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on Technology and Industrial Dynamics |
| By: | Thomas Fackler; Oliver Falck; Moritz Goldbeck; Fabian Hans; Annina Hering |
| Abstract: | We investigate differences in labor demand between German automotive firms specializing in green propulsion technology and those with a focus on combustion engines. To this end, we introduce a firm-level labor demand index based on the near-universe of online job postings and firms’ patent portfolios. Workforce adjustments are a crucial dimension of technology-related structural change, and labor demand as a highly reactive decision parameter is an ideal measure to detect employment adjustments. Our index enables us to distinguish labor demand by firms’ greenness in real-time, a notable advantage over survey or administrative data. In a difference-in-differences setup, we exploit the poly-crisis triggered by unexpected escalations of trade conflicts and sustained by consequences of the pandemic and the war in Ukraine. We find green firms’ labor demand is significantly and persistently higher than before the outbreak of the poly-crisis, by 34 to 50 percentage points compared to firms with a focus on combustion technology. This gap widens over time and is not driven by unobserved firm heterogeneity. Green firms systematically adjust labor demand towards production and information technology jobs. |
| Keywords: | low carbon technology, firm employment decisions, sustainability, disruptive innovation |
| JEL: | C55 J23 M51 O14 O33 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11160&r= |
| By: | Maynou, Laia; McGuire, Alistair; Serra-Sastre, Victoria |
| Abstract: | Increasing evidence suggests that new technologies tend to substitute for low skilled labour and complement highly skilled labour. This paper considers the manner in which new technology impacts on two distinct groups of highly skilled health care labour, cardiologists and cardiac surgeons. We consider the diffusion impact of PCI as it replaces CABG in the treatment of cardiovascular disease in the English NHS, and explicitly estimate the degree to which the cardiac surgical workforce reacts to this newer technology. Using administrative data we trace the complementarity between CABG and PCI during the mature phase of technology adoption, mapped against an increasing employment of cardiologists as they replace cardiothoracic surgeons. Our findings show evidence of growing employment of cardiologists, as PCI is increasingly expanded to older and sicker patients. While in cardiothoracic surgery, surgeons compensate falling CABG rates in a manner consistent with undertaking replacement activity and redeployment. While for cardiologists this reflects the general findings in the literature, that new technology enhances rather than substitutes for skilled labour, for the surgeons the new technology leads to redeployment rather than a downsizing of their labour. |
| Keywords: | complementarity; high-skilled workforce; task reallocation; technological diffusion; workforce elasticity |
| JEL: | R14 J01 |
| Date: | 2024–07–01 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:124065&r= |
| By: | Batabyal, Amitrajeet; Kourtit, Karima; Nijkamp, Peter |
| Abstract: | We analyze economic growth in a stylized, high-tech region A with two key features. First, the residents of this region are high-tech because they possess skills. In the language of Richard Florida, these residents comprise the region’s creative class and they possess creative capital. Second, the region is high-tech because it uses an artificial intelligence (AI)-based technology and we model the use of this technology. In this setting, we first derive expressions for three growth metrics. Second, we use these metrics to show that the economy of A converges to a balanced growth path (BGP). Third, we compute the growth rate of output per effective creative capital unit on this BGP. Fourth, we study how heterogeneity in initial conditions influences outcomes on the BGP by introducing a second high-tech region B into the analysis. At time t=0, two key savings rates in A are twice as large as in B. We compute the ratio of the BGP value of income per effective creative capital unit in A to its value in B. Finally, we compute the ratio of the BGP value of skills per effective creative capital unit in A to its value in B. |
| Keywords: | Artificial Intelligence, Creative Capital, Regional Economic Growth, Skills |
| JEL: | O33 R11 |
| Date: | 2023–12–11 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:121328&r= |
| By: | Croce, Giuseppe; Piselli, Paolo |
| Abstract: | The gap in the employment dynamics between larger urban areas and other areas has widened dramatically in recent decades in advanced economies. A proposed explanation for this trend argues that the technological change occurs with greater intensity in larger urban areas than in medium and small cities, since it interacts with the urban agglomeration forces. In particular, more qualified, better paid jobs are expected to grow more in larger cities. This work focuses on the dynamics of most paying jobs and their spatial distribution across different-size cities in Italy in the period between 1993 and 2016. We investigate whether their share has grown and whether its growth has actually been concentrated in the larger cities. Using Bank of Italy’s Survey of Household Income and Wealth (SHIW), we find that the share of most paying jobs has increased in aggregate but its growth in large cities was much weaker than in medium and small cities and even negative after 2008. We also estimate a probit IV model of the worker’s probability of being employed in a most paying job across cities. The results show that being in a bigger city does not increase the chances of getting a better paid job. Furthermore, a shift-share decomposition reveals that the weak growth of most paying jobs in larger cities is only partly explained by the sectoral shifts. Our evidence can be explained by the slow diffusion of new technologies in the Italian economy. Moreover, it is consistent with studies showing the poor performance of the largest urban economies in Italy. |
| Keywords: | employment change, technological change, most paying jobs, cities, local labour markets, agglomeration |
| JEL: | J24 J31 O14 O18 O33 R11 |
| Date: | 2024–06–18 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:121228&r= |
| By: | Dawid, Herbert; Neugart, Michael |
