A Note on the Use of Syndicated Loan Data
Isabella Müller, Felix Noth, Lena Tonzer
IWH Discussion Papers,
No. 17,
2022
Abstract
Syndicated loan data provided by DealScan is an essential input in banking research. This data is rich enough to answer urging questions on bank lending, e.g., in the presence of financial shocks or climate change. However, many data options raise the question of how to choose the estimation sample. We employ a standard regression framework analyzing bank lending during the financial crisis of 2007/08 to study how conventional but varying usages of DealScan affect the estimates. The key finding is that the direction of coefficients remains relatively robust. However, statistical significance depends on the data and sampling choice and we provide guidelines for applied research.
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On the Employment Consequences of Automation and Offshoring: A Labor Market Sorting View
Ester Faia, Sébastien Laffitte, Maximilian Mayer, Gianmarco Ottaviano
Lili Yan Ing, Gene M. Grossman (eds), Robots and AI: A New Economic Era. Routledge: London,
2022
Abstract
We argue that automation may make workers and firms more selective in matching their specialized skills and tasks. We call this phenomenon “core-biased technological change”, and wonder whether something similar could be relevant also for offshoring. Looking for evidence in occupational data for European industries, we find that automation increases workers’ and firms’ selectivity as captured by longer unemployment duration, less skill-task mismatch, and more concentration of specialized knowledge in specific tasks. This does not happen in the case of offshoring, though offshoring reinforces the effects of automation. We show that a labor market model with two-sided heterogeneity and search frictions can rationalize these empirical findings if automation strengthens while offshoring weakens the assortativity between workers’ skills and firms’ tasks in the production process, and automation and offshoring complement each other. Under these conditions, automation decreases employment and increases wage inequality whereas offshoring has opposite effects.
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Preferred Field of Study and Academic Performance
Francesco Berlingieri, André Diegmann, Maresa Sprietsma
Abstract
This paper investigates the impact of studying the first-choice university subject on dropout and switching field of study for a cohort of students in Germany. Using detailed survey data, and employing an instrumental variable strategy based on variation in the local field of study availability, we provide evidence that students who are not enrolled in their preferred field of study are more likely to change their field, delay graduation and drop out of university. The estimated impact on dropout is particularly strong among students of low socio-economic status and is driven by lower academic performance and motivation.
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The Place-based Effects of Police Stations on Crime: Evidence from Station Closures
Sebastian Blesse, André Diegmann
Journal of Public Economics,
March
2022
Abstract
Many countries consolidate their police forces by closing down local police stations. Police stations represent an important and visible aspect of the organization of police forces. We provide novel evidence on the effect of centralizing police offices through the closure of local police stations on crime outcomes. Combining matching with a difference-in-differences specification, we find an increase in reported car theft and burglary in residential properties. Our results are consistent with a negative shift in perceived detection risks and are driven by heterogeneous station characteristics. We can rule out alternative explanations such as incapacitation, crime displacement, and changes in police employment or strategies at the regional level. We argue that criminals are less deterred due to a lower visibility of the local police.
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Power Generation and Structural Change: Quantifying Economic Effects of the Coal Phase-out in Germany
Katja Heinisch, Oliver Holtemöller, Christoph Schult
Energy Economics,
2021
Abstract
In the fight against global warming, the reduction of greenhouse gas emissions is a major objective. In particular, a decrease in electricity generation by coal could contribute to reducing CO2 emissions. We study potential economic consequences of a coal phase-out in Germany, using a multi-region dynamic general equilibrium model. Four regional phase-out scenarios before the end of 2040 are simulated. We find that the worst case phase-out scenario would lead to an increase in the aggregate unemployment rate by about 0.13 [0.09 minimum; 0.18 maximum] percentage points from 2020 to 2040. The effect on regional unemployment rates varies between 0.18 [0.13; 0.22] and 1.07 [1.00; 1.13] percentage points in the lignite regions. A faster coal phase-out can lead to a faster recovery. The coal phase-out leads to migration from German lignite regions to German non-lignite regions and reduces the labour force in the lignite regions by 10,100 [6300; 12,300] people by 2040. A coal phase-out until 2035 is not worse in terms of welfare, consumption and employment compared to a coal-exit until 2040.
