Chapter 16 corporate risk management and pension asset allocation

CHAPTER

16

Corporate Risk
Management and
Pension Asset Allocation
Yong Li
CONTENTS
16.1 I ntroduction
16.2 Background and Prior Research
16.3 Development of Hypotheses
16.3.1 Financial Reporting Risk
16.3.2 Contribution Volatility Risk
16.4 Re search Design
16.4.1 Em pirical Model
16.4.2 Measures of Explanatory Variables
16.4.3 Sample and Data
16.4.4 De scriptive Statistics
16.5 E mpirical Results
16.5.1 U nivariate Analysis
16.5.2 Results from Simultaneous-Equation Estimation
16.5.3 R obustness Tests
16.6 C onclusion
References 38

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366 ◾ Pension Fund Risk Management: Financial and Actuarial Modeling

16.1 INTRODUCTION
The growing size of pension plans’ assets and liabilities* in relation to the
market capitalization of sponsoring companies raises the possibility that
firms’ overall financial position and prospects may influence not only its
strategy for funding their pension liabilities but also its allocation of pension assets among alternative investment categories. The oretical research
prior to the 1990s has developed competing hypotheses to explain pension
asset a llocation decision f rom a co rporate financial perspec tive (Sharpe,
1976; Treynor, 1977; Black, 1980; Tepper, 1981; Harrison and Sharpe, 1983).
The t ax-based Black –Tepper h ypothesis i mplies t hat firms w ith o verfunded pension plans should invest in the most heavily taxed assets (such
as bonds) to maximize their tax-savings because overfunded plans are less
likely to default on their pension promises (Black, 1980; Tepper, 1981). The

“pension put” hypothesis (Sharpe, 1976; Treynor, 1977) implies that firms
with underfunded pension plans should invest more in riskier assets (such
as equities) to maximize the value of the “put option” to default.†
However, the competing theoretical hypotheses lack consistent support
from the small volume of empirical research on pension asset allocation
(Friedman, 1983; B odie e t a l., 1987; Peterson, 1996; A mir a nd B enartzi,
1999; Frank, 2002). The corporate asset allocation strategy over alternative
asset investment categories (equities versus bonds) is not well understood
based on findings from prior empirical literature. Bodie et al. (1987) cautioned that further empirical research remains to be fi lled before a cl ear
picture of these important corporate pension decisions can emerge.
The objective of this chapter is to seek empirical regularities in the U.K.
firms’ r isk ma nagement o f pens ion a sset a llocation, a nd i ts i nterrelationship w ith t heir pens ion f unding a nd pens ion-related acco unting po licy
over an extended period of FRS 17 adoption (1998–2002). The U.K. pension
fund i nvestment st rategy ha s e volved subst antially over t he pa st dec ades.
The issue of the new U.K. pension GAAP (FRS 17: ASB, 2000) in 2000 has
transpired the risks of providing defined benefit (DB) pensions to investors.
Pension trustees and managers started to attach greater importance to managing their pension risk exposures. With the changing pension legislation
* In m id-July 2 008, F TSE 1 00 c ompanies re cognized £ 14 bi llion p ension d eficits o n t heir
balance sheets.
† Pension B enefit Gu aranty C orporation i nsures U.S. fi rms’ p ension l iabilities i n f ull i n t he
event of default. The PBGC has a claim on 30% of the market value of the firms’ assets. The
PBGC’s insurance of pension benefits provide the firm a “put” option: it can shed its pension
liabilities by giving the PBGC the assets in the scheme plus one-third of the firms’ assets.

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Corporate Risk Management and Pension Asset Allocation ◾ 367

and a g lobal convergence toward t he fa ir-value-based pension accounting

standards, changes in asset allocation strategy are taking place.
A new body of theoretical research concerning pension asset allocation
has emerged over recent years (Sharpe, 1990; Leibowitz et al., 1994; Blake,
2003). These st udies de veloped a sset/liability or su rplus return models of
portfolio diversification taking into account not only asset returns and variances but also changes in pension liabilities and their covariance with asset
returns. In light of these new theoretical insights on pension asset a llocation, this chapter develops and tests the hypotheses that U.K. sponsors have
managed t heir pens ion a sset a llocation w ith a n attempt t o m itigate t heir
exposure to t he potential volatility risk of t he financial statements a nd/or
cash flows during a period of accounting regulatory uncertainty.
Controlling for the endogeneity among asset allocation, pension funding, and the expected rate of return assumption choices, the empirical evidence based on the cross-sectional data on a panel of 279 firm-years during
the period from 1998 to 2002, suggests that the relationships among asset
allocation, pens ion f unding, a nd r elated pens ion r eporting ch oices a re,
for m ost pa rt, co nsistent w ith t he co rporate r isk-management o bjective
of hedging the cash contribution risks that stem from measuring pension
assets and liabilities at a “fair value” basis.
The rest of this chapter proceeds as follows: Section 16.2 describes the
institutional background and critically reviews the prior literature. Section
16.3 de velops r esearch h ypotheses. Section 1 6.4 de scribes t he r esearch
methodology, variable specification, data, and descriptive statistics. Results
are presented in Section 16.5 and concluding remarks in Section 16.6.

16.2 BACKGROUND AND PRIOR RESEARCH
The productive deployment of pension plan assets directly reduces costs
of f unding a D B pens ion p lan (McGill a nd Gr ubs, 1989). Pr ior em pirical research a lso e stablished t hat t he a sset a llocation i s t he ma in de terminant of the investment performance of a pension fund (Brinson et al.,
1991; Ibbotson and Kaplan, 2000). Thus the decision to allocate plan assets
among different investment vehicles represents a critical pension management decision by employer sponsors.
During the last four decades, U.K. employer sponsors have invested
the majority of their assets in equities (Blake et al., 1999). Davis (1991)
observes that the U.K. firms have maintained a substantially higher equity
proportion than firms in the United States, Canada, Japan, and Germany.

