Local characteristics, contestability, and the dynamic structure of rural banking: A market study

The Quarterly Review of Economics and Finance, Vol. 35, No. 3, Fall, 1995, pages 271-287 Copyright 0 1995 Trustees of the University of Illinois All rights of reproduction in any form reserved. ISSN 00335797

Local Characteristics, Contestability, and the Dynamic Structure of Rural Banking: A Market Study MIRE DEVANEY Southeast Missouri State University

BILL WEBER Southeast Missouri State University

If a market is pe$ectly

contestable, incumbentfinns

in eoen highly concentrated markets will

produce a leoel of output consistent with a welfare maximum. Alternatively, if a market is impe$ectly contestable, the conduct of in~cumbentfirms will be influenced by the degree of actual and potential competition. The results of our simultaneous, twoequation

model of

bank behavior and actualized potential competition bad to theconclusion that rural banking markets are imperfectly contestable. This finding

suggests that rural bank policy should

continue to promote both actual and potential competition.

The 1980’s was not a good decade for rural America. With the exception of New England, economic growth in the rural US. lagged behind metropolitan America (Smith, 1992). Accompanying the poor economic performance was a slowdown in lending as well as charges by critics that rural banks were “upstreaming” deposits to urban, money market centers (Morris and Drabenstott, 1989,199l) see also Council of Northeast Economic Action (1981)) Economic Research Service (1991)) The Delta Initiatives (1990) and Espy and Emerson (1992). Unlike urban markets with a large assortment of credit alternatives, rural enterprise is much more dependent on banks as a source of financing (Pulver and Hustedde, 1990; Rogers, Shaffer and Pulver, 1990). Because the Comptroller of the Currency forecasts a twenty percent reduction in the number of rural banks over the next five years, the competitive rivalry in rural banking markets in the 1990’s may help to determine whether rural economies fall further behind the metropolitan U.S. (Economic Research Service, 1991). In this paper, the competitive scope of rural banking markets is analyzed in the context of contestability theory. Morrison and Winston (1987) show that market contestability is not an all or nothing proposition. The finding that markets are not “perfectly contestable” does not preclude the possibility that they are “imperfectly 271

272

QUARTERLY REVIEW OF ECONOMICS AND FINANCE

contestable”

and that both potential

and actual competition

influence on consumer welfare. In empirical work, actual competition deposits while potential competition profit equations,

have an important

is usually proxied by concentration

in

is inferred from market entry, the estimation of

or changes in markets share (Amel and Liang, 1992b; Whalen,

1992). A major difftculty in analyzing the profitability of rural banking markets is the aggregation Federal

bias. In states that allow unrestricted

or limited branch banking, the

Reserve Bank Call and Income Reports aggregate

income statements

the balance

sheet and

of all branches with the home office. Yet the branches of these

banks may operate in markets that vary a great deal with regard to concentration

and

local market characteristics. In the 2280 counties included in this study, there are 8267 banks with over 67% of those banks operating a branch in more than one county. Consequently, the aggregation problem renders profits a less effective measure in rural bank contestability studies. While actual profits in most rural banking markets cannot be directly observed, disaggregated deposit data are available. The Federal Reserve Summary of Deposits provides disaggregated county deposits for all FDIC insured banks and branches. Deposits can be interpreted

as an output service or as an input in the production

of

loans. If a rural banking market is perfectly contestable, potential competition insures that incumbent firms are producing a level of output (deposits) consistent with a welfare maximum. Alternatively, in “imperfectly contestable and non-contestable” markets, actual competition may serve as a deterrent to potential competitors allowing incumbent firms to restrict deposit growth below the level associated with a welfare maximum. If rural branches of urban banks are “upstreaming” deposits to money market centers, then deposit “leakages” in these markets should result in slower deposit growth. Inferring

conduct from deposit data has an advantage over

profits in that total deposits are directly observable for all 2,280 rural counties in the United States while profit data are not. In this study, we test whether rural banking markets conform to the “perfectly contestable”

hypothesis by estimating a dynamic model of rural bank structure. Our

model tests whether the change in market concentration

and deposit growth are

simultaneously determined and assumes both depend on the economic performance of the local market and the regulatory environment. Change in market concentration between 1980-1988 is interpreted as a measure of actualized “potential competition” while growth in deposits proxies as a measure of conduct. From a policy perspective, evidence of perfect contestability lends support to the assertion that the dynamic structure of banking markets did not contribute to the slow growth in rural economies during the 1980’s (Morris and Drabenstott, 1989, 1991). The next section provides a brief review of the literature on market characteristics and bank structure. In Section II we estimate a simultaneous equation model of rural bank structure. In the final section we summarize the results and present our conclusions.

RURALBANKING

I.

273

MARKET CHARACTERISTICS AND BANKSTRUCTURE

Research into the competitive characteristics

of banking markets has tended to focus

on market entry, exit, or structure as the endogenous

variable. During the 1980s

most observers agree that the primary barrier to entry into rural banking markets was regulatory. Because rural branch banks are frequently located in renovated gas stations or abandoned fast food restaurants, the bank literature suggests that the sunk costs of opening a rural branch are near zero (Whalen, 1988,1992). In regard to market exit, Amos (1992) found that states with a larger proportion of gross state product derived from oil and gas were more likely to experience bank closings in the 1980’s. In addition, bank closings were more likely to occur in states with greater volatility in their economies suggesting that the characteristics of the local economic

base are an important

that state branching

determinant

of bank exit. Amos also found

laws influence bank exit.

