Does State Pension Fund Management Matter?Siona Listokin

November 24, 2005

WORKING DRAFT – DO NOT QUOTE

AbstractThis paper examines how the management composition of public employee retirement systems affects the decision to increase retiree benefits. The results suggest that management boards that are dominated by political appointees or elected officials (“political boards”) increase benefits more than boards that are dominated by state employee representatives (“non-political boards”). In contrast to previous studies regarding pension fund management, state fiscal balance and general financial health are included, as is the role of the legislative body’s control over the retirement system. Political boards appear to be more sensitive the state’s financial health, and raise benefits more during “flush” years. Political boards are similarly sensitive to the state election cycle.s and the state’s fiscal balance than non-political boards. The paper explores possible explanations for the counterintuitive results.

I. Introduction

Public employee retirement systems cover over 14 million state and local government employees with

retirement and disability benefits.1 The 2,600 systems at the state and local level have combined assets

of almost $3 trillion in cash and investments; their combined equity holdings account for about 12% of

total outstanding US equity value (Ilkiw 2003). In an environment where state budgets face shortfalls

in excess of $200 billion, state retirement systems often account for large portions of state fiscal

planning, and annual obligations can amount to 5-15% of state deficits (Census 2002).

Who runs these financial behemoths? Management schemes vary, though most state systems have a

board of trustees that oversee general asset investment, benefits and disability arrangements. The

retirement board trustees are appointed in a variety of ways and have different qualifications; roughly,

trustees are either active or retired members of the retirement system (“non-political trustees”) or

appointed by the state government or voters (“political trustees”). Given the amount of money these

officers control and the relative freedom under which they operate, the governance of public employee

retirement systems is an important issue for state sponsor government, system beneficiaries and state

voters. This paper studies whether fund governance affects the provision of benefit increases. In

particular, I examine whether trustees chosen by system members behave differently than trustees

chosen by voters or the state government body, and the extent to which political operators are sensitive

to the state political and fiscal environment when making their benefit decisions.

Pension fund governance and board composition has been highlighted in a number of previous studies.

The vast majority of these papers focus on the relationship between board composition and investment

1 State employee retirement systems are also called state pensions and funds. I use these terms interchangeably.

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performance or fund solvency, and the studies are decidedly inconclusive (a thorough review of this

literature will follow). I shift the focus from the asset management side to the benefit side of

retirement system decision making. I can thus bypass many of the difficulties that plague previous

studies – such as endogenous asset mixes and investment restrictions – and better examine the effect

of pension fund governance.

My results suggest that board composition does influence the decision to increase benefits. Namely,

boards that are dominated by political trustees increase benefits more often and by a greater amount.

In addition, political trustees are sensitive to both state gubernatorial election years and shifts in state

fiscal balances. There is tentative support that political boards in Democratic states raise benefits

more than political boards in Republican states.

This study makes a number of contributions. First, it reexamines the question of public pension

system board influence in a setting that can offer more conclusive results. Second, it advances the

study of how the choice of managerial control of public retirement systems are influenced by political

and fiscal factors. More generally, the paper highlights the forces and incentives that may impact

management officers in charge of public moneys.

The paper proceeds as follows. Section 2 reviews the relevant literature, and section 3 describes the

relevant factors about public pension funds. Section 4 describes the data and methodology. Results

are presented in section 5 and section 6 concludes.

II. Literature Review

This study is related to two areas of research, the first on governance and agency and the second on

pension funds specifically.

Empirical and theoretical studies on corporate and public agency governance focus on the separation

between ownership and control. Relevant shareholders provide resources (mostly financial) to a

manager, whom they may not be able to properly monitor thereafter. Thus the principal-agent

problem arises, in this case that investors cannot be sure that managers are not spending their money

unwisely or otherwise acting opportunistically (see Jensen and Meckling, 1979; Shleifer and Vishny,

1997 offer a survey of corporate governance). Agency theory has had success in describing the

governance structures and contract arrangements that help solve the principal-agent problem given the

level of possible monitoring and differences between the two actors (theoretical and empirical

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examples include Williamson, 1971; Fama and Jensen, 1983b; Masten and Saussier, 2000; Bajari and

Tadelis, 2002).2

Agency theory in political models of organization examines the same principles of agent self-interest

and conflicts of interest between principals (mostly constituents) and agents (representatives) (March,

1962; Pfeffer, 1981). The mechanisms through which principals try to solve the agent problem are

through appointment types, voting and negotiations. In the case of public pension fund governance,

the fund trustees are the agents, who may have political career concerns that result in increasing

benefits too much or too often with regards to the health of the fund.

The logic of principal-agent theory suggests that elected officials should desire reelection and are

inclined to behave as their constituents desire. A full review of a state pension fund’s principals

(stakeholders) and agents (trustees) follows in the next section; suffice to say now that the

stakeholders include current public employees, former public employees, the state government, and

state taxpayers. Uncertainty and goal divergence creates agency problems, as when politically

motivated actions on the part of the trustees are not in the fund’s overall best interests, 3 or when fund

beneficiaries have exclusive control of the board and are not subject to outside vigilance from

taxpayers.

Beneficiary trustees, whose constituents are a well defined and fairly homogenous group as members

of the pension system, arguably have clearer voter interests than other trustees. These interests would

include high benefit levels and fund solvency. Political trustees, in contrast, have varied constituent

groups. This condition is known as common agency, and opens the door to special interest group

maneuvering (c.f. Berheim and Whinston, 1986; Grossman and Helpman, 2001). Trustees elected by

the entire state may be sensitive to non-public employee voters’ concerns that higher benefits lead to

higher taxes in the future; these trustees would also be aware of the public employee special interest

group. Finally, trustees that are appointed by the governor may be highly sensitive to the governor’s

interests.

The major set of empirical studies about pension fund governance focuses on principal-agent

considerations where fund trustees may have differing interests than the vast majority of the system’s

stakeholders. (Impavido and Hess (2003) outline the agency considerations relevant to pension fund

governance.) Empirical research on public pension fund governance is somewhat unique in that there

2 Note that the governance literature focuses on the question, described by Jensen (1983) as “why [do] certain contractual relations arise?” This study examines the opposite mechanism: how does certain contractual/governance structures affect outcomes?3 A well cited example is the case of a former political trustee member of the NYC pension fund board who publicized her corporate governance activism while part of the board of trustees, even as she was criticized for acting outside of the fund’s interests (see Romano 2001).

