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WHEN DOES FINANCIAL LIBERALIZATION
MAKE BANKS RISKY? AN EMPIRICAL EXAMINATION
OF ARGENTINA, CANADA AND MEXICO
William C. Gruben
Jahyeong Koo
Robert R. Moore
Research Department
Working Paper 9905
Center for Latin American Economics
Working Paper 0399
August 1999

FEDERAL RESERVE BANK OF DALLAS

WHEN DOES FINANCIAL LIBERALIZATION MAKE BANKS RISKY?
AN EMPIRICAL EXAMINATION OF ARGENTINA, CANADA AND MEXICO

William C. Gruben
Jahyeong Koo
Robert R. Moore

William C. Gruben is assistant vice president in the Research Department of the Federal Reserve
Bank of Dallas. Jahyeong Koo is an economist in the Research Department of the Federal
Reserve Bank of Dallas. Robert R. Moore is senior economist in the Financial Industry Studies of
the Federal Reserve Bank of Dallas.

Abstract
In the literature on systemic banking crises, two common themes are: (1) lack of market
discipline encourages risky lending and (2) financial liberalization or privatization lead to risky
lending. However, there is evidence to suggest that neither financial liberalization nor weak
market discipline always precedes risky lending. We test for depositor discipline and, separately
for post-liberalization or post-privatization risky lending in Argentina, Canada, and Mexico. In
the countries without market discipline, lending risk increases significantly in the wake of
liberalization. Where depositors discipline banks, banks neither behave riskily nor does their risk
increase in the wake of privatization.

William C. Gruben
Jahyeong Koo
Robert R. Moore

Acknowledgement

The authors thank Pierre-Richard Agénor, Jeffery Gunther, Ricardo Hausmann, George
Kaufman, Kenneth Robinson, Eric Rosengren, Maria Soledad Martinez, Sherill Shaffer, John
Welch, and the participants at sessions of the 1999 Federal Reserve Bank of Dallas and World
Bank conference on bank privatization, of the 1999 American Economics Association meetings,
of the 1998 Jornadas of the Central Bank of Uruguay, and of the 1998 meetings of the Network
of Central Bank Researchers of the Americas. The opinions expressed in this paper do not reflect
the opinions of the Federal Reserve Bank of Dallas or of the Federal Reserve System.

In the literature on systemic banking crises (viz. Calomiris, 1990: de la Cuadra and
Valdés, 1992; Kaminksy and Reinhart, 1996; McKinnon and Pill, 1996), two of the most
common themes are: (1) Lack of market (depositor) discipline on the banking system - which is
typically blamed on government guarantees including deposit insurance - encourages risky
lending that ultimately disrupts the financial system. (2) Financial liberalization or privatization
often results in regulatory breakdowns and market share struggles that lead to risky lending that
ultimately disrupts the financial system.
Nevertheless, while risky lending and financial disruptions occur from time to time in
many countries, these events are neither continuous nor eternal components of most countries’
financial landscapes. Blowups happen, but most of the time most bankers go about their
business uneventfully. Similarly, not every financial liberalization in every country precedes a
bubble and then a bust. Sometimes a regulatory transition is just a regulatory transition.
In sum, on the one hand there do seem to be connections of market indiscipline and of
financial liberalization to what McKinnon and Pill (1996) call “overborrowing” or what - as bank
regulators - we view as risky overlending. On the other hand, the sporadic appearances of these
connections ought to suggest that they are conditional on something else.
This paper relies on what could be called circumstantial econometrics to suggest one type
of conditionality. The econometrics are circumstantial in the sense that - with a sample of only
three countries - we cannot unequivocally prove the conditionality we postulate. Nevertheless, in
our model, risky bank behavior turns out to materialize just where and when we would expect it
if it were indeed persistently conditional on the absence of market discipline.
We model market discipline during crisis periods in the Argentine, Canadian, and
Mexican banking systems by relating depositor responses at such times to bank asset quality,
1

capitalization and to other factors reflecting asset and liability characteristics. The degree of
banking market discipline turns out to vary greatly among these three countries.
Having identified the degree of market discipline on banks in each country, we test for the
proclivity of banks to take on risk in the wake of liberalization or privatization. We use
empirical models of market contestability that can determine if and when financial institutions
operate at output levels where marginal cost exceeds marginal revenue before or after regulatory
or ownership regime changes. Running where marginal cost exceeds marginal revenue is a
statistical result consistent with a struggle for market share. Indeed, we claim that banks run in
this way when some present value calculation motivates them to countenance taking short-term
losses in expectation of longer-term gains.
Our results suggest a negative and direct connection between the degree of depositorimposed discipline on a nation’s banks and their predisposition towards risky lending in the wake
of liberalizations or privatization.
Market Discipline: The Role of Depositors
Although government guarantees are commonly blamed for breakdowns (or the simple
absence) of discipline upon bankers by depositors, the use of direct measures of government
guarantees to identify such breakdowns is difficult. The reason is, depositors may perceive
implicit government guarantees even when explicit guarantees do not exist.
In the literature on moral hazard and depositor discipline, bankers are typically imagined
to know beforehand how much depositors will (or will not) discipline them - punishing (or not
punishing) the bankers with bank runs in retaliation for poor performance. Bankers’ perceptions
of the punishments they will receive for a bad outcome of risky lending is accordingly supposed
to affect how riskily bankers will lend. If bankers do not expect any or much punishment, the
2

