2012 Angelo Leogrande Cooperative Banks vs Financial Crisis

8/10/2019 2012 Angelo Leogrande Cooperative Banks vs Financial Crisis

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COOPERATIVE BANKS VS FINANCIAL CRISIS:

AN APPLICATION OF THE STV VS. SHV DEBATE

ABSTRACT

The Great Financial Crisis of 2007-09 makes an interesting case study to test the shareholder vs.

stakeholder debate in banking and finance. The hegemony of shareholder value maximization in the

financial community showed its weaknesses being a factor in destroying the common good of

financial stability. While shareholder value maximizing (SHV) organizations appear to have greatly

contributed to the financial crisis, stakeholder value maximizing (STV) ones seem to have

continued assuring credit, mortgages, financial services and financial sustainability to communities.

In this paper we use probit and tobit models to test whether the probability of a country being in

crisis in 2007-09 and the associated costs related the extent of the presence of Cooperative Banks

taken as a proxy of STV organizations in the country. We start with the model of Caprio et al.

(2010) introducing a new variable that is the percentage of the total assets of Cooperative Banks on

the total assets of the national banking system. The database that we constructed from Bankscope

features 83 countries containing data for 20,000 banks among Commercial Banks, Cooperative

Banks, Bank Holding Companies, Investment Banks, Savings Banks. We find that the higher the

percentage of Cooperative Banks total assets, the lower the probability of crisis. Through the tobit

estimates, we also show that the costs of the crisis negatively relate to the extent of Cooperative

Banks assets. Thus, Cooperative Banks appear to have reduced both the probability of suffering the

crisis and, in the event, its consequences. This is in line with the virtues of biodiversity in banking.

JEL Classification: G0; G01; G14; G15; G18; G21; G20; G24; G28; G30; G32.

Keywords: Governance; Financial Crisis; Banking Crisis; Government Intervention; Regulation; Economic Institutions

and Organizations; Financial Constitutional Economics, Shadow Banking System.


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1. INTRODUCTION

The Great Financial Crisis of 2007-09, the subprime mortgage crisis, materialized under the

hegemony of the shareholder value maximization (SHV) model through financial institutions and

organizations! (Deakin & Floor, 2010; Ingley et al. 2011; Hellwig, 2009). Different kinds of

financial intermediaries, Banks, Insurance Companies, Mortgages Institutions", have pursued a

corporate governance model based on SHV generating strong connections between credit and

financial markets# increating systemic risks forcing the policy makers to apply the Too big too

fail paradigm (Bullard et al., 2009 ) and financing the shadow banking system ( Gennaioli et al

2012). The hegemony of the SHV model was part and contributed to produce several modifications

in the banking business: i) a change in the credit management model from Originate-to-Hold (OTH)

to Originate-to-Distribute (OTD; Berndt & Gupta, 2009; Bord & Santos, 2012); ii) a change in

credit management model from relationship banking to transaction banking (Berger e Udell 2002) ;

iii) improving the importance of the bank-lending channel for the transmission of monetary policy

(Cavalcanti, 2009; Bernanke, 2007; Disyatat, 2011 ); iv) a change in the evaluation of credit risks

1In this paper we use the term institution referring to norms, behaviors, best practices and ethical codes working asrules of the game (North, 1990), while the term organization refers to the players of the game constitutionally

founded on these institutions and using them in the game. For example, corporate governance models are institutions

while financial intermediaries are organizations. The distinction between financial institutions and organizations lets us

investigate the reasons of inefficiency and mal-function in the financial constitution of the economic order.2We must consider that the set of financial organizations and institutions features a high degree of heterogeneity.

Financial organizations include Banks, Insurance Companies, Government Banks, and also Financial Markets.

Financial institutions count different economic orders based on financial constitution, for example differentiated on thebasis of their legal origin as in the Legal Origin Theory, and within a single economic order it features different kinds of

financial and banking laws defining obligations, degrees of freedom and geographical and social mandates of financial

organizations. But, despite the heterogeneity of financial organizations and financial institutions, the unique model of

corporate governance based on SHV theory exercised by global financial governance established its hegemony(Gramsci, 1936). Through this Hegemony global financial governance has changed the meaning of the financial

constitution of the economic order and the management of the financial organizations contributing to the crisis. Only

few kinds of financial institutions and organizations resisted this hegemony, such as cooperation and Cooperative

Banks, Savings Banks, Credit Unions, Micro-credit Intermediaries. These financial institutions and organizations are

the pillars of the embedded stakeholder value (STV) maximization.3A great part of the economic literature (Kindleberger, 1978; Minsky, 1982; Galbraith, 2009) studies the causal relation

between the growth of the credit borrowed from financial intermediaries to financial intermediaries and financial

markets and the manifestation of a financial crisis. When the financial system uses credit to generate credit without

connection to the real economy, households, public administrations, socially oriented organizations and firms, theprobability of a financial crisis grows approaching the value of 1. The SHV theory has offered the accounting meta-

narrative to strengthen the establishment of credit from financial intermediaries to financial intermediaries and financial

markets.


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from relationship lending to credit scoring with a reduction of informational capital (Petersen,

2004; Diamond, 1984 and 1989; Boot and Thakor, 1994) ; v) a change in the accumulation

procedure of reputational capital from long-run multi-relationships with economic counterparts in

the community to credit rating agencies especially for SMEs (Mariano, 2012; Moro & Fink, 2013),

and vi) a change in the dynamic of perspective from a long-run perspective to shortermism%(World

Bank, 2008) through commercial papers and short term debt (Rappaport, 2005, Diamond & Rajan

2001, 2005 and 2009).

The debate between Stakeholder and Shareholder has been reported also in banking (Freeman ,

2010; Coyne, 2011). Stakeholder oriented banks apply originate to hold credit management model

(STH-OTH) developing multiple long-run relationships with households and firms (Slovin et al.

1993, Cornell & Shapiro, 1998), performing an ethical banking governance (Wijnberg, 2010),

producing hard and soft information (Stein, 2002), endogenously evaluating the reputational

capital&of the borrower.

On the other side we have Shareholder oriented banks applying the originate to distribute credit

management model (STV-OTD) related with credit scoring, hard information and securitization

(Rajan et al. 2008;, Efraim, & Dlugosz. 2008) and shadow banking system generating financial

instability and financial crisis ( Zamagni, 2006 and 2009). SHV-OTD due to their profit orientation

have undervalued the systemic risk related to the securitization of mortgages ( Raghuram G. Rajan,

2005; and Anil K. Kashyap, Raghuram G. Rajan, and Jeremy C. Stein, 2008).

All these modifications were justified by the SHV-OTD model offering the meta-narrative (Eiter,

1997) for these more speculative and sometimes even irrational behaviors increasing systemic

risk and producing the Great Financial crisis.

4The short-term temptation is an old question in the economic debate (Hayes and Abernathy,1980; Laverty, 1996).

