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Can Germany’s economy stage an unexpected recovery?Steffen MüllerThe Economist, January 30, 2025
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.
The chief human resource officer (CHRO) role elevates people-related matters to the apex of the firm. Why do some companies’ leading management teams place so much emphasis on human resources while others do not? The present study argues that CHROs’ presence in the C-suite is driven by firms’ imitation of industry peers’ leadership structures as a response to uncertainty. The investigation also sheds light on the moderating role of environmental factors that can influence mimetic isomorphism in HR leadership. Through a longitudinal analysis of large listed firms between 2006 and 2020, the study shows a positive relationship between the prevalence of the CHRO position among firms’ peers and a focal firm having a CHRO in its top management. The results demonstrate that certain types of uncertainty serve as boundary conditions for such copying actions: Industry growth strengthens mimicking behavior while industry dynamism weakens it. There is no clear evidence for the moderating role of industry competition. The findings contribute a neo-institutional view of human resource structures in the top management and strengthen the bond between the strategy and human resource literature.
This paper provides a comprehensive analysis of the forecastability of the real price of natural gas in the United States at the monthly frequency considering a universe of models that differ in their complexity and economic content. Our key finding is that considerable reductions in mean-squared prediction error relative to a random walk benchmark can be achieved in real time for forecast horizons of up to two years. A particularly promising model is a six-variable Bayesian vector autoregressive model that includes the fundamental determinants of the supply and demand for natural gas. To capture real-time data constraints of these and other predictor variables, we assemble a rich database of historical vintages from multiple sources. We also compare our model-based forecasts to readily available model-free forecasts provided by experts and futures markets. Given that no single forecasting method dominates all others, we explore the usefulness of pooling forecasts and find that combining forecasts from individual models selected in real time based on their most recent performance delivers the most accurate forecasts.
Kinder mit Migrationshintergrund besuchen im Vergleich zu Kindern ohne Migrationshintergrund deutlich seltener Kindertagesstätten (Kitas), obwohl gerade sie von einem Kitabesuch besonders profitieren würden. Ist sich die Bevölkerung dieser Diskrepanz bewusst? Und wie steht sie zu verschiedenen politischen Maßnahmen, die dieses Problem angehen? Wir untersuchen, ob Informationen über Ungleichheiten und Diskriminierung in der frühkindlichen Betreuung die Zustimmung der Bevölkerung zu gleichheitsfördernden Politikmaßnahmen beeinflussen. Dafür befragen wir 4 800 repräsentativ ausgewählte Personen aus der deutschen Bevölkerung. Es zeigt sich, dass die Befragten oft erhebliche Fehleinschätzungen über das Ausmaß der Ungleichheiten und Diskriminierung beim Kitazugang zwischen Familien mit und ohne Migrationshintergrund haben. Zufällig bereitgestellte Informationen über das tatsächliche Ausmaß dieser Diskrepanzen verringern die politische Polarisierung, d.h. Unterschiede in der Zustimmung zu Unterstützungsmaßnahmen für Familien mit Migrationshintergrund. Unsere Ergebnisse legen nahe, dass verzerrte Wahrnehmungen sozialer Ungleichheiten zu Meinungsunterschieden in der Bevölkerung beitragen. Ein besserer Informationsstand in der Bevölkerung könnte diese Polarisierung in der Zustimmung zu gleichheitsfördernden Politikmaßnahmen beim Zugang zu Kitas verringern.
The European Commission’s growth forecasts play a crucial role in shaping policies and provide a benchmark for many (national) forecasters. The annual forecasts are built on quarterly estimates, which do not receive much attention and are hardly known. Therefore, this paper provides a comprehensive analysis of multi-period ahead quarterly GDP growth forecasts for the European Union (EU), euro area, and several EU member states with respect to first-release and current-release data. Forecast revisions and forecast errors are analyzed, and the results show that the forecasts are not systematically biased. However, GDP forecasts for several member states tend to be overestimated at short-time horizons. Furthermore, the final forecast revision in the current quarter is generally downward biased for almost all countries. Overall, the differences in mean forecast errors are minor when using real-time data or pseudo-real-time data and these differences do not significantly impact the overall assessment of the forecasts’ quality. Additionally, the forecast performance varies across countries, with smaller countries and Central and Eastern European countries (CEECs) experiencing larger forecast errors. The paper provides evidence that there is still potential for improvement in forecasting techniques both for nowcasts but also forecasts up to eight quarters ahead. In the latter case, the performance of the mean forecast tends to be superior for many countries.
This paper investigates forecast aggregation via the random subspace regressions method (RSM) and explores the potential link between RSM and the Shapley value decomposition (SVD) using the US GDP growth rates. This technique combination enables handling high-dimensional data and reveals the relative importance of each individual forecast. First, it is possible to enhance forecasting performance in certain practical instances by randomly selecting smaller subsets of individual forecasts and obtaining a new set of predictions based on a regression-based weighting scheme. The optimal value of selected individual forecasts is also empirically studied. Then, a connection between RSM and SVD is proposed, enabling the examination of each individual forecast’s contribution to the final prediction, even when there is a large number of forecasts. This approach is model-agnostic (can be applied to any set of predictions) and facilitates understanding of how the aggregated prediction is obtained based on individual forecasts, which is crucial for decision-makers.
Die deutsche Wirtschaft steht unter Druck, doch die aktuellen Maßnahmen der Regierung führen kaum zu einer nachhaltigen Erholung. Unternehmen sind mit Unsicherheiten konfrontiert, die Investitionen hemmen – insbesondere hinsichtlich der Energieversorgung und der damit verbundenen Kosten. Viele Betriebe schieben deshalb notwendige Investitionen auf – genau die Investitionen, die das wirtschaftliche Wachstum antreiben könnten.
