Blacconiere, Johnson e Johnson (2000)

7/23/2019 Blacconiere, Johnson e Johnson (2000)

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The authors thank Mary Barth, Daniel Beneish, Julia D'Souza, Peter Easton, Frank Hodge,

Patrick Hopkins, Ivo Jansen, Marty Loudder, Tom Lyon, Jody Magliolo, Jamie Pratt, Jerry

Salamon, Jim Seida, Nathan Stuart, Jim Wahlen, the editors (Ray Ball and Jerry Zimmerman) and

especially the referee (Dan Collins) for their comments. We also appreciated feedback received from

participants at the Indiana University, Michigan State University, Pennsylvania State University,

Stanford University Summer Camp, and University of Michigan Spring Training accounting

workshops and the 1999 American Accounting Association Annual Meetings. Walt Blacconiere and

Marilyn Johnson gratefully acknowledge the "nancial support of Ernst & Young, L.L.P.

*Corresponding author. Tel.:#1-812-855-2653.

E-mail address:[email protected] (W.G. Blacconiere).

Journal of Accounting and Economics 29 (2000) 231}260

Market valuation and deregulation ofelectric utilities

Walter G. Blacconiere*, Marilyn F. Johnson,Mark S. Johnson

Kelley School of Business, Indiana University, Bloomington, IN 47405-1701, USA

Eli Broad College of Business, Michigan State University, East Lansing, MI 48824-1121, USA

Received 2 September 1998; received in revised form 21 July 2000

Abstract

This study examines the e!ect of ongoing deregulation in the electric utility industry on

the relation between market value, book value, and earnings. We predict that deregula-

tion decreases (increases) the relative importance of book value (earnings) in explaining

price. We test this prediction by examining changes in the value relevance of book value

and earnings during the 1988}1996 time period for a sample of large, investor-owned

electric utilities. We "nd that the regression coe$cients and incremental explanatory

power related to book value (earnings) have decreased (increased) over this time period.

These results are generally robust in sensitivity analysis. 2000 Elsevier Science B.V.

All rights reserved.

JEL classixcation: G10; L43; L94; M41

Keywords: Market valuation; Electric utilities; Deregulation

0165-4101/00/$ - see front matter 2000 Elsevier Science B.V. All rights reserved.

PII: S 0 1 6 5 - 4 1 0 1 ( 0 0 ) 0 0 0 2 1 - 5


2/30

This is a simpli"ed description of the rate determination process. Although there are other

complicating factors (discussed later), the general concept of assured returns to utility shareholders

has strong support. For example, in the 1944 case Federal Power CommissionvHope Natural Gas Co

(320 US 591), United States Supreme Court Justice William O. Douglas wrote, &2it is important

that there be enough revenue not only for operating expenses, but also for the capital costs of the

business. These include service on the debt and dividends on the stock.'

1. Introduction

Recent studies have investigated the assertion that accounting information

has become less value relevant over time (see Collins et al., 1997; Francis andSchipper, 1999; Lev and Zarowin, 1999; Brown et al., 1999). This paper provides

additional evidence on this issue by focussing on a single industry undergoing

rapid change as a result of deregulation. This setting allows us to use economic

theory to make ex ante predictions about changes in the relation between

accounting information and "rm value. Speci"cally, we examine the "nancial

statement analysis implications of deregulation and increased competition in the

electric utility industry by investigating changes in the relative roles of book

value and earnings in explaining market value.Historically, electric utilities have been considered natural monopolies and

have been rate regulated. Under rate regulation, utilities have been allowed to

earn revenues equal to expenses plus a return on investment.However, techno-

logical advances (e.g., improved gas-turbine technology has made it easier to

generate electricity) and other economic factors (e.g., lower natural gas prices)

have prompted a call for a more competitive electric power industry. In re-

sponse, Congress passed the Energy Policy Act of 1992 in an e!ort to deregulate

the industry and reduce wholesale electricity prices.We hypothesize that the trend towards deregulation triggered by the 1992 Act

is associated with changes in the market's use of accounting information. In

theory, if all costs are eventually recoverable and the allowed return on invest-

ment is equal to the cost of equity capital, the market value of equity for

a regulated electric utility should approximately equal book value. Assuming

that there is little uncertainty about the allowed return and little measurement

error in book value, earnings will explain little variation in market value

incremental to book value. In contrast, in a deregulated environment where

utilities are not assured a return on book value, earnings signal a "rm's ability to

generate future abnormal earnings and should have greater importance. Thus,

we predict that book value (earnings) will become a less (more) important

determinant of market value following deregulation.

In practice, electric utility rate regulation contains imperfections. For

example, regulators can disallow some expenses and allowed returns are not

always equal to the cost of capital for the utility, so market value need not be

exactly equal to book value (Kolbe et al., 1984). In addition, earnings may be

232 W.G. Blacconiere et al./Journal of Accounting and Economics 29 (2000) 231}260


3/30

Brown et al. (1999) and Chang (1998) assert that time-series variation in scale confounds tests

that use incrementalRto assess changes in value relevance over time. Although there is no evidence

of pre- versus post-deregulation variation in the distribution of electric utility market values, the

presence of time-series variation in scale may limit tests of incremental explanatory power in other

settings.

value relevant in the pre-deregulation period due to a regulatory lag in the rate

setting process (Kahn, 1988) and the e!ect of incentive regulation on some

utilities (Lyon, 1994). Thus, imperfections in utility rate regulation prior to 1992

potentially bias our analysis against "nding results consistent with our predic-tions.

Our electric utility analyses are based on a sample of 933"rm/year observa-

tions for 1988}1996. Similar to Collins et al. (1997), we investigate changes in the

value relevance of book value and earnings by examining changes in both

regression coe$cients and the incremental explanatory power of the valuation

models. Two alternative de"nitions of earnings are considered: &bottom line'

net income and income before extraordinary items and discontinued operations.

We compare our electric utility "ndings to similar analyses of 836 "rm/yearobservations from a sample of capital intensive, non-utilities to show that this

control group did not exhibit similar types of changes during the period.

To provide empirical motivation for the value relevance of earnings, we assess

the empirical signi"cance of deregulation by testing for changes in earnings

persistence during the pre- versus post-Act periods. Consistent with the argu-

ment that an electric utility's ability to earn abnormal rents (or incur abnormal

losses) increased following the Act's passage, we "nd a statistically signi"cant

post-Act increase in earnings persistence. In contrast, no such increase is presentin the control sample.

Our value relevance tests suggest that following deregulation, the book value

of equity has become less value relevant for electric utilities. We observe

a decline in the magnitude of estimated coe$cients on book value over the study

period when earnings is de"ned as income before extraordinary items and

discontinued operations. In addition, the incremental explanatory power of

book value decreases for our utility sample under either de"nition of earnings.

In contrast, there is evidence that the magnitude of the estimated coe$cients on

book value increased for the control sample while the incremental explanatory

power of book value did not increase signi"cantly.

We"nd that the association between stock prices and earnings increased for

electric utilities. Using either de"nition of earnings, the regression coe$cient on

earnings has increased in magnitude. Additionally, the incremental explanatory

power of earnings before extraordinary items and discontinued operations also

increased. By comparison, there is no signi"cant change in the earnings coe$-

cients or the incremental explanatory power of earnings for the control sample.

