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This chapter first describes the economic model used to measure the possible effect of welfare reform and the improved economy on low-skill employment and wages. Then it describes the data used in the analysis, assumptions about the elasticity of labor demand and supply, and estimates of welfare recipients in the labor force.
The economic model presented here provides a framework for studying the entry of large numbers of welfare recipients into the low-skill labor market as a result of (1) the pull of the economy, and (2) the push of welfare reform.
The pull of the economy refers to an increase in the labor demanded by firms at any given wage level, and the entry of welfare recipients into the low-skill labor market in response to better job opportunities. These welfare recipients would have entered the labor force even in the absence of welfare reform. The push of welfare reform refers to an increase in the number of persons willing to work at any given wage level as a direct result of welfare reform, and the consequent entry of welfare recipients into the labor market. These welfare recipients would not have entered the labor force in the absence of welfare reform.
The discussion of the model in the next section is divided into four subsections. Subsection A discusses the economic model. Subsection B stresses the importance of elasticities on the effect of welfare reform. Subsection C discusses unemployment. Subsection D discusses the effect of downward wage rigidities on unemployment.
A. Assessment of the Impact of Welfare Reform and Economic Expansion
The pull of the economy is modeled as a “demand shift” — an increase in the demand for low-skill labor at any wage level (i.e., an outward shift in the demand curve). The push of welfare reform is modeled as a “supply shift” — an increase in the supply of low-skill labor at any wage level (i.e., an outward shift in the supply curve). Both shifts are positive, i.e., they involve an increase in demand and an increase in supply at every wage.
The shifts can be illustrated on a standard labor demand/labor supply diagram (Exhibit 4.1). LS0 is the labor supply curve before welfare reform, and LS1 is the labor supply curve after welfare reform. LD0 is the labor demand curve before economic expansion, and LD1 is the labor demand curve after economic expansion.
The demand shift from LD0 to LD1 and the movement along LS0 from Point A to Point B represent the pull of the economy. It is important to note that the pull of the economy does not shift the supply curve. Employment increases from E0 to EB. The number of welfare recipients pulled into employment is less than this amount, because some who are pulled into employment by the expansion are not welfare recipients.
Exhibit 4.1
Demand and Supply for Low-Skill Labor
Symmetrically, the supply curve shift from LS0 to LS1 and the movement along LD1 from Point B to Point C represents the push of welfare reform. As a result, employment increases from EB to E1. As drawn, the new equilibrium is at a lower wage than the initial equilibrium — the upward pressure of economic expansion on wages is more than offset by the downward pressure of welfare reform. Under such a scenario, some individuals who are working in the initial equilibrium will not be willing to work in the new equilibrium, because of the lower wage. These workers are “displaced” by welfare reform. In the diagram, they are represented by the horizontal distance from EV to E0. The number of new workers is represented by the distance from EV to E1, and is exactly equal to the size of the shift in the supply curve.
It is important to keep in mind that the supply curve represents the supply of workers from two populations — adults who are in the group targeted by welfare programs and all other low-skill, working-age adults. Thus, the increased employment due to the pull of the economy that is represented in Exhibit 4.1 exceeds the number of welfare recipients who are drawn into employment by the economic expansion. Similarly, the workers displaced by welfare reform in Exhibit 4.1 might include some who are in the target group for welfare programs, and some of these might even enter welfare as a result.(32)
Points A and C represent initial and final equilibrium outcomes, before and after welfare reform (supply shift) and economic expansion (demand shift). The percentage changes in employment and wages between these two points can be expressed formally by the following equations, which show the effects of the demand and supply shifts on wages and employment.(33)
(i) % D employment = ( es * % D demand + ed * % D supply) / ( ed + es)
(ii) % D wage = (% D demand - % D supply) / ( ed + es)
where:
We observe the initial (pre-reform) equilibrium point (Point A) and final (post-reform) equilibrium point (Point C) in the data collected (discussed in Section II.A below). These data give us the following information.
This information can be used along with information about the shapes of the supply and demand curves to obtain Point B in Exhibit 4.1. Point B is the wage and employment combination that would have been attained as a result of the economic expansion in the absence of welfare reform. The wage and employment information described above defines Points A and C (equilibrium outcomes before and after welfare reform).
