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on Innovation |
| By: | Kyle R. Myers; Lauren Lanahan; Evan Johnson |
| Abstract: | Small businesses have long supplied a disproportionate share of major innovations in the United States. We review a centerpiece policy on this topic: the US Small Business Innovation Research (SBIR) program. We trace its legislative history and summarize program evaluations over the past four decades. Using newly matched data on SBIR awards and venture capital investments into small businesses, we show that, despite often being compared to venture-backed businesses, SBIR-backed businesses pursue very different strategies. We use simple economic theories to motivate the SBIR program as a vehicle for the government to invest in small-scale, well-defined, but risky technologies that have large externalities, and we highlight a number of case studies consistent with this framework. Because the motivating friction lies at the level of ideas, our perspective encourages future evaluations to determine how the SBIR program influences not just who does the inventing, but what gets invented. Looking forward we discuss how rising industrial concentration and the diffusion of artificial intelligence may reshape the program’s comparative advantage in the innovation policy toolkit. |
| JEL: | O30 O32 O38 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33945 |
| By: | Hasna, Z.; Hatton, H.; Jaumotte, F.; Kim, J.; Mohaddes, K.; Pienknagura, S. |
| Abstract: | This paper investigates how climate policies affect low-carbon innovation (as measured by patents) and assesses the link between such innovation and economic activity. Climate policies, including international cooperation, spur both specific and overall innovation, with regulations, emissions-trading systems, and expenditure measures such as R&D subsidies and feed-in tariffs being particularly impactful. In turn, low-carbon innovation raises economic activity as much as other types of innovation and past technological revolutions. However, the mechanisms are different: low-carbon innovation increases capital accumulation, while other types of innovation increase total factor productivity (TFP). |
| Keywords: | Low-Carbon Innovation, Growth, Climate Policies, Climate Change, Porter Hypothesis |
| JEL: | F64 H23 O33 O44 Q55 Q56 Q58 |
| Date: | 2025–06–30 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2544 |
| By: | Wesley M. Cohen; Matthew J. Higgins; William D. Miles; Yoko Shibuya |
| Abstract: | Using detailed product- and invention-level data from the pharmaceutical industry, we demonstrate that firms with particularly high-selling “blockbuster” products concentrate their development efforts on new products that both target the same customer segments and are more likely to be technically similar to existing blockbuster products. This behavior, driven by an expectation of the stickiness of demand for existing product offerings, limits firms' incentives to invest in entirely new products targeting different customer segments. Our findings offer insights into how blockbuster products shape firms' customer segment and innovation choices, with implications for understanding the dynamics of technological change in R&D-intensive industries. |
| JEL: | O3 O31 O33 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33957 |
| By: | Dror Shvadron; Hansen Zhang; Lee Fleming; Daniel P. Gross |
| Abstract: | Using newly-collected data on the near-population of U.S. STEM PhD graduates since 1950, we examine who funds PhD training, how many graduates are trained in areas of strategic national importance, and the effects of public investment in PhD training on the scientific workforce. The U.S. federal government is by far the largest source of financial and in-kind support for STEM PhD training in America. We identify universities and fields where PhD training has a higher or lower intensity of government, industry, or philanthropic support, and the organizations and universities that fund and train the most PhDs in critical technology areas such as AI, quantum information technology, and biotechnology. Leveraging variation in government support across agencies and over time, we provide evidence suggesting that increasing government-funded PhD trainees increases PhD production roughly one-for-one. To support further research, we provide public datasets at multiple levels of aggregation, reporting PhD graduates by (i) critical technology area and (ii) source of support. |
| JEL: | I23 I28 O31 O32 O33 O38 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33944 |
| By: | Joel P. Flynn; Antoine B. Levy; Jacob Moscona; Mai Wo |
| Abstract: | This paper studies how innovation reacts to foreign political risk and shapes its economic consequences. In a model with foreign political shocks that can disrupt the supply of foreign inputs, we show that greater political risk abroad increases domestic innovation, thereby lowering reliance on risky sourcing countries. We then combine data on sector-level technology development with time-varying measures of industry-level exposure to foreign political risk and report three sets of empirical findings. First, sectors and commodities with higher exposure to foreign political risk exhibit significantly greater innovative activity. This finding holds across sectors in the US, across country-sector pairs in a global sample, and across critical minerals that are essential for modern economic activity. Second, the response of innovation is particularly strong when risk emanates from geopolitical adversaries. This is consistent with our finding that trade restrictions are more likely to emerge between non-allies following a rise in political risk in either country. Third, directed innovation reduces countries’ reliance on imports from risky foreign markets. In doing so, technological change amplifies the negative effects of domestic political risk on export performance. |
| JEL: | F50 O3 O31 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33964 |
| By: | Philippe Aghion; Lint Barrage; Eric Donald; David Hémous; Ernest Liu |
| Abstract: | We analyze a model of green technological transition along a supply chain. The model generates a unique equilibrium for given initial conditions but multiple steady-states. We show that: (i) even in the presence of Pigouvian environmental taxation, targeted sectoral subsidies are generally necessary to implement the social optimum; (ii) small, targeted industrial policy may bring large welfare gains; (iii) a government which is unable to subsidize greenification in more than one sector or price carbon at its true social cost should primarily target downstream sectors; (iv) over-investing in greenification in the wrong upstream branch may derail the overall transition towards greenification. Finally, we calibrate our model to decarbonization of heavy duty transportation (trucking, aviation, etc.) via hydrogen. We find that, absent industrial policy, the economy can get stuck in the “wrong” steady-state with CO₂ emissions vastly above the social optimum even with a Pigouvian carbon price in place. |
