Being Local or Going Global? Competition and Entry Barriers in the
Canadian Banking Industry
Hector Perez-Saiz and Hongyu Xiaoy
January 9, 2014
Abstract
For decades, the Canadian retail banking industry has had an oligopolistic structure, along with
large variations in geographical presence among the di¤erent depository institutions. These facts could
potentially be explained by the regulatory and cultural entry barriers between provinces, as well as the
large heterogeneity between the “global” Big Six banks and the local players such as credit unions. In
this paper, we quantify the importance of these e¤ects in rural markets by estimating a static entry
game, as in Bajari, Hong and Ryan (2010). We …nd that credit unions are the strongest competitors
among all banks, and that entry barriers vary greatly across Canadian provinces. We also …nd that large,
global banks do not have an advantage when competing against smaller, local players. We use these
estimates to model the e¤ect of a new regulation that would allow Desjardins, a large regional credit
union, to expand across provinces. We …nd that this new regulation would not signi…cantly change the
competitive landscape in Canada.
1
Introduction
The Canadian banking industry has been oligopolistic for the last 50 years, with large banks, namely
the "Big Five" banks, (Royal Bank of Canada, Bank of Montreal/BMO, Bank of Nova Scotia, Canadian
Imperial Bank of Commerce and Toronto-Dominion Bank) dominating the landscape. While this market
We want to thank for comments and suggestions Jason Allen, James Chapman, Evren Damar, and participants at seminars
at the Bank of Canada, and the University of Ottawa. Any opinions and conclusions expressed herein are those of the authors
and do not necessarily represent the views of the Bank of Canada.
y
Bank of Canada, Financial Stability Department, 234 Wellington Street, Ottawa, Ontario, K1V 1V8. Contact email:
[email protected] and [email protected].
concentration has only increased over the last three decades with the emergence of universal banking and
breaking down of regulatory barriers, there are still local and regional players, such as credit unions and
regional banks, that play a signi…cant role in certain parts of the country. We also observe geographical
variation in the presence of retail bank branches even among the Big Five banks. The coexistence of an
overall oligopolistic market structure and signi…cant geographical variation motivate us to investigate how
competitive the retail banking industry is in Canada, and how important entry barriers are in shaping the
branch distribution.
This paper uses a static game of perfect information to analyze the competitive e¤ects of individual
banks and other …nancial …rms against each other. We estimate entry barriers, taking into account geographical variations due to regulatory and cultural entry barriers between provinces. We also estimate
the e¤ects of …rm heterogeneity. Our empirical strategy follows a large structural entry literature that has
developed over the past two decades, starting with Bresnahan and Reiss (1991) and Berry (1992). We also
estimate a counterfactual experiment based on recent regulatory changes that permitted the establishment
of federally-chartered credit unions in Canada.
Our main results show evidence of di¤erentiation between many potential entrants we have in our
model. We discover that credit unions are the hardest competitors by a signi…cant margin, while other
institutions, including national banks or regional players, compete less hard against each other. We also
…nd evidence for large geographical di¤erences in entry costs across provinces, with an almost four-time
di¤erence between the province that has the lowest entry cost and the one with the highest. Surprisingly,
we …nd little e¤ect of a bank’s national asset base on its competitiveness. This means that a large national
bank does not have a competitive advantage in the retail banking market versus a regional player such as
credit unions, despite having a national and often, an international presence. Hence, going "global" might
not be a winning strategy against staying "local". The counterfactual experiment also shows that the new
credit union regulations do not have a large impact on the overall market structure. This suggests that
further lowering of entry barriers might be needed to foster more competition.
We use a simulated method of moments estimator adapted from Bajari et al. (2010) to estimate a perfect
information entry game. Moments are obtained by di¤erencing the observed and simulated equilibrium
probabilities, weighted by functions of exogenous variables. In cases of multiple equilibria, we adopt
the equilibrium selection rule that chooses the equilibrium with the highest joint pro…t. We di¤er from
previous papers on bank competition (Cohen and Mazzeo (2007)) by examining an oligopolistic market
2
with clear identi…cation of potential entrants due to entry barriers. We are also able to identify many more
heterogenous agents, with up to 7 …rms as potential entrants for each market, than previous studies and
estimate their competitive e¤ects against each other. Finally, the ‡exible approach we took allow us to
look at …rms with potentially di¤erent objective functions than maximizing pro…t, such as credit unions.
This paper is divided into six sections. Section II goes into more detail regarding the evolution of
Canadian banking industry and references earlier literature that examined industry concentration. Section
III explains our estimation methodology and relates it to the larger structural entry literature. Section
IV examines the data we use, as well as our market and potential entrant selection criteria. Section V
analyzes our estimation results and the counterfactual experiment. Section VI concludes.
2
Background & Lit Review
Our research is motivated by the sustained oligopolistic nature and geographical dispersion of the Canadian
retail banking industry. Indeed, the Canadian banking industry is very concentrated, with the Big Six banks
(Big Five + National Bank of Canada) controlling 98% of total banking system assets in 2008, and over
80% of the assets from all Canadian …nancial …rms combined.
This dominance has been enhanced over the last three decades through deregulation. Traditionally,
Canadian banks’activities were strictly regulated, with product portfolio regulations di¤erentiating banks
from trust and loan companies, which specialized in mortgage lending. Strict cross-ownership restrictions
were implemented to ensure that losses in one sector does not spill over to the others. Foreign ownership was
also forbidden for large public banks. Deregulations since the 1980s gradually weakened and eliminated
these type of business, cross-owneship, and foreign ownership restrictions.
