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In markets where information is complete and symmetrically distributed among agents and where externalities are absent competition leads to Pareto optimal outcomes. 

In the case of banking services, more competition should lead to higher efficiency, higher deposit rates and lower loan rates, therefore increasing borrowers’ and depositors’ welfare (Besanko and Thakor, 1992). 

However, the existence of financial intermediaries has been since long traced back to market imperfections. In credit markets asymmetries in the distribution of information and externalities influence banks’ risk-taking behavior, their ability and their incentives to price risk correctly. 

In a number of circumstances the heightening competition can exacerbate market distortions making the welfare effects less straightforward. 

Economic theory also suggests that asymmetric information can work as a barrier to entry in credit markets and that incumbents’ market power can be to some extent shielded from outside potential competition. 

This view is supported by two main arguments. The first one is related to the possibility that once entry occurred, previously rejected applicants can apply for loans at additional banks. 

As far as borrowers’ credit-worthiness is assessed through screening procedures which are not fully revealing and are unperfectly correlated across banks, a larger number of banks rises the probability that a bad risk is considered as credit worthy by at least one of them (Broecker, 1990). 

Adverse selection is greater for new entrants because the pool of their applicants is likely to include those potential borrowers previously rejected by mature banks in the market (Shaffer, 1998). The second argument relates on the informational advantages of the incumbents on market characteristics. 

A relevant amount of information used by banks for screening loan applicants and for monitoring borrowers is generated through repeated interaction with their customers. 

Many studies, both of theoretical and empirical nature, have documented that long term relationships established between lenders and borrowers are an important feature of most bilateral credit markets (i.e. Sharpe,1990; Rajan 1992; Boot, 2000). 

A considerable amount of valuable information can be acquired only on a market specific “learning by doing” basis, thus implying that incumbents’ credit-worthiness tests may well be more precise than those of the entrants. 

Empirical evidence on the link between entry and default rates of the loans extended by the entrants is scarce. Several episodes of banking crisis around the world have been directly or indirectly related to the lifting, or relaxation, of the constraints imposed by regulation. 

Demirguc-Kunt and Detragiache (1998), analyzing a sample of 53 countries, show that financial liberalization rises the probability of a bank crisis. Caprio and Klingebiel (2000) document a recent increase in the frequency of bank crises and argue that it is at least partially due to the lifting of structural controls. 

Pesola (2001) finds that market liberalization had a substantial role in the bank crisis experienced by the Scandinavian countries during the early 1990s. 

To our knowledge, Shaffer (1998), which is very close in spirit to our paper, is the only study that empirically tests the winner’s curse hypothesis, i. e. the idea that entrants in a credit market are forced to assume too much risk because their pool of borrowers is adversely selected. 

This paper contributes to the subject through an empirical study of the Italian outburst of bad loans in the early 1990s. The 1992-93 recession caused an unprecedented upsurge in non-performing loans followed by severe losses for a large number of banks. 

Thanks to a unique database on loan default rates made available by the Italian Central Credit Register, we investigate individual banks’ loan default rates in each local market. The regulatory reforms introduced in the late 1980s allowed a substantial increase in the number of banks operating in each local market (here defined as a province). 

We distinguish between two different ways in which a bank enters a local market. The first one consists of extending loans from branches or the headquarters outside the local market. The second one is by directly opening of branch. 

We argue the two types of entry differ substantially with respect to the information gap vìs a vìs the incumbents. Having on site branches allows banks a more rigorous monitoring of the borrowers and a better understanding of the local economy. 

Moreover entry with branches is usually anticipated by entry with loans extended from outside. Consistently with the predictions of the theory we find evidence that entrants are more exposed to bad loans than the incumbents, since they have to deal with the backlog of previously rejected applicants. 

The consequences of entry on the loan default rate vary with the level of information. Those banks entered with relatively more information, i.e. by opening a branch, experienced a lower default rate than those entered without branches. 

The negative consequences for the entrants are less severe when markets are characterized by a high level of banks’ customers turnover. According to our data there is also a positive relation between the loan default rate and the number of banks operating in a market, as predicted by the winner’s curse hypothesis. 

As a general result, we find that the suboptimal effects of entry on loans quality are mitigated when entrant banks belong to the top performers of the industry. Borrowers of well capitalized, efficient, and aboveaverage profitable banks are characterized by substantially lower default rates. 

 The remaining of this paper is organized as follows. In Section 2 some theoretical and empirical contributions in this field are surveyed. In section 3 we illustrate our empirical specifications, while in Section 4 we discuss our data and explain how the relevant variables have been constructed. Results are presented in Section 5 and section 6 draws the conclusions.

Related literature

The possibility that an increase in competition in the banking industry may have sub-optimal allocative effects has been recognized since long, but only recently the argument has been cast in formal models. 

The backbone of most of them is an application of the theory of common value first-bid auctions (Milgrom and Weber, 1982). 

When banks compete in prices (i.e. interest rates) and have an imperfect knowledge of the would-be borrowers’ ability to repay their debts, they face an externality caused by the decisions of the other banks. 