5We can observe a change from endogenous reputational capital to exogenous reputational capital. In the first case the

reputational capital arises for the fact that organizations respect institutions in the long run and they are re-paid by their

counterparts by gains in reputational capital. In the second case reputational capital is accumulated through externalcertification offered by a third subject in respect to parties that assign rankings offered to counterparts. An example of

endogenous reputational capital is offered by the relationship banking. An example of exogenous reputational capital is

offered by credit rating lending.


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Maximizing the value of shares in the short-run (Gaspar et al., 2005) has created a new paradigm in

financial contracting based on shortermism (Rappaport, 2005) that reduced the propensity of

financial organizations to build the future through investment'.

Financial intermediaries have phased out constitutional financial institutions infringing their public

mandate to offer solution to classical market failures and have started to concentrate their effort in

the corporate value function strictly based on the actualization of SHV maximization generating a

more unstable banking model ( Shleifer& Vishny, 2010) .

The strict relationship between financial crisis and the SHV-OTD paradigm has been largely

showed in the economic literature and in the chronicles of the Great Financial Crisis (Purnanandam,

2009).

In this paper we concentrate our analysis on the relationship between stakeholder value

maximization (STV) financial intermediaries and the Great Financial Crisis of 2007-09. In

particular, we ask whether the presence of Cooperative Banks played a role in reducing the

probability of suffering the Great Financial Crisis of 2007-09.

We start our analysis from the paper of Caprio et al. (2010), where the authors investigate the

relationship among financial and banking regulation and the probability to be in crisis in 2007-09.

We focus on some of the Caprio et al.s variables introducing a variable that captures the percentage

of total assets of Cooperative Banks in the national banking system.

Our research question is related to the debate on STV vs. SHV in banking and finance. Cooperative

Banks have an STV oriented management and control and this enforces their ability to work for the

community(.

6The relation between saving and investment is one of the main ideas at the foundations of macroeconomics. Indeed,

since Keynes (1936), economists have based their macroeconomic analysis on this relation defined as an identity. But

financial contracting has introduced a third element in this equation. Saving and Investment differ from the value of the

saving that is borrowed in the financial markets in non-investment assets such as securitization. This new element, thatis produced as financial innovation, breaks the identity of saving and investment and produces distortions and risks that

regulators and intermediaries are not able to tackle and that, when increasing their assets, can create a financial crisis.7In particular, we can refer to Cooperative Banks as Embedded STV organizations since in these organizations the STVtheory is not exogenously affirmed in their statutory mandate, and in their corporate governance model. In these case

STV theory is embedded in the constitutional mandate and functioning of Cooperative Banks. Other kinds of Banks,

such as Commercial Banks, can use corporate social responsibility codes but in this case they approach STV from a


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Cooperative Banks have statutory obligations that impose a one head one vote rule for voting in

the assembly and a social mandate in the exercise of banking business.

The STV orientation of Cooperative Banks) is juxtaposed to the SHV orientation of Investment

Banks*, Commercial Banks and Bank Holding Companies.

Our research question relates to evaluating the STV orientation in banking and finance.

The economic behavior of STV oriented financial institutions and organizations has been more

virtuous than that of SHV oriented financial institutions and organizations (Beltratti & Stulz, 2011).

In fact, embedded STV organizations are less prone to securitize, to adopt the OTD model, to

financing speculation, and asset-price-bubbles. STV banking and finance focuses on relationship

banking, and OTH enforcing the relationship with communities (Groeveneld & Vries, 2009). STV

oriented financial organizations develop a more sustainable model (Coco & Ferri, 2010). Due to this

theoretical base we have investigated whether more STV oriented countries from the point of

view of their financial constitution were less prone to the Great Financial Crisis (Allen & Gale,

2000).

The Great Financial Crisis at an operational level has been created by the OTD model,

securitization and the strengthening of the finance-credit nexus through the hegemony of the SHV

theory. This hegemony has been implemented by Commercial Banks, Investment Banks, Bank

Holding Companies, while Cooperative Banks generally have a differentiated corporate governance

model based on OTH, relationship banking and more socially oriented business. We have shown

that the more the banking system was STV oriented in the period 1998-2006 the lower was the

probability to suffer the Great Financial Crisis of 2007-09. This seems to show that the banking

SHV orientation. In this case STV maximization is not embedded in the institutional building of financial organization

but its just a tool in a SHV based financial organization.8We have used Cooperative Banks as a proxy for all the STV oriented banking and financial institutions and

organizations. During the years the number of STV oriented institutions and organizations in banking and finance has

been increasing. We must consider not only Cooperative Banks but also Savings Banks, Government Banks, and Micro-finance and Micro-credit organizations, and never forget to mention the economic organizations devoted to the

reduction of financial exclusion.9We know that many of these banks have the skills to pursue socially oriented objectives. Some of them have adoptedrules based on corporate social responsibility and ethical codes devoted to humanitarian ends. But this kind of

normative legislation, as a simple fact, is not sufficient to code these banks as STV oriented. Economists, managerial

scientists and business ethicists address the nexus between corporate social responsibility and STV management.


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model of Cooperative Banks is sustainable and actively participates to financial stability (OHara,

1981; Esty, 1997; Fraser & Zardkoohi, 1996).

We have used data based on the paper of Caprio et al. (2010) and data from Bankscope for the total

assets of Cooperative Banks, Commercial Banks, Investment Banks, Bank Holding and Savings

Banks from 1998 to 2006.

The paper is divided as follows. In the second section we present a brief literature review where we

tackle the question of the importance of cooperation in economic games, in which we connect

cooperation with managerial models in banking and finance stressing the macro financial influence

of the banking governance. In the third section we focus on methodology illustrating the strategy

that we have taken to model the econometric technique that we have implemented. Here, we also

illustrate the database and show the results obtained. The fourth section contains our conclusions.

2. LITERATURE REVIEW

In this section we present a brief literature review relative to the topics directly connected with our

research question: the relation between Cooperative Banks and Financial Crisis as a case in the STV

vs. SHV debate. While the Great Financial Crisis has been created by the hegemony of SHV

financial organizations, Cooperative Banks are considered to be a proxy of STV oriented financial

organizations (Freeman, 1984). The first thing to recall is the fundamental importance of

cooperation in economics. In particular, economists such as North have developed a theory of

institutional building based on cooperative behavior. In Norths theory cooperative behavior is a

tool to solve market failures produced by asymmetric information and shortermism. In the theory of

North cooperative behavior has the ability to impede free riding and by this way to develop a

mechanism to build the common good of confidence. Cooperative behavior has the ability to solve

market failures and, at the same time, to develop institutions based on long-run perspective.


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The efficiency of cooperation has been showed in the repeated game theory both theoretically and

empirically (Axelrod, 1984; 1986; 1987; 1997). The use of cooperation!+ in banking and finance

has important effects on financial stability (Beck et al., 2009). The transformation of individual

risks into systemic risk is more difficult in the case of cooperative banks in which their statute and

economic organization strictly connect to their social mandate (Fonteyne, 2007). In this sense we

have referred to cooperative banks as embedded STV governance!!organizations.

