CLEN Discussion Group: Access Barriers to Big Data

Seminar/Forum

CLEN Discussion Group: Access Barriers to Big Data

Room 608
Law
185 Pelham Street

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More information

T: 0390353068

law-clen@unimelb.edu.au

While data were always valuable in a range of economic activities, the advent of new and improved technologies for the collection, storage, mining, synthesizing, and analysis of data has led to the ability to utilize vast volumes of data in real-time in order to learn new information. Part I explores the four primary characteristics of big data: volume, velocity, variety, and veracity and their effects of the value of data. Part II analyzes the different types of access barriers that limit entry into the different links of the data value chain. In Part III, we tie together the characteristics of big data markets including potential entry barriers, to analyze their competitive effects. The analysis centers on those instances in which the unique characteristics of big data markets lead to variants in the more traditional competitive analysis. Our analysis suggests that the unique characteristics of big data have an important role to play in analyzing competition and in evaluating social welfare.

Presenter

  •  Daniel Rubinfeld
    Daniel Rubinfeld, University of California Berkeley