Lawrence and Watkins (1986) found that multi-bank holding companies were more likely to enter rural banking markets that were larger and growing. Similar to Amos, Lawrence and Watkins also found a significant relationship between state banking laws and multi-bank holding company entry. Based on 100 metropolitan markets, Boczar (1977) found that holding company entry is more likely to occur in markets characterized by fast deposit growth, high total bank deposits per bank, high expected rates of return, and low concentration. Similar to subsequent research, he found state branching laws were also significant in determining entry. Rose (1992) also found evidence that the reduced entry barriers in banking for the period 1969-1987

enhanced

concluded

that artificial barriers resulted in substantial costs to shareholders

bank performance

consistent

with agency theory and he and

depositors. Bennett and Loucks (1993) found that interstate bank holding company entry is more likely to occur in faster growing statewide branching

states.

Research interest in the structure of banking markets has been attributed to the 1963 Philadelphia National Bank case which brought banking under the jurisdiction of antitrust laws. The structure-conduct-performance paradigm typically maintains that tacit or explicit collusion is more likely to exist in markets with few competitors and should result in a statistically significant, positive relationship tration and profits. The empirical evidence linking market concentration

between concen-

to bank performance

has

spawned a vigorous debate concerning the magnitude of the relationship between concentration and profitability (Gilbert, 1984; Rhoades, 1982). Smirlock (1985) found that profits are linked to a firm’s market share rather than market concentration. Graddy and Kyle (1979) found firm performance and market concentration to be simultaneously determined so that failure to consider simultaneity has biased efforts to link concentration with profitability. Liang (1989) found that bank managers may tradeoff monopoly profits for reduced risk so that when simultaneity is controlled, a positive relationship between market concentration and profitability

274

QUARTERLY

REL’IEW OF ECONOMICS

exists. Amel and Liang (1992b) tration

and profitability

AND FINANCE

also found a positive relationship

for urban

and rural banking

markets.

between concenWhalen

(1988)

however, models bank profitability and market rivalry simultaneously and found no link between concentration

and profitability for rural banks in Ohio. For a larger

sample of rural banking markets in Ohio, West Virginia, (1992)

found concentration

and Kentucky, Whalen

increases rivalry and decreases profitability. Clark and

Speaker (1992) found concentration

has a stronger positive effect on firm profitabil-

ity in states where bank branching laws restrict entry into local banking markets. The contestable markets literature has shown that if entry and exit are costless, the economic outcome in even highly concentrated

markets can approximate perfect

competition

(Baumol, Willig and Panzer, 1982). Consequently, if a market is perfectly

contestable,

there is no expected

relationship

between concentration

Monopoly power and profits deriving from concen~ation/collusioll time if the threat of entry by potential competitors

and profits.

can persist over

is more costly than the profits to

be reaped once the firm has entered the market.’ The argument

that the threat of potential competition

can affect the behavior

of incumbent firms is not new but can be traced to the work of Bain (Morrison and Winston, 1987). However, until recently, banks confronted an assortment of regulatory constraints

that limited services, geographic

quently, highly localized bankingmarke~ of economic

entry, and even pricing. Conse-

failed to conform to the contestable model

theory.

Amel and Liang (1992b)

estimate a two-equation model of entry and perform-

ance for rural and metropolitan

banking markets. They find that although concen-

tration has a negative effect on entry in urban markets, it was significant only for two periods, and was insignificant potential

competition

contestability significant

for rural markets. They also tested for the effects of

on entry and profitability.

perfect

for urban banking markets. For rural banking markets, entry had a

negative effect on profits indicating

contestable.

Their findings indicate

Whalen (1988,199Z)

but examines

that the markets were not perfectly

concludes rural banking markets are contestable,

only a small sample of rural banks in the Fourth Federal Reserve

District. While actual competition because of enhanced

(as measured

potential competition,

by concentration)

need not change

over time an un-actualized “threat” by

potential competitors should have diminishing influence on the behavior of incumbent firms. Numerous examples in game theory demonstrate that in order for a potential

“threat” to be credible,

actualized to extract m~imum we interpret

such as a labor strike, it must occasionally

be

advantage (Baumol, 1977; Schelling, 1960). Similarly,

the change in concentration

in rural banking markets between 1980-

1988 as the “actualized threat of potential competitors.” absolute value of the percentage

Whalen

(199‘2) used the

change in the market share of the three largest

institutions as a measure of market rivalry (i.e., potential competition).

RURALBANKING

In our two equation

275

model, change in market structure rather than entry is

selected as the endogenousvariable in the first equation. Since the 1963 Philadelphia National Bank case, public policy has tended to define banking’s competitive environment in the context of market concentration.