Defining the Cooperative Banks Governance as Embedded Stakeholder Governance, gives us the

possibility to consider the connections between Cooperative Banks and Financial Crisis interlinking

the theory of economic cooperation, the economics of banking and finance, and the governance

modeling in managerial science.

STV banks suffered less the Great Financial Crisis. In particular, some studies show that

cooperative banks may develop a more sustainable lending model (Coco & Ferri, 2010).

Cooperative banks!" have a model of ownership that is egalitarian based on one head one vote

(ICA, 1995; European Commission, 2001). At the same time they have the ability to develop more

socially oriented business (EACB, 2004). Their legal statutory mandate, their ethical codes and the

STV oriented governance produce positive effect on economic development, economic growth,

reducing financial exclusion!#, improving the value of entrepreneurial human capital with long run

banking relationships and horizons (Rajan, 1994), and being active part of the soft power locally

10We know that we cooperative banks are only one kind of economic organizations working on the side of cooperativebehavior in banking and finance. Other organizations can implement cooperative behavior even if they are not

cooperative in their statutory mandate.11We have developed the definition of Embedded STV Governance from the definition of embedded liberalism that

we have discovered occasionally and fortunately (Ruggie, 1982). In effect as in the definition of embedded liberalismwe have considered what are the institutions and the organization for which STV theory is not an approach, or an ends,

or an orientation, but it is a constitutional mandate inspiring the exercise of governance. In this sense we can distinguish

Embedded STV Governance from Governance STV Oriented where STV is an approach that can be affirmed in the

SHV organizations.12We can accept the proposition of Nobel Prize Yunus (Yunus, 2010) in which he considers the possibility that

cooperative banks can be under a free riding attack. In the sense that it is possible that people in cooperative banksrealize unethical oriented behavior de facto misapplying the constitutional mandate of cooperative banks. But this case

is strongly related with the corruption of the social environment that depreciates the value of human capital. In this case

we have free riding oriented cooperative banks in which the statutory mandate of cooperative banks can be perverted.13The reduction of financial exclusion is one of the pillars in the ethical foundation of cooperative banks recalling to

our mind the Latin adage Homo sine pecunia est imago mortis. The goal of reducing financial exclusion is pursued

especially due to Cooperative Banks local ethos (De Bruyn & Ferri, 2005).


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defined in exercising governance (Brazda & Schediwy, 2001). Cooperative Banks become active

part of economic change. Cooperative banks, as mutual banks are less prone to take risk (Chaddad

& Cook, 2004; Gurtner, Jaeger & Ory, 2002; Fama & Jensen, 1983, Cannari & Signorini, 1997).

The embedded STV governance of Cooperative Banks affects positively the common goods of

financial stability (Cihk & Hesse, 2007), and economic development and growth even at a local

level (Cosci & Mattesini, 1997; Usai & Vannini, 2005). Cooperative Banks produce financial

sustainability. This ability of Cooperative Banks to produce financial stability is showed both

theoretically and empirically. Theoretically it has been showed that cooperation has the ability to

solve market failures and this per se produces economic equilibrium overcoming the

microeconomic foundation of market failures caused by asymmetric information (Hansmann,

1996). Empirically, it has been demonstrated that Cooperative Banks are less prone to take risks, are

characterized by long-term horizon. Cooperative Banks have the ability to collect both explicit and

implicit information. In particular, on the theoretical point of view Cooperative Banks have the

possibility to solve the agency problem through the collection of explicit and implicit information

building confidence (Kay, 2006). Cooperative Banks have the economic and constitutional mandate

that cast them economically and socially in the role of producing economic sustainability as well as

participating actively to the financial stability building (Ayadi et al., 2010).

Another important implication of the STV oriented banking and financial organizations is

implementing the OTH model in credit management. Originate to hold is a model of credit

management that is based on the practices to generate credit, holding it until maturity. Credit

holding and relationship banking are strictly related.But in the mutation of financial globalization

during the late 1990s and the early years of the new decade OTH has been substituted by OTD

through securitization. The passage from OTH to OTD has been a passage from monitoring based

on implicit information to monitoring based on explicit information collected by credit scoring. This

passage from OTH to OTD has been justified in the interest of SHV maximization. The hegemony

of SHV maximization theory has offered the meta-narrative for the exercising of a financial market


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oriented banking governance that through securitizations, financial innovations and risks sharing

has produced the Great Financial Crisis. Many economists and policy makers are calling for a return

to more traditional banking (De Grauwe, 2008; Group of Thirty, 2009; de Laroisire, 2009).

The change from OTH to OTD has created a multiplication of un-hedged risks and the

libertarization!%

of financial markets based on non-regulated financial markets has generated the

worst financial Crisis since that of 1929.

Particularly, we can say that the Great Financial Crisis has been aggravated by an approach in

which the traditional relationship banking model based on OTH has been discontinued. On the

contrary, embedded STV Governance in Cooperative Banks produces administrative methodologies

based on relationship banking (Kay, 1991). Relationship banking is the traditional way of doing

banking that is a long track in the history of capitalism!&.

Cooperative Banks generally apply relationship banking. Relationship banking is a model in which

banks hold long-run relationships with firms, households, and constituencies. These long-run

relationships put the bank in the position to have more information about the borrower (Ghatak,

2000). Having more information is a strategy to reduce the risk generating long-run relationships

that reinforce the role of the bank in the community and gives confidence to the community. The

relationship banking model has the ability to develop relational capital, confidence and, by this way,

it is a model to produce common immaterial goods that can sustain economic growth (Alexopoulos

and Goglio, 2012).

14In this case we want to distinguish between liberalization and libertarization. In classical liberalism (e.g. Smith, Mills)

there is the idea that markets should have some public control exercising a defense to small enterprises operating to

solve market failures, while in classical libertarianism the idea of the State as an active economic subject removing

market failures conditions is completely absent.15

Indeed, we can say that the economics of banking, insurance and financial services is pre-capitalist. In particular, thehistory of banking shows us that relationship banking is the rule in the development of financial economics during the

ages. The positive effect of relationship banking on the efficiency of banks is showed in the reduction of the cost of

factoring, in reducing the risk of failures of counterparts, and in reinforcing the stability of the bank and the presence ofthe bank in the community. So we can say that relationship banking is the classical model of banking exercising

positive effects in management, in the promotion of the banking business and in the social acceptance and reputation of

the banks as economic organizations.


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3. METHODOLOGY

To estimate whether the increasing importance of Cooperative Banks total assets did affect the

probability to suffer the Great Financial Crisis, we have used a probit model putting the value of 0

when the country was not in crisis in 2007-09 and a value of 1 otherwise. We have data on 83

countries in their mean value from 1998 to 2006. Our model is based on a cross section analysis.

We have collected these data by using the database of Caprio et al. (2010), that of La Porta et al.

(1998) and adding new information drawn from Bankscope.

