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On the Employment Consequences of Automation and Offshoring: A Labor Market Sorting View
Ester Faia, Sébastien Laffitte, Maximilian Mayer, Gianmarco Ottaviano
Lili Yan Ing, Gene M. Grossman (eds), Robots and AI: A New Economic Era. Routledge: London,
2022
Abstract
We argue that automation may make workers and firms more selective in matching their specialized skills and tasks. We call this phenomenon “core-biased technological change”, and wonder whether something similar could be relevant also for offshoring. Looking for evidence in occupational data for European industries, we find that automation increases workers’ and firms’ selectivity as captured by longer unemployment duration, less skill-task mismatch, and more concentration of specialized knowledge in specific tasks. This does not happen in the case of offshoring, though offshoring reinforces the effects of automation. We show that a labor market model with two-sided heterogeneity and search frictions can rationalize these empirical findings if automation strengthens while offshoring weakens the assortativity between workers’ skills and firms’ tasks in the production process, and automation and offshoring complement each other. Under these conditions, automation decreases employment and increases wage inequality whereas offshoring has opposite effects.
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The Impact of Active Aggregate Demand on Utilisation-adjusted TFP
Konstantin Gantert
IWH Discussion Papers,
No. 9,
2022
Abstract
Non-clearing goods markets are an important driver of capacity utilisation and total factor productivity (TFP). The trade-off between goods prices and household search effort is central to goods market matching and therefore drives TFP over the business cycle. In this paper, I develop a New-Keynesian DSGE model with capital utilisation, worker effort, and expand it with goods market search-and-matching (SaM) to model non-clearing goods markets. I conduct a horse-race between the different capacity utilisation channels using Bayesian estimation and capacity utilisation survey data. Models that include goods market SaM improve the data fit, while the capital utilisation and worker effort channels are rendered less important compared to the literature. It follows that TFP fluctuations increase for demand and goods market mismatch shocks, while they decrease for technology shocks. This pattern increases as goods market frictions increase and as prices become stickier. The paper shows the importance of non-clearing goods markets in explaining the difference between technology and TFP over the business cycle.
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Do Digital Information Technologies Help Unemployed Job Seekers Find a Job? Evidence from the Broadband Internet Expansion in Germany
Nicole Gürtzgen, André Diegmann, Laura Pohlan, Gerard J. van den Berg
European Economic Review,
February
2021
Abstract
This paper studies effects of the introduction of a new digital mass medium on reemployment of unemployed job seekers. We combine data on high-speed (broadband) internet availability at the local level with German individual register data. We address endogeneity by exploiting technological peculiarities that affected the roll-out of high-speed internet. The results show that high-speed internet improves reemployment rates after the first months in unemployment. This is confirmed by complementary analyses with individual survey data suggesting that internet access increases online job search and the number of job interviews after a few months in unemployment.
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Promoting Higher Productivity in China — Does Innovation Expenditure Really Matter?
Hoang Minh Duy, Filippo di Mauro, Jo Van Biesebroeck
Singapore Economic Review,
No. 5,
2020
Abstract
The slowing down of the global economy adds additional challenges to China? economic policies as the country orchestrates its transition to lower resource dependency and higher technology intensity of output. Are policies aimed at technologically advanced sectors the right answer? Drawing from a newly created dataset of firms? balance sheets over the period 1998?2013, matched with patents data until 2009, we uncover that expenditure in innovation had limited effect on boosting productivity, without generating a clear gain in overall productivity for the high-tech sector. As a matter of fact, there is a much higher dispersion in productivity outcomes in firms belonging to the low-technology sectors, which derives from a bunch of champions in those sectors scoring higher productivity dynamics than in the High-technology sectors. The paper finds those barriers to entry and in general, market power of incumbents in the high-tech generate less than optimal resource reallocation, which hampers the overall productivity. Policies should presumably aim at removing such obstacles rather than solely promote innovation expenditure.
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