In urban markets, the proliferation

of non-bank competitors renders the concentration measure suspect. However, rural banks have very few non-bank competitors so that concentration and change in concentration

should be reliable

measures of actual and potential

respectively. Most entry models examine

competition,

only new entry and do not consider

an

increase in the number of branches in an existing market as “entry” although it may significantly

alter market dynamics, especially in small rural markets

Liang, 1992b). The change in market concentration and changes

in market share and is believed

1980-1988

(Amel and

captures entry, exit,

to be the best single measure

of

actualized “potential competition.” Our second equation models deposit growth. While deposits can be viewed as either an input in the production of loans or as an output service, nearly all banking market research measures banking market structure as concentration in deposits. The economic effect of the collusive structure defines the welfare loss associated with deviations from the perfectly competitive market (Needham, 1977). In the static model, the restricted output is a manifestation of the monopolist’s profit maximizing “conduct”. It follows that in a dynamic model of bank structure, the welfare loss attributed to collusive structure will depend on the amount by which the change in deposits deviates from the change associated with a competitive equilibrium. In collusive markets, banks exhibit profit maximizing “conduct” by restricting the growth in deposits below the level associated with a competitive equilibrium.* This interpretation of deposit growth would only apply in a market for deposits similar to the post Regulation Q environment of the 1980’s. The estimated conduct-performance. the “performance”

model is a test of market contestability

rather than structure-

Consequently, the unit of comparison is the rural market and variables

influencing

the bank environment.

These

are the

economic performance of the local economy rather than an aggregated measure of bank profitability. If rural economic growth is a policy objective and the dynamic structure of rural banking markets is related to local economic

performance,

then

policy should facilitate a structure conducive to growth.

II.

A MODEL OF RURAL BANK STRUCTURE

Clark (1986) suggests that much of the empirical work on bank structure suffers from a single equation bias. Accordingly, we estimate a simultaneous equation model with two structural equations. The endogenous variable in the first equation is the 1980-1988 change in the Herfindahl-Hirschman Index (HHI) for deposit liabilities (dC). The HHI is calculated by squaring and summing each individual bank’s share

276

QUARTERLY REX’IEW OF ECONOMICS AND FINANCE

of county deposits. The endogenous

variable in the second equation is the growth

rate in deposits over the same period (dDEP) . Our model of change in concentration

and deposit growth takes the following

form:

where:

dC = f(dDEP, zt)

(I)

dDEP = g(dC, z2)

(2)

dC = the change in concentration, dDEP = is deposit growth, zt = a vector of exogenous variables that influence changes in concentration, z2 = a vector of exogenous variables that influence deposit growth.

If banking markets are perfectly contestable and in long-run equilibriltm, firms are earning a normal rate of return, and there is no incentive for firms to enter or exit the market. The rate of deposit growth consistent with long-run competitive equilibrium is DEP* in Figure 1 and corresponds to the vertical line labeled “Perfectly Contestable.” If markets are perfectly contestable, deposit growth (dDEP) will be independent of actualized potential competition (dC) . Incumbent firms are earning a normal profit and providing a level of service consistent with a welfare maximum. Even in highly concentrated markets, there is no attempt by incumbent firms to collude since any collusive advantage would be quickly offset by potential competitors. In this case, only exogenous variables, ~2, influence deposit growth with changes in z2 causing shifts in the curve. Alternatively, “non-contestable” markets are represented by the curve showing an inverse relationship between change in concentration and deposit growth. For an increase in concentration, the market for deposits becomes more monopolistic and collusive firms restrict deposit growth relative to more competitive markets. As concentration growm3

decreases, there is less collusion and an associated increase in deposit

Finally, if markets are imperfectly petitors influence

contestable,

the conduct of incumbent

both actual and potential

com-

firms (Morrison and Winston, 1987).

The slope of the curve labeled “imperfectly contestable” is expected to be greater than for non-contestable markets. In the short run, market rivalry may even result in a positive relationship between the change in concentration and deposit growth as some incumbent firms attempt to increase market share by increasing dDEP above the level supported by exogenous variables, ~2. A positive relationship between deposit growth and the change in concentration may also occur if increased concentration allows firms to realize greater economies of scale. To test whether rural banking markets are perfectly contestable, we estimate Equations 1 and 2 simultaneously and check for the endogeneity of the system. If deposit growth is determined only by ~2, and not influenced by dC, then we conclude

RURALBANIUNG Change dC

277

In HHI Imperfectly

Perfectly

Contestable

Contestable

Non-Contestable

Deposlt Growth dDEP

DEP+

Figure1. Bank ContestabilityHypotheses

that rural banking markets are perfectly contestable. Alternatively, if the change in concentration and deposit growth are simultaneously determined, we conclude that rural banking markets are less than perfectly contestable.

The literature suggests that besides deposit growth, the change in concentration in credit markets depends on the regulatory environment, the local economic base, and other structural characteristics of the market (Amel and Liang, 1992b; Amos, 1992; Boczar, 1977; Lawrence and Klugman, 1992; Whalen, 1988,1992). Therefore, the first structural equation is: dC = a~ + aldDEP + a$JNIT

+ a&IMITED

+ a,jdTRADE + a&SERV t where:

+ a&RBAN

+ a5dMANU

a&ELF t %BHC t a&IHI80

dC = the change in the Herfindahl-Hirschman

t allRELAX

(3)

Index between1980-1988

dDEP = the change in the log of total county deposits over the same period, and UNIT, LIMITED, URBAN, dMANU, dTRADE, RELAX correspond to z1 in Equation 1.

dSERV, SELF, BHC, HH180, and

The influence of state banking laws is measured by a dummy regulatory variable for UNIT, LIMITED, and STATEWIDE. These variables define whether the county is in a state with unit, limited or statewide branching laws as of 1980. To avoid the

278

QUARTERLY REVIEW OF ECONOMICS AND FINANCE

exact linear

dependence

among

the three regulatory

variables,

STATEWIDE

is

dropped in the estimation process. If the sunk costs of branching are near zero, ceteris @ibus,

STATEWIDE markets should be the most contestable,

followed by LIMITED

and UNIT markets. We also include the dummy variable RELAX which takes a value of one if the county is in a state that relaxed bank branching laws during the period 1980-1988.