good outcomes that can occur from risky lending will motivate them to lend more riskily, even
though they know bad outcomes are possible. It follows that if lenders perceive that depositors
believe implicit guarantees exist, lenders will lend more riskily in anticipation that depositors
will not punish them for it, even in the absence of explicit guarantees.1
To test for depositor-imposed market discipline on banks in Argentina, Canada and
Mexico, we apply an empirical model of depositor growth for each country during a period of
financial stress.2 The examination corrects for the effect of other links between deposit flows and
asset quality. Consistent with a narrative in which depositors may or may not flee banks whose
assets have begun to sour, this model uses bank-by-bank data to examine bank-by-bank
characteristics that might aggravate or temper depositor reactions. These include a capitalization
ratio to capture a bank’s capital adequacy, a bank’s share of total assets to account for too-big-tofail perceptions, and a measure of liability composition.3 However, very detailed analyses using
numerous financial measures are not practical because of limitations on the number of financial
institutions. Adequate data were available for only sixteen Mexican banks. In the case of
Canada, a full set of data (particularly past-due loan data) was available for only the six largest
banks (although it should be noted that they account for 90 percent of total Canadian bank
assets).

Gilbert’s (1990) review of the literature suggests that it generally finds discipline where
guarantees do not exist and does not find it where guarantees exist. The literature since Gilbert
seems to derive similar results (See Park and Peristiani, 1998).
2

We focus on periods of natural financial stress because we think such periods are when
depositors are most likely to consider whether they ought to leave their present banks for safer
financial institutions or mattresses.
3

Rojas-Suarez and Weisbrod (1996) argue that suitable measures of capital may be
unavailable for Latin American banks. Based on the rates offered on deposits, they conclude that
bank liability holders in both Argentina and Mexico were able to identify risky banks, however.
3

An examination of the results (Table I) linking deposit growth rates and bank
characteristics in Argentina, Canada, and Mexico offers large differences across countries.
Depositors exerted significant discipline on Argentine banks but not on Canadian or Mexican
banks. In all models, the dependent variable (DEPGRP) is the percentage change in inflationadjusted deposits.
Recall that the examination period chosen for each country is one of financial stress. For
Argentina and Mexico, the examination is performed for the Tequila Effect period of December
1994-June 1995. For Canada the percentage change is year-over-year for 1984, 1985 and 1986,
so as to capture the stresses leading to the first Canadian bank closures (in 1985 and 1986) in
more than six decades. PDL/TA is past-due loans as a percentage of total assets, included to
measure the quality of the asset portfolio. EQ/TA is equity capital as a percentage of total assets,
which is included to measure the ability to maintain solvency in case of financial losses.
Ln(TAi/TA) is the logarithm of the quotient of total assets for a given bank divided by the sum
of all bank assets, so as to account for too-big-to-fail perceptions. DEP/L is deposits as a
percentage of total liabilities, which we include to control for the potential influence of liability
composition on depositor behavior.
In the cases of Mexico and Canada, none of the explanatory variables is individually
significant at the 10 percent level. They are also not jointly significant at the .10 level although,
with an F-value level of significance of .2027, Canada’s joint significance level is closer to an
acceptable level than Mexico’s .4751. In contrast, the model’s explanatory power for Argentina
is highly statistically significant at the .0001 level.
Despite our concerns about implicit guarantees, the degree of depositor discipline among
the three countries turns out to be inversely related to the maximum level of deposits that are

TABLE I
Deposit Growth and Asset Quality
In Three Western Hemisphere Nations

Argentina

Canada

Mexico

-30.600
(-0.24)

-54.999
(-1.82)

Constant

-67.546
(-2.17)

PDLi/TAi

-1.052
(-3.43)

***

-0.060
(-0.01)

0.473
(0.12)

EQi/TAi

0.821
(1.90)

-6.366
(-1.65)

-0.888
(-0.25)

Ln(TAi/TA)

2.978
(0.63)

-9.389
(-1.33)

-8.376
(-1.27)

DEPi/LI

1.075
(4.20)

0.504
(0.38)

0.386
(0.66)

0.770

0.348

0.255

Prob(F-Stat)