Using the elasticity assumptions (that is, the value of the percentage change in employment associated with the percentage change in wages), we can draw labor demand and labor supply curves that pass through Points A and C. The intersection of the demand curve passing through Point C (LD1) and the supply curve passing through Point A (LS0) is Point B. Points A and C, along with the elasticity assumptions, are sufficient to produce the entire figure. We can also use this information to calculate other information of interest (e.g., the size of the shifts in the demand and supply curves, and the number of displaced workers).
The only remaining unknowns in the equations (i) and (ii) are the magnitudes of the demand and supply shifts (% D demand and % D supply). Because we have two equations and two unknowns, we can solve these two equations for % D demand and % D supply (see below). We can then use the equations to estimate the effects of the demand and supply shifts independently; that is, we can produce counterfactuals for the impact of economic expansion on employment and wages in the low-skill market, as well as counterfactuals for the impact of welfare reform on the same outcomes.
Solving equations (i) and (ii) for % D demand and % D supply, we get the magnitudes of the demand and supply shifts (equations (iii) and (iv)).
(iii) % D demand = % D employment + ed * % D wage
(iv) % D supply = % D employment - es * % D wage
Equations (i) through (iv) apply to small shifts in the supply and demand curves, but provide reasonable approximations for larger shifts if the elasticities of supply and demand are reasonably constant; they are exact if elasticities are constant. Constant elasticity functions are often used to represent supply and demand curves in the applied economics literature. We make use of elasticity estimates from the literature and the above relationships in our analysis.
The wage and employment equations can be used to analyze the impact of the supply shift alone (let % D demand be zero), or the demand shift alone (let % D supply be zero); that is, given the shift to the demand curve or the supply curve, and given the elasticities, we can use the equations to predict the impact on employment and wages. The percentage of workers displaced by an increase in supply can be derived from (iv).
(v) % displacement = % D supply - % D employment = - es * % D wage
B. Elasticity of Labor Demand and Labor Supply
The magnitude of the effect of welfare reform on wages and employment is highly dependent on the elasticity of labor demand and labor supply. The effect of the elasticity of labor demand and labor supply on the percentage change in wages and employment can be obtained by differentiating equations (i) and (ii) with respect to the elasticities. Results are summarized in Exhibit 4.2.
| Demand/Supply | Elasticity | % D Wage (Absolute Value) | % D Employment |
|---|---|---|---|
| % D demand > % D supply (wage increases; employment increases) | |||
|
Elasticity of Demand |
More elastic | Lower | Lower |
| Less elastic | Higher | Higher | |
|
Elasticity of Supply |
More elastic | Lower | Higher |
| Less elastic | Higher | Lower | |
| % demand < % D supply (wage falls; employment increases) | |||
|
Elasticity of Demand |
More elastic | Lower | Higher |
| Less elastic | Higher | Lower | |
|
Elasticity of Supply |
More elastic | Lower | Lower |
| Less elastic | Higher | Higher | |
|
Note: These results assume that the elasticities of demand and supply are greater than zero. |
|||
The direction of the percentage change in the wage is determined by the relative magnitudes of the supply and demand shifts; elasticities only affect the magnitude of the percentage change in the wage. If the labor demand and supply curves are more responsive to the wage (i.e., more elastic), then only a small change in the wage will be needed to restore the labor market to equilibrium. For example, consider the response of the economy if there is a positive demand shift. More workers will be demanded. Wages will rise. If the labor supply curve is very elastic, just a small increase in the wage will be sufficient to draw enough new workers into the labor market to satisfy the increased demand. Alternatively, consider the response of the economy if there is a positive supply shift. Wages will fall. If the labor demand curve is elastic, a small decrease in the wage will be sufficient to increase the quantity of labor demanded to absorb the increased supply. In either case, the equilibrium will be restored with a small change in the wage. Regardless of the relative magnitude of the demand and supply shifts, a higher elasticity of demand and/or supply will result in a smaller absolute change in the wage.
In equation (i) (the % D employment equation), if the demand shift is greater than the supply shift (% D demand > % D supply), then a higher elasticity of demand will result in a lower percentage change in employment, while a higher elasticity of supply will have the opposite effect. If the supply shift is greater than the demand shift (% D supply > % D demand), the results are reversed: the higher the elasticity of demand, the higher the percentage change in employment, and the higher the elasticity of supply, then the lower the percentage change in employment.