W.G. Blacconiere et al./Journal of Accounting and Economics 29 (2000) 231}260 233


4/30

3 See Brennan et al. (1996) for a more detailed review of the history and regulation of the electric

utility industry. Prior research in accounting focussing on the electric utility industry includes

Blacconiere et al. (1997), Bowen (1981), D'Souza (1998), Khurana and Loudder (1994), Loudder et al.

(1996), Olsen (1985), and Teets (1992), among others.

Finally, when coe$cient estimates for the utility sample are compared with

the control in a pooled time-series cross-sectional model, we "nd signi"cant

di!erences prior to deregulation. However, both appear to be valued similarly

after passage of the 1992 Act.Overall, our results suggest that deregulation in the electric utility industry

has changed investors' perceptions of the relative roles of book value and

earnings in "rm valuation. Book value (earnings) has become less (more)

important in the valuation of electric utilities. In addition, our results are robust

to sensitivity analyses that (1) include controls for factors a!ecting the demand

for and supply of electricity; (2) test the predictions using a &changes', as opposed

to &levels', methodology; and (3) isolate regulatory assets from other components

of book value.The remainder of the paper proceeds as follows. In Section 2, we provide

a brief overview of the electric utility industry in the United States and explain

recent moves towards deregulation. We also discuss the value relevance of book

value and earnings under regulation, as well as the predicted e!ects of deregula-

tion on valuation relations. In Section 3, we describe the sample and empirical

models. Results of the empirical analysis are presented in Section 4. The "nal

section is the conclusion.

2. Background and predictions

2.1. Overview of the electric utility industry3

The modern public utility arose from the 1877 U.S. Supreme Court decision,

Munnv. Illinois, establishing the right of the federal and state governments to

regulate"rms that provide public services in a non-competitive environment.

Electric utility rate (or &cost-of-service') regulation attempts to determine prices

that balance customer requests for low rates against the need of electric utilities

to recover costs and earn a reasonable rate of return on investment.

Electric utilities have three operating segments. First, electric power is pro-

duced at large generation facilities. Second, electric power is transmitted to

substations. Third, power is distributed from the substations to customers

(Hyman, 1992). Early in the twentieth century, policymakers believed that

electric power would be provided to end-users at a minimum cost if there were

a small number of suppliers, each of whom operated in all three functional



5/30

Kuhn (1996) notes that nearly 60% of new electricity generation came from non-utility gener-

ators by 1995.

In subsequent sensitivity analyses, we demonstrate that the impact of deregulation on valuation

relations varies with the pace at which individual states are moving towards deregulation of the

generation segment.

segments. In 1935, in response to perceived abuses by these suppliers, the Public

Utility Holding Company Act (PUHCA) reorganized the small number of large

holding companies into a large number of smaller utilities. Each smaller utility

retained control over the generation, transmission, and distribution facilities inits region.

Until the Oil Embargo and related &Energy Crisis' in 1973, the industry

prospered and the regulatory climate was stable. However, increased oil prices

combined with the abandonment of expensive nuclear facilities due to unex-

pected shifts in forecasted demand resulted in rate increases under cost-of-

service regulation. Consumer pressure for lower electric rates and increased

competition led to the enactment of the Public Utility Regulatory Act of 1978.

This Act allowed new, low cost generating "rms that were not subject tocost-of-service regulation to compete with established utilities.

Initially, new generators sold their output to utilities since these new "rms did

not have the infrastructure to transmit and distribute power directly. However,

the Energy Policy Act of 1992 expanded competition in the generation segment

by instructing the Federal Energy Regulatory Commission (FERC) to order

electric utilities to open their transmission grids to third-party suppliers. This

Act has allowed new suppliers to provide an increasing share of electric power

generation.

Thus, federal legislation that provided open access to the nation'stransmission grid, together with the development of low-cost gas turbine tech-

nology, have increased the level of competition in the generation segment.

Although deregulation was still in process during the middle 1990s, utilities

were becoming increasingly competitive. After passage of the 1992 Act, electric

utilities began to manage their generation, transmission, and distribution seg-

ments as if they were stand-alone. Power generation was moving toward

complete deregulation, as evidenced by the increased volume of sales of kilowatt

hours in competitive regional wholesale markets. By the end of 1994, deregula-

tion of the generation segment had been implemented in California, Pennsyl-

vania, Rhode Island, and New Hampshire and was about to begin in twelve

other states (Miller, 1997).Generating assets comprised approximately 50% of

the typical electric utility's assets (Tilles, 1997), implying that a signi"cant

portion of a utility's earnings is determined in a competitive environment.

Deregulation of the generation segment has been accompanied by increased

competition in the distribution segment. For example, some states are unbund-

ling the distribution function into competitively provided services for meter

reading, accounts receivable, and customer service (Lapson, 1997). Although the



6/30

The Energy Policy Act of 1992 was introduced in the House of Representatives in February 1991

and signed by the President in October 1992. Thus, market values of electric utilities potentially

re#ected investors'expectations prior to 1992. Johnson et al. (1998)"nd that a negative stock price

reaction to events leading to the Act for a sample of publicly-held electric utilities. The announce-

ment with the most negative cumulative abnormal return was the bill's introduction.

transmission and parts of the distribution segments ostensibly remain rate-

regulated, limited incentive regulation schemes are being replaced by compre-

hensive performance-based regulations (Yajima, 1997). One example is the

&price-cap' system, which has been applied in the United Kingdom electric utilityand the U.S. telephone industries.

2.2. Prior empirical research on thevalue relevance of bookvalue and earnings

The relevance of"nancial statement information has been increasingly ques-

tioned. Jenkins (1994, p. 78) states that &[s]ome argue the external reporting

highway is in crisis and dangerously close to collapse'. Underlying this concern

is the argument that the "nancial reporting model is unable to capture theuncertain consequences of rapid, structural change in a value relevant manner.

Lev and Zarowin (1999) discuss signi"cant changes that are not adequately

re#ected by the "nancial accounting system and suggest that the usefulness of

earnings has decreased over time.

Recent empirical evidence on the changing value relevance of book value and

earnings is not necessarily consistent with the assertion that accounting in-

formation has become less useful over time. Collins et al. (1997) examine the

value relevance of earnings and book value over the last 40 years using 115,154"rm}year observations. They "nd that the value relevance of accounting in-

formation has not declined, but the relative importance of earnings has de-

creased while book value has become more value relevant. Further investigation

by Collins et al. reveals that the shift in value relevance from earnings to book

values is associated with: (1) an increase in the frequency and magnitude of

one-time items; (2) an increase in frequency of negative earnings; (3) changes in

average "rm size; and (4) changes in intangible intensity across time. Francis and

Schipper (1999) also "nd that the explanatory power of book value has in-

creased over the period 1952}1994, but there is evidence that the explanatory

power of earnings has decreased. In contrast, after controlling for scale e!ects in

levels regressions, Brown et al. (1999) document a decline in value relevance.

Our analysis is similar to Collins et al. (1997) and Brown et al. (1999) in that

we address the issue of the change in the value relevance of earnings and book

value over time. However, we focus on a single industry. The Energy Policy Act

of 1992 was a signi"cant event in the process towards deregulation and competi-

tion in the electric utility industry. Knowledge of industry structure and the



7/30

If the allowed rate of return is a cross-sectional constant, book value and earnings are redundant.

However, in practice, this does not appear to be the case. Kolbe et al. (1984) note that regulators use

a variety of methods to estimate allowed rates of return, each of which is aimed at calculating

a "rm-speci"c cost of capital.

