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on Technology and Industrial Dynamics |
| By: | Silvia Rocchetta; Martina Iori; Andrea Mina; Robert Gillanders |
| Abstract: | We study the effects of different types of technological diversification on the performance of regional economies. We focus on the relatedness and unconventionality of technological capabilities as drivers of GDP and employment growth. Using economic indicators from Eurostat regional statistics and patent records from the European Patent Office (EPO) PATSTAT and the OECD RegPat databases, we estimate Panel Vector Autoregression models and generate Impulse Response Functions to assess to what extent and with what persistence relatedness and unconventionality affect growth. Our findings, which have implications for place-based innovation policies, reveal that technological relatedness has short-term effects on employment growth and negative effects on GDP growth, whereas technological unconventionality has a long-lasting positive impact on GDP growth and no effect on employment growth. |
| Keywords: | Technological capabilities; Diversification; Relatedness; Unconventionality; Innovation; Regional development |
| Date: | 2023–12–23 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2023/46&r=tid |
| By: | Colin Davis; Ken-ichi Hashimoto |
| Abstract: | This paper studies how national research subsidies affect productivity growth and national welfare through adjustments in the geographic location of research and development (R&D) across countries. Our two-country framework features a tension in the firm-level innovation location decision between accessing technical knowledge and sourcing low-cost high-skilled labor. With trade costs and imperfect international knowledge diffusion, the larger country has a greater share of industry and tends to host a larger share of innovation. In this setting, we find that an R&D subsidy expands the implementing country’s share of innovation and raises the rate of productivity growth. Although the non-implementing country experiences a welfare improvement, the rising cost of the policy generates a concave relationship between the R&D subsidy and the welfare of the implementing country, yielding an optimal R&D subsidy rate. |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:dpr:wpaper:1226&r=tid |
| By: | Johan Hombert; Adrien Matray |
| Abstract: | Innovation booms are often fueled by easy financing that allows new technology firms to pay high wages that attracts skilled labor. Using the late 1990s Information and Communication Technology (ICT) boom as a laboratory, we show that skilled labor joining this new sector experienced sizeable long-term earnings losses. We show these earnings patterns are explained by faster skill obsolescence rather than either worker selection or the overall bust in the ICT sector. During the boom, financing flowed more to firms whose workers would experience the largest productivity declines, amplifying the negative effect of labor reallocation on aggregate human capital accumulation. |
| JEL: | E23 J24 O33 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32012&r=tid |
| By: | Gaia Dossi; Marta Morando |
| Abstract: | We study the role of political ideology for a critical group of economic agents: inventors. We document that, in "politically polarizing" fields, inventors patent innovations aligned with their political beliefs. We construct a novel dataset matching data from the US Patent Office (USPTO) with individual Voter Register data for two large US states, and with the universe of US campaign contributions data. We proxy political ideology with individual party affiliation and focus on fields where the ideological distance between Republicans and Democrats is especially large in the general population. We find that, compared to Republicans, Democrats are: i) more likely to file green patents; ii) more likely to file female-health patents, and this persists in the sub-set of male inventors; and iii) less likely to file weapon-related patents. The magnitudes are large and range from one-fourth to one-third of total patent production in these technologies. This pattern is explained by inventors sorting into firms, rather than by within-firm dynamics. Socio-economic status, geography, or differential reactions to monetary incentives cannot explain our findings. Importantly, ideological sorting persists in research organizations, suggesting that inventors may derive intrinsic utility from producing innovation aligned with their beliefs. We rationalize our findings using a stylized model of the labor market where inventors derive amenity value from producing innovation close to their political ideology. |
| Keywords: | political ideology, innovation, inventors |
| Date: | 2023–12–19 |
| URL: | http://d.repec.org/n?u=RePEc:cep:cepdps:dp1969&r=tid |
| By: | Gustavo de Souza; Haishi Li |
| Abstract: | What is the effect of robots and tools on employment and inequality? Using natural language processing and an instrumental variable approach, we discover that robots have led to a sizable decrease in the employment and wages of low-skill workers in operational occupations. However, tools - machines that complement labor – have led to an equally large reinstatement of these workers, increasing their employment and wages. Using a quantitative model, we find that the lower prices of robots and tools over the last 20 years have reduced inequality and increased welfare without a significant effect on employment. |
| Keywords: | robots, automation, tools, labor-saving, labor-augmenting |
| JEL: | J23 J24 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10813&r=tid |
| By: | KIMURA Yosuke |
