How Well Have Rural and Small Metropolitan Labor Markets Absorbed Welfare Recipients?. Analysis of Supply Shifts and the Maximum Impact of Welfare Reform

04/01/2001

In this section we analyze the estimated supply shifts further and also produce estimates of the maximum impact that welfare reform could have had on employment and wages during both periods.

We begin by assessing the plausible magnitudes of three factors that could account for the estimated supply shifts: welfare reform, reduction of excess supply of labor following the 1991 recession; and population growth.

1.Increase of Welfare Recipients in the Labor Force

The impact of welfare reform on the supply shift could be no larger than the change in employment in the welfare population. Both demand pull and welfare reform push contributed positively to this growth, so the impact of welfare reform could be no larger than the total change in employment. We calculated the increase of welfare recipients in the labor force based on caseload declines, estimates of the percentage of leavers in the labor force, and estimates of the percentage of welfare recipients combining work and welfare from caseload reports.(44)

2.Reduction of Excess Supply of Labor

Because wages tend to be rigid downward, there was an increase in unemployment at the prevailing wage between 1989 and 1993.(45) When economic recovery began in 1993, these previously unemployed workers began to find employment at the prevailing wage. There was an increase in low-skill employment without an increase in low-skill wages. Because we did not model downward wage rigidity, this observation was interpreted as a supply shift in the economic model during this time period. We predicted that the economy would have completely recovered from the recession by 1996 in most regions.

To assess the possible contribution of reductions in the excess supply of labor following the 1991 recession, we estimated the difference between employment in the base year for each of the two periods (i.e., 1993 or 1996) and what employment would have been had the employment rate (employment divided by the adult population) in that year been the same as in 1989. We interpreted the latter as an estimate of pre-recession peak employment, adjusted for population growth. If the difference was positive, we interpreted it as the excess labor supply remaining in the base year as the result of the recession. If the difference was negative, we assumed that no excess labor supply remained. We calculated the percentages by dividing the difference by base-year employment. Note that these percentages applied to all skill levels, combined. We did not have the information needed to compute estimates by skill level. We suspect that relative excess labor supply for low-skill workers would be greater than for all workers combined, so these estimates likely understated the contribution of excess labor supply to the estimated supply shifts.

3.Population Growth

The final factor we considered explicitly was population growth. The contribution of population growth to supply shifts was estimated as the percentage increase in the entire population over each period. We assumed that the percent increase in the low-skill labor force due to population growth would be similar.(46)

All regions, with the exception of the New York regions, experienced some population growth that contributed to the supply shift. In particular, the Oregon regions experienced significant growth during this period.

4.Other Factors

As indicated earlier, at least two other factors could have contributed to change in the supply curve over this period  the EITC and the increase in the minimum wage. The EITC would have shifted the supply curve out, and the increase in the minimum wage would have effectively made the supply curve more inelastic at wage rates near the minimum and generated excess supply.

Results of the analysis for 1993 to 1996 and 1996 to 1998 appear in the first four columns of Exhibits 5.7 and 5.8, respectively.

For the earlier period (Exhibit 5.7), the maximum that welfare reform could have contributed to the supply shift was well below the estimated supply shift in all but one region (North Country, New York). Population growth and excess supply helped explain the large estimated shifts in most areas, but if we used the values in the table to estimate the contributions of welfare reform, excess supply, and population growth to the estimated supply shift, there was a considerable residual in several areas. We do not have good explanations for all of these residuals. Those in Alabama and Mississippi could have reflected the fact that these areas economies had high unemployment rates throughout the 1980s, so our estimates might have substantially underestimated the size of excess supply in 1993.(47) The source of the exceptionally high residual for Eau Claire, Wisconsin is unknown. The EITC and minimum wage might explain some of the residual shift. Measurements errors and errors in the elasticity estimates could also have been contributing factors.

For the later period (Exhibit 5.8), the maximum that welfare reform could have contributed to the supply shift was below the estimated supply shift in all regions. There was excess labor supply from the recession in only 4 of 12 regions. The residuals were smaller than they were for the earlier period, but they were still not negligible.

It is apparent from this analysis that the estimated supply shift was a poor indicator of the impact of welfare reform on supply, with the possible exception of a few regions in the 1993 to 1996 period. The maximum estimate of the impact of welfare reform on the supply shift, which was based on analysis of caseload data, appears to be much more useful for our purposes. Based on this estimate, plus the estimated demand and supply elasticities, we also estimated the maximum impact of welfare reform on both employment and wages in each period. These estimates appear in columns seven of Exhibits 5.7 and 5.8. For comparison purposes, we also show the total change in employment and wages (columns six and nine), and the total that the supply and demand analysis attributed to supply shifts (columns eight and eleven).

