The state-level data for our analysis included information on states' economic conditions. We merged this state-level information by month or year (depending on data availability) to the SIPP data file using monthly (annual) information on the state in which each sample member lived.(7) We used this information to explore the relationship between state characteristics and the dynamics of the low-wage labor market in the multivariate analysis.
We used variables from the following categories of state economic indicator variables that are intended to proxy for the labor market situation faced by SIPP sample members:
- Unemployment rate and the change in the unemployment rate during the follow-up period (Source: U.S. Department of Labor's Bureau of Labor Statistics [BLS])
- Employment growth per capita (Source: BLS)
- Poverty rate (source: Statistical Abstract of the United States)
- Household median income (source: Statistical Abstract of the United States)
- 20th percentile of monthly wages of employed people age 18 and older
- Per-capita income (source: Bureau of Economic Analysis)
- Real minimum wage (source: Statistical Abstract of the United States)
- Mean wage in the manufacturing industry
Rural population share
Although we initially included all these measures as explanatory variables in our multivariate models, we ultimately narrowed the list because of the high correlation among many of the state-level measures. This high degree of multicollinearity increased the standard errors of all parameter estimates and made it difficult to isolate the separate effects of each of the state-level measures. The final list of explanatory variables included (1) the unemployment rate measures, (2) the poverty rate measure, (3) the 20th percentile of monthly wages, and (4) the rural population share.