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is more varied work on international pension systems than US public funds, and as noted the work to

date often focuses on fund performance and solvency. Impavido (2002) gives a thorough review of

both the international and US domestic literature. Many of the conclusions in this literature suggest a

correlation between countries with poor governance records (e.g., high levels of corruption) and poor

investment returns (see, for example, Iglesias and Pacios 2000). Despite a fairly robust theoretical

understanding of where agency problems might impact public pension fund governance and outcomes

and papers that focus on international pension systems, empirical studies of US public system

governance remain inconclusive.4

The major thrust of this empirical research has been conducted by the Pension Research Council at

Wharton (for example, Mitchell and Smith 1994; Yang and Mitchell 2004; Mitchell and Hsin 1997;

Useem and Mitchell 2000), and the release of longitudinal PENDAT survey data has greatly increased

the available information regarding public pension board governance, investment behavior and

restrictions, and actuarial reviews. However, there remain very few papers that utilize the longitudinal

aspect of the data in their pension studies, and the vast majority of these studies focus on the

management and investment practices’ effects on funding flow and fund performance. Yang and

Mitchell (2004) provide a thorough review of both the cross-sectional and panel data papers; I will

highlight important conclusions and remaining questions.

Useem and Mitchell (2000) show that pension governance affects asset allocation and independent

financial management. They find that non-political boards are associated with less external

investment management and less equity investment. The Useem and Mitchell study is interesting

because it mainly uses fund management practices – rather than fund financial performance – as its

dependent variables (though they do look at financial performance as well, with no results). Their

study, however, is empirically limited in that it examines only one year (1993), and cannot distinguish

between asset allocation targets that are set outside of the purview of the board of trustees and those

targets that are set expressly by the board. Useem and Mitchell do limit their sample to funds that do

not have constitutional restrictions on investments. Pension systems, however, are subject to

numerous outside restrictions, such as pension charter in-state investment targets. Their paper is

illustrative of the difficulties in studying pension funding levels and investment performance, which

may be endogenously determined – since asset targets may have been set along with the board. (Other

examples of papers that encounter these difficulties include Inman 1986; Mark 1997; and Coronado et

al. 2003.) Given the difficulties involved in relating pension fund governance to funding and

investment performance, the question remains: does pension fund governance affect outcomes, and

how might board composition influence fund decisions?

4 Romano (1993), Useem and Mitchell (2000) and Mitchell and Hsin (1997) offer a stark example of this contradictory conclusions. Using variations of the same survey (over different years), the papers show negative correlation between political trustees and fund performance, no significant correlation between board composition and performance, and positive political trustee correlation with performance, respectively.

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For all the inconsistencies in the studies focusing on fund financial performance, there is only one

study I have found that touches on fund governance and benefit decisions (Murphy and Van Nuys

1994). These authors hypothesize that beneficiary trustees are relatively risk averse and value income

stability highly, and make benefit decisions that enhance the security of benefits (p3). Their paper

suggests that a 10% increase in the number of non-political trustees on the board translates into an

average annual benefit decrease of $852 – a surprisingly large result. The Murphy and Van Nuys

paper, too, is fraught with measurement problems, including a small sample size and an assumption

that there are no state-specific characteristics that may drive part of the results. Another limitation of

their study – and one that the authors point out themselves – is that their dependent variable only

includes the retirement benefit, while my data includes other areas of benefit increases such as health

and disability benefits. (More on this construct follows in the section describing data.) The Murphy

and Van Nuys paper suggests a positive correlation between political board composition and benefit

levels, but due to the nature of their data they are unable to conclude that there is causality.

Further areas of study regarding benefit levels and increases remain unexplored, such as how

exogenous market and fiscal conditions impact boards’ benefit decisions. In papers unrelated to

benefit decisions, Mark (1997), Chaney et al. (2002) and Schneider and Damanpour (2002) examine

how exogenous factors, such as stock market conditions and state budget balances, relate to funding

levels, though they do not relate these outside conditions to governance. I have not seen a study that

examines the effects of exogenous political factors, such as political party control and electoral

competitiveness, on either funding or benefit behavior.5

To summarize, a good deal of work has explored the influence of public pension fund governance on

funding levels and investment performance. Perhaps due to data limitations, these studies are

inconclusive and often directly contradictory; questions fundamentally remain as to the effect of board

composition on system outcomes. System benefit decisions are particularly understudied, as is the

impact of exogenous factors. In his 2002 World Bank survey, Impavido concludes that “(However,) a

direct link between governance and performance cannot be established with US data… A few results

are contradictory, like the impact of the size and composition of the board… Further research is

clearly needed.” (p 6)

III. Public Pension Funds

The first incarnation of US public pension schemes were intended primarily for army personnel in the

mid-19th century (March, 1962). State pension systems began with teacher and firefighter systems,

and truly grew in the 1930s by which time, state and local public pension outlays totaled $106 million

5 Schneider and Damanpour (2002) do look at the percentage of voters in a given state.

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(March 1980). In 2003, state and local plans held around $3 trillion in assets (Ilkiw 2003), and there

are 2,600 systems at the state and local level (GAO, 1996). While public retirement systems were

originally intended as forms of social welfare programs, today they have evolved into an integral

incentive to work for the government. Public employment offers a number of attractions, including

health care, job stability and retirement benefits (Lowenstein 2005). In the US, a state or local

government employee who has fulfilled his/her system's requirements receives an average of about

$1,400 a month (Census 2000).

The vast majority of public pension funds are run as defined benefit systems, meaning that the sponsor

(e.g. state public schools) and sometimes the public employee make regular contributions to the fund,

which is invested (saved) and from which benefits are paid to current retirees. Retirement benefits are

calculated by a schedule of factors, such as tenure, salary and retirement age, and are generally

updated for cost-of-living adjustments (COLAs) through formulas that are connected to CPI. The

upshot is that benefits are well established -- though often confusing to calculate -- while contributions

by the government sponsor can vary over the lifetime of an employee's tenure.

