Developing State Personal Income Distribution Statistics

Dirk van Duym

Christian Awuku-Budu

FCSM Conference, November 2

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Introduction

Goal: create a distributional account for State Personal Income

Allows for analysis of inequality by state and over time

Benchmarked to BEA SPI aggregates

Contributes to BEA’s Beyond GDP initiative

Builds off BEA work distributing national personal income (Fixler et al, 2020), adapting to state data constraints

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Other Estimates of State Inequality

Census provides official state median household money income and Gini coefficients by state

Directly from American Community Survey and/or Current Population Survey

Not benchmarked to NIPA or State Personal Income, or tax data

Economic Policy Institute (think tank) has top 1% state and county estimates up to 2015, based on IRS SOI data and ACS

Forthcoming research from Census using linked survey and tax microdata

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Source Data

Base datasets

State Personal Income accounts

CPS Annual Social and Economic Supplement (ASEC) microdata

Other data sources

IRS Statistics of Income

Medical Expenditure Panel Survey

Survey of Consumer Finances

American Community Survey

Center for Medicare and Medicaid Services

Congressional Budget Office

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Base Dataset 1: SPI Accounts

We start by selecting 75 detailed annual state personal income components, to be allocated to households

These population aggregates are BEA’s bread & butter: measured using a variety of source data, often in partnerships with IRS, BLS

Components measured on place-of-work basis are transformed to place-of-residence basis, to be consistent with survey data used in next steps

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Base Dataset 2: CPS ASEC microdata

Base dataset for allocation to state households is pooled CPS ASEC microdata, from three previous years

CPS is only source that has enough variety of income types

Following Census guidance on using multiple years for state estimates

Similar structure to ACS 3 or 5-year files used for smaller geographies

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CPS Adjustments

CPS is adjusted for under/misreporting, to improve estimates of the top of the distribution

Using state IRS Statistics of Income data on wages, interest, dividends, business income (sole proprietor & partnership)

Other data sources used to supplement, or “fill out” CPS

CPS alone is not suitable to distribute some income types to households: medical income components, imputed interest/rent, etc.

Bring in: CMS, MEPS, SCF, BEA’s recent housing work based on ACS, others

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Allocating, and Generating Estimates

Each detailed, place-of-residence SPI component is allocated to state households using adjusted CPS

We now have microdata that adds up to State Personal Income

Household size-adjusted income is used to define the ranking of households

Inequality measures can now be produced

Median, Gini, quintile shares of State PI

Quintile shares of sub-aggregates, consistent with existing BEA Regional publication tables

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Results

New results for 2009-2018

Many statistics to look at, just a selection today (more in paper)

Focus on Gini, median income, top quintile borders

Quintiles borders are defined at the state level

Comparison to Census state money income estimates

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Gini Coefficients, 2018

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Our estimates vs. Census state estimates from ACS

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Note: results not equivalized for household size, for comparability to Census

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Our estimates vs. Census state estimates from ACS

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Note: results not equivalized for household size, for comparability to Census

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80th Percentile of Equivalized SPI, 2018

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20th Percentile of Equivalized SPI, 2018

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20th Percentile of RPP-Adjusted Equiv. SPI, 2018

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Mean vs. Median Growth

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Future Research

State disposable personal income

Involves distributing taxes

Allows for analysis post-tax and post-transfer

Moving towards official BEA statistics

Your feedback needed!

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