1
The subsequent industry
consolidation eventually led to all large national trust companies being acquired by the Big Six banks by
the late 1990s.
2
Consequently, the trust company share of the mortgage lending market dropped from
around 30% to less than 10%. (Allen et al. (2011))
Despite this consolidation, a third type of depository institution exists in Canada to provide competition
to the banks. They are the credit unions. Credit unions (caisses populaires in French) are …nancial
1
The 1980 Bank Act revisions allowed banks
to establish subsidiaries in other …nancial services markets such as mortgage lending. Allen and Engert (2007) Foreign
banks were allowed to establish subsidiaries. The 1987 revisions allowed banks to acquire securities dealers. The 1992 revisions
allowed banks to acquire trust companies.
2
The major national trust companies that were acquired were: Royal Trust in 1993, Montreal Trust in 1994, National Trust
in 1997 and Canada Trust in 2000. Allen et al. (2011)
3
institutions founded on the cooperative principle and owned by their members. They can provide the
same type of depository and lending services as banks do, and in many areas of the country, they provide
the strongest competition to banks in the retail market. In fact, Desjardins Group is the largest …nancial
institution in Quebec by asset size. Canada has one of the largest credit union systems in the world in
percentage terms, with 11 million members covering more than 40% of the economically active population.
(World Council of Credit Unions, Raw Statistical Data 2006) One signi…cant disadvantage that credit
unions faced was the constraint to operate within their home province, where they are incorporated and
regulated. In contrast, the federally-chartered banks are regulated federally, and they can operate across
Canada. The Credit Union Central of Canada was created to provide a national …nancing facility and
liquidity pool for its member credit unions. However, it is only an imperfect substitute at best for a truly
national credit union.
While some literature on credit unions emphasize the theoretical possibility that they can pursue
a di¤erent objective function than to maximize pro…ts, such as seeking to maximize the surplus of its
members, Taylor (1971) they do face real-world limitations that orient them more towards pro…ts. Firstly,
they face competition from commercial banks and other …nancial institutions that force them to trump
member bene…ts in order to survive. Secondly, they need to make pro…t to build their capital base and
satisfy regulatory requirements, given that they cannot raise money by issuing shares. McKillop and Wilson
(2011)
A …nal note on ATB Financial, a provincially-owned savings bank that operates solely in the province
of Alberta. It is not legally considered to be a bank, however, it possesses all the the deposit-taking and
lending powers of a bank within Albertan jurisdiction. ATB Financial is also one of the largest …nancial
institutions in this oil-rich province.
The Canadian retail banking is not only concentrated, but also seems to exhibit a high entry cost.
Indeed, no signi…cant entry in the industry occurred after 2000. This entry barrier still has a regulatory
component, since despite dropping foreign ownership restrictions, the 2012 Bank Act still stipulates that
no single shareholder or group of shareholders can have de facto control of a large bank, de…ned to be any
bank with an equity of $12 billion or more (The Big Five qualify). Furthermore, the CEO and the majority
of directors on the board of such banks must be residing in Canada.
Despite the evolution of online banking, there is strong evidence that consumers still prefer to do
business with banks that o¤er physical branch locations near them. (Amel and Starr-McCluer (2002))
4
This result is corroborated by the fact the largest online-only bank in Canada, ING Bank of Canada, only
had an asset base of $23 billion by the end of 2006, which is in the same range as regional players such as
ATB Financial, and much smaller than the Big Six or Desjardins.
The evolution of the Canadian retail banking industry can be seen in Figure 1, and we can see that
it has, to some extent, entered into a state of long-term equilibrium by 2006. From Figure 1, we can see
that the total number of retail branches in the country stabilized after 2003, after decades of long decline
following deregulation of the …nancial sector in the 1980s and 1990s, with many branches having closed in
rural areas due to mergers between banks and trust companies. At a same time, a stable industry struture
emerged after the merger between Canada Trust and TD Bank in 1999, characterized by the absence of
entry and merger between large players. Even the relative ranking of the Big Six banks by asset size
stayed the same. In fact, two proposed mergers between members of the Big Six were vetoed by the federal
government in the 1990s for their potential harm to competition, and no merger proposals between large
national banks have come up since.
This market concentration and lack of entry naturally raises questions about how competitive the Canadian retail banking industry actually is. Historically, studies in contestability have shown that concentrated
markets can still be competitive. Baumol and others (1982) Indeed, some prior studies of competitiveness
in the Canadian banking industry focused on indicators of contestability on a national scale, using bankwide variables such as total assets, like in Allen and Liu (2007). They found that the industry structure
was monopolistic competition. Other studies focused on speci…c products such as competition in mortgage
loans Allen et al. (2011). This paper di¤ers from the above because it studies in detail the competition
between canadian banks in geographically separated local markets, by looking at the entry decision of each
bank with respect to each market. This decision is made independently for every bank per market, which
would take into account how competitive the entire portfolio of retail banking products is in each location
for each bank.
Our paper is also relevant because it is one of the …rst structural entry models that looks at an oligopolistic banking industry. Indeed, the large majority of literature on banking entry, such as Cohen and Mazzeo
(2007), looked at the US industry, which is very fragmented in comparison. This industry concentration
makes estimating a structural model with each individual bank as a potential entrant feasible, without
resorting to homogenous agent assumptions. In other words, we take into account …rm heterogeneity and
…rm-speci…c competitive e¤ects. The various regulatory and linguistic barriers also allow us to determine
5
the number and identity of potential entrants in each province with good con…dence, which is a common
di¢ culty in other structural models.
