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on Technology and Industrial Dynamics |
| By: | Craig A. Chikis; Benny Kleinman; Marta Prato |
| Abstract: | Most U.S. innovation output originates from firms that operate R&D facilities across multiple local markets. We study how this geographic structure influences aggregate innovation and growth, and whether it is socially optimal. First, we develop an endogenous growth model featuring multi-market innovative firms that generate knowledge spillovers to geographically proximate firms. In equilibrium, firms may operate in too few or too many local markets, depending on how sensitive are the local spillovers they generate to their local size. Second, to quantify these effects, we link the model to data on firms’ R&D locations, patents, and citation networks. Using an event-study design, we show that firms’ spatial expansion increases spillovers to other firms and estimate how these spillovers depend on a firm's local footprint. Our estimates imply that U.S. innovative firms operate in too few markets relative to the social optimum. Third, using quantitative counterfactuals, we find that policies promoting broader spatial scope yield larger welfare gains than standard R&D subsidies. Moreover, unlike R&D subsidies, such policies can also reduce regional inequality. |
| JEL: | E0 F0 L0 O0 R0 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34010 |
| By: | Francesco Roncone |
| Abstract: | Both the demand for skilled labor and the skill wage premium have become increasingly dispersed across the United States. This paper examines how technological change within occupations drives these uneven local developments. Combining a novel measure of technological change - capturing shifts in task intensities within 430 detailed occupations - with patent data and microdata, I demonstrate that innovation reallocates labor toward cognitive-intensive tasks, especially in densely populated areas. Motivated by this, I show that greater exposure to technological change increases the relative employment of college-educated workers while causing within-occupation wage declines for less-educated workers, widening the college wage premium. |
| JEL: | J23 J24 J31 O33 R12 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:bol:bodewp:wp1208 |
| By: | Victor (Xucheng); CHEN |
| Abstract: | This study investigates the relationship between innovation activities and firm-level productivity among early-stage high-tech startups in China. Using a proprietary dataset encompassing patent records, R&D expenditures, capital valuation, and firm performance from 2020 to 2024, we examine whether and how innovation, measured by patents and R&D input, translates into economic output. Contrary to established literature, we find that patent output does not significantly contribute to either income or profit among the sampled firms. Further investigation reveals that patents may primarily serve a signaling function to external investors and policymakers, rather than reflecting true innovative productivity. In contrast, R&D expenditure shows a consistent and positive association with firm performance. Through mechanism analysis, we explore three channels (organizational environment, employee quality, and policy-driven incentives) to explain the impact of R&D, identifying capital inflow and valuation as key drivers of R&D investment. Finally, heterogeneity analysis indicates that the effects of R&D are more pronounced in sub-industries such as smart terminals and digital creativity, and for firms based in Shenzhen. Our findings challenge the prevailing assumption that patent output is a universal indicator of innovation success and underscore the context-dependent nature of innovation-performance linkages in emerging markets. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.18227 |
| By: | Jan Malek; Jo Seldeslachts; Reinhilde Veugelers |
| Abstract: | This paper provides empirical evidence on which M&A deals spur innovation, and which stifle it. To do so, we consider not only the product market position of the acquiring firm, but also the position of both target and acquirer in the technology space. Focusing on the antidiabetic drugs market, our dataset tracks the lifecycle and patenting of all individual antidiabetic projects in development between 1997 and 2017. We show that most terminations of acquired projects occur while the projects are still far from product market entry. Nevertheless, a number of these early-stage acquisitions have a positive impact on innovation. These cases arise when incumbents acquire projects close to their own projects in product markets, but only if these projects are also close in technology markets. Those deals are associated with increased subsequent patenting, which is consistent with the exploitation of technological synergies. Our results point to the crucial role of combining both product market and technology market positions in assessing the innovation effects of pharmaceutical M&As. |
| Keywords: | M&As, innovation, R&D, pharmaceutics, technology, novelty, patents |
| Date: | 2025–07–11 |
| URL: | https://d.repec.org/n?u=RePEc:ete:msiper:768578 |
| By: | Daron Acemoglu (MIT); Fredric Kong (MIT); Pascual Restrepo (Yale University) |
| Abstract: | This chapter reviews recent advances in the task model and shows how this framework can be put to work to understand trends in the labor market in recent decades. Production in each industry requires the completion of various tasks that can be assigned to workers with different skills or to capital. Factors of production have well-defined comparative advantage across tasks, which governs substitution patterns. Technological change can: (1) augment a specific labor type—e.g., increase the productivity of labor in tasks it is already performing; (2) augment capital; (3) automate work by enabling capital to perform tasks previously allocated to labor; (4) create new tasks. The task model clarifies that these different technologies have distinct effects on labor demand, factor shares, and productivity and their full impact depends on the substitution patterns between workers that arise endogenously in the task framework. We explore the implications of the task framework using reduced-form evidence, highlighting the central role of automation and new tasks in recent labor market trends. We also explain how the general equilibrium effects ignored in these reduced-form approaches can be estimated structurally. |
