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Rapid technological advances since the 1980s have revolutionized data gathering and changed the nature of many day-to-day transactions. Today, nearly every economic and financial transaction is recorded and can be linked to the individuals involved. This proliferation of “big data” makes it possible for economists and political scientists to empirically analyze the spending behavior of far greater numbers of individuals and firms, over much longer periods of time, than ever before. In “Big Data in Political Economy,” edited by Atif Mian and Howard Rosenthal, a group of quantitative researchers explore the possibilities and challenges of this data boom for the social sciences, focusing on how big data can help us gain new insights into such issues as social inequality, political polarization, and the influence of money in politics.
 
Among other topics, the articles in this issue demonstrate how large-scale data sources can be used to analyze campaign contributions and political participation. Adam Bonica outlines the development of a comprehensive “map” of the American political system that collects, processes, and organizes data on politicians’ campaign finances, policy positions, and voting records, and makes such information available to voters. Drew Dimmery and Andrew Peterson show how web-based data-gathering techniques can augment such a map to include political contributions made by nonprofits, which are often overlooked or not fully transparent. Deniz Igan links campaign contribution data to both policymakers’ voting records and financial institutions’ lending behavior and shows that legislators who were heavily lobbied by institutions engaging in risky lending, such as subprime lenders, were more likely to vote for deregulation. Chris Tausanovitch connects big data on voters’ income and policy preferences to the voting records of their congressional representatives in order to study how effectively the political system represents voters of different income levels. And Sharyn O’Halloran and coauthors discuss how big data can augment traditional observational research by replacing tedious hand coding of volumes of text with automated procedures.
 
As research in political economy increasingly focuses on the role of money in shaping the outcomes of elections and policymaking, new methods of aggregating and examining financial data have become central. Together, the papers in this volume show how big data provides unprecedented opportunities for social scientists to better understand the links between politics and markets.

In recent years many countries have liberalized their financial markets as a central element of their efforts to reform their economies and increase their economic growth rates. Financial deregulation leads to a fundamental restructuring of a country's economy and polity, as market forces, not state officials, begin to determine who obtains financial resources and at what cost. A critical question is whether countries can undertake a program of liberalization while undergoing democratic transformation. In this study, Arvid John Lukauskas explores why governments tightly regulate their country's financial system and why they choose to liberalize it. Using a rational choice approach, Lukauskas contends that public officials provide the dynamic behind the evolution of financial regulation as they seek to retain power and generate public revenue. Lukauskas argues that the nature of a country's political institutions shape the incentives facing politicians and influence whether they seek to regulate closely or liberalize financial markets in the pursuit of their goals. Lukauskas then tests his ideas in an in-depth case study of the evolution of financial policy in Spain, a country that transformed its financial system into a mostly market-based system after years of heavy state intervention, while undergoing a transformation from a dictatorship to a democracy. Contrary to the conventional wisdom that leaders will not undertake structural change during periods of democratization, he finds that leaders in Spain undertook financial liberalization despite opposition from powerful groups, because democratization gave Spanish leaders a strong incentive to improve economic performance through financial reform in order to compete for votes. Regulating Finance will be of interest to political scientists and economists interested in studying financial markets and the effects of regime change, including democratization, on economic reform.

Robert Gehl's timely critique, Reverse Engineering Social Media, rigorously analyzes the ideas of social media and software engineers, using these ideas to find contradictions and fissures beneath the surfaces of glossy sites such as Facebook, Google, and Twitter. 

 

Gehl adeptly uses a mix of software studies, science and technology studies, and political economy to reveal the histories and contexts of these social media sites. Looking backward at divisions of labor and the process of user labor, he provides case studies that illustrate how binary "Like" consumer choices hide surveillance systems that rely on users to build content for site owners who make money selling user data, and that promote a culture of anxiety and immediacy over depth.

 

Reverse Engineering Social Media also presents ways out of this paradox, illustrating how activists, academics, and users change social media for the better by building alternatives to the dominant social media sites.