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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
Journal of Corporate Finance,
2021
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 provide evidence of monetary policy's impact on a nonbank financial institution's risk-taking. We find that the search-for-yield is the main driving force 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 greater riskiness of credit allocation. However, these changes do not necessarily relate to a larger loan amount on average.
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Evolvement of China-related Topics in Academic Accounting Research: Machine Learning Evidence
June Cao, Zhanzhong Gu, Iftekhar Hasan
China Accounting and Finance Review,
No. 4,
2020
Abstract
This study employs an unsupervised machine learning approach to explore the evolution of accounting research. We are particularly interested in exploring why international researchers and audiences are interested in China-related issues; what kinds of research topics related to China are mainly investigated in globally recognised journals; and what patterns and emerging topics can be explored by comprehensively analysing a big sample. Using a training sample of 23,220 articles from 46 accounting journals over the period 1980 to 2018, we first identify the optimal number of accounting research topics; the dynamic patterns of these accounting research topics are explored on the basis of 46 accounting journals to show changes in the focus of accounting research. Further, we collect articles related to Chinese accounting research from 18 accounting journals, eight finance journals, and eight management journals over the period 1980 to 2018. We objectively identify China-related accounting research topics and map them to the stages of China’s economic development. We attempt to identify the China-related issues global researchers are interested in and whether accounting research reflects the economic context. We use HistCite TM to generate a citation map along a timeline to illustrate the connections between topics. The citation clusters demonstrate “tribalism” phenomena in accounting research. The topics related to Chinese accounting research conducted by international accounting researchers reveal that accounting changes mirror economic reforms. Our findings indicate that accounting research is embedded in the economic context.
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Changing Business Dynamism and Productivity: Shocks versus Responsiveness
Ryan A. Decker, John Haltiwanger, Ron S. Jarmin, Javier Miranda
American Economic Review,
No. 12,
2020
Abstract
The pace of job reallocation has declined in the United States in recent decades. We draw insight from canonical models of business dynamics in which reallocation can decline due to (i) lower dispersion of idiosyncratic shocks faced by businesses, or (ii) weaker marginal responsiveness of businesses to shocks. We show that shock dispersion has actually risen, while the responsiveness of business-level employment to productivity has weakened. Moreover, declining responsiveness can account for a significant fraction of the decline in the pace of job reallocation, and we find suggestive evidence this has been a drag on aggregate productivity.
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Wages and the Value of Nonemployment
Simon Jäger, Benjamin Schoefer, Samuel Young, Josef Zweimüller
Quarterly Journal of Economics,
No. 4,
2020
Abstract
Nonemployment is often posited as a worker’s outside option in wage-setting models such as bargaining and wage posting. The value of nonemployment is therefore a key determinant of wages. We measure the wage effect of changes in the value of nonemployment among initially employed workers. Our quasi-experimental variation in the value of nonemployment arises from four large reforms of unemployment insurance (UI) benefit levels in Austria. We document that wages are insensitive to UI benefit changes: point estimates imply a wage response of less than $0.01 per $1.00 UI benefit increase, and we can reject sensitivities larger than $0.03. The insensitivity holds even among workers with low wages and high predicted unemployment duration, and among job switchers hired out of unemployment. The insensitivity of wages to the nonemployment value presents a puzzle to the widely used Nash bargaining model, which predicts a sensitivity of $0.24–$0.48. Our evidence supports wage-setting models that insulate wages from the value of nonemployment.
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Automation, Globalization and Vanishing Jobs: A Labor Market Sorting View
Ester Faia, Sébastien Laffitte, Maximilian Mayer, Gianmarco Ottaviano
IZA Discussion Paper,
No. 13267,
2020
Abstract
We show, theoretically and empirically, that the effects of technological change associated with automation and offshoring on the labor market can substantially deviate from standard neoclassical conclusions when search frictions hinder efficient assortative matching between firms with heterogeneous tasks and workers with heterogeneous skills. Our key hypothesis is that better matches enjoy a comparative advantage in exploiting automation and a comparative disadvantage in exploiting offshoring. It implies that automation (offshoring) may reduce (raise) employment by lengthening (shortening) unemployment duration due to higher (lower) match selectivity. We find empirical support for this implication in a dataset covering 92 occupations and 16 sectors in 13 European countries from 1995 to 2010.
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