Economic Preferences for Risk-Taking and Financing Costs
Manthos D. Delis, Iftekhar Hasan, Maria Iosifidi, Chris Tsoumas
Journal of Corporate Finance,
June
2023
Abstract
We hypothesize and empirically establish that economic preferences for risk-taking in different subnational regions affect firm financing costs. We study this hypothesis by hand-matching firms' regions worldwide with the corresponding regional economic risk-taking preferences. We first show that higher regional risk-taking is positively associated with several measures of firm risk and investments. Subsequently, our baseline results show that credit and bond pricing increase when risk-taking preferences increase. For the loan of average size and maturity a one-standard-deviation increase in regional risk-taking increases interest expense by $0.54 million USD. We also find that these results are demand (firm)-driven and stronger for firms with more local shareholders.
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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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Do Larger Firms Exert More Market Power? Markups and Markdowns along the Size Distribution
Matthias Mertens, Bernardo Mottironi
IWH-CompNet Discussion Papers,
Nr. 1,
2023
Abstract
Several models posit a positive cross-sectional correlation between markups and firm size, which characterizes misallocation, factor shares, and gains from trade. Accounting for labor market power in markup estimation, we find instead that larger firms have lower product markups but higher wage markdowns. The negative markup-size correlation turns positive when conditioning on markdowns, suggesting interactions between product and labor market power. Our findings are robust to common criticism (e.g., price bias, non-neutral technology) and hold across 19 European countries. We discuss possible mechanisms and resulting implications, highlighting the importance of studying input and output market power in a unified framework.
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Do Larger Firms Exert More Market Power? Markups and Markdowns along the Size Distribution
Matthias Mertens, Bernardo Mottironi
IWH Discussion Papers,
Nr. 1,
2023
Abstract
Several models posit a positive cross-sectional correlation between markups and firm size, which characterizes misallocation, factor shares, and gains from trade. Accounting for labor market power in markup estimation, we find instead that larger firms have lower product markups but higher wage markdowns. The negative markup-size correlation turns positive when conditioning on markdowns, suggesting interactions between product and labor market power. Our findings are robust to common criticism (e.g., price bias, non-neutral technology) and hold across 19 European countries. We discuss possible mechanisms and resulting implications, highlighting the importance of studying input and output market power in a unified framework.
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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,
Nr. 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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