Amel and Liang (1992a) discuss the liberalization

of state branching laws

over the period 1976-1988. Change in bank concentration the market. proportion

is also influenced

base is measured

by the local economic

by the change

base of

in the log of the

of the civilian work force employed in each of three categories-manu-

facturing (dSERV)

The economic

(dMANU) , wholesale/retail

from 1980-1988.

trade

(dTRADE) , and service

industries

The variable SELF, which measures the proportion

of

self-employed in the civilian labor force in 1980, is also included as an economic base variable. Finally, the relative importance related to the percentage

of agriculture

in the county is inversely

of the rural county population

residing in a town or an

urban area (URBAN) and is included as an economic base variable. If actual competition “perfectly contestable”

influences

potential competitors,

and actual competition

variable. To determine whether the level of actual competition in concentration

the market is less than

continues to be an important policy influences the change

(dC) , we include the variable BHC and continuous variable HH180.

The variable BHC measures the change in the number of states offering a reciprocal interstate bank holding company agreement with the state the county is located in. The Douglas Amendment

to the 1956 Bank Holding Company Act prohibited bank

holding companies from acquiring banks outside their home state unless a reciprocal agreement

between the two states allowed such acquisitions.

Up until 1982, Maine

was the only state that allowed its banks to be acquired by out of state bank holding companies, Tschinkel

but no other state offered a reciprocal and Whitehead,

competition

1989).

Some research

agreement

may serve as a deterrent to potential competition

the level of concentration

with Maine (Ring,

suggests that the level of actual so the variable HH180,

in 1980 is included. In addition, bank holding companies

may be able to circumvent

state laws allowing only unit or limited branching,

by

chartering a number of banks and operating them as if they were branches of a single bank. If the coefficients

on (BHC) and (HH180) are significant, then actual compe-

tition in rural banking markets influences to the contention

potential competition

and lends support

that rural banking markets are imperfectly contestable.

The growth rate of county deposits from 1980-1988 is our measure of conduct and is the endogenous variable in our second structural equation. The growth in local bank deposits depends on the change in concentration dC and exogenous variables z2 in Equation 2. Exogenous variables include: the regulatory environment (UNIT, LIMITED,

STATEWIDE,

BHC, and RELAX),

the performance

of the local

economy as proxied by the change in county population from 1980 to 1988 (dPOP),

RURALBAhWlNG the log of the change

in county personal

income

per capita

(dINC),

279

and the

percentage of the rural county population residing in town or urban area (URBAN). Therefore, the second structural equation in our model is: dDEP = b0 t b1dC t b2UNIT + b3LIMITED t b4URBAN t bsBHC t b&ELAX

t b-/dPOP t bsdINC

(4)

where STATEWIDE has again been dropped to avoid the exact linear dependence among UNIT, LIMITED, and STATEWIDE. The significance of the structural parameters and a test for simultaneity in dC and dDEP will be used to determine whether this is an adequate specification of dynamic structure in rural credit markets. Data The change in concentration, dC, is computed from the 1980 and 1988 Summary of Deposits data tape available from the Federal Reserve. The tape includes county number, deposits, and holding company information for all FDIC insured banks and branches in the United States. For purposes of calculating the HHI, multiple branches of the same bank in a given county are treated as a single institution as are multiple banks in a county held by a single bank holding company. Information on whether the county was classified as rural was taken from An Update; TheDiverseSocial and Economic Structure of Nonmetropolitan America. Amos (1992) provides information for UNIT, LIMITED, and STATEWIDE regulatory variables. Amel and Liang (1992a) provide information for those states that relaxed state branching restrictions in the 1980s. Information on reciprocal bank holding company regulations are provided by Ring et al. (1989). All other data items were taken from the 1983 County and City Data Book and the 1990 CD-ROM Counties compiled by the Bureau of the Census. The mainframe SAS subroutine PROC !SYSNLIN was used to estimate the model’s structural parameters. Table 1 provides descriptive statistics for the variables in the two structural equations. For the period 1980-1988, changes in rural bank concentration as measured by the mean dC declined while rural bank deposits grew at an average annual rate of 6.8%. Of the 2,280 counties in our sample, 1,113 counties experienced an increase in concentration, 997 experienced a decline in concentration, and 90 counties experienced

no change in concentration

for the test period.