However, co rporate st rategic a sset a llocations i n t he U nited K ingdom

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368 ◾ Pension Fund Risk Management: Financial and Actuarial Modeling

evolved since recent years have seen rapid changes occurring in both the
legislative and t he accounting regulation for final sa lary pensions in the
United Kingdom.
The case of Boots group provides a perspec tive over the asset allocation
decision undertaken by employer sponsors during a period of regulatory
uncertainty. In November 2001, the Boots group announced that its £2.3 billion pension fund, one of the U.K.’s 50 largest funds with 72,000 members,
had switched 100% of its pension assets from equity into long-dated highquality bonds.* Duration-matching by investing in fixed-income investment
products, such as bonds, can effectively reduce the likelihood of the accumulated assets falling short of the long-term pension liabilities (Blake, 2003).
It is also noticeable that patterns of DB pension plan asset allocation
in t he United K ingdom and United States have been relatively invariant
over the last several years. The average equity allocation for a typical U.K.
sponsor wa s 6 0% ( Urwin, 2 002). Rec ent U.S. r esearch su ggests t hat t he
actuarial smoothing in the valuation of pension assets and liabilities has
contributed to t he high equity a llocations by sponsors (e.g., Gold, 2000;
Coronado a nd Sha rpe, 2003). The U.K. financial press a lso cla imed t hat
the “fair value” approach as espoused by FRS 17-style pension accounting
standard would lead corporate sponsors to shift t heir asset a llocation in
favor of fi xed-income securities, in order to shield themselves against the
potential volatility onto their financial statements (e.g., Financial Times,
March 20, 2004).
Very l imited empirical research ha s focused on ex plaining corporate
asset allocation decisions. Friedman (1983) presents evidence suggesting
that less-profitable companies w ith h igher leverage a nd h igher e arnings

variability tended to hold less in equities. His results on asset a llocation
seem to suggest that firms ma nage t heir pens ion f und a sset a llocations
to counterbalance the risks across firms that are stemming from product
markets or financial structure. By contrast, Bodie et al. (1987) find that the
proportion of assets allocated to equities is negatively related to the level of
funding and positively related to the size of the company. In other words,
underfunded plans tend to hold more equities and less fixed-income securities. The n egative co rrelation be tween f unding a nd t he p roportion o f
assets allocated to equities provides some support to the “pension put”
hypothesis. Thei r findings on asset allocations taken together suggest that
* The bonds are a close match for the maturity and the indexation of U.K. pension liabilities,
which has a weighted average maturity of 30 years and 25% are inflation-linked.

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Corporate Risk Management and Pension Asset Allocation ◾ 369

firms do not manage their sponsored pension funds as if they are entirely
separate entities from the sponsor (Friedman, 1983; Bodie et al., 1987).
Nevertheless, U .S.-based em pirical r esearch d uring t he 1 990s p rovides no e vidence supporting a t ax a rbitrage–based pension i nvestment
strategy. Motivated by t he i nconsistency a mong t heoretical a nd empirical st udies, F rank (2002) r eexamines t he ex tent t o wh ich t axes a ffect a
firm’s decision to allocate its DB plan’s assets between equity and bonds
within a simultaneous system of equations, which attempts to capture the
joint corporate capital structure and pension asset allocation decision in
such arbitrage strategy. Contrary to prior empirical research, Frank (2002)
finds ev idence consistent w ith firms t rading off t ax benefits a nd nontax
factors as described by Black (1980).
Motivated by t he release of U.S. pension GA AP (SFAS 87), A mir a nd
Benartzi (1999) investigate the possibility of a relation between firms’ pension accounting and investment choices during a post-pension accounting
regulatory change period (1988–1994) in the United States. They contend

that SFAS 87 provides managers the opportunity to choose between recognition and disclosure. In particular, they focus on the question of whether
the r ecognition o f add itional m inimum pens ion l iability i n acco rdance
with SFAS 87 affects asset allocation decision. Indeed, they find evidence
that companies closing to a recognition threshold will make an economic
decision of allocating more plan assets into fixed-income investments.
Uncovering the existence of such a r elationship implies that SFAS 87 has
potential economic consequences for firms, consistent with the corporate
finance perspective. The adoption of a “ fair va lue” approach i n pension
accounting ( FRS 17), co nsistent w ith t he co rporate finance perspective,
implies a short-term volatility mismatch between pension assets and liabilities. It is possible that U.K. firms may manage their pension asset allocation in a way so as to mitigate their pension risk exposures attributable
to changing pension accounting regulation.

16.3 DEVELOPMENT OF HYPOTHESES
16.3.1 Financial Reporting Risk
The r elease o f n ew pens ion acco unting i nformation ( FRS 17) ma y a lter
the nature or the perception of risks of employers’ pension exposure. One
common assumption was that the adoption of FRS 17 would expose U.K.
firms t o s ignificant ba lance sh eet v olatility. U nder FR S 17, t he pens ion
deficits or surpluses are required to be r ecognized on the corporate balance sheets once they arise. By contrast, the former U.K. pension GAAP

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370 ◾ Pension Fund Risk Management: Financial and Actuarial Modeling

(SSAP 24: ASC, 1988) allows any surpluses or deficits to be spread over the
employees’ future working time, typically 15 years.
If sponsoring firms were forced to recognize their past funding practices on a “fair value” basis onto the balance sheets, the desired positioning of the firm’s consolidated pension balance sheet may not be attainable
solely t hrough pens ion ben efit r eductions, such a s p lan ter minations.
Consequently, plan sponsors a re ex posed to r isks of having potentially