| Abstract: | As the risk of climate change has increased, companies have advanced their research and development in green transformation (GX) technologies. This paper utilizes the GX classification published by the Japan Patent Office to estimate the values of green and non-green innovation, and analyzes their impacts on firms' resource allocation and growth. This paper finds that (1) green innovation has higher value than non-green innovation on average, (2) non-green innovation measures at the firm level predict a future increase in sales, capital and labor, but green innovation measures do not have predictive power in terms of future variation of firm growth or resource allocation. |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:eti:dpaper:23086&r=tid |
| By: | Stefano Bianchini; Moritz M\"uller; Pierre Pelletier |
| Abstract: | New technologies have the power to revolutionize science. It has happened in the past and is happening again with the emergence of new computational tools, such as Artificial Intelligence (AI) and Machine Learning (ML). Despite the documented impact of these technologies, there remains a significant gap in understanding the process of their adoption within the scientific community. In this paper, we draw on theories of scientific and technical human capital (STHC) to study the integration of AI in scientific research, focusing on the human capital of scientists and the external resources available within their network of collaborators and institutions. We validate our hypotheses on a large sample of publications from OpenAlex, covering all sciences from 1980 to 2020. We find that the diffusion of AI is strongly driven by social mechanisms that organize the deployment and creation of human capital that complements the technology. Our results suggest that AI is pioneered by domain scientists with a `taste for exploration' and who are embedded in a network rich of computer scientists, experienced AI scientists and early-career researchers; they also come from institutions with high citation impact and a relatively strong publication history on AI. The pattern is similar across scientific disciplines, the exception being access to high-performance computing (HPC), which is important in chemistry and the medical sciences but less so in other fields. Once AI is integrated into research, most adoption factors continue to influence its subsequent reuse. Implications for the organization and management of science in the evolving era of AI-driven discovery are discussed. |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2312.09843&r=tid |
| By: | Jesse LaBelle; Immaculada Martinez-Zarzoso; Ana Maria Santacreu; Yoto Yotov |
| Abstract: | We build a stylized model that captures the relationships between cross-border patenting, globalization, and development. Our theory delivers a gravity equation for cross-border patents. To test the model’s predictions, we compile a new dataset that tracks patents within and between countries and industries, for 1980-2019. The econometric analysis reveals a strong, positive impact of policy and globalization on cross-border patent flows, especially from North to South. A counterfactual welfare analysis suggests that the increase in patent flows from North to South has benefited both regions, with South gaining more than North post-2000, thus lowering real income inequality in the world. |
| Keywords: | cross-border patents; gravity; policy; globalization; development |
| JEL: | F63 O14 O33 O34 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedlwp:97470&r=tid |
| By: | Amit Goyal (University of Lausanne; Swiss Finance Institute); Sunil Wahal (Arizona State University) |
| Abstract: | We investigate the relation between inventive input (R&D), inventive output (the economic value of patents, EVP), firm-level profitability and asset growth, and stock returns. Current R&D and EVP forecast future profitability. Neither forecast future asset growth. Factor models motivated by q-theory and the dividend discount model fail to price R&D and EVP correctly, leaving large alphas on the table. But model failure is due to design specifics, not economic underpinnings: using cash-based operating profitability to measure expected profitability resurrects both models. The stock market does not appear to misprice inventive input or output. |
| Keywords: | Research & Development, Patents, Innovation, Intangibles, Profitability, Asset Pricing, Expected Returns, Accruals |
| JEL: | G11 G12 G13 |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:chf:rpseri:rp23107&r=tid |
| By: | ARATA Yoshiyuki; MIYAKAWA Daisuke; MORI Katsuki |
| Abstract: | This paper investigates firm growth dynamics by using the theory of stochastic processes and data on corporate tax records covering almost all firms in Japan. We show that the growth path of high-growth firms (HGFs) is characterized by a single large jump rather than a gradual increase. Specifically, before the jump occurs, the growth path of a HGF is similar to that of non-HGFs, but then it experiences a rapid increase in size. This growth pattern with a jump is typical (i.e., most likely) for HGFs. To provide further empirical evidence, we consider the ratio of the growth rate in the first period to the entire growth rate over two periods. The histogram of this ratio exhibits a U-shaped curve for HGFs, indicating that high growth over the two periods is explained by high growth either in the first or second period (but not both). This U-shaped curve is consistent with the idea that a single large jump determines the growth path of HGFs. |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:eti:dpaper:23087&r=tid |
| By: | Dandan Qiao; Huaxia Rui; Qian Xiong |
