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New Approaches to Measuring Comprehensive and Fully Integrated Household Financial Statements at the Micro and Macro Levels

Paper Session

Sunday, Jan. 3, 2021 10:00 AM - 12:00 PM (EST)

Hosted By: American Economic Association & Committee on Economic Statistics
  • Chair: John Sabelhaus, Non-affiliated

Sharing is Caring: Inequality, Transfers and Growth in the National Accounts

Marina Gindelsky
,
U.S. Bureau of Economic Analysis

Abstract

Using the updated Distribution of Personal Income by the Bureau of Economic Analysis for U.S. households (2007-2018) with a focus on the bottom of the distribution, I show that transfers significantly lower the level of pre-tax and post-tax inequality in a national accounts framework. However, 2/3 of the reduction in the Gini derives from Social Security and Medicare. Though mostly available to elderly households, together these programs quadruple the share of the bottom income quintile and reduce the Gini by 16%. Conversely, the inclusion of all means-tested programs (such as Medicaid and refundable tax credits) reduces the Gini by half as much, raises the share of the bottom quintile by only 1.8 percentage points, and does not increase the income share of the middle quintiles. Consistent with an aging population, transfers have increased as a share of personal income; yet, inequality continues to rise.

The Distributional Financial Accounts of the United States

Michael Batty
,
Federal Reserve Board
Jesse Bricker
,
Federal Reserve Board
Joseph Briggs
,
Non-affiliated
Sarah Friedman
,
Federal Reserve Board
Danielle Nemschoff
,
Federal Reserve Board

Abstract

This paper describes the construction of the Distributional Financial Accounts
(DFA), a dataset containing quarterly estimates of the distribution of U.S. household
wealth since 1989. The DFA build on two existing Federal Reserve Board statistical
products | quarterly aggregate measures of household wealth from the Financial Ac-
counts of the United States, and triennial wealth distribution measures from the Survey
of Consumer Finances | to incorporate distributional information into a national ac-
counting framework. The DFA complement other sources by generating distributional
statistics that are consistent with macro aggregates, by providing quarterly data on a
timely basis, and by constructing wealth distributions across demographic characteris-
tics. We encourage policymakers, researchers, and other interested parties to use the
DFA to better understand issues related to the distribution of U.S. household wealth.

Real Time Measurement of Household Electronic Financial Transactions in a Population Representative Panel

Marco Angrisani
,
University of Southern California
Arie Kapteyn
,
University of Southern California
Swaroop Samek
,
University of Southern California

Abstract

From September 2016 to September 2018, we piloted the collection of financial transaction and account balance data in the Understanding America Study (UAS), an Internet panel representative of the U.S. adult population. Unlike previous studies relying on electronic transaction information from financial aggregators, our data allow us to explore heterogeneity in consumer behavior as driven by demographics, health, cognitive ability, and financial literacy, among others. In this paper, we describe the results of this pilot project, documenting selectivity issues and the major barriers associated with participation in the study. We carry out illustrative exercises to highlight how the combination of surveys and electronic financial records can open new research avenues to better understand individual financial decision making and well-being.

Starting from Scratch: A Multi-Mode Approach to Collecting Micro Data for Fully Integrated United States Household Financial Statements

Scott Schuh
,
West Virginia University
Robert Townsend
,
Massachusetts Institute of Technology

Abstract

This paper proposes a plan to obtain fully integrated household financial statements (IHFS) by “starting from scratch” at the individual household level with a new multi-modal data collection program. We simply ask and answer two questions: 1) what precise data are needed to calculate IHFS?; and 2) how can we best obtain the necessary data? Addressing these questions is the centerpiece of our long-run research program.
Discussant(s)
Karen Dynan
,
Harvard University
Eric Zwick
,
University of Chicago
Michaela Pagel
,
Columbia University
Andrew Caplin
,
New York University
JEL Classifications
  • G5 - Household Finance
  • C8 - Data Collection and Data Estimation Methodology; Computer Programs