Before granting a loan a bank needs to assess the creditworthiness of the applicant. The screening procedure may be thought as a not fully revealing test of the quality of the applicant. Conditional on the result of the test the bank offers an interest rate or denies credit. 

The borrower chooses to sign the credit contract with the bank that offers the lowest interest rate. If the tests run by different banks are not perfectly correlated, there is a positive probability that an applicant’s credit-worthiness is assessed differently by different lenders. 

This implies that probability that a high risk borrower is assessed as credit-worthy is positively correlated with the number of tests that are run. 

It follows that the average quality of the pool of borrowers that obtain a loan (and consequently the expected losses from bad loans) declines (increases) as the number of banks in the market increases. This idea has been formalized by Broeker (1990) using credit-scoring tests with binary outcome. 

Competition is modeled in two different ways - as a one-stage game and as a two-stage game - obtaining different results concerning the existence and the characterization of the equilibrium solutions. 

In both cases the intuition that an increase in the number of banks may have negative effects on the average ability to repay the loan of those who are granted credit holds true. A similar result was obtained by Riordan (1993) in a model where banks are able to run credit-worthiness tests delivering continuous signals. 

An increase in the number of banks rises the threshold value of the signal above which the loan is granted, but this effect can be offset by the increase in the probability that at least one bank observes a “high quality” signal screening a “low quality” applicant. 

In Riordan’s model the entry of new banks into a credit market is associated with a more restrictive supply stance. For a non trivial set of parameters also the equilibrium default rate in the market is positively correlated with the number of active banks. 

This basic framework has been extended by several papers. Gehrig (1998) allows the banks to choose the precision of their binary credit-worthiness test and models the integration of two previously separated credit markets as a sequential entry game and as simultaneous duopoly. 

In the first case entry, if it ever occurs, doesn’t have any effect on the incumbent’s screening intensity choice, while the entrant, facing an adversely selected pool of applicants, substitutes a less accurate screening with higher interests rates. 

As auction theory has recognized since long, additional insights may be gained when information about the value of the object being sold is asymmetrically distributed among participants (Wilson 1967, 1977). 

Dell’Ariccia et al. (1999) analyze an entry model where the incumbent has an informational advantage on the entrant since he has a long-term relationship with part of his customers. This advantage is greater the lower is the customers turnover in the market. 

They characterize the equilibrium under Bertrand duopoly and show that the adverse selection of the borrowers’ pool causes entry to be blockaded. Marquez (2002) proposes a two periods model assuming that borrowers’ characteristics are observable by banks only once a loan has been granted and that there is some turnover among borrowers. 

In the second period banks will refuse to continue financing borrowers revealed to be bad. Since information is proprietary, these borrowers remain as part of the pool of customers unknown to all other banks. 

In this framework an increase in the number of banks disperses borrower-specific information reducing banks’ screening ability. Incumbents’ informational advantage may also act as a barrier to entry if borrower turnover is low. 

 The role of relationship lending in magnifying entrants’ vulnerability has been extensively studied. Relationship lending generates informational rents accruing to the banks from which “captured” firms can try to escape searching for better deals in the credit market. 

Sharpe (1990) has shown that if an uninformed outsider bank offers a competitive interest rate (e.g. reflecting the average credit quality), only bad borrowers would prefer to switch.

The information asymmetries on the same side of the market (the supply side) induced by relationship lending is therefore most likely to add to the adverse selection problems faced by a new entrant banks (Nakamura, 1993).

Furthermore, when assessing the credit worthiness of a loan applicant, banks usually refer to their past experience with similar borrowers in similar markets. This may imply that when a bank expands in a new market or sector the negative effects of a lack of expertise may overcome the benefits from risk diversification (Winton 1997). 

Comparing with the abundance of theoretical papers on the subject, the empirical work has been rather limited. Shaffer (1998) tests empirically the prediction that de novo banks should suffer higher loan losses due to the adverse selection effect. 

He considers all U.S. commercial banks during the period 1986-1995 and regress the net chargeoff ratio versus annual age dummies for each of a bank’s first 10 years, controlling for business cycle and other macroeconomic effects including quarterly calendar time dummies. 

He finds that the net chargeoff rates are strongly and significantly higher from year 3 on. After discussing alternative explanations of this pattern (such as the seasoning of a new portfolio or the presence of a learning process of an inexperienced lender), he concludes that adverse selection appears the main cause of the observed phenomenon. 

Shaffer also estimates a cross sectional model using data from mature banks, each operating in a single geographic market (MSA). He finds a strong positive linkage between gross chargeoff rates and the total number of banks in each MSA. 

Hedricks and Porter (1988) investigate the links between the winners’ curse and asymmetric information among bidders in auctions. They show that in equilibrium the uninformed buyer makes zero profits, while the informed buyer makes positive profits thanks to its superior information. 

They also test these theoretical conclusions examining data from the federal offshore oil and gas drainage lease sales finding that both types of buyers actually behave consistently with the Bayesian-Nash equilibrium.
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