volatile financial statements. Managers can mitigate such financial reporting risk by choosing a d ifferent mix of equities and bonds. Investing in
bonds has the advantage of obtaining a h igh correlation between assets
and liabilities, thus reducing such financial reporting risks.
Following Bergstresser et al. (2006), a sens itivity measure (PENRISK)
is constructed to capture the variation in firms’ pension exposure to the
potential financial reporting r isk. PENRISK i s c alculated a s t he natural
logarithm of t he r atio of t he ma rket va lue of pension a ssets to total net
assets in a firm year.*
Hypothesis 1 ( H1): Ceteris p aribus, t he per centage o f a ssets
invested in e quities d ecreases as firms’ ex posure t o t he po tential
financial reporting risk increases.
16.3.2 Contribution Volatility Risk
Risky assets, such a s equities, are characterized by their volatile returns.
Financial theory suggests that the higher risk of equity investment is
awarded b y t he h igher r eturn i t g enerates ( Markowitz, 1 952; Sha rpe,
1964). However, if the volatile return on the pension assets translates into
changes in the required cash contribution, then risky assets will translate
into more risky required contributions to the pension plan. The main concern of “cash flow risk” managers is to minimize the volatility of changes
in cash flows (Culp, 2001). Friedman (1983) finds some evidence that firms
have incentives to time their pension contributions so as to smooth the
reported earnings. Prior to FRS 17, firms’ past pension funding practices
are not reported on financial statements. Shareholders and investors may
judge the firm’s performance by its reported earnings rather than by more
comprehensive c ash flow measures. Coronado et al. (2008) show that
investors fa iled t o d istinguish be tween pens ion a nd o perating e arnings
* Bergstresser e t a l. ( 2006) s uggest t hat s uch a s ensitivity me asure c ollapses t he i nfluence
of out liers a nd br ings t he d istribution of t he r atio c loser to t hat of a nor mally d istributed
random variable.

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Corporate Risk Management and Pension Asset Allocation ◾ 371

and capitalize them similarly. The adoption of FRS 17 implies that investors a re beco ming m ore a ware o f t he r elative ma gnitude a nd po tential
risks of DB pension provisioning (Klumpes and Li, 2004). Consequently,
prudent va lue ma ximizing ma nagers fac e st rong i ncentive t o h edge t he
riskiness of their future cash contributions.
By matching pension assets with liabilities, that is, allocating plan assets
into bonds, sponsoring firms can effectively reduce the volatility of their
pension contributions, thus achieve to hedge their cash contribution risks.
If the incentive is strong for sponsors to minimize the volatility of pension
contributions, then it would be observed that firms with both extremely
overfunded and underfunded plans invest in bonds because such extreme
overfunding a nd u nderfunding a fford le ss flexibility t o ad just t he t iming of pension contributions than do firms with moderate funding levels.
Pension plans with greater deficits are required to make deficit-reduction
contributions and those with greater surpluses have to conform to the tax
regulations.* By contrast, pension contributions are fairly predictable for
moderate funding levels, but less predictable when funding levels become
more e xtreme. The contribution risk hypothesis thus predicts a nonlinearity relationship between variations in funding level and pension asset
allocation, and provides an alternative risk-management explanation for
the conflicting results from prior studies on the effect of pension funding
on asset allocation.† This discussion leads to the second hypothesis:
Hypothesis 2 ( H2): Ceteris p aribus, t he per centage o f a ssets
invested in equities increases as the funding level increases up to a
specific point, then decreases as the funding level increases beyond
this point.

16.4 RESEARCH DESIGN
16.4.1 Empirical Model

Accounting researchers have recognized the importance of analyzing the
potential endogeneity in the choices made by firms along different dimensions (e.g., Beatty et al., 1995; D’Souza, 1998). Treating endogenous variables as exogenous, or excluding relevant choice variables, leads to biased
* U.K. corporate sponsors of defined benefit pension plans w ith a f unded status in excess of
105% were subject to taxation at a rate of 35%.
† Amir a nd B enartzi (1999) fi nd s ome e mpirical e vidence on s uch a non linear re lationship
between pension funding and asset allocation. However, their study does not control for the
potential endogeneity between pension funding and asset allocation.

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372 ◾ Pension Fund Risk Management: Financial and Actuarial Modeling

and i nconsistent pa rameter e stimates. Pr ior pens ion r esearch ha s n ot
taken into account the simultaneity of pension asset allocation, funding,
and r elated financial r eporting ch oices.* C ausality i s t herefore u nclear,
and t he s ame c ross-sectional r esults c an be r ationalized by a va riety o f
explanations.
It is possible that the corporate pension asset allocation policy is conditional upon firms’ long-term pension funding and their discretion over
the l ong-term ex pected r ate o f r eturn o n pens ion i nvestments ( hereinafter “ ERR”). Pr ior U .S.-based r esearch ha s dem onstrated t hat firm
management ha s a ttempted t o eng age i n t he s moothing a nd sp reading
of pension costs over time (Picconi, 2006). Corporate sponsors can exercise the discretion in the level of ERR assumptions to change the pattern
and t he magnitude of pension liabilities, t hus mitigating t heir contribution volatility risk. They could a lso increase t he a llocation of equities in
their pension fund investment portfolio to justify the high level of the ERR
assumptions. Klumpes et al. (2009) provide evidence that corporate pension termination decision is indeed not independent of their discretionary
ERR choices. Consequently, a simultaneous equations model is employed
to control for the simultaneity and identify the impact of pension reporting risks on the pension asset allocation decision.
The hypotheses concerning corporate pension asset allocation decision
are tested by employing a simultaneous model with three equations: asset
allocation, funding, and pension actuarial assumption choices. It is based

on t he assumption t hat sponsors can adjust t heir asset a llocation, f unding, and related pension reporting choices simultaneously. Specifically, the
system of simultaneous equations is specified as follows:
%EQUITYit = α 0 + α1t FUNDit + α 2t FUNDSQit + α 3t PENRISK it
+α 4t ERR it Φ1′ Χ1it + γ t + ε1t

(16.1)

FUNDit = β0 + β1t %EQUITYit + β2t ERR it + Φ′2 Χ2it + γ t + ε2t

(16.2)

ERR it = δ0 + δ1t %EQUITYit + δ2t FUNDit + Φ′3 Χ 3it + γ t + ε3t

(16.3)

* Mitchell a nd Smith (1994) employs si multaneous equations model approach to i nvestigate
pension funding in the U.S. public sector. They attempt to control the simultaneity between
the required per worker annual contribution (REQ), actual pension plan funding in the public sector (ACT), and average worker compensation package (AVEPAY).