One purpose of this project is to assess the impact of welfare reform on the unemployment rate. The unemployment rate, as defined by the Bureau of Labor Statistics (BLS), is an estimate of the percentage of persons who want to work who are not employed. Hence, it is intended to capture “involuntary” unemployment and does not include those who do not want to work (i.e., who are voluntarily unemployed).
In the conceptual model we have presented thus far, there is no involuntary unemployment, by definition. When shifts to the demand or supply curves occur, wages adjust so that everyone who is willing to work at the prevailing wage is employed. While there are some who might be willing to work only at a higher wage, they are voluntarily unemployed.
As discussed above, the influx of workers into the labor market as a result of welfare reform will lead to the displacement of existing workers unless the expansion of demand is sufficient to completely offset the negative effect of the supply shift on wages. Displacement occurs because workers who were employed before welfare reform lose their jobs to welfare recipients who are willing to work for a lower wage. From a theoretical standpoint, displaced workers might be voluntarily unemployed, because they are not willing to work at the lower wage that now prevails in the labor market. However, from a practical standpoint, BLS defines displaced workers as unemployed as long as they are looking for work. If displaced workers eventually decide that they cannot get a job at a wage they would be willing to accept, they might drop out of the labor force and no longer be counted as involuntarily unemployed by BLS.
We assume that job displacement does increase the unemployment rate in the short-run, as displaced workers are not perfectly aware that the prevailing wage in the labor market has fallen. Displaced workers are replaced by welfare recipients who are willing to work for a lower wage. We assume displacement is the primary means through which welfare reform leads to unemployment in the low-skill labor market.
An inability of wages to adjust to new conditions in the long run would, however, result in long-term unemployment. One reason why this might occur is downward wage rigidity, an issue that we turn to next.
The above discussion assumes that the responsiveness of wage adjustments to shifts in either curve are symmetric: in percentage terms, the effects of a positive shift in a curve on wages and employment are equal, but opposite in sign, to the effects of a negative shift of the same size. Economists have long argued, however, that institutional factors, such as the minimum wage and union contracts, result in asymmetric responses to demand shifts. More specifically, a downward shift in demand, induced by a recession or some other factor, might have very little negative impact on wages, but result in large reductions in employment, while an outward shift in demand of equivalent size, starting from the same point, results in higher wages and small increases in employment.
This phenomenon is very relevant for our analysis because many low-skill workers receive wages that are close to the minimum wage and because the starting point of our analysis, 1993, is near the beginning of a recovery from a major recession. If unemployment in an area in 1993 is still high relative to historical values, then the number of low-skill workers who are willing to work at current wage rates might be substantially higher than the number who are employed, and outward demand shifts are likely to increase employment, with little effect on wages, while outward supply shifts might simply result in greater unemployment, with little effect on employment or wages.
This is illustrated in Exhibit 4.3, in a stylized fashion. The initial supply curve is “kinked;” it is horizontal at wage level W0, to the left of Point B, then follows the upward sloping LS0. W0 represents a “peak” wage from the most recent expansionary period. The demand curve that generated that wage rate (i.e., pre-recession peak demand) is represented by LD-1, and peak employment is E-1. The initial demand curve LD0 passes through the horizontal portion of the initial supply curve at E0 (Point A).
Exhibit 4.3
Demand and Supply for Low-Skill Labor in the Presence of Downward Wage
Rigidity
Consider first an outward shift in demand (LD1), holding supply constant. The wage remains constant until the demand curve shifts past the previous peak demand curve at Point B, then rises along LS0 to Point C, where LD1 intersects LS0. This scenario can be used to illustrate what happens if we ignore the kinked supply curve in the analysis. Suppose we, mistakenly, assume that the initial supply curve is LS* — which also passes through LD0 at Point A, but is not kinked. The employment and wage change generated by the fixed kinked supply curve and the shift in demand is identical to what would be observed if LS* was the initial supply curve and supply shifted from LS* to LS0 as demand shifted from LD0 to LD1 (Point C). Thus, if we ignored the kinked nature of the hypothetical true supply curve, we could easily mistake an increase in employment and wages that is due solely to a demand shift as the result of both a shift in demand and a smaller shift in supply. The size of the false supply shift is the horizontal distance from Point A to Point B. In this stylized model, this is identical to the drop in employment from peak pre-recession employment, E-1, to E0. While the increase in employment from E0 to E1 is entirely due to the demand shift, the analysis would attribute part of the change to the false supply shift — represented by the distance between E1 and E*.
