nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2020‒01‒13
ten papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. Productivity & Innovation Competencies in the Midst of the Digital Transformation Age: A EU-US Comparison By Bart van Ark; Klaas de Vries; Abdul Erumban
  2. Robots & the Rise of European Superstar Firms By Jens Suedekum; Nicole Woessner
  3. AI and Robotics Innovation: a Sectoral and Geographical Mapping using Patent Data By Van Roy, Vincent; Vertesy, Daniel; Damioli, Giacomo
  4. Misallocation, Selection and Productivity: A Quantitative Analysis with Panel Data from China By Tasso Adamopoulos; Loren Brandt; Jessica Leight; Diego Restuccia
  5. Learning Before and After the Global Crisis: Firm-level Innovation in Latin America By King Yoong Lim; Diego Morris
  6. Frontier and Superstar Firms in Italy. By Francesca Lotti; Enrico Sette
  7. Competitive strategies, heterogeneous demand sources and firms’ growth trajectories By Caravella, Serenella; Crespi, Francesco; Guarascio, Dario; Tubiana, Matteo
  8. Institutions and the Productivity Challenge for European Regions By Andrés Rodríguez-Pose; Roberto Ganau
  9. A multi-sector model of relatedness, growth and industry clustering By Steven Bond-Smith; Philip McCann
  10. Barriers to Entry and Regional Economic Growth in China By Loren Brandt; Gueorgui Kambourov; Kjetil Storesletten

  1. By: Bart van Ark; Klaas de Vries; Abdul Erumban
    Abstract: This paper reviews the latest evidence on productivity growth by industry and innovation competencies by occupation to observe whether, beneath the productivity slowdown of the past decade in both the European Union and the United States, signs can be detected of structural performance improvements due to digital transformation. We find that in the United States, the digital-producing sector has continued to contribute strongly to aggregate productivity in recent years. While labour productivity growth in the US was only 0.6 percent from 2013-2017, as much as 0.5 percentage point (or 86 percent) was coming from digital-producing industries representing only 8.2 percent of US GDP. Other industries, which account for the remaining 92 percent of the US economy, including some of the most digital intensive-using industries, have seen a dramatic decline in their contribution to productivity growth. In the European Union, the digital-producing sector has seen a strong decline in its contribution to productivity growth, which by 2013-2017 was only one third of the US contribution at 0.15 percentage points. However, the most digital intensive-using industries contributed 4 times as much to labor productivity as in the United States, driving overall labour productivity growth from 2013-2017 up to 0.9 percentage point – 0.3 percentage points higher than in the US. A positive factor, both in the EU and in the US, is that total factor productivity (TFP) growth in the most intensive digital-producing industries, notably trade and business services has improved. Digital intensiveusing manufacturing industries generally contribute less to productivity than digital intensive-using services, partly because of slower productivity growth and partly because of their smaller size. A novel measure of innovation competencies by occupation shows that, when applied to industries, those industries with the highest competencies, also show positive productivity contributions, and the most intensive digital-using industries are strongly represented in this category. Overall, while the evidence is still thin due to time lags in the data, there are signs of positive contributions to productivity growth related to digital transformation even though those effects are still not widespread observable across the economy.
    JEL: O40 O47 O30
    Date: 2019–10
  2. By: Jens Suedekum; Nicole Woessner
    Abstract: We estimate the impact of a recent digital automation technology - industrial robotics - on the distribution of productivity and markups within industries. Our empirical analysis combines data on the industry-level stock of industrial robots with firms' balance sheet data for six European countries from 2004 to 2013. We find that robots dis-proportionally raise productivity in those firms that are already most productive to begin with. Those firms are able to increase their markups, while markups tend to decline for less profitable firms within the same industry, country and year. We also show that industrial robots contribute to the falling aggregate labour income share through a rising concentration of industry sales. In short, our paper suggests that robots boost the emergence of superstar firms within European manufacturing, and thereby shifts the functional income distribution away from wages and towards profits.