Of the 2,280 rural counties in the study, 27% were located in states that allowed unit banking only, 51% were in states that allowed limited branching, and the remaining 22% were located in states allowing statewide branching. From 1980-1988 six states relaxed branch banking restrictions (RELAX) with those six states consisting of 6.4% of the rural counties.4 Reciprocal banking regulations passed in the 1980s meant that banks in the average county could experience potential competition from bank holding companies in approximately 18 other states (BHC). The distribution

280

QUARTERLY REVIEW OF ECONOMICS AND FINANCE

Table 1. DESCRIPTIVE

STATISTICS

Variable

OBS = 2280 Mean

Standard Deviation

HHI - 1980

0.45980

0.23740

HHI - 1988

0.45390

0.22840

dC = HH188 - HHI80

0.09890

-0.00590

dep1980(in

1000s)

149733.96

170826.99

depl988(in

1000s)

264037.79

315277.53

dDEP=Iog(dep88)

- log(dep80)

0.60871

0.44615

IN030

7804.73

1625.68

INC88

12460.89

2604.29

dINC = log(INC88) - log(INC80)

0.46846

0.12788

UNIT

0.26798

0.44300

LIMITED

0.51095

0.50000

STATEWIDE

0.22105

0.41504

URBAN

0.27530

0.23732

POP80

23071.0

21223.7

POP88

24073.0

22938.2

dPOP = Iog(POP88) - log(POP80)

0.02001

0.10194

MANU80

0.12799

0.12111

MANU88

0.11944

0.11388

dMANU = Iog(MANU88)-

log(MANU80)

TRADE80

-0.12321

1.85221

0.16947

0.03472

0.13215

0.05103

-6.32293

0.42505

SERV80

0.07608

0.05362

SERV88

0.09855

0.06277

dSERV = log(SERV88) - log(SERV80)

0.40080

0.84932

SELF80

0.12965

TRADE88 dTRADE = log(TRADE88)

- log(TRADE80)

BHC RELAX Seurws:

0.06447 of Deposits.

Aw lIpnIt; Thr Diomr Research Service.

S~rurrurr oJIVovonmrImpolilnnAmtmn,

For information

on regulatory

0.24565

1983 County and City Doln Book and 1990 CD-ROM.

19RO and 1988 Federal Reserve Summary census. Soonl md Emmnir

0.07529 16.74

18.4

United

\a]-iables see Amos (19932). Amel and Liang (199%).

States Department

Coundes,

Bureau of Ihe

of Agriculture.

Economic

and Ring et al. (1989).

of the economic base variables (MANU, TRADE, SERV, SELF, and URBAN) along with the population and income variables are also provided in Table 1. As mentioned previously, the relative economic gains of the rural U.S. in the 1970’s were relinquished in the 1980’s. With the exception of New England, employment and income growth for rural counties in the 1980’s lagged behind metropolitan America (Smith, 1992). Manufacturing employment as a proportion of the civilian labor force fell as did employment in wholesale and retail trade. Over the same period, employment in the service sector increased. Self-employment in 1980 (SELF) accounted for 13% of all employed workers. The average county population grew from 23,076 in 1980 to an estimated 24,073 by 1988. Over the same period, per capita

RURALBANKING

personal income grew from $7,804 to $12,460 on average. In 1980,27%

281

of the county

population lived in an urban area in the rural county. Results

In estimating

the system of equations

Hausman’s

(1978)

determine

whether

given by Equations

m test for model specificadon.5 the two equations

3 and 4 we employ

The purpose of the test is to

are simultaneously

determined.

We first

estimate each equation using the ordinary least squares (OLS) regression algorithm in SAS. The system of equations is then re-estimated using three-stage-least

squares.

Hausman’s m statistic is calculated from the two sets ofparameter estimates. The null hypothesis is that the parameters of the model specified in Equations 3 and 4 and estimated by OLS are consistent and efficient, while the alternative hypothesis is that the parameters

are unbiased and efficient estimators only when estimated by three-

stage-least squares (SSLS). Hausman has shown that the m statistic is distributed as X*K, where K is the number of parameters estimated. There

are twenty-one parameters

statistic of 52.224.

in Equations

3 and 4 with an estimated m

The critical chi-square with 5% significance

freedom is 32.671. Therefore,

and 21 degrees of

we reject the null hypothesis and conclude

that the

parameters are unbiased and efficient only when estimated by 3SLS and also conclude that the change in concentration and deposit growth are simultaneously determined. The parameter estimates based on 3SLS appear in Table 2. Standard errors appear below the parameter estimates and &values under the standard errors. Seventeen of the twenty-one parameters estimated are significant at the 95% confidence level. The growth of deposits, dDEP, is significant and negative in Equation 3 while the change in concentration,

dC, is significant and positive in Equation 4.

In our model, the result showing that changes in bank concentration and deposit growth are endogenous is consistent with banking markets being less than “perfectly contestable.”

The negative coefficient

on dDEP in Equation 3 supports the assertion

that markets experiencing rapid deposit growth will attract entry and market concentration declines. However, in Equation 4, the change in concentration has a positive effect on county deposit growth. A positive relationship between change in concentration and deposit growth could occur in the short-run if banks increase deposit growth to gain market share and discourage entry. The positive coefficient can also be supported if rural banks have increasing returns to scale or other size/cost economies.

Although

beyond the scope of this paper, recent

research

on scale

economies in banking suggests that when risk is adequately accounted for, constant returns to scale begin to set in at $500 million in assets (Berger, Hunter and Timme, 1993). Because 40% of rural banks have total assets of less than $25 million, the potential for greater scale economies through increased concentration seems probable (Economic Research Service, 1991). For 1988, the total deposit/asset ratio of

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QUARTERLY REVIEW OF ECONOMICS AND FINANCE

domestic commercial

banks was more than 80%.6 The average total county deposits

of $264 million listed in Table 1 is well within the range of increasing returns to scale. Deposit growth and changes in concentration can vary from market to market depending on the values of the exogenous variables z1 and z2 in Equations

1 and 2.