Fund health is determined through the plan's funding flow. The funding flow is the ratio of

accumulated assets to the pension benefit obligation (PBO). It is thus considered a good “stock”

measure, in that the cumulative financial health of the systems is considered, rather than a measure of

the fund’s ability to pay the following year’s requirements (Mitchell and Smith 1994). Both

components of the funding flow measure (assets and PBO) can be difficult to determine, especially

because actuarial assumptions are not clearly outlined. One stark example is the discrepancy between

reported funding flow, which measures about $300 billion in the red for all state and local systems,

and private assessments of public pensions’ funding flow, which can measure up to $460 billion in

deficit (Barclay’s Global Investment 2005). The difference between these measures lies in either

interest rate assumptions or definitions of the PBO. In general, the PBO is composed of obligations:

1) pledged to currently retired employees; 2) vested to terminated employees; 3) vested to active

employees; 4) payable to non-vested active employees who may vest in the future; and 5) those that

will be earned by current workers resulting from future salary increases (Mitchell and Smith 1994).

A fund is said to be underfunded if the assets are not sufficient to cover the projected liabilities, and

will instead rely on future contributions (i.e., heading towards pure pay-as-you-go), surprise increases

in investment returns, or other sources of increased assets (e.g., tax increases). A funding ratio of zero

corresponds to a pure pay-as-you-go system; a funding ratio of one means that the fund's current assets

are sufficient to cover the present value of projected liabilities. Severely underfunded systems must

adjust contributions or asset allocation in order to cover obligations.

Stakeholders

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The structure of these defined benefit systems means that former public employees drawing benefits

are not the only population with a vested interest in public pension funds. Current government

employees have a stake in both their future retirement benefits and current contribution obligations.

Current and future public employees are known as the fund beneficiaries. The pension sponsor,

responsible for employer contributions and future liabilities, is also a stakeholder, as are the officers in

charge of the fund. Every state pension fund in my sample is protected by either state law or

constitutional provision in that the state is obligated by statute to meet its obligations. States can issue

government bonds, raise taxes or shift other government revenue to the retirement systems if the funds

face insolvency; whatever the method, liabilities must be met. All taxpayers are therefore stakeholders,

as residual claimants of the public pension systems.

While insolvency requiring emergency bailout by the state is rare, underfunded plans are not. In 1993,

close to 75% of all state pension plans were underfunded; about half were underfunded in 2001. Part

of the fluctuations in funding flow is determined by equity performance. As more and more public

pension funds increase their asset allocations to the stock market, they become more sensitive to

movements in the market.

Defined benefit plans include provisions for benefit increases. The vast majority of benefit increases

are COLAs. While these are occasionally tweaked -- for example, changing from an adjustment equal

to annual CPI up to 3% to a fixed increase of 2% every 2 years -- they are generally stable and do not

significantly vary on average over time. Benefits can also be changed for a host of other reasons (for

example, to make public employment more desirable, under political pressure). I am interested in

these ad hoc benefit increases.6

Fund Management

While there is variation in the organizational and management structure of public pension funds, most

follow the same general formation. Executive officers and administrative staff are responsible for

programs and day to day activities. The retirement systems vary in administration and investment of

retirement fund assets, and membership and benefit issues. The vast majority of these pension systems

have a board of trustees that make benefit decisions. There is considerably more variation in

investment control decisions. About 60% of the funds place investments under the control of the board

of trustees, though the extent of trustee involvement in actual investment decisions appears to vary

greatly. Other arrangements include investment and benefit committees, a public equivalent to a chief

investment officer at private pension funds and additional decision structures.

6 Excluding COLA differences between systems allows me to study the specific issue of increasing benefits, but results in a dependent variable that does not fully capture benefit changes. I will discuss this issue in a later section.

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The board of trustees consists of an average of 10 officers, though size varies from 5 to 17 officers in

my sample. Board members are chosen by gubernatorial appointment, elections by the general

population, or elections by current and future public retirees. I designate trustees that are appointed or

elected by the state as political trustees, and those chosen by the fund members are beneficiary

trustees. Many boards have a combination of trustee types, thus ensuring that sponsor citizens (e.g.,

state voters) and fund beneficiaries are both represented. The trustee types seem to differ along a

number of dimensions, including tenure, career path and expertise. While I do not have

comprehensive data, I checked the board tenure for the current boards of 26 of the retirement systems.

This rough examination shows that the average tenure of beneficiary trustees is about 5 years longer

than political trustees, and about a fifth of the beneficiary trustees have been involved in fund

management for more than 20 years. The differentiation in time span may be a factor in their benefit

decisions, and I explore this possibility later in the paper.

The decision making process varies by fund. Here too, I do not have comprehensive data on

procedural rules, and the information has been culled from retirement system information packets and

board meeting minutes. Of this sample, I found a few funds that have formal voting minimums for

budget proposals (e.g. benefit increases), requiring a majority.7 In the systems where I did not see a

voting minimum (although it may exist), I examined meeting minutes to learn about the group

decision making process. While discussions are obviously highly condensed in published meeting

minutes, the votes recorded are overwhelmingly unanimous, suggesting that a consensus view is

determined at some point during the meeting. Although I cannot make strong conclusions about the

overall board procedures, my inspection supports the study in that different board composition may

impact decision making, either through formal voting or in reaching consensus.

What is the board's legal fiduciary responsibility? Private fund management boards are obligated to act

in the interests of the fund beneficiaries by the Employee Retirement Income Security Act of 1974

(ERISA). Public pension funds do not have an analogous federal law mandating fiduciary

responsibility (Romano 1993). Many states, however, have varying degrees of ERISA-like statutes for

the fund board. One popular guideline for public board decision making is the "prudent man" standard,

which holds that "a fiduciary must discharge his or her duties with the care, skill, prudence and

diligence that a prudent person acting in a like capacity would use in the conduct of an enterprise of

like character and aims." There are differences across government sponsors regarding the strength of

their fiduciary responsibilities, and certainly no standard across systems.

