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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What Does Peer-to-Peer Lending Evidence Say About the Risk-taking Channel of Monetary Policy?
Yiping Huang, Xiang Li, Chu Wang
Abstract
This paper uses loan application-level data from a peer-to-peer lending platform to study the risk-taking channel of monetary policy. By employing a direct ex-ante measure of risk-taking and estimating the simultaneous equations of loan approval and loan amount, we are the first to provide quantitative evidence of the impact of monetary policy on the risk-taking of nonbank financial institution. We find that the search-for-yield is the main workhorse of the risk-taking effect, while we do not observe consistent findings of risk-shifting from the liquidity change. Monetary policy easing is associated with a higher probability of granting loans to risky borrowers and a greater riskiness of credit allocation, but these changes do not necessarily relate to a larger loan amount on average.
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Predicting Free-riding in a Public Goods Game – Analysis of Content and Dynamic Facial Expressions in Face-to-Face Communication
Dmitri Bershadskyy, Ehsan Othman, Frerk Saxen
IWH Discussion Papers,
No. 9,
2019
Abstract
This paper illustrates how audio-visual data from pre-play face-to-face communication can be used to identify groups which contain free-riders in a public goods experiment. It focuses on two channels over which face-to-face communication influences contributions to a public good. Firstly, the contents of the face-to-face communication are investigated by categorising specific strategic information and using simple meta-data. Secondly, a machine-learning approach to analyse facial expressions of the subjects during their communications is implemented. These approaches constitute the first of their kind, analysing content and facial expressions in face-to-face communication aiming to predict the behaviour of the subjects in a public goods game. The analysis shows that verbally mentioning to fully contribute to the public good until the very end and communicating through facial clues reduce the commonly observed end-game behaviour. The length of the face-to-face communication quantified in number of words is further a good measure to predict cooperation behaviour towards the end of the game. The obtained findings provide first insights how a priori available information can be utilised to predict free-riding behaviour in public goods games.
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Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks
Christiane Baumeister, James D. Hamilton
American Economic Review,
No. 5,
2019
Abstract
Traditional approaches to structural vector autoregressions (VARs) can be viewed as special cases of Bayesian inference arising from very strong prior beliefs. These methods can be generalized with a less restrictive formulation that incorporates uncertainty about the identifying assumptions themselves. We use this approach to revisit the importance of shocks to oil supply and demand. Supply disruptions turn out to be a bigger factor in historical oil price movements and inventory accumulation a smaller factor than implied by earlier estimates. Supply shocks lead to a reduction in global economic activity after a significant lag, whereas shocks to oil demand do not.
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National Culture and Risk-taking: Evidence from the Insurance Industry
Chrysovalantis Gaganis, Iftekhar Hasan, Panagiota Papadimitri, Menelaos Tasiou
Journal of Business Research,
April
2019
Abstract
The gravity of insurance within the financial sector is constantly increasing. Reasonably, after the events of the recent financial turmoil, the domain of research that examines the factors driving the risk-taking of this industry has been signified. The purpose of the present study is to investigate the interplay between national culture and risk of insurance firms. We quantify the cultural overtones, measuring national culture considering the dimensions outlined by the Hofstede model and risk-taking using the ‘Z-score’. In a sample consisting of 801 life and non-life insurance firms operating across 42 countries over the period 2007–2016, we find a strong and significant relationship among insurance firms' risk-taking and cultural characteristics, such as individualism, uncertainty avoidance and power distance. Results remain robust to a variety of firm and country-specific controls, alternative measures of risk, sample specifications and tests designed to alleviate endogeneity.
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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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Innovation and Top Income Inequality
Philippe Aghion, Ufuk Akcigit, Antonin Bergeaud, Richard Blundell, David Hemous
Review of Economic Studies,
No. 1,
2019
Abstract
In this article, we use cross-state panel and cross-U.S. commuting-zone data to look at the relationship between innovation, top income inequality and social mobility. We find positive correlations between measures of innovation and top income inequality. We also show that the correlations between innovation and broad measures of inequality are not significant. Next, using instrumental variable analysis, we argue that these correlations at least partly reflect a causality from innovation to top income shares. Finally, we show that innovation, particularly by new entrants, is positively associated with social mobility, but less so in local areas with more intense lobbying activities.
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Zu den rentenpolitischen Plänen im Koalitionsvertrag 2018 von CDU, CSU und SPD: Konsequenzen, Finanzierungsoptionen und Reformbedarf
Oliver Holtemöller, Christoph Schult, Götz Zeddies
Zeitschrift für Wirtschaftspolitik,
No. 3,
2018
Abstract
In the coalition agreement from February 7, 2018, the new German federal government drafts its public pension policy, which has to be evaluated against the background of demographic dynamics in Germany. In this paper, the consequences of public pensions related policy measures for the German public pension insurance are illustrated using a simulation model. In the long run, the intended extensions of benefits would lead to an increase in the contribution rate to the German public pension insurance of about two and a half percentage points. Referring to pension systems of other countries, we discuss measures in order to limit this increase in the contribution rate.
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A Market-based Measure for Currency Risk in Managed Exchange Rate Regimes
Stefan Eichler, Ingmar Roevekamp
Journal of International Financial Markets, Institutions and Money,
November
2018
Abstract
We introduce a novel currency risk measure based on American Depositary Receipts (ADRs). Using an augmented ADR pricing model, we exploit investors’ exposure to potential devaluation losses to derive an indicator of currency risk. Using weekly data for a sample of 807 ADRs located in 21 emerging markets over the 1994–2014 period, we find that a deterioration in the fiscal balance and higher inflation increase currency risk. Interaction models reveal that the fiscal balance and inflation drive the determination of currency risk for countries with poor sovereign rating, low foreign reserves, low capital account openness and managed float regimes.
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