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Data, development, and growth

Abstract
Abstract

Economic development and growth theory have long grappled with the consequences of cross-border flows of goods, services, ideas, and people. But the most significant growth in cross-border flows now comes in the form of data. Like other flows, data flows can demonstrate imbalances among exports and imports. Some of these flows represent ‘raw’ data while others represent high-value-added data products. Does any of this make a difference in national economic development trajectories? This paper argues that the answer is yes. After reviewing the core logic of ‘high development theories’ from the twentieth century, I analyze the sometimes implicit applications of these arguments to data as they are evolving in the existing literature. I then put forward a different argument which takes better account of unique characteristics of the political economy that emerges at the intersection of data, machine learning, and the platform firms that use them. I explore the implications of this new argument for some policy choices that governments face with regard to data localization, import substitution, and other decisions relevant to growth in both advanced and emerging economies.

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* Corresponding author: Steven Weber, Professor, School of Information and Department of Political Science University of California Berkeley steve_weber@berkeley.edu
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Funding for this work was provided by the Hewlett Foundation via the Center for Long Term Cybersecurity at UC Berkeley; and by the Carnegie Corporation via the ‘Bridging the Gap’ grant program.

Acknowledgments: Thank you to Jesse Goldhammer, Stephane Grumbach, Phil Nolan, AnnaLee Saxenian, Naazneen Barma, Elliot Posner, two anonymous reviewers, and the Editors of Business and Politics for comments and critiques.

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This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

Min Chen , Shiwen Mao , and Yunhao Liu 2014. “Big Data: A Survey.” Mobile Networks and Applications 19 (2): 171209.

Yong Chen , 2016. “Big Data Analytics and Big Data Science: A Survey.” Journal of Management Analytics 3 (1): 142.

Aurelien Faravelon , Stephane Frenot and Grumbach Stephane 2016. “Chasing Data in the Intermediation Era: Economy and Security at Stake.” IEEE Security and Privacy Magazine, Economics of Cybersecurity, Part 2.

Samuel Fosso Wambe , 2015. “How Big Data Can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study.” International Journal of Production Economics 165: 234246.

Atish R. Ghosh , Jonathan D. Ostry , and Mahvash S. Qureshi . 2016. “When Do Capital Inflow Surges End in Tears?American Economic Review 106 (5).

Paul Krugman . 1992Toward a Counter Counter-Revolution in Development Theory.” World Bank Economic Review 6 (suppl 1): 1538.

Jean-Charles Rochet and Jean Tirole . 2006. “Two Sided Markets: A Progress Report.” Rand Journal of Economics 37 (3): 645667.

Dani Rodrik . 2005. “Growth Strategies.” In Handbook of Economic Growth Volume 1, edited by Philipe Again and Steven Durlauf , chapter 14.

Oliver E. Williamson 1981. “The Economics of Organization: The Transaction Cost Approach,” The American Journal of Sociology 87 (3): 548577.

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Business and Politics
  • ISSN: -
  • EISSN: 1469-3569
  • URL: /core/journals/business-and-politics
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