0.0001

0.2027

0.4751

# of Observations

***

Note: the dependent variable is the percentage change in the inflation-adjusted deposit
growth rate of bank i. PDLi/TAi is bank i’s past-due loan as a percentage of total assets.
EQi/TAi is bank i’s equity capital as a percentage of total assets. Ln(TAi/TA) is the log of
bank i’s total assets over the sum of total assets of the banks examined. DEPi/LI is bank
i’s deposit as a percentage of total liability. t-statistics in parentheses, based on
approximate standard errors (***: significant at 0.01 level, **: significant at 0.05 level, *:
significant at 0.1 level)

explicitly insured in each country. While Mexico’s deposit insurance was virtually open-ended,
that of Canada was limited to $60,000 (Canadian dollars), while Argentina’s maximum was
$10,000 or $20,000 (U.S.) depending on type of deposit.4 Accordingly, in our model, a bank’s
asset quality least explains its deposit growth in Mexico (the country with the most explicit
guarantees) and most fully explains deposit growth in Argentina (the country with the lowest
level of explicit guarantees). Indeed, for Mexico the effect of asset quality weakness (PDL/TA,
past-due loans divided by total assets) on deposit growth takes on a perversely positive value,
although the t-value of 0.12 (.904 level of significance) is far from significant. Canada’s
PDL/TA coefficient is also insignificant, but the negative sign is as expected. In contrast to
Mexico or Canada, the relation between asset quality weakness and deposit growth in Argentina
is not only negative but significant. That is, when asset quality weakens, depositors withdraw
their funds.
Results for Argentina differ noticeably from those of Mexico and Canada not only
because of the model’s joint significance and because of the significance of the past due loans as
a share of total assets variable (PDL/TA), but also because of the significance and signs of the
equity and deposit-share-of-liabilities variables. If depositors are very sensitive to a bank’s
capitalization, and if they are more likely to remove their funds from a poorly capitalized bank
than from a well-capitalized institution, the coefficient on EQ/TA (equity as a percentage of total
assets) ought to be positive and significant. For Mexico and Canada, the coefficient was negative
4

Fernandez and Schumacher (1998) note that, because the deposit insurance program was
not fully funded, the de facto level of deposit insurance was in fact far lower than the $10,000
and $20,000 maxima. They also note that, by tying the size of monetary base to the size of
foreign reserves, Argentina’s Convertibility Law severely restricts the government’s ability to
finance assistance programs through money creation. See Caprio et al. (1996) for more extensive
discussion of the constraints a currency board - as Argentina has - imposes on the lender-of-last
resort function.
6

and insignificant. For Argentina, the coefficient was positive and significant at the .08 level. In
sum, for Argentina but not for Canada and Mexico, the results support the view that depositors
discriminated based on the financial condition of banks.5 That is, during stress periods,
depositors disciplined Argentine banks but did not significantly (if at all) discipline Canadian
banks and did not discipline Mexican banks at all according to the present criterion.6
Financial Liberalization, Market Share Struggles, and Risky Behavior
Having established that banks receive more market discipline in some countries than
others, we now test for conditions under which banks lend more riskily in countries with less
discipline than in countries with more discipline. Recall that, in testing for market discipline, we
chose periods when each country’s banking system was under stress.
But in testing for risky behavior, we chose periods when there is reason to suspect that
each country’s banks might be particularly subject to temptations to take risks. Since the periods
we chose immediately followed either a financial liberalization or privatization, it is useful to
clarify why we think such temptations occurred then.
Large changes in legal regimes for banks can signify changed opportunities to develop
various categories of markets. The liberalization or privatization of a banking sector is typically
followed by a large increase in liabilities - as banks are permitted to take on liabilities at the rate
the market will bear instead of at what the government permits - and by rapid increases in bank

Note that the too-big-to-fail variable, the logarithm of the ratio of a banks assets to all
sample banks’ assets (Ln(TAi/TA)), was not significant for any of the three countries. We used
this ratio of assets in order to address the Canadian data problem, in which we had to use three
years’ data in order to have enough degrees of freedom to run the model. We were concerned
that if we had simply used assets instead of a ratio, year-over-year growth in assets might distort
our results. We also ran the models using simple logarithms of bank-by-bank assets instead of
ratios. Neither the signs nor the significance of the coefficients changed as a result.
6

It may be said, however, that poorly performing Mexican banks were disciplined by
having to pay higher interbank rates on the Mexican interbank market.
7

assets (Gorton, 1992). In a narrative that resonates particularly with privatization episodes de
Juan (1995) notes that on a bank-by-bank level, when new owners take control of a bank, they
commonly increase lending relative to the value of equity capital or the deposit base. Whether or
not liberalizations and related rapid loan expansions are followed by large increases in loan
defaults - as they typically are in Gorton (1992), de Juan (1995), Kaminsky and Reinhart (1996),
and McKinnon and Pill (1994) - a common adjunct to financial liberalization is markedly
increased competition in the banking system (IMF,1993).
As liabilities expand and banks seek to match them with new assets, not only the quantity
but the quality of assets changes - and in more than one sense of the term. First, more assets
sometimes means much more of certain types of assets. Mexico’s newly privatized banks focused
on consumer markets far more than when those same banks had been publicly owned.
But asset quality also often changes in the sense of the other meaning of the term quality.
Under this same paradigm of financial liberalization, after a repressed financial system is
liberalized, banks cannot supply intermediation services efficiently because they lack expertise
and adequate technology (Kaufman, 1998). Banks' portfolios become riskier because banks
cannot evaluate the riskiness of loans and higher real interest rates under the new regime.
Lenders lack past distributions on which to base their assessments.
These depictions of post liberalization/privatization banking markets are consistent with a
more general theoretical literature on strategic interaction among firms in growing markets where
investment and growth of the firm are constrained by physical factors (which could include
qualified personnel) or financial factors. In this literature, firms make pre-emptive investments
as part of a struggle for market share (Spence, 1979). This struggle for market share in a
suddenly new market environment may be seen as key to the onset of the high-risk bank behavior