3
Model
We estimate a static entry game of perfect information for the Canadian retail banking industry. In other
words, each potential entrant decides independently whether to enter into a market, observing all the
factors that enter into each other’s pro…t function. These factors are not necessarily observed by the
econometrician. Each potential entrant i’s decision to enter market n is determined by the pro…t relation:
ni
=
0
+ Xn + Zi +
X
ij 1[if
bank j enters market n] +
ni
(1)
j;i6=j
where
ni
is the expected pro…t that the entrant will obtain if it enters market n, Xn and Zi respectively
are vectors of market-level and …rm-level exogenous variables that a¤ect the …rm’s pro…t function.
a constant that represents a …xed entry cost, while
with variance normalized to one.
ni
ni
0
is
is a market and …rm-speci…c error term that is iid
is not observed by the econometrician.
Similar to Berry (1992) and Ciliberto and Tamer (2009), we adopt the heterogenous agents approach
with a reduced-form pro…t equation that includes …xed and variable parameters. We do not distinguish
between costs and revenues, with both their e¤ects netted out and the net e¤ect on pro…t included in
the equation. We also model competitive e¤ects between banks. We estimate separate competitive e¤ects
between every pair of …rms, if they are both potential entrants in at least one market. In the pro…t
equation,
ij
is the competitive e¤ect of bank j’s entry into the market on bank i’s pro…t, which only
enters into the equation if bank j has decided to enter market n. By allowing the competitive e¤ect to
vary across bank pairs, we di¤erentiate between …rms such that the e¤ect of CIBC’s entry on TD’s pro…t
would not be the same as that of RBC’s entry on TD. This is a ‡exible way to take into account …rm-level
unobserved e¤ects that a¤ect each bank’s competitiveness against speci…c other banks, such as portfolio
di¤erences. This ‡exible approach also allows us to di¤erentiate between di¤erent competitive models for
every …rm. For example, credit unions could compete more aggressively because they don’t always seek to
maximize pro…ts. We do assume that each competitor a¤ects other potential entrants’pro…t only through
the competitive term, given that our markets are isolated and therefore, there are no network e¤ects.
Economics of density are probably small in our markets, contrary to other industries (Panle Econometrica
6
paper). Due to computational tractability concerns, we impose the symmetry constraint
ij
=
ji .
We
also constrain the maximum number of potential entrants in each market to 7,3 though that is still a
large increase over recent banking industry models (Cohen and Mazzeo (2007)). It also captures the vast
majority of potential entrants in every market. (Figure 2)
A potential entrant decides to enter a market n if
ni
> 0; conditional on the rest of the potential
entrants having some strategy. Otherwise, it does not enter. This rule clearly makes sense for the banks,
but it also applies to credit unions, who cannot a¤ord to lose money if they want to stay in business. The
game is played simultaneously by all potential entrants in every market and we compute all Nash equilibria.
A potential equilibrium is reached when all entrants that have entered have a positive pro…t with entry,
while the other potential entrants have a negative pro…t upon entry.
We use a simulated method of moments estimator as our estimation strategy, adapting the approach
from Bajari et al. (2010). The moment conditions are obtained by weighing the di¤erence between observed
equilibrium and predicted probability of equilibria being observed, with exogenous variables:
mk = E[1(an = k)
Pr(k j X; Z; ; ; )] w(X; Z) = 0
(2)
where X and Z are vectors of market-level and …rm-level exogenous variables, which also include their
interactions. an is the observed equilibrium in market n, and 1(an = k) is an indicator function such that:
1(an = k) =
1 if observed equilibrium in market n is the kth equilibrium
0 otherwise
(3)
where k is one con…guration out of potential 2E possible con…gurations, where E is the number of potential
entrants in market m. The probability of equilibrium k being selected conditional on exogenous variables
is Pr(k j X; Z; ; ; ):The …rm-speci…c pro…t functions are identi…ed via …rm-level exogenous variables, in
the same way as the traditional identi…cation strategy for entry models used by Berry (1992) and Bajari
et al. (2010), among others.
To accomodate the fact that the Canadian retail banking market is not uniform across the country due
to regulatory and cultural entry barriers, with di¤erent sets of …nancial institutions having large presences
in di¤erent provinces, we allow di¤erent regions (province groupings) to have di¤erent potential entrants,
with di¤erent competitive e¤ects in play. We constrain these groupings in the overall model by assuming
3
Some provinces have 6 potential entrants.
7
that the competitive e¤ect between the same pair of banks are the same in all regions where they are
both potential entrants. So in the example above, the competitive e¤ect between B and C are the same
in both regions I and II. Furthermore, we introduce provincial …xed e¤ects within each grouping to take
into account systematic di¤erences between provinces. The latter are included as market-level exogenous
variables.
We observe the current long-term industry equilibrium in a market. However, we do not observe the
predicted probabilitity that such an equilibrium or other potential equilibria being realized because we
only have one realization out of potentially in…nitely many. Therefore, we use simulations to estimate
the probability of each equilibrium being realized, with error terms drawn from independently normal
distributions. Given a set of coe¢ cients ,
and , we compute the sample probability of an equilibrium
k being selected conditional on exogenous variables so that
S
X
c j X; Z; ; ; ) = 1
f1[equilibrium k is selected; x; z; "s ; ; ; ]g
Pr(k
S
(4)
s=1
where S is the total number of simulations for each market, "s is the error term drawn fresh for each
simulation. For each draw, we solve for all Nash equilibria and choose the most pro…table one.
