Suchergebnisse

Die vorliegende Expertise verfolgte das Ziel, Datenbedarfe für die Evaluierung der Kapitel-1-Maßnahmen des InvKG abzuleiten. Die Evaluierung und die daraus entstehenden Datenbedarfe müssen sich in ein theoretisches Modell der ökonomischen Literatur zur Wirkung von Politikmaßnahmen einordnen lassen. Bei den Kapitel-1-Maßnahmen handelt es sich im weitesten Sinne um Investitionen in wirtschaftsnahe Infrastrukturen. Charakteristisch für Infrastrukturen ist, dass sie durch mittlere Zeiträume der Planung und Errichtung auf der einen sowie lange Nutzungszeiträume auf der anderen Seite gekennzeichnet sind. Hinzu kommt, dass die Phasen der Planung/Errichtung und der Nutzung Aspekte von Marktmängeln berühren. In der Praxis unterliegt dieser Bereich daher einer umfassenden staatlichen Regulierung.

Small and young businesses are essential for job creation, innovation, and economic growth. Even most of the superstar firms start their business life small and then grow over time. Small firms have less internal resources, which makes them more fragile and sensitive to macroeconomic conditions. This suggests the need for frequent and real-time monitoring of the small business sector's health. Previously this was difficult due to a lack of appropriate data. This paper fills this important gap by developing a new Intuit QuickBooks Small Business Index that focuses on the smallest of small businesses with at most 9 workers in the US and the UK and at most 19 workers in Canada. The Index aggregates a sample of anonymous QuickBooks Online Payroll subscriber data (QBO Payroll sample) from 333,000 businesses in the US, 66,000 in Canada, and 25,000 in the UK. After comparing the QBO Payroll sample data to the official statistics, we remove the seasonal components and use a Flexible Least Squares method to calibrate the QBO Payroll sample data against official statistics. Finally, we use the estimated model and the QBO Payroll sample data to generate a near real-time index of economic activity. We show that the estimated model performs well both in-sample and out-of-sample. Additionally, we use this analysis for different regions and industries.

Competition in the U.S. appears to have declined. One contributing factor may have been heterogeneity in the availability of credit during the financial crisis. I examine the impact of product market peer credit constraints on long-run competitive outcomes and behavior among non-financial firms. I use measures of lender exposure to the financial crisis to create a plausibly exogenous instrument for product market credit availability. I find that credit constraints of product market peers positively predict growth in sales, market share, profitability, and markups. This is consistent with the notion that firms gained at the expense of their credit constrained peers. The relationship is robust to accounting for other sources of inter-firm spillovers, namely credit access of technology network and supply chain peers. Further, I find evidence of strategic investment, i.e. the idea that firms increase investment in response to peer credit constraints to commit to deter entry mobility. This behavior may explain why temporary heterogeneity in the availability of credit appears to have resulted in a persistent redistribution of output across firms.

The standard economic model of occupational choice following a basic Roy model emphasizes individual selection and comparative advantage, but the sources of comparative advantage are not well understood. We employ a unique combination of Dutch survey and registry data that links math and language skills across generations and permits analysis of the intergenerational transmission of comparative skill advantages. Exploiting within-family between-subject variation in skills, we show that comparative advantages in math of parents are significantly linked to those of their children. A causal interpretation follows from a novel IV estimation that isolates variation in parent skill advantages due to their teacher and classroom peer quality. Finally, we show the strong influence of family skill transmission on children's choices of STEM fields.

The Roy-Borjas model predicts that international migrants are less educated than nonmigrants because the returns to education are generally higher in developing (migrant-sending) than in developed (migrant-receiving) countries. However, empirical evidence often shows the opposite. Using the case of Mexico-U.S. migration, we show that this inconsistency between predictions and empirical evidence can be resolved when the human capital of migrants is assessed using a two-dimensional measure of occupational skills rather than by educational attainment. Thus, focusing on a single skill dimension when investigating migrant selection can lead to misleading conclusions about the underlying economic incentives and behavioral models of migration.

We propose a novel mechanism through which established firms contribute to the startup ecosystem: the allocation of R&D tax credits to startups via the M&A channel. We show that when established firms become eligible for R&D tax credits, they increase their R&D and M&A activity. In particular, they acquire more venture capital (VC)-backed startups, but not non-VC-backed firms. Moreover, the impact of R&D tax credits on firms' R&D is increasing with their acquisition of VC-backed startups. The results suggest that established firms respond to R&D tax credits by acquiring startups rather than solely focusing on increasing their R&D intensity in-house. We also highlight evidence that startups do not appear to benefit from R&D tax credits directly, perhaps because they typically lack the taxable income necessary to directly benefit from the tax credits. In this context, established firms can play an intermediary role by acquiring startups and reallocating R&D tax credits, effectively relaxing the financial constraints faced by startups.

