Complex systems and a computational social science perspective on the labor market
Name
958684972-MIT.pdf
Description
Full printable version
Size
20.48 MB
Format
Adobe PDF
Checksum (MD5)
e070669d5c3f8d296545791609e1f9cb
Author(s)
Almaatouq, Abdullah
Advisor(s)
Alex (Sandy) Pentland and Olivier de Weck.
Alternative Title
Computational social science perspective on the labor market
Date Issued
2016
Publisher
Massachusetts Institute of Technology
Abstract
Labor market institutions are central for modern economies, and their polices can directly affect unemployment rates and economic growth. At the individual level, unemployment often has a detrimental impact on people's well-being and health. At the national level, high employment is one of the central goals of any economic policy, due to its close association with national prosperity. The main goal of this thesis is to highlight the need for frameworks that take into account the complex structure of labor market interactions. In particular, we explore the benefits of leveraging tools from computational social science, network science, and data-driven theories to measure the flow of opportunities and information in the context of the labor market. First, we investigate our key hypothesis, which is that opportunity/information flow through weak ties, and this is a key determinant of the length of unemployment. We then extend the idea of opportunity/information flow to clusters of other economic activities, where we expect the flow within clusters of related activities to be higher than within isolated activities. This captures the intuition that within related activities there are more "capitals" involved and that such activities require similar "capabilities." Therefore, more extensive clusters of economic activities should generate greater growth through exploiting the greater flow of opportunities and information. We quantify the opportunity/information flow using a complexity measure of two economic activities (i.e. jobs and exports).
Description
Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 99-109).
Thesis: S.M.. Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2016.
Subjects
Program in Media Arts and Sciences ()
MIT Department
Massachusetts Institute of Technology. Computation for Design and Optimization Program
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Persistent DSpace Link