Exhibit 5.7
Factors Contributing to Estimated Supply Shift, 1993-1996
  Factors Contributing to Estimated Supply Shift Employment Growth Wage Growth
Region Total Welfare Reform (max) Net Job Loss Pop Growth Residual Total Welfare Reform (max) Supply Shift Total Welfare Reform (max) Supply Shift
Decatur and Florence, Alabama 9.6 0.5 0.0 1.1 8.0 9.2 0.2 4.0 -0.8 -0.7 -13.7
Rural Mississippi 13.0 1.0 0.0 2.6 9.4 13.5 0.5 5.8 1.2 -1.7 -18.6

Joplin, Missouri

8.1 0.3 0.9 4.3 2.6 10.8 0.1 4.6 6.6 -0.4 -11.6

Southeast Missouri

9.1 1.8 2.7 2.3 2.3 9.3 0.8 4.0 0.4 -2.6 -13.0

Jamestown, New York

3.0 0.3 0.7 -1.1 3.1 1.9 0.7 0.8 -2.7 -2.4 -4.2

North Country, New York

-0.1 0.7 0.4 -1.4 0.2 -0.3 0.6 -0.1 -0.4 -1.8 0.1

Medford-Ashland, Oregon

13.5 1.0 1.8 6.6 4.1 12.8 0.4 5.5 -1.8 -1.4 -19.3

Central Oregon

15.5 0.6 2.3 11.3 1.3 14.0 0.2 6.0 -3.8 -0.7 -22.2

Florence, South Carolina

8.3 0.5 4.4 3.1 0.3 8.1 0.3 3.5 -0.5 -0.9 -11.9

Vermont

8.3 1.3 1.8 2.2 3.0 7.4 0.5 3.2 -2.0 -1.8 -11.8

Eau Claire, Wisconsin

16.0 0.8 1.5 1.5 12.4 15.5 0.3 6.6 -1.5 -1.1 -22.9

Wausau, Wisconsin

8.2 0.5 0.8 1.8 5.2 8.6 0.2 3.7 1.0 -0.7 -11.8

Average

9.4 0.8 1.4 2.9 4.3 9.2 0.4 4.0 -0.4 -1.4 -13.4

United States

8.8 0.6 1.7 2.9 3.6 8.7 0.2 3.7 -0.1 -0.8 -12.5

Source: Lewin calculations using ES-202, NISP, BLS education and training requirements data, and data provided by state welfare agencies.

Exhibit 5.8
Factors Contributing to Estimated Supply Shift, 1996-1998
Factors Contributing to Estimated Supply Shift Employment Growth Wage Growth
Region Total Welfare Reform (max) Net Job Loss Pop Growth Residual Total Welfare Reform (max) Supply Shift Total Welfare Reform (max) Supply Shift

Decatur and Florence, Alabama

2.1 0.8 -2.8 1.4 -0.1 2.5 0.4 0.9 1.1 -1.2 -3.0

Rural Mississippi

6.1 2.8 -1.5 1.1 2.2 6.8 1.3 2.6 1.9 -4.2 -8.7

Joplin, Missouri

7.4 1.2 -1.3 2.1 4.1 7.9 0.6 3.2 1.4 -1.9 -10.5

Southeast Missouri

4.5 2.4 -0.4 1.0 1.1 4.8 1.1 1.9 0.8 -3.6 -6.4

Jamestown, New York

1.3 1.1 -0.9 -1.8 2.0 2.5 0.5 0.6 3.0 -1.6 -1.8

North Country, New York

3.6 1.5 -0.9 -1.5 3.6 4.5 0.7 1.6 2.3 -2.3 -5.2

Medford-Ashland, Oregon

7.2 1.2 1.6 2.7 3.3 8.1 0.5 3.1 2.1 -1.8 -10.3

Central Oregon

6.8 0.5 2.4 6.3 0.0 7.5 0.3 2.9 1.7 -0.8 -9.8

Florence, South Carolina

6.1 2.1 4.0 1.1 2.9 6.4 0.9 2.6 0.6 -3.2 -8.7

Vermont

4.0 0.5 1.0 0.3 3.2 5.0 0.2 1.7 2.5 -0.7 -5.7

Eau Claire, Wisconsin

1.9 0.7 -0.6 0.4 0.8 4.4 0.3 0.8 6.2 -1.1 -2.8

Wausau, Wisconsin

6.6 0.8 -0.5 1.1 4.8 7.4 0.3 2.8 1.9 -1.1 -9.5

Average

4.8 1.3 0.0 1.2 2.3 5.7 0.6 2.1 2.1 -2.0 -6.9

United States

5.6 1.7 0.1 1.9 1.9 7.1 0.7 2.4 3.8 -2.5 -7.9

Source: Lewin calculations using ES-202, NISP, BLS education and training requirements data, and data provided by state welfare agencies