparency and is likely to be unaccepted by political
stakeholders can be harmful to the state budget-making process, regardless of the forecast’s
accuracy.
Using data compiled for the Truth and Integrity in Government Finance project by the
Volcker Alliance, this paper examined revenue forecasting practices in the southeast and
generally found that on average the forecasts were more accurate than prior research would have
led us to anticipate. That being said, the 2015 and 2016 budget years were not particularly
volatile. Additionally, some of the case analysis of the circumstances around some forecasts
suggest that these cannot always be taken at face value: the forecasts exist in institutional as well
as political frameworks and for a variety of reasons, the anticipated revenues are not always the
same as the formal forecast. This finding is important when considering embarking on a larger
quantitative analysis assessing forecast accuracy or using forecast accuracy as an independent
variable. While certainly not determinative, there was little evidence that consensus forecasts
were consistently associated with improved accuracy.
In terms of transparency, only two states draw a clear line between economic
assumptions and the actual revenue forecast. Most states present some generic economic trends
and the forecast not explicitly connected to these trends. The rigor of states that clearly explain
their models is refreshing but more research would be required to validate their accuracy.
Last, when examining political acceptance or the legitimacy of the forecast, there was
little evidence that any of the forecasts faced a significant challenge, regardless of the
methodology or the process around the forecast. Again, this analysis is by no means
determinative but simply adds another observation or data point to broader theory. As observed
in the literature review, it is quite possible that the revenue forecasting process is endogenous to
political conflict – so high conflict situations lead to processes that help resolve the conflict,
whether this be consensus forecasts or other strategies.
24 | P a g e
1
McNichol, Elizabeth. 2014. Improving State Revenue Forecasting: Best Practices for a More Trusted and Reliable
Revenue Estimate. Center on Budget and Policy Priorities.
2
Mikesell, John L. State Revenue Forecasting in the State of Indiana. 2008. In Government Budget Forecasting:
Theory and Practice. ed. Jinping Sun and Thomas D. Lynch. 142: 415-429. Boca Raton, FL: CRC Press.
3
Klay, William Earle. And Joseph A. Vonasek. 2008. Consensus Forecasting for Budgeting in Theory and Practice. In
Government Budget Forecasting: Theory and Practice. ed. Jinping Sun and Thomas D. Lynch. 142: 379-391. Boca
Raton, FL: CRC Press.
4
Sun, Jinping. Forecast Evaluation: A Case Study. 2008. In Government Budget Forecasting: Theory and Practice.
ed. Jinping Sun and Thomas D. Lynch. 142: 223-240. Boca Raton, FL: CRC Press.
5
Tebbs, Jeffrey M. 2009. Breaking The Stalemate: A Proposal for a Consensus Revenue Forecasting Process.
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