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The Characteristics and Geographic Distribution of Robot Hubs in U.S. Manufacturing Establishments
Erik Brynjolfsson, Catherine Buffington, Nathan Goldschlag, J. Frank Li, Javier Miranda, Robert Seamans
Abstract
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.
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BigTech Credit, Small Business, and Monetary Policy Transmission: Theory and Evidence
Yiping Huang, Xiang Li, Han Qiu, Dan Su, Changhua Yu
IWH Discussion Papers,
No. 18,
2022
Abstract
This paper provides both theoretical and empirical analyses of the differences between BigTech lenders and traditional banks in response to monetary policy changes. Our model integrates Knightian uncertainty into portfolio selection and posits that BigTech lenders possess a diminishing informational advantage with increasing firm size, resulting in reduced ambiguity when lending to smaller firms. The model suggests that the key distinction between BigTech lenders and traditional banks in response to shifts in funding costs, triggered by monetary policy changes, is more evident at the extensive margin rather than the intensive margin, particularly during periods of easing monetary policy. Using a micro-level dataset of small business loans from both types of lenders, we provide empirical support for our theoretical propositions. Our results show that BigTech lenders are more responsive in establishing new lending relationships in an easing monetary policy environment, while the differences in loan amounts are not statistically significant. We also discuss other loan terms and the implications of regulatory policies.
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Micro-mechanisms behind Declining Labor Shares: Rising Market Power and Changing Modes of Production
Matthias Mertens
International Journal of Industrial Organization,
March
2022
Abstract
I derive a micro-founded framework showing how rising firm market power on product and labor markets and falling aggregate labor output elasticities provide three competing explanations for falling labor shares. I apply my framework to 20 years of German manufacturing sector micro data containing firm-specific price information to study these three distinct drivers of declining labor shares. I document a severe increase in firms’ labor market power, whereas firms’ product market power stayed comparably low. Changes in firm market power and a falling aggregate labor output elasticity each account for one half of the decline in labor's share.
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Returns to ICT Skills
Oliver Falck, Alexandra Heimisch-Roecker, Simon Wiederhold
Research Policy,
No. 7,
2021
Abstract
How important is mastering information and communication technology (ICT) on modern labor markets? We answer this question with unique data on ICT skills tested in 19 countries. Our two instrumental-variable models exploit technologically induced variation in broadband Internet availability that gives rise to variation in ICT skills across countries and German municipalities. We find statistically and economically significant returns to ICT skills. For instance, an increase in ICT skills similar to the gap between an average-performing and a top-performing country raises earnings by about 8 percent. One mechanism driving positive returns is selection into occupations with high abstract task content.
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Do Digital Information Technologies Help Unemployed Job Seekers Find a Job? Evidence from the Broadband Internet Expansion in Germany
Nicole Gürtzgen, André Diegmann, Laura Pohlan, Gerard J. van den Berg
European Economic Review,
February
2021
Abstract
This paper studies effects of the introduction of a new digital mass medium on reemployment of unemployed job seekers. We combine data on broadband internet availability at the local level with German individual register data. We address endogeneity by exploiting technological peculiarities that affected the roll-out of broadband internet. Results show that broadband internet improves reemployment rates after the first months in unemployment for males. Complementary analyses with survey data suggest that internet access mainly changes male job seekers’ search behavior by increasing online search and the number of job applications.
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Do Digital Information Technologies Help Unemployed Job Seekers Find a Job? Evidence from the Broadband Internet Expansion in Germany
Nicole Gürtzgen, André Diegmann, Laura Pohlan, Gerard J. van den Berg
Abstract
This paper studies effects of the introduction of a new digital mass medium on reemployment of unemployed job seekers. We combine data on high-speed (broadband) internet availability at the local level with German individual register data. We address endogeneity by exploiting technological peculiarities that affected the roll-out of high-speed internet. The results show that high-speed internet improves reemployment rates after the first months in unemployment. This is confirmed by complementary analyses with individual survey data suggesting that internet access increases online job search and the number of job interviews after a few months in unemployment.
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Complex-task Biased Technological Change and the Labor Market
Colin Caines, Florian Hoffmann, Gueorgui Kambourov
Review of Economic Dynamics,
April
2017
Abstract
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.
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On the Trail of Core–periphery Patterns in Innovation Networks: Measurements and New Empirical Findings from the German Laser Industry
Wilfried Ehrenfeld, Toralf Pusch, Muhamed Kudic
Annals of Regional Science,
No. 1,
2015
Abstract
It has been frequently argued that a firm’s location in the core of an industry’s innovation network improves its ability to access information and absorb technological knowledge. The literature has still widely neglected the role of peripheral network positions for innovation processes. In addition to this, little is known about the determinants affecting a peripheral actors’ ability to reach the core. To shed some light on these issues, we have employed a unique longitudinal dataset encompassing the entire population of German laser source manufacturers (LSMs) and laser-related public research organizations (PROs) over a period of more than two decades. The aim of our paper is threefold. First, we analyze the emergence of core–periphery (CP) patterns in the German laser industry. Then, we explore the paths on which LSMs and PROs move from isolated positions toward the core. Finally, we employ non-parametric event history techniques to analyze the extent to which organizational and geographical determinates affect the propensity and timing of network core entries. Our results indicate the emergence and solidification of CP patterns at the overall network level. We also found that the paths on which organizations traverse through the network are characterized by high levels of heterogeneity and volatility. The transition from peripheral to core positions is impacted by organizational characteristics, while an organization’s geographical location does not play a significant role.
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Taking the First Step - What Determines German Laser Source Manufacturers' Entry into Innovation Networks?
Jutta Günther, Muhamed Kudic, Andreas Pyka
International Journal of Innovation Management,
No. 5,
2015
Abstract
Early access to technological knowledge embodied in the industry’s innovation network can provide an important competitive advantage to firms. While the literature provides much evidence on the positive effects of innovation networks on firms’ performance, not much is known about the determinants of firms’ initial entry into such networks. We analyze firms’ timing and propensity to enter the industry’s innovation network. More precisely, we seek to shed some light on the factors affecting the duration between firm founding and its first cooperation event. In doing so, we apply a unique longitudinal event history dataset based on the full population of German laser source manufacturers. Innovation network data stem from official databases providing detailed information on the organizations involved, subject of joint research and development (R&D) efforts as well as start and end times for all publically funded R&D projects between 1990 and 2010. Estimation results from a non-parametric event history model indicate that micro firms enter the network later than small-sized or large firms. An in-depth analysis of the size effects for medium-sized firms provides some unexpected findings. The choice of cooperation type makes no significant difference for the firms’ timing to enter the network. Finally, the analysis of geographical determinants shows that cluster membership can, but do not necessarily, affect a firm’s timing to cooperate.
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