Medienanfragen richten Sie bitte an:
Telefon: +49 345 7753-720
Email: presse@iwh-halle.de
Team Kommunikation
Unsägliche Industriepolitik und ein übergriffiger StaatReint GroppThe Pioneer, 1. März 2025
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.
The Transition Report 2024-25 focuses on industrial policies in the EBRD regions and beyond. Such policies have seen a resurgence, seeking to address market failures such as environmental degradation. However, their track record is mixed. Their growing popularity is shaped primarily by domestic political economy considerations and rising geopolitical tensions. While industrial policies are typically employed by higher-income economies, they are also now used more frequently in economies with less administrative and fiscal capacity to implement them.
This paper analyzes the distribution and composition of pre-tax national income in Germany since 1992, combining personal income tax returns, household survey data, and national accounts. Inequality rose from the 1990s to the late 2000s due to falling labor incomes among the bottom 50% and rising incomes in the top 10%. This trend reversed after 2007 as labor incomes across the bottom 90% increased. The top 1% income share, dominated by business income, remained relatively stable between 1992 and 2019. A large share of Germany’s top 1% earners are non-corporate business owners in labor-intensive professions. At least half of the business owners in P99-99.9 and a quarter in the top 0.1% operate firms in professional services – a pattern mirroring the United States. From 1992 to 2019, Germany’s top 0.1% income concentration exceeded France’s and matched U.S. levels until the late 2000s.
We document and dissect a new stylized fact about firm growth: the shift from labor to intermediate inputs. This shift occurs in input quantities, cost and output shares, and output elasticities. We establish this fact using German firm-level data and replicate it in administrative firm data from 11 additional countries. We also document these patterns in micro-aggregated industry data for 20 European countries (and, with respect to industry cost shares, for the US). We rationalize this novel regularity within a parsimonious model featuring (i) an elasticity of substitution between intermediates and labor that exceeds unity, and (ii) an increasing shadow price of labor relative to intermediates, due to monopsony power over labor or labor adjustment costs. The shift from labor to intermediates accounts for one half to one third of the decline in the labor share in growing firms (the remainder is due to wage markdowns and markups) and rationalizes most of the labor share decline in growing industries.
Choosing a university and field of study is a key life decision that influences one’s lifelong earnings trajectory. Data shows that the share of individuals going to university is unequally distributed, and is lower among disadvantaged students. High-achieving students who are low income are less likely to opt for ambitious education paths, despite the high returns of education. Even among those students who decide to apply for college, the likelihood of whether they will apply to prestigious colleges or renowned study programs differs along the distribution of socioeconomic background. It does not only matter if you study, but also what and where you study, as there is a large variation in long-run outcomes, such as earnings, both between universities as well as between fields of study. Part of this mismatch can be attributed to unequal starting points for children, in terms of both institutional settings and the quality of information available within their close networks.
We compare the effects of external financing shocks on patient mortality at nonprofit and for-profit hospitals. Using confidential patient-level data, we find that patient mortality increases to a lesser extent at nonprofit hospitals than at for-profit ones facing exogenous, negative shocks to debt capacity. Such an effect is not driven by patient characteristics or their choices of hospitals. It is concentrated among patients without private insurance and patients with higher-risk diagnoses. Potential economic mechanisms include nonprofit hospitals' having deeper cash reserves and greater ability to maintain spending on medical staff and equipment, even at the expense of lower profitability. Overall, our evidence suggests that nonprofit organizations can better serve social interests during financially challenging times.
Der deutsche Konjunkturmotor stottert weiter vor sich hin. Obwohl das Bruttoinlandsprodukt (BIP) im dritten Quartal 2024 um 0,2% zunahm, liegt es immer noch unter dem Niveau vom ersten Quartal 2024, da das zweite Quartal nach neuesten Zahlen weitaus schwächer ausgefallen ist als zuvor gemeldet (vgl. Abbildung 1). Der leichte Zuwachs im dritten Quartal dürfte dabei vor allem auf gestiegene staatliche und private Konsumausgaben zurückzuführen sein. In den Unternehmen ist die Stimmung weiterhin trüb und die wirtschaftspolitische Unsicherheit dürfte weiterhin hoch bleiben. Zudem belasten nach wie vor gestiegene Energie- und Lohnkosten die Investitionsbereitschaft der Unternehmen. Alles in allem dürfte das Bruttoinlandsprodukt (BIP) laut IWH-Flash-Indikator im vierten Quartal 2024 stagnieren. Für den Jahresbeginn 2025 deuten allerdings die Frühindikatoren auf eine Belebung der wirtschaftlichen Aktivitäten und einen Anstieg des BIP um 0,4% hin. Diese reflektieren jedoch noch nicht die jüngsten politischen Ereignisse in den USA und in Deutschland.
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.
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.