See Joskow and Schmalensee (1986) and Lyon (1994) for a detailed discussion of various

incentive regulation schemes. Kahn (1988) reviews regulatory lag.

impact of deregulation allows us to make ex ante predictions about changes in

the relative and absolute importance of book value and earnings. Thus, this

legislation provides a &natural experiment' for examining the circumstances

under which structural change induced by an exogenous event such as de-regulation does (or does not) in#uence the relevance of "nancial statement

information.

2.3. Value relevance of bookvalue and earnings under rate regulation

In theory, in a rate-regulated environment, regulators set revenues such that

E"rBV, whereEis earnings,ris the allowed return (i.e., cost of equity capital),

and BV is book value.

Thus, the market value of equity for an electric utilityshould be approximately equal to book value under regulation assuming costs

are eventually recoverable and the allowed return on investment is equal to the

cost of equity capital.

In practice, imperfections in electric utility rate regulation tend to complicate

the relation between market value, book value, and earnings. It is unlikely that

utilities will be allowed to recover all costs and the allowed return will not

necessarily be set equal to the cost of equity (Kolbe et al., 1984). Although these

imperfections suggest that utility market-to-book ratios need not equal oneunder regulation, Nwaeze (1998) "nds that book value coe$cients are approx-

imately equal to one in regressions of electric utility prices on book value and

earnings.

However, earnings are not value irrelevant under regulation. In practice,

actual rate regulation deviates from cost-plus pricing due to the existence of

implicit and explicit incentive schemes. An example of an implicit incentive

scheme is regulatory lag, which arises because the periodic nature of the rate

setting process implies a delay in the downward (upward) adjustment of electric

rates in response to positive (negative) shocks. Freezing rates for the period of

the lag imposes an implicit penalty on managers'mistakes. However, managers

who improve their "rms' performance are allowed to keep the higher pro"ts

until the next rate hearing. Explicit incentive regulation schemes typically allow

rto vary with some indicator of managers'performance. Most common are the

various sliding scale plans, where a "xed ceiling on the rate that a utility can

charge is set and it is allowed to keep all pro"ts earned up to a limit. Pro"ts in



8/30

Stranded assets are relatively high-cost generating facilities, regulatory assets, and other costs

that are not expected to be recovered in a competitive wholesale power market (Blacconiere et. al.,

1997; D'Souza and Jacob, 2000).

Prior research documents a negative relation between competition and earnings persistence

(Lev, 1983; Biddle and Seow, 1991; Ahmed, 1994). In the absence of rate regulation, increased

competition in product markets is associated with smaller future earnings revisions in response to

a current earnings surprise. However, monopoly rents are disallowed under rate regulation (unless

regulators are captured). Therefore, increased competition under deregulation implies an increasein

earnings persistence.

excess of the limit are shared with customers via future rate reductions or

rebates.

Under theoretical cost-plus pricing, an electric utility's abnormal earnings are

zero. However, all utility regulatory commissions have adopted some variant ofan incentive regulation scheme (Joskow and Schmalensee, 1986), implying

a limited opportunity for all electric utilities to earn non-zero abnormal earn-

ings. The existence of non-zero abnormal earnings implies that an electric

utility's earnings will provide information about"rm value incremental to that

contained in book value. Consistent with this argument, in analyses of the

valuation relevance of book value and earnings prior to 1991 for a sample of

utilities, Nwaeze (1998) "nds that the coe$cient on earnings is signi"cant in

three of four years during 1987}1990.

2.4. Value relevance of bookvalue and earnings under deregulation

Following deregulation in 1992, as competition in the electric utility industry

increases, uncertainty about a "rm's ability to earn a return on book value

increases, and the value relevance of book value should decrease. This uncer-

tainty arises as a result of &stranded assets'. Under rate regulation, utility

shareholders are virtually assured a rate of return on these assets. In contrast, ina deregulated environment, the eventual recovery of these capitalized costs

depends upon factors beyond regulatory control (e.g., growth in demand for

electric power, improvements in generating technology, and the future prices of

energy), as well as factors under the control of utility regulators (e.g., the pace of

deregulation and the #exibility utilities are allowed in setting prices).

Conversely, the Act's passage implies an increase in the value relevance of

earnings. Generating segment earnings are determined in a competitive environ-

ment, while transmission and distribution earnings are determined under perfor-

mance-based regulatory schemes that are more comprehensive than traditional

incentive regulation (Yajima, 1997). Together, these factors suggest that the

ability of"rms in the electric utility industry to earn abnormal pro"ts and losses

has increased following deregulation.

Residual income valuation models such as Ohlson (1995) split equity value,


9/30

Frankel and Lee (1998) and Dechow et al. (1999) assess the descriptive validity of residual

income valuation models, as well as discussing the relative roles of BV and E in these models.

However, we include variables that proxy for changes in demand and supply factors in

subsequent sensitivity analysis.

equity investment andE, a measure of the "rm's ability to earn abnormal pro"ts.

The more persistent a "rm's abnormal income, the higher (lower) the weight that

is placed on E (BV) when determining


10/30

Collins et al. (1997) include special items along with extraordinary items and discontinued

operations when de"ning &one-time' items. However, COMPUSTAT includes the &Allowance for

funds used during construction' in special items. Since this is a recurring, value relevant item for

many utilities (Bowen, 1981), our adjusted earnings number considers only the e!ects of extraordin-

ary items and discontinued operations. We consider the potential e!ect of special items in sensitivity

analysis.

earnings persistence. We also expect earnings persistence to increase for electric

utilities that will be at a competitive disadvantage under deregulation since these

"rms are likely to incur abnormal losses. Consequently, we test for a change in

earnings persistence following the passage of the 1992 Act by regressing thecurrent year change in earnings per share (E) on the prior year's change and an

indicator variable, TIME, that allows the slope coe$cient on the prior year's

change to vary following the Act's passage:

E!E

"

#

(E

!E

)

#

(E!E

)TIME#

TIME#e

, (1)

whereE

is the earnings per share for"rmjover the"scal yeart, and TIME an

indicator variable equal to one for the years 1992}1996 and zero otherwise.

If there is an increase in earnings persistence following the Act 's passage, we

expect that

will be positive and signi"cant.

3.3. Evidence of changingvaluation relations

Similar to Collins et al. (1997), we estimate annual regressions of the followingmodel:

P"

#

BV

#

E#

, (2)

wherePis price per share of"rmjthree months after the close of the"scal year

(adjusted for dividends and net changes in capital during the "scal year), BVthe

book value per share of"rmj at the close of"scal year, andEthe earnings per

share for "rm j over the "scal year.

We use two de"nitions of earnings in the analysis. Consistent with Collins et

al. (1997), E

is de"ned as &bottom line' net income (NI). In addition, income

before extraordinary items and discontinued operations (IBEIDO) is used to

control for non-recurring items in earnings.

We expect that the magnitude and signi"cance of the estimates of

(

) will

decrease (increase) for the electric utility sample as a result of deregulation. To

assess the e!ect of deregulation on the regression coe$cients, two Z-statistics,

Z

and Z

are used to test the signi"cance of annual t-statistics during the



11/30

Z

tests the null hypotheses that the time-series mean of annual t-statistics equals zero under

the assumption that parameters are independent across years. If parameters are not independent,

Z

potentially is overstated. Thus, we also estimate Z

that corrects for this potential lack of

independence (see Barth, 1994; Healy et al., 1987).