| Abstract: | Artificial intelligence (AI) refers to the ability of machines or software to mimic or even surpass human intelligence in a given cognitive task. While humans learn by both induction and deduction, the success of current AI is rooted in induction, relying on its ability to detect statistical regularities in task input -- an ability learnt from a vast amount of training data using enormous computation resources. We examine the performance of such a statistical AI in a human task through the lens of four factors, including task learnability, statistical resource, computation resource, and learning techniques, and then propose a three-phase visual framework to understand the evolving relation between AI and jobs. Based on this conceptual framework, we develop a simple economic model of competition to show the existence of an inflection point for each occupation. Before AI performance crosses the inflection point, human workers always benefit from an improvement in AI performance, but after the inflection point, human workers become worse off whenever such an improvement occurs. To offer empirical evidence, we first argue that AI performance has passed the inflection point for the occupation of translation but not for the occupation of web development. We then study how the launch of ChatGPT, which led to significant improvement of AI performance on many tasks, has affected workers in these two occupations on a large online labor platform. Consistent with the inflection point conjecture, we find that translators are negatively affected by the shock both in terms of the number of accepted jobs and the earnings from those jobs, while web developers are positively affected by the very same shock. Given the potentially large disruption of AI on employment, more studies on more occupations using data from different platforms are urgently needed. |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2312.04180&r=tid |
| By: | Klauser, Roman (RWI); Tamm, Marcus (Hochschule der Bundesagentur für Arbeit (HdBA)) |
| Abstract: | Do returns to training differ if training is accompanied by technological innovations at the workplace? We analyze this potential heterogeneity of returns based on panel data from Germany that provide a unique measure for individuals' adoption of new technology at the workplace. In the preferred analysis we run fixed effects estimations. As a robustness test we also allow for individual time trends. The findings indicate positive wage effects and more job stability for training participants in general but no effects on wages and job mobility for new technology adoption. Furthermore, the combined occurrence of new technology adoption and of training participation does not make individuals better off in terms of wages or job stability compared with individuals experiencing neither training nor new technology adoption. |
| Keywords: | returns to education, training, technology |
| JEL: | I26 J24 J62 M53 O33 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16659&r=tid |
| By: | Richiardi, Matteo; Valenzuela, Luis |
| Abstract: | We propose a model-based decomposition method for the aggregate labour share in terms of the first moments of the joint distribution of TFP, market power, wages and prices, and apply it to UK manufacturing using firm-level data for 1998-2014. Contrary to a narrative focussing on increasing disparities between firms, the observed decline in the aggregate labour share over the period is driven entirely by the decline in the labour share of the representative firm, mostly due to an increasing disconnect between average productivity and real wages. Changes in the dispersion of firm-level variables have contributed to slightly contain this decline. |
| Date: | 2023–12–13 |
| URL: | http://d.repec.org/n?u=RePEc:ese:cempwp:cempa9-23&r=tid |
| By: | Pietro Santoleri (European Commission - JRC); Emanuele Russo (Bank of Italy) |
| Abstract: | In the attempt to boost innovation, policy-makers have enacted a myriad of programs targeting innovative start-ups in recent years. Empirical evidence on these initiatives has almost exclusively focused on national-level programs, overlooking those implemented at the local level. This paper provides the first quasi-experimental evidence on the joint effects of local policies focusing on Italy, where regional governments have been very active in providing financial support to these firms. By leveraging discontinuities in program design, we adopt a local randomization approach and document a null effect of these programs over a wide range of firm-level outcomes. However, we find that securing local subsidies increases start-ups' probability to obtain additional public subsidies, which points in the direction of a vicious “Matthew effect” in subsidy allocation. Consistent with a reputation/certification mechanism, the increase in follow-on subsidies occurs for funds disbursed at the local level only, whereas no effect is detected for subsidies allocated by national or international authorities. |
| Keywords: | Regression discontinuity design, Innovation Policy, Place-based Policy, Start-ups. |
| JEL: | D22 G24 G32 L53 O31 O38 R58 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:termod:202313&r=tid |
| By: | Nikolova, Milena (University of Groningen); Cnossen, Femke (University of Groningen); Nikolaev, Boris (Colorado State University) |
| Abstract: | This paper is the first to examine the impact of robotization on work meaningfulness and autonomy, competence, and relatedness, which are essential to motivation and well-being at work. Drawing on surveys from workers and industry-specific robotization data across 14 industries in 20 European countries from 2005 to 2021, our analysis reveals a consistent negative impact of robotization on perceived work meaningfulness and autonomy. Using instrumental variables, we find that doubling robotization correlates with a 0.9% decrease in work meaningfulness and a 1% decrease in autonomy. To put this in perspective, aligning the robotization intensity of the top five industry with the leading industry's robotization level in 2020—which would mean a 7.5-fold increase—would lead to a 6.8% reduction in work meaningfulness and a 7.5% reduction in autonomy. The link between robotization, competence, and relatedness is also negative but less robust. We also examine how tasks, skills, and socio-demographic characteristics moderate the relationship. We find that workers with routine tasks drive the negative effects of robotization on autonomy. However, we also discover that engaging in social tasks and utilizing computers as tools for independent work can help workers maintain a sense of autonomy in industries and job roles that adopt robots. Our results highlight that by deteriorating work meaningfulness and self-determination, robotization can impact work life above and beyond its consequences for employment and wages. |