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Corporate Risk Management and Pension Asset Allocation ◾ 373

where
% EQUITY is the percentage of equity invested by corporate sponsors
FUND is the reported stock funding level
ERR is the level of reported expected rate of return on pension assets
assumptions*
FUNDSQ is the squared value of FUND

PENRISK i s t he sens itivity m easure o f firms’ pe nsion ex posure t o
reporting risk
X1it, X 2it, a nd X 3it a re a v ector o f p redetermined co ntrol va riables i n
three respective equations
γt represents dummy variables for years 1998–2002
Equations 16.1 through 16.3 model pension asset allocations, funding, and
ERR reporting choices, respectively. ε1t, ε2t, and ε3t are error terms.
16.4.2 Measures of Explanatory Variables
Multiple p roxies a re de veloped t o co ntrol f or t he co mpeting t heoretical ex planations o n t he co rporate pens ion a sset a llocation dec ision o f
Equation 16.1. The “pension put” hypothesis (Sharpe, 1976; Treynor, 1977)
implies that firms for which the pension “put” option is more valuable (i.e.,
more in the money) will hold more of the most risky assets, presumably
equities, and vice versa. The “put” option is likely to be more valuable for
underfunded plans, for unprofitable companies or firms with higher variability in their cash flows, or firms with more debt.
Consistent w ith p rior l iterature ( Friedman, 1 983; B odie e t a l., 1 987;
Frank, 2 002), t hree p roxies u sed t o m easure t he va lue o f pens ion “ put
option” to sponsoring firms include leverage (LEV), profitability (PROF),
and firm r isk (STDCF). L EV is calculated as t he long-term debt d ivided
by total tangible assets. Higher leverage implies less debt covenant slack
and higher probability of financial distress. Thus the “put” option is more
valuable to highly levered firms. PROF is calculated as the mean return on
shareholders equity over the preceding 10 years, which is a proxy for longterm p rofitability. Less-profitable firms a re l ess l ikely t o f ulfill the fixed
payments of retirees’ benefits and thus more likely to invest more in equities to ma ximize t he va lue of t he “put” option to default (Sharpe, 1976).
STDCF is calculated as the standard deviation of operating cash flows over
the preceding 10 years deflated by t he book va lue of equity. Firms w ith
* FUND me asures t he r atio of t he p ension pl an’s tot al a ssets to it s tot al prom ised b enefit
obligations.

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374 ◾ Pension Fund Risk Management: Financial and Actuarial Modeling

higher va riability i n t heir c ash flows are likely to invest more in equity
to maximize the “pension put.” Friedman (1983) finds a negative relation
between firm risk, measured as income variability, and the percentage of
assets invested in equities. He proposes a “risk offsetting story” to interpret
his finding. The a rgument i s t hat r isky firms t end to offset t he r isks b y
investing in less-risky assets in their pension plans, such as bonds.
The “ Black–Tepper” h ypothesis p redicts t hat firms sh ould o verfund
their pensions because tax arbitrage enables firms to earn a tax-free rate of
return on investments. TAXST is included as a proxy for firm’s average tax
rate. TAXST is calculated as the total reported taxes minus the change in
deferred taxes over the preceding 10 years deflated by beginning year total
assets. Firms with higher tax rate would gain more by investing the assets
in fixed-income securities.
It is i mportant we a lso control for va rious economic determinants of
pension asset allocation posited by prior research. Prior U.S.-based studies find the plan demographics influences asset allocations (e.g., Amir and
Benartzi, 1999; F riedman, 1983). The ma turity o f t he pens ion l iabilities
may be an important determinant affecting the asset allocation decision
by U.K. sponsors in the current economic environment when most of the
funds g radually ma ture a nd dema nd n ontrivial fixed benefit payments.
Firms with mature pensions may wish to invest more assets in bonds so
as to achieve better asset/liability matching, thus reduce the likelihood of
the assets falling short of obligations. PRET, measured as the percentage of
vested member over the total number of vested and non-vested members,
is included as a control for the maturity of pension plan.
It is also argued that the U.K. pension fund management is partially
driven by t he herding behavior (Klumpes a nd W hittington, 2 003). This
suggests that U.K. pension funds often benchmark their investment performance against other funds’ performance and relevant market indices.

The co ntemporaneous ac tual r ate o f r eturn o n pens ion a sset po rtfolio
(MKRTN) is included to control for this argument. MKRTN is calculated
as the actual rate of return on a weighted market portfolio with an equivalent asset mix.
The pension f unding regression (Equation 16.2) adopts t he empirical
framework employed by Francis a nd Reiter (1987) to ex plain corporate
pension f unding st rategy, wh ile controlling for t he endogeneity a mong
asset allocation (%EQUITY) and ERR assumption choices. The “financial
slack” effect ha s em phasized t he pens ion f und’s u sefulness a s a so urce
of corporate liquidity or as a store of temporarily excess corporate funds

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Corporate Risk Management and Pension Asset Allocation ◾ 375

(Myers and Majluf, 1984). Such slack could be kept in the form of either
liquid assets, unused debt capacity, or pension assets. The financial slack
hypothesis predicts that the firms should overfund its pensions to build
excess assets, which can accumulate at the pretax rate and be used when
firms require f unds to finance positive NPV projects. The proxy for t he
rate of undertaking new investments (RUNI), measured as the sum total
of capital expenditure plus R&D expenditure divided by total assets, controls f or t he “ financial slack” hypothesis of high-level funding. Sharpe
(1976) argues that “pension put” is of greatest value to underfunded pension plans, therefore risky firms should underfund their pensions to maximize the “put option” value. STDCF is included as a proxy to control for
the firm risk for the “pension put option” incentive of low-level funding.
The ERR regression (Equation 16.3) explains cross-sectional variations
in r eported ER R l evels. I n add ition, E quation 16.3 i ncludes t he l evel o f
funding as a n add itional endogenous va riable. Bodie et a l. (1987) find a
negative association between the size of the pension plan and the percentage of bonds allocated in the pension portfolio. So a general control variable is included, plan size (LNSIZE), in all three equations.*
16.4.3 Sample and Data
The main constraint on the sample size is the availability of detailed pension a sset c omposition.† The proprietary a sset a llocation d ata a re ha ndcollected f rom t he p rofessional p ublication “ Pension F und a nd Thei r