Like Collins et al. (1997), we control for potential"rst-order autocorrelation using the approach

developed by Prais and Winsten (1954) and described in Greene (1990).

sample period. The Z-statistics are computed as:

Z"

1

N

t-stat

k/(k!2), (3)

where

t-stat"t-statistic for year t,

k "degrees of freedom for year t,

N "number of years

and

Z"

t-stat

(t-stat)

1

(N!1)(4)

where

t-stat "mean t-statistic during the N year period,

(t-stat)"standard deviation of the t-statistics during the N year period.

Since we expect that book value (earnings) will become less (more) signi"cant

after deregulation, Z-statistics associated with t-statistics of

(

) are pre-

dicted to be lower (higher).

In addition, regressing the estimated coe$cients on a time-trend variable as

follows formally assesses the signi"cance of any change in coe$cient magni-

tudes:

"#TIME# , (5a)

"

#

TIME

#

, (5b)

where

,"estimated coe$cients from Eq. (2) for year t,

TIME"1,2, 9 for the years 1988}1996.



12/30

This test implicitly assumes that the e!ect of deregulation on the value relevance of book value

and earnings started to occur prior to the passage of the 1992 Act and has since been ongoing. This is

a reasonable assumption given the evidence in Johnson et al. (1998) of a negative reaction to

announcements of impending deregulation during February 1991. Further, the pace of deregulation

has varied by states, and no state had fully implemented deregulation by 1996. Thus, we assume that

the market is making a &rolling assessment' of the e!ect of deregulation on value relevance during the

sample period.

Negative estimates of

(positive estimates of

) are consistent with our

expectations of a decrease (increase) in the relative importance of book value

(earnings) in explaining price.

Following from Collins et al. (1997) and Easton (1985), we also decompose thetotal explanatory power of Eq. (3) (the adjusted Rvalue denotedR

) into the

incremental explanatory power of book value (R

), and the incremental ex-

planatory power of earnings (R

). To calculate the incremental explanatory

power, we"rst estimate theRvalues (R

andR

) from annual (year-by-year)

regressions of the following models:

P"

#

BV

#

, (6a)

P"#E# . (6b)

The incremental explanatory power of book value is R"R

!R

, and

the incremental explanatory power of earnings isR"R

"R

. To assess the

e!ect of deregulation on the total explanatory power, incremental explanatory

power of book value, and incremental explanatory power of earnings, we regress

R

, R

, and R

on a time-trend variable as follows:

R"

#

TIME

#

, (7)

wheren" for total, BV for book value, and E for earnings.

A negative estimate of

and a positive estimate of

are consistent with

our expectations of a decrease (increase) in the value relevance of book value

(earnings) for electric utilities as the industry faces deregulation.

The analyses are also performed on the control. Since these "rms were not

facing deregulation, we o!er no predictions about the existence or direction of

time trends in the estimates. However, we do o!er predictions about the relative

magnitudes of the coe$cients before and after deregulation. To compare theestimated coe$cients for both samples, we estimate the following pooled time-

series cross-sectional, "xed"rm and year e!ects valuation model:

P"

#

BV

#

BV

NONUTIL#

BV

TIME

#

BVNONUTIL TIME#

E

#

E

NONUTIL

#E

TIME#

E

NONUTIL TIME#

, (8)



13/30

Unlike the year-by-year analysis where we assume that deregulation has been an ongoing

process, this model assumes that the electric utilities are valued as regulated "rms up to the Energy

Policy Act of 1992 and are valued as deregulated "rms thereafter.

Nwaeze (1998)"nds that the coe$cients for book value (earnings) are higher (lower) for electric

utilities compared to manufacturing"rms during 1970}1990.

All variables are winsorized at the 0.5% and 99.5% in the analyses.

where

NONUTIL" an indicator variable equal to one for the control and zero for

utilities,TIME " an indicator variable equal to one for the years 1992}1996 and

zero otherwise.

A negative estimate of

and a positive estimate of

are consistent with our

expectations of a decrease (increase) in the value relevance of book value

(earnings) for electric utilities as a result of deregulation. In the pre-deregulation

era, we expect that the coe$cients on utility book value (earnings) to be higher

(lower) than the coe$cient on the control book value (earnings), (i.e., (0,

'0).After deregulation, we expect that the coe$cients for book value and

earnings are the same for both samples of"rms (i.e.,#

"0,

#

"0).

4. Results

4.1. Descriptive statistics

Descriptive statistics are provided in Table 1 panels A and B.Mean price,

P(adjusted for dividends, net changes in capital, and stock splits) is smaller for

the electric utility sample ($28.711) compared to the control ($37.256). Mean

Pdecreases for the electric utility sample between the two periods (from $29.948

to$27.099) while it increases for the control (from$35.433 to$38.813). However,

there is a decrease in the median price per share over the two periods for both

samples. The mean per share values of BV, NI, and IBEIDO are higher for the

control, and it has greater variance in these values, as measured by higher

standard deviations and wider interquartile ranges. In the post-deregulation

period, standard deviations for the electric utility sample are lower than those

observed during the pre-period. In contrast, standard deviations for the control

variables are of comparable magnitudes in the two periods.

Panels C and D in Table 1 contain the Pearson (Spearman) correlation

coe$cients. For both samples, correlations amongP, BV, NI, and IBEIDO are

large and positive. The correlations between P and BV decrease while the

correlations betweenPand both NI and IBEIDO increase over the two periods



14/30

Table 1

Descriptive statistics and correlations

Variable Mean

Standard

deviation

Lower

quartile Median

Upper

quartile

Panel A: Descriptive statistics for the electric utility sample

1988}1996

P 28.711 9.469 22.494 27.958 34.872

BV 19.401 6.279 15.544 18.720 22.879

NI 2.228 1.771 1.858 2.341 2.940

IBEIDO 2.265 1.502 1.864 2.335 2.916

1988}1991P 29.948 9.658 23.166 29.008 36.235

BV 20.206 6.482 16.012 19.311 23.771

NI 2.298 2.164 1.971 2.464 3.215

IBEIDO 2.372 1.809 1.992 2.447 3.198

1992}1996

P 27.099 8.976 21.422 26.784 32.256

BV 18.352 5.847 15.188 17.956 21.800

NI 2.136 1.052 1.755 2.163 2.690

IBEIDO 2.125 0.949 1.747 2.159 2.643

Panel B: Descriptive statistics for the control

1988}1996

P 37.256 26.331 18.455 31.894 49.407

BV 19.921 13.591 10.501 19.045 28.135

NI 3.042 2.251 1.353 2.642 4.236

IBEIDO 3.020 2.266 1.339 2.605 4.128

1988}1991

P 35.443 24.009 18.040 34.680 47.804

BV 20.795 13.197 11.178 20.229 28.699NI 3.366 2.254 1.489 3.171 4.698

IBEIDO 3.275 2.300 1.401 3.097 4.511

1992}1996

P 38.813 28.157 18.634 30.036 50.766

BV 19.171 13.919 9.285 17.098 26.184

NI 2.764 2.217 1.249 2.303 3.423

IBEIDO 2.800 2.220 1.298 2.331 3.599

for the utility sample. For the control "rms, there is a slight increase (decrease) in

the correlation(s) betweenPand BV (both NI and IBEIDO) over the same time

frame.