on which much of the current literature on financial and exchange rate crises is based.
These same depictions of post liberalization/privatization banking markets are also
consistent with studies of consumer behavior in which, for example, a credit card holder typically
develops a long-standing affinity for the first credit card he or she receives (Wall Street Journal,
1996). That is, banks fighting for market share may be willing to engage in riskier strategies in
newly opened markets (for example, consumer credit markets in Mexico in the early 1990s), than
they might in a more mature market, for the simple reason that the long-term stream of rewards
might be correspondingly greater to survivors who practiced pre-emptive behavior.
At some point, or perhaps at several, since the beginning of the 1980s Argentina, Canada,
and Mexico have all undergone significant changes in the role of government in banking. In
probing for shifts in risky behavior in the banking system of each country, we focus on one such
major regime shift for each country.
As of 1991 publicly-owned banks controlled 61 percent of all bank assets in Argentina.
Beginning in 1991, at the same time as the initiation of Argentina’s Convertibility Plan and of
related financial liberalizations, Argentina initiated efforts to privatize its extensive governmentowned provincial banking system.7
Nevertheless, by the onset of the Tequila crisis at the end of 1994, only three banks were
actually privatized and only one more was effectively privatized in January 1995. However,
from December 1995 through the first quarter of 1997 an additional eleven institutions were
privatized so that by the latter date less than one-third of all bank assets were in publicly-owned
banks. We model the period 1991.IV-1997.I to assess onsets of what may be construed as risky
bank behavior. The discussion below focuses on efforts to find a structural break at 1995.IV, the
7

For a thorough and incisive analysis of the Argentine privatization process see Abad,
Burdisso, D’Amato and Molinari (1997).
9

onset of the massive privatization effort.
Canada’s regime shift commenced with the 1980 Bank Act. The Act permitted a large
increase in the number of banks and allowed nonbank financial institutions to clear checks - a
practice previously prohibited. The Act was the beginning of a trajectory of financial
liberalization in the 1980s that relaxed restrictions on commercial and consumer lending, allowed
federally chartered financial institutions and foreign investors to own 100% of securities dealers,
and more generally permitted fuller bank competition with nonbanks and vice versa.8
In contrast, Mexico’s banking system was characterized by financial repression until the
late 1980s. The government had nationalized the banking system in 1982 and restricted interest
rates on deposits and loans. The government forced the banks to lend to it, crowding out
extensions of credit to the private sector.
The late 1980s saw profoundly market-oriented changes. In 1987, the government of
Mexico sold to the private sector a total of 34 percent of the ownership in the publicly-owned
commercial banks. In 1989, Mexico introduced reforms to eliminate controls on interest rates
and on the term structure of traditional types of bank deposits, eliminated forced loans to the
public sector at below-market interest rates, and eliminated governmental edicts on the industryby-industry allocation of funds.
These liberalizations notwithstanding, the most profound regime change since the 1982
bank nationalization was the June 1991-July 1992 privatization, when Mexico auctioned off
majority ownership in all eighteen-government owned commercial banks. We present a model of
Mexico’s banking system performance during the period 1987-1993, with particular attention to

Amoaku-Adu and Smith (1995) note that, within a year after the passage of Bill C-56,
the six largest banks in Canada had acquired control of most of the nation’s large investment
dealers.
10

a structural break at the beginning of 1992, in the middle of the privatization process.
The Model
Although the purpose of the model, as we apply and interpret it, is to identify moves
toward high-risk behavior in a banking system, the model was originally designed to assess the
degree of banking system competitiveness. When the model is able to identify breaks at which
the typical bank commences the high-risk tactic of producing where marginal cost exceeds
marginal revenue, this identification is an adjunct to the original purpose for which the model
was designed. We measure the degree of competition because one state of competition - the state
that Shaffer (1993) has defined as supercompetition - is mathematically identical to the high-risk
tactic of producing where marginal cost exceeds marginal revenue.
It is important to reiterate why we emphasize breaks in bank behavior. Our efforts are
intended as examinations of an aspect of the current literature (Kaminsky and Reinhart, 1996, for
example) in which a trajectory beginning with financial liberalization, leading through
subsequent risky bank behavior, and continuing with an onset of serious financial stress in a
country can conclude with a financial and exchange rate crisis. We here focus on the portion of
the trajectory that joins the financial liberalization to the risky bank behavior.
However, when seeking the bases for high-risk bank behavior, there is a second and
equally important reason to focus on structural breaks. The paradigm we have presented so far
involves banks’ struggles for market share when liberalization and privatization have suddenly
made new market opportunities possible. A market share struggle occurs when the present value
of expected future return to the struggle looks consistent with the short-term stresses involved in
a cost/revenue relation that cannot long be sustained, i.e marginal cost exceeds marginal

