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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Financial Literacy and Self-employment
Aida Ćumurović, Walter Hyll
Journal of Consumer Affairs,
No. 2,
2019
Abstract
In this paper, we study the relationship between financial literacy and self‐employment. We use established financial literacy questions to measure literacy levels. The analysis shows a highly significant and positive correlation between the index and self‐employment. We address the direction of causality by applying instrumental variable techniques based on information about maternal education. We also exploit information on financial support and family background to account for concerns about the exclusion restriction. The results provide support for a positive effect of financial literacy on the probability of being self‐employed. As financial literacy is acquirable, the findings suggest that entrepreneurial activities might be increased by enhancing financial literacy.
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Lock‐in Effects in Relationship Lending: Evidence from DIP Loans
Iftekhar Hasan, Gabriel G. Ramírez, Gaiyan Zhang
Journal of Money, Credit and Banking,
No. 4,
2019
Abstract
Do prior lending relationships result in pass‐through savings (lower interest rates) for borrowers, or do they lock in higher costs for borrowers? Theoretical models suggest that when borrowers experience greater information asymmetry, higher switching costs, and limited access to capital markets, they become locked into higher costs from their existing lenders. Firms in Chapter 11 seeking debtor‐in‐possession (DIP) financing often fit this profile. We investigate the presence of lock‐in effects using a sample of 348 DIP loans. We account for endogeneity using the instrument variable (IV) approach and the Heckman selection model and find consistent evidence that prior lending relationship is associated with higher interest costs and the effect is more severe for stronger existing relationships. Our study provides direct evidence that prior lending relationships do create a lock‐in effect under certain circumstances, such as DIP financing.
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An Evaluation of Early Warning Models for Systemic Banking Crises: Does Machine Learning Improve Predictions?
Johannes Beutel, Sophia List, Gregor von Schweinitz
Abstract
This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance measure, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly effciently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.
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Lame-Duck CEOs
Marc Gabarro, Sebastian Gryglewicz, Shuo Xia
SSRN Working Papers,
2018
Abstract
We examine the relationship between protracted CEO successions and stock returns. In protracted successions, an incumbent CEO announces his or her resignation without a known successor, so the incumbent CEO becomes a “lame duck.” We find that 31% of CEO successions from 2005 to 2014 in the S&P 1500 are protracted, during which the incumbent CEO is a lame duck for an average period of about 6 months. During the reign of lame duck CEOs, firms generate an annual four-factor alpha of 11% and exhibit significant positive earnings surprises. Investors’ under-reaction to no news on new CEO information and underestimation of the positive effects of the tournament among the CEO candidates drive our results.
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Information Feedback in Temporal Networks as a Predictor of Market Crashes
Stjepan Begušić, Zvonko Kostanjčar, Dejan Kovač, Boris Podobnik, H. Eugene Stanley
Complexity,
September
2018
Abstract
In complex systems, statistical dependencies between individual components are often considered one of the key mechanisms which drive the system dynamics observed on a macroscopic level. In this paper, we study cross-sectional time-lagged dependencies in financial markets, quantified by nonparametric measures from information theory, and estimate directed temporal dependency networks in financial markets. We examine the emergence of strongly connected feedback components in the estimated networks, and hypothesize that the existence of information feedback in financial networks induces strong spatiotemporal spillover effects and thus indicates systemic risk. We obtain empirical results by applying our methodology on stock market and real estate data, and demonstrate that the estimated networks exhibit strongly connected components around periods of high volatility in the markets. To further study this phenomenon, we construct a systemic risk indicator based on the proposed approach, and show that it can be used to predict future market distress. Results from both the stock market and real estate data suggest that our approach can be useful in obtaining early-warning signals for crashes in financial markets.
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Bank Financing, Institutions and Regional Entrepreneurial Activities: Evidence from China
Iftekhar Hasan, Nada Kobeissi, Haizhi Wang, Mingming Zhou
International Review of Economics and Finance,
November
2017
Abstract
We investigate the effects of bank financing on regional entrepreneurial activities in China. We present contrasting findings on the role of quantity vs. quality of bank financing on small business formation in China: while we document a consistent, significantly positive relationship between the quality of bank financing and new venture formation, we find that the quantity of supplied credit is insignificant. We report that formal institutions are positively correlated to regional entrepreneurial activities, and informal institutions substitute formal institutions. Our findings also reveal that the institutional environment tends to supplement bank financing in promoting regional entrepreneurial activities.
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Banking Globalization, Local Lending, and Labor Market Effects: Micro-level Evidence from Brazil
Felix Noth, Matias Ossandon Busch
Abstract
This paper estimates the effect of a foreign funding shock to banks in Brazil after the collapse of Lehman Brothers in September 2008. Our robust results show that bank-specific shocks to Brazilian parent banks negatively affected lending by their individual branches and trigger real economic consequences in Brazilian municipalities: More affected regions face restrictions in aggregated credit and show weaker labor market performance in the aftermath which documents the transmission mechanism of the global financial crisis to local labor markets in emerging countries. The results represent relevant information for regulators concerned with the real effects of cross-border liquidity shocks.
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Foreign Funding Shocks and the Lending Channel: Do Foreign Banks Adjust Differently?
Felix Noth, Matias Ossandon Busch
Finance Research Letters,
November
2016
Abstract
We document for a set of Latin American emerging countries that the different nature of foreign funding accessed by foreign and local banks affected their lending performance after September 2008. We show that lending growth was weaker for shock-affected foreign banks compared to shock-affected local banks. This evidence represents valuable policy information for regulators concerned with the stability and well-functioning of banking sectors.
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To Invest or Not to Invest, That Is the Question: Analysis of Firm Behavior under Anticipated Shocks
Dejan Kovač, Nikola Kleut, Boris Podobnik, Vuk Vukovic
Plos One,
No. 8,
2016
Abstract
When companies are faced with an upcoming and expected economic shock some of them tend to react better than others. They adapt by initiating investments thus successfully weathering the storm, while others, even though they possess the same information set, fail to adopt the same business strategy and eventually succumb to the crisis. We use a unique setting of the recent financial crisis in Croatia as an exogenous shock that hit the country with a time lag, allowing the domestic firms to adapt. We perform a survival analysis on the entire population of 144,000 firms in Croatia during the period from 2003 to 2015, and test whether investment prior to the anticipated shock makes firms more likely to survive the recession. We find that small and micro firms, which decided to invest, had between 60 and 70% higher survival rates than similar firms that chose not to invest. This claim is supported by both non-parametric and parametric tests in the survival analysis. From a normative perspective this finding could be important in mitigating the negative effects on aggregate demand during strong recessionary periods.
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