| Keywords: | work meaningfulness, self-determination theory, robotization, automation |
| JEL: | J01 J30 J32 J81 I30 I31 M50 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16656&r=tid |
| By: | KOUAKOU, Dorgyles C.M.; YEO, Kolotioloma I.H. |
| Abstract: | A substantial body of literature has examined the determinants of the informal economy. However, this literature has predominantly focused on proximate causes, such as unemployment and taxation, while largely overlooking the role of innovation. This paper contributes to filling this gap by studying the impact of innovation production on the size of the informal economy using a sample of 138 countries, spanning the period from 2007 to 2018. Estimations, based on the entropy balancing method for continuous treatments, demonstrate that innovation reduces the size of the informal economy, emphasizing the importance of innovation policies in addressing informality. This result remains robust across a wide array of controls, alternative estimation techniques, restricted samples, and different measures of both the informal economy and innovation. The study identifies economic development, domestic credit mobilization, and e-government as channels through which innovation influences the informal economy. Potential government policies are explored. |
| Keywords: | Informal economy; Innovation; Economic development; Domestic credit mobilization; E-government; Entropy balancing |
| JEL: | O11 O17 O31 O38 |
| Date: | 2023–10–28 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:119264&r=tid |
| By: | Ruixue Jia; Xiao Ma; Jianan Yang; Yiran Zhang |
| Abstract: | This study investigates how enhanced regulation can promote innovation, focusing on the impacts of a significant regulatory reform in China's pharmaceutical sector implemented in 2015. Inspired by regulatory practices in the U.S., the reform aimed to address application backlogs and reduce administrative waiting time for new drug development. Using data at the drug and firm levels during 2012--2021, we make three main findings: (1) drug categories experiencing improved approval times witnessed a surge in investigational new drug applications and related clinical trials; (2) despite little improvement in innovativeness (measured by novel targets unexplored by U.S. counterparts) within drug categories, the reform led to changes in firm composition, attracting innovative new firms and boosting overall drug innovativeness; and (3) the market recognized the improvement in drug innovation, as reflected in stock price adjustments post new drug registrations after the reform. Our findings demonstrate that regulatory barriers can hinder the entry of innovative firms and suggest that latecomers could boost their innovation potential by adopting specific, effective regulatory practices from frontier countries. |
| JEL: | D22 I15 I18 O31 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31976&r=tid |
| By: | Carlos Bianchi (Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración. Instituto de Economía); Fernando Isabella (Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración. Instituto de Economía); Anaclara Martinis (Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración. Instituto de Economía); Santiago Picasso (Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración. Instituto de Economía) |
| Abstract: | This work analyses trajectories of structural change of countries trapped in middle-income trap (MIT) in a comprehensive manner from both the supply and the demand sides. First, it provides evidence that there is a regular trapping mechanism determined by the interaction between external demand constraints and the level of complexity of the economies. External constraint operates since MIT countries depend on exogenous prices to grow. Meanwhile, that constraint relaxes as the complexity of production increases. Second, this paper uses indicators of economic complexity and proposes a novel identification of the countries’ trajectories. A typology of the varieties of MIT is built according to the level of complexity of country economies and the relatedness between their current productive structure and more complex goods. It shows that having reached certain levels, further increases in supply complexity require a deepening of structural change through unrelated diversification. |
| Keywords: | middle-income trap, structural change, external restriction, economic complexity |
| JEL: | O14 O40 L16 |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:ulr:wpaper:dt-16-23&r=tid |
| By: | DELIS Fotis (European Commission - JRC); DELIS Manthos; LAEVEN Luc; ONGENA Steven |
| Abstract: | We provide estimates of profit shifting for over 2 million firm-year observations in 100 countries over the period 2009-2020. Employing nonparametric estimation techniques within a mainstay model of profit shifting, we examine how profits for both parent and subsidiary firms within a multinational group respond to marginal changes in the composite tax indicator. The key merit of this approach is that it yields firm-year estimates of profit shifting. We find that multinational firms engage in extensive profit shifting by maintaining affiliates in low-tax countries and zero-tax havens. Multinational groups with an ultimate owner in tax havens exhibit the largest responses of profits to the tax incentive. Our comprehensive estimates of global profit-shifting volumes exceed those obtained elsewhere in the literature using firm-level data and are in line with estimates obtained using macro-level data. Our new database opens important avenues to analyse the sources and effects of profit shifting. |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:taxref:202312&r=tid |