Next, consider an outward shift in supply, to LS1, holding demand constant, again starting at Point A. As the wage rate is already at the pre-expansion peak, it cannot decline further. There is no increase in employment, because demand does not shift. The number of persons seeking jobs at the existing wage rate is E3 (Point D), and E3 – E1 workers are unemployed. Hence, under this stylized scenario, the push of welfare reform would just increase unemployment without increasing employment or depressing wages. This scenario further illustrates what happens if the analysis were to ignore the kinked supply curve. It would appear that the shift in supply due to welfare push was the horizontal distance from LS* to LS1, greater than the horizontal distance which represents the actual shift, from LS0 to LS1, again by amount E-1 – E0.
The analysis becomes more complex if there is both a demand and a supply shift, because the order in which they shift matters. If supply shifts first, to LS1, then demand shifts to LD1, the wage rate stays constant and employment expands to E2; E3 – E2 workers are unemployed. If, instead, demand shift firsts, then supply, wages increase to W1, employment increases to E1, and the shift in supply has no impact on wages or employment, but results in unemployment of E4 – E1.
In a less stylized version of the above example, the supply curve would be more elastic at wage rates below previous peaks, and less elastic at higher wage rates. Such a supply curve would yield findings that are qualitatively similar to the stylized version presented above, with outward shifts in supply generating only modest wage reductions and outward shifts in demand generating only modest increases up to the point where demand passes the previous peak, and more pronounced increases thereafter.
In the decomposition of employment and wage changes into changes due to welfare push and changes due to the economy, we do not attempt to model kinks in the supply curve like those that appear in this stylized example, because we do not have a sound empirical basis for differentiating between the supply elasticity for low-skill workers during the early recovery from a recession and the elasticity as economic expansion passes the earlier peak. Instead, we use a constant elasticity model with an elasticity based on findings in the literature. The analysis of the kinked supply curve, above, is very important, however, in helping us interpret the findings.
The economic model presented here provides a framework for analyzing the entry of large numbers of welfare recipients into the low-skill labor market. Better job opportunities and welfare reform are the two main reasons for this phenomenon.
The economic model is an equilibrium model of low-skill labor demand and labor supply. In the economic model, a shift in labor demand represents the increase in job opportunities and a shift in labor supply represents the increase in labor market entry of welfare recipients due to work requirements and time limits. Both of these changes increase employment, but have opposite impacts on prevailing wages.
If the equilibrium wage falls, some former workers will be displaced; i.e., their employers will replace them with welfare recipients who have entered the labor market and are willing to work for lower wages. This is likely to result in short-term unemployment, as those displaced continue to seek work at a higher wage. In the long-term some of these individuals are likely to become discouraged and leave the labor force, mitigating the impact on the unemployment rate.
To calculate low-skill employment and wages, we calculated employment and wages by occupation. We first classified occupations as low-skill, medium-skill, and high-skill, and then aggregated employment and wages across all occupations that were classified as low-skill.
A. Calculating Employment and Wages by Occupation
To estimate employment and wages by occupation, we obtained employment and wage data by industry from the BLS Covered Employment and Wages (ES-202) system. We distributed employment and wages in each industry across occupations using the National Industry Staffing Patterns (NISP).
It would have been preferable to use employment and wage data by occupation instead of by industry, obviating the need for an industry to occupation conversion. The Occupational Employment Statistics (OES) survey, on which the NISP is based, tabulates employment and wage data by occupation. However, wage data are only available for 1998. In addition, the OES did not survey all agricultural, forestry, fishing, and private household industries. Therefore, we used the ES-202 for employment and wages.
1.Covered Employment and Wages (ES-202)
The ES-202 program provides comprehensive employment and wage information by industry for workers covered by state Unemployment Insurance laws and federal workers covered by the Unemployment Compensation for Federal Employees program. Employment is reported monthly for covered workers who were working or who received pay during the pay period including the 12th of the month. Wages, from payroll records, are reported quarterly for all covered workers who received pay during the quarter.