    JEL: D4 L11 O33
    Date: 2019–10
  3. By: Van Roy, Vincent; Vertesy, Daniel; Damioli, Giacomo
    Abstract: Economic activities based on the invention, production and distribution of artificial intelligence (AI) technologies have recently emerged worldwide. Yet, little is known about the innovative activities, location and growth performance of AI innovators. This chapter aims to map and analyse the global innovative landscape of AI by exploring 155,000 patents identified as AI-related by means of text-mining techniques. It highlights the emergence and evolution of AI technologies and identifies AI hotspots across the world. It explores the scale and pervasiveness of AI activities across sectors, and evaluates the economic performance of AI innovators using firm accounting information. Finally, it assesses recent trends in venture capital investments towards AI as financial support to promising AI startups. Findings of this chapter reveal a tremendous increase in AI patenting activities since 2013 with a significant boom in 2015-2016. While most of AI patenting activities remain concentrated in the sectors of software programming and manufacturing of electronic equipment and machinery, there are clear signs of cross-fertilisation towards (non-tech) sectors. The market of AI patenting firms is very vibrant and characterised by a large increase of new and small players with economic performances above industry average. This trend is also reflected by the recent increase in venture capital towards AI startups.
    Keywords: Artificial intelligence,innovation,patents,robotics
    JEL: O31 O33
    Date: 2019
  4. By: Tasso Adamopoulos; Loren Brandt; Jessica Leight; Diego Restuccia
    Abstract: We use household-level panel data from China and a quantitative framework to document the extent and consequences of factor misallocation in agriculture. We find that there are substantial within-village frictions in both the land and capital markets linked to land institutions in rural China that disproportionately constrain the more productive farmers. These frictions reduce aggregate agricultural productivity in China by affecting two key margins: (1) the allocation of resources across farmers (misallocation) and (2) the allocation of workers across sectors, in particular the type of farmers who operate in agriculture (selection). We show that selection can substantially amplify the static misallocation effect of distortionary policies by affecting occupational choices that worsen the distribution of productive units in agriculture.
    Keywords: agriculture, misallocation, selection, productivity, China.
    JEL: O11 O14 O4 E02 Q1
    Date: 2019–12–31
  5. By: King Yoong Lim; Diego Morris
    Abstract: Economic shocks of the kind we recently witnessed with the 2008 global financial and economic crisis do not come around very often but when they do, their effect can be catastrophic, not the least because of their impact on businesses. Existing theories of how firms react to crises such as these are ambiguous and very little empirical evidence exist, particularly for the developing world. As such, our main contribution to the literature is to shed light on these issues, articulating a theoretical framework and testing it using three waves of cross-country innovation identifying survey implemented by the World Bank in Latin American economies. The three waves coincide with a timespan that covers before, during, and after the global crises. Our results provide strong support that firms alter their practices and witness different profit outcomes before and after a downturn depending on innovation decisions. In fact, we find evidence that indicates that the profitability gains from new products for firms may be higher during downturns.
    Keywords: Economic crisis, Innovation, Latin America, Productivity.
    JEL: D22 D24 O30 O31
    Date: 2020–01
  6. By: Francesca Lotti (Bank of Italy); Enrico Sette (Bank of Italy)
    Abstract: We study the dynamics of firms in the top decile of the TFP distribution in Italy (frontier firms). Using granular microdata from the census of corporations, we show their main characteristics, their weight in terms of revenues and employment, and measure their persistency in the top deciles of the TFP distribution. Frontier firms are more profitable, less likely to go bankrupt and younger; they invest more and use less long-term bank debt to finance their assets; and they are larger in terms of revenues, but not in terms of employees. Finally, we gauge their contribution to aggregate TFP growth, finding that TFP growth of frontier firms has intensified over time, as did the divide between firms at the top and the bottom of the TFP distribution. However, the market share of frontier firms only increased over time in the business services and transportation sectors; there is no increase, and in some cases, there is actually a decrease in other industries, notably in manufacturing. Hence, we do not find strong evidence of superstar firm effects, except in business services.
