Church Membership and Economic Recovery: Evidence from the 2005 Hurricane Season
Iftekhar Hasan, Stefano Manfredonia, Felix Noth
Economic Journal,
im Erscheinen
Abstract
This paper investigates the critical role of church membership in the process of economic recovery after high-impact natural disasters. We document a significant adverse treatment effect of the 2005 hurricane season in the Southeastern United States on establishment-level productivity. However, we find that establishments in counties with higher rates of church membership saw a significantly stronger recovery in terms of productivity for 2005–10. We also show that church membership is correlated with post-disaster entrepreneurship activities and population growth.
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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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Industry Mix, Local Labor Markets, and the Incidence of Trade Shocks
Steffen Müller, Jens Stegmaier, Moises Yi
Journal of Labor Economics,
Nr. 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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Risky Oil: It's All in the Tails
Christiane Baumeister, Florian Huber, Massimiliano Marcellino
NBER Working Paper,
Nr. 32524,
2024
Abstract
The substantial fluctuations in oil prices in the wake of the COVID-19 pandemic and the Russian invasion of Ukraine have highlighted the importance of tail events in the global market for crude oil which call for careful risk assessment. In this paper we focus on forecasting tail risks in the oil market by setting up a general empirical framework that allows for flexible predictive distributions of oil prices that can depart from normality. This model, based on Bayesian additive regression trees, remains agnostic on the functional form of the conditional mean relations and assumes that the shocks are driven by a stochastic volatility model. We show that our nonparametric approach improves in terms of tail forecasts upon three competing models: quantile regressions commonly used for studying tail events, the Bayesian VAR with stochastic volatility, and the simple random walk. We illustrate the practical relevance of our new approach by tracking the evolution of predictive densities during three recent economic and geopolitical crisis episodes, by developing consumer and producer distress indices that signal the build-up of upside and downside price risk, and by conducting a risk scenario analysis for 2024.
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The Long-term Legacy of the Liberation of the Sudetenland by the Red and US Armies
Jakub Grossmann, Štěpán Jurajda
IDEA CERGE EI Studie,
Nr. 7,
2022
Abstract
Forced migration results in trauma to the millions of people displaced from their homes, but very little is known about the fate of those who avoided expulsion and became a minority in the new society. This analysis reveals how and to what degree the manner and extent of the post-war expulsion of the German population from the Sudetenland influenced the country’s long-term social development. (This publication is written in czech language.)
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Do Public Bank Guarantees Affect Labor Market Outcomes? Evidence from Individual Employment and Wages
Laura Baessler, Georg Gebhardt, Reint E. Gropp, Andre Guettler, Ahmet Taskin
IWH Discussion Papers,
Nr. 7,
2024
Abstract
We investigate whether employees in Germany benefit from public bank guarantees in terms of employment probability and wages. To that end, we exploit the removal of public bank guarantees in Germany in 2001 as a quasi-natural experiment. Our results show that bank guarantees lead to higher employment, but lower wage prospects for employees after working in affected establishments. Overall the results suggest that employees do not benefit from bank guarantees.
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Forecasting Economic Activity Using a Neural Network in Uncertain Times: Monte Carlo Evidence and Application to the
German GDP
Oliver Holtemöller, Boris Kozyrev
IWH Discussion Papers,
Nr. 6,
2024
Abstract
In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an autoregressive benchmark model in many practically relevant cases. Then, we applied GRNN to forecast quarterly German GDP growth by extending univariate GRNN to multivariate and mixed-frequency settings. We could distinguish between “normal” times and situations where the time-series behavior is very different from “normal” times such as during the COVID-19 recession and recovery. GRNN was superior in terms of root mean forecast errors compared to an autoregressive model and to more sophisticated approaches such as dynamic factor models if applied appropriately.
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Supranational Rules, National Discretion: Increasing versus Inflating Regulatory Bank Capital?
Reint E. Gropp, Thomas Mosk, Steven Ongena, Ines Simac, Carlo Wix
Journal of Financial and Quantitative Analysis,
Nr. 2,
2024
Abstract
We study how banks use “regulatory adjustments” to inflate their regulatory capital ratios and whether this depends on forbearance on the part of national authorities. Using the 2011 EBA capital exercise as a quasi-natural experiment, we find that banks substantially inflated their levels of regulatory capital via a reduction in regulatory adjustments — without a commensurate increase in book equity and without a reduction in bank risk. We document substantial heterogeneity in regulatory capital inflation across countries, suggesting that national authorities forbear their domestic banks to meet supranational requirements, with a focus on short-term economic considerations.
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Climate Change Exposure and the Value Relevance of Earnings and Book Values of Equity
Iftekhar Hasan, Joseph A. Micale, Donna Rapaccioli
Journal of Sustainable Finance and Accounting,
March
2024
Abstract
We investigate whether a firm’s exposure to climate change, as proxied by disclosures during quarterly earnings conference calls, provides forward-looking information to investors regarding the long-term association of stock prices with current earnings and the book values of equity. Following a key regulatory mandate around the formation of the cap-and-trade program to reduce emissions related to climate change, firms’ climate change exposure decreases the association between current earnings and stock prices while increasing the relevance of book values of equity (i.e., historical earnings). However, these relationships flip when the sentiment around climate change exposure is negative, suggesting that the risks related to climate change exposure provide forward-looking information to investors when they evaluate the ability of current earnings to predict firm values. Such a relationship is stronger for new economy firms and is sensitive to conservative accounting. We also observe that the inclusion of climate change disclosure to our models improves the joint ability of earnings and book values to predict stock prices.
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