4.2. Ewect of deregulation on earnings persistence

Table 2 reports the results from tests that examine whether there was an

increase in earnings persistence following deregulation. Consistent with our



15/30

Table 1 (continued)

Variable P BV NI IBEIDO

Panel C: Correlation coezcients for the electric utility sample

1988}1996

P 0.737 0.541 0.576

BV 0.700 0.543 0.597

NI 0.727 0.753 0.929

IBEIDO 0.735 0.760 0.979

1988}1992

P 0.746 0.549 0.557

BV 0.707 0.553 0.593

NI 0.718 0.769 0.929

IBEIDO 0.717 0.770 0.983

1992}1996

P 0.709 0.605 0.681

BV 0.686 0.594 0.660

NI 0.739 0.752 0.939

IBEIDO 0.755 0.762 0.976

Panel D: Correlation coezcients for the control

1988}1996P 0.725 0.733 0.763

BV 0.793 0.698 0.703

NI 0.770 0.733 0.979

IBEIDO 0.792 0.740 0.979

1988}1992

P 0.748 0.771 0.826

BV 0.780 0.733 0.742

NI 0.797 0.750 0.958

IBEIDO 0.828 0.755 0.960

1992}1996

P 0.722 0.738 0.744

BV 0.792 0.669 0.670

NI 0.768 0.712 0.997

IBEIDO 0.776 0.713 0.993

The descriptive statistics and correlations are based on 933 "rm/year observations for the utility

sample and 836 "rm/year observations for the control.

Variable descriptive statistics are on a per share basis. Variables are de"ned as follows:P"price three months after the close of the"scal year (adjusted for dividends and net changes in

capital during the "scal year),

BV"book value at the close of the "scal year,

NI"net income at the close of the "scal year, and

IBEIDO"income before extraordinary items and discontinued operations at the close of the

"scal year.

The upper diagonals (lower diagonals) of Panels C and D contain the Pearson (Spearman)

correlation coe$cients for the utility and control samples, respectively.



16/30

Table 2

Changes in the persistence of earnings for 1988}1996

Eq. (1): E!E

"

#

(E

!E

)#

(E

!E

) TIME#

TIME#

Variable Electric utility sample Non-utility sample

Intercept 1.188 0.216

(0.0001) (0.2595)

(E!E

) 0.444 0.621

(0.0001) (0.0001)

(E!E

) TIME 0.157 !0.040

(0.0096) (0.2537)

TIME 0.191 0.945

(0.0447) (0.0001)AdjustedR 0.22 0.24

Reportedp-values (shown parenthetically) for the estimated coe$cients are one-tailed except for

the intercept. The variables in Eq. (1) are de"ned as follows:

E"earnings per share for "rm j over the "scal year t, and

TIME"an indicator variable equal to one for the years 1992}1996 and zero otherwise.

In results not reported, we formally test the hypothesis that the coe$cients on book value equalone. For the electric utility sample, when earnings is de"ned as either IBEIDO or NI,

is

statistically indistinguishable from one in three of the four pre-deregulation years. In contrast, for

the control, when earnings is de"ned as either IBEIDO or NI,

is statistically indistinguishable

from one in none of the four pre-deregulation years. Following deregulation, when earnings is

de"ned as IBEIDO (NI),

for utilities equals one in only two out of"ve (three out of"ve) years.

By comparison,

for control"rms equals one in four out of"ve years under either de"nition of

earnings. Thus, we observe pre-deregulation di!erences across the two samples that are mitigated

post-deregulation.

prediction for the utility sample, the coe$cient on is positive and signi"cant(p"0.0096, one-tailed test). For the control, this coe$cient is insigni"cant,

implying that there is no evidence that control "rms experienced a change in

earnings persistence.

4.3. Ewect of deregulation on the magnitude of coezcients

Table 3 presents results from the year-by-year estimation of Eq. (2). Overall,

the book value coe$cient estimates,

, tend to be larger and more signi"cant

for the electric utilities than the control. Utility sample estimates of

are close

to one in most cases, while estimates for the control are typically less than one.

For both samples, almost all estimates of

exceed one. Re#ecting the signi"-

cance of the year-by-year coe$cients, when the t-statistics are averaged across

the sample period, the resulting Z

and Z

statistics are all signi"cant.



17/30

Means and Z-statistics (not presented) comparing the periods 1988}1992 and 1993}1996 are

similar to those reported in Table 2.

We also compute separate Z-statistics for the pre-deregulation and post-

deregulation periods. For the electric utility sample, the mean estimate of

decreases from 0.938 to 0.845, Z

decreases from 19.223 to 15.200, and

Z decreases from 19.732 to 7.337 where earnings are de"ned as NI. A similarpattern holds where earnings are IBEIDO. The coe$cient related to earnings

(

) increased for the electric utility sample (e.g., when earnings are de"ned as

NI, the mean estimate of

increases from 1.002 to 2.935). The corresponding

Z-statistics also increased. In contrast, the control shows an increase in both the

magnitude and signi"cance of

from the 1988}1991 period to the 1992}1996

period, while a decrease in the magnitude of

between the two periods is

observed.

To assess the formal signi"cance of the coe$cient patterns in Table 3,Table 4 presents estimates from Eqs. (5a) and (5b) in which the year-by-year

and

estimates are regressed on a time-trend variable. In panel A, when

earnings are de"ned as NI, there is a negative but insigni"cant trend in

(i.e.,

thet-statistic for

is}0.332); however this relation becomes signi"cant when

earnings are IBEIDO (i.e., the t-statistic for

is }2.212). Under both de"ni-

tions of earnings, there is a signi"cant increase in

over time for the electric

utility sample (i.e., thet-statistics for

are 2.344 and 3.324 for NI and IBEIDO,

respectively). In contrast, panel B suggests that the estimated coe$cient forbook value increased over time for the control while the time trend in the

earnings coe$cient is not signi"cant. Since the coe$cient patterns for the

electric utility sample di!er markedly from those of the control, the electric

utility results are attributable to the impact of deregulation, as opposed to

capital intensity, per se. Taken together, the results for the electric utility sample

are generally consistent with our prediction that deregulation is followed by

a decrease (increase) in the value relevance of book value (earnings).

4.4. Ewect of deregulation on total and incremental explanatory power

Table 5 presents the total and incremental R values for NI and IBEIDO

earnings. As expected, the incremental explanatory power of book value (R

)

before deregulation is much higher than the incremental explanatory power of

earnings (R

) for the utility sample. However, the incremental explanatory

power of electric utility book value has shown a decreasing trend since 1991

under both NI and IBEIDO. After being less value relevant in the earlier years,

electric utility earnings have shown some tendency to increase in relevance. Bycomparison, the incremental explanatory power of book value for the control

has generally shown an increasing trend under both NI and IBEIDO. Except for



18/30

Table 3

Coe$cient estimates, t-statistics, andZ-statistics from annual regressions of price on book value and

earnings for 1988}1996

Eq. (2): P"

#

BV

#

E

#

Earnings"

NI Earnings"

IBEIDO

Year

No. of

"rms

t-stat

t-stat

t-stat

t-stat

Panel A: Estimates for the electric utility sample

1988 108 0.771 8.793 1.420 4.877 0.766 5.931 2.233 3.926

1989 105 0.856 10.124 1.590 5.747 0.871 10.010 1.689 5.104

1990 106 1.079 10.674 0.733 2.894 1.073 10.481 0.836 2.858

1991 104 1.045 9.225 0.265 0.991 1.005 8.969 0.482 1.517

1992 105 1.075 8.280 2.871 4.035 0.927 7.697 3.383 4.2971993 103 0.826 8.896 1.690 3.991 0.828 9.627 1.968 4.677

1994 100 0.508 4.341 4.998 6.159 0.553 4.624 4.640 5.560

1995 101 0.949 7.142 2.459 3.304 0.747 4.668 4.091 3.816

1996 101 0.871 5.667 2.655 2.799 0.469 2.937 7.009 5.854

1992}1996

Mean 0.887 2.076 0.804 2.415

Z

24.415 11.420 21.439 12.414

Z

11.662 6.600 7.406 8.673

1988}1991

Mean 0.938 1.002 0.929 1.310

Z

19.223 7.087 17.527 6.639

Z

19.732 2.806 7.495 3.797

1992}1996

Mean 0.845 2.935 0.705 3.521

Z

15.200 8.984 13.087 10.718

Z

7.337 6.331 4.387 11.338

1994, the incremental explanatory power of earnings has been greater than the

incremental explanatory power of book value for the control.