The ES-202 data are coded according to the Standard Industrial Classification (SIC) system, which classifies establishments by industry activity. While a four-digit SIC level is assigned to all reporting establishments, employment and wages are often aggregated to the two-digit or one-digit level. Examples of industries in these categories include the following:
| Four-Digit | Two-Digit | One-Digit |
|---|---|---|
|
Wheat Grains |
Agricultural Production Crops | Agriculture, Forestry, Fishing |
|
Creamery Butter |
Food and Kindred Products | Manufacturing |
|
Women’s Clothing |
Stores Apparel & Accessory Stores | Retail Trade |
|
Junior Colleges |
Educational Services | Services |
Because of confidentiality concerns, ES-202 data are not disclosed for any level in which the universe has three or fewer employers or is dominated by a single employer that represents more than 80 percent of employment. We obtained ES-202 data at the two-digit SIC level rather than four-digit SIC to reduce the number of undisclosed employment records.(34) When we encountered undisclosed cells at the two-digit SIC level, we allocated the remaining employment and payroll at the one-digit SIC level (total minus all disclosed employment within an industry level) equally across all undisclosed cells.
2.National Industry Staffing Patterns (NISP)
For this study, we use the NISP’s occupational estimates by industry, which are produced from the national OES, to convert employment and payroll (total wages) by industry for each region to employment and payroll by occupation. Prior to 1996, the OES surveyed only one-third of the industries in the sample each year, taking three years to fully complete the survey. This was done to reduce respondent burden. In addition, it only collected employment data. In 1996, OES began to survey all industries in each year, but recommended using three years of data to reduce sampling error. As discussed above, it began collecting wage information in 1996.
We obtained the NISP at the two-digit level from BLS for 1990 through 1998. We combined 1990 to 1992, 1993 to 1995, and 1996 to 1998 NISPs to obtain the industry occupation matrix for 1993, 1996, and 1998. Because NISP is only produced at the national level, we made the implicit assumption that there were no significant regional differences in the occupational distribution for each industry. We tested this assumption using the Current Population Survey (CPS), and found a consistent pattern of occupational employment in each industry across four regions (Northeast, Midwest, South, West) and in urban versus rural areas. These results are presented in Appendix A.
The 1998 NISP was used to distribute payroll for 1993, 1996, and 1998. We assumed there were no significant differences in the occupational distribution within an industry over time. We tested this assumption using the CPS. The CPS shows a declining percentage of payroll in low-skill occupations over time, while we assumed no decline in the proportion of total payroll allocated to low-skill occupations (see Appendix B). We are not too concerned about the latter assumption because there is no decline in the share of employment in low-skill occupations from the CPS, while there is an increase over time from the NISP (i.e., we found employment in low-skill occupations grew at a faster rate than employment in high-skill occupations). Thus, in both cases, wages per low-skill worker grew at a slower rate than wages per high-skill worker.
B. Classifying Occupations by Education and Training Requirements
We classified occupations into three skill categories (low, medium, and high) using the BLS education and training requirements for occupation groups. The BLS requirements are straightforward and consistent with the CPS and OES. BLS classifies occupations in 11 groups according to their education and training requirements. We grouped occupations that require short-term (less than one month) on-the-job training as low-skill. This is the occupation category that requires the least level of education and training in the BLS classification. Examples of occupations in the low-skill category are retail salespersons, office clerks, cashiers, truck drivers, personal care and home health aides. We grouped occupations that require more than short-term on-the-job training, but less than a bachelor’s degree, as medium-skill. These occupations may require more on-the-job training, more work experience, vocational training, or an associate’s degree. We grouped occupations that require a bachelor’s degree or higher as high-skill.
One disadvantage of the BLS classification is that it does not indicate whether occupations require a high school degree. This should not be a problem, however, as CPS tabulations show that there is a mix of high school graduates and high school drop-outs in the population who received income from TANF in 1998 (see Exhibit 2.1).
Other researchers (Leete and Bania(35); Lerman, Loprest, and Ratcliffe(36)) have defined low-skill jobs to include both short-term and moderate-term training occupations. Leete and Bania also included long-term training occupations in their definition, but limited the percentage of welfare recipients who were eligible for these jobs. We chose to include only short-term training occupations in our definition because we believed these occupations would be affected most by welfare reform.
As discussed above, we assumed there were no regional differences between the occupational distribution of employment within an industry (i.e., differences in skill level resulted from differences in the industry mix of employment across regions). Appendix C presents a comparison of the percentage of 1998 employment by skill level from our estimates (ES-202 merged with the NISP) and the OES, which we were able to obtain for selected regions only. The percentage of employment that was low-skill was slightly lower from the ES-202/NISP than from OES.