revenue.9 We focus on breaks because high-risk bank behavior as we characterize it must be a
temporary phenomenon. Because the type of high-risk behavior we attempt to characterize
occurs as a struggle among banks for market share, it takes place across much or all of the
banking system.
In order to characterize breaks into high-risk bank behavior, we present a simultaneous
equation model that Shaffer (1993) introduced to the banking literature. This approach permits
testing of the competitiveness of a commercial banking system through estimation of an index of
market power (U) and then identifying breaks in competitiveness by applying a dummy variable.
The test revolves around the idea that profit-maximizing firms would set marginal cost
equal to what the literature calls their perceived marginal revenue. If the firm's perceived
marginal revenue schedule and the firm's demand schedule are identical, then setting marginal
cost equal to perceived marginal revenue is the same as setting marginal cost equal to demand
price, yielding the classical conditions for a competitive equilibrium. Here, of course, firms
behave simply as price takers.
In the collusive extreme, in which firms act as a joint monopoly, the firm sets marginal
cost equal to a perceived marginal revenue that corresponds to the industry's marginal revenue
curve (Bresnahan, 1982). Because the firm only perceives the marginal revenue schedule and the
demand schedule as identical under competitive equilibrium, the index we use to gauge the
competitiveness of a commercial banking system simply expresses the deviation of the average
bank's perceived marginal revenue curve from the industry demand schedule. If there is no

The discussion above of consumer behavior with respect to credit cards offers a case in
point. If credit cards have been little used in a country until a certain moment and if the first
bank that presents a consumer with a credit card is likely to win the consumer for life, then some
banks entering the suddenly new credit card market may be motivated to distribute credit cards as
rapidly as possible and with less thought than otherwise to borrower creditworthiness.
12

deviation, we have pure competition.
Following Bresnahan (1982)) we write a demand function for commercial bank services:
Q = D(P, Y, ?) + I,

(1)

where Q is quantity, P is price, Y is a vector of exogenous variables, ? is a vector of demand
equation parameters to be estimated, I is a random error term. Actual (as distinguished from
perceived) marginal revenue is:
MR = P + h(Q, Y, ?),

(2)

= P + Q/(jQ/jP)
The function h(Q, Y, ?) is the semi-elasticity of demand, and h(]) @ 0. Firms’ perceived
marginal revenue is:
MRp = P + Uh(Q, Y, ?),

(2')

where U is a new parameter to be estimated, 0 @ U @ 1. Here, U measures the degree to which
firms recognize the distinction between demand and marginal revenue functions. Let c(Q, W, A)
be the average firm’s marginal cost function, where W is a vector of exogenous supply side
variables and A is a vector of supply side parameters to be estimated. Maximizing firms will set
perceived marginal revenue equal to marginal cost or, where M is a random error term,
P = c(Q, W, A) - Uh(Q, Y, ?) + M

(3)

Price taking firms perceive no difference between their marginal revenue functions and
demand function. For them, U = 0. Firms acting as joint monopolies clearly perceive a
difference between their demand and marginal revenue functions. They set output where
marginal cost equals marginal revenue such that U = 1. Intermediate values of U correspond to
other oligopoly solution concepts. A Cournot equilibrium is suggested when U = 1/n.
An instructive detail of this estimating procedure is that (Shaffer, 1993) -U is also a local

estimate of the percentage deviation of aggregate output from the competitive equilibrium level
of output. Since actual price deviates from the competitive price by -UQ/(jQ/jP), and actual
quantity deviates from the competitive quantity by jQ/jP times the deviation in price, actual
quantity will deviate from the competitive quantity by -UQ. Thus, the percentage deviation in
quantity is -UQ/Q = -U. If -U<0, then output is less than what would occur in competitive
equilibrium, meaning that firms are behaving as if they perceived that they had market power.
Of greatest importance for the purposes of this paper, if -U>0, then actual output seems
to exceed the competitive equilibrium output level, even though static allocative efficiency
requires the marginal cost pricing outcome of U = 0. This bank behavior outcome is referred to
as supercompetition. It signifies that the typical bank in the market is operating at an output level
where marginal cost exceeds marginal revenue.
To estimate U, it is necessary to estimate simultaneously specifications of both (1) and
(3), treating P and Q as endogenous variables. The demand function is specified as:
Q = ?0 + ?1P + ?2Y + ? 3 PZ + ? 4 Z + ? 5 PY +? 6YZ + I

