Immigration and Entrepreneurship in the United States
American Economic Review: Insights,
Immigration can expand labor supply and create greater competition for native-born workers. But immigrants may also start new firms, expanding labor demand. This paper uses U.S. administrative data and other data resources to study the role of immigrants in entrepreneurship. We ask how often immigrants start companies, how many jobs these firms create, and how these firms compare with those founded by U.S.-born individuals. A simple model provides a measurement framework for addressing the dual roles of immigrants as founders and workers. The findings suggest that immigrants act more as "job creators" than "job takers" and that non-U.S. born founders play outsized roles in U.S. high-growth entrepreneurship
Robot Adoption at German Plants
IWH Discussion Papers,
Using a newly collected dataset of robot use at the plant level from 2014 to 2018, we provide the first microscopic portrait of robotisation in Germany and study the potential determinants of robot adoption. Our descriptive analysis uncovers five stylised facts concerning both extensive and, perhaps more importantly, intensive margin of plant-level robot use: (1) Robot use is relatively rare with only 1.55% German plants using robots in 2018. (2) The distribution of robots is highly skewed. (3) New robot adopters contribute substantially to the recent robotisation. (4) Robot users are exceptional along several dimensions of plant-level characteristics. (5) Heterogeneity in robot types matters. Our regression results further suggest plant size, low-skilled labour share, and exporter status to have strong and positive effect on future probability of robot adoption. Manufacturing plants impacted by the introduction of minimum wage in 2015 are also more likely to adopt robots. However, controlling for plant size, we find that plant-level productivity has no, if not negative, impact on robot adoption.
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Borrowers Under Water! Rare Disasters, Regional Banks, and Recovery Lending
Journal of Financial Intermediation,
We show that local banks provide corporate recovery lending to firms affected by adverse regional macro shocks. Banks that reside in counties unaffected by the natural disaster that we specify as macro shock increase lending to firms inside affected counties by 3%. Firms domiciled in flooded counties, in turn, increase corporate borrowing by 16% if they are connected to banks in unaffected counties. We find no indication that recovery lending entails excessive risk-taking or rent-seeking. However, within the group of shock-exposed banks, those without access to geographically more diversified interbank markets exhibit more credit risk and less equity capital.
Intangible Capital and Productivity. Firm-level Evidence from German Manufacturing
IWH Discussion Papers,
We study the importance of intangible capital (R&D, software, patents) for the measurement of productivity using firm-level panel data from German manufacturing. We first document a number of facts on the evolution of intangible investment over time, and its distribution across firms. Aggregate intangible investment increased over time. However, the distribution of intangible investment, even more so than that of physical investment, is heavily right-skewed, with many firms investing nothing or little, and a few firms having very large intensities. Intangible investment is also lumpy. Firms that invest more intensively in intangibles (per capita or as sales share) also tend to be more productive. In a second step, we estimate production functions with and without intangible capital using recent control function approaches to account for the simultaneity of input choice and unobserved productivity shocks. We find a positive output elasticity for research and development (R&D) and, to a lesser extent, software and patent investment. Moreover, the production function estimates show substantial heterogeneity in the output elasticities across industries and firms. While intangible capital has small effects for firms with low intangible intensity, there are strong positive effects for high-intensity firms. Finally, including intangibles in a gross output production function reduces productivity dispersion (measured by the 90-10 decile range) on average by 3%, in some industries as much as nearly 9%.
28.09.2017 • 36/2017
Aufschwung im Osten so stark wie in Deutschland insgesamt – Implikationen der Gemeinschaftsdiagnose Herbst 2017 für Ostdeutschland
Für das Jahr 2017 prognostiziert das Leibniz-Institut für Wirtschaftsforschung Halle (IWH) einen Anstieg des ostdeutschen Bruttoinlandsprodukts mit Berlin um 1,9% (Gemeinschaftsdiagnose für Deutschland insgesamt ebenfalls 1,9%). Der gegenüber dem Jahr 2016 (2,1%) etwas schwächere Zuwachs der Produktion resultiert lediglich aus der geringeren Anzahl von Arbeitstagen. Auch im Jahr 2018 dürfte die ostdeutsche Wirtschaft mit 2,0% so kräftig wie in Deutschland insgesamt zulegen.
Complex-task Biased Technological Change and the Labor Market
Review of Economic Dynamics,
In this paper we study the relationship between task complexity and the occupational wage- and employment structure. Complex tasks are defined as those requiring higher-order skills, such as the ability to abstract, solve problems, make decisions, or communicate effectively. We measure the task complexity of an occupation by performing Principal Component Analysis on a broad set of occupational descriptors in the Occupational Information Network (O*NET) data. We establish four main empirical facts for the U.S. over the 1980–2005 time period that are robust to the inclusion of a detailed set of controls, subsamples, and levels of aggregation: (1) There is a positive relationship across occupations between task complexity and wages and wage growth; (2) Conditional on task complexity, routine-intensity of an occupation is not a significant predictor of wage growth and wage levels; (3) Labor has reallocated from less complex to more complex occupations over time; (4) Within groups of occupations with similar task complexity labor has reallocated to non-routine occupations over time. We then formulate a model of Complex-Task Biased Technological Change with heterogeneous skills and show analytically that it can rationalize these facts. We conclude that workers in non-routine occupations with low ability of solving complex tasks are not shielded from the labor market effects of automatization.