Advisers” book (PFTA 1988–2004). The sample period consists of period
over 1998–2002. During this period, U.K. sponsors were subject to both
legislative-imposed minimum funding solvency restrictions and differential pension accounting regulatory requirements. To be included in the
sample, t he sponsor first had t o be a p ublicly l isted F TSE 350 firm that
sponsors a t l east o ne D B pens ion sch eme w ith co mplete pens ion a sset
allocation data available. Second, to increase the power of empirical tests,
firms with more than 5% of their pension assets as “unclassified” are deleted.‡
Finally, firms with missing data required for analysis are deleted.
* A H ausman s pecification t est i s p erformed on t he e quation s ystem s pecified to check t he
existence of endogeneity (Hausman, 1978). The result indicates that exogeneity of asset allocation decision (% EQUITY) can be rejected at 5% level.
† Frank (2002) also noted the obstacle to investigating DB investment policy is obtaining the
asset allocation data necessary to compute percentage of bonds invested by pension funds.
‡ Amir a nd B enartzi (1999) a nd Fr ank ( 2002) d eleted fi rms with 5% of th e a ssets th at a re
“unclassified” in their studies.

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376 ◾ Pension Fund Risk Management: Financial and Actuarial Modeling

Following t he abo ve c riteria, t he co mplete a sset a llocation d ata c an
only be obtained between 60 and 70 firms per year. After eliminating outliers, the final sample comprises 279 firm-year observations. All the data
used for this study is collected from the financial statements of the sample
firms, Datastream and “PFTA” book.
16.4.4 Descriptive Statistics
Table 16.1 presents t he descriptive statistics on t he distribution of pension a sset co mposition i n t he s ample. A t t he en d o f 1 998, spo nsoring
firms allocate 72.73% of their assets to equities and 15.12% to fi xedincome securities. On average, sample U.K. firms in vest s ignificantly
more in equities than in bonds. Th is evidence is consistent with the pension asset allocation of relevant population. U.K. firms on average invest
about 49%–59% of their total pension funds in domestic equities and an
additional 16%–22% in international e quities (Urwin, 2 002). The allocation to equities dropped nearly 8% in 2002 for the sample firms and

an increase of nearly 4% allocated to bonds. Overall the sample pension a sset a llocation d isplays a sl ow t rend t oward a g reater percentage
of bonds among the overall pension asset composition during the study
period (1998–2002).
Panel A o f Table 1 6.2 p resents t he c ross-sectional d istribution o f
%EQUITY b y y ear. % EQUITY va ries s ignificantly a cross t he firms with
a st andard de viation o f 1 3.66 f or t he poo led s ample. T o ex amine t he
TABLE 16.1

Distribution of Pension Asset Composition by Year

Asset Category

1998
(n = 53)

1999
(n = 56)

2000
(n = 58)

2001
(n = 55)

2002
(n = 57)

All
(n = 279)

U.K. equity
OS equity
U.K. fixed interest
OS fixed interest
Index bonds
Property
Cash
Total equity
Total bonds

54.54%
18.19
7.95
2.57
4.60
3.23
5.95
72.73
15.12

54.27%
18.26
8.37
2.52
4.57
3.03
5.68
72.53
15.46

51.65%
18.36
8.64
2.37
5.55
3.07
4.56
70.01
16.56

50.64%
22.77
8.02
2.26
5.52
2.01
2.87
71.21
15.80

44.20%
20.60
12.48
1.53
5.00
3.04
2.86
64.80
19.01

51.06%
19.64
9.09
2.25
5.05
2.88
4.38
70.26
16.39

Notes: This table presents the descriptive statistics on the distribution of pension asset composition of the sample U.K. firms. The asset investment categories are the U.K. equity,
the overseas equity, the U.K. fixed interest, the overseas fixed interest, index-linked
bonds, property, and cash.

© 2010 by Taylor and Francis Group, LLC


Corporate Risk Management and Pension Asset Allocation ◾ 377
TABLE 16.2

The Distribution of Equity Investmentsa

Quintile of Equity
Investments

1998
(n = 53)

1999
(n = 56)

2000
(n = 58)

2001
(n = 55)

Panel A: Equity investments ranked by quintiles every year
1 (less equities)
35.00
37.00
30.00
30.00
2
70.00
69.00
68.71
66.71
3
75.00
72.62
75.00
74.40
4
77.00
77.40
80.00
80.25
5 (more equities)
88.00

91.00
91.00
90.00
Mean
72.41
71.73
71.50
70.43
Std
9.91
11.74
14.18
14.19
t test for quintiles
−5.85*** −11.96*** −14.36*** −8.93***
5 versus 1
Panel B: The distribution of changes in equity investments
Annual Changes
Two-Year Changes
Statistic (N)
(120)
(80)
Mean
−1.36%
−2.86%
Std
6.75
9.86
Minimum
−42.68

−42.66
10th percentile
−6.00
−11.84
Median
0.00
−1.00
90th percentile
4.02
5.17
Maximum
22.00
22.00

2002
(n = 57)

All
(n = 279)

28.78
28.78
62.42
67.05
69.25
73.00
78.24
78.00
89.96
91.00

66.40
70.33
15.68
13.66
−6.96*** −18.13***

Thr ee-Year
Changes (51)
−4.70%
11.30
−38.66
−11.68
−3.09
6.33
22.00

Notes: Panel A p resents t he cr oss-sectional distr ibution o f %EQ UITY b y y ear o ver t he
study period (1998–2002). Panel B presents the changes in %EQUITY over one, two,
and three years.
a Equity investment is the percentage of the pension assets allocated to equities.
* indica tes significance at 10% level.
** indica tes significance at 5% level.
*** indica tes significance at 1% level.

