Reassessing EU Comparative Advantage: The Role of Technology
Filippo di Mauro, Marco Matani, Gianmarco Ottaviano
IWH-CompNet Discussion Papers,
No. 2,
2024
Abstract
Based on the sufficient statistics approach developed by Huang and Ottaviano (2024), we show how the state of technology of European industries relative to the rest of the world can be empirically assessed in a way that is simple in terms of computation, parsimonious in terms of data requirements, but still comprehensive in terms of information. The lack of systematic cross-industry correlation between export specialization and technological advantage suggests that standard measures of revealed comparative advantage only imperfectly capture a country’s technological prowess due to the concurrent influences of factor prices, market size, markups, firm selection and market share reallocation.
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Reassessing EU Comparative Advantage: The Role of Technology
Filippo di Mauro, Marco Matani, Gianmarco Ottaviano
IWH Discussion Papers,
No. 26,
2024
Abstract
Based on the sufficient statistics approach developed by Huang and Ottaviano (2024), we show how the state of technology of European industries relative to the rest of the world can be empirically assessed in a way that is simple in terms of computation, parsimonious in terms of data requirements, but still comprehensive in terms of information. The lack of systematic cross-industry correlation between export specialization and technological advantage suggests that standard measures of revealed comparative advantage only imperfectly capture a country’s technological prowess due to the concurrent influences of factor prices, market size, markups, firm selection and market share reallocation.
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A Multi-Model Assessment of Inequality and Climate Change
Marie Young-Brun, et al.
Nature Climate Change,
October
2024
Abstract
Climate change and inequality are critical and interrelated defining issues for this century. Despite growing empirical evidence on the economic incidence of climate policies and impacts, mainstream model-based assessments are often silent on the interplay between climate change and economic inequality. For example, all the major model comparisons reviewed in IPCC neglect within-country inequalities. Here we fill this gap by presenting a model ensemble of eight large-scale Integrated Assessment Models belonging to different model paradigms and featuring economic heterogeneity. We study the distributional implications of Paris-aligned climate target of 1.5 degree and include different carbon revenue redistribution schemes. Moreover, we account for the economic inequalities resulting from residual and avoided climate impacts. We find that price-based climate policies without compensatory measures increase economic inequality in most countries and across models. However, revenue redistribution through equal per-capita transfers can offset this effect, leading to on average decrease in the Gini index by almost two points. When climate benefits are included, inequality is further reduced, but only in the long term. Around mid-century, the combination of dried-up carbon revenues and yet limited climate benefits leads to higher inequality under the Paris target than in the Reference scenario, indicating the need for further policy measures in the medium term.
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Training, Automation, and Wages: International Worker-level Evidence
Oliver Falck, Yuchen Guo, Christina Langer, Valentin Lindlacher, Simon Wiederhold
CESifo Working Papers,
No. 11533,
2024
Abstract
Job training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of automation risk based on tasks performed at work. Our analysis reveals substantial within-occupation variation in automation risk, overlooked by existing occupation-level measures. To assess whether job training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without job training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that job training reduces workers’ automation risk by 4.7 percentage points, equivalent to 10 percent of the average automation risk. The training-induced reduction in automation risk accounts for one-fifth of the wage returns to job training. Job training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Women tend to benefit more from training than men, with the advantage becoming particularly pronounced at older ages.
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Climate-resilient Economic Development in Vietnam: Insights from a Dynamic General Equilibrium Analysis (DGE-CRED)
Andrej Drygalla, Katja Heinisch, Christoph Schult
IWH Technical Reports,
No. 1,
2024
Abstract
In a multi-sector and multi-region framework, this paper employs a dynamic general equilibrium model to analyze climate-resilient economic development (DGE-CRED) in Vietnam. We calibrate sector and region-specific damage functions and quantify climate variable impacts on productivity and capital formation for various shared socioeconomic pathways (SSPs 119, 245, and 585). Our results based on simulations and cost-benefit analyses reveal a projected 5 percent reduction in annual GDP by 2050 in the SSP 245 scenario. Adaptation measures for the dyke system are crucial to mitigate the consumption gap, but they alone cannot sufficiently address it. Climate-induced damages to agriculture and labor productivity are the primary drivers of consumption reductions, underscoring the need for focused adaptation measures in the agricultural sector and strategies to reduce labor intensity as vital policy considerations for Vietnam’s response to climate change.
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Productivity, Place, and Plants
Benjamin Schoefer, Oren Ziv
Review of Economics and Statistics,
No. 5,
2024
Abstract
Why do cities differ so much in productivity? A long literature has sought out systematic sources, such as inherent productivity advantages, market access, agglomeration forces, or sorting. We document that up to three quarters of the measured regional productivity dispersion is spurious, reflecting the “luck of the draw” of finite counts of idiosyncratically heterogeneous plants that happen to operate in a given location. The patterns are even more pronounced for new plants, hold for alternative productivity measures, and broadly extend to European countries. This large role for individual plants suggests a smaller role for places in driving regional differences.
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Industry Mix, Local Labor Markets, and the Incidence of Trade Shocks
Steffen Müller, Jens Stegmaier, Moises Yi
Journal of Labor Economics,
No. 3,
2024
Abstract
We analyze how skill transferability and the local industry mix affect the adjustment costs of workers hit by a trade shock. Using German administrative data and novel measures of economic distance we construct an index of labor market absorptiveness that captures the degree to which workers from a particular industry are able to reallocate into other jobs. Among manufacturing workers, we find that the earnings loss associated with increased import exposure is much higher for those who live in the least absorptive regions. We conclude that the local industry composition plays an important role in the adjustment processes of workers.
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State Ownership and Financial Statement Comparability
William Francis, Xian Gu, Iftekhar Hasan, Joon Ho Kong
Journal of Business Finance and Accounting,
No. 7,
2024
Abstract
This paper investigates how state ownership affects financial reporting practices in China. Using several measures of state (government) ownership, we show that a one-standard-deviation increase in state ownership decreases financial statement comparability by 36.61%, and the impact is more pronounced when the central authority has majority control of the company. Moreover, lower earnings quality and lower levels of accounting conservatism among state-owned enterprises (SOEs) may explain the lower accounting comparability between SOEs and non-SOEs (NSOEs). Additionally, similar (different) managerial objectives converge (diverge) financial statement comparability between SOEs and NSOEs. Last, the geographical locations of firms also contribute to financial statement comparability. We employ a difference-in-differences design, changes regression and entropy balancing to mitigate potential endogeneity bias.
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Non-Standard Errors
Albert J. Menkveld, Anna Dreber, Felix Holzmeister, Juergen Huber, Magnus Johannesson, Michael Koetter, Markus Kirchner, Sebastian Neusüss, Michael Razen, Utz Weitzel, Shuo Xia, et al.
Journal of Finance,
No. 3,
2024
Abstract
In statistics, samples are drawn from a population in a datagenerating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidencegenerating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
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COVID-19 and Political Preferences Through Stages of the Pandemic: The Case of the Czech Republic
Alena Bičáková, Štěpán Jurajda
Abstract
We track the effects of the COVID-19 pandemic on political preferences through ‘high’ and ‘low’ phases of the pandemic. We ask about the effects of the health and the economic costs of the pandemic measured at both personal and municipality levels. Consistent with the literature, we estimate effects suggestive of political accountability of leaders during ‘high’ pandemic phases. However, we also find that the pandemic political accountability effects are mostly short-lived, and do not extend to the first post-pandemic elections.
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