Substituting the values of the exogenous variables for each county into Equations 3 and 4, the change in concentration

and rate of deposit growth can be determined.

For the 2,280 counties in the sample, the mean change in concentration, to -.015

dC, is equal

and the mean change in deposits, dDEP, is equal to .604 for the period

1980-1988. The estimated coefficients

given in Table 2 for Equations 3 and 4 give partial

equilibrium adjustments of dC and dDEP due to changes in the exogenous variables. The variables URBAN, dMANU, and dTRADE, all had a significant negative effect on dC. The variables dSERV and SELF each had a positive effect on the growth rate of concentration

although dSERV was insignificant

at the 95% confidence

level.

Of particular interest was the relationship among the UNIT-LIMITED-STATEWIDE markets, and the change in concentration.

In regard to 1980 state branching

we assume that markets where statewide branching most contestable contestable.

(STATEWIDE)

laws,

is allowed are the

while those markets allowing only unit banks (UNIT) are the least

With STATEWIDE

serving as the control variable (the intercept

term

captures its effect), states which allowed unit or limited branching had a greater rise in bank concentration

than those that allowed statewide branching.

on UNIT was insignificant

The coefficient

indicating that UNIT branch banking states had the same

regulatory effect on concentration as STATEWIDE branching states. States which relaxed branch banking restrictions (RELAX) had a positive but insignificant

effect on concentration,

while states allowing reciprocal interstate bank

holding companies had no effect on concentration.

The level of market concentra-

tion at the beginning of the test period (HH180) had a significant negative influence on the change in market concentration. potential competition,” influences

potential

If dC is a reliable measure of “actualized

this result supports the contention

competition

that actual competition

and that rural banking

markets are less than

perfectly contestable. Equation 4 describes the growth rate of deposits, dDEP The parameters variables in the dDEP equation

were statistically significant.

on all

Both LIMITED

and

UNIT counties had significantly higher deposit growth rates than STATEWIDE branching states. County population growth and income growth were significant and positively related to deposit growth. Somewhat surprisingly, states that relaxed branch banking laws experienced

lower deposit growth. One explanation

for this result,

although beyond the scope of this paper, is that the regulatory process is endogenous to the level of deposit growth and changes in market structure. Slower deposit growth might also be the result of a lag between the time the policy is implemented time the policy begins to affect the banking market.

and the

RURALRANKING

Table 2.

PARAMETER ESTIMATES

Variable

Parameter

constant

dC

Parameter

0.08001** (0.01269) 6.31

&value dC

bl

t-value dDEP

al

t-value UNIT

a2

t-value LIMITED

a3

&value URBAN

a4

&value dMANU

a5

t-value dTRADE

a6

f-value dSERV

a7

t-value dSELF

a8

&value BHC

a9

t-value HH180

al0

&value RELAX

all

&value dPOP

-0.06773** (0.01371) -4.94 0.00432 (0.00608) 0.71 0.01487** (.00515) 2.89 -0.02174** (0.03208) -3.02 -0.00310”* (0.00106) -2.91 -0.02523** (0.00529) -4.77 0.00381 (0.00235) 1.62 0.09158** (0.03163) 2.89 0.00000 (0.00013) 0.05 -0.15089** (0.00937) -16.09 0.00245 (0.00835) 0.29

*indicates

b

b4

hi

b6

ba

t-value

**indicates

b2

b

t-value dINC

NOW

bo

statistical significance

at the 95% confidence

level.

rtatisdcal

at the 99% conlidencr

level.

signiticance

dDEP 0.25689** (.03158) 8.13 0.09477** (.01813) 5.23

0.06429** (0.01875) 3.43 0.08310** (0.01666) 4.99 -0.13120** (0.02708) A.84

0.00223** (0.00041) 5.47

-0.07910** (0.02594) -3.05 1.16281** (0.006828) 17.03 0.49347** (0.05000) 9.87

283

284

QUmTERLY

REVIEW OF ECONOMICS AND FINANCE Table3.

Comparative Static Results

Variable

dDEP/dx

dC/dx

UNIT

-0.00003

0.06470

0.00924

0.08451

URBAN

-0.02319

-0.13424

dMANU

-0.00310

-0.00029

dTRADE

-0.02523

-0.00239

LIMITED

dSERV

0.00381

0.00036

SELF80

0.09158

0.00868

BHC

-0.00015

0.00223

NH180

-0.15089

-0.01430

dPOP

-0.07876

1.16281

dINC

-0.03342

0.49343

0.00781

-0.07887

dRELAX

To measure the magnitude of the relationship between the endogenousvariables and each of the exogenous variables in a general equilibrium lated comparative

framework, we calcu-

static results which appear in Table 3. Bank concentration

and

deposit growth both decrease for those rural counties which have a larger percentage of their population significant

residing in an urban area (URBAN).

agricultural

concentrated

Rural counties without a

base are more likely to have more of their population

in an urban area along with greater access to non-bank competitors.

The 1980-88

trend in employment

showed the share ofjobs

in manufacturing

and wholesale and retail trade falling, with the share of jobs in the service sector increasing.