We then construct our sample moments m
b for each market n by di¤erencing the observed equilibrium
against the sample probability of it being selected in each market, and then averaged across all markets,
so that
1 Xh
m
bk =
1(an = k)
N
N
n=1
c
Pr(kjX
n ; Z; ; ; )
i
!(X; Z)
(5)
where m
b k is the sample moment for the kth industry con…guration. In the end, we compute our simu-
lated method of moments estimator using an indentity weighting matrix and …nd the global minimum in
coe¢ encts space
min m
b 0 (X; Z; ) W m(X;
b
Z; )
(6)
where m
b is a concatenation of moments from all provincial groupings.
Identi…cation of the parameters in our model is achieved in three ways. Firstly, we use variation in
covariates and outcomes in the GMM objective function to identify parameters associated with market-level
and …rm-level variables. Secondly, for the strategic interaction parameters, we use exclusion restrictions
where the pro…t for one …rm is shifted independently of other …rms, such as national and regional size of
each institution, for identi…cation. This approach is discussed in Bajari et al. (2010).
8
Thirdly, given the assumptions of our model, multiple equilibria are possible, contrary to other papers
(Mazzeo (2002), Cohen and Mazzeo (2007), cite others) where additional assumptions guarantee a unique
equilibrium. This poses a problem for identi…cation. To identify the equilibrium we use, we compute all
equilibria and then select the most e¢ cient one as our predicted equilibrium. E¢ ciency is de…ned as the
highest joint pro…t among entrants. Unlike Berry (1992), we cannot exploit the uniqueness in the number
of …nal entries because it is not a given that all equilibria have the same number of entrants that decide
to enter. Furthermore, given our assumption that the industry has reached long-term equilibrium (look
at Figure 1), it is plausible that the most pro…table …rms were able to establish themselves and squeeze
out less pro…table …rms. Our equilibrium selection rule can be considered in the context of Bajari et al.
(2010), with the most e¢ cient equilibrium always being selected with probability one.4
4
Data
For our model, we use bank branch location data from the 2006/2007 edition of Canadian Financial Services,
a comprehensive directory of all Canadian Financial Institutions, their o¢ ces and branches. The directory
is updated annually and contains the exact address of each branch. We gather data from depository
institutions such as domestic banks, foreign banks, trust companies and credit unions in our model, and
exclude non-depository institutions such as life insurers. After the deregulation in Canadian banking in
the 1980s and 1990s, the depository institutions can all accept deposits from individuals and businesses,
and they no longer have regulatory barriers the prevent them from entering each other’s businesses, except
for credit unions. So we consider them to be competing in the same overall market.
We de…ne markets using census subdivisions, which is a general term for municipalities in Canada.
They vary widely in area, population and other observed characteristics. For example, Toronto, with a
population of more than 2.6 million people, constitutes one census division, just like Martensville, SK, a
small city with less than 8000 souls. Apart from cities and towns, census subdivisions also include rural
areas grouped together into counties, indian reserves and other unorganized territory. There are 5,XXX
census subdivisions in Canada. We obtain market-level data such as population and average income from
the 2006 census.
Because census subdivisions do not necessarily re‡ect the boundaries of a market, we manually select
4
An interesting recent literature has developed a partial identi…cation approach. We use the traditional point identi…cation
approach.
9
small rual isolated markets to include in our model, based on well-de…ned criteria. In particular, we only
include census subdivisions that have between 200 and 50,000 individuals. The population lower limit
eliminates regions too uninhabited to support bank branches, while the upper limit exists to ensure that
we do not include large cities, which are composed of multiple neighhoods and have an internal structure
that makes harder to get a well-de…ned market. Large cities are also excluded given that our model does
not take into account the number of branches a bank has in a market, only whether it enters into a market
at all. In fact, we do not di¤erentiate between a bank that has 1 branch in a market versus another that has
3 in the same market, despite the fact that a bank clearly has to consider di¤erent factors when considering
a decision to open a …rst branch in a market and thus establish a presence, versus a decision to add a
branch in a market where it is already present. Eliminating large population centers will minimize this
confounding factor. The limits themselves were tested to include as many potential markets as possible.
We then eliminate markets that are located less than 50km away from any major urban centers, which
we de…ne to be a census subdivision with more than 100,000 people. Excluding markets located close to
large urban centers will help avoid the confounding factor of commuters. Indeed, if a worker lives in a
suburb and commutes downtown for work, he or she might satisfy his banking needs at a branch closer to
work than at a branch close to home. 50km can be an hour’s drive to work, and we believe that the vast
majority of people do not commute that far. (citation?) Then, we limit the area of each market to 300
square kilometers so it can be reasonally thought of as a single market rather than composed of multiple
separated markets, which occurs frequently in large rural counties. We also exclude indian reserves from
consideration, given their special administrative status and thus avoid potential regulatory confounders.
A map of one of the markets we have selected, Moose Jaw, Saskatchewan, is in Figures 3 and 4.
