Should Forecasters Use Real‐time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence
Katja Heinisch, Rolf Scheufele
German Economic Review,
No. 4,
2019
Abstract
In this paper, we investigate whether differences exist among forecasts using real‐time or latest‐available data to predict gross domestic product (GDP). We employ mixed‐frequency models and real‐time data to reassess the role of surveys and financial data relative to industrial production and orders in Germany. Although we find evidence that forecast characteristics based on real‐time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator models. However, when obtaining the optimal combination of soft and hard data, the use of final release data may understate the role of survey information.
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Hidden Gems and Borrowers with Dirty Little Secrets: Investment in Soft Information, Borrower Self-selection and Competition
Reint E. Gropp, Andre Guettler
Journal of Banking and Finance,
No. 2,
2018
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 valuable 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 observed soft information is positive or negative. Competition affects the investment in learning the soft information from firms by relationship banks and transaction banks asymmetrically. Relationship banks invest more; transaction banks invest less in soft information, exacerbating the selection effect.
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Should Forecasters Use Real-time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence
Katja Heinisch, Rolf Scheufele
Abstract
In this paper we investigate whether differences exist among forecasts using real-time or latest-available data to predict gross domestic product (GDP). We employ mixed-frequency models and real-time data to reassess the role of survey data relative to industrial production and orders in Germany. Although we find evidence that forecast characteristics based on real-time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator models. However, when obtaining the optimal combination of soft and hard data, the use of final release data may understate the role of survey information.
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Consumer Bankruptcy, Bank Mergers and Information
Jason Allen, H. Evren Damar, David Martinez-Miera
Review of Finance,
No. 4,
2016
Abstract
This article analyzes the relationship between consumer bankruptcy patterns and the destruction of soft information caused by mergers. Using a major Canadian bank merger as a source of exogenous variation in local banking conditions, we show that local markets affected by the merger exhibit an increase in consumer bankruptcy rates post-merger. The evidence is consistent with the most plausible mechanism being the disruption of consumer–bank relationships. Markets affected by the merger show a decrease in the merging institutions’ branch presence and market share, including those stemming from higher switching rates. We rule out alternative mechanisms such as changes in quantity of credit, loan rates, or observable borrower characteristics.
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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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