For each of these changes the model predicts an increase in concentra-

tion along with an increase in deposit growth. The variable SELF was presumed to act as a proxy for small business. The model predicts that in counties where a greater proportion

of the civilian labor force was selfemployed

in 1980, concentration

and

deposit growth increase. Counties located in states which pass reciprocal interstate bank holding company agreements

are predicted

to have less concentration

Higher levels of initial concentration concentration

but also contribute

(HH180)

and greater deposit growth.

were predicted

to reduce future

to slower deposit growth. Finally, increases

in

population and county per capita income were predicted to decrease concentration and increase deposit growth.

III.

SUMMARY AND CONCLUSIONS

Our results indicate

that the change

deposits are simultaneously

in concentration

determined.

and the growth of bank

This result implies that rural banking

RURAL RANICING markets are not perfectly contestable.

285

Growth in deposits had a negative influence

on the change in market concentration

in Equation

3. This lends support to the

notion that banks will tend to enter markets where deposits are growing. On the other hand, the change in market concentration

was positively related to deposit growth

in Equation 4. We attribute this latter result to the existence of increasing returns to scale in small rural banking markets. Coefficients

on the exogenous

variables support the assertion that changes in

rural banking market concentration depended on changes in the economic base of the local market. Comparative statics on economic performance measures, population and income growth, indicate that they are positively related to deposit growth and inversely related to change in concentration. concentration

We also found that the change in

was inversely related to both the level of concentration

ning of the test period and the passage of a reciprocal

interstate

at the beginbank holding

company agreement. Again, this suggests that rural banking markets are not perfectly contestable.

Our results also suggest that reciprocal interstate bank holding company

agreements helped spur deposit growth and reduced concentration. This lends support to recently passed interstate banking legislation as a means of promoting greater competition in banking markets. The 1980s was a decade of rapid structural change in banking. Numerous bank failures occurred

while states began relaxing branching

restrictions

and allowing

limited interstate banking through bank holding companies. Future research should continue to examine the contestability of banking markets as they respond to these structural and regulatory changes. While our research suggest that rural banking markets as a whole are not perfectly contestable, whether

individual

further research should examine

rural bank markets are perfectly

markets characterized

contestable.

Unlike

urban

by a wide range of credit alternatives from investment banking

firms to pawnshops, rural economies are much more dependent on banks as a source of financing.

The Comptroller

of the Currency forecasts that over the next five years,

the number of rural banks will contract by more than 20%. (e.g., Economic Research Service, 1991) If rural banking markets are not perfectly contestable

as suggested by

our results, then public policy should promote both “actual” as well as “potential” competition. Acknowledgment:

We would like to thank two anonymous

referees

for helpful

comments on previous versions of this paper. We maintain all responsibility for any remaining errors.

NOTES *Direct all correspondence ment of Economics,

to: Bill Weber, Southeast Missouri State University, Depart-

One University Plaza, Cape Girardeau, MO 63701.

QUARTERLY REVIEW OF ECONOMICS AND FINANCE

286

1. Another view asserts that the relationship is not between concentration

and perform-

ance, but market share and profitability (Brozen, 1982; Demsetz, 1973; Smirlock, 1985). This view holds that market concentration

is the result of firms with superior efficiency obtaining

a larger market share. Market concentration

and profits may be correlated,

causal relationship from concentration to profits. 2. If banks in imperfectly contestable or noncontestable than perfectly contestable contestable

but there is no

markets grow at a faster rate

markets, eventually that market’s output level catches up with the

market, contradicting

the result that firms in imperfectly competitive markets

produce less output than competitive firms. 3. In noncontestable markets above normal profits or slower deposit growth are possible if there is no threat of potential competition. If changes in concentration are unrelated to deposit growth, and if changes in potential competition do not cause changes in concentration, then the market would seem to be noncontestable. 4.

The states that relaxed branching

laws in the 1980s were Connecticut,

Indiana,

Oregon, Pennsylvania, Utah, and Washington (Amel and Liang, 1992a). 5.

Hausman’s m statistic is given as: m = N(B2 - Bt)’ [ yB2) - v(Bl)]-l(B:,

and B2 are the parameter estimates under OIS and JSIS, and V(Bt) and V(@) estimation method. 6.

correspond

- Bl), where Bl

N is the number of observations,

to the inverse of the information

matrix under each

Source: Federal Reserve Bulletin, June 1989, p. A82.