National descriptive statistics for the markets we selected are presented in Table 2. Nationally, the
average population is little above 3000, with a standard deviation almost twice as big. These numbers
re‡ect the fact that the vast majority of our markets are small rural towns with population in the few
thousands, but that we also include some small cities with population up to 50,000. The average income
is much more tightly clustered around $22,000 per person. The area of each market is in general small,
but with a few big outliers that break the 300 square kilometer rule, which are manually-selected markets
that only contain one population center, so they are still well-de…ned. Finally, the average unemployment
rate of 12% in our markets is almost double the national average of little more than 6%.
Provincial market descriptive statistics in Table 3 and Table 4 show that signi…cant di¤erences exist
between provinces. For example, the unemployment rate is lowest in rural Alberta, perhaps due to the oil
10
& gas boom then in full swing. In contrast, Newfoundland and Labrador has the lowest average income
of them all, while Ontario, the most populous province, has the highest number of people per census
subdivision.
We construct the dependent variable of bank entry/no entry into a market by looking for its branches
within a 10 km radius of the centroid of a given census subdivision. If one branch of the bank is found, we
say that the bank has entered in the market and set the dependent variable to 1. Otherwise, we set the
dependent variable to 0. The industry structure is determined by the decisions of all E potential entrants,
and can have 2^E con…gurations. While constructing the dependent variable, we further exclude markets
where a 10km radius involves overlap with bank branches in neighboring markets. In the end, we select
1,447 markets for the estimation of our model.
Due to the geographical fragmentation of the Canadian banking industry, we have di¤erent potential
entrants across provinces. To determine which ones enter which provinces, we use Table 1, which is a
detailed breakdown of all branches in our markets by province and …nancial institution. We can see that
while the Big Five (BMO, BNS, CIBC, RBC, TD) have large presences in nearly all provinces, other
players are more regional in scope. Unsurprisingly, ATB Financial can only be a potential entrant in
Alberta given that it is incorporated under Albertan law. Desjardins and National both cater primarily to
French-speaking Canadians, so they only boast signi…cant presences in provinces with large native Frenchspeaking populations in percentage terms, which are Quebec (80%) and New Brunswick (30%). In 2003,
Laurentian Bank sold its retail branch network outside Quebec to focus on its home province. In general,
whether a bank is a potential entrant in a province depends on its market position within that province.
The detailed breakdown of potential entrants is in 5. With these entrants we cover around 90% of all
branches in Canada. Only some small banks, trust companies and foreign bank branches are excluded.
This omission has even less impact on our result than this …rst impression gives because most of these
branches lie in large cities, which we exclude anyway.
We take population, total income and unemployment as market-level exogenous variables for all potential entrants. Higher population and income can lead to more demand for banking services while higher
unemployment can be linked with less. Provincial …xed e¤ects are included as well, separately for each
grouping of provinces. We also look at two …rm-level exogenous variables, the asset of a bank within a
province’s borders and the amount held outside. These …rm-speci…c variables serve as exclusion restrictions
that identify our model. We chose asset size partly becuase it can be a signi…cant variable on the banks’
11
cost function (McAllister and McManus (1993)). It can also correlate with potential consumer preference
for banks that have a larger local presence, or the ones that are larger and therefore could be perceived to
be safer. The latter can also be attractive due to their larger national and international presence.
The case of credit unions is somewhat special because regulations prior to 2011 limited their activities
to their home province. Coupled with the inability of a member-owned organization to raise money on the
equity market, this meant that each province contains dozens of small credit unions with one to several
branches, each located in di¤erent markets. These credit unions mostly did not compete against each
other, being located in separate markets. Almost all credit unions in a province are part of the Credit
Union Central in that province, which provides services and linkages to …nancial markets that are beyond
the ability of any individual credit union. So we group all the disparate credit unions within each province
as a single entity in our model.
5
Results & Analysis
5.1
Benchmark Model
Table 6 presents the baseline model estimation results with competitive e¤ects between …nancial institutions, along with the standard deviations obtained through bootstrapping. Around three quarters of the
estimated competitive coe¢ cients are negative, which match our expectations that …rm’s pro…t is negatively a¤ected by entry from rival …rms. One potential explanation for the positive e¤ects could be the
small sample size in which both …rms are potential entrants, like Desjardins and generic Credit Union,
which only enter together in New Brunswick.
Among all potential entrants, the generic CU’s estimated coe¢ cients are the most negative by far,
proving that credit unions already provide strong competition to the Big Six in small rural isolated markets.
In contrast, the Big Six’s coe¢ cients are still generally negative, but much less so, indicating a lesser degree
of competition among the national banks. Desjardins’coe¢ cients are surprisingly similar to those of the
Big Six by being less negative, in constrast to its English counterpart.
There are many alternative explanations to explain the credit unions’signi…cantly higher competitiveness. One potential explanation for the credit unions’ competitiveness is that they do not need to focus
solely on the goal of maximizing pro…t, meaning that they can a¤ord to lower prices more than commercial
12
banks. They could also face lower entry barriers in local towns, given that some people might be intrinsically attracted to do business with a locally-owned …nancial institution, similar to how local farmers’
markets are able to thrive. (…nd citation) Furthermore, they may be more nimble than larger national
banks and tailor their product o¤erings to the speci…c town they serve.