| Abstract: | The advent of artificial intelligence is changing the task allocation of workers and machines in firms’ production processes with potentially wide ranging effects on workers and firms. We develop an agent-based simulation framework to investigate the consequences of different types of automation for industry output, the wage distribution, the labor share, and industry dynamics. It is shown how the competitiveness of markets, in particular barriers to entry, changes the effects that automation has on various outcome variables, and to which extent heterogeneous workers with distinct general skill endowments and heterogeneous firms featuring distinct wage offer rules affect the channels via which automation changes market outcomes. |
| Date: | 2024–06–25 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:146300&r= |
| By: | Alexander Quispe; Rodrigo Grijalba |
| Abstract: | Advancements in Artificial Intelligence, particularly with ChatGPT, have significantly impacted software development. Utilizing novel data from GitHub Innovation Graph, we hypothesize that ChatGPT enhances software production efficiency. Utilizing natural experiments where some governments banned ChatGPT, we employ Difference-in-Differences (DID), Synthetic Control (SC), and Synthetic Difference-in-Differences (SDID) methods to estimate its effects. Our findings indicate a significant positive impact on the number of git pushes, repositories, and unique developers per 100, 000 people, particularly for high-level, general purpose, and shell scripting languages. These results suggest that AI tools like ChatGPT can substantially boost developer productivity, though further analysis is needed to address potential downsides such as low quality code and privacy concerns. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.11046&r= |
| By: | Carlo Bottai; Jacopo Di Iorio; Martina Iori |
| Abstract: | Economic growth results from countries' accumulation of organizational and technological capabilities. The Economic and Product Complexity Indices, introduced as an attempt to measure these capabilities from a country's basket of exported products, have become popular to study economic development, the geography of innovation, and industrial policies. Despite this reception, the interpretation of these indicators proved difficult. Although the original Method of Reflections suggested a direct interconnection between country and product metrics, it has been proved that the Economic and Product Complexity Indices result from a spectral clustering algorithm that separately groups similar countries or similar products, respectively. This recent approach to economic and product complexity conflicts with the original one and treats separately countries and products. However, building on previous interpretations of the indices and the recent evolution in spectral clustering, we show that these indices simultaneously identify two co-clusters of similar countries and products. This viewpoint reconciles the spectral clustering interpretation of the indices with the original Method of Reflections interpretation. By proving the often neglected intimate relationship between country and product complexity, this approach emphasizes the role of a selected set of products in determining economic development while extending the range of applications of these indicators in economics. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.16199&r= |
| By: | Mai Dao; Josef Platzer |
| Abstract: | We study U.S. labor productivity growth and its drivers since the COVID-19 pandemic. Labor productivity experienced large swings since 2020, due to both compositional and within-industry effects, but has since returned to its pre-pandemic trend. Industry-level panel regressions show that measures of labor market churn are associated with higher productivity growth both in the cross-section and over time. Sectors with higher investment in digitalization, particularly in teleworkable industries, also experience higher productivity growth on average. There has also been an increase in business formation since the pandemic, but its impact on productivity dynamics will likely need more time to be reflected in the data. |
| Keywords: | Productivity; COVID-19; Digitalization |
| Date: | 2024–06–21 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2024/124&r= |
| By: | Dawid, Herbert; Gemkow, Simon; Harting, Philipp; Kabus, Kordian; Neugart, Michael; Wersching, Klaus |
| Abstract: | We develop an agent-based macroeconomic model featuring a distinct geographical dimension and heterogeneous workers with respect to skill types. The model, which will become part of a larger simulation platform for European policymaking (EURACE), allows us to conduct exante evaluations of a wide range of public policy measures and their interaction. In particular, we study the growth and labor market effects of various policy types that promote workers’ general skill levels. Using a calibrated model it is examined in how far effects differ if spending is uniformly spread over all regions in the economy or focused in one particular region. We find that the geographic distribution of policy measures significantly affects the effects of the policy even if total spending is kept constant. Focussing training efforts in one region is the worst policy outcome while spreading funds equally across regions generates a larger output in the long-run but not in the short-run. |
| Date: | 2024–07–01 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:146365&r= |
| By: | Ofori, Pamela E.; Ofori, Isaac K.; Castelnovo, Paolo |
| Abstract: | The Sustainable Development Goal 5 emphasises the need to achieve gender parity in economic participation. Perusing the extant scholarship on female economic inclusion in Africa, we identify two pressing gaps. First, we find that previous studies have not explored how innovation affects female economic inclusion (FEI). Second, we note that prior studies have not examined the interactive effect of innovation and economic freedom on FEI. This study addresses these gaps by using macro data from 1995-2022 for a sample of 51 African countries. Findings from the two-step system GMM estimator reveal the following: (1) innovation reduces FEI, whereas economic freedom increases it, and (2) economic freedom moderates innovation to promote FEI. Further, we find that this positive total effect of innovation on FEI is remarkable at higher thresholds of economic freedom. We conclude that for innovation to promote FEI in Africa, investments in promoting economic freedom are critical. |
| Keywords: | Africa; Innovation; Economic freedom; Female economic inclusion, GMM. |
| JEL: | E24 J16 J21 O31 O55 |
| Date: | 2024–03–15 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:121244&r= |