In our cross country analysis we have taken into consideration the mean value of each independent

variable form 1998 to 2006. This could be criticized in the sense that mean values are unable to

capture the dynamics of the change of each variable. If this kind of critique can in a certain sense

produce a sort the skepticism on the methodology used in this paper we can say, on the other side,

that the representative characteristics of the mean as statistical entity are perfectly working. This

lets us infer about some generality of our proposition. Indeed, if we lose some information about the

dynamics of the financial phenomena, on the other side we have the ability to produce a more

general rule due to the statistical properties of the mean value. In particular, taking the mean over an

extended nine-year period reduces the extent of errors in measurement of the exogenous variables.

Although our analysis is based on the paper of Caprio et al. (2010), we have used different variables

from that paper. In line with the model of Caprio et al. (2010) our dependent variable (Table 1) is:

CRISIS= dummy equal to 1 if the country is classified as either borderline crisis or systemic crisis

by Laeven and Valencia (2010) and 0 otherwise. The average value of this variable is 0.23

with a standard deviation of 0.42.

We employ a wide set of independent variables (Table 2) to take into account the various

characteristics of the national financial systems, such as, for example, the banking efficiency,


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stability, profitability, the market structure and the regulation!'

. In particular, we use the following

banking indicators:

CONCENTRATION = annual mean of the asset value of the three largest banks as a share of assets

of all banks, from 1998 to 2006 (source: Beck et al., 2000). The average of this variable is

67.4% with a standard deviation of 18.9%.

CREDIT/DEPOSIT= annual mean of the ratio of loans to deposits from 1998 to 2006 (source: Beck

et al., 2000)!(. While a high loan/deposit ratio indicates high intermediation efficiency, a

ratio significantly above one also suggests that private sector lending is funded with non-

deposit sources, which could result in funding instability (see Beck et al., 2000; Merrouche

and Nier, 2010)!). The average of credit deposit ratio is 102.2%, with a standard deviation

of 38.6%.

ROA= annual mean of return on assets (net income to total assets) from 1998 to 2006 (source: Beck

et al., 2000). The average ROA is 1% with a standard deviation of 1.1%.

RESTRICTION = mean value of the Overall Restrictions index reported in the three surveys by

Barth et al. (2004). This index measures the degree to which banks face regulatory

restrictions on their activities in: (a) securities markets, (b) insurance, (c) real-estate, and

(d) owning shares in non-financial firms. The index can take values from 0 to 4 for each of

these four sub-categories, where 4 indicates the most restrictive regulations on this sub-

category of bank business. Thus, the index of overall restrictions can potentially range

from 0 to 16. Its average value is 7.4 with a standard deviation of 1.7.

16Our database provides aggregate (that is country-level) information on all countrys banks and not just on larger

banks.17This variable only includes customer deposits and does not include interbank deposits.18The ratio of credit to deposit measures how much non-deposit funding is used to increase domestic credit. These

alternative sources of funding include short-term debt (e.g. commercial paper and asset-backed commercial paper) andlong-term debt (e.g. bonds). Though desirable, a breakdown of funding into short-term and long-term instruments is not

available even from International Monetary Fund, such as International Financial Statistics, or from international bank-

level databases, such as Bankscope (see Huang & Ratnovski, 2009).


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BANK Z-SCORE = annual mean of bank z-score from 1998 to 2006 (source: Beck et al., 2000).

The z-score is the ratio of return on assets plus capital-asset-ratio to the 5-years standard

deviation of return on assets. A higher z-score indicates that the bank is more stable,

therefore, this index can be seen as the inverse of the probability of insolvency. Its average

is 11.3 with a standard deviation of 6.6.

CAPITAL= mean value of the Capital Regulation index reported in the three surveys by Barth et

al. (2004). This index includes information on (1) the extent of regulatory requirements

regarding the amount of capital banks must hold and (2) the stringency of regulations on

the extent to which the source of funds that count as regulatory capital can include assets

other than cash or government securities, borrowed funds, and on whether the

regulatory/supervisory authorities verify the sources of capital. Large values indicate more

stringent capital regulations. The index can be considered as a proxy of Basel Pillar 1. The

average value of CAPITAL REGULATION is 6.2 with a standard deviation of 1.5.

SUPERVISION = mean value of the Official Supervisory index reported in the three surveys by

Barth et al. (2004). This index measures the degree to which the countrys commercial

bank supervisory agency has the authority to take specific actions. It is determined by the

information provided on the following features of official supervision: (1) does the

supervisory agency have the right to meet with external auditors about banks? (2) are

auditors required to communicate directly to the supervisory agency about elicit activities,

fraud, or insider abuse? (3) can supervisors take legal action against external auditors for

negligence? (4) can the supervisory authority force a bank to change its internal

organizational structure? (5) are off-balance sheet items disclosed to supervisors? (6) can

the supervisory agency order the bank's directors or management to constitute provisions to

cover actual or potential losses? (7) can the supervisory agency suspend the directors'

decision to distribute: a) dividends? b) bonuses? c) management fees? (8) can the


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supervisory agency supersede the rights of bank shareholders-and declare a bank

insolvent? (9) can the supervisory agency suspend some or all ownership rights? (10) can

the supervisory agency: a) supersede shareholder rights? b) remove and replace

management? c) remove and replace directors? The official supervisory index has a

minimum value of 0 and a maximum value of 14, where larger numbers indicate a greater

power. It can be seen as a measure of Basel Pillar 2. The average value of this index is 10.9

with a standard deviation of 2.3.

INT_DEBT_ISS_GROSS_GDP = annual mean of the gross flow of international bond issues as

percentage of GDP, from 1998 to 2006 (source: Beck et al., 2000). This variable measures

the degree to which a countrys financial system is interlinked with international financial

markets. Its average value is 21.9% with a standard deviation of 25.8%.

We augmented this model with a new variable named COOPERATIVE_BANKS defined as:

COOPERATIVE_BANKS= percentage annual mean of total assets of Cooperative Banks on the

sum of total assets of Cooperative Banks, Commercial Banks, Investment Banks, Bank

Holding Companies, Investment Banks. The mean of this variable is 0.1636 with a

standard deviation of 0.1633.

So our model (Table 3 reports pairwise correlations; Table 4 shows descriptive statistics of the

variables) is defined in this way:

Pr(CRISISi)= !+1COOPERATIVE_BANKSi+2CONCENTRATIONi+3CREDIT/DEPOSITi

+4ROAi +5RESTRICTIONi+5PRIVATE MONITORINGi+5BANK Z-SCOREi+6

SUPERVISIONi+ INT_DEBT_ISS_GROSS_GDPi+ "i,

3.1DATA AND THEORETICAL MODEL


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The data have been taken from 3 sources: from the database of the paper of Caprio et al. (2010),

from the Bankscope database and from the paper of La Porta et al. (1998). In particular, we have

taken from the paper of Caprio et al. (2010) the variables related to the international financial

regulations and banking activities. We have taken this model as our reference point since it is

devoted to the analysis of the relationships among financial regulations, banking business and the

financial crisis. This model offers a sound basis for our research question relative to the evaluation

of the impact of Cooperative Banks on Financial Crisis based on both the theoretical framework as

well as on the contemporary development of the international political economy. We have taken

data from La Porta et al. (1998) relative to Legal Origin, using dummy variables for French Legal

Origin countries, German Legal Origin countries, UK Legal Origin countries and Socialist Legal

Origin countries that we have used to instrument the probit model verifying the exogeneity of the

Cooperative Banks variable. From the Bankscope Database we have taken data relative to the total

assets of Cooperative Banks, Commercial Banks, Investment Banks, Bank Holding Companies and

Saving Banks!*

.