frequency o f a sset a llocation r evisions, cha nges i n % EQUITY a re c alculated over one, two, and three years. Results in Panel B, Table 16.2 suggests
that most firms maintain a constant allocation to equities. Over a one-year
period, more than 80% of the firms remained within five percentage points
of their beginning allocation to equities. Over a t hree-year period, 80% of
the firms decreased their allocation to equities by less than 12%, or increased
it by less than 7%. Given the stability of equity allocation over the five-year

study period (1998–2002), we focus on cross-sectional differences in asset
allocation rather than time-series changes.
Table 16.3 provides m eans a nd st andard de viations f or t he ex planatory variables required for estimating Equation 16.3 by year. The average

© 2010 by Taylor and Francis Group, LLC


Variable (N)
FUND
FUNDSQ
ERR
PENRISK
LEV
PROF
STDCF
TAXST
PRET
LNSIZE

Descriptive Statistics on the Regression Variables by Year
Statistics

1998 (n =53)

1999 (n = 56)

2000 (n = 58)

2001 (n = 55)

2002 (n = 57)

All (n = 279)

Mean
Std
Mean
Std
Mean
Std
Mean
Std
Mean
Std
Mean
Std
Mean
Std
Mean
Std
Mean
Std
Mean
Std

1.144
0.167
1.337
0.403
8.430

0.778
−7.751
1.055
0.183
0.136
13.518
13.488
0.087
0.079
0.032
0.227
0.426
0.226
5.681
1.366

1.155
0.156
1.359
0.369
7.867
0.963
−7.561
1.074
0.188
0.128
12.502
14.105
0.224
0.672

0.027
0.029
0.421
0.217
5.881
1.323

1.110
0.131
1.249
0.298
7.325
1.053
−7.688
1.644
0.205
0.129
13.728
11.528
0.130
0.134
0.032
0.042
0.445
0.241
5.970
1.432

1.112
0.163

1.262
0.370
6.852
0.848
−7.723
1.688
0.221
0.146
9.498
10.307
0.155
0.170
0.025
0.021
0.490
0.263
5.947
1.397

1.086
0.151
1.202
0.331
6.578
0.746
−7.449
1.340
0.269
0.284
7.820

10.677
0.128
0.131
0.065
0.038
0.517
0.237
6.338
1.021

1.120
0.154
1.280
0.356
7.386
1.104
−7.624
1.367
0.215
0.182
11.296
12.226
0.146
0.330
0.024
0.033
0.462
0.237
5.979
1.309

© 2010 by Taylor and Francis Group, LLC

378 ◾ Pension Fund Risk Management: Financial and Actuarial Modeling

TABLE 16.3


ARR
MKRTN

SGR
∆ROA

13.989
47.867
29.054
1.818
0.09
0.05
6.12
0.82
0.26
0.04

19.424
25.908
10.702
0.926
0.08

0.05
5.58
0.89
0.14
0.05

11.734
19.527
11.708
2.340
0.07
0.05
5.14
0.87
0.02
0.08

8.532
20.392
−6.526
2.930
0.06
0.05
4.65
0.71
0.09
0.03

4.335
15.789

−1.114
0.880
0.06
0.04
4.33
0.65
0.18
0.07

11.484
27.998
8.450
12.157
0.07
0.05
5.15
1.01
0.13
0.06

Notes: This table presents the means and standard deviations of regression variables used multivariate analysis. The variable definitions are as
follows: %EQUITY is the percentage of pension fund portfolio invested in equities; FUND is the reported funding status under SSAP24;
FUNDSQ is the squared value of FUND; ERR is the expected rate of return on pension assets assumption used in the estimation of pension expenses; PENRISK is the natural logarithm of the ratio of the market value of pension assets to total net assets; LEV is the firms’
leverage ratio defined as t otal short-term plus long-term debt, deflated by shareholders’ equity; PROF is the mean of return on shareholders’ equity over the preceding 10 y ears; STDCF is t he standard deviation of operating cash flows (earnings before extraordinary
items plus depreciation expenses) over the preceding 10 years deflated by the book value of equity; TAXST is the total reported taxes
minus the change in def erred taxes over the preceding year deflated by beginning year total assets; PRET is t he percentage of vested
members over total number of vested and nonvested members, a proxy for the maturity of pension plans; LNSIZE is the natural logarithm of the market value of pension assets; ARR is the contemporaneous actual rate of return on pension fund investment; SGR is the
projected salary growth rate assumption used in t he estimation of pension expenses; MKRTN is t he contemporaneous actual rate of
return on a weighted market portfolio with an equivalent asset mix; RUNI is the capital expenditures plus R&D deflated by beginning
year total assets; ∆ROA is the changes in operating earnings deflated by beginning year total assets.

© 2010 by Taylor and Francis Group, LLC

Corporate Risk Management and Pension Asset Allocation ◾ 379

RUNI

Mean
Std
Mean
Std
Mean
Std
Mean
Std
Mean
Std


380 ◾ Pension Fund Risk Management: Financial and Actuarial Modeling

pension f unding ratio gradually declined from 1.144 in 1998 to 1.086 in
2002, r eflecting t he fa ll of t he eq uity r eturn s ince 2 000. O ver t he s ame
period, the maturity of pension plans increased by nearly 22%. The sensitivity m easure o f firms’ ex posure t o t he financial r eporting r isk ha s
increased g radually o ver t he per iod 1 998–2002 a s ex pected. I t i s a lso
observed t hat firms’ profitability ( PROF) ex hibits a decl ining t rend b ut
the LNSIZE exhibits stability over the entire sample period.