IV. Data and Methodology

7 Alabama Employee Retirement System, for example, requires approval by 8 of 14 trustee members.

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My data comes from a number of sources. A significant portion of the structural elements of the

systems comes from the PENDAT survey. The PENDAT survey is a biannual longitudinal study of

state, county, municipal, city, district and other local pension systems in the US administered by the

Public Pension Coordinating Council. It includes detailed information about board composition, term

limits and legislative restrictions, as well as reliable funding flow reports. I supplement the PENDAT

survey with the Public Fund Survey, the Wisconsin Comparative Study of Major Public Employee

Retirement Systems, and the State and Local Pension Exchange. Remaining data is collected from the

National Association of State Retirement Administrators (NASERS), the National Conference of

Public Employee Retirement Systems, the National Council on Teacher Retirement, and the Census

Bureau. Where possible, I use system websites and conversations with system employees to confirm

and fill in data. Benefit data is double checked and supplemented with survey data from RV Kuhns

and Wilshire Capital.

The data sample consists of state employee retirement systems over the decade between 1993 and

2003. As the data is only collected every other year, that results in six years of information between

1993 and 2003. Given the difficulties of the previous studies, I restrict my data set to those state and

special systems whose board of trustees control benefit decisions. This reduces the number of systems

available in my sample by about 40%, however the study cannot be conducted reliably otherwise.

Variables

Dependent Variable

I am primarily interested in the determinants of both the incidence and extent of benefit increases, and

therefore require an accurate measure of changes in system benefits. Benefit changes, however, can

be difficult to calculate for a variety of reasons, most notably the wide range of norms used in benefit

formulas. I use three different variables as constructs of benefit increases as robustness checks.

My primary dependent variable is year over year change of self-reported “accumulated benefit earned

as a % of final average salary (FAS).” This number is reported for different levels of years of service

(5, 10, 20 and 30 years of service); I use the percentage from 30 years of service because that is the

longest and most frequent FAS formula. The unique aspect of this measure is that it does not measure

benefits to current retirees, but rather the benefit calculation for active and retired members (in other

words, it measures a benefit increase for retirees and for active member obligations going forward).

This is a crucial, and hard to find, measure. The downside of this variable is that it does not

differentiate between FAS calculations.8 However, insofar as the percentage of FAS changes from

system to system it can still be an accurate measure of the extent of a benefit increase.

8 Common FAS calculation variation occurs in whether it is an average of the previous year, average of the previous five years, the average of the highest year in the previous five years, and other “compensation” components that are included in FAS.

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My second measure of benefit changes is simply a binary variable that equals one if the system raised

benefits during that year. While this construct only gives an indication of whether there was a benefit

increase, it is self-reported in the PENDAT survey and its reliability is strong. The benefit increases

here are ad hoc increases, meaning they are outside of changes to COLAs.

Finally, for a third measure I take the year over year change in PBO, adjusted for the previous year’s

actual benefit expenditures. This measure makes a number of assumptions, most prominently that the

system did not significantly change its hiring procedures from year to year.

For the years 1995-2003, I have a breakdown of the benefit expenditures into four components:

service (retirement payments to retirees), disability (payments to disabled retirees and active

members), health (partial health benefit payments to retirees and active members), and survivor

benefits (payments to deceased partners of retirees and active members). While only the service

measure is dedicated to retiree benefit payments – the main focus of this study – the remaining three

categories are directed primarily at retired members. The data in year 1993 is only given in aggregate

form. I therefore include all categories in my measure in order to get the most accurate metric of true

benefit changes, and to keep the measure consistent throughout my study period. I adjust for inflation

(all expenditures are baselined to 1993 dollars).

Independent Variables

My primary explanatory variable measures the board composition. I use a binary variable set to one if

the board of trustees of a pension system is composed of more than 50% political board types. 9 Ex

officio and appointed trustees are considered political trustees, whereas the board members chosen by

beneficiary members are considered beneficiary trustees. This board data was collected from

PENDAT and pension system websites. Personal data collection and review was especially vital for

“special” state systems, namely those beyond the teachers’ and general state employees’ retirement

funds, as the PENDAT data tended to replicate board composition in these instances.

I control for the systems’ level of benefits and fund solvency in the previous year. Controlling for

benefit level is important in order to determine what drives the changes in benefits. Perhaps boards

change benefits when the benefit level is low, in which case board composition would be less of a

factor. To measure the level of benefits, I divide that year’s benefit expenditures by the number of

benefit recipients.

Next, I control for fund solvency using the funding flow measure explained previously. The funding

flow is an important control because solvency could reasonably be a major determinant of benefit

9 Note that since I do not have decision rules for each of the funds – and it certainly seems that many boards do not use majority rules – the choice of 50% composition is not necessary. I choose the majority level as a cutoff to suggest that majorities can drive consensus and influence outcomes.

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changes. For example, one could imagine a fund deciding to increase benefits when the fund is

overfunded, and to keep benefits steady when the system is underfunded. For the funding flow, I use

the PENDAT data to get the systems’ pension benefit obligation (PBO) and current level of assets at

market price. I divide the PBO by the market value of total assets to get the funding flow. This

measure is cross-checked with actuarial reports of funding flow levels and lagged one time period.10

In order to consider the ongoing tradeoff between salary and retirement benefits, I control for monthly

salary. This data comes from the Census Bureau’s state statistical abstracts, where the average public

employee salary (for either March or October of every year) is broken down by job function. The

categories included in the census match nearly all of the system-types in my data (for example, the

Census differentiates between teachers, judges, government employees, and judiciary). For states that

have only one state system, I use the average state monthly salary. (Note: I am only able to do this

because the census data differentiates between state, city, county, and other governmental employees.)

I also control for certain state characteristics in given years. I control for per-capita income in order to

control for general increases in state welfare that could influence benefit decisions. I proxy for state

employee service quality with a density measure of the number of state employees per 1,000 state

citizens. Both of these variables are collected from the Census Bureau.

Descriptive statistics can be found in Table 1. The PENDAT survey covers many more public

retirement systems than I use in my data set; only the relevant set of systems are included in this

table.11 There are 163 systems that qualify for inclusion. Of these, 27% have a board that is

dominated (50% or more) by political trustees. It is interesting to note that while I have defined a

political board as one composed of more than 50% political trustees, my results are similar when my

definition is looser; I can relax the political cutoff to 40% without significantly changing my results.

