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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Städte und Regionen im Standortwettbewerb – Neue Tendenzen, Auswirkungen und Folgerungen für die Politik
Albrecht Kauffmann, Martin T. W. Rosenfeld
Forschungs- und Sitzungsberichte der ARL, Bd. 238,
2012
Abstract
Aufgrund anhaltender Globalisierungstendenzen und zunehmender Intensität des Austauschs von Informationen, Gütern und Dienstleistungen wird sich der Wettbewerb zwischen Regionen vermutlich weiter verschärfen. Dabei ergeben sich aus den in vielfacher Hinsicht veränderten Rahmenbedingungen auch neuere Planungs- und Steuerungsansätze. Diese reichen von den unterschiedlichen Wettbewerbsarten bis hin zu Fragen neuer Strategien der Regional- und Stadtentwicklungspolitik. Anhand verschiedener Fragestellungen werden in diesem Band die vielseitigen Dimensionen von Strukturveränderungen im Standortwettbewerb und deren Ursache mithilfe von „Querschnittsstudien“ vor allem auf der Basis vorliegender Untersuchungen nachgezeichnet, geordnet und konkretisiert. Da es in der bestehenden Literatur weitestgehend an empirischen Belegen zu den konkreten Folgen der veränderten Wettbewerbsbedingungen fehlt, wurde in explorativen Fallstudien für ausgewählte Städte und Regionen untersucht, inwieweit sich die erwarteten Veränderungen aufgrund der neuen Strukturen des Standortwettbewerbs nachweisen lassen und wie die jeweils zuständigen politischen Akteure hierauf bislang reagiert haben.
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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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Efficiency in the UK Commercial Property Market: A Long-run Perspective
Steven Devaney, Oliver Holtemöller, R. Schulz
IWH Discussion Papers,
Nr. 15,
2012
Abstract
Informationally efficient prices are a necessary requirement for optimal resource allocation in the real estate market. Prices are informationally efficient if they reflect buildings’ benefit to marginal buyers, thereby taking account of all available information on future market development. Prices that do not reflect available information may lead to over- or undersupply if developers react to these inefficient prices. In this study, we examine the efficiency of the UK commercial property market and the interaction between prices, construction costs, and new supply. We collated a unique data set covering the years 1920 onwards, which we employ in our study. First, we assess if real estate prices were in accordance with present values, thereby testing for informational efficiency. By comparing prices and estimated present values, we can measure informational inefficiency. Second, we assess if developers reacted correctly to price signals. Development (or the lack thereof) should be triggered by deviations between present values and cost; if prices do not reflect present values, then they should have no impact on development decisions.
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Corporate Boards and Bank Loan Contracting
Bill Francis, Iftekhar Hasan, Michael Koetter, Qiang Wu
Journal of Financial Research,
Nr. 4,
2012
Abstract
We investigate the role of corporate boards in bank loan contracting. We find that when corporate boards are more independent, both price and nonprice loan terms (e.g., interest rates, collateral, covenants, and performance-pricing provisions) are more favorable, and syndicated loans comprise more lenders. In addition, board size, audit committee structure, and other board characteristics influence bank loan prices. However, they do not consistently affect all nonprice loan terms except for audit committee independence. Our study provides strong evidence that banks recognize the benefits of board monitoring in mitigating information risk ex ante and controlling agency risk ex post, and they reward higher quality boards with more favorable loan contract terms.
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Foreign Bank Entry, Credit Allocation and Lending Rates in Emerging Markets: Empirical Evidence from Poland
Hans Degryse, Olena Havrylchyk, Emilia Jurzyk, Sylwester Kozak
Journal of Banking and Finance,
Nr. 11,
2012
Abstract
Earlier studies have documented that foreign banks charge lower lending rates and interest spreads than domestic banks. We hypothesize that this may stem from the superior efficiency of foreign entrants that they decide to pass onto borrowers (“performance hypothesis”), but could also reflect a different loan allocation with respect to borrower transparency, loan maturity and currency (“portfolio composition hypothesis”). We are able to differentiate between the above hypotheses thanks to a novel dataset containing detailed bank-specific information for the Polish banking industry. Our findings demonstrate that banks differ significantly in terms of portfolio composition and we attest to the “portfolio composition hypothesis” by showing that, having controlled for portfolio composition, there are no differences in lending rates between banks.
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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.
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