Understanding Unemployment in the Era of Big Data: Policy Informed by Data-Driven Theory

23 Pages Posted: 17 Jan 2016

See all articles by Omar A Guerrero

Omar A Guerrero

The Alan Turing Institute; University College London - Department of Economics

Eduardo Lopez

University of Oxford - Said Business School

Multiple version iconThere are 2 versions of this paper

Date Written: January 15, 2016

Abstract

On one hand, unemployment is a central issue in all countries. On the other the economic policies designed to mitigate it are usually built on theoretical grounds that are validated at an aggregate level, but have little or no validity from a micro point of view. This situation is a cause for concern because policies are designed and implemented at the level of individuals and organisations, so ignoring realistic micro-mechanisms may lead to costly outcomes in the real world. Ironically, the data to inform theoretical frameworks at the micro-level has existed in labour studies since the 1980's. However, it is only now that we count with analytical methods and computational tools to take full advantage of it. In this paper we argue that big data from administrative records, in conjunction with network science and agent-computing models offer new opportunities to inform unemployment theories and improve policies. We introduce a data-driven model of unemployment dynamics and compare its predictions against a conventional theory built on assumptions that are common among policy models. We show that these assumptions, while reasonable at a first glance, lead to erroneous predictions that have real-world consequences.

Keywords: Unemployment, labor flows, networks, policy, big data, agent-based modeling, economics

Suggested Citation

Guerrero, Omar A and Lopez, Eduardo, Understanding Unemployment in the Era of Big Data: Policy Informed by Data-Driven Theory (January 15, 2016). Available at SSRN: https://ssrn.com/abstract=2716264 or http://dx.doi.org/10.2139/ssrn.2716264

Omar A Guerrero (Contact Author)

The Alan Turing Institute ( email )

96 Euston Road
London, NW1 2DB
United Kingdom

University College London - Department of Economics ( email )

Drayton House, 30 Gordon Street
30 Gordon Street
London, WC1H 0AX
United Kingdom

Eduardo Lopez

University of Oxford - Said Business School ( email )

Park End Street
Oxford, OX1 1HP
Great Britain

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