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Distributional Diversity in the National Accounts

Paper Session

Sunday, Jan. 6, 2019 10:15 AM - 12:15 PM

Atlanta Marriott Marquis, International 9
Hosted By: American Economic Association
  • Chair: Heather Boushey, Washington Center for Equitable Growth

Improving the Measure of the Distribution of Personal Income

Marina Gindelsky
U.S. Bureau of Economic Analysis
Dennis Fixler
U.S. Bureau of Economic Analysis
David Johnson
University of Michigan


Developing a national account based measure of the distribution of income from the commonly used Census based concept of money income has been the subject of earlier research—see Fixler and Johnson (2014) and Fixler, et al. (2015) for example. A limitation of the earlier work is that the extrapolation from the survey data to the national account aggregate was based on “blow-up “factors that were constant across households. In this paper, we will explore using micro tax data to create income quintile specific blow up factors. More specifically, CPS data is linked to IRS data by household in order to address misreporting and survey bias for several income categories. Next, blow-up factors are constructed by income decile in order to create a distribution of national accounts. Preliminary results indicate significantly different factors by decile and by income category. It is hoped that this additional feature will help bridge the gap

Unequal distributions: EG DNA versus DINA approach

Jorrit Zwijnenburg


Distributional results in line with national accounts totals differ from those obtained from micro statistics due to differences in underlying concepts and due to the fact that micro data usually do not perfectly match national accounts totals. Furthermore, different underlying concepts and methodology to combine micro and the macro results may also lead to different results across projects aiming for distributional data consistent with macroeconomic aggregates. To have a better understanding of possible differences, it is important to have more insight in the various aspects of compiling distributional results and how different decisions and assumptions may affect the results. This paper provides an overview of the concepts and methodology used in the OECD-Eurostat Expert Group on Disparities in a National Accounts framework (EG DNA) project to compile distributional results in line with national accounts totals. It explains how this may lead to different results from micro statistics and it also explains how different assumptions and decisions in this compilation process may affect the results. The latter is done by looking at the main differences between the EG DNA approach and the Distributional National Accounts (DINA) approach. The paper will assist in better understanding differences between distributional results and will provide input for a further discussion on pros and cons of applying different concepts and assumptions in the compilation of distributional results.

Top 1 Percent Income Shares: Comparing Estimates Using Tax Data

Gerald Auten
U.S. Office of Tax Analysis
David Splinter
U.S. Joint Committee on Taxation


Many studies have used tax data to measure the U.S. income distribution, but results vary widely. For example, in 2014 the top 1% share of pre-tax income is 21.5% in Piketty and Saez (2003 and updates), 16.7% in Congressional Budget Office (2018), and 13.1% in our analysis. What accounts for such large differences? We provide a step-by-step analysis of how methodological differences affect the results and address issues raised in Piketty, Saez, and Zucman (2018, 2019). Important differences include accounting for declining marriage rates, including social insurance and employer benefits, accounting for tax reforms, and including income missing from tax returns.

Distributional National Accounts: Lessons from Country Studies

Gabriel Zucman
University of California-Berkeley


This paper synthesizes the lessons learned from constructing distributional national accounts — that is, annual estimates of the distribution of income and wealth consistent with macroeconomic national accounts — in a number of countries, including the United States, France, China, India, and Russia. We describe the methods used in this project, compare our concepts and results to the literature, and discuss areas where further progress is warranted.
Claudia Sahm
Federal Reserve Board
Katharine G. Abraham
University of Maryland
JEL Classifications
  • E6 - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook
  • D3 - Distribution