Following the white rabbit of the relationship among Cooperative Banks and Financial Crisis, we

have modified the model of Caprio et al. (2010) in two ways: introducing a new variable and

dropping others. Specifically, we introduced a new original variable, i.e. Cooperative Banks that we

have computed based the Bankscope database. The other variables taken from Caprio et al. (2010)

are: Return on Assets (ROA), Bank Z-Scores, Supervision and INT_DEBT_ISS_GROSS_GDP,

measuring the annual mean of the gross flow of international bond issues as percentage of GDP. We

have done these modifications to better answer our research question. In particular, we have

dropped NET_INTEREST_MARGIN from Caprio et al. (2010) since there is in a certain sense an

effect of substitution between NET_INTEREST_MARGIN and COOPERATIVE BANKS due to

19We know that the Bankscope database classifies different kinds of financial organizations, for example Government

Banks, Mortgage Banks, Insurance Companies and similar. But we have concentrated our attention on the traditional

banking sector putting it in relation with the Great Financial Crisis. Indeed, we have considered only private bankingorganizations excluding Government Banks, and on the other side we have considered pure banking organizations

excluding for this reason Insurance Companies. We are aware that the set of private banking organizations is a subset of

the set of banking organizations while the set of banking organizations is a subset of the set of financial organizations.


15/35

the fact that Cooperative Banks have generally high level of NET_INTEREST_MARGIN in their

balance sheet as direct manifestation of the embedded STV maximization. So, for this reason, we

have considered the contemporaneous presence of these two variables as redundant. At the same

time we have introduced new variables ROA, BANK Z-SCORE, SUPERVISION and

INT_DEBT_ISS_GROSS_GDP in the original model of Caprio et al. using them to explain the

relationships between Cooperative Banks and Financial Crisis through variables explain banking

returns and financial regulation on 83 countries.

Pr(CRISISi)= !+1COOPERATIVE_BANKSi+2CREDIT/DEPOSIT i+3

CONCENTRATIONi+4RESTRICTIONi +5PRIVATE MONITORINGi+5ROAi+5BANK

Z-SCORE i+6SUPERVISIONi+ INT_DEBT_ISS_GROSS_GDPi+ "i,

Our theoretical model has the right variables developed in the economics of banking for the

evaluation of the banking performance and we have the ability to test it econometrically thanks to

the data collected we have the possibility to test it econometrically.

3.2RESULTS

We have found a statistical significance of the importance of Cooperative Banks in being negatively

associated with the Financial Crisis of 2007-09.

To address the problem of exogeneity, we use the instrumental variable probit, instrumenting for the

legal origins of the country. Performing the Wald test of exogeneity we have found that the variable

of our interest was not endogenous (Table 7). We have than checked for the marginal effects

quantifying the marginal derivative of the variables and we have confirmed the importance of the

size of the negative association between cooperative banks and the probability of financial crisis.

We have obtained equations that can explain in a dynamic context how the change in the percentage


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of Cooperative Banks total assets share can change the probability to suffer the Great Financial

Crisis of 2007-09.

Now we can consider the single regressors in this equation.

The regressor COOPERATIVE BANKS is negatively associated with the dependent variable

CRISIS. The regressor COOPERATIVE BANKS has a coefficient closed to 4.5, with a p-value

equal to 0.018 (Table 5). Marginal effects show a negative relation between the variable

COOPERATIVE and the CRISIS (Table 6). This leads us to affirm that the presence of Cooperative

Banks reduced the probability to suffer for the Great Financial Crisis.

Our analysis shows that there is also a negative relation between the regressor BANK

CONCENTRATION and the dependent variable CRISIS. The BANK CONCENTRATION has a

coefficient value equal to 3 and a p-value of 0.089 (Table 5) that becomes 0.052 checking for the

marginal effects (Table 6).

The value of the CREDIT DEPOSIT RATIO regressor is positively associated with the independent

variable CRISIS and its p-value show a statistical significance either in the probit model (0.011 as

in Table 5) or checking for the marginal effects (0.001 as in Table 6). The CREDIT DEPOSIT

RATIO measures the mean of the ratio of loans to deposits. This variable in the data has a mean of

1.022 a minimum value of .036 and a maximum value of 2.49. This means that on average national

banking systems tend to have a level of credit that overcomes that of deposits and this fact can

destabilize the economy. In particular, we can say that for 33 countries on 83"+

the level of the ratio

20 The countries are: Australia (1.36), Austria (1.26), Bolivia (1.13), Burundi (1.13), Chile (1.31), Colombia (1.41),

Costa Rica (1.65), Denmark (2.48), El Salvador (1.06), Estonia (1.51), Finland (1.29), Germany (1.26), Iceland (2.49),

Ireland (1.49), Italy (1.52), Kazakhstan (1.30), Korea Rep. Of (1.29), Latvia (1.42), Malaysia (1.05), Mali (1.08),

Netherlands (1.48), New Zealand (1.37), Norway (1.46), Oman (1.25), Panama (1.13), Portugal (1.48), South Africa

(1.25), Spain (1.33), Sweden (1.92), Switzerland (1.22), Thailand (1.03), Tunisia (1.24), United Kingdom (1.26). Wecan observe that even if the subprime crisis has been produced in the United States, United States doesnt figure in this

list. In effect if we look at the data we can see that the level of Credit Deposit Ratio in the USA in the period between

1998-2006 was, on average, lower than 1 and in particular equal to 0.79. This means that the banking system in theUSA was informed to the prudential principle of having a value of Credit Deposit Ratio lower than 1. This let us infer

that the financial crisis was not created in the banking system but in the non-regulated connections between banking

system and financial markets.


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is greater than 1 and in two cases the value is greater than 2"!

. We can say that the level of CREDIT

DEPOSIT RATIO when is greater than 1 can produce financial sustainability risks and this can

argue the strong and negative relation between this regressor and the dependent variable.

Our probit model shows that there is a negative relation between the RESTRICTION regressor and

the dependent variable CRISIS. This variable is statistically significant (0.008 in probit and 0.006 in

probit marginal effects as showed in Tables 5 and 6). This relation can be better explained

considering the fact that liberalization produces more competition, competition reduces profits, and

this leads banks to manage more risky portfolio increasing the risk of failure (Hellmann et al.,

2000). Banking restrictions reduce competition, lowering the propensity of banks to manage risky

portfolio bringing down the probability to suffer for the Financial Crisis.