(2")

where Q is output quantity, P is output price, Y is a measure of macroeconomic activity, assumed
to be an exogenous variable, and Z is the price of a substitute for bank output, also assumed to be
exogenous. The interaction terms, the products PZ, PY and YZ, are necessary to permit rotation
of the demand curve as required to identify U.10
Following Shaffer (1993), a translog cost function is used to estimate the average

As Shaffer (1993) explains, a necessary and sufficient condition to identify U is that the
demand equation not be separable in at least one exogenous variable that is included in the
demand function, but excluded from the marginal cost function. This condition is satisfied if
?3 and ?5 do not both equal zero. This specification of the demand function, apart from the
interaction terms, represents a first-order (linearized) approximation of the true demand
function (Shaffer 1993). Our results lead to the conclusion that ?3 and ?5 are not zero.
Therefore U is identified.
10

commercial bank’s cost function as follows:
ln C =

E0 + E1 ln Q + E2 (ln Q)2 + E3 ln W1 +
E4 ln W2 + E5 ln (W1)2 /2 + E6 ln (W2)2 /2 +
E7 ln W1 ln W2 + E8 ln Q lnW1 + E9 ln Q ln W2,

(4)

where C is total cost, W1 and W2 are exogenous input prices, as explained below. Equation (4)
gives rise to following marginal cost function, c(Q, W, A),
MC = (C/Q)(A1 + A2 lnQ + A3 ln W1 + A4 ln W2) + M

(5)

Therefore, equation (3) is specified as follows:
P = -UQ/(?1 +?3 Z + ?5Y) + (C/Q)(A1 + A2 ln Q + A3 ln W1
+ A4 ln W2) + [ .

(3')

However, equation (3') is not configured to facilitate analysis of breaks in bank behavior. To
allow for breaks, we rely on the following specification of (3):
P = -UQ/(?1 +?3 Z + ?5 Y) + (C/Q)(A1 + A2 ln Q + A3 ln W1 + A4 ln W2)
- A5 DQ/(?1 +?3 Z + ?5Y) + [ ,

(3")

where D is a dummy variable to be more fully explained below and [ is a random error term.
The system of equations represented by (2") and (3") is then estimated simultaneously.
It is not unusual in articles on the banking systems of any of the three countries we
consider to disaggregate a banking system according to market scope. Banks are sometimes
characterized as large national, small national, multiregional or regional. Out of appreciation for
this bank-by-bank heterogeneity of market scope, it should be noted that the technique offered
here does not rely on any particular definition of bank markets. As long as the data sample spans
at least one complete market, then estimates of U are unbiased. Where the industry comprises
multiple markets, U signifies the average degree of market power over the separate markets.

Note that U reflects the behavior of the average firm in the sample.
Another important detail is that, although this model assumes banks are input price
takers, violations of the assumption do not damage the results in a way that would bother most
modelers. If banks have market power over deposits, in violation of the assumption, it can be
shown that the specification of U overstates the overall degree of market power by misattributing
any deposit power to the asset side.11 Here a finding of perfect competition or supercompetition
would be even more striking than if the input price-taking assumption were not violated.
Data
So as to maximize degrees of freedom, we used the most often-reported data available for
the applicable period for each country. This decision means that the number of observations per
year is different in each of the three country models. For Mexico, the data were monthly and the
period was April 1987 through December 1993. For Argentina, the data were quarterly and the
period was 1991.I through 1997.I. For Canada, we ran a model using data presented in Shaffer
(1993), which are annual and run from 1965 through 1989.12
It is important to reiterate that the latter portions of these time series capture events
following major liberalizations and privatizations. These periods give us roughly two years
(1992-93) of monthly observations on the Mexican commercial banks during and after which the

For a proof, see Shaffer (1994), 8-9.

In the case of Mexico, we stopped the model at 1993 because thereafter data reporting
began to take place on a quarterly rather than monthly basis. We started with 1987 for Mexico
and 1991 for Argentina because those were the earliest years for which data were available from
each country’s central bank. Recall that 1987 was an important year in the history of modern
Mexican financial liberalization. In that year, the government sold off 34 percent of ownership
in Mexico’s publicly-owned banks. Thereafter, in the years prior to the 1991-92 privatizations of
the majority of bank ownership, substantial liberalizations included removal of controls on
deposit and loan rates and considerable other changes. In Argentina, 1991 marked the inception
of the Convertibility Plan and attendant financial liberalizations .
16

