Determinants of AFDC Caseload Growth. 2. Labor Market and Economic Factors

07/01/1997

Nearly all models of AFDC participation include measures of labor market conditions as explanatory variables (Exhibit 2.3). The most commonly used measure is the unemployment rate. Many models include both current and lagged values of the unemployment rate in their specifications. Other variables intended to capture labor market conditions that were used instead of the unemployment rate include: the number of unemployment insurance claims filed, employment rates of females or in female-dominated industries, and employment gap measures (the difference between current and full employment).

In addition to the unemployment rate, models frequently include a measure of earnings. These range from overall average earnings for females within a specified age/education group (males, in UP models), to average wages in specific industries. Wage data for the retail trade industry or for "predominantly female" industries were used in some Basic models, while manufacturing wages were used in some UP models as well as in one Basic model (Cromwell et al., 1986). Many researchers have found that both the unemployment rate, or some other employment measure, and an earnings variable have statistically significant coefficients -- experience that suggests there is room for both types of measures in our models.

Availability of accurate data at the state level and by quarter is a key issue. The unemployment rate is available at this level and is generally considered to be of high quality. It is our understanding that the Bureau of Labor Statistics (BLS) collects state-level earnings data by industry on a monthly basis, but does not tabulate it at the state level other than annually. The state-level monthly or quarterly earnings data used in some models evidently come from special tabulations of BLS data. We are investigating the feasibility of having BLS prepare special tabulations for this project.

Another issue related to the use of an earnings variable is whether or not earnings should be adjusted to reflect taxes. Only one model has used an after-tax measure of earnings, and in this case, it is used in combination with the AFDC benefit to construct a variable representing the net gain to participating in the AFDC program.(19) Federal tax adjustments, including potentially important Earned Income Tax Credits, can be made fairly simply based on a set of standard assumption about a family. State adjustments are probably not feasible because they vary by state.

A final issue concerns the inclusion of lagged values. CBO (1993) uses the longest lag specification on a labor market variable of any study reviewed -- six quarters in the UP equation only (three quarters in the Basic equation). No other specification uses a lag length of more than one year. Use of pooled data for states makes it feasible to explore longer lag lengths in comparison to what might be feasible using time-series for a single geographic area. This could be important because national time-series data suggest that economic recovery from a recession is followed by very slow declines in program participation. The pooled studies to date, however, have not considered longer lag lengths.

Exhibit 2.3

Economic Variables Used in Previous Studies of AFDC Caseload Growth

Variable Type Description Model(s)
Unemployment Annual, state State unemployment rate Moffitt (1986)
  Annual, state Log of average unemployment rate in state Shroder(1995), recipiency model
  Quarterly, national Current and lagged unemployment rates Grossman (1985)
  Quarterly, state Three month average; seasonally adjusted and unadjusted rates Barnow (1988)
  Quarterly, state Seasonally adjusted unemployment rate Florida
  Quarterly, state The number of unemployed persons, three month average Barnow (1988)
  Quarterly, state Average number of weekly unemployment insurance claims measured in thousands of claims (current and lagged one and two quarters) Garasky (1990)
  Monthly, state New unemployment claims smoothed two months Maryland, AFDC-UP model
  Monthly, state Various lags of unemployment rate Minnesota, Basic and UP models
Employment Annual, state Proportion of female household heads employed full time Moffitt (1986)
  Annual,

state

Proportion of female household heads employed part time Moffitt (1986)
  Monthly, county Ratio of aggregate level of employment in seventeen female dominated industries (females> 40% of workers) and the number of female headed households with related children Maryland, Prince George's County AFDC-Basic model
Employment Gap Quarterly, national Percent difference between potential and actual employment (current and lagged three quarters for Basic; current and lagged five quarters for UP) CBO(1993), AFDC-Basic and AFDC-UP models
  Monthly, state Gap between "full" employment (5.5 percent unemployment) and actual non-agricultural employment Texas
  Monthly, state Gap between current employment rate and its previous maximum Washington, Basic exit model, UP entry and exit models
State's "Composite Neighbor's" Unemployment Rate Annual, state Log of average unemployment rate in state's "composite neighbor" Shroder (1995), recipiency model
Product of UP Program Dummy and State's Unemployment Rate Quarterly, state Unemployment rate, current and lagged three quarters, for states with UP program Cromwell et al. (1986)
Real Earnings of Women, HS, 18-24 Quarterly, national Average earnings of women aged 18 -24 with exactly four years of high school and who work full time, year round, in 1991 dollars CBO (1993), AFDC-Basic

Exhibit 2.3 (Continued)

Economic Variables Used in Previous Studies of AFDC Caseload Growth

Variable Type Description Model(s)
Real Earnings of Men, HS, 18-24 Quarterly, national Average earnings of men aged 18 -24 with exactly four years of high school and who work full time, year round, in 1991 dollars CBO (1993), AFDC-UP
State's Own Wage Level Annual, state Log of average weekly wages for laundry, cleaning, and garment services in state (SIC 271) (nominal). Source: Employment and Wages Annual Averages, Bureau of Labor Statistics, 1982-1988. Shroder (1995), recipiency model
Disposable Income Annual, state Log of per capita after tax income Shroder (1995), benefit model
State's "Composite Neighbor's" Wage Level Annual, state Log of average annual wages for laundry, cleaning, and garment services in state's "composite neighbor" (SIC 271) (nominal) Shroder (1995), recipiency model
Manufacturing Wage Quarterly, state Average monthly manufacturing earnings (real) Cromwell et al. (1986)
Retail Wage Quarterly, state Average weekly wage in retail trade (real) Barnow (1988), Garasky (1990)
  Monthly, state Average real wage rate in retail industry Texas
Retail/Wholesale Wage Index Monthly, state Calculated from total wage bill for selected retail and wholesale trade industries Maryland, AFDC-UP model
Interaction Weekly Wage in Retail Trade Variable Quarterly, state OBRA dummy variable multiplied by average weekly wage in retail trade (real) Barnow (1988)
Monthly Non-wage Income Annual, individual Sum of non-transfer non-wage income and earnings of others in 1977 dollars, divided by 100, for female household heads Moffitt (1986)
Tax Capacity per Capita (in $1000s) Quarterly, state Measure reflects alternative forms of taxpayer revenues in addition to personal income, e.g., property and corporate taxes, severance taxes; Source: Advisory Commission on Intergovernmental Relations (1983) Cromwell et al. (1986)
Poverty Level Monthly, state Federal poverty level income for a family of three Oregon, AFDC-Basic model
Index of Help Wanted Advertisements Monthly, state Index of help wanted advertisements (lagged twelve months, smoothed two months in recovery model; lagged eight months, smoothed two months in recession model); Source: Regional Economic Studies Program, University of Baltimore Maryland, Balance of state AFDC-Basic model, excludes Prince George's County
  Monthly, metro area Index of help wanted advertisements for District of Columbia metro area, lagged thirteen months, smoothed four months; Source: Regional Economic Studies Program, University of Baltimore Maryland, Prince George's County AFDC-Basic model
Seasonal Dummies Quarterly   Grossman (1985); Cromwell et al. (1986); Barnow (1988); CBO (1993)
Monthly Dummies Monthly   Washington, AFDC-Basic and AFDC-UP entry and exit models