Credit Rationing and Credit View: Empirical Evidence from Loan Data

Becchetti, Leonardo; Garcia, Maria Melody; Trovato, Giovanni

doi:10.2139/ssrn.1434509

Cited by 11 publications

(11 citation statements)

References 36 publications

(26 reference statements)

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“…Social banks present obvious similarities with other types of relational banks, such as credit cooperatives and community banks, in terms of organizational architecture and credit‐granting procedures (see e.g., Cornée, Masclet, and Thenet ; De Young, Hunter, and Udell ; Kalmi ; Scott ). However, social banks distinguish themselves from their counterparts through their accomplishment of an explicit social mission, which translates into providing external debt financing to SEs (Barigozzi and Tedeschi ; Becchetti, Garcia, and Trovato ; Cornée and Szafarz ;San‐Jose, Retolaza, and Gutierrez ). SEs may be viewed as a specific type of SMEs, aimed at achieving a double‐bottom line by putting the emphasis chiefly on social goals (Borzaga and Defourny ).…”

Section: Soft Information Default Prediction and Profitabilitymentioning

confidence: 99%

The Relevance of Soft Information for Predicting Small Business Credit Default: Evidence from a Social Bank

Cornée

2017

Journal of Small Business Management

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Using a unique, hand-collected database of 389 small loans granted by a French social bank dealing with genuinely small, informationally opaque businesses (mainly social enterprises), our study highlights the relevance of including soft information (especially on management quality) to improve credit default prediction. Comparing our findings with those of previous studies also reveals that the more opaque the borrower, the higher the predictive value of soft information in comparison with hard. Finally, a cost-benefit analysis shows that including soft information is economically valuable once collection costs have been accounted for, albeit to a moderate extent. ABSTRACTUsing a unique, hand-collected database of 389 small loans granted by a French social bank dealing with genuinely small, informationally opaque businesses (mainly social enterprises), our study highlights the relevance of including soft information (especially on management quality) to improve credit default prediction. Comparing our findings with those of previous studies also reveals that the more opaque the borrower, the higher the predictive value of soft information in comparison with hard. Finally, a cost-benefit analysis shows that including soft information is economically valuable once collection costs have been accounted for, albeit to a moderate extent.

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Section: Soft Information Default Prediction and Profitabilitymentioning

confidence: 99%

The Relevance of Soft Information for Predicting Small Business Credit Default: Evidence from a Social Bank

Cornée

2017

Journal of Small Business Management

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“…Finally, SBs fulfill criteria ( vi ) to ( ix ) because of their ownership and governance attributes. Profit is not their main objective but a means of achieving economic sustainability (Becchetti et al ; Benedikter ; Weber and Remer ; Mykhayliv and Zauner ). Many SBs operate with a stakeholder‐ownership structure, either as a cooperative or as a savings bank.…”

Section: What Is a Social Bank?mentioning

confidence: 99%

“…Because Europe is the SB stronghold, research has focused mainly on social banking in the European context. Existing studies have uncovered some key features of SBs, which are often portrayed as double bottom line institutions, implying that profit‐making is a way to achieve economic sustainability while adhering to social goals (Becchetti et al ; Benedikter ; San‐Jose et al, 2011; Weber and Remer ). SBs support their communities and the common good through simple, transparent, and prudent intermediation principles.…”

Section: Introductionmentioning

confidence: 99%

The Business Model of Social Banks

Cornée¹,

Kalmi²,

Szafarz³

2019

Kyklos

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SUMMARY Based on an extensive literature review, this paper proposes to define social banks (SBs) as social enterprises that run banking activities with the social mission of supplying credit to other social enterprises, which are typically less profitable than for‐profit businesses. This definition marks our starting point for developing a theoretical framework to explain how SBs survive without subsidies in the banking market. We build on a two‐pillar business model of value‐based financial intermediation, which comprises an ownership structure that limits residual ownership claims and preferential credit conditions associated with financial sacrifices from motivated depositors. We also clarify the link between SBs and stakeholder banks and weigh up the importance of market interest rates for facilitating the business of SBs. An empirical analysis based on panel regressions on 5,400 European banks over the 1998‐2013 period attests to the relevance of our theoretical framework. It also confirms that a low interest rate environment raises concerns about the sustainability of the SB business model.

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“…Finally, Becchetti et al (2009) documents that the proportion of Italian firms subject to credit rationing is around 20%. We assume the rate of credit rationing is 15% in the U.S. Then the proportion of matched firms is q = γθ 1−ε = 85%, where θ is also related to (φ, γ, ε).…”

Section: Proposition 3 the Model Is Locally Indeterminate If And Onlymentioning

confidence: 99%

“…Credit rationing is not only of theoretical interest, but also plays a non-trivial role in real-world firm financing. As documented in Becchetti et al (2009) based on Italian firm data, around 20.24% of firms are subject to credit rationing in Italy. However, the literature on credit rationing is extremely thin despite the seminal work of Stiglitz and Weiss (1983).…”

Section: Introductionmentioning

confidence: 97%

Credit Search and Credit Cycles

Dong

Wang

Wen

2015

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The supply and demand of credit are not always well aligned and matched, as is reflected in the countercyclical excess reserve-to-deposit ratio and interest spread between the lending rate and the deposit rate. We develop a search-based theory of credit allocations to explain the cyclical fluctuations in both bank reserves and the interest spread. We show that search frictions in the credit market can not only naturally explain the countercyclical bank reserves and interest spread, but also generate endogenous business cycles driven primarily by the cyclical utilization rate of credit resources, as long conjectured by the Austrian school of the business cycle. In particular, we show that credit search can lead to endogenous local increasing returns to scale and variable capital utilization in a model with constant returns to scale production technology and matching functions, thus providing a micro-foundation for the indeterminacy literature of Benhabib and Farmer (1994) and Wen (1998).

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Credit Rationing and Credit View: Empirical Evidence from Loan Data

Cited by 11 publications

References 36 publications

The Relevance of Soft Information for Predicting Small Business Credit Default: Evidence from a Social Bank

The Relevance of Soft Information for Predicting Small Business Credit Default: Evidence from a Social Bank

The Business Model of Social Banks

Credit Search and Credit Cycles

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