| JEL: | O0 O3 O38 O4 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33934 |
| By: | Josh Burke; Siyu Feng; Maxwell Read; Esin Serin; Ram Smaran Suresh Kumar |
| Abstract: | This report analyses innovation activity represented by patenting data for two carbon dioxide removal (CDR) technologies - bioenergy with carbon capture and storage (BECCS) and direct air carbon capture and storage (DACCS), referred to collectively as geological CDR - to shed light on the countries that might be best positioned to lead the market for relevant technologies to capture growth opportunities while supporting global climate goals. |
| Keywords: | Green Growth, carbon capture, Technological change |
| Date: | 2025–07–09 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepsps:51 |
| By: | Wohlschlegel, Julian; Jussupow, Ekaterina; Pumplun, Luisa; Dittrich, Janek |
| Abstract: | The work of knowledge brokers comprises the transfer, translation, and transformation of knowledge between individuals who are unlikely to interact efficiently because of knowledge boundaries. In an extension of this theory, algorithmic brokers are defined as individuals performing these practices with artificial intelligence (AI) output to enable a community to leverage this output in their work. However, with the introduction of large language models (LLMs), we argue this brokerage role is shifting and that LLMs have the potential to broker knowledge between humans. We conducted a case study with domain experts in a Research and Development (R&D) department of a large multinational science and technology company who regularly use a recently developed domain-specific R&D-LLM. Our preliminary findings show that the R&D-LLM is reshaping interactions between human experts through three knowledge brokerage practices of varying complexity, assisting in simple knowledge recall, enabling the approach to experts and being a simulated counterpart. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:155585 |
| By: | Ziesemer, Thomas (Mt Economic Research Inst on Innov/Techn, RS: GSBE MORSE) |
| Abstract: | Macroeconomic productivity is modelled as a Cobb-Douglas function of private and public R&D stocks in recent literature. The slope parameters of a growth rate version may change over time and with circumstances. Using the method of functional-coefficient regression, we show that human capital, GDP (per worker), services and defence R&D (both % GDP), lags of domestic and foreign private and public R&D, and lagged labour-augmenting technical change, all in growth rates, change the elasticities of productivity. The result is a panel data set of regression coefficients representing elasticities of productivity. Eventually, the panel average of the productivity elasticities of domestic and foreign private R&D goes to constant values; elasticities of public R&D go down slightly. This may contribute to an explanation of the productivity slowdown and why private R&D has been expanded relative to public R&D in recent years. |
| JEL: | O33 O47 |
| Date: | 2025–07–11 |
| URL: | https://d.repec.org/n?u=RePEc:unm:unumer:2025017 |
| By: | Daniel Souza; Aldo Geuna; Cornelia Lawson |
| Abstract: | The paper studies the development of the Economics of Science as a new emerging field in the social sciences during the period 1994-2023. To identify the community of scholars working on this new scientific topic, we examine authors citing two seminal papers and use network analysis to investigate the cognitive and organizational characteristics of the community of authors. Our findings suggest that the Economics of Science is still in the process of becoming an independent and cohesive field, exhibiting a highly fragmented structure. We also study the role of the "Workshop on the Organisation, Economics, and Policy of Scientific Research" (WOEPS), initiated in 2007, for the Economics of Science community. We show that WOEPS presenters have more economists of science as coauthors and are better positioned to connect different clusters of authors in the wider Economics of Science network than other members of the network, highlighting its importance for linking scholars in the field. We also show that WOEPS papers are published in higher "quality" journals, receive relatively more citations, and significantly more citations from within the Economics of Science field compared to other Economics of Science papers. |
| Keywords: | Economics of Science, Scientific Communities, Network Analysis, Field Formation |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:cca:wpaper:745 |
| By: | Daniela Grieco; Patrick Llerena; Anne-Gaëlle Maltese |
| Abstract: | This paper explores how individuals perceive open versus closed tasks in creative contexts and how this perception influences their choice between these tasks. We find that perceptions of task openness align with existing assumptions in the creativity literature regarding goal clarity and the freedom to explore. Additionally, we show that the likelihood of choosing an open task increases with the perceived freedom to explore, while it decreases with goal clarity, particularly when incentives are present. The effects of self-selection on creative performance are then investigated. |
| Keywords: | creativity; openness; perception; constraints; self-selection. |
| JEL: | C91 D91 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ulp:sbbeta:2025-16 |
| By: | Niklas Garnadt; Lena Füner; Konrad Stahl; Joacim Tag; Konrad O. Stahl |
| Abstract: | Identifying high growth startups ex-ante and fostering their success is an important policy challenge. Using Swedish registry data, we show that previous labor market earnings of entrepreneurs is a simple observable that is strongly correlated with entrepreneurship success. Entrepreneurs from the top decile of income from dependent employment are four times more likely to succeed than those from the lowest decile. Their firms are larger and more productive from the outset, and this effect intensifies over time. This correlation is virtually unaffected by variations in the entrepreneurs' personal traits. It does also not vary across the business cycle. |
| Keywords: | entrepreneurship, high-growth startups, labor income, unemployment |
| JEL: | L26 J24 M13 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11978 |