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CTC and ACTC Participation Results and IRS-Census Match Methodology, Tax Year 2020

December 2024

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  EITC Participation Results and IRS-Census Match Methodology, Tax Year 2021
  

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  CES-23-24

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  December 2014

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  carra-2014-15

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  The EITC and Intergenerational Mobility
  

  November 2020

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  CES-20-35

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  Investigating the Use of Administrative Records in the Consumer Expenditure Survey
  

  March 2018

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  carra-2018-01

  In this paper, we investigate the potential of applying administrative records income data to the Consumer Expenditure (CE) survey to inform measurement error properties of CE estimates, supplement respondent-collected data, and estimate the representativeness of the CE survey by income level. We match individual responses to Consumer Expenditure Quarterly Interview Survey data collected from July 2013 through December 2014 to IRS administrative data in order to analyze CE questions on wages, social security payroll deductions, self-employment income receipt and retirement income. We find that while wage amounts are largely in alignment between the CE and administrative records in the middle of the wage distribution, there is evidence that wages are over-reported to the CE at the bottom of the wage distribution and under-reported at the top of the wage distribution. We find mixed evidence for alignment between the CE and administrative records on questions covering payroll deductions and self-employment income receipt, but find substantial divergence between CE responses and administrative records when examining retirement income. In addition to the analysis using person-based linkages, we also match responding and non-responding CE sample units to the universe of IRS 1040 tax returns by address to examine non-response bias. We find that non-responding households are substantially richer than responding households, and that very high income households are less likely to respond to the CE.
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  Mobility, Opportunity, and Volatility Statistics (MOVS): Infrastructure Files and Public Use Data
  

  April 2024

  Authors: Maggie R. Jones, Sonya R. Porter, John Voorheis, Nikolas Pharris-Ciurej, Adam Bee, Jonathan Rothbaum, Kendall Houghton, Amanda Eng

  Working Paper Number:

  CES-24-23

  Federal statistical agencies and policymakers have identified a need for integrated systems of household and personal income statistics. This interest marks a recognition that aggregated measures of income, such as GDP or average income growth, tell an incomplete story that may conceal large gaps in well-being between different types of individuals and families. Until recently, longitudinal income data that are rich enough to calculate detailed income statistics and include demographic characteristics, such as race and ethnicity, have not been available. The Mobility, Opportunity, and Volatility Statistics project (MOVS) fills this gap in comprehensive income statistics. Using linked demographic and tax records on the population of U.S. working-age adults, the MOVS project defines households and calculates household income, applying an equivalence scale to create a personal income concept, and then traces the progress of individuals' incomes over time. We then output a set of intermediate statistics by race-ethnicity group, sex, year, base-year state of residence, and base-year income decile. We select the intermediate statistics most useful in developing more complex intragenerational income mobility measures, such as transition matrices, income growth curves, and variance-based volatility statistics. We provide these intermediate statistics as part of a publicly released data tool with downloadable flat files and accompanying documentation. This paper describes the data build process and the output files, including a brief analysis highlighting the structure and content of our main statistics.
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