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...

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...

This paper demonstrates that it is possible to construct accurate pictures of firm revenue, growth, geographic dispersion, and customer base characteristics using an increasingly accessible class of consumer financial transaction data. We develop two new measures which characterize firms'...

This paper provides a comprehensive, global database of deposit insurance arrangements as of 2013. We extend our earlier dataset by including recent adopters of deposit insurance and information on the use of government guarantees on banks' assets and liabilities, including during the recent...

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...

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...

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...

Thanks to big data, artificial intelligence (AI) has spurred exciting innovations. In the meantime, AI and big data are reshaping the risk in consumer privacy and data security. In this essay, I first define the nature of the problem and then present a few facts about the ongoing risk. The bulk...

In this paper we present and describe a large quarterly frequency, macroeconomic database. The data provided are closely modeled to that used in Stock and Watson (2012a). As in our previous work on FRED-MD, our goal is simply to provide a publicly available source of macroeconomic “big data”...