Table 6 assesses the statistical signi"cance of the trends displayed in Table 5.

For the electric utility sample, the decrease in the incremental explanatorypower of book value is signi"cant under both NI and IBEIDO. For IBEIDO,

the trend in earnings (R

) is positive and signi"cant, but the positive trend is not

signi"cant under the NI de"nition. For the control, there are no signi"cant

trends in total or incremental explanatory power. Again, the di!erences in

results for the utility sample versus the control suggest that the changes in the

incremental explanatory power of earnings and book value for electric utilities

are attributable to the movement towards deregulation.

Brown et al. (1999) and Chang (1998) suggest that the results of incrementalR are sensitive to time-series variation in scale e!ects. Consequently, we



19/30

Table 3 (continued)

Earnings"NI Earnings"IBEIDO

Year

No. of

"rms

t-stat

t-stat

t-stat

t-stat

Panel B: Estimates for the control

1988 80 0.605 2.733 4.619 3.571 0.491 2.823 5.841 5.607

1989 86 0.286 0.867 6.315 4.814 0.285 0.861 6.316 4.816

1990 85 0.436 1.795 8.444 4.071 0.371 1.515 8.937 4.295

1991 87 0.172 0.447 14.629 5.109 0.233 0.523 14.011 4.447

1992 92 1.188 3.619 11.189 3.864 0.827 2.380 9.343 4.5671993 95 0.546 4.438 9.835 7.607 0.538 4.184 9.622 7.249

1994 100 1.165 4.472 3.628 1.441 1.087 4.145 4.567 1.833

1995 106 0.637 1.762 3.998 2.227 0.649 1.832 4.022 2.268

1996 105 0.563 1.976 10.850 6.846 0.598 2.128 10.709 6.843

1988}1996

Mean 0.622 8.167 0.564 8.152

Z

7.292 13.042 6.725 13.824

Z

4.973 6.264 4.967 7.268

1988}1991Mean 0.375 8.502 0.345 8.776

Z

2.886 8.679 2.827 9.470

Z

2.484 10.868 2.440 14.157

1992}1996

Mean 0.820 7.900 0.740 7.653

Z

7.201 9.734 6.494 10.077

Z

4.962 3.209 5.146 3.632

Eq. (2) is estimated for each year based on the number of"rms indicated in the second column.Earnings are de"ned alternatively as net income (NI) and income before extraordinary items and

discontinued operations (IBEIDO). Annual estimates of

and

and the related t-statistics are

presented for both speci"cations of earnings.

These are the mean coe$cient estimates andZ-statistics for the period 1988}1996.Z

andZ

test

the null hypotheses that the time-series mean of annual t-statistics equals zero and are computed as

follows:

Z"

1

N

t-stat

k/(k

!2)

Z"

t-stat

(t-stat)

1

(N!1)

wheret-stat is the t-statistic for year t, k

is the degrees of freedom for year t, N is the number of

years,t-stat is the meant-statistic during theNyear period, and(t-stat) is the standard deviation of

the t-statistics during the N year period.

These are the mean coe$cient estimates andZ-statistics for the pre-deregulation (1988}1991) and

post-deregulation periods (1992}1996).



20/30

Table 4

Autoregression of coe$cient estimates from price-book value-earnings-regressions on a time trend

variable

Eq. (5a): "#TIME# .

Eq. (5b): "

#

TIME

#

.


Trend in:


,

estimate !0.009 0.315 !0.046 0.590

t-Statistic !

0.332 2.344 !

2.212 3.324


,

estimate 0.064 0.228 0.070 0.072

t-Statistic 1.612 0.743 1.833 0.134

Estimates of

and

from Eq. (2) are the dependent variables in Eqs. (5a) and (5b). Earnings

are de"ned alternatively as net income (NI) and income before extraordinary items and discontinued

operations (IBEIDO). TIMEequals 1 for 1988 and increases by 1 with every additional year in Eqs.

(5a) and (5b). Estimates of

,

and related t-statistics are presented for both measures of

earnings. These estimates are adjusted for"rst-order autocorrelation using the approach developedby Prais and Winsten (1954) and described in Greene (1990).

examine whether the post-deregulation cross-sectional distribution of the mar-

ket values of our utility sample di!ers from the pre-deregulation distribution.

Speci"cally, we apply the Kolmogorov}Smirno!test to examine whether the

pre- versus post-electric utility samples come from the same distribution. The

analysis is sensitive to any type of di!erence (i.e., shape or location) between the

two samples and is based on the largest di!erence between the cumulative

density functions of the two samples. The test statistic, 0.63, does not signi"-

cantly di!er from zero (p"0.8151), implying that we cannot reject the null

hypothesis that the pre- versus post-sample market values are drawn from the

same distribution. Thus, issues raised by Brown et al. (1999) and Chang (1998)

do not appear to be applicable to our sample.

4.5. Pooled time-series cross-sectional analysis

Table 7 presents results from estimating Eq. (8). We include interaction terms

that allow the slope coe$cients on book value and earnings to vary following

deregulation, as well as interaction terms that allow coe$cients to vary across

the samples.

We "rst consider the utility results. When earnings are de"ned as NI, the

estimated coe$cients on BV TIME and ETIME have the correct sign but are



21/30

Table 5

Total and incremental R values from annual regressions of price on book value and earnings for

1988}1996


Total Increm. Increm. Total Increm. Increm.

Year R

R

R

R

R

R


1988 0.6318 0.2652 0.0792 0.6062 0.1270 0.0536

1989 0.6948 0.3008 0.0749 0.6781 0.3099 0.0582

1990 0.6558 0.3739 0.0244 0.6551 0.3610 0.0237

1991 0.6451 0.2926 !

0.0010 0.6497 0.2729 0.00451992 0.7282 0.1782 0.0403 0.7332 0.1509 0.0453

1993 0.7000 0.2321 0.0443 0.7147 0.2591 0.0590

1994 0.6956 0.0554 0.1147 0.6789 0.0668 0.0980

1995 0.5710 0.2167 0.0429 0.5849 0.0871 0.0568

1996 0.3644 0.1998 0.0439 0.4914 0.0392 0.1709


1988 0.7145 0.0393 0.0713 0.7834 0.0321 0.1402

1989 0.7142 !0.0027 0.2439 0.7143 !0.0028 0.2440

1990 0.7023 0.0265 0.1855 0.7154 0.0147 0.1986

1991 0.8244 !0.0127 0.4008 0.7871 !0.0140 0.3635

1992 0.8542 0.1176 0.1354 0.8790 0.0376 0.1602

1993 0.8607 0.0685 0.2084 0.8525 0.0642 0.2002

1994 0.5539 0.2231 0.0127 0.5681 0.1840 0.0269

1995 0.4458 0.0364 0.0686 0.4486 0.0406 0.0714

1996 0.8224 0.0129 0.2037 0.8223 0.0157 0.2036

Total explanatory power (R

) is the adjusted R values from Eq. (2) estimated for each year.