| Keywords: | automation, productivity, technology, inequality, wages, rents |
| JEL: | J23 J31 O33 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:2535 |
| By: | Barros, Fernando; Delalibera, Bruno; Ribeiro, Marcos |
| Abstract: | This paper examines the relationship between economic complexity and industrial robot adoption. Using panel data for 61 countries from 1996 to 2022, we find that higher robot density is significantly associated with greater economic complexity. This positive relationship remains robust after controlling for per capita income, human capital, institutional quality, and other relevant factors. Notably, the complexity-enhancing effect of robots is stronger in countries with a larger share of low-skilled workers. |
| Keywords: | economic complexity robot density economic development |
| JEL: | O33 |
| Date: | 2025–06–25 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:125125 |
| By: | Yoshiki Ando; Emin Dinlersoz; Jeremy Greenwood; Ruben Piazzesi |
| Abstract: | How do advanced technology adoption and venture capital (VC) funding impact employment and growth? An analysis of data from the US Census Bureau suggests that while both advanced technology use and VC funding matter on their own for firm outcomes, their joint presence is most strongly correlated with higher employment levels. VC presence is linked with a high increase in employment, though primarily among a limited subset of firms. In contrast, technology adoption is associated with a smaller rise in employment, yet it influences a considerably larger number of firms. A model of startups is created, focusing on decisions to use advanced technology and seek VC funding. The model is compared with firm-level data on employment, advanced technology use, and VC investment. Several thought experiments are conducted using the model. Some experiments assess the importance of advanced technology and VC in the economy. Others examine the reallocation effects across firms with different technology choices and funding sources in response to shifts in taxes and subsidies. |
| Keywords: | Advanced technology, banks, capital gains taxation, corporate income taxation, difference-in-difference analysis, employment, firm-level data, reallocation effects, startups, subsidies, synergy, venture capital, technology adoption, U.S. Census data |
| JEL: | E13 G24 O30 O40 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:cen:wpaper:25-49 |
| By: | Albanesi, Stefania; Da Silva, António Dias; Jimeno, Juan F.; Lamo, Ana; Wabitsch, Alena |
| Abstract: | We examine the link between the diffusion of artificial intelligence (AI) enabled technologies and changes in the female employment share in 16 European countries over the period 2011-2019. Using data for occupations at the 3-digit level, we find that on average female employment shares increased in occupations more exposed to AI. Countries with high initial female labor force participation and higher initial female relative education show a stronger positive association. While there exists heterogeneity across countries, almost all show a positive relation between changes in female employment shares within occupations and exposure to AI-enabled automation. JEL Classification: J23, O33 |
| Keywords: | artificial intelligence, employment, gender, occupations, skills |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:ecb:ecbwps:20253077 |
| By: | Miguel Ortiz (Departamento de Economía de la Pontificia Universidad Católica del Perú); Juan Palomino (Departamento de Economía de la Pontificia Universidad Católica del Perú) |
| Abstract: | This study examines how technologyextension and transfer services (TETS) drive firm-level innovation andproductivity. Since research and development (R&D) investments are subjectto market failure, engaging with external agents enables firms to innovate atlower risk and cost. Using data from Peru’s National Innovation Survey (ENI), we apply the Crépon, Duguet, and Mairesse (CDM) model alongside propensityscore matching (PSM) to enhance the reliability of our results. Additionally, we employ the generalized propensity score (GPS) method to analyze thesensitivity of innovation and sales outcomes to varying investment levels. Thefindings confirm that investment in training and external R&D significantlyenhances innovation, thereby boosting labor productivity. However, thisrelationship is nonlinear, suggesting the presence of investment thresholdsrequired to maximize impact. Palabras claves: Technology Transfer, Innovation, Productivity, R&D, CDM model JEL Classification-JE: L25, O32, O38 |
| Keywords: | Technology Transfer, Innovation, Productivity, R&D, CDM model |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pcp:pucwps:wp00543 |
| By: | Omar R. Malik |
| Abstract: | Using data from the U.S. Census Bureaus Business Trends and Outlook Survey (BTOS), I examine the adoption of AI among US firms at national, state, industry, and firm size levels. I find that adoption remains overall low (only around 7% of firms currently use AI), but is on a steady upward trajectory with a rising share of firms planning to implement AI. Adoption rates vary significantly across regions and sectors: some states are emerging as early adopters, while others lag, and knowledge-intensive industries (such as information technology and professional services) along with larger firms show higher openness to AI adoption compared to sectors like construction or small businesses. In general, these trends indicate that a quiet revolution in AI adoption is underway; a gradual but expanding diffusion of AI across the economy with important implications for future productivity and policy. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.14721 |
| By: | Michael D. Frakes; Melissa F. Wasserman |
