We study a model where firms accumulate data as a valuable intangible asset. Data accumulation affects firms' dynamics. It increases the skewness of the firm size distribution as large firms generate more data and invest more in active experimentation. On the other hand, small data- savvy firms...

One of the most important trends in modern macroeconomics is the shift from small firms to large firms. At the same time, financial markets have been transformed by advances in information technology. We explore the hypothesis that the use of big data in financial markets has lowered the cost of...

Income inequalities have increased in most OECD countries over the past decades; particularly the income share of the top 1%. In this paper we argue that the growing importance of digital innovation – new products and processes based on software code and data – has increased market rents,...

As it becomes cheaper to copy and share digital content, vendors are turning to technical protections such as encryption. We argue that if protection is nevertheless imperfect, this transition will generally lower the prices of content relative to perfect legal enforcement. However, the effect...

Globally, an estimated 734 million jobs will be required between 2010 and 2030 to accommodate recent and ongoing demographic shifts, account for plausible changes in labour force participation rates, and achieve target unemployment rates of at or below 4 percent for adults and at or below 8...

We study why acquisitions of entrant firms by an incumbent can deter innovation and entry in the digital platform industry, where there are strong network externalities and some customers face switching costs. A high probability of an acquisition induces some potential early adopters to wait for...

In academic and policy circles, there has been considerable interest in the impact of “big data” on firm performance. We examine the question of how the amount of data impacts the accuracy of Machine Learned models of weekly retail product forecasts using a proprietary data set obtained from...

Policymakers can take actions to prevent local conflict before it begins, if such violence can be accurately predicted. We examine the two countries with the richest available sub-national data: Colombia and Indonesia. We assemble two decades of fine-grained violence data by type, alongside...

Modern investors face a high-dimensional prediction problem: thousands of observable variables are potentially relevant for forecasting. We reassess the conventional wisdom on market efficiency in light of this fact. In our model economy, which resembles a typical machine learning setting, N...

Text data is ultra-high dimensional, which makes machine learning techniques indispensable for textual analysis. Text is often selected—journalists, speechwriters, and others craft messages to target their audiences' limited attention. We develop an economically motivated high dimensional...