This may be a consequence from the “consensus” style of decision making on boards mentioned

previously; the results are not driven by majority rule by political trustees, but rather a strong presence

of political trustees on the board.

The descriptive statistics highlight the relative frequency of benefit increases, which occur in 70% of

the system-year observations. This may be a result of frequent “tweaks” to the benefit formulations.

The other primary measure of benefit increases changes less often, but the average change is large (9%

change). For this and other reasons, I focus my identification on the continuous variable, as it seems

to be a more realistic measure of benefit changes in retirement systems.

10 Note that this funding flow is in fact a stock measure and not a flow measure (despite its name), meaning that it measures the systems ability to fund its projected liabilities. Flow measures the system’s ability to pay for the current year’s obligations. Funding flow is the accepted name in private and public actuarial calculations.11 I do not include city, county and municipal systems. I only include systems where the board has control over benefits.

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The data also indicate that 65% of the retirement funds require state legislature approval for its annual

budget. This legislative process can complicate my study, in that final approval for benefit increases

may not lie with the board of trustees, but with the state sponsor government. Benefit decisions at the

board level may be influenced by the board’s expectations of final approval by the legislature;

alternatively, political boards may have more success in pushing through benefit increase decisions

through the government. This will be an area of future research, in order to get a fuller picture of the

relationship between board recommendations and legislative approval. For the moment, this study

highlights the marginal effect of board composition on benefit decisions.

Methodology

Using probit and OLS regression analysis, I first seek to determine if boards that are dominated by

political operators are more likely to raise benefits and/or increase benefits by more than boards

dominated by fund members, controlling for the fund’s lagged level of benefits, lagged level of system

salary, the fund’s lagged solvency, and state characteristics, such as income level and the number of

public employees per 1,000 citizens. This base result is difficult to identify, since there may be

unobservable system characteristics that affect the benefit decisions systematically, which would bias

the results. For example, suppose the California public school teachers had undue influence over all of

the board members of CALSTRS (The California School Teachers Retirement System). The

CALSTRS benefit decisions would thus be partly a product of the unique relationship between

teachers and board members, and this effect would persist over the decade under study. I would not be

able to identify this type of relationship in my data set, and so results that suggest a board-type effect

may in fact be a system-relationship effect.

Generally, there are two main ways to control for these system effects. The first is to include system

fixed effects (basically, dummy variables for each system) in the identification, which would capture

any unique, systematic fund characteristics that could influence benefit decisions. The second general

method would be to look at systems that have experienced a board-type change. If there was a change

in benefit behavior within systems that had changed their board, it would suggest that the benefit

decisions are in fact a result of the board-type and not the systems. Both these methods, however,

require that pension system board-types change during the period I am studying. Board-type changes

are incredibly rare, however, and after I drop systems that do not meet base requirements for this

study, I have only six board changes.

I use state fixed effects in order to get at the question of whether political board-types raise benefits

more than beneficiary board-types. The state fixed effects control for unobserved state-specific, time-

invariant characteristics that would influence benefit decisions. To the extent that systems within a

certain state would share the unique characteristics that could influence benefit decisions, the state

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fixed effects can capture these unobserved effects. In the CALSTRS example, this method would

control for those unique aspects of California that would give state public employees undue influence

over their respective pension system boards. To the extent that the California teachers’ special

relationship with their pension is shared across other California state employees, state fixed effects

would be sufficient. The main question is whether the unobservable variables are unique to California

or CALSTRS.

The baseline estimation for the OLS regression model is:

(1)

where i denotes a unique system, are system control variables, are state control variables,

are year fixed effects and are state fixed effects. This model seeks to determine if board

composition affects benefit increases. In order to go beyond this basic “effect” question, I examine to

what extent, and under what conditions, the board composition influences benefits. I look at the board

impact under different political party dominance (proxied by gubernatorial affiliation), during

gubernatorial election years, and under varying levels of state fiscal health and decline. For these

estimations, I am looking for complementarities between these factors and the board composition. For

example, in the case of gubernatorial elections, I test: 1) whether board composition matters to benefit

decisions regardless of whether the state faces an election year or not; 2) whether benefit increases are

different during election years versus non-election years; and 3) whether political boards are more

sensitive to election years in their benefit decisions than non-political boards. The third effect is

perhaps the most interesting, as it serves to confirm the baseline results and gives a contextual picture

to the manners in which board composition is important. If there is an interaction, then it suggests that

political boards are susceptible to electoral pressure to raise benefits.

The interaction estimations are: (2)

where state factor is either a political party dummy, an election year dummy, or the state

surplus/deficit (which vary by year).

V. Results

Does board composition affect benefit increases?

Table 2 shows the difference in means between political boards and non-political boards. The table

suggests that there are differences in benefit increase levels between the two types of boards: the

13

average benefit change is higher by about 4-5 percentage points with political boards, and this

difference is significant at the 1% level.12 The difference is not significant for the binary benefit

variable. While these univariate results cannot be conclusive, they do suggest that we can differentiate

benefit behavior by board composition.

Baseline multivariate results are found in table 3. Columns 1-3 use a fixed effects regression on

benefit changes. This identification has the largest sample and the strongest results. Regardless of the

state and system controls used, the results show that political boards increase benefit increases by over

3 percentage points more than non-political boards. The previous year’s benefit levels have a negative

influence on benefit increase, supporting the view that the benefit increases are higher when the base

level of monthly benefits is low. This effect is large and significant, corresponding to a 5 to 9

percentage point lower benefit increase for every increase of $100 in the previous year’s average

benefit level.13

Column 3 differs from column 2 only in that it excludes the six retirement systems that actually

changed their board composition during the decade. This extra estimation serves as a check that the

results are not purely driven by these six board changes; the results show very little change when the

relevant systems are not included.

Columns 4 and 5 use a probit model with the binary dependent variable equal to one if the system

increased benefits in a given year. The coefficient on the board type dummy is significant but small,

corresponding to about a 1% increase in the probability of a benefit increase when the board is

dominated by political operators. Columns 6 and 7 use the PBO extrapolation of benefits, and results

are not significant.