Incremental explanatory power of book value (R

) and earnings (R

) is calculated in two steps.

First,R values (R

and R

) are estimated for annual regressions of the following models:

P"

#

BV

#

(5a).

P"

#

E

#

(5b).

Second, the incremental explanatory power is computed as follows:

R"R

!R (5b).

R"R

!R (5a).

Earnings are de"ned alternatively as net income (NI) and income before extraordinary items and

discontinued operations (IBEIDO), and annual estimates are presented under both speci"cations of

earnings.

insigni"cant. By comparison, these coe$cients are signi"cant (p(0.05) under

the IBEIDO de"nition. This is consistent with the evidence in panel A of

Table 4 that shows stronger results for IBEIDO. Additionally, the coe$cient on



22/30

Table 6

Autoregression of total and incremental R on a time trend variable

Eq. (7): R"

#

TIME

#

where n", BV, or E.


Trend in: R

R

R

R

R

R


Estimate !0.024 !0.021 0.018 !0.012 !0.028 0.011

t-Statistic !1.527 !2.209 0.711 !0.973 !2.183 2.097


Estimate !

0.009 0.009 !

0.012 !

0.014 0.008 !

0.014t-Statistic !0.433 0.957 !0.779 !0.682 0.959 !1.167

An estimate ofR

is the dependent variable in Eq. (7), and these estimates are described in the

notes to Table 4. Earnings are de"ned alternatively as net income (NI) and income before

extraordinary items and discontinued operations (IBEIDO). TIMEequals 1 for 1988 and increases

by 1 with every additional year. Estimates of

and related t-statistics are presented for both

measures of earnings. These estimates are adjusted to consider potential "rst-order autocorrelation

using the approach developed by Prais and Winsten (1954) and described in Greene (1990).

As an additional test of di!erences between samples, we estimated year-by-year regressions

including interaction terms that allow the slope coe$cients on BV andE (i.e., IBEIDO) to vary for

the control (i.e., BV NONUTIL,E NONUTIL). Results (not reported) suggest that the book value

(earnings) coe$cients di!er signi"cantly during 1988}1991 and 1993 (1988}1993) while the di!er-

ences in coe$cient estimates are not signi"cant after 1993.

BV (i.e., the pre-deregulation coe$cient) does not di!er from one under either

NI or IBEIDO.

When the utility coe$cients are compared with the control, there is evidence

that the value relevance of book value and earnings di!ered between the two

prior to deregulation. The estimated negative coe$cient on BV NONUTIL and

positive coe$cient on E NONUTIL are signi"cantly di!erent than zero under

both NI and IBEIDO. In contrast, post-deregulation, the estimated coe$cient

on BV does not appear to di!er between the samples, as evidenced by results

from an F-test indicating that the sum of the coe$cients BV NONUTIL and

BV NONUTIL TIME is not signi"cantly di!erent from zero. Results from

F-tests of the sum of the coe$cients E NONUTIL and E NONUTIL TIME are

mixed. For NI earnings, the control has a signi"cantly more positive earnings

coe$cient. However, the coe$cients across the two samples are not signi"cantly

di!erent for IBEIDO earnings. Overall, these results are consistent with utilities

being valued di!erently than non-utilities prior to deregulation and more

similarly to non-utilities following deregulation.



23/30

Table 7

Pooled "xed e!ects time-series cross-sectional regression models comparing the utility sample to the

control

Eq. (8): P"#BV#BVNONUTIL#BVTIME#BVNONUTIL TIME#

E

#

E

NONUTIL#

E

TIME#

E

NONUTIL TIME#

.

Variable Expected sign Earnings"NI Earnings"IBEIDO

Intercept ? 7.991 7.938

(0.0001) (0.0001)

BV (#) 0.975 0.990

(0.0001) (0.0001)

BV NONUTIL (!) !0.377 !0.429

(0.0038) (0.0001)BV TIME (!) !0.0468 !0.133

(0.1916) (0.0182)

BV NONUTIL TIME ? 0.303 0.475

(0.0031) (0.0001)

E (#) 0.235 0.144

(0.0863) (0.2501)

E NONUTIL (#) 0.906 1.816

(0.0779) (0.0004)

E TIME (#) 0.371 1.118

(0.1920) (0.0014)E NONUTIL TIME ? 0.527 !0.865

(0.4535) (0.2542)

AdjustedR 0.85 0.85

F-tests (p-values in parentheses):

NI model: BV NONUTIL#BV NONUTIL TIME"0, F"0.2679 (0.6048).

NI model: ENONUTIL#ENONUTIL TIME"0, F"7.2131 (0.0074).

IBEIDO model: BV NONUTIL#BV NONUTIL TIME"0, F"0.1031 (0.7482).

IBEIDO model: ENONUTIL#ENONUTIL TIME"0, F"2.6308 (0.1051).

Both year and "rm intercepts are included in the pooled "xed e!ects regressions. Reported

p-values (shown parenthetically) for the estimated coe$cients are one-tailed unless no sign is

predicted.

The dependent variable is price adjusted for net capital transactions (i.e., the e!ects of dividends,

share issuances, and share repurchases) on a per share basis.

Independent variables are de"ned as follows:

BV"book value of equity per share at the close of"scal year,

E"net income (or income before extraordinary items and discontinued operations) per share for

the "scal year,

NONUTIL"an indicator variable equal to one for the control and zero for utilities, andTIME"an indicator variable equal to one for the years 1992}1996 and zero otherwise.

4.6. Specixcation checks

Our primary analyses follow from Collins et al. (1997). To test the robustness

of our results, we use data for the utility sample to perform several speci"cation



24/30

Collins et al. (1997) found that the intertemporal shift in value relevance is associated with

one-time items and negative earnings. In results not reported, we estimate pooled "xed "rm and year

e!ects models where (a) earnings are de"ned as income before extraordinary items, discontinued

operations, and special items and (b) observations where net income is negative are eliminated. The

estimated coe$cients on BV TIME and ETIME are signi"cant in the predicted directions under

these speci"cations.

checks. These analyses are based on pooled time-series cross-sectional regres-

sions with "xed"rm and "xed year e!ects (see Table 8). Throughout, earnings

are de"ned as IBEIDO, as we "nd it is a more relevant measure than NI.

4.6.1. Alternative pooled time-series cross-sectional models of returns

Skinner (1996) notes that cross-sectional valuation models like those we

estimate potentially have correlated omitted variables and an associated

measurement error bias. Easton (1998) argues that scale exerts a signi"cant

e!ect on the results of value relevance tests that are speci"ed in price form, but

that returns speci"cations of the tests are less sensitive to scale e!ects. In

contrast, Barth and Clinch (1999) argue that size di!erences across"rms do not

imply scale e!ects that lead to incorrect inferences. Although our utilities sampleis not characterized by pre- versus post-deregulation variation in scale, it is still

possible that other correlated omitted variables exist. To address this possibility,

we examine the sensitivity of our results to the consideration of three issues.

