IT Use, Productivity, and Market Power in Banking
Michael Koetter, Felix Noth
Journal of Financial Stability,
No. 4,
2013
Abstract
Information management is a core process in banking that can resolve information asymmetries and thereby help to mitigate competitive pressure. We test if the use of information technology (IT) contributes to bank output, and how IT-augmented bank productivity relates to differences in market power. Detailed bank-level information on the use of IT reveals a substantial upward bias in bank productivity estimates when ignoring banks’ IT expenditures. IT-augmented bank productivity correlates positively with Lerner markups. A mere increase in IT expenditures, however, reduces markups. Results hold across a range of bank output definitions and productivity estimation methods.
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Default Options and Social Welfare: Opt In versus Opt Out
Jan Bouckaert, Hans Degryse
Journal of Institutional and Theoretical Economics JITE,
No. 3,
2013
Abstract
We offer a social-welfare comparison of the two most prominent default options – opt in and opt out – using a two-period model of localized competition. We demonstrate that when consumers stick to the default option, the prevailing default policy shapes firms' ability to collect and use customer information, and affects their pricing strategy and entry decision differently. The free-entry analysis reveals that fewer firms enter under opt out as competition becomes harsher, and that opt out is the socially preferred default option.
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Determinants of Illegal Mexican Immigration into the US Southern Border States
A. Buehn, Stefan Eichler
Eastern Economic Journal,
No. 4,
2013
Abstract
We model illegal immigration across the US-Mexico border into Arizona, California, and Texas as an unobservable variable applying a Multiple Indicators Multiple Causes model. Using state-level data from 1985 to 2004, we test the incentives and deterrents influencing illegal immigration. Better labor market conditions in a US state and worse in Mexico encourage illegal immigration while more intense border enforcement deters it. Estimating the state-specific inflow of illegal Mexican immigrants we find that the 1994/95 peso crisis in Mexico led to significant increases in illegal immigration. US border enforcement policies in the 1990s provided temporary relief while post-9/11 re-enforcement has reduced illegal immigration.
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Financial Constraints of Private Firms and Bank Lending Behavior
Patrick Behr, L. Norden, Felix Noth
Journal of Banking and Finance,
No. 9,
2013
Abstract
We investigate whether and how financial constraints of private firms depend on bank lending behavior. Bank lending behavior, especially its scale, scope and timing, is largely driven by bank business models which differ between privately owned and state-owned banks. Using a unique dataset on private small and medium-sized enterprises (SMEs) we find that an increase in relative borrowings from local state-owned banks significantly reduces firms’ financial constraints, while there is no such effect for privately owned banks. Improved credit availability and private information production are the main channels that explain our result. We also show that the lending behavior of local state-owned banks can be sustainable because it is less cyclical and neither leads to more risk taking nor underperformance.
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Social Capital and Migration Preferences - An Empirical Analysis for the Case of the Reunified Germany
Peter Bönisch, Lutz Schneider, Walter Hyll
Grincoh Working Papers July 2013,
2013
Abstract
We focus on the relevance of different types of social capital on migration intentions in the context of shrinking regions. On the one hand, formal social capital characterised by weak ties without local roots is supposed to drive selectivity and outmigration. On the other hand, informal social capital stressing strong ties to friends, relatives or neighbours might hinder migration. In our regression results we do not find an effect of shrinking regions on mobility intentions. Thus, living in a shrinking area is by itself not a reason to move away or to invest less in social capital. However, if an individual considers to move away she reduces her participation in informal and formal networks. Individuals characterised by strong informal ties, i.e. strong relationships to friends, relatives or neighbours show a significantly lower probability of moving away. And, more qualified types of social capital as participation in local politics or initiatives seem to encourage spatial mobility.
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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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Effects of Incorrect Specification on the Finite Sample Properties of Full and Limited Information Estimators in DSGE Models
Sebastian Giesen, Rolf Scheufele
Abstract
In this paper we analyze the small sample properties of full information and limited information estimators in a potentially misspecified DSGE model. Therefore, we conduct a simulation study based on a standard New Keynesian model including price and wage rigidities. We then study the effects of omitted variable problems on the structural parameters estimates of the model. We find that FIML performs superior when the model is correctly specified. In cases where some of the model characteristics are omitted, the performance of FIML is highly unreliable, whereas GMM estimates remain approximately unbiased and significance tests are mostly reliable.
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Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment
Katja Drechsel, Rolf Scheufele
Abstract
This paper presents a method to conduct early estimates of GDP growth in Germany. We employ MIDAS regressions to circumvent the mixed frequency problem and use pooling techniques to summarize efficiently the information content of the various indicators. More specifically, we investigate whether it is better to disaggregate GDP (either via total value added of each sector or by the expenditure side) or whether a direct approach is more appropriate when it comes to forecasting GDP growth. Our approach combines a large set of monthly and quarterly coincident and leading indicators and takes into account the respective publication delay. In a simulated out-of-sample experiment we evaluate the different modelling strategies conditional on the given state of information and depending on the model averaging technique. The proposed approach is computationally simple and can be easily implemented as a nowcasting tool. Finally, this method also allows retracing the driving forces of the forecast and hence enables the interpretability of the forecast outcome.
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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,
No. 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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