Understanding the Federal Communication Commission's Policy-Making Using Big Data

11 Pages Posted: 2 Apr 2015

See all articles by Adam Candeub

Adam Candeub

Michigan State University - College of Law

Michael James Bommarito

Bommarito Consulting, LLC; Licensio, LLC; Stanford Center for Legal Informatics; Michigan State College of Law

Date Written: March 31, 2015

Abstract

The increasing availability of financial and consumer data through the internet as well as ever more accessible computing power to collect, organize, and analyze information has encouraged the widespread use of big data -- and has transformed all aspects of business from banking to retailing. On the other hand, big data has yet to play a role in our understanding of government, the administrative process, and policy-making.

In one of the first efforts to use big data to understand regulation and policy-making, we look to the Federal Communications Commission (FCC) and communications policy. In particular, we employ a unique data set representing the entire Electronic Comment Filing System (ECFS), a database that spans nearly three decades and includes virtually every formal submission to the FCC. Under agency regulation, all comments and other filings, including all replies, reports, applications, adjudication submissions, and, significantly, notices of ex parte meetings with commissioners and agency staff must be filed in ECFS. Our database has over 4 million specific records. In addition, we combine this database with another unique database derived from the official FCC Record, which publishes all agency action at a commission and bureau level.

Using various recursive regression techniques, we derive correlations between the activity of the commenters and ex parte meetings and agency action. Our tentative conclusions provide evidence on the drivers of FCC behavior. First, we find that comments and ex parte meeting are positively correlated with agency order production. While the causal arrow between these two variables is, of course, ambiguous, this result is expected given that comments and ex parte action likely both drive and anticipate agency action. On the other hand, we find significantly higher correlations between ex parte meetings and orders than comments and orders, suggesting a greater impact of ex parte meetings by elites as opposed to the broader community of commenters. This result has serious implications for how we understand the “democratic” nature of rule-making and other administrative practices.

Second, we extend this approach to examine correlations between FCC action and other variables. For instant, we examine how certain law firms and lobbying firms correlate with agency action. We also compare how these effects vary among the various FCC bureaus. We find variation in the correlations between particular firms and agency action, suggesting the existence of “insiders” at the FCC who have an advantage in getting the agency to do things.

Finally, we consider the role of correlation and big data analysis in policy formation. We argue from normative grounds that descriptive correlations offer a powerful tool to understanding institutions and how they form policy. These techniques deserve a wider acceptance in both legal scholarship and social science as big data becomes more easily available.

Keywords: FCC, big data, administrative law

JEL Classification: H11, K23

Suggested Citation

Candeub, Adam and Bommarito, Michael James, Understanding the Federal Communication Commission's Policy-Making Using Big Data (March 31, 2015). TPRC 43: The 43rd Research Conference on Communication, Information and Internet Policy Paper. Available at SSRN: https://ssrn.com/abstract=2588092

Adam Candeub (Contact Author)

Michigan State University - College of Law ( email )

318 Law College Building
East Lansing, MI 48824-1300
United States

Michael James Bommarito

Bommarito Consulting, LLC ( email )

MI 48098
United States

HOME PAGE: http://bommaritollc.com

Licensio, LLC ( email )

Okemos, MI 48864
United States

Stanford Center for Legal Informatics ( email )

559 Nathan Abbott Way
Stanford, CA 94305-8610
United States

Michigan State College of Law ( email )

318 Law College Building
East Lansing, MI 48824-1300
United States

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