This page provides access to papers and presentations prepared by BEA staff. Abstracts are presented in HTML format; complete papers are in PDF format with selected tables in XLS format. The views expressed in these papers are solely those of the authors and not necessarily those of the U.S. Bureau of Economic Analysis or the U.S. Department of Commerce.

Household Consumption Expenditures for Medical Care: An Alternate Presentation


Ana M. Aizcorbe, Eli Liebman, David M. Cutler, Allison B. Rosen
Last Updated
JEL Code(s)None Assigned

Introducing Demographic Labor Market Data into the U.S. National Accounts

The U.S. gross domestic product and its foundational National Income and Product Accounts contain some of the most widely used and followed economic statistics in the world yet contain limited information on the labor market and almost no information on demographic groups. We build a new dataset… Read more

Jon D. Samuels
JEL Code(s)E01

Introducing Consumer Durable Digital Services into the BEA Digital Economy Satellite Account

Measuring the digital economy is a high priority for analysts of economic growth. We augment the Bureau of Economic Analysis’s Digital Economy Satellite Account to include digital services provided by high-tech consumer durables. We find that including the service flow from these goods raises… Read more

Benjamin R. Bridgman, Tina Highfill, Jon D. Samuels
JEL Code(s)D13, E01

Capitalizing Data: Case Studies of Tax Forms and Individual Credit Reports

Early papers on capitalizing data focused on complex digital data that are stored on supercomputers and managed by highly skilled computer scientists (Statistics Canada 2019) (Eurostat 2020) (Coyle 2022) (Calderon and Rassier 2022) (Mitchell et al. 2022). This paper studies two very different… Read more

Rachel Soloveichik
JEL Code(s)D14, E01, G14

For What It’s Worth: Measuring Land Value in the Era of Big Data and Machine Learning

This paper develops a new method for valuing land, a key asset on a nation’s balance sheet. The method first employs an unsupervised machine learning method, kmeans clustering, to discretize unobserved heterogeneity, which we then combine with a supervised learning algorithm, gradient boosted… Read more

Scott Wentland, Gary Cornwall, Jeremy G. Moulton
JEL Code(s)E01

Consumption Zones

Local area data are important to many economic questions, but most local area data are reported using political units, such as counties, which often do not match economic units, such as product markets. Commuting zones (CZs) group counties into local labor markets. However, CZs are not the most… Read more

Andrea Batch, Benjamin R. Bridgman, Abe C. Dunn, Mahsa Gholizadeh
JEL Code(s)R12

Proof of Concept for a U.S. Air Emissions Physical Flows Account

Measuring the physical flows of resources and waste between the economy and environment is a central component of environmental-economic accounting as outlined in the System of Environmental-Economic Accounting (SEEA), the United Nations standard for environmental accounting.

This paper… Read more

Matthew Chambers
JEL Code(s)E01, E20, I31, L92, L93, Q5, Q53, Q54

Developing a National Measure of the Economic Contributions of the Bioeconomy

In recent years, interest in biotechnology, biomanufacturing, and the bioeconomy has grown steadily. Researchers in the United States and other countries have sought to measure the bioeconomy and have developed a variety of definitions and approaches for doing so. Executive Order 14081, issued… Read more

Tina Highfill, Matthew Chambers
JEL Code(s)None Assigned

The Geography of Consumption and Local Economic Shocks: The Case of the Great Recession

We estimate across-county spending flows between firms and consumers for every county in the United States, providing a new consumption link that has not been studied previously. We highlight the importance of this link by estimating the effect of changes in local housing wealth on consumption… Read more

Abe C. Dunn, Mahsa Gholizadeh
JEL Code(s)None Assigned

Valuing the U.S. Data Economy Using Machine Learning and Online Job Postings

With the recent proliferation of data collection and uses in the digital economy, the understanding and statistical treatment of data stocks and flows is of interest among compilers and users of national economic accounts. In this paper, we measure the value of own-account data stocks and flows… Read more

J Bayoán Santiago Calderón, Dylan Rassier
JEL Code(s)E22, O3, O51