We conducted a field experiment in the natural setting of blood donations to test how oxytocin relates to empathy and altruism. We randomly assigned blood donors in the Croatian Institute for Transfusion Medicine to three groups with the aim to induce different levels of empathy by showing a neutral video to the donors from the control group and an emotional to the donors from the first and second treatment groups. In addition to watching the emotional video, donors from the second treatment group are given a gift which relates to the emotional story from the video. We find no effect of our treatment on induced levels of oxytocin. Null effects of our treatments could be explained by the above average baseline levels of oxytocin and inability of our treatments to provoke emotional stimuli in blood donors. Nonetheless, for our empathy measures we find the effect of gift exchange on empathic concerns, but not on perspective taking. After our experimental treatments, we followed the return of our blood donors for a whole year. We find that only variable which consistently predicts return for blood donation in stated period is the number of previous donations. From policy perspective it is an important finding. Especially for hospitals and other blood providers when faced with time and resource constraints.

We provide new insights into determinants of international interest rates spillovers across seven advanced economies. To disentangle and quantify their respective importance, we identify country-specific structural monetary policy, demand, and supply equations in a Bayesian structural panel vector autoregressive model. We formulate prior beliefs on magnitudes and signs of contemporaneous structural coefficients (i.e., (semi-)elasticities), based on a standard theoretical multi-country open economy model from the literature. Our findings show that interest rate spillovers occur via an aggregated demand channel. Unexpected monetary tightening causes modest declines in most foreign interest rates, while demand and supply shocks result in increased foreign interest rates. Our results support that central banks respond to changes in the domestic macroeconomic environment induced by domestic or foreign shocks rather than directly reacting to foreign shocks. Spillovers are quantitatively stronger for shocks originating in economically large areas with strong trade linkages.

The paper describes the "Halle Institute for Economic Research (IWH) Forecasting Dashboard (ForDas)". This tool aims at providing, on a non-commercial basis, historical and actual macroeconomic forecast data for the Germany economy to researchers and interested audiences. The database renders it possible to directly compare forecast quality across selected institutions and over time. It is partly based on data collected in the DFG-funded project "Macroeconomic Forecasts in Great Crises".

We provide the first causal evidence of discrimination against migrants seeking child care. We send emails from fictitious parents to > 18,000 early child care centers across Germany, asking if there is a slot available and how to apply. Randomly varying names to signal migration background, we find that migrants receive 4.4 percentage points fewer responses. Responses to migrants also contain substantially fewer slot offers, are shorter, and less encouraging. Exploring channels, discrimination against migrants does not differ by the perceived educational background of the email sender. However, it does differ by regional characteristics, being stronger in areas with lower shares of migrants in child care, higher right-wing vote shares, and lower financial resources. Discrimination on the child care market likely perpetuates existing inequalities of opportunities for disadvantaged children.

This paper contributes to a better understanding of the important role that credit demand plays for credit markets and aggregate macroeconomic developments as both a source and transmitter of economic shocks. I am the first to identify a structural credit demand equation together with credit supply, aggregate supply, demand and monetary policy in a Bayesian structural VAR. The model combines informative priors on structural coefficients and multiple external instruments to achieve identification. In order to improve identification of the credit demand shocks, I construct a new granular instrument from regional mortgage origination. I find that credit demand is quite elastic with respect to contemporaneous macro-economic conditions, while credit supply is relatively inelastic. I show that credit supply and demand shocks matter for aggregate fluctuations, albeit at different times: credit demand shocks mostly drove the boom prior to the financial crisis, while credit supply shocks were responsible during and after the crisis itself. In an out-of-sample exercise, I find that the Covid pandemic induced a large expansion of credit demand in 2020Q2, which pushed the US economy towards a sustained recovery and helped to avoid a stagflationary scenario in 2022.

This paper studies the role of social connections in shaping individuals' concerns about climate change. I combine granular climate data, region-level social network data and survey responses for 24 European countries in order to document large information spillovers. Individuals become more concerned about climate change when their geographically distant friends living in sociallyconnected regions have experienced large increases in temperatures since 1990. Exploring the heterogeneity of the spillover effects, I uncover that the learning via social networks plays a central role. Further, results illustrate the important role of social values and economic preferences for understanding how information spillovers affect individual concerns.

We use data from the Annual Survey of Manufactures to study the characteristics and geography of investments in robots across U.S. manufacturing establishments. We find that robotics adoption and robot intensity (the number of robots per employee) is much more strongly related to establishment size than age. We find that establishments that report having robotics have higher capital expenditures, including higher information technology (IT) capital expenditures. Also, establishments are more likely to have robotics if other establishments in the same Core-Based Statistical Area (CBSA) and industry also report having robotics. The distribution of robots is highly skewed across establishments' locations. Some locations, which we call Robot Hubs, have far more robots than one would expect even after accounting for industry and manufacturing employment. We characterize these Robot Hubs along several industry, demographic, and institutional dimensions. The presence of robot integrators and higher levels of union membership are positively correlated with being a Robot Hub.

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.