largest banks were privatized, six quarterly observations (1995.IV-1997.I) for Argentina during
which most privatized banks there went through their privatizations, and a nine-year Canadian
period (1981-89) following Canada’s Bank Act of 1980.13
The model applied here uses the intermediation model of a bank. This approach,
developed by Klein (1971) and Sealey and Lindley (1977) and applied in Shaffer (1993) treats
the bank as a firm that uses labor to acquire deposits and, then, uses labor and deposits to
generate assets. The measure of output (Q) is thus total assets. The price of output (P) is total
interest income divided by total assets, i.e. average rate earned on assets. It should be noted that
this average rate of return will be affected not only by market lending rates but by changes in the
past-due loan ratio. Since deposits and labor are the only production inputs, input prices for
deposits (W1) and labor (W2) are required. In the marginal cost function, for W1 the average
interest rate paid on deposits (i.e. total financial costs/total liabilities) is used. For W2 total
personnel expenditures/total personnel is applied.
In principal, a particularly appropriate substitute for banking services would be the
commercial paper rate in each country. Unfortunately, during the periods under study in each
country, data on such instruments were not available. Accordingly, in the case of Mexico, the
interest rate on 28-data cetes, or Mexican treasury bills was used. In the Canada model, rates on
three-month Canadian government paper were applied. In the Argentine case, because of a lack
of a series even for Argentine government paper rates for the period, three-month U.S. treasury
bill rates were used because of their close correlation with LIBOR rates. Use of this series in the
Argentine model provided the expected signs and hoped-for levels of significance in most cases.

We also tested as Argentina’s privatization period 1995.I-1997.I, so as to pick up twelve
of the fifteen privatizations instead (as with 1995.IV-1997.I) of eleven. The results were not
substantively different from characterizing the regime shift period as 1995.IV-1997.I.
17

As a measure of national output, an index of industrial production was used for Argentina
and Mexico since less-than-annual observations for GDP were not always available. In the
Canada model, annual GNP is used. All nominal variables were deflated using the consumer
price index.
Estimation and Results
Table II presents the estimation results for the models of each of the three countries, with
dummy variables for the relevant period of privatization or liberalization in each case. The results
show that, after national liberalization or privatization regime changes, the average bank in the
high-guarantee, low depositor-discipline nations of Canada and Mexico began to pursue
statistically significantly riskier behavior than before these changes. In contrast, the average bank
in the low-guarantee, high depositor-discipline nation of Argentina did not.
Indeed, our a priori expectations of the parameter estimates (ai for ?i, bi for Ai) were in
general confirmed by the results, with the exception of a2 in the cases of Argentina and Mexico.
Since the demand curve is assumed to be downward sloping, the estimate of jQ/jP = a1 + a3Z <
0
must hold, as it did in all cases. We also expected to find a2 > 0 and a4 > 0. As earlier noted,
either a3 or a5 must be different from zero in order to identify U, a condition that was always
satisfied by a3. Our estimate of the parameter vector A also met with a priori expectations,
although we held no a priori expectation on b5.
The systems of equations were estimated by the method of Full Information Maximum
Likelihood. This method assumes normally distributed errors. Initial parameter values for the
FIML estimation were supplied by first estimating the system by non-linear Three-Stage Least
Squares. The interaction variable YZ had to be omitted in the estimation because it was nearly

perfectly linearly correlated with the variable Z for both Argentina and Mexico. This was due to
the small variation in industrial production that occurred over the period of the sample.
Therefore, in the reported results, there are no estimates for a6 for those two countries although
there are estimates for Canada, where GNP was used for Y.
Problems with multicollinearity remain in this sample. In particular, ln W1 is highly
correlated with Z, causing difficulty in estimating and making inferences on the parameter vector

A. Nevertheless, convergence of the estimates was fairly rapid in all cases. The estimates also
appear to be robust relative to initial values of the parameter estimates.
For the purposes of this discussion, the most important results involve the coefficients of

U, the variable that measures level of competitiveness, and of b5, the U-related dummy variable
coefficient for the liberalization or privatization period for each of the three countries. Recall that
the value of -U represents a typical bank's percentage deviation of output from competitive levels.
Thus, a -U<0 signifies output below the competitive level while -U>0 suggests that output for
some reason exceeds the competitive level.
The null hypothesis that U = 0 could not be rejected at a reasonable level of significance
for any of the estimations. That is, the average bank in each of the three countries behaves
consistently with the competitive paradigm. The inability to reject the null hypothesis means that
in no case did the average bank operate for each total observation period where marginal cost
exceeded marginal revenue.

TABLE II
Estimation of Equation (2’’) and (3’)

Argentina

Canada

M exico

***

-12211
(-0.11)
***
-3020770
(-5.25)
0.56925
(1.27)
61863
(0.72)
9874
(0.76)
***
13.869
(4.48)
-0.07015
(-1.69)

425690
(0.74)
*
-38456010
(-1.89)
-156
(-0.03)
***
1828469
(4.19)
***
-186328
(-5.36)
**
460617
(2.37)

6.89405
(4.16)
***
-0.36894
(-4.09)
0.01051
(0.17)
**
0.39261
(2.23)
0.00620
(1.25)
-0.00053
(-0.24)

***

0.71310
(0.95)
0.01034
(0.26)
**
-0.06658
(-2.54)
-0.00272
(-0.03)
*
-0.03563
(-1.95)
-0.00183
(-1.08)

