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AUTOMATION SIGNED

AUTOMATION AND INCOME DISTRIBUTION: A QUANTITATIVE ASSESSMENT

Total Cost €

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EC-Contrib. €

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Partnership

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Project "AUTOMATION" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITAT ZURICH 

Organization address
address: RAMISTRASSE 71
city: ZURICH
postcode: 8006
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Switzerland [CH]
 Total cost 1˙295˙890 €
 EC max contribution 1˙295˙890 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2018-STG
 Funding Scheme ERC-STG
 Starting year 2018
 Duration (year-month-day) from 2018-11-01   to  2023-10-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITAT ZURICH CH (ZURICH) coordinator 1˙295˙890.00

Map

 Project objective

Since the invention of the spinning frame, automation has been one of the drivers of economic growth. Yet, workers, economist or the general public have been concerned that automation may destroy jobs or create inequality. This concern is particularly prevalent today with the sustained rise in economic inequality and fast technological progress in IT, robotics or self-driving cars. The empirical literature has showed the impact of automation on income distribution. Yet, the level of wages itself should also affect the incentives to undertake automation innovations. Understanding this feedback is key to assess the long-term effect of policies. My project aims to provide the first quantitative account of the two-way relationship between automation and the income distribution. It is articulated around three parts. First, I will use patent data to study empirically the causal effect of wages on automation innovations. To do so, I will build firm-level variation in the wages of the customers of innovating firms by exploiting variations in firms’ exposure to international markets. Second, I will study empirically the causal effect of automation innovations on wages. There, I will focus on local labour market and use the patent data to build exogenous variations in local knowledge. Third, I will calibrate an endogenous growth model with firm dynamics and automation using Danish firm-level data. The model will replicate stylized facts on the labour share distribution across firms. It will be used to compute the contribution of automation to economic growth or the decline of the labour share. Moreover, as a whole, the project will use two different methods (regression analysis and calibrated model) and two different types of data, to answer questions of crucial policy importance such as: Taking into account the response of automation, what are the long-term effects on wages of an increase in the minimum wage, a reduction in labour costs, or a robot tax?

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The information about "AUTOMATION" are provided by the European Opendata Portal: CORDIS opendata.

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