    Keywords: productivity, firm dynamics, reallocation, market power.
    JEL: D24 O47 L16
    Date: 2019–12
  7. By: Caravella, Serenella; Crespi, Francesco; Guarascio, Dario; Tubiana, Matteo
    Abstract: The present paper explores the demand-pull effect of distinct demand sources (i.e. households and retailers, other firms and public sector) on Italian companies’ growth patterns. Data relies on the PEC (Indagine sulle Professioni e le Competenze) survey carried out by the Institute for Public Policy Analysis (INAPP), which provides a rich set of information on a representative sample of Italian companies (~32.000) observed during the years 2012, 2014 and 2017. In particular, we investigate if and to what extent firm-level growth profiles are linked to the prevalent source of the demand flows that such firms face. The analysis contextually accounts for the role played by technological and knowledge-related heterogeneities in shaping the growth pattern-demand type relationship. The empirical analysis shows that the demand-pull effect on firms’ growth is heterogeneous across different types of demand sources and that the ability to seize the growth-related chances provided by distinct demand conditions is contingent on firms’ specific knowledge profiles.
    Keywords: firms,growth,demand-pull,innovation
    JEL: L1 L21 L22 L25
    Date: 2020
  8. By: Andrés Rodríguez-Pose; Roberto Ganau
    Abstract: Europe has witnessed a considerable labour productivity slowdown in recent decades. Many potential explanations have been put forward to try to address this so-called productivity ‘puzzle’. However, how the quality of local institutions influences labour productivity in different parts of Europe has been, so far, overlooked by the literature. This paper addresses this gap in our knowledge by evaluating how the quality of local institutions affects changes in labour productivity at a regional level, across 248 European regions during the period between 2003 and 2015. The results indicate that institutional quality plays a crucial role in determining different regional labour productivity trajectories. This role is both direct – as improvements in institutional quality have a substantial impact on productivity growth – as well as indirect – as the returns of investments in human capital and local innovative capacity rise significantly as the quality of government increases.
    JEL: E24 J24 O47 R11
    Date: 2019–10
  9. By: Steven Bond-Smith (Bankwest Curtin Economic Centre, Curtin University); Philip McCann (Faculty of Spatial Sciences, University of Groningen)
    Abstract: This article builds an understanding of regional innovation specialization by developing a multi-sector model with endogenous growth through quality improving innovations and spillovers from related technologies. The model provides an approach to incorporate the relatedness literature within the mainstream theoretical frameworks of endogenous growth and economic geography. Each firm’s technology sector and the location of other firms play a role in each firm’s ability to improve its own technology. As a result, firms prefer to co-locate in technologically compatible clusters. Without relying on scale assumptions, the model for the first time coherently links related variety knowledge spillovers to mainstream urban economic frameworks and demonstrates that clustering is possible in both core and peripheral areas.
    Keywords: Innovation; endogenous growth; knowledge spillovers; relatedness; clusters
    JEL: R11 O41
    Date: 2019–09
  10. By: Loren Brandt; Gueorgui Kambourov; Kjetil Storesletten
    Abstract: Labor productivity in manufacturing differs starkly across regions in China. We document that productivity, wages, and start-up rates of non-state firms have nevertheless experienced rapid regional convergence after 1995. To analyze these patterns, we construct a Hopenhayn (1992) model that incorporates location-specific capital wedges, output wedges, and entry barriers. Using Chinese Industry Census data we estimate these wedges and examine their role in explaining differences in performance and growth across prefectures. Entry barriers explain most of the differences. We investigate the empirical covariates of these entry barriers and find that barriers are causally related to the size of the state sector
    Keywords: Chinese economic growth; SOEs; firm entry; entry barriers; capital wedges; output wedges; SOE reform.
    JEL: O11 O14 O16 O40 O53 P25 R13 D22 D24 E24
    Date: 2020–01–05

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