The Z-SCORE regressor is negatively associated with the dependent variable CRISIS. Its

coefficient is small and its p value is equal to 0.045 (Table 5). The negative relation between Z-

SCORE and CRISIS is explained by the economic meaning of the Z-SCORE regressor, that is

representative of banking stability.

The ROA regressor is positively associated with the probability to suffer for the Great Financial

Crisis measured by the dependent variable CRISIS. This positive relation is statistically significant

with a p-value equal to 0.022 and a coefficient equal to 6.5 (Table 5). This means that an increase in

the return on asset increase the probability to be in Crisis. The reason can be related with the strong

connection between banks and financial markets. Using ROA to evaluate the banking performance

is one of the strategies that can be practiced to realize a shareholder oriented banking governance.

The CAPRIO CAPIT MEAN regressor is positively associated with the dependent variable CRISIS.

The coefficient of this variable is near to 0 and the variable has a p value equal to 0.050 (Table 5).

Marginal effects show a detriment in the statistical significance (p value = 0.057 as shown in Table

21The value is greater than 2 for Denmark (2.48) and Iceland (2.49). Many economists have showed that the collapse of

the Icelandic banking system actively contributed to let the financial crisis going global. Icelandic bankingorganizations have developed a global attitude but their ability to manage for systemic risks wasnt sufficient to secure

the Icelandic economy. The Icelandic banking system international activism was not supported by an adequate Central

Bank monetary policy leading to the crisis (Buiter & Sibert, 2008).


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6). The fact that there is a positive relation between the CAPITAL restrictions and the probability of

a Financial Crisis can be explained by a qualitative approach on the basis of an efficient evaluation

of the capital restriction banking legislation.

There is a positive relation between the SUPERVISION regressor and the dependent variable

CRISIS. This means that the more a country has a system of supervision the higher the probability

to suffer for the financial crisis. We can say that this variable is statistically significant at the level

of 5% with a coefficient closed to 0 (Table 5). The negative effect of RESTRICTION and the

positive one of SUPERVISION suggest that, at least in our specification, regulatory restrictions

were particularly important to secure financial stability.

The INTERNATIONAL regressor is positively related with the probability to suffer for the Great

Financial Crisis, measured by the dependent variable CRISIS. The value of the coefficient is 6.315

and the level of the p value is equal to 0.000 (Table 5). This positive relation between the increasing

financial international interconnectedness and the probability to suffer for the Great Financial crisis

shows us that the Great Financial Crisis is global in its causation, materializing also through

contagion.

We have checked not only for Crisis but also for the Ordered Crisis and Cost of the Crisis both

variables present in the paper of Caprio et al. (2010). We have found that in both cases the negative

relation between Cooperative Banks and Financial Crisis though with different significance level

still remains (as showed in Tables 8, 9 and 10).

Firstly, the ordered probit results confirm the signs, the coefficient magnitude and the level of

statistical significance of the variables in the model as showed in Table 8. Also here, the marginal

effects show similar signs, coefficients and statistical significance of the variables as showed in

Table 9.

Finally, we have checked for the variable Cost of the Crisis measured as the cost of government

interventions to salvage banks taken as a ratio to GDP using the tobit model. In this case all the

regressors preserve their statistical relation with the independent variable, with small changes in the


19/35

coefficient magnitude, and all the variable are statistical significant at least at a level of 5%, with

the exception of CAPRIO CAPIT MEAN that has a p value equals to 0.181. This check lets us infer

about a certain kind of robustness of the econometric estimation of our theoretical model.

4 CONCLUSIONS

4.1The importance of Cooperation for economic growth, and financial sustainability

Our results find a negative relation between Cooperative Banks presence and the occurrence of the

Financial Crisis. Our work sheds light on a part of the classical economic theory that economists

and policy makers have ignored in the libertarian post-modern age of financial globalization.

Cooperation has a positive impact on the efficiency of the economic game (North, 1990).

Various economists have shown the importance of cooperative behavior in the institutional building

process able to reduce market failures. Cooperative Banks may produce sustainability (Coco &

Ferri, 2010), enforcing an STV maximizing approach, serving communities and constituencies

(Freeman, 2010), having an egalitarian corporate governance model able to develop more socially

oriented investment. Cooperative Banks preserve a level of competitive operational efficiency with

respect to Commercial Banks (Cebenoyan et al, 1993; Valnek, 1999; Altunbas et al., 2001; Ayadi et

al., 2009). Cooperative Banks can develop the firm-bank nexus, reducing the use of securitization.

Cooperative Banks prevent local capital drain and actively promote local economic growth and

development (Hakenes & Schnabel, 2006; Hakenes, Schmidt & Xie, 2009). Cooperative Banks may

develop a more sustainable oriented banking system.

4.2Relationship banking

An important strength of Cooperative Banks is their ability to develop relationships with firms and

customers"" (Boot, 2000; Elyasiani & Goldberg, 2004). In this sense Cooperative Banks are very

22The relationship banking model affects directly the way in which Cooperative Banks produce value added. While inSHV model valued added is incorporated in profits, in Cooperative Banks, as a proxy for STV banks, the value added is

incorporated in products and services offered to customers (Drake & Llwellyn, 2001). The value added process is based

on relationship and the quality of relationship affect directly the production of value added.


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fundamental. Several economists in this post-crisis period argue that it is very important to preserve

relations as a basis to develop human capital and common confidence"#. Some economists speak

about the capital of relationships, or, in other terms, the economics of relationships, using this

expression referring to the complex of relationships that are created among economic agents

(Zamagni, 2004). These relationships generate information, both explicit and implicit, promoting

the exchange of immaterial goods among economic agents"%(Stiglitz, 1990; Varian, 1990; Besley &

Coate, 1995). Evaluating the relational capital seems to be fundamental to solve market failures and

create confidence in the market. The nexus among human capital, relational capital and the banking

market seems to be a key for the description of macroeconomic and microeconomic phenomena.

This gives some suggestions for policy makers. Financial political economies based on relationship

banking have three effects: increase the value of human capital; increase the value of relational

capital; producing sustainability.

4.3 Heterogeneity and hegemony in the financial constitution of the economic order

The hegemony of SHV maximization has produced an age of increasing financial risks, of rising

global uncertainties and, at the end, the Great Financial Crisis. The Hegemony of the SHV

maximization is the managerial representation of a widespread post-1989 idea: the idea of the end

of history (Fukuyama, 1993), the idea of the unipolar world, the idea of the definitive victory of

capitalism. The Great Financial Crisis has showed that the idea of a unipolar world is not

sustainable, that the economic order needs heterogeneity of institutions and organizations (Kirman,

2006), and that at the end globalization can be more sustainable in the heterogeneity of economic

orders representative of ethno-anthropological differentiation. Our results show that countries with a

more heterogeneous financial constitution less likely suffered the Great Financial Crisis.

23 We can say that relational goods are able to increase the value of human capital. In effect human capital can

depreciate if it is not applied in the exercise of relational goods, since the fundamental characteristic of human capital is

that to produce a knowledge economics optimized under a relational constraint.