The baseline results in table 3 demonstrate that board composition is an important factor in the extent

of benefit increases. These results correspond with Murphy and Van Nuys’ (1994) conclusion that

greater beneficiary representation on retirement fund boards leads to lower benefits and less increases.

The conclusion may seem counterintuitive: why would political boards raise benefits more than boards

dominated by beneficiaries? After all, beneficiary trustees are current or future retirees themselves,

and they are chosen by government employees. It is reasonable to assume that the beneficiaries are

aligned in their desire to increase benefits. Murphy and Van Nuys hypothesize that beneficiaries are

more conservative than political trustees, and are more concerned about the long term solvency of the

fund. Another factor may be the difference in career paths of the two types of trustees. (I elaborate on

12 To clarify: percentage differences refer to level of benefit increases. In this case, there is a 4% difference between political and non-political boards; it refers to the difference between, for example, a 2% benefit increase and an 6% benefit increase. 13 This effect is actually less extreme than it may seem, as benefits average about $1,400 monthly for state employees. An increase of $100 would be a substantial step.

14

this in the discussion section. Without better controls for system characteristics, this result may be

driven by omitted variables bias.) To compare the motivations of political and non-political boards, it

is helpful to get a picture of what drives the political boards to increase benefits. With this

information, I may be able to better explain why political boards increase benefits more than their

beneficiary trustee counterparts. I therefore examine outside conditions that may influence the

political boards to test the sensitivity of board composition.

Is there a difference in board composition impact based on state political party?

Table 4 begins this examination by looking at the role of state political party in benefit decisions and

board composition. Perhaps political board’s proclivity to increase benefits more than non-political

boards is only true when Republicans or Democrats hold the gubernatorial power. To test this

possibility, I run the same regression as in the previous slide (with reported benefit changes as the

dependent variable) and split the samples into “Democratic” and “Republican” states. The political

party of the state is designated as the governor’s political party. The results show that regardless of

political party, political boards still raise benefits more than non-political boards. There is a

significant difference, however, in the extent of the benefit increment between Republican and

Democratic states. In states with a Republican governor, political boards increase benefits by about

1.5% more than non-political boards; the difference between board types grows to 5.5% in states with

a Democratic governor. The difference between these coefficients is significant at the 99% confidence

level. Likewise, lagged benefits have a greater negative effect in Republican states than in Democratic

states.

The results suggest there is a greater “political governance” effect in Democratic states than

Republican. Political boards in states with a Democratic governor behave significantly differently

than political boards in states with a Republican governor, in their differentiation from non-political

boards. Many factors may drive this result. Public employee unions traditionally have stronger ties to

and support from Democratic politicians, and political boards in Democratic states may be more

receptive to using their managerial control in response to union requests for higher benefits (see, for

example Zander 1962 or Shaffer 2002). This explanation, however, does not fully explain why

political boards in Democratic states would be so different than non-political boards.

Do election years change board composition impact on benefit increases?

A state’s dominant political party seems to influence the extent of the disparity between board types,

which suggests that the political environment is an important part of my study. In order to examine

other areas of political variation, I look at the effect of gubernatorial electoral cycles on benefit

increases, and how board composition interacts with election year influences. These results are found

in table 6. The first column shows the results for the full data sample. Benefit increases are 1% higher

during election years, regardless of board type. Further, benefit increases are 0.06% higher when both

15

the board is political and it is an election year (at a 90% confidence level). In other words, political

boards raise benefits more than non-political boards, and this effect is more pronounced during

election years. While the 0.06% effect may seem economically small, recall that public pension

funds’ benefit expenditures can be huge. In 2001, this increase corresponds to about a $15 million

increase in annual benefit expenditures for the average pension system; for CALPERS, the figure

translates into about a $250 million in added annual benefit expenditures. This election effect is

interesting, for both its direct and indirect implications. First, it may indicate that benefit increases are

election tools, as they are more pronounced in election years than non-election years. Second, the

positive interaction effect between elections and political boards suggests that political boards are

more sensitive to political factors such as elections than non-political boards. This may not be a

surprising deduction, but it is now supported by statistical evidence.

Columns 2 and 3 compare the election effect between states that are politically competitive and states

that are not politically competitive. A state is defined as politically competitive if there was a switch

in gubernatorial political party (e.g., in New Jersey the governor position went from a Democrat to a

Republican in 1994) or if at least one gubernatorial election had less than a 15% vote split (e.g., in

North Dakota in 2002, a Democratic gubernatorial candidate won with 52% of the vote, compared

with a 48% vote capture by the Republican candidate). There is not a significant difference in the

election or interaction effect; however, the board composition effect is significantly different between

the two types of state political competitiveness. I cannot draw conclusions from this result. I run a

similar comparison in columns 4 and 5, this time between Democratic and Republican states. Again,

there is not a statistically significant difference between the two types of states and the election effect.

Do state finances change board composition impact on benefit increases?

In addition to political factors, I also check if the state balance complements the board composition

effect. The results can be found in table 6, and suggest that while the state fiscal balance may not

influence benefit increases on its own, political boards do increase benefits by a greater amount than

non-political boards, and this effect is positively sensitive to the state fiscal balance. This interaction

effect is smaller than the election year effect noted earlier, but it does indicate that political boards

may be aware of the state’s fiscal affairs when deciding to increase benefits.

VI. Discussion

My present results suggest an interesting relationship between public pension board composition and

the decision to increase benefits. Public pension funds with boards that are dominated by political

trustees are more likely to increase benefits and increase benefits by more a greater amount than

boards that are dominated by beneficiary trustees. In addition, my study suggests that pension fund

16

boards are influenced by electoral cycles, political party dominance, and state fiscal levels. These

exogenous factors have not been examined in previous studies of pension fund governance.

While it seems clear that political boards are influenced to some degree by political considerations and

fiscal realities, it is still unclear why political boards raise benefits more than non-political boards.

Recall that I have defined non-political boards as those boards that are dominated by beneficiary

representatives. One might expect beneficiaries to have strong preferences for higher benefits, and

their representatives on the board of trustees would have strong incentives to increase benefits

significantly. Why do political boards increase benefits more than beneficiary boards?

