Name File Type Size Last Modified
Data dictionary.xlsx application/vnd.openxmlformats-officedocument.spreadsheetml.sheet 19.1 KB 09/25/2020 01:20:PM
acs_cells.csv text/csv 10.4 MB 09/04/2020 10:45:AM
at_risk_by_cell.csv text/csv 9.1 MB 09/04/2020 10:32:AM
cps_data.csv text/csv 85.9 MB 09/25/2020 01:18:PM
ssa_data.csv text/csv 23.1 KB 09/04/2020 10:59:AM

Project Citation: 

Ben-Shalom, Yonatan. Who is at risk of workforce exit because of disability? United States, 2003–2016. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-05-13. https://doi.org/10.3886/E170303V1

Project Description

Summary:  View help for Summary The deposited data include the analysis files we used for a study entitled “Who is at risk of workforce exit because of disability? State Differences in 2003–2016”. We constructed these data from secondary sources, as detailed below. In the study, we used these data and Bayesian multilevel modeling techniques to produce yearly estimates of trends in the risk of workforce exit because of a disability for states and demographic subgroups. We identified Current Population Survey respondents as being newly at risk of exiting the workforce because of a disability if they reported being employed in one month and out of the labor force because of a disability in the next month, and we refer to their share of the working-age population as the at-risk rate.
Funding Sources:  View help for Funding Sources NIDILRR (9ORTGE0001)

Scope of Project

Subject Terms:  View help for Subject Terms workers; labor force; employment; disabilities; government programs
Geographic Coverage:  View help for Geographic Coverage United States
Time Period(s):  View help for Time Period(s) 2003 – 2006
Universe:  View help for Universe U.S. civilian respondents ages 18 to 64 (CPS and ACS data), 50 states and the District of Columbia (SSA data)
Data Type(s):  View help for Data Type(s) aggregate data; survey data
Collection Notes:  View help for Collection Notes The study data include analysis variables constructed from secondary data sources:
  1. Current Population Survey (CPS). For each year, we restricted the sample to civilian respondents ages 18 to 64 who completed their first or fifth sampled month in that year so that we include each respondent only once in each calendar year. We used the IPUMS-CPS version of these data, which includes a unique identifier that can serve to link people across monthly CPS samples. Link to source: https://cps.ipums.org/cps/ 
  2. American Community Survey (ACS). We used the IPUMS-USA version of these data. Link to source: https://usa.ipums.org/usa/
  3. Social Security Administration (SSA) data on applications and awards. We used a publicly available data set containing historical information about SSA’s processing of initial claims for disability benefits to obtain national and state data for such claims and for initial allowances for those claims. The state-level SSA data provide the annual number of adult initial claims received and favorable disability findings made for each state. We treat the former as the combined number of Social Security Disability Insurance (SSDI) and Supplemental Security Income (SSDI) applications and the latter as combined SSDI and SSI awards. These numbers do not perfectly measure SSDI and SSI applications and awards. First, some disability claims are not referred to a state agency for a disability determination, and all disability claims received by a state agency do not result in a disability determination. Our measure of applications excludes the former and includes the latter. Second, some state agencies’ favorable disability determinations do not ultimately result in a benefit award, but our measure of awards includes them. The same data also provide annual state-level estimates of the population ages 18 to 64, sourced from the U.S. Census Bureau. Link to source: https://www.ssa.gov/disability/data/ssa-sa-fywl.htm
The individual-level data (cps_data.csv) include CPS civilian respondents ages 18 to 64 who completed their first or fifth sampled month in a given year. The cell-level data (at_risk_by_cell.csv and acs_cells.csv) include information for cells defined by the cross-classification of several categorical characteristics: year (2003 to 2016), state (50 states and the District of Columbia), age category (18 to 19 and five-year age groups beginning with 20 to 25 and ending with 60 to 64), gender (male, female), race (Black, non-Black), and ethnicity (Hispanic, non-Hispanic). The SSA data (SSA_data.csv) contain state-level counts of SSDI/SSI applications and awards as well as state-level estimates of the population ages 18 to 64, by year. 

Methodology

Sampling:  View help for Sampling Most of the study data come from the CPS, which is a monthly survey administered by the U.S. Census Bureau using a probability selected sample of about 60,000 occupied households. It is designed primarily to produce national and state estimates of labor force characteristics of the civilian non-institutional population ages 16 and older. More information is available at https://www.census.gov/programs-surveys/cps/technical-documentation/methodology/sampling.html.
Collection Mode(s):  View help for Collection Mode(s) mixed mode
Unit(s) of Observation:  View help for Unit(s) of Observation individual, group
Geographic Unit:  View help for Geographic Unit State

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