21/35

Heterogeneity of institutions and organizations can create the right incentives to overcome classical

distortions of information developed in modern economics, thus securing better allocations.

4.4 Law and banking: a new perspective

In the last few years we have witnessed a development in the field of law and economics, especially

law and finance (La Porta et al., 1998). We can say that the nexus between the financial system and

the banking system has been studied in depth in the last fifteen years. It is important to understand

that the banking system and the financial system are in the relation of a part to the whole, in the

sense that the banking system is completely contained inside the financial system, but at the same

time it is important that the nexus between the banking system and the financial system still remains

under regulatory control. This control is important since it seems that overly increasing the volume

of credit to the financial sector produces financial crises. For this reason it seems important to

develop a law and banking perspective inside the law and finance field in law and economics to

preserve banks from taking excessive financial risks that end up destroying saving as public good.

Within economics, the field of financial economics has been developed more than banking

economics. Financial economics includes the economics of financial institutions and organizations

and, due to the rising relative importance of the financial markets, it is possible recognize a

financial constitution of the economic order that possesses some degree of heterogeneity even in the

financial globalization. Banking economics is a subfield of financial economics but it is the

diamond of the financial constitution of the economic order. The supremacy of the banking

economics is in the pragmatic of capitalism. Economists should weigh the need to defend the

economics of banking with appropriate laws. In this effort, they should not forget the importance to

safeguard cooperative financial institutions and organizations, so to support financial stability

within sustainable economies.


22/35

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Zamagni S., The lesson and warning of a crisis foretold: a political economy approach, International

Review of Economics, September 2009, Volume 56, Issue 3, pp 315-334

TABLE 1. DEPENDENT VARIABLES

Probit Model: CRISIS Dummy equal to 1 if the country is classified as either borderline crisis or systemic crisis by Laeven and Valencia

(2010) and 0 otherwise

Dependent variable

ordered probit model

ORDERED CRISIS

Dummy equal to 1 is the country is classified as borderline crisis, equal to 2 if the country is classified as systemiccrisis and 0 otherwise (source: Laeven and Valencia , 2010)

Dependent variable tobit

model: CRISIS_COST

Variable as provided by Laeven and Valencia (2010) that measures the cost of public support to the financial system in

term of GDP

TABLE 2. INDEPENDENT VARIABLES


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COOPERATIVE BANKS Mean value of the percentage, from 1998 to 2006, of total assets of Cooperative Banks on the sum of total assets ofCooperative Banks, Commercial Banks, Bank Holding, Investment Banks, Savings Banks, (source: Bankscope

Database)

CREDIT DEPOSIT

RATIO

Mean of the ration of loans to deposits from 1998 to 2006 (source: Beck Demigurc-Kunt and Levine, 2000)

BANK

CONCENTRATION

Mean of assets of three largest banks as a share of assets of all commercial banks from 1998 to 2006 (source: Beck,

Demigurc-Kunt and Levine, 2000)

PRIVATE

RESTRICTION

Mean value of the "overall restrictions" index reported in the three surveys (source: Barth, Caprio and Levine , 2004)

Z SCORE Mean value of bank z score from 1998 to 2006 (source: beck, Demigurc-Kunt and Levine , 2000)

ROA Mean of average return on assets (net income/total equity)=, from 1998 to 2006 (source: Beck, Demigurc-Kunt and

Levine, 2000)

CAPRIO CAPIT MEAN Mean value of the "Capital Regulation" index reported in the three surveys (source: Barth, Caprio and Levine 2004).

CAPRIO SUPER MEAN Mean value of the "Official Supervisory" index reported in the three surveys (source: Barth, Caprio and Levine, 2004)

INTERNATIONAL Mean of the gross of international bond issues, relative to GDP from 1998 to 2006 (source: Beck, Demigurc-Kunt and

Levine, 2000)

TABLE 3. CORRELATIONS

CRISIS COOP CONCENTRATION

CREDITDEPOSIT

RESTRICTION

BANK ZSCORE

ROA CAPITMEAN

SUPERMEAN

INTERNATIONAL

CRISIS 10.000

COOPERATI

VE BANKS

-0.2485 10.000

BANK

CONCENTR

ATION

0.0419 -0.3489 10.000

CREDIT

DEPOSITRATIO

0.3520 -0.2228 0.2682 10.000

PRIVATE

RESTRICTION

-0.4445 0.2687 -0.1515 -0.1273 10.000

BANK ZSCORE 0.0569 -0.2212 0.2321 0.1511 -0.1024 10.000

BANK ROA 0.0813 0.1037 0.3226 -0.0132 0.0624 0.2321 10.000

CAPRIOCAPIT MEAN

0.1667 0.0621 0.0071 -0.0374 0.0250 -0.0815 0.0379 10.000

CAPRIO

SUPER

MEAN

-0.0664 0.0799 -0.0624 -0.2512 0.2888 -0.0045 0.2572 0.1326 10.000

INTERNATIO

NAL

0.6074 -0.1951 -0.0267 0.1772 -0.5633 0.0746 0.0001 -0.0192 -0.2418 10.000

TABLE 4. STATISTICSOF VARIABLES

Variable Obs Mean Std. Dev. Min Max

CRISIS 83 .2289157 .4226889 0 1

COOPERATIVE BANKS 83 .1636145 .1633758 0 .77

BANK CONCENTRATION 83 .6739759 .1896398 .25 1

CREDIT DEPOSIT RATIO 83 1.022.289 .3861736 .36 2.49

CAPRIO RESTRICTION 83 7.427.831 1.741.259 3.33 12

BANK Z SCORE 81 1.125.506 6.626.298 4.2 39.17

BANK ROA 83 .0108434 .0111754 -.02 .04


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CAPRIO CAPIT MEAN 83 615.253 1.492.439 3 10

CAPRIO SUPER MEAN 82 1.093.902 2.310.924 5 14.25

INTERNATIONAL 73 .2141096 .2563192 0 1.46

TABLE 5. PROBIT REGRESSION

PROBIT REGRESSION

Number of obs = 71

Wald chi2(9) = 39.07

Prob > chi2 = 0.0000

Pseudo R2 = 0.5981

CRISIS COEF. R. STD. ERR. Z P>|Z| [95% !

!!

!

Conf.Interva

COOPERATIVE BANKS -4.499.449 1.909.812 -2.36 0.018 -.8160095 -7562862BANK CONCENTRATION -2.981.543 1.718.613 -1.73 0.083 -6.349.963 .3868772

BANK CREDIT/DEPOSIT 2.042.641 .7992698 2.56 0.011 .4761009 3.609.181

CAPRIO RESTRICTION MEAN -.4681251 .1774953 -2.64 0.008 -.8160095 -.1202407

BANK Z SCORE -.0621564 .0309377 -2.01 0.045 -.1227933 -.0015196

BANK ROA 6.522.032 2.849.678 2.29 0.022 9.367.655 121.073

CAPRIO CAPIT MEAN .299565 .1525842 1.96 0.050 .0005054 .5986246

CAPRIO SUPER MEAN .2725048 .1291008 2.11 0.035 .0194719 .5255378

INTERNATIONAL 6.315.616 1.594.051 3.96 0.000 3.191.334 9.439.898

CONSTANT -3.537.184 2.190.953 -1.61 0.106 -7.831.372 .757004


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TABLE 6. MARGINAL EFFECTS OF PROBIT REGRESSION

,-./01. 20/13405 .66.789

:;? @ A;BC98

?DE/.993;4 @ F/G>/3939HI E/.|Z| [95% !!!

