Hidden Gems and Borrowers with Dirty Little Secrets: Investment in Soft Information, Borrower Self-Selection and Competition
Reint E. Gropp, C. Gruendl, Andre Guettler
Abstract
This paper empirically examines the role of soft information in the competitive interaction between relationship and transaction banks. Soft information can be interpreted as a private signal about the quality of a firm that is observable to a relationship bank, but not to a transaction bank. We show that borrowers self-select to relationship banks depending on whether their privately observed soft information is positive or negative. Competition affects the investment in learning the private signal from firms by relationship banks and transaction banks asymmetrically. Relationship banks invest more; transaction banks invest less in soft information, exacerbating the selection effect. Finally, we show that firms where soft information was important in the lending decision were no more likely to default compared to firms where only financial information was used.
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Who Invests in Home Equity to Exempt Wealth from Bankruptcy?
S. Corradin, Reint E. Gropp, H. Huizinga, Luc Laeven
Abstract
Homestead exemptions to personal bankruptcy allow households to retain their home equity up to a limit determined at the state level. Households that may experience bankruptcy thus have an incentive to bias their portfolios towards home equity. Using US household data for the period 1996 to 2006, we find that household demand for real estate is relatively high if the marginal investment in home equity is covered by the exemption. The home equity bias is more pronounced for younger households that face more financial uncertainty and therefore have a higher ex ante probability of bankruptcy.
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Financial Factors in Macroeconometric Models
Sebastian Giesen
Volkswirtschaft, Ökonomie, Shaker Verlag GmbH, Aachen,
2013
Abstract
The important role of credit has long been identified as a key factor for economic development (see e.g. Wicksell (1898), Keynes (1931), Fisher (1933) and Minsky (1957, 1964)). Even before the financial crisis most researchers and policy makers agreed that financial frictions play an important role for business cycles and that financial turmoils can result in severe economic downturns (see e.g. Mishkin (1978), Bernanke (1981, 1983), Diamond (1984), Calomiris (1993) and Bernanke and Gertler (1995)). However, in practice researchers and policy makers mostly used simplified models for forecasting and simulation purposes. They often neglected the impact of financial frictions and emphasized other non financial market frictions when analyzing business cycle fluctuations (prominent exceptions include Kiyotaki and Moore (1997), Bernanke, Gertler, and Gilchrist (1999) and Christiano, Motto, and Rostagno (2010)). This has been due to the fact that most economic downturns did not seem to be closely related to financial market failures (see Eichenbaum (2011)). The outbreak of the subprime crises ― which caused panic in financial markets and led to the default of Lehman Brothers in September 2008 ― then led to a reconsideration of such macroeconomic frameworks (see Caballero (2010) and Trichet (2011)). To address the economic debate from a new perspective, it is therefore necessary to integrate the relevant frictions which help to explain what we have experienced during recent years.
In this thesis, I analyze different ways to incorporate relevant frictions and financial variables in macroeconometric models. I discuss the potential consequences for standard statistical inference and macroeconomic policy. I cover three different aspects in this work. Each aspect presents an idea in a self-contained unit. The following paragraphs present more detail on the main topics covered.
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Predicting Financial Crises: The (Statistical) Significance of the Signals Approach
Makram El-Shagi, Tobias Knedlik, Gregor von Schweinitz
Journal of International Money and Finance,
Nr. 35,
2013
Abstract
The signals approach as an early-warning system has been fairly successful in detecting crises, but it has so far failed to gain popularity in the scientific community because it cannot distinguish between randomly achieved in-sample fit and true predictive power. To overcome this obstacle, we test the null hypothesis of no correlation between indicators and crisis probability in three applications of the signals approach to different crisis types. To that end, we propose bootstraps specifically tailored to the characteristics of the respective datasets. We find (1) that previous applications of the signals approach yield economically meaningful results; (2) that composite indicators aggregating information contained in individual indicators add value to the signals approach; and (3) that indicators which are found to be significant in-sample usually perform similarly well out-of-sample.
