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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Gender Stereotypes still in MIND: Information on Relative Performance and Competition Entry
Sabrina Jeworrek
Journal of Behavioral and Experimental Economics,
October
2019
Abstract
By conducting a laboratory experiment, I test whether the gender tournament gap diminishes in its size after providing information on the relative performance of the two genders. Indeed, the gap shrinks sizeably, it even becomes statistically insignificant. Hence, individuals’ entry decisions seem to be driven not only by incorrect self-assessments in general but also by incorrect stereotypical beliefs about the genders’ average abilities. Overconfident men opt less often for the tournament and, thereby, increase their expected payoff. Overall efficiency, however, is not affected by the intervention.
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Drivers of Effort: Evidence from Employee Absenteeism
Morten Bennedsen, Margarita Tsoutsoura, Daniel Wolfenzon
Journal of Financial Economics,
No. 3,
2019
Abstract
We use detailed information on individual absent spells of all employees in 4140 firms in Denmark to show large differences in average absenteeism across firms. Using employees who switch firms, we decompose days absent into an individual component (e.g., motivation, work ethic) and a firm component (e.g., incentives, corporate culture). We find the firm component explains 50%–60% of the difference in absenteeism across firms, with the individual component explaining the rest. We present suggestive evidence of the mechanisms behind the firm effect with family firm status and concentrated ownership strongly correlated with decreases in absenteeism. We also analyze the firm characteristics that correlate with the individual effect and find that firms with stronger career incentives attract lower-absenteeism employees.
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What Drives Discretion in Bank Lending? Some Evidence and a Link to Private Information
Gene Ambrocio, Iftekhar Hasan
Journal of Banking and Finance,
2019
Abstract
We assess the extent to which discretion, unexplained variations in the terms of a loan contract, has varied across time and lending institutions and show that part of this discretion is due to private information that lenders have on their borrowers. We find that discretion is lower for secured loans and loans granted by a larger group of lenders, and is larger when the lenders are larger and more profitable. Over time, discretion is also lower around recessions although the private information content is higher. The results suggest that bank discretionary and private information acquisition behavior may be important features of the credit cycle.
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Flight from Safety: How a Change to the Deposit Insurance Limit Affects Households‘ Portfolio Allocation
H. Evren Damar, Reint E. Gropp, Adi Mordel
IWH Discussion Papers,
No. 19,
2019
Abstract
We study how an increase to the deposit insurance limit affects households‘ portfolio allocation by exogenously reducing uninsured deposit balances. Using unique data that identifies insured versus uninsured deposits, along with detailed information on Canadian households‘ portfolio holdings, we show that households respond by drawing down deposits and shifting towards mutual funds and stocks. These outflows amount to 2.8% of outstanding bank deposits. The empirical evidence, consistent with a standard portfolio choice model that is modified to accommodate uninsured deposits, indicates that more generous deposit insurance coverage results in nontrivial adjustments to household portfolios.
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How Forecast Accuracy Depends on Conditioning Assumptions
Carola Engelke, Katja Heinisch, Christoph Schult
IWH Discussion Papers,
No. 18,
2019
Abstract
This paper examines the extent to which errors in economic forecasts are driven by initial assumptions that prove to be incorrect ex post. Therefore, we construct a new data set comprising an unbalanced panel of annual forecasts from different institutions forecasting German GDP and the underlying assumptions. We explicitly control for different forecast horizons to proxy the information available at the release date. Over 75% of squared errors of the GDP forecast comove with the squared errors in their underlying assumptions. The root mean squared forecast error for GDP in our regression sample of 1.52% could be reduced to 1.13% by setting all assumption errors to zero. This implies that the accuracy of the assumptions is of great importance and that forecasters should reveal the framework of their assumptions in order to obtain useful policy recommendations based on economic forecasts.
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History, Microdata, and Endogenous Growth
Ufuk Akcigit, Tom Nicholas
Annual Review of Economics,
2019
Abstract
The study of economic growth is concerned with long-run changes, and therefore, historical data should be especially influential in informing the development of new theories. In this review, we draw on the recent literature to highlight areas in which study of history has played a particularly prominent role in improving our understanding of growth dynamics. Research at the intersection of historical data, theory, and empirics has the potential to reframe how we think about economic growth in much the same way that historical perspectives helped to shape the first generation of endogenous growth theories.
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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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Mission, Motivation, and the Active Decision to Work for a Social Cause
Sabrina Jeworrek, Vanessa Mertins
Abstract
The mission of a job does not only affect the type of worker attracted to an organisation, but may also provide incentives to an existing workforce. We conducted a natural field experiment with 267 short-time workers and randomly allocated them to either a prosocial or a commercial job. Our data suggest that the mission of a job itself has a performance enhancing motivational impact on particular individuals only, i.e., workers with a prosocial attitude. However, the mission is very important if it has been actively selected. Those workers who have chosen to contribute to a social cause outperform the ones randomly assigned to the same job by about 15 percent. This effect seems to be a universal phenomenon which is not driven by information about the alternative job, the choice itself or a particular subgroup.
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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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