!Conf.Interval]

COOPERATIVE BANKS LM&&%(!*% M"#"#!)% L"M#* +M+!( L!M+!+M+&& LM+**#)#)

BANK CONCENTRATION LM#'(&)") M!)*!&)( L!M*% +M+&" LM(#)#"( M++#!'!&

BANK CREDIT / DEPOSIT M"&!)"*" M+()(* #M"+ +M++! M+*(#*#" M%+'"'&"

CAPRIO RESTRICTION ME LM+&((!## M+"+*')' L"M(& +M++' LM+*))!!! LM+!''!&&

BANK Z SCORE LM++(''# M++#(+*( L"M+( +M+#* LM+!%*##) LM+++#*""

BANK ROA )M+%+M(&) #M"(%M!"( "M%' +M+!% !M'"#M&)' !M%%&M(*#

CAPRIO CAPIT MEAN M+#'*#"" M+!*%!!' !M*+ +M+&( LM++!!!#) M+(%*()"

CAPRIO SUPER MEAN M+##&*'! M+!&'&&! "M!& +M+#" M++"*!"' M+'%"(*&

INTERNATIONAL M(()'"(' M!("!&"& %M&" +M+++ M%%!"!%* !!!M'+%

TABLE 7. WALD TEST OF EXOGENEITY

TEST FOR EXOGENEITY

Instruments: BANK CONCENTRATION BANK CREDIT / DEPOSIT RATIO

CAPRIO RESTRICTION MEAN

BANK Z SCORE BANK ROA CAPRIO CAPIT MEAN CAPRIO

SUPER MEAN INTERNATIONAL

Wald test of exogeneity chi2(1) = 0.20 Prob > chi2 = 0.6560


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TABLE 8. PROBIT REGRESSION ORDERED CRISIS

F/;B38 /.1/.993;4 JC2B./ ;6 ;B9 K (!

N05< 7O3"G*H K #*M+( F/;B P 7O3" K +M++++

Q;1 E9.CSJ>?JTA,TUSJ L"M*)!M&%# !M(!)M'!# L!M(# +M+)# L'M#%*M*'# M#)')(("

>A?YUT Y?FSXUT A,TUS "M+%"M'%! M(**"'*) "M&' +M+!! M%('!++* #M'+*M!)!

>,FAUS A?XTAU>TUSJ LM%')!"&! M!((%* L"M'% +M++) LM)!'++*& LM!"+"%+(

V,JW Z X>SA? LM+'"!&'% M+#+*#(( L"M+! +M+%& LM!""(*## LM++!&!*'

V,JW AS, 'M&""M+#" "M)%*M'() "M"* +M+"" *M#'(M'&& !"!M+(#

>,FAUS >,FUT :?,J M"**&'& M!&"&)%" !M*' +M+&+ M+++&+&% M&*)'"%'

>,FAUS X[F?A :?,J M"("&+%) M!"*!++) "M!! +M+#& M+!*%(!* M&"&()

UJT?AJ,TUSJ,Q 'M#!&M'!' !M&*%M+&! #M*' +M+++ #M!*!M##% *M%#*M)*)

>SJXT,JT L#M(M!)% "M!*+M* L!M'! +M!+' L(M)#!M#(" M(&(++%'

TABLE 9. MARGINAL EFFECTS PROBIT REGRESSION ORDERED CRISIS

!"#$"$# &"'('( &!$)* "* (+# $""!" , -./,/ 0123 &456*'5789:;SSF?A,TU=? V,JWX LM&&%(!*% M"#"#!)% L"M#* +M+!( L!M+!+M+&& LM+**#)#)

V,JW >SJ>?JTA,TUSJ LM#'(&)") M!)*!&)( L!M*% +M+&" LM(#)#"( M++#!'!&

>A?YUT Y?FSXUT A,TUS M"&!)"*" M+()(* #M"+ +M++! M+*(#*#" M%+'"'&"

>,FAUS A?XTAU>TUSJ LM+&((!## M+"+*')' L"M(& +M++' LM+*))!!! LM+!''!&&

V,JW Z X>SA? LM++(''# M++#(+*( L"M+( +M+#* LM+!%*##) LM+++#*""

V,JW AS, )M+%+M(&) #M"(%M!"( "M%' +M+!% !M'"#M&)' !M%%&M(*#

>,FAUS >,FUT :?,J M+#'*#"" M+!*%!!' !M*+ +M+&( LM++!!!#) M+(%*()"

>,FAUS X[F?A :?,J M+##&*'! M+!&'&&! "M!& +M+#" M++"*!"' M+'%"(*&

UJT?AJ,TUSJ,Q M(()'"(' M!("!&"& %M&" +M+++ M%%!"!%* !!!M'+%

TABLE 10. TOBIT REGRESSION: COST OF THE CRISIS

T;B38 /.1/.993;4 JC2B./ ;6 ;B9 K (!

\G *I '"H K #M++ F/;B P \ K +M++%*

Q;1 E9.CSSF?A,TU=? V,JWX L!M('#M%*% )M("#M*'( L"M+" +M+%) L#&+M(#* LM!*&*(#(

V,JW >SJ>?JTA,TUSJ L!M()(M%"( )M()&M*(# L"M+# +M+%' L#M&%#M(!) LM#!!#'"'

>A?YUT Y?FSXUT A,TUSJ (M*""M!#% "M)"#M&'* "M)! +M++( "M"((M)** !M#&'M'#(

FAU=,T? A?XTAU>TUSJ L"M!'!M"+' M)(&)'+& L"M%( +M+!' L#M*!"M+"' LM%!+#)'"

V,JW Z X>SA? LM"*&("(% M!%*(% L!M*( +M+ LM&*&+)+" M++#'"&&

V,JW AS, #M%!+M&+& !M!*'M')! "M)& +M++' !M+!)M#(% &M)+"M'#&

>,FAUS >,FUT :?,J LM&!)*+"" M#)#"#!# L!M#& +M!)! L!M")%M*(! M"%(!''#

>,FAUS X[F?A :?,J !+%M*)# M#))&'&" "M(+ +M++* M"(#+**! !M)"'M&'!

UJT?AJ,TUSJ,Q !M#&"M(+% %M")*M)!' #M!& +M++" %*&M!)" "M"!+M""'>SJXT,JT ##( )#' ) !+' "%# + %" + '() L! ")" &(* ! *&) "&!

2012 Angelo Leogrande Cooperative Banks vs Financial Crisis

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