Economic data engineering deliberately designs novel forms of data to solve fundamental identification problems associated with economic models of choice. I outline three diverse applications: to the economics of information; to life-cycle employment, earnings, and spending; and to public policy...

Using the Census Bureau's internal March Current Population Surveys (CPS) file, we construct and make available variances and cell means for all topcoded income values in the public-use version of these data. We then provide a procedure that allows researchers with access only to the public-use...

How should an investor value financial data? The answer is complicated because it depends on the characteristics of all investors. We develop a sufficient statistics approach that uses equilibrium asset return moments to summarize all relevant information about others' characteristics. It can...

We propose an approach to measuring the state of the economy via textual analysis of business news. From the full text content of 800,000 Wall Street Journal articles for 1984{2017, we estimate a topic model that summarizes business news as easily interpretable topical themes and quantifies the...

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"...

The use of historical data has become a standard tool in economics, serving three main purposes: to examine the influence of the past on current economic outcomes; to use unique natural experiments to test modern economic theories; and to use modern economic theories to refine our understanding...

The rise of information technology and big data analytics has given rise to "the new economy." But are its economics new? This article constructs a growth model where firms accumulate data, instead of capital. We incorporate three key features of data: 1) Data is a by-product of economic...

The market price-dividend ratio is highly correlated with several macroeconomic variables, particularly inflation and labor market variables, but not with aggregate consumption and GDP. We incorporate this observation in an exchange economy with learning about the economic regime from...

This paper measures option-implied skewness for individual firms and the overall stock market between 1980 and 2021, giving real-time measures of conditional micro and macro skewness. There are three key results: 1. Micro skewness is significantly procyclical, while macro skewness is acyclical;...

We introduce FDIF, a measure of Fed communication surprise based on the text of FOMC statements. FDIF measures the difference between text-implied and actual values of key market variables. Positive FDIF of countercyclical variables (e.g., credit spreads) is associated with negative...