Our assumption is that welfare reform will have the largest effect on the low-skill labor market. Hence, the relevant elasticities of labor demand and labor supply are those for low-skill labor. Bartik presents a summary of elasticity estimates used in studies that examine the effect of welfare reform on wages and displacement.(37) The three studies cited in the exhibit (Mishel and Schmitt,(38) Holzer,(39) and Bernstein(40))used a labor demand elasticity of -0.3. Holzer and Bernstein used a labor supply elasticity of 0.4; Mishel and Schmitt used a labor supply elasticity of zero. All three studies repeated their calculations for alternative labor demand and labor supply elasticity assumptions.
Because elasticities for different types of labor can vary, it is necessary to use an elasticity estimate for workers who are similar in characteristics to welfare recipients. The labor demand estimates used in the studies cited above are taken from the minimum wage literature. The labor supply estimates used in these studies are taken from the literature on the decline in employment among low-skill adult males in the 1980s.
Based on these studies, we used a labor demand elasticity of -0.3 and a labor supply elasticity of 0.4. We were not able to find any studies that compared the differences in the elasticities across rural and urban areas. We were also not able to find any studies that compared the differences in the elasticity of labor supply before and after welfare reform.
Assumptions about the elasticity of labor supply and labor demand are critical to our analysis. As was discussed in Section 4.A and will be discussed in more detail in Chapter 5, the elasticity assumptions are instrumental in determining the size of the demand and supply shifts from the employment and wage data that we collected. Therefore, we used alternative labor demand and labor supply elasticities to test the sensitivity of our results to the elasticity assumptions. These results are presented in Appendix D. We found that our basic findings are not affected much by reasonable changes in the elasticities as a result of the small size of the increase in employment due to welfare reform relative to the low-skill labor market.
To estimate the number of welfare recipients in the labor force, we collected caseload information from all regions and estimated labor force participation from a combination of caseload employment reports, state estimates produced by DHHS, and a study of TANF leavers from the National Survey of America’s Families (NSAF).
The change in welfare caseloads over time is due to two effects: the change in the number of welfare recipients who enter the welfare rolls (inflow) and the change in the number of welfare recipients who leave the rolls (outflow).
Change in Inflow
Changes in inflow can be caused by the economy and by welfare reform. For example, potential welfare recipients who might have entered the rolls under previous economic conditions (e.g., the 1991 recession) may be less likely to apply if they can find jobs easily in a strong economy. Potential welfare recipients might also be diverted from welfare due to welfare reforms, such as time limits, stringent work requirements, and state welfare diversion programs that either require an applicant to look for work before being approved for benefits or offer a one-time lump sum payment to help potential clients to avoid welfare altogether. These potential recipients might instead rely on family support for income or enter the labor market.
Change in Outflow
Changes in outflow also are due to the economy and welfare reform. For example, in a strong economy, more recipients might leave welfare due to better job opportunities in the labor market. Welfare reform policies also play a role. More recipients might leave welfare due to time limits and stringent work requirements. Recipients who leave may rely on family support for income or might enter the labor market. Some might have been working “off the books” while on welfare and could continue to rely on their shadow labor market activities for income after they leave the rolls.
For this analysis, we are measuring the change in stock between two points in time and not focusing on changes in flows. Therefore, our analysis assumes there is no net effect on the labor market when a person leaves welfare, but is replaced by another person who enters welfare.
Our analysis uses the number of welfare recipients who are newly employed. That is, our estimates include those who were not in the labor force initially (e.g., in a given month in 1993), but who entered at a later point in time (e.g., in a given month in 1996). The number of welfare recipients entering the labor market is estimated using the following equation:
(vi) (C0 – C1) *(L1 – W0) + C1 * (W1 – W0)
where:
C0 = Caseload at time(0)
C1 = Caseload at time(1)
W0 = Percent of caseload in labor force at time(0)
W1 = Percent of caseload in labor force at time(1)
L1 = Percent of leavers in labor force at time(1)
Note that C0 – C1 represents the change as a result of welfare recipients leaving (net of those arriving) and others diverted from entering the rolls. While the formula appears to assume that welfare leavers and welfare stayers — those who continued to be on the rolls at time(1) — had equal labor force participation rates at time(0), this is not a necessary condition. We can assume that welfare leavers had a higher rate of labor force participation in the initial period than did stayers and still get the same results.(41)
Exhibit 4.4 presents each region’s monthly caseload, for each relevant year, along with estimates of the percentage of welfare recipients and welfare leavers who were in the labor force. These estimates came from the following sources:
As this exhibit shows, New York, Vermont, and Wisconsin welfare recipients were more likely to be in the labor force while on welfare. These states offer relatively high cash grants that enable individuals with earnings to remain eligible for welfare. The Southern states, on the other hand, offer lower grants and have a lower share of the welfare population employed.