First, we estimate a model using returns (i.e., changes) rather than price (i.e.,

levels). The model examined is similar to the speci"cations of Francis and

Schipper (1999) and Nwaeze (1998) where returns are included as the dependent

variable and earnings (i.e., change in book value of equity due to earnings) and

change in earnings are the independent variables (see Table 8, panel A). In model1, the dependent variable is percentage change in price (adjusted for dividends

and capital transactions). The independent variables}the change in book value

and the change in earnings } are de"ned as IBEIDO and change in IBEIDO,

respectively. The estimated coe$cients in model 1 for ETIME and ETIME

are signi"cant in the prediction direction (at p(0.001).

The second issue is the existence of other correlated variables that a!ect the

market values of electric utilities. Model 2 in panel A of Table 8 includes six

control variables. The"rst three are proxies for growth opportunities (&demand'

factors): POPULATION, INCOME, and CPI. The remaining three are proxies

for the cost of generating electricity (&supply' factors): FUEL COST, CAPEXP

COST, and INTEREST. These variables are obtained from the Statistical

Abstract of the United States. Three of the six control variables are signi"cant in

the expected direction. More importantly, the estimated coe$cients onE TIME

and ETIME are signi"cant.

The third issue is the pace of deregulation, which varies considerably across

states (D'Souza and Jacob, 2000). If our earlier "ndings are attributable to



25/30

Table 8

Speci"cation checks of the utility sample results under pooled "xed e!ects time-series cross-sectional

regression models

Variable Expected sign Model 1 Model 2 Model 3

Panel A: Estimates where the dependentvariable is change in adjusted price (i.e., **returns++)

Intercept ? 2.943 3.950 3.830

(0.0001) (0.0001) (0.0001)

E (#) 0.833 1.074 1.548

(0.0001) (0.0001) (0.0001)

ETIME (!) !1.444 !1.739 !1.660(0.0001) (0.0001) (0.0001)

E (#) !0.205 !0.221 !0.319

(0.8706) (0.8835) (0.8381)ETIME (#) 1.003 1.060 0.615

(0.0001) (0.0001) (0.0353)

POPULATION (#) !3.756 7.301

(0.5758) (0.3580)INCOME (#) 10.849 9.680

(0.0001) (0.0002)

CPI (!) 21.880 9.283

(0.2884) (0.6707)

FUEL COSTS (!) !0.091 !0.091

(0.0001) (0.0001)CAPEXP COSTS (!) !0.650 !0.683(0.0001) (0.0001)

INTEREST RATE (!) !1.297 !1.043

(0.3036) (0.6609)

EPACE ? !0.662

(0.0056)

EPACE TIME (!) !0.355

(0.0616)

EPACE ? !0.030(0.5445)

EPACE TIME (#) 1.114

(0.0229)

PACE ? 1.081

(0.5060)

AdjustedR 0.32 0.37 0.38

Panel B: Sensitivity analysis for the ewect of regulatory assets on bookvalue of equity

Intercept ? 7.134 8.383

(0.0001) (0.0001)

BVBRA (#) 1.001 1.170

(0.0001) (0.0001)BVBRA TIME (!) !0.1184 !0.2416

(0.0096) (0.0001)RA (#) 1.162 1.275

(0.0001) (0.0001)

RA TIME (!) !0.2231 !0.3326

(0.0001) (0.0001)

E (#) 0.190 0.291

(0.1187) (0.0220)



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Table 8 (continued)

Variable Expected sign Model 1 Model 2

ETIME (#) 1.103 0.906(0.0016) (0.0033)

POPULATION (#) 115.157

(0.0001)

INCOME (#) 6.637

(0.0066)

CPI (!) 5.662

(0.6028)

FUEL COSTS (!) !0.071

(0.0001)

CAPEXP COSTS (!) !1.692(0.0001)

INTEREST RATE (!) !4.845

(0.0297)

AdjustedR 0.78 0.83

F-tests (p-values in parentheses) of selected combinations of coe$cient estimates in Model 3:

ETIME#EPACE#EPACE TIME"0,F"62.056 (0.0001).

ETIME#EPACE#EPACE TIME"0,F"12.155 (0.0003).

Both year and "rm intercepts are included in the pooled "xed e!ects regressions. Reported

p-values (shown parenthetically) for the estimated coe$cients are one-tailed unless no sign is

predicted.

Independent variables are de"ned as follows:

BV"book value of equity per share at the close of"scal year,

E"income before extraordinary items and discontinued operations per share for the "scal year,

E"year-to-year change in income before extraordinary items and discontinued operations per

share for the "scal year,

TIME"an indicator variable equal to one for the years 1992}1996 and zero otherwise,

POPULATION"year-to-year percentage change in population of the state in which the utility'scorporate headquarters is located,

INCOME"year-to-year percentage change in per capita income of the state in which the

utility's corporate headquarters is located,

CPI"year-to-year percentage change in the all-urban consumer price index of the region (North

Central, North East, South, and West) in which the utility's corporate headquarters is located,

FUEL COSTS"year-to-year percentage change in the fuel oil producer price index,

CAPEXP COST"year-to-year percentage change in the capital expenditure producer price

index,

INTEREST RATE"year-to-year percentage change in the yield to maturity of public utility

bonds,PACE"an indicator variable equal to one if the state in which a utility's corporate headquarters

is located has enacted restructuring legislation (10 states) or issued a comprehensive regulatory order

about restructuring (5 states) as of December 2, 1997,

BVBRA"book value of equity before regulatory assets per share at the close of"scal year, and

RA"regulatory assets per share at the close of"scal year.

The dependent variable in panels A, C, and D, adjusted price, is price adjusted for net capital

transactions (i.e., the e!ects of dividends, share issuances, and share repurchases) on a per share

basis. The dependent variable in panel B is the year-to-year percentage change in the adjusted price.



27/30


28/30

post-deregulation (i.e., BVBRA TIME and RA TIME are negative and signi"-

cant at p(0.0001). Thus, the earlier support for our book value prediction is

not attributable to the inclusion of regulatory assets in book value.

5. Conclusions

Academic researchers, "nancial analysts, the SEC, and the FASB have ex-

pressed concerns about the value relevance of"nancial statement information.

This study contributes to the growing literature that investigates changes in the

value relevance of accounting information by examining a setting where these

changes can be predicted ex ante.Technological innovation in the form of improved gas turbine technology and

deregulation resulting from the passage of the Energy Policy Act of 1992 have

contributed to increased competition in the electric utility industry. We use this

period of rapid change as a laboratory for examining the role of book value and

earnings in explaining market value. Under rate-regulation where costs are

recovered and investors are assured a return, we expect that earnings should

explain relatively little variation in market value, incremental to that explained

by book value. In contrast, following deregulation, earnings should explainmore of the incremental variation in market value because earnings re#ect the

"rm's ability to capture economic rents.

We test for changes in the value relevance of book value and earnings in

response to deregulation by examining changes in coe$cient magnitudes and

incremental explanatory power for the period 1988}1996. We "nd that the value

relevance of book value (earnings) decreased (increased). Our "ndings are

consistent with investors'changing perceptions about the relative role of book

value and earnings in the valuation of electric utility "rms as a consequence ofindustry deregulation.

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