A fourth alternative is that in Canada, credit unions face provincial prudential regulations that are
looser than their federal counterparts,
5
with the notable exception of Quebec. With lower capital require-
ments and higher leverage cap, if it exists, credit unions can a¤ord to be more aggressive. The …nding
from recent literature that even when applying the same rules, state regulators tend to be more lenient
than federal regulators in the US, Agarwal et al. (2012) can also play a role in making credit unions more
competitive if it is replicated in Canada. This explanation is consistent with the experience of the 2008
global …nancial crisis, where dozens of credit unions failed in Canada, but none of the banks did. It can
also explain why Desjardins does not compete like other credit unions, given that it is based in Quebec,
which applies the same prudential regulations as the federal regulators. Furthermore, its market position
as one of the largest …nancial institutions in the provinces where it is a potential entrant, Quebec and New
Brunswick, might also make it act similarly to national banks.
The coe¢ cients of the demographic variables in Table 7 mostly follow expectations. A doubling of
the population would increase the expected pro…t by 0.98, far more signi…cant than the 0.08 provided by
doubling total income. This can be explained by the fact that Canada has a relatively egalitarian income
distribution, so the population’s e¤ect is far larger. A doubling of the unemployment rate also has a large
e¤ect, lowering expected pro…t by 0.39. A doubling of within-province presence increases the expected
pro…t by 0.47, but surprisingly, a doubling of overall national presence provide insigni…cant to slightly
negative e¤ect on expected pro…t. The last result goes against our intuition that a larger national presence
can attract customers who are frequent travelers. However, this factor is potentially more important in
larger cities than in rural markets, which o¤ers a potential explanation to this puzzling coe¢ cient.
Finally, the …xed e¤ect is strongly negative at -1.42, con…rming the presence of large entry costs. This
number is larger than any of the competitive e¤ects and demographic coe¢ cients. Therefore, there needs
to be roughly a 1.5 standard deviation increase in population to overcome the entry barrier. Furthermore,
the entry barrier varies tremendously between provinces, going from -0.21 in Quebec, where the entry costs
are even steeper than in Ontario, to 0.73 in New Brunswick, where the barriers are more than halved.
5
For example, Ontario credit unions face a leverage cap of 25 while federal banks face a cap of 20. (Ontario regulations
237/09) BC credit unions do not face leverage requirements. (BC Internal Capital Target for Credit Unions, March 2013)
13
5.2
Counterfactual Exercise
The motivation for this counterfactual exercise comes from the amendment to the Bank Act in December
2010, which allowed the establishment of federally-chartered credit unions subject to federal regulations.
Before then, as mentioned in Section III, credit unions and caisses populaires could only be incorporated
provincially and therefore be regulated provincially. While their provincial status provided some bene…ts
such as an exemption from more strict federal prudential regulations, as well as the ability to sell insurance
and automotive leasing products, the disadvantages are just as stark. First, provincially-regulated credit
unions could not expand their presence beyond their home province. Therefore, they cannot merge across
jurisdictions to expand in size. Second, provincial regulations are increasingly struggling to keep up to
date with the expanding universe of …nancial services, so credit unions are disadvantaged by being unable
to provide the newest …nancial products.
In contrast, a federally-chartered credit union would be able to do business nationwide, just like banks,
and also like the latter, they would be subject to the tight federal regulatory standards. Our counterfactual
exercise evaluates the long-run consequences of dropping interprovincial barriers for the largest credit union
in Canada, Desjardins Group, by assuming that it becomes an entrant in all provinces, up from just Quebec
and New Brunswick. We also increase its national size from zero to the sum of its provincial sizes, to make
equivalent to all national banks. Furthermore, we add an arbitrary amount to its national asset size to put
its size closer to its big bank competitors.
We also assume that the competitive coe¢ cients between Desjardins and other …nancial institutions
does not change as it expands from French-speaking provinces. This provides an upper bound to the
e¤ect of Desjardins will have on market structure by entering, since it does not take into account the
additional "cultural/linguistic" entry barriers it faces outside French-speaking areas. Indeed, this scenario
assumes that they could potentially change their focus and decide to serve English and French-speaking
populations equally, starting potentially with a name change so it can free itself from the local association
that Desjardins has accumulated. (cite marketing paper) The results are shown in Table 8.
Our counterfactual results show that while Desjardins does expand its rural branch network by 50%,
largely in provinces where it is not present, it does not fundamentally change the competitive landscape.
There is a small increase in the number of credit union branches, and a small decrease for most other
institutions. Furthermore, this is an upper limit due to cultural entry barriers and the actual results will
certainly be even less rosy. An important caveat to this result is that it only applies to small rural isolated
14
markets, where the ability to use banking services outside provincial boundaries could count far less than
it is for urban consumers, who tend to be more mobile. So the e¤ects of federal credit unions might be
much larger in urban markets. An additional caveat comes from the fact that we are abstracting from any
regulatory changes other than geographic barriers. So we are not taking into account the new portfolio
restrictions and expansions, nor are we taking into account the e¤ect of tighter prudential regulations.
6
Conclusion
In this paper, we use a static entry game of perfect information to analyze the competitive e¤ects between
…rms in the Canadian retail banking industry in 1447 small rural isolated markets. Our results show
that the credit unions compete the hardest, perhaps due to looser regulation that they face compared to
federally-regulated banks. The Big Six banks compete less hard, which is consistent with the oligopolistic
nature of the market. We also found large variations in entry barriers, which could be attributed to
regulatory and cultural di¤erences. And most surprisingly, we found that "global" banks do not have a
signi…cant advantage over strictly "local" players.
