Determinants of AFDC Caseload Growth. 2. Labor Market Variables

07/01/1997

We assess the explanatory power of several labor market variables in our models:

1. the unemployment rate;

2. unemployed persons, total and per capita;

3. employed persons, total and per capita;

4. persons employed in trade industries, total and per capita;

5. persons employed in manufacturing industries, total and per capita;

6. average weekly wage in retail trade industries; and,

7. average weekly wage in manufacturing industries.

We obtained monthly, state-level unemployment rate data from BLS for the period from January 1976 through December 1994. We converted this series to a quarterly series by averaging the monthly values within a given quarter. The specification used in all models is age-adjusted: the log of the actual value for each quarter divided by an expected value for the quarter.

The expected value is constructed at an annual level first, using national unemployment rates by age and sex for 1990 and state population data by age and sex for each year, then interpolated to get quarterly figures. As discussed in Chapter Two, substantial evidence already exists that increases in the unemployment rate have their full impact on participation only after several quarters have passed, and therefore we experimented with various lag specifications for this variable.

We similarly obtained monthly data series for total employment, employment in trade, and employment in manufacturing from the BLS for the period from January 1976 through December 1994. We converted these monthly series to quarterly series by averaging the monthly values within a given quarter. The total unemployment series was calculated from the total employment and unemployment rate series.(7) The per capita series were obtained simply by dividing by the state population and then multiplying by 1000. All variables were entered in log form. As with the unemployment rate variable, we experimented with various lag specifications for these variables.

Annual average-weekly wage data at the state level for both the retail and manufacturing industries were obtained from BLS for 1978 through 1994. The quarterly values used in the model are interpolated from the annual series and then divided by the appropriate regional CPI-U. The variable as it appears in the models is equal to the log of the real wage.

Following previous researchers (Chapter Two), we initially used the retail wage variable for the Basic model and the manufacturing wage variable for the UP model. As with the unemployment rate variable, we experimented with various lag specifications of the wage variables.