nep-tid New Economics Papers
on Technology and Industrial Dynamics
Issue of 2020‒10‒05
eight papers chosen by
Fulvio Castellacci
Universitetet i Oslo

  1. Growing Like China: Firm Performance and Global Production Line Position By Davin Chor; Kalina B. Manova
  2. Automation, trade and multinational activity: Micro evidence from Spain By Katherine Stapleton; Michael Webb
  3. International Trade and Innovation Dynamics with Endogenous Markups By Laurent Cavenaile; Pau Roldan-Blanco; Tom Schmitz
  4. Role of quality differentiation on firm size distributions By William Connell Garcia; Hylke Vandenbussche
  5. Taxation and Innovation: What Do We Know? By Ufuk Akcigit; Stefanie Stantcheva
  6. Supervised learning for the prediction of firm dynamics By Falco J. Bargagli-Stoffi; Jan Niederreiter; Massimo Riccaboni
  7. Knowledge Intensity and Gender Wage Gaps: Evidence from Linked Employer-Employee Data By Radu Barza; Cristian Jara-Figueroa; César A. Hidalgo; Martina Viarengo
  8. Employment Reallocation over the Business Cycle: Evidence from Danish Data By Bertheau, Antoine; Bunzel, Henning; Vejlin, Rune Majlund