16.5 EMPIRICAL RESULTS
16.5.1 Univariate Analysis

Table 16.4 ex amines t he r elation be tween e ach o f t he ex planatory va riables i n E quation 16.1 a nd % EQUITY, u sing a n onparametric po rtfolio
analysis. Each independent variable is divided into five equal-size portfolios, where portfolio 1(5) contains firms with the lowest (highest) values.
The relation between the funding ratio of the pension plan (FUND) and
equity allocation is consistent with the nonlinear relationship as predicted
in hypothesis H2. The allocation to equities increases from 67.43% for the
first quintile to 71.79 for the fourth quintile, and then it decreases to 68.24
for the fifth quintile. Consistent with hypothesis H1, the measure of firms’
sensitivity to financial reporting risk (PENRISK) is statistically significant
in ex plaining t he a llocation t o eq uities. Firms w ith h ighest ex posure t o
financial reporting risk (fift h quintile) allocate 65.77% of pension assets to
equities, whereas firms with the smallest exposure (first quintile) allocated
75.99 to equities.
It i s f ound t hat a n egative a ssociation be tween t he ma turities o f t he
pension plans and equity allocation. Firms with the more mature pension
funds (fift h quintile) allocate 55.46% of pension assets to equities, whereas
firms with younger funds (first quintile) allocate 75.71%. This evidence is
consistent with prior findings in Amir and Benartzi (1999) and Peterson
(1996) that firms with more mature aging distribution of plan participants
allocate more in bonds than equities.
The effect of long-term profitability (PROF) a nd pens ion f und s ize
(LNSIZE) a re st atistically s ignificant in e xplaining t he a llocation
to e quities. M ore p rofitable fi rms ( fi ft h q uintile) a llocate 7 6.93% t o
equities, wh ereas l ess-profitable fi rms ( fi rst q uintile) a llocate 6 2.56%
to eq uities. F inally, fi rms w ith s maller pens ion f unds i nvest m ore i n
equities. The firms sponsoring smallest pension funds allocate 75.47%
to equities, wh ile t he fi rms sponsoring la rgest pension f unds a llocate
67.75% to equities.
© 2010 by Taylor and Francis Group, LLC

Corporate Risk Management and Pension Asset Allocation ◾ 381
TABLE 16.4 Mean Equity Investments by Quintile of the Explanatory Variables
in Equation 16.1
Quintile of the Independent Variable
Explanatory
Variables Used to
Form Quintiles

(low)1

2

3

4

5 (high)

t Test for
Quintiles
5 versus 1

FUND
PENRISK
ERR
LEV
PROF
STDCF
TAXST
PRET

MKRTN
LNSIZE

67.43
75.99
66.61
72.37
62.56
73.71
65.93
75.71
73.94
75.47

69.38
72.35
69.40
70.48
68.34
71.09
68.33
77.22
63.37
68.48

70.89
70.05
73.02
68.75
72.05

70.08
72.15
72.87
66.01
66.81

71.79
65.33
72.21
65.87
73.75
61.75
71.72
68.17
72.34
71.00

68.24
65.77
70.85
72.16
76.93
72.91
71.57
55.46
73.99
67.75

1.18
−4.58***

−1.19
−1.09
4.84***
−0.97
2.58**
−4.87***
1.15
−4.28***

Notes: This table presents the results from a nonparametric portfolio analysis of %EQUITY
and exp lanatory va riables in Eq uation 16.1. E ach exp lanatory va riable is di vided
into five equal-size portfolios, where portfolio 1(5) co ntains firms with the lowest
(highest) values. The variable definitions are as follows: %EQUITY is the percentage
of pension fund portfolio invested in equities; FUND is the reported funding status
under SSAP24; FUNDSQ is the squared value of FUND; ERR is the expected rate of
return on p ension ass ets assumption us ed in t he estimation of p ension exp enses;
PENRISK is the natural logarithm of the ratio of the market value of pension assets
to total net ass ets; LEV is t he firms’ leverage ratio defined as t otal short-term plus
long-term deb t, deflated by sha reholders’ eq uity; PR OF is t he me an o f r eturn o n
shareholders’ equity over the preceding 10 years; STDCF is the standard deviation of
operating cash flows (e arnings b efore extrao rdinary i tems p lus dep reciation
expenses) over the preceding 10 years deflated by the book value of equity; TAXST
is the total reported taxes minus the change in deferred taxes over the preceding year
deflated by beginning year total assets; PRET is t he percentage of vested members
over total number of vested and nonvested members, a p roxy for t he maturity of
pension p lans; LNS IZE is t he na tural loga rithm o f t he ma rket val ue o f p ension
assets; ARR is t he contemporaneous actual rate of return on pension fund investment; SGR is the projected salary growth rate assumption used in the estimation of
pension exp enses; MKR TN is t he co ntemporaneous ac tual ra te o f r eturn o n a
weighted market portfolio with an equivalent asset mix; RUNI is the capital expenditures plus R&D deflated by beginning year total assets; ∆ROA is t he changes in
operating earnings deflated by beginning year total assets.

* indica tes significance at 10% level.
** indica tes significance at 5% level.
*** indica tes significance at 1% level.

16.5.2 Results from Simultaneous-Equation Estimation
Table 16.5 presents results f rom t hree-stage least squares (3SLS) estimation o f t he s imultaneous eq uation m odel ( Equations 16.1 t hrough 16.3)
© 2010 by Taylor and Francis Group, LLC


Explanatory
Variable
FUND
%EQUITY
ERR
FUNDSQ
PENRISK
LEV
PROF
STDCF
TAXST
RUNI
PRET
∆ROA
ARR
SGR

Three-Stage Least Squares (3SLS) Regression Results of Pension Asset Allocation
(Equation 16.1)
%EQUITY

(Equation 16.2)
FUND

Pred Sign

Est Coef.

t-Stat

+

15.551**

1.86

+
—
—
+
+
+
?

0.037
−6.416**
−0.054*
0.061
0.006**
0.004
0.645

0.86
−1.79
−1.42
0.52
2.06
0.03
0.85

—

−0.056***

−3.17

Pred. Sign

Est Coef.

t-Stat

+
—

0.629***
−0.032**

4.26
−1.90

+

0.002**
0.079***
−0.601*
−0.233

2.27
2.62
−1.57
−1.04

—

© 2010 by Taylor and Francis Group, LLC

(Equation 16.3)
ERR
Pred. Sign

Est Coef.

t-Stat

—
+

−1.433***
0.834

−3.87
0.47

+

0.116**

2.20

—
—
—
+

−0.109
−0.164
0.001
0.781***

−0.34
−0.15
0.38
14.96

382 ◾ Pension Fund Risk Management: Financial and Actuarial Modeling

TABLE 16.5


?