6.71503
(2.91)
**
-0.35608
(-2.63)
-0.00144
(-0.02)
*
0.37083
(1.83)
**
-0.32464
(-2.57)
0.45874
(1.63)

Adj R (2”)
2
Adj R (3”)

0.770
0.959

0.971
0.995

0.700
0.969

# of Observations

?0
?1
?2
?3
?4
?5
?6
A1
A2
A3
A4
A5
λ
2

750979
(3.86)
***
-23857842
(-4.55)
***
-7342
(-3.89)
***
-3373371
(-5.33)
***
133609
(5.38)
***
243664
(4.73)

***

Note: t-statistics in parentheses, based on approximate standard errors (***: significant at
0.01 level, **: significant at 0.05 level, *: significant at 0.1 level).

That is, the average bank in each country did not follow the high-risk tactic. The question
remains, however, as to whether these countries operated at such levels during their postliberalization or privatization periods.
In examining the results for the post-liberalization or privatization period, the sign and
value of b5, the dummy variable coefficient, deserve particular attention. For such periods,
instead of equaling U, the index of market power will equal U + b5 and b5 is the difference of
level of competitiveness between two periods. If b5 is negative and significant, the period for
which the dummy applies demonstrates a significant increase in the riskiness of bank behavior.
For both Canada and Mexico, b5 is negative, significant, and takes on a modulus
(absolute) value substantially larger than that of U (where U’s value is insignificant in any case).
The negative and significant value of b5 suggests that the average bank in each of these two highguarantee countries significantly increased the riskiness of its behavior after liberalization or
privatization. In the Argentine model, by contrast, neither b5 nor U were significantly different
from zero. This signifies that neither did the average Argentine bank pursue the high-risk tactic
of operating where marginal cost exceeded marginal revenue for the entire measurement period
nor did banks increase the riskiness of their tactics in the wake of privatization. That is, the post
regime-shift operating behavior of Canadian and Mexican banks was at marked variance from
Argentina’s but pre-shift behavior was not.14

We tried to test the robustness of the results for other specifications especially for log
first differences. The results are qualitatively unchanged if iterations converge.
21

Conclusion
Although the oft-alleged relation between market discipline and risky bank tactics is
clearly demonstrated in the models we present here, of equal importance in our results is that this
connection is not an eternal feature of banking systems - at least not in extremis. While a
predisposition towards high risk tactics revealed itself in the low-discipline high-guarantee
countries of Canada and Mexico and not in the high-discipline low-guarantee nation of
Argentina, no country’s banking system always operated where marginal cost exceeded marginal
revenue. Although it would be hard to imagine a scenario in which any particular bank always
operated where marginal cost exceeded marginal revenue (at least in the absence of both eternal
stockholder optimism and eternal managerial optimism of the most extreme nature), the endless
replacement of old banks with new and optimistic institutions would be possible. Neither
phenomenon materialized.
Instead, banks in low-market-discipline, high-guarantee countries followed risky tactics
when there were new markets that may have seemed to warrant new market-share struggles.
Otherwise, high-risk tactics did not appear to be typical. While this additional conditionality for
risky behavior may not be surprising, discussions of it are less common in the literature than are
simple allegations of links between guarantees or low market discipline and risky lending
without detailed consideration of how or when15. According to our results, the risky behavior
15

Another factor that might conceivably have influenced cross-country differences in bank
risk is the strength or weakness of a country’s banking supervision and regulation. Banks in a
country with less prudential banking supervision and regulation might tend to behave more
riskily. However, it turns out to be unlikely that banking supervision and regulation factors cause
significant bias in the estimation of our model. In order to examine this problem, we need to have
a single cross country index which measures a country’s regulation and its ability to supervise its
banks. The research to set up this cross country index is in progress (See Barth, Caprio and
Levine 1998, Caprio 1998, and JP Morgan 1997) but is not yet refined enough for our purposes.
An alternative method is to use proxies for banking supervision and regulation. La Porta et al
(1998) report the indexes of law enforcement variables during 1980-95. Since prudential
22

and liberalization story is true and the risky behavior and guarantees story is true, but only when
the two stories are told together.

supervision depends more on the quality of supervision than on institutional elements, indexes of
rule of law and of corruption can be proxies for prudential supervision. With the best law
enforcement indexed to 10, the indexes of rule of law in Canada, Argentina and Mexico are
10.00, 5.35, 5.35, respectively. The indexes of corruption in Canada, Argentina and Mexico are
10.00, 6.02, 4.77, respectively. These proxies suggest that banking supervision in Canada would
not be worse than Argentina and Mexico, and the difference between Argentina and Mexico may
not be significant. Our results in Table 2 do not reflect these differences in the proxies of banking
supervision.
23

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Full text of Working Papers (Federal Reserve Bank of Dallas) : When Does Financial Liberalization Make Banks Risky? : An Empirical Examination of Argentina, Canada and Mexico, Center for Latin American Economics Working Paper 0399

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