Common Ownership, Tacit Know-How, and the Market for Technology
Dennis Hutschenreiter
IWH Discussion Papers,
No. 3,
2026
Abstract
Firms increasingly rely on markets for technology to acquire innovations developed outside their boundaries, yet acquiring intellectual property rights alone often does not guarantee successful implementation. Many technologies depend on tacit know-how that must be supplied by the provider after the transaction is completed. This paper examines whether common ownership between a technology provider and a potential adopter mitigates this implementation problem. I develop a model in which overlapping institutional investors cause the provider to partially internalize the adopter’s gains from successful implementation, strengthening incentives to transfer tacit know-how. This mechanism operates only when know-how is unverifiable – absent this friction, common ownership leaves matching and outcomes unchanged. Under moral hazard, the model predicts that common ownership increases the likelihood of technology transfer to a given adopter, that this effect is stronger when tacit know-how is more important, and that common ownership improves post-transfer outcomes conditional on adoption. I test these predictions using U.S. patent reassignments between publicly traded firms. Using within-deal variation across competing potential adopters and plausibly exogenous variation from passive index-fund holdings, I show that common ownership increases the likelihood that a firm acquires a technology, particularly when the transferred bundle is more tacit. Common ownership predicts stronger subsequent innovation and higher future firm value, especially when ownership overlap is concentrated among investors with stronger incentives to monitor the provider. These findings show how ownership structure shapes interfirm technology transfer by affecting not only who acquires a technology, but also how much value is created.
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Advanced Technology Adoption: Determinants and Labor Market Effects of Robot Use
Verena Plümpe
PhD Thesis, Otto-von-Guericke-Universität Magdeburg,
2024
Abstract
The recent advances in automation technology, robotics in particular, have sparked a heated debate over the future of labor and human society at large. The ongoing process of robotization may engender profound impacts on various segments of the labor market. Given the far-reaching implications of robots, it is thus very important to understand the scale and scope of robot use and characteristics of robot users. However, the main challenge is the limited availability of robot data at the microeconomic level (Raj and Seamans, 2018). Due to the data constraint, the bulk of the existing literature relies on cross-country industry-level data from the International Federation of Robotics (IFR). The lack of micro-level robot data makes it difficult to paint a comprehensive picture of robotization in industrial settings, and perhaps more importantly, to assess how within-industry firm level heterogeneity manifests itself in robot use and adoption.
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Too Poor to Be Green? The Effects of Wealth on the Residential Heating Transformation
Tobias Berg, Ulf Nielsson, Daniel Streitz
SSRN Working Paper,
2024
Abstract
Using the near-universe of Danish owner-occupied residential houses, we show that an exogenous increase in wealth significantly increases the likelihood to switch to green heating. We estimate an elasticity of one at the median of the wealth distribution, i.e., a 10% increase in wealth increase raises green heating adoption by 10%. Effects are heterogeneous along the wealth distribution: all else equal, a redistribution of wealth from rich households to poor households can significantly increase green heating adoption. We further explore potential channels of our findings (pro-social preferences, financial constraints, and luxury goods interpretation). Our results emphasize the role of economic growth for the green transition.
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Financial Technologies and the Effectiveness of Monetary Policy Transmission
Iftekhar Hasan, Boreum Kwak, Xiang Li
European Economic Review,
Vol. 161 (January),
2024
Abstract
This study investigates whether and how financial technologies (FinTech) influence the effectiveness of monetary policy transmission. We use an interacted panel vector autoregression model to explore how the effects of monetary policy shocks change with regional-level FinTech adoption. Results indicate that FinTech adoption generally mitigates the transmission of monetary policy to real GDP, consumer prices, bank loans, and housing prices, with the most significant impact observed in the weakened transmission to bank loan growth. The relaxed financial constraints, regulatory arbitrage, and intensified competition are the possible mechanisms underlying the mitigated transmission.
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