—

−0.002
−0.023
Included
0.1086***

−0.21
−0.98

—

−0.058
Included
0.2475***

−2.79

—

−0.048
Included
0.7446***

−0.89

Notes: This table presents the three-stage least-square (3sls) estimate of the system of three regression equations, that is, Equations 16.1
through 16.3 for %EQUITY, FUND, and ERR, respectively. The variable definitions are as follows: %EQUITY is the percentage of
pension fund portfolio invested in equities; FUND is the reported funding status under SSAP24; FUNDSQ is the squared value of
FUND; ERR is the expected rate of return on pension assets assumption used in the estimation of pension expenses; PENRISK is

the natural logarithm of the ratio of the market value of pension assets to total net assets; LEV is the firms’ leverage ratio defined
as total short-term plus long-term debt, deflated by shareholders’ equity; PROF is the mean of return on shareholders’ equity over
the preceding 10 years; STDCF is the standard deviation of operating cash flows (earnings before extraordinary items plus depreciation expenses) over the preceding 10 years deflated by the book value of equity; TAXST is the total reported taxes minus the
change in deferred taxes over the preceding year deflated by beginning year total assets; PRET is the percentage of vested members
over total number of vested and nonvested members, a proxy for the maturity of pension plans; LNSIZE is the natural logarithm
of the market value of pension assets; ARR is the contemporaneous actual rate of return on pension fund investment; SGR is the
projected salary growth rate assumption used in the estimation of pension expenses; MKRTN is the contemporaneous actual rate
of return on a w eighted market portfolio with an equivalent asset mix; RUNI is t he capital expenditures plus R&D deflated by
beginning year total assets; ∆ROA is the changes in operating earnings deflated by beginning year total assets.
* ,** ,*** indicates significance at 10%, 5%, and 1% level, respectively.

© 2010 by Taylor and Francis Group, LLC

Corporate Risk Management and Pension Asset Allocation ◾ 383

MKRTN
LNSIZE
YEAR
Adjusted R2


384 ◾ Pension Fund Risk Management: Financial and Actuarial Modeling

for t he pooled sample. Panel A, Table 16.5 reports results f rom estimating E quation 1 6.1, t he a sset a llocation m odel o f t he p rimary i nterest.
Consistent wi th H 2, th e e ffect o f f unding l evel o n a sset a llocation f ollows a n onlinear r elationship. The coefficient on FUNDSQ is negative
and s ignificant at 5% level. This finding su ggests t hat t he s ample firms
with ex tremely o verfunded a nd u nderfunded pens ion p lans a llocated
more pension assets into bonds than equities. This allocation strategy can
minimize the cash flow risk caused by volatile pension contributions, as
extreme underfunded plans have stronger incentive to avoid the accelerated funding requirements and overfunded plans have stronger incentive

to avoid exceeding the full-funding limits.
The coefficient on PENRISK is of negative sign as predicted, and significant at 10% level. This ev idence is s upportive o f H1, wh ich p redicts
firms that are sensitive to risks of volatile financial statements allocate less
pension assets into equities. Another interesting finding is the significant
positive relationship b etween firms’ l ong-term p rofitability ( PROF) a nd
the eq uity a llocation. The “pension put” hypothesis predicts that lessprofitable firms should be i nvesting their pension portfolio in equities to
maximize the value of the “put” option. By contrast, this finding suggests
that sample firms with higher long-run profitability have allocated higher
percentage of their pension assets in equities, consistent with the univariate analysis. This result appears to provide some support for “risk-offsetting” st ory adv ocated b y F riedman (1983) t hat t he l ess-profitable firms
face higher risk to default on fi xed payments, thus prefer bonds to equities.
Finally, t he results i n Table 16.5 su ggest t hat t he maturity of sponsored
pension fund is statistically significant in explaining pension asset allocation decision. Other things being equal, the percentage of pension assets
allocated to equities decreases as the pension fund maturity increases.
16.5.3 Robustness Tests
The pooled time-series, cross-sectional regression assumes the coefficients
are consistent ac ross t ime a nd firms a nd t he residuals a re i ndependent.
To assess the sensitivity of the results to data choices and model specification, t he a sset a llocation m odel i s r eestimated u sing fixed effects panel
regression to control for firm-specific factors that may affect pension asset
allocation d ecision. The u ntabulated r esults f rom fixed-effects regression a re consistent w ith t he 3SLS e stimates a s fa r a s t he ma in va riables
on pension funding (FUND) and the sensitivity measure on firms’ financial report r isk (PENRISK) a re concerned. The coefficient on PENRISK

© 2010 by Taylor and Francis Group, LLC


Corporate Risk Management and Pension Asset Allocation ◾ 385

remains negative and significant at 5% level, and the coefficient for FUND
is p ositive a nd sig nificant. The coefficient f or F UNDSQ i s n egative a nd
significant at 5% level. In summary, the sensitivity test indicates that the
findings are not driven by dependence among observations or the set of

control variables included.

16.6 CONCLUSION
This chapter examines the U.K. firms’ risk management of their pension
fund a sset a llocation, a nd its i nterrelationship w ith t heir pension f unding and pension-related accounting policy over an extended period (1998–
2002), during which the new U.K. pension accounting standard (FRS 17)
became effective. C ontrolling f or t he en dogeneity a mong pens ion a sset
allocation, funding, and the actuarial assumption on pension investment
return, the empirical evidence suggests that pension asset management is
consistent with a risk-offsetting explanation. Firms manage their pension
risk exposure in order to minimize cash contribution risks associated with
the adoption of “ fair va lue” based pension accounting r ules. The results
also support the view that U.K. trustees and managers have incorporated
their co rporate r isk-management p ractices i nto t he a llocation o f t heir
pension assets.

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