Policymakers keep professing their desire to increase competition in the Canadian …nancial services
industry. One signi…cant reform, passed in 2010, allows the creation of federally-chartered credit unions
that can potentially compete with banks nationwide. Our counterfactual experiment, however, show that
this exercise will not signi…cantly change the competitive landscape, and that other measures are needed
to reach the policymakers’ aim. One potential remedy would be to open the market further for foreign
banks.
References
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banking. Technical report, National Bureau of Economic Research, 2012.
Jason Allen and Walter Engert. E¢ ciency and competition in canadian banking. Bank of Canada Review,
2007(Summer):33–45, 2007.
Jason Allen and Ying Liu. E¢ ciency and economies of scale of large canadian banks. Canadian Journal
of Economics/Revue canadienne d’économique, 40(1):225–244, 2007.
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Jason Allen, Robert Clark, and Jean-François Houde. Discounting in mortgage markets. Technical report,
Bank of Canada Working Paper, 2011.
Dean F Amel and Martha Starr-McCluer. Market de…nition in banking: Recent evidence. Antitrust Bull.,
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1971.
16
7
Appendix
17
18
British
Columbia
Alberta
Saskatchewan
Manitoba
Ontario
Quebec
New
Brunswick
PEI
Nova
Scotia
Newfoundland
and Labrador
Province
0
90
0
0
0
162
52
105
0
173
0
0
0
0
ATB
391
452
374
164
540
865
Total
Branches
22
8
12
3
49
37
22
8
73
32
BMO
42
21
31
15
41
31
31
11
78
0
BNS
12
12
7
10
74
57
60
21
82
47
CIBC
13
12
19
2
104
82
150
62
73
0
Credit
Unions
1
1
53
0
0
0
0
8
19
574
Desjardins
0
0
0
0
4
1
0
0
1
0
HSBC
0
0
0
0
0
0
0
0
0
31
Laurentian
Table 1: Branch distribution by province and institution
0
0
18
2
0
0
0
0
11
147
National
12
24
15
3
59
41
62
40
95
30
RBC
3
9
7
3
29
29
24
14
80
4
TD
0
3
0
14
31
1
25
0
28
0
Other
Table 2: National Descriptive Statistics
stats
mean
sd
min
p25
p50
p75
max
pop
3378.738
6062.689
251
568
1081
3294
48821
income
22237.79
4925.904
3792
18652
21713
25077
47958
area
94.65027
189.467
.5627
4.3041
25.7586
126.2058
2961.578
Source: Statistics Canada
19
french
.2773174
.4060309
0
.0026961
.0201565
.7923169
1.033835
unemploy
12.33144
11.88778
0
5.1
8.7
16
80
Table 3: Provincial Descriptive Statistics, Part I
province
Alberta
British Columbia
Manitoba
New Brunswick
Newfoundland and
Labrador
Nova Scotia
stats
mean
sd
min
p25
p50
p75
max
mean
sd
min
p25
p50
p75
max
mean
sd
min
p25
p50
p75
max
mean
sd
min
p25
p50
p75
max
mean
sd
min
p25
p50
p75
max
mean
sd
min
p25
p50
p75
max
pop
3013.417
4907.616
252
537
1076
3538.5
47076
5586.89
6843.383
293
1113
3163
7259
35944
2429.229
5139.045
265
546
923
1672
41511
2597.217
3212.703
303
860
1404
2754
18129
1472.018
2741.331
251
387
646
1246
21966
4040.96
3301.412
444
1401
3455
5815
11765
income
25626.63
4935.564
15662
21970
25220.5
28389.5
47906
24283.36
4706.041
12292
21596
23781
26472
38984
21992.83
4525.82
3792
19687
21870
24589
34900
20723.52
3360.569
14101
18403
20993
22563
34145
17583.5
3265.015
10880
15712
17006
18675
36091
20330.76
1963.32
17771
19143
20209
20579
27443
Source: Statistics Canada
20
area
8.231355
13.12853
.5627
1.8754
3.68045
8.7404
107.9287
44.48434
63.31547
.7489
6.5456
17.9984
51.3385
277.5185
61.25539
184.5155
.9205
2.5308
3.4218
16.3862
901.8378
79.82445
95.94881
2.0005
9.0323
21.7303
179.8377
291.0376
54.31297
150.4933
1.8942
10.0474
26.0239
46.2493
1847.263
55.9986
172.2512
2.0397
4.0094
9.9258
14.8824
852.8229
french
.0260633
.0707305
0
0
.0112889
.0215403
.6028369
.0168153
.014587
0
.0083022
.015048
.0204082
.0928571
.0625076
.1401853
0
.0067568
.018226
.0365186
.7724957
.2943592
.3948442
0
.0166945
.0292969
.8230088
.968523
.0037673
.0181718
0
0
0
0
.2015678
.0627676
.1499725
0
.0100476
.0144763
.0237376
.6456372
unemploy
5.696429
5.323666
0
2.25
4.75
7.55
28
9.217431
