Methods - Data Sources

We evaluate the economic effects of the COVID-19 pandemic on consumer spending using daily card transaction data. Overall, we find large effects of this pandemic on sectors such as accommodations and restaurants, which by the second week of March, show declines of around 80 percent and 70 percent, respectively. However, these declines were partly offset by the large 100 percent immediate increase in food and beverage store sales. For select goods and services in our data, we find an aggregate decline in spending of around 13.7 percent for March, and we estimate an aggregate “pandemic effect”—the effect of the pandemic on consumer spending after mitigation measures have had time to take hold—of around –27.8 percent.

This paper explores potential ways to develop experimental estimates of the value of U.S. imports of illegal drugs. It builds on the initial exploration of this topic by the Bureau of Economic Analysis (BEA) in Soloveichik (2019), which presents experimental estimates of U.S. domestic consumption of illegal drugs and of import of illegal drugs into the United States. In this paper, I extend Soloveichik’s research by exploring the feasibility of developing estimates of imports of methamphetamines and marijuana using seizure data, and I evaluate the extent to which source data allow us to estimate heroin and cocaine imports by geography. International guidelines for national economic accounts (the System of National Accounts 2008, or SNA) and international economic accounts (the Balance of Payments and International Investment Position Manual, sixth edition) explicitly recommend that some illegal market activity should be included in measured output. Soloveichik suggests that illegal drugs comprise the largest share of imports of this activity for the United States and would have added $111 billion to U.S. GDP in 2017.

Investment funds, which include mutual funds, other regulated investment companies, and real estate investment trusts, play an increasingly important role in the U.S. economy, with financial assets of about $23 trillion in 2017. Currently, in the U.S. National Income and Product Accounts (NIPAs), statistics on investment funds are included within larger aggregate statistics but not published separately. This paper presents separate statistics on investment funds from the NIPAs, using the framework of the integrated macroeconomic accounts, or sectoral accounts. As expected, investment funds account for a significant share of total interest and dividend payments. One feature of BEA’s accounting treatment of investment funds is that they are persistent net borrowers. This paper also discusses possible alternative treatments of investment funds, currently used by the Federal Reserve Board’s Financial Accounts and the national accounts of some other countries, in which net saving and net lending are closer to zero.

The internationally agreed guidelines for national economic accounts, System of National Accounts 2008 (hereafter referred to as SNA 2008) (United Nations Statistics Division 2008), explicitly recommend that illegal market activity should be included in the measured economy. This recommendation has not yet been implemented by the U.S. Bureau of Economic Analysis (BEA) because of challenges inherent in identifying suitable source data and differences in conceptual traditions. This paper explores how tracking illegal activity in the U.S. national economic accounts might impact nominal Gross Domestic Product (GDP), real GDP, productivity, and other economic statistics. Nominal GDP rises in 2017 by more than 1 percent when illegal activity is tracked in the U.S. National Income and Product Accounts (NIPAs). By category, illegal drugs add $108 billion to measured nominal GDP in 2017, illegal prostitution adds $10 billion, illegal gambling adds $4 billion, and theft from businesses adds $109 billion. Real GDP and productivity growth also change. Real illegal output grew faster than overall GDP during the 1970s and post–2008. As a result, tracking illegal activity ameliorates both the 1970s economic slowdown and the post–2008 economic slowdown considerably.

This paper studied the feasibility of reconciling BEA state personal income (SPI) and IRS adjusted gross income (AGI) at the state level. After reviewing data sources from BEA, IRS, and other agencies, it was concluded that it is feasible to prepare accurate reconciliations of state level wages and salaries. Further work is needed to determine the feasibility and value of reconciling BEA SPI and IRS AGI for other components of personal income—such as proprietors’ income, personal current transfer receipts, and dividends, interest, and rent. A limitation in reconciling these other income components is that BEA relies heavily upon IRS data to make its estimates. Thus, only limited insights might be obtained from the reconciliation.

Tables in this paper (XLS)

This paper provides an overview of the source data and the estimating methods used by the Bureau of Economic Analysis (BEA) to prepare the quarterly estimates of the U.S. gross domestic product (GDP). When BEA prepares its first estimates of quarterly GDP, a wide mix of source data are used. In some cases, these data are not as complete or as detailed as desired. Over time, more complete and detailed data are received that are more consistent with the concepts and framework of the national accounts. Consequently, BEA has a regular schedule for revising its estimates to reflect the most accurate source data and to incorporate the most appropriate estimating methods. This paper describes the various source data and estimating methods used to prepare the current- and constant-price estimates of quarterly GDP; it describes how these data and methods change over the course of a GDP revision cycle.

This paper is part of a series that provides the details behind the Bureau of Economic Analysis's (BEA) satellite account on research and development (R&D) activity. It describes the data and experimental methodology used to create the GDP-by-Industry component of the satellite account for thirteen R&D-intensive industries and an aggregation of all other for-profit industries.

The Bureau of Economic Analysis (BEA), under contract with the Internal Revenue Service (IRS) Office of Research, undertook an update of BEA’s state-level wage reconciliation for 2000 between BEA wages and salaries and IRS wages and salaries in Adjusted Gross Income. The initial reconciliation for the year 2000 was documented in the BEA Working Paper, The Feasibility of Producing Personal Income to Adjusted Gross Income (PI-AGI) Reconciliations by State. This study updates state estimates of the reconciliation of BEA and IRS wages and salaries for 2001 and 2002.

Results (XLS)