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Payment Defaults and Interfirm Liquidity Provision
F. Boissay, Reint E. Gropp
Review of Finance,
Nr. 6,
2013
Abstract
Using a unique data set on French firms, we show that credit constrained firms that face liquidity shocks are more likely to default on their payments to suppliers. Credit constrained firms pass on a sizeable fraction of such shocks to their suppliers. This is consistent with the idea that firms provide liquidity insurance to each other and that this mechanism is able to alleviate credit constraints. We show that the chain of defaults stops when it reaches unconstrained firms. Liquidity appears to be allocated from firms with access to outside finance to credit constrained firms along supply chains.
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Did TARP Distort Competition Among Sound Banks?
Michael Koetter, Felix Noth
Abstract
This study investigates if the Troubled Asset Relief Program (TARP) distorted price competition in U.S. banking. Political indicators reveal bailout expectations after 2009, manifested as beliefs about the predicted probability of receiving equity support relative to failing during the TARP disbursement period. In addition, the TARP affected the competitive conduct of unsupported banks after the program stopped in the fourth quarter of 2009. Loan rates were higher, and the risk premium required by depositors was lower for banks with higher bailout expectations. The interest margins of unsupported banks increased in the immediate aftermath of the TARP disbursement but not after 2010. No effects emerged for loan or deposit growth, which suggests that protected banks did not increase their market shares at the expense of less protected banks.
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Bank Bailouts and Moral Hazard: Evidence from Germany
Lammertjan Dam, Michael Koetter
Review of Financial Studies,
Nr. 8,
2012
Abstract
We use a structural econometric model to provide empirical evidence that safety nets in the banking industry lead to additional risk taking. To identify the moral hazard effect of bailout expectations on bank risk, we exploit the fact that regional political factors explain bank bailouts but not bank risk. The sample includes all observed capital preservation measures and distressed exits in the German banking industry during 1995–2006. A change of bailout expectations by two standard deviations increases the probability of official distress from 6.6% to 9.4%, which is economically significant.
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Predicting Financial Crises: The (Statistical) Significance of the Signals Approach
Makram El-Shagi, Tobias Knedlik, Gregor von Schweinitz
Abstract
The signals approach as an early warning system has been fairly successful in detecting crises, but it has so far failed to gain popularity in the scientific community because it does not distinguish between randomly achieved in-sample fit and true predictive power. To overcome this obstacle, we test the null hypothesis of no correlation between indicators and crisis probability in three applications of the signals approach to different crisis types. To that end, we propose bootstraps specifically tailored to the characteristics of the respective datasets. We find (1) that previous applications of the signals approach yield economically meaningful and statistically significant results and (2) that composite
indicators aggregating information contained in individual indicators add value to the signals approach, even where most individual indicators are not statistically significant on their own.
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The Impact of Banking and Sovereign Debt Crisis Risk in the Eurozone on the Euro/US Dollar Exchange Rate
Stefan Eichler
Applied Financial Economics,
Nr. 15,
2012
Abstract
I study the impact of financial crisis risk in the eurozone on the euro/US dollar exchange rate. Using daily data from 3 July 2006 to 30 September 2010, I find that the euro depreciates against the US dollar when banking or sovereign debt crisis risk increases in the eurozone. While the external value of the euro is more sensitive to changes in sovereign debt crisis risk in vulnerable member countries than in stable member countries, the impact of banking crisis risk is similar for both country blocs. Moreover, rising default risk of medium and large eurozone banks leads to a depreciation of the euro while small banks’ default risk has no significant impact, showing the relevance of systemically important banks with regards to the exchange rate.
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Extreme Dependence with Asymmetric Thresholds: Evidence for the European Monetary Union
Stefan Eichler, R. Herrera
Journal of Banking and Finance,
Nr. 11,
2011
Abstract
Existing papers on extreme dependence use symmetrical thresholds to define simultaneous stock market booms or crashes such as the joint occurrence of the upper or lower one percent return quantile in both stock markets. We show that the probability of the joint occurrence of extreme stock returns may be higher for asymmetric thresholds than for symmetric thresholds. We propose a non-parametric measure of extreme dependence which allows capturing extreme events for different thresholds and can be used to compute different types of extreme dependence. We find that extreme dependence among the stock markets of ten initial EMU member countries, the United Kingdom, and the United States is largely asymmetrical in the pre-EMU period (1989–1998) and largely symmetrical in the EMU period (1999–2010). Our findings suggest that ignoring the possibility of asymmetric extreme dependence may lead to an underestimation of the probability of co-booms and co-crashes.
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