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on Innovation |
| By: | Montobbio, F.; Staccioli, J.; Virgillito, M.E.; Vivarelli, Marco |
| Abstract: | What have we learned, from the most recent years of debate and analysis, of the future of work being threatened by technology? This paper presents a critical review of the empirical literature and outlines both lessons learned and challenges ahead. Far from being fully exhaustive, the review intends to highlight common findings and main differences across economic studies. According to our reading of the literature, a few challenges-and also the common factors affecting heterogeneous outcomes across studies-still stand, including (i) the variable used as a proxy for technology, (ii) the level of aggregation of the analyses, (iii) the deep heterogeneity of different types of technologies and their adopted mix, (iv) the structural differences across adopters, and (v) the actual combination of the organisational practices in place at the establishment level in affecting net job creation/destruction and work re-organisation. |
| JEL: | O33 |
| Date: | 2022–11–17 |
| URL: | http://d.repec.org/n?u=RePEc:unm:unumer:2022037&r=ino |
| By: | Schubert, Torben; Ashouri, Sajad; Deschryvere, Matthias; Jäger, Angela; Visentin, Fabiana (RS: GSBE other - not theme-related research, Mt Economic Research Inst on Innov/Techn); Cunningham, Scott; Hajikhani, Arash; Pukelis, Lukas; Suominen, Arho |
| Abstract: | Digitalization is considered an important driver of the unravelling societal and economic transformations. However, holding both promises and challenges, its effects on the performance of individual firms are still underexplored. In this paper, we recognize that digitalization may take many shapes and try isolating the effects specifically of product digitization on firm level labour productivity. Our analyses are based on a large Europe-wide unique dataset combining structured information from ORBIS and PATSTAT with novel web-scraped information on digitalization in firms involved in high-tech manufacturing. We show that digitalization benefits productivity. However, the effect appears to result exclusively from product digitization, while a general digital intensity measure turned out to be insignificant. Moreover, we show that the effects are stronger for firms with higher initial productivity and firms located in countries considered digitally leading. Our results from the European high-tech sector suggest that the digital transformation in Europe is slow paced and scaled-up in only a fraction of the firms. |
| JEL: | O49 C81 O33 D20 O47 |
| Date: | 2023–02–14 |
| URL: | http://d.repec.org/n?u=RePEc:unm:unumer:2023004&r=ino |
| By: | Daisuke Matsuzaki; Yoshiyasu Ono |
| Abstract: | When faced with economic stagnation, innovation, product innovation in particular, is often cited as an effective stimulus because it is thought to encourage household consumption and lead to higher demand. Using a secular stagnation model with wealth preference, we examine the effects of product innovation on employment and consumption. Two types of product innovation are examined: quantity-augmenting-like innovation and addictive innovation. The former works as if a larger quantity were consumed although the actual quantity remains the same. The latter reduces the elasticity of the marginal utility of consumption. We find that the former reduces both consumption and employment whereas the latter expands them. |
| Date: | 2023–03 |
| URL: | http://d.repec.org/n?u=RePEc:dpr:wpaper:1204&r=ino |
| By: | Norbäck, Pehr-Johan (Research Institute of Industrial Economics (IFN)); Persson, Lars (Research Institute of Industrial Economics (IFN)) |
| Abstract: | The application of machine learning (ML) to big data has become increasingly important. We propose a model where firms have access to the same ML, but incumbents have access to historical data. We show that big data raises entrepreneurial barriers making the creative destruction process less destructive (less business-stealing) if the entrepreneur has weak access to the incumbent’s data. It is also shown that this induces entrepreneurs to take on more risk and be more creative. Policies making data generally available may therefore be suboptimal. Supporting entrepreneurs’ access to ML might be preferable since it stimulates creative entrepreneurship. |
| Keywords: | Machine Learning; Big Data; Creative Destruction; Entrepreneurship; Operational Data |
| JEL: | L10 L20 M13 O30 |
| Date: | 2023–02–22 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:iuiwop:1454&r=ino |
| By: | Bouscasse, P.; Nakamura, E.; Steinsson, J. |
| Abstract: | We provide new estimates of the evolution of productivity in England from 1250 to 1870. Real wages over this period were heavily influenced by plague-induced swings in the population. We develop and implement a new methodology for estimating productivity that accounts for these Malthusian dynamics. In the early part of our sample, we find that productivity growth was zero. Productivity growth began in 1600—almost a century before the Glorious Revolution. We estimate productivity growth of 3% per decade between 1600 and 1760, which increased to 6% per decade between 1770 and 1860. Our estimates attribute much of the increase in output growth during the Industrial Revolution to a falling land share of production, rather than to faster productivity growth. Our evidence helps distinguish between theories of why growth began. In particular, our findings support the idea that broad-based economic change preceded the bourgeois institutional reforms of 17th century England and may have contributed to causing them. We estimate relatively weak Malthusian population forces on real wages. This implies that our model can generate sustained deviations from the “iron law of wages†prior the Industrial Revolution. |
| JEL: | N13 O40 J10 |
| Date: | 2023–03–07 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:2323&r=ino |