Data Source and Methodology for Estimates of CalEITC Beneficiaries, Costs, and Demographics

The following are the methodology notes for the California Budget & Policy Center post, Proposed Legislation Would Extend CalEITC to Include Young Adults and Seniors as Well as Immigrant Workers Filing With ITINs.

These estimates are based on US Census Bureau, American Community Survey (ACS) microdata (from the Integrated Public Use Microdata Series produced by the University of Minnesota) for California for 2015. The estimates were developed by first constructing tax units and calculating federal income taxes in the ACS data using an income tax simulation program developed for the California Poverty Measure, a collaborative project of the Stanford Center on Poverty & Inequality and Public Policy Institute of California. This income tax simulation program uses self-reported information about family relationships and income in the ACS, which is assembled and then processed through the Taxsim tax calculator developed by the National Bureau of Economic Research. The tax units and federal adjusted gross income produced through the tax simulation program are then combined with additional ACS data related to wage earnings and work participation to identify individuals likely eligible to file tax returns to claim the CalEITC and to calculate their estimated CalEITC credit amounts for the baseline CalEITC data. Tax unit data are also used to identify filers who would become eligible for the CalEITC under proposals to extend credit eligibility to new groups of filers and to calculate the credit amounts for which they would become eligible. The family members of these tax filers are then also identified, in order to analyze demographic characteristics of all people likely to benefit from the CalEITC.

These estimates have certain limitations. The ACS is a useful data source for examining CalEITC eligibility because it has a large sample that is representative of the full population of California (including individuals who do not file income taxes), and it includes relatively detailed income and family and demographic information, including information not available in administrative tax data. However, some information that is relevant to CalEITC eligibility is not directly reported in ACS data. For one, tax units and immigrant legal status of tax filers are not reported in ACS data, so these are imputed in the California Poverty Measure income tax data. The estimation and imputation strategies used in this analysis are necessary to deal with information that is not directly reported in the ACS and to examine characteristics of individuals who are likely eligible for the CalEITC though they may not file taxes to claim the credit. As a result, however, these estimates have a level of uncertainty and should be interpreted accordingly.

For further information about these analytical methods, contact Sara Kimberlin, Senior Policy Analyst, California Budget & Policy Center, at