In their 1994 paper, Murphy and Van Nuys suggest that beneficiary trustees “represent the interests of

active and retired state workers, who are likely to be more risk averse than the population at large, and

facing the prospect of living off of their retirement checks (pg 31).” The authors go further and

propose that beneficiaries are more interested in secure inflation adjustments than benefit increases

(recall: inflation adjustments are not included in my benefit increase variable). Murphy and Van Nuys

show preliminary correlations between beneficiary trustees and higher COLAs, subject to the data

complications mentioned in the literature review. The conclusion they draw is that beneficiaries prefer

high, secure income streams rather than occasionally large jumps in their benefits that cannot be

foreseen. If so, it may be that beneficiary boards increase benefits less in exchange for higher cost of

living adjustments, while political boards prefer the more unpredictable benefit increases as they can

be used opportunistically. In my conversations with employees of two public employee unions

(American Federation of State, County and Municipal Employees, and Communication Workers of

America), this “exchange” possibility was supported: they suggested that variations in COLA

formulas can be a tool of benefit increases that beneficiaries may prefer.

Another possibility to explain why political boards increase benefits more than non-political boards

involves the differing career paths of trustees. While accurate data is unavailable, a quick check of the

retirement systems’ websites indicate that many of the beneficiary trustees are “lifers,” in that they

have been trustees for well over a decade. The political trustees, on the other hand, have shorter time

spans on the boards, partly as a natural consequence of the state electoral process (e.g., the political

trustees can get voted out of office for issues unrelated to the pension fund). The differentiation in

career focus may naturally make beneficiary trustee more forward thinking since he expects to remain

on the board in the future, while political trustees are concerned with a shorter, electorally driven, time

period.

These possibilities present interesting areas for future data collection and research. In addition, there

are certain caveats in interpreting my results thus far. First, my measures of benefit increases are

imperfect. The reported formulaic changes, taken at an average level, may not be an accurate measure

17

of the increased costs or employee windfalls of the benefit increases. While I have tried to alleviate

these weaknesses by using three measures of the construct, I cannot be certain that my results capture

what I intend. Also, the level of state employer contributions is not accounted for in my data. Just as

the pension boards in my sample have control over benefit levels, they also control the rate at which

the state employers (e.g. public schools or police departments) must contribute to the fund. Thus,

boards could choose to fully fund their benefit increases with contribution increases. Alternatively,

boards could choose to pass the financial burden of the benefit increases to the future. My results

cannot distinguish between these highly different alternatives. It would be of great empirical benefit

to have data about contribution levels; I could then determine if board composition affects the choice

to “pay now or pay later.”14

I would like to get a clearer picture of the legislative approval process. To what extent do the boards

control benefit decisions if legislative approval is required for annual retirement system budgets?

Previous studies have used different measures of the board control; in one paper, a board composed

completely of political trustees with control over benefits is considered a “legislative” control instance,

while other papers consider the same case as being “board” control. Ultimate control may be a soft

variable, in that some boards have a tacit understanding of the extent of their control pending

legislative approval. One AFSCME employee suggested that even in cases where the board must go

to the legislature for approval, the trustees are responsible for projections and recommendations.

The conclusions of this paper lead to a number of implications. The most general is that pension fund

governance matters, at least insofar as the decision to increase benefits. As pension funds continue to

be plagued with massive underfunding yet repeatedly raise benefits, it is important to understand that

the management structure found in the retirement systems’ boards of trustees can impact the extent of

benefit increases. Additionally, the study suggests that concerns outside of fund solvency influence

the governance effect (indeed, fund solvency did not seem to lead to benefit increases at all). As a

result of runaway benefit burdens, many states are looking to shut down their defined benefit pension

systems in favor of defined contribution programs, where benefits are determined by investment

returns. (See, for example, the public employee retirement systems in Alaska and Michigan, which

have closed their programs to new employees. Arizona, California, Colorado, Ohio, Montana and

South Carolina are moving toward defined contribution, or seriously floated the idea.) In essence,

these states are choosing to wrest control over benefit increases away from trustee boards or

legislatures, despite massive upheaval costs. As other states consider how to deal with ever-escalating

benefits, it is paramount to understand the governance dynamics that led to the present state. A recent

New York Times Magazine article summarizes the implications of continued ignorance about this

issue: “The average voter doesn’t take notice when the legislature debates the benefits levels of

14 Contribution data is available as a PENDAT survey file. I hope to receive this data, but I cannot say for certain if it will vary.

18

firemen, teachers and the like… So benefits keep rising… [Eventually], you start firing cops and

teachers (NYT Magazine, 10/31/05).”

19

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22

Appendix

Table 1: Descriptive Statistics

N (unique observations) Mean Median SD

Systems 163Board of Trustees

Beneficiary Trustees (%) 163 0.28 0.47 0.31Political Trustees (%) 163 0.47 0.33 0.25Board Type (=1 if political) 163 0.27 0 0.44Trustee Term 57 4.23 4.0 0.87

Benefits

Benefit Increase Dummy (=1 if increase) 369 0.7 1 0.46Percent Benefit Change 949 1.09 0 0.20COLA Change 516 0.27 0.28 0.28Current Benefit Level 949 1550 1359 1334

System FinancialsFunding Flow 949 0.91 0.91 0.78Assets (market value, $mil) 848 10,304 5,163 12,869

Procedures

Benefits Gauranteed by Statute 97 0.87 1 0.34System Budget Approved by Legislature 97 0.65 1 0.48State Vote Required for Change in Benefits 97 0.03 0 0.17

Table 2: Means Differences

Political Board Non-Political Board ttest

Benefit Increase Dummy (=1 if increase ) 0.7283 0.6963 1.6230

Benefit Change 1.0123 1.0078 3.4550***

COLA Change 0.0300 0.0221 3.0952***

Assets (at market, in $mil) 10976 8767 1.4346

Average Monthly Earnings 3106 2969 2.8951***

Means

23

(1) (2) (4) (5) (6) (7)

Dependent VariableReported Benefit

ChangesReported Benefit

Changes

Benefit Increase Dummy (=1 if

increase )