5.597037
0
5.8
8.1
10.9
35.5
6.683133
6.081877
0
2.9
5.8
8.1
34.2
14.27246
8.999769
0
8.9
13.5
18
43.8
32.02749
16.14667
0
21.9
29.4
41.2
80
12.052
4.076878
5.7
8.7
11
15.4
21.6
Table 4: Provincial Descriptive Statistics, Part II
province
Ontario
Prince Edward
Island
Quebec
Saskatchewan
stats
mean
sd
min
p25
p50
p75
max
mean
sd
min
p25
p50
p75
max
mean
sd
min
p25
p50
p75
max
mean
sd
min
p25
p50
p75
max
pop
7750.776
9536.079
277
1209
4187
10481
48821
2157.867
6215.202
261
400
616.5
853
32174
3129.458
5832.794
252
662
1262
2717
47637
1484.495
3699.661
251
367.5
609
1078.5
34138
income
25444.17
4793.178
13941
22004
25204
28729
39947
21155.8
3430.708
15744
18294
20627.5
22920
29766
21000.06
3925.854
13243
18400
20804
23107
47958
22771.51
4729.317
6896
19429
22615.5
25844.5
41726
Source: Statistics Canada
21
area
250.7862
316.1103
1.7135
58.4281
189.2358
288.8549
2961.578
63.47348
32.77636
1.2243
44.3298
77.4602
85.0389
95.3656
152.2767
199.6155
2.5896
72.4895
118.5168
180.6543
2821.645
5.640542
11.69341
.6024
1.36785
2.5315
4.4545
121.9215
french
.0892252
.1775144
0
.0099182
.0170197
.0607601
.8243452
.0118295
.0152154
0
0
.0081223
.0191205
.0593103
.8707449
.2276045
0
.9009972
.9544271
.9770115
1.033835
.0235169
.0540373
0
0
.0082782
.0207767
.4022988
unemploy
8.347541
5.65994
0
5.2
7.3
9.8
36.6
13.20333
7.622719
0
9.1
12.45
16.7
30.2
12.76675
9.136004
0
6.8
10
16.9
50
7.416509
8.86408
0
0
5.65
10.15
45.5
Table 5: Potential Entrants by Province
Province
British Columbia
Alberta
Saskatchewan
Manitoba
Ontario
Quebec
New Brunswick
PEI
Nova Scotia
Newfoundland
Entrants
BMO, BNS, CIBC, CU, RBC, TD
ATB, BMO, BNS, CIBC, CU, RBC, TD
BMO, BNS, CIBC, CU, RBC, TD
BMO, BNS, CIBC, CU, RBC, TD
BMO, BNS, CIBC, CU, RBC, TD
BMO, CIBC, Desjardins, Laurentian, National, RBC
BMO, BNS, CIBC, CU, Desjardins, National, RBC
BMO, BNS, CIBC, CU, RBC, TD
BMO, BNS, CIBC, CU, RBC, TD
BMO, BNS, CIBC, CU, RBC, TD
22
Table 6: Competitive E¤ects
ATB
BMO
0:6892
(0:1598)
BMO
BNS
CIBC
BNS
0:8572
(0:1958)
0:2348
(0:0675)
CIBC
0:0774
(0:0141)
0:3479
(0:0768)
0:1538
(0:0409)
CU
1:2597
DESJ
NAT
(0:2053)
0:2377
0:2077
(0:0554)
(0:0511)
1:0127
0:2321
(0:0435)
0:0965
(0:2302)
0:8679
0:2508
(0:0570)
0:1760
(0:0333)
0:2574
(0:0501)
0:8653
(0:0617)
(0:1689)
0:4818
(0:1084)
LAUR
(0:1160)
(0:2129)
0:1460
DESJ
0:5481
0:5446
(0:0260)
(0:2177)
CU
LAUR
0:1301
(0:0714)
0:0812
(0:0142)
NAT
RBC
0:3419
TD
0:1089
(0:0566)
(0:0241)
0:0870
(0:0174)
0:4195
(0:1181)
0:1102
(0:0217)
0:8626
(0:2041)
0:5628
(0:1194)
0:1679
(0:0564)
0:1818
(0:0407)
0:8576
(0:3439)
0:5414
(0:1202)
0:4361
(0:0715)
0:2402
(0:0461)
RBC
0:4146
(0:0884)
23
Table 7: Other Parameters
Parameters
Intercept
Population
Income
Unemployment rate
Alberta
British Columbia
Manitoba
New Brunswick
Newfoundland and Labrador
Nova Scotia
Prince Edward Island
Quebec
Saskatchewan
National Size
Regional Size
Estimated Value
Standard Deviation
-1.4206
0.9843
0.0851
-0.3930
0.6126
0.2933
0.6723
0.7336
-0.0729
1.0439
0.0226
-0.2149
0.2414
-0.0274
0.4664
0.0948
0.1568
0.0225
0.0782
0.0713
0.0769
0.1254
0.1312
0.0158
0.2347
0.0057
0.0611
0.0423
0.0030
0.0295
Table 8: Counterfactual Scenario
Predicted
Counterfactual
ATB
57.24
57.09
BMO
319
315.71
BNS
316.72
310.13
CIBC
385.85
375.92
CU
174.12
191.92
24
DESJ
328.84
485.28
LAUR
57.64
57.64
NAT
136.09
136.09
RBC
326
312.01
TD
253.94
240.26
Figure 1: The evolution of total number of bank branches in Canada shows a steady decrease in the 1990s
and early 2000s, with a stabilization after the mid 2000s.
Figure 2: This …gure of number of entrants vs. population shows a clear positive correlation between the
two. We also see that most markets have 6 entrants or less.
25
Figure 3: Moose Jaw, Saskatchewan is one of the rural markets we have selected.
26
Figure 4: This map highlights the various bank branches in Moose Jaw, Saskatchewan. Each dot represents
a branch, and di¤erent colors represent di¤erent institutions.
27