| Abstract: | Biological drugs account for just two percent of prescriptions filled in the U.S. but fifty percent of prescription-drug spending. To explore the role patents play in explaining high biologics prices, we build the first comprehensive database of patents associated with all FDA-approved biologics. We first establish that much of what drives biologic patenting is the desire to block entry by competing biosimilars. For these purposes, we estimate the response to a 2010 Act that created an abbreviated pathway for biosimilars to receive FDA approval. We then document robust evidence consistent with two patenting strategies that may block biosimilar competition: thicketing and evergreening, whereby firms supplement primary patents with a dense web of later-expiring patents on secondary drug features. We conduct various exercises to suggest that these behaviors are undertaken with exclusionary purposes that go beyond the traditional justifications of the patent system. We then set forth various descriptive statistics surrounding biosimilar entry to suggest that these patenting strategies are, in fact, effective at delaying biosimilar entry. Finally, we simulate the degree to which biologics patent portfolios are impacted by policy proposals currently under consideration to address thicketing and evergreening. |
| JEL: | K0 L50 L65 O34 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34024 |
| By: | Elfsbacka-Schmöller, Michaela; Goldfayn-Frank, Olga; Schmidt, Tobias |
| Abstract: | This paper provides novel empirical evidence on the impact of monetary policy on innovation investment using unique firm-level data. First, we document the effect of a large, systematic monetary tightening (ECB rate increases from 0% to 4.5% during 2022-23), with average firm-level innovation cuts of 20%. These cuts persist over the medium term, indicating a sustained innovation slowdown. Second, we use the survey to identify elasticities of innovation expenditure to exogenous policy rate changes. Responses to hikes and cuts are significant and largely symmetric at the baseline rate (4.5%), though we detect potential state-dependent asymmetry due to the extensive margin. The financing channel emerges as one of the transmission channels, with more pronounced effects in firms with higher shares of bank loans and variable-rate loans. Crucially, we show that monetary policy transmits via aggregate demand, with stronger responses in firms with pessimistic demand expectations. Forward guidance provides substantial additional stimulus by reducing uncertainty about future rates, suggesting long-term, supply-side effects of announcements. These results challenge monetary long-run neutrality and are suggestive of policy endogeneity of R∗ operating through innovation-driven technology growth. JEL Classification: E52, E22, E24, D22 |
| Keywords: | endogenous growth, forward guidance, monetary policy transmission, R&D, R∗ |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:ecb:ecbwps:20253080 |
| By: | Francesco Zanetti; Jesús Fernández-Villaverde; Yang Yu |
| Abstract: | Defensive hiring of researchers by incumbent firms with monopsony power reduces creative destruction. This mechanism helps explain the simultaneous rise in R&D spending and decline in TFP growth in the US economy over recent decades. We develop a simple model highlighting the critical role of the inelastic supply of research labor in enabling this effect. Empirical evidence confirms that the research labor supply in the US is indeed inelastic and supports other model predictions: incumbent R&D spending is negatively correlated with creative destruction and sectoral TFP growth while extending incumbents lifespan. All these effects are amplified when ideas are harder to find. An extended version of the model quantifies these mechanisms implications for productivity, innovation, and policy. |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:cnn:wpaper:25-016e |
| By: | Federico Colozza (UNIPV - Università degli Studi di Pavia [Italia] = University of Pavia [Italy] = Université de Pavie [Italie], ROMA TRE - Università degli Studi Roma Tre = Roma Tre University); Carlo Pietrobelli (UNU-MERIT - UNU-MERIT - United Nations University - Maastricht University, ROMA TRE - Università degli Studi Roma Tre = Roma Tre University); Antonio Vezzani (ROMA TRE - Università degli Studi Roma Tre = Roma Tre University, ESC [Rennes] - ESC Rennes School of Business) |
| Abstract: | In this paper we investigate the relationship between participation in global value chains and the environment from a spatial perspective. By drawing on an original dataset on global value chain participation, emissions of nitrogen oxides and sulphur oxides, and green patents for European regions, we present novel evidence about the relationship between global value chains, green technologies and air pollution at the regional level. Our findings suggest that although participation in global value chains may lead to lower polluting emissions, this effect largely depends on the capacity of regions to exploit the green knowledge deriving from participation and on the specific form of participation. When European regions are integrated with backward linkages (i.e., importing inputs to produce exports) they record lower levels of air pollution; conversely, participation through forward linkages (i.e., exporting inputs for other places' exports) leads to an increase in air pollution. Backward participation also come out to support the development of green technologies that mediate the effects of global value chains on the environment posited by the "Pollution Haven" hypothesis. Overall, the relationship between global value chains participation and air pollution will depend on the type of participation and on the capacity of territories to profit it for the development of green technologies. |
| Keywords: | Global value chains, Green technologies, Emissions, EU regions, Pollution haven hypothesis |
| Date: | 2024–02–13 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05136372 |
| By: | Hussinger, Katrin; Issah, Wunnam Basit |
| Abstract: | We investigate whether family ownership is associated with a preference for patents or trade secrets. Using a sample of S&P 500 firms, we show that family ownership is negatively associated with patenting and positively associated with the usage of trade secrets. We further show that both relationships are moderated by firm performance below the aspiration level, i.e. the performance benchmark level that an organization sets. These results can be explained with a mixed gambles behavioral agency framework. When family firms perform below their aspiration level, prospective financial gains become relatively more important as compared to current socioemotional wealth so that patents become more and trade secrets less attractive. |
| Keywords: | Family firms, patents, trade secrets, mixed gambles, aspiration gap |
| JEL: | O34 O32 G32 M14 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:zewdip:319899 |