  1. By: Davin Chor; Kalina B. Manova
    Abstract: Global value chains have fundamentally transformed international trade and development in recent decades. We use matched firm-level customs and manufacturing survey data, together with Input-Output tables for China, to examine how Chinese firms position themselves in global production lines and how this evolves with productivity and performance over the firm lifecycle. We document a sharp rise in the upstreamness of imports, stable positioning of exports, and rapid expansion in production stages conducted in China over the 1992-2014 period, both in the aggregate and within firms over time. Firms span more stages as they grow more productive, bigger and more experienced. This is accompanied by a rise in input purchases, value added in production, and fixed cost levels and shares. It is also associated with higher pro fits though not with changing profit margins. We rationalize these patterns with a stylized model of the firm lifecycle with complementarity between the scale of production and the scope of stages performed.
    Keywords: global value chains, production line position, upstreamness, firm heterogeneity, firm lifecycle, China
    JEL: F10 F14 F23 L23 L24 L25
    Date: 2020
  2. By: Katherine Stapleton; Michael Webb
    Abstract: We use a rich dataset of Spanish manufacturing firms from 1990 to 2016 to shed new light on how automation in a high-income country affects trade and multinational activity involving lower-income countries. We exploit supply-side improvements in the capabilities of robots over time, as described in patents, that made it technically feasible to automate some specific tasks. We show that, contrary to the speculation that automation will cause reshoring, the use of robots in Spanish firms actually had a positive impact on their imports from, and number of affiliates in, lower-income countries. Robot adoption causes firms to expand production, increase productivity and makes them more likely to start importing from, or opening affiliates in, lower-income countries. The sequencing of automation and offshoring has important consequences for the impact of automation, however. For firms that had not already offshored to lower-income countries, robot adoption made them more likely to start doing so. By contrast, for firms that were already offshoring to lower-income countries, robot adoption had no effect on their value of imports from lower-income countries, but decreased their share of imports sourced from lower-income countries. We show that these findings can be explained in a framework that incorporates firm heterogeneity, the choice between automation, offshoring and performing tasks at home and where automation and offshoring both involve upfront fixed costs, such that their sequencing matters.
    Keywords: Automation; Robotics; Technology; Offshoring; Trade; Multinationals; Global supply chains; Heterogeneous firms; Labour share; Productivity
    JEL: F12 F16 J23 J24
    Date: 2020
  3. By: Laurent Cavenaile; Pau Roldan-Blanco; Tom Schmitz
    Abstract: Lower costs of international trade affect both firms’ innovation incentives and theirmarket power. We develop a dynamic general equilibrium model with endogenous innovation and endogenous markups to study the interaction between these effects. Lower trade costs stimulate innovation by large firms that are technologically close to their rivals. However, as innovators increase their productivity advantage over others, they also increase their markups. Our calibrated model suggests that a fall in trade costs which increases the trade-to-GDP ratio of the US manufacturing sector from 12% (its level in the 1970s) to 24% (its current level) increases productivity growth by 0.12 percentage points and the aggregate markup by 1.70 percentage points. Without the feedback effect of innovation on the productivity distribution, markups would actually have fallen. JEL codes: F43, F60, L13, O31, O32, O33, and O41. Keywords: International Trade, Markups, Innovation, R&D, Productivity.
    Date: 2020
  4. By: William Connell Garcia; Hylke Vandenbussche
    Abstract: The dispersion of firm size distributions vary strongly across sectors. Until now, sectoral variations in intra-industry heterogeneity were attributed to sectoral differences in the exogenous dispersion of the productivity of _rms, differences in sectoral horizontal differentiation, sectoral trade openness and country characteristics. In this paper, we build on this result by additionally examining the role of the sectoral scope for quality differentiation. Our theoretical and empirical findings reveal that whenever there is room for quality differentiation, the role of large firms is even stronger and inequality in firm size is exacerbated.
    Keywords: Size distribution of Firms, Power Law Distribution, Quality, Firm Level Analysis, Trade Openness
    Date: 2020
  5. By: Ufuk Akcigit (University of Chicago, CEPR and NBER); Stefanie Stantcheva (Harvard University, CEPR and NBER)
    Abstract: Tax policies are a wide array of tools, commonly used by governments to influence the economy. In this paper, we review the many margins through which tax policies can affect innovation, the main driver of economic growth in the long-run. These margins include the impact of tax policy on i) the quantity and quality of innovation; ii) the geographic mobility of innovation and inventors across U.S. states and countries; iii) the declining business dynamism in the U.S., firm entry, and productivity; iv) the quality composition of firms, inventors, and teams; and v) the direction of research effort, e.g., toward applied versus basic research, or toward dirty versus clean technologies. We give ideas drawn from research on how the design of policy can allow policy makers to foster the most productive firms without wasting public funds on less productive ones.
    Date: 2020
  6. By: Falco J. Bargagli-Stoffi; Jan Niederreiter; Massimo Riccaboni
    Abstract: Thanks to the increasing availability of granular, yet high-dimensional, firm level data, machine learning (ML) algorithms have been successfully applied to address multiple research questions related to firm dynamics. Especially supervised learning (SL), the branch of ML dealing with the prediction of labelled outcomes, has been used to better predict firms' performance. In this contribution, we will illustrate a series of SL approaches to be used for prediction tasks, relevant at different stages of the company life cycle. The stages we will focus on are (i) startup and innovation, (ii) growth and performance of companies, and (iii) firms exit from the market. First, we review SL implementations to predict successful startups and R&D projects. Next, we describe how SL tools can be used to analyze company growth and performance. Finally, we review SL applications to better forecast financial distress and company failure. In the concluding Section, we extend the discussion of SL methods in the light of targeted policies, result interpretability, and causality.
    Date: 2020–09
  7. By: Radu Barza; Cristian Jara-Figueroa; César A. Hidalgo; Martina Viarengo
    Abstract: Do knowledge intense jobs exhibit lower gender gaps in wages? Here we use a linked employeremployee dataset of the entire Brazilian formal labor force to study the relationship between gender wage gaps and the knowledge intensity of industries and occupations. We find that employees in high-skilled occupations and industries experience lower gender wage gaps, and that the effect of knowledge intensity is stronger when the demand for skilled labor is high and the supply of skilled labor is low. We also find evidence that the gender wage gap of skilled workers, but not that of unskilled workers, decreases when knowledge intense industries grow. These effects are robust to controlling for individual, occupation, sector, and location characteristics. To address endogeneity concerns, we use a Bartik instrument based on labor demand shocks. Together, these findings suggest that competition for skilled labor in knowledge intense industries contributes to the reduction of gender wage gaps.
    Date: 2020
  8. By: Bertheau, Antoine (University of Copenhagen); Bunzel, Henning (Aarhus University); Vejlin, Rune Majlund (Aarhus University)
    Abstract: We present new evidence on how employment growth varies across firm types (size, productivity, and wage) and over the business cycle using Danish data covering almost 30 years. We decompose net employment growth into two recruitment margins: net hirings from/to employment (poaching) and net hirings from nonemployment. High-productivity firms are the most growing firms due to poaching. High wage firms poach almost as many workers, but shed an almost equal amount to non-employment. Large firms do not poach workers from smaller firms. In terms of employment cyclicality, we find that low-productive and low-wage firms shed proportionally more jobs in recessions. We relate our findings to recent models of employment fluctuations that jointly analyze worker and firm dynamics.
    Keywords: worker flows, firm heterogeneity, matched employer-employee data, business cycle, equilibrium search models
    JEL: E24 E32 J63
    Date: 2020–09

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