Benefit Increase Dummy (=1 if

increase )Adjusted PBO

ChangeAdjusted PBO

Change

Estimation Regression Regression Probit Probit Regression Regression

Independent Variables

Board Type (=1 if political) 0.0348*** 0.0347*** 0.0072*** 0.0083** 0.0183 0.0191*(0.0080) (0.0079) (0.0027) (0.0028) (0.0118) (0.0118)

Benefits (Lagged) -0.0846*** -0.0596** -0.1450* 0.4393 -0.1796 -0.2351(0.0013) (0.0237) (0.0624) (0.1749) (0.5889) (0.6390)

Funding Flow (Lagged) 0.1880 0.1908 -0.0093 -0.0251 0.3028* 0.2912(0.1564) (0.1562) ('(0.0454) (0.0494) (0.1753) (0.1801)

Average monthly salary (Lagged) 0.0011 -0.0006 0.0042***(0.0009) (0.0004) (0.0012)0.0082 0.0158 0.3707

(0.1394) (0.1434) (0.4354)0.0091 -0.0199** 0.00121

(0.0070) (0.0073) (0.0072)

Year Fixed Effects Y Y Y Y Y YState Fixed Effects Y Y Y Y Y Y

Observations 949 848 269 250 516 501Systems 163 143 52 52 97 97States 46 45 18 18 41 41Years 6 6 5 5 6 6

R-squared 0.28 0.29 0.23 0.29 0.45 0.46Predicted x bar (for probits) 0.6930 0.7007Notes: Robust standard errors reported in parantheses. * refers to significance at 10% level, ** at 5%, and *** at 1%Reported probit results are marginal effects for small changes in continuous variables and discrete changes in binary variables

Table 3: Baseline Results

State Per Capita Income Level (Lagged)State Public Employee Density (Lagged)

24

(1) (2)

Dependent VariableReported Benefit

ChangesReported Benefit

Changes

Estimation Regression RegressionRepublican Democrat

Independent Variables

Board Type (=1 if political) 0.0157* 0.0550***(0.0094) (0.0122)

Benefits (Lagged) -0.0793*** -0.0458**(0.0039) (0.0050)

Funding Flow (Lagged) 0.0733 0.2449(0.1593) (0.2245)

Average monthly salary (Lagged) 0.0036 0.00090.0024 0.00110.0061 0.0136

(1.0082) 0.20890.0019 0.0062

(0.0145) 0.0075

Year Fixed Effects Y YState Fixed Effects Y Y

Observations 508 340Systems 96 72States 30 21Years 6 6

R-squared 0.22 0.37Notes: Robust standard errors reported in parantheses. * refers to significance at 10% level, ** at 5%, and *** at 1%States that changed party during this time: CA, MS, NE, NH, NJ, NV, VA, WVDifference in Board Type coefficient is significant at 1% (z=2.55)

Table 4: Baseline Results

State Per Capita Income Level (Lagged)State Public Employee Density (Lagged)

Is there a difference between Democrat Political Boards and Republican Political Boards?

25

(1) (2) (3)

Dependent Variable

Reported Benefit Changes

Reported Benefit Changes

Reported Benefit Changes

Condition Republican Democrat

Independent Variables

Board Type (=1 if political) 0.032*** 0.0448*** 0.0203*(0.0093) (0.0143) (0.0121)

Benefits (Lagged) -0.0819*** -0.0885*** -0.0718***(0.0152) (0.0224) (0.0203)

Funding Flow (Lagged) 0.0012 0.0031 0.0013(0.0018) (0.0027) (0.0019)

Per Capita Balance Change 0.0005 0.0017*** 0.00120.0003 (0.0000) (0.0014)

Balance*Board Type 0.0048*** 0.0002** 0.0032(0.0016) (0.0001) (0.0057)

State and System Variables+ Y Y YYear Fixed Effects Y Y YState Fixed Effects Y Y Y

Observations 848 508 340Systems 143 96 72States 45 30 21Years 6 6 6

R-squared 0.23 0.3 0.23Notes: Robust standard errors reported in parantheses. * refers to significance at 10% level, ** at 5%, and *** at 1%+ Note: Per Capita Income is Not included In the State Variables

Table 5: Marginal State Fiscal Balance Effects

Is there a marginal difference in political board behavior complimented by changes in state's fiscal level?

26

(1) (2) (3) (4) (5)

Dependent VariableReported Benefit

ChangesReported Benefit

ChangesReported Benefit

ChangesReported Benefit

ChangesReported Benefit

Changes

State Type N/APolitically

CompetitiveNot Politically Competitive Republican Democrat

Independent Variables

Board Type (=1 if political) 0.0349*** 0.0343*** 0.0265*** 0.0195** 0.0512**(0.0083) (0.0110) (0.0093) (0.0093) (0.0284)

Benefits (Lagged) -0.1193** -0.0634*** -0.0811** -0.1059*** -0.0693(0.0475) (0.1910) (0.0089) (0.0389) (0.3367)

Funding Flow (Lagged) 0.1900 -0.0016 0.0024 -0.009 0.3124(0.1562) (0.0011) (0.0026) (0.1330) (0.2406)

Election (=1 if election year) 0.0109** 0.0182*** 0.0129*** 0.0141* 0.0215**(0.0047) (0.0027) (0.0027) (0.0024) (0.0095)0.0006* 0.0005*** 0.0008* 0.0004* 0.0011(0.0003) (0.0002) (0.0004) (0.0002) (0.0008)

State and System Variables Y Y Y Y YYear Fixed Effects Y Y Y Y YState Fixed Effects Y Y Y Y Y

Observations 848 390 458 508 340Systems 143 65 78 96 72States 45 21 24 30 21Years 6 6 6 6 6

R-squared 0.33 0.23 0.19 0.28 0.47Notes: Robust standard errors reported in parantheses. * refers to significance at 10% level, ** at 5%, and *** at 1%

Notes on Magnitude: a 0.0008 marginal interaction effect translates into an average of $16.22million in annual benefit expenditures for a given system. For CALPERS, that translatesinto $259 million in added annual benefit expenditures.

A state is defined as politically competitive if a) there is gubernatorial party switch or b) at least one gubernatorial election had less than a 15% split

Table 6: Marginal Election EffectsIs there a marginal difference in political board behavior during election years?

Election*Board Type

27