nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2023‒11‒27
six papers chosen by
Fulvio Castellacci, Universitetet i Oslo

  1. Knowledge spillovers from clean innovation. A tradeoff between growth and climate? By Ralf Martin; Dennis Verhoeven
  2. Artificial intelligence and the skill premium. By David E. Bloom; Klaus Prettner; Jamel Saadaoui; Mario Veruete
  3. New frontiers: The origins and content of new work, 1940-2018 By David Autor; Caroline Chin; Anna Salomons; Bryan Seegmiller
  4. Local and national concentration trends in jobs and sales: The role of structural transformation By David Autor; Christina Patterson; John Van Reenen
  5. Labor market turnover and inequality in Latin America By Menezes-Filho, Naercio; Narita, Renata
  6. Technologies follow technologies and occasionally social groups By Michael Huebler; Dorothee Buehler

  1. By: Ralf Martin; Dennis Verhoeven
    Abstract: Innovation policy faces a tradeoff between growth and climate objectives when the knowledge spillover externality from clean innovation is low compared to other sectors. To make such a comparison, we use patent data to estimate field-specific spillover returns generated by R&D support. Supporting Clean presents itself as a win-win opportunity, yielding global returns one-eighth higher than those of an untargeted policy. Nevertheless, only a modest portion of the returns stays within country borders, raising the question of whether national interests distort efficient allocation. Our policy simulations underscore the benefits of supranational coordination in clean innovation policy, potentially boosting returns by approximately 25% for the EU and over 60% globally. Moreover, the EU benefits strongly from US Clean innovation spillovers, impacting the debate on the Inflation Reduction Act. Overall, we identify no explicit innovation policy tradeoff in tackling the twin challenges of economic growth and climate change but emphasize the necessity for international cooperation.
    Keywords: innovation, knowledge spillovers, clean technology, innovation policy, green transition, net-zero, patent data, Economic geography, Green Growth, Productivity, Technological change
    Date: 2023–07–12
  2. By: David E. Bloom; Klaus Prettner; Jamel Saadaoui; Mario Veruete
    Abstract: What will likely be the effect of the emergence of ChatGPT and other forms of artificial intelligence (AI) on the skill premium? To address this question, we develop a nested constant elasticity of substitution production function that distinguishes between industrial robots and AI. Industrial robots predominantly substitute for low-skill workers, whereas AI mainly helps to perform the tasks of high-skill workers. We show that AI reduces the skill premium as long as it is more substitutable for high-skill workers than low-skill workers are for high-skill workers.
    Keywords: Automation, Artificial Intelligence, ChatGPT, Skill Premium, Wages, Productivity.
    JEL: J30 O14 O15 O33
    Date: 2023
  3. By: David Autor; Caroline Chin; Anna Salomons; Bryan Seegmiller
    Abstract: We address three core questions about the hypothesized role of newly emerging job categories ('new work') in counterbalancing the erosive effect of task-displacing automation on labor demand: what is the substantive content of new work; where does it come from; and what effect does it have on labor demand? To address these questions, we construct a novel database spanning eight decades of new job titles linked both to US Census microdata and to patent-based measures of occupations' exposure to labor-augmenting and labor-automating innovations. We find, first, that the majority of current employment is in new job specialties introduced after 1940, but the locus of new work creation has shifted - from middle-paid production and clerical occupations over 1940-1980, to high-paid professional and, secondarily, low-paid services since 1980. Second, new work emerges in response to technological innovations that complement the outputs of occupations and demand shocks that raise occupational demand; conversely, innovations that automate tasks or reduce occupational demand slow new work emergence. Third, although flows of augmentation and automation innovations are positively correlated across occupations, the former boosts occupational labor demand while the latter depresses it. Harnessing shocks to the flow of augmentation and automation innovations spurred by breakthrough innovations two decades earlier, we establish that the effects of augmentation and automation innovations on new work emergence and occupational labor demand are causal. Finally, our results suggest that the demand-eroding effects of automation innovations have intensified in the last four decades while the demand-increasing effects of augmentation innovations have not.
    Keywords: technological change, new tasks, augmentation, automation, demand shifts
    Date: 2022–12–06
  4. By: David Autor; Christina Patterson; John Van Reenen
    Abstract: National U.S. industrial concentration rose between 1992-2017. Simultaneously, the Herfindahl Index of local (six-digit-NAICS by county) employment concentration fell. This divergence between national and local employment concentration is due to structural transformation. Both sales and employment concentration rose within industry-by-county cells. But activity shifted from concentrated Manufacturing towards relatively unconcentrated Services. A stronger between-sector shift in employment relative to sales explains the fall in local employment concentration. Had sectoral employment shares remained at their 1992 levels, average local employment concentration would have risen by 9% by 2017 rather than falling by 7%. JEL: L11, L60, O31, O34, P33, R3
    Keywords: Employment concentration, sales concentration, local labor markets, structural transformation
    Date: 2023–04–19
  5. By: Menezes-Filho, Naercio; Narita, Renata
    Abstract: This paper describes the patterns of worker turnover in selected Latin American countries and their implications for wage inequality. It documents a higher positive annual wage growth rate for jobto-job changers compared to stayers, due to turnover capturing the immediate gains from search behavior in the short run. Younger workers benefit relatively more from the positive effects of jobto-job changes, as expected. We also show that transitions are relatively higher within the informal sector for most countries, and particularly so for workers without college education. Moreover, total job separations and transitions from formal into informal employment occur more often among low-skill and young individuals. Next, the paper analyzes wage growth by percentiles for all workers and job-to-job movers for each country over a more extended period. We find that jobto-job changes are inequality-reducing in the short run, consistent with search gains associated with turnover exhausting more rapidly for high-paid workers. In contrast, we find that human capital effects dominate the search effects in the long run, as human capital accumulates over time. Thus, long-run wage growth is lower for job changers than for stayers, so that, while in the short run the search effects tend to dominate those of human capital, in the long run the opposite occurs. As unskilled workers change jobs more frequently, this suggests that job changes are inequalityincreasing in the long run. A potential explanation for limited wage growth in Latin American economies may include high informality rates. Policies to reduce wage inequality should focus on improving the conditions for positive turnover towards better investment and, thus, higher-quality jobs.
    JEL: N0 R14 J01
    Date: 2023–09–01
  6. By: Michael Huebler; Dorothee Buehler
    Abstract: An innovative model describing the convergence of technology use at the micro level is introduced. ICT (information and communication technology) ownership, measured as the number of smartphones within a household, depends upon socioeconomic character- istics, such as income, education, technologies and occupation. ICT ownership and the socioeconomic characteristics are specified in relative terms between household pairs. Indicators for jointly belonging to a social group define a new explanatory variable type. Applying this model to survey and geographic data on rural households in Thailand and Vietnam, Heckman-type regressions show that better education and existing technologies unequivocally enhance convergence of ICT ownership among households, whereas the effect of social groups depends on the specific group. Self-employment or employment outside agriculture enhance convergence, whereas farming or employment in agriculture lead to divergence. The results advice policymakers to support the spread of ICT that provides access to valuable information and creates income-generating opportunities.
    Keywords: ICT, Smartphones, Technology diffusion, Rural development, Social networks
    JEL: F63 O33 Q12 Q17 Q54
    Date: 2023–10

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