REFERENCES Amel, Dean F. and J. Nellie Liang. 1992a. “The Relationship Between Entry into Banking Markets and Changes in Legal Restrictions on Entry.” The Antitrust Bulletin, xx&i: 631-649. 1992b. “A Dynamic Model of Entry and Performance In the U.S. Banking Industry.” -. Pp. l-32 in Finance and Economic Discussion Series, Division of Research and Statistics, Division of Monetary Affairs, Federal Reserve Board, Washington DC. Amos, Orley M. 1992. “The Regional Distribution of Bank Closings in the United States From 1972 to 1988.” Soutkern Economic Journal, 58: 805-815. Baumol, William. 1977. P. 451 in Economic Theory and Operations Analysis, 4th ed. Englewood Cliffs, NJ: Prentice Hall. Baumol, William, Robert D. Willig and John C. Panzer. 1982. ContestableMarkets and the Theory oflndustrial Structure. New York: Harcourt Brace and Jovanovich. Bennett, Randall W. and Christine Loucks. 1993. “Banking Markets and Interstate Entry in the Southeastern United States.” Quarterly Journal ofBusiness and Economics, 32: 3-13. Berger, Allen N., William C. Hunter and Stephen G. Timme. 1993. “The Efficiency ofFinancial Institutions: A Review and Preview of Research Past, Present, and Future.” Journal of Banking and Finance, 17: 221-249. Boczar, Gregory E. 1977. “Market Characteristics and Multibank Holding Company Acquisitions.” Journal ofFinance, 32: 131-l 46. Brozen, Yale. 1982. Concentration, Mergers and Public Policy. New York: Macmillan. Clark, Jeffrey A. 1986. “Single Equation, Multiple Regression Methodology: Is it An Appropriate Methodology for the Estimation of the Structure-Performance Relationship In Banking?” Journal of Monetary Economics, 18: 295-312. Clark, Jeffrey A. and Paul J. Speaker. 1992. “The Impact of Entry Conditions on the Concentration-Profitability Relationship in Banking.” Quarterly Review ofEconomics and Finance, 32: 45-64.

RURALBANKING

287

Council of Northeast Economic Action. 1981. An EmpiricalAnalysis of UnmetDemand In Domestic CapitalMarkets In Five U.S. Regions. Boston, MA: Research Division, Council of Northeast Economic Action. The Delta Initiatives. 1990. Report Issued By The Lower Mississippi Delta Development Commission, Memphis, TN. Demsetz, Harold. 1973. “Industry Structure, Market Rivalry, and Public Policy.“Journal of Law and Economics, 16: l-9. Economic Research Service. 1991. United States Department OfAgriculture, Rural Conditions and Trends, Special Report On Financial Institutions, (Supplement 1). Espy, Mike and Bill Emerson. 1992. A Bill To Promote Economic Development In the Lower Mississippi Delta Region by Establishing the LMDR Development Financing Corporation, 102d Congress, 2D Session H.R 6188, October 6. Gilbert, R. Alton. 1984. “Bank Market Structure and Competition: A Survey.” Journal ofMonq! Credit, and Banking, 16: 617-645. Graddy, Duane B. and Reuben Kyle III. 1979. “The Simultaneity of Bank Decision Making, Market Structure, and Performance.” Journal ofFinance, 314:l-18. Hausman, J.A. 1978. “Specification Tests in Econometrics.” Econometrica, 46: 1251-1271. King, B. Frank, Sheila L. Tschinkel and David D. Whitehead. 1989. “Interstate Banking Developments in the 198Os,” Federal Reserve Bank of Atlanta Economic Review, (May/June): 32-51. Lawrence, David B. and Thomas G. Watkins. 1986. “Rural Banking Markets and Holding Company Entry.” Journal of Economics and Business, 38: 123-l 30. Lawrence, David B. and Marie R. Klugman. 1992. ‘Interstate Banking In Rural Markets: The Evidence From the Corn Belt.” Journal of Bunking andFinance, 15: 1081-1091. Liang, Nellie. 1989. “Bank Profits, Risk, and Local Market Concentration.” JournalofEconomics and Business, 41: 297-305. Morris, Charles and Mark Drabenstott. 1989. “Financing Rural Business: What Role For Public Policy?” Federal Reserve Bank of Kansas City Economic Review, (September-October): 30-45. -. 1991. “Rethinking the Rural Credit Gap.” Rural Development Perspectives, (OctoberJanuary) : 20-25. Morrison, Steven A. and Clifford Winston. 1987. “Empirical Implications and Tests of the Contestability Hypothesis.” Journal of Law and Economics, 30. 53-66. Needham, Douglas. 1978. The Economics of Industrial Structure, Conduct and Perfmance. New York: St. Martin’s Press. Pulver, Glen and Ronald J. Hustedde. 1990. “Regional Variables That Influence the Allocation of Venture Capital: The Role of Banks.” The Review of Regional Studies, 20: l-l 1. Rhoades, Stephen A. 1982. Structure-Performance Studies In Banking: An Updated Summary and Evaluation. Staff Economic Studies 119, Board of Governors of the Federal Reserve System, Washington, DC. Rogers, Glenn, Ron Shaffer and Glen Pulver. 1990. “The Adequacy of Capital Markets For Rural Nonfarm Enterprise.” Tke Review of Regional Studies, 20: 23-32. Rose, Peter S. 1992. “Agency Theory and Entry Barriers In Banking.” Financial Reviem, 27: 323-353. Schelling, Thomas C. 1960. The Strategy of Conflict. Cambridge, MA: Harvard University Press. Smirlock, Michael. 1985. “Evidence On the (Non)Relationship Between Concentration and Profitability In Banking.” Journal of Monq, Credit, and Banking, 17: 69-83. Smith, Tim R. 1992. Determinants of Rural Growth: Winners and Losers in the 1980’s. Research working paper, Research Division, The Federal Reserve Bank of Kansas City. Whalen, Gary. 1988. “Actual Competition, Potential Competition, and Bank Profitability in Rural Markets.” Federal Reserve Bank of Cleveland Economic Review, 24: l-10. -. 1992. “The Determinants and Performance Effects of Rivalry In Local Banking Markets.” Quarterly Journal of Business and Economics, 31: 38-51.