Distributional Income Effects of Banking Regulation in Europe
Lars Brausewetter, Melina Ludolph, Lena Tonzer
IWH Discussion Papers,
Nr. 24,
2023
Abstract
We study the impact of stricter and more harmonized banking regulation along the income distribution using household survey data for 25 EU countries. Exploiting country-level heterogeneity in the implementation of European Banking Union directives allows us to control for confounders and identify effects. Our results show that these regulatory reforms aimed at increasing financial system resilience affected households heterogeneously. More stringent regulation reduces income growth for low-income households due to employment exits. Yet it tends to increase growth rates at the top of the distribution both for employee and self-employed income.
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Chinesische Massenimporte stärken extreme Parteien Die Globalisierung hat den politischen Rändern in Europa...
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Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one...
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Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one...
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LRF Research Profile
Research Profile of the Department of Laws, Regulations and Factor Markets The ...
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Das IWH auf der ASSA-Jahrestagung 2020 in San Diego
Das IWH auf der ASSA-Jahrestagung 2020 in San Diego Die American Economic...
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Globalization, Productivity Growth, and Labor Compensation
Christian Dreger, Marius Fourné, Oliver Holtemöller
IWH Discussion Papers,
Nr. 7,
2022
Abstract
We analyze how changes in international trade integration affect productivity and the functional income distribution. To account for endogeneity, we construct a leaveout measure for international trade integration for country-industry pairs using international input-output tables. Our findings corroborate on the country-industry level that international trade integration increases productivity. Moreover, we show that both trade in intermediate inputs and trade in value added is associated with lower labor shares in emerging markets. For advanced countries, we document a positive effect of trade in value added on the labor share of income. Further, we show that the effects on productivity and labor share are heterogeneous across different sectors. Finally, we discuss the implications of our results for a possible throwback in international trade integration due to experiences from recent crises.
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Measuring and Accounting for Innovation in the Twenty-First Century
Carol Corrado, Jonathan Haskel, Javier Miranda, Daniel Sichel
NBER Studies in Income and Wealth,
2021
Abstract
Measuring innovation is challenging both for researchers and for national statisticians, and it is increasingly important in light of the ongoing digital revolution. National accounts and many other economic statistics were designed before the emergence of the digital economy and the growing importance of intangible capital. They do not yet fully capture the wide range of innovative activity that is observed in modern economies.
This volume examines how to measure innovation, track its effects on economic activity and prices, and understand how it has changed the structure of production processes, labor markets, and organizational form and operation in business. The contributors explore new approaches to, and data sources for, measurement—such as collecting data for a particular innovation as opposed to a firm, and the use of trademarks for tracking innovation. They also consider the connections between university-based R&D and business startups, and the potential impacts of innovation on income distribution.
The research suggests potential strategies for expanding current measurement frameworks to better capture innovative activity, such as more detailed tracking of global value chains to identify innovation across time and space, and expanding the measurement of the GDP impacts of innovation in fields such as consumer content delivery and cloud computing.
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Introduction to "Measuring and Accounting for Innovation in the Twenty-First Century"
Javier Miranda
Measuring and Accounting for Innovation in the Twenty-First Century,
NBER Studies in Income and Wealth, Vol 78 /
2021
Abstract
Measuring innovation is challenging both for researchers and for national statisticians, and it is increasingly important in light of the ongoing digital revolution. National accounts and many other economic statistics were designed before the emergence of the digital economy and the growing importance of intangible capital. They do not yet fully capture the wide range of innovative activity that is observed in modern economies. This volume examines how to measure innovation, track its effects on economic activity and prices, and understand how it has changed the structure of production processes, labor markets, and organizational form and operation in business. The contributors explore new approaches to, and data sources for, measurement—such as collecting data for a particular innovation as opposed to a firm, and the use of trademarks for tracking innovation. They also consider the connections between university-based R&D and business startups, and the potential impacts of innovation on income distribution. The research suggests potential strategies for expanding current measurement frameworks to better capture innovative activity, such as more detailed tracking of global value chains to identify innovation across time and space, and expanding the measurement of the GDP impacts of innovation in fields such as consumer content delivery and cloud computing.
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HIP, RIP, and the Robustness of Empirical Earnings Processes
Florian Hoffmann
Quantitative Economics,
Nr. 3,
2019
Abstract
The dispersion of individual returns to experience, often referred to as heterogeneity of income profiles (HIP), is a key parameter in empirical human capital models, in studies of life‐cycle income inequality, and in heterogeneous agent models of life‐cycle labor market dynamics. It is commonly estimated from age variation in the covariance structure of earnings. In this study, I show that this approach is invalid and tends to deliver estimates of HIP that are biased upward. The reason is that any age variation in covariance structures can be rationalized by age‐dependent heteroscedasticity in the distribution of earnings shocks. Once one models such age effects flexibly the remaining identifying variation for HIP is the shape of the tails of lag profiles. Credible estimation of HIP thus imposes strong demands on the data since one requires many earnings observations per individual and a low rate of sample attrition. To investigate empirically whether the bias in estimates of HIP from omitting age effects is quantitatively important, I thus rely on administrative data from Germany on quarterly earnings that follow workers from labor market entry until 27 years into their career. To strengthen external validity, I focus my analysis on an education group that displays a covariance structure with qualitatively similar properties like its North American counterpart. I find that a HIP model with age effects in transitory, persistent and permanent shocks fits the covariance structure almost perfectly and delivers small and insignificant estimates for the HIP component. In sharp contrast, once I estimate a standard HIP model without age‐effects the estimated slope heterogeneity increases by a factor of thirteen and becomes highly significant, with a dramatic deterioration of model fit. I reach the same conclusions from estimating the two models on a different covariance structure and from conducting a Monte Carlo analysis, suggesting that my quantitative results are not an artifact of one particular sample.
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