| 1993 | 1996 | 1998 | ||||||
|---|---|---|---|---|---|---|---|---|
| Monthly Caseload | Caseload in Labor Force (%) | Monthly Caseload | Caseload in Labor Force (%) | Leavers in Labor Force (%) | Monthly Caseload | Caseload in Labor Force (%) | Leavers in Labor Force (%) | |
|
Decatur and Florence, Alabama |
1,577 | 1.0 | 1,167 | 1.1 | 50.0 | 645 | 8.7 | 61.0 |
|
Rural Mississippi |
45,384 | 9.1 | 36,565 | 8.1 | 50.0 | 19,096 | 7.6 | 61.0 |
|
Joplin, Missouri |
2,081 | 4.5 | 1,906 | 4.6 | 50.0 | 1,271 | 10.1 | 61.0 |
|
Southeast Missouri |
12,674 | 4.6 | 10,817 | 8.6 | 50.0 | 7,972 | 14.1 | 61.0 |
|
Jamestown, New York |
3,154 | 17.0 | 2,516 | 24.0 | 50.0 | 1,975 | 27.0 | 61.0 |
|
North Country, New York |
6,656 | 9.0 | 5,749 | 15.8 | 50.0 | 4,145 | 20.9 | 61.0 |
|
Medford-Ashland, Oregon |
2,540 | 12.7 | 1,820 | 11.8 | 50.0 | 896 | 3.8 | 61.0 |
|
Central Oregon |
1,342 | 12.7 | 1,026 | 11.8 | 50.0 | 635 | 3.8 | 61.0 |
|
Florence, South Carolina |
2,619 | 6.8 | 2,469 | 9.8 | 50.0 | 1,665 | 16.8 | 61.0 |
|
Vermont |
10,081 | 12.0 | 9,210 | 23.1 | 50.0 | 7,591 | 22.7 | 61.0 |
|
Eau Claire, Wisconsin |
2,037 | 28.2 | 1,116 | 27.9 | 50.0 | 302 | 13.6 | 61.0 |
|
Wausau, Wisconsin |
1,162 | 22.5 | 785 | 23.1 | 50.0 | 234 | 15.8 | 61.0 |
|
United States |
4,963,000 | 7.8 | 4,628,000 | 10.3 | 50.0 | 3,305,000 | 15.6 | 61.0 |
| Source: Lewin calculations using data provided by state welfare agencies and DHHS. | ||||||||
(32) Technically, there are two supply curves behind the supply curve drawn, one for each of the population groups. The sum of labor supplied at a given wage from the two groups corresponds to total labor supplied at that wage on the supply curve shown. The shift in the labor supply curve for the welfare target group corresponds to the shift in the total labor supply curve. [Back To Text]
(33) The derivation of these equations can be found in Freeman (1977). They hold only approximately, except for infinitesimally small shifts. A simple way to derive them is to begin with the assumption that the demand and supply curves are linear in natural logarithms (i.e., assume that the wage and employment axes in Exhibit 4.1 are natural log scales). For small changes, changes in logs are equivalent to percentage changes in levels. The slope of the supply curve on the log scales is the inverse of the supply elasticity and the slope of the demand curve is the negative of the inverse of the demand elasticity. Given these slopes, Equations (i) and (ii) can be derived via the use of geometry. If percentage changes in the equation are replaced by changes in logarithms, and if the demand and supply curves are linear in the logarithms, the equations apply exactly. [Back To Text]
(34) We obtained data for all of our metropolitan regions from the BLS and for nonmetropolitan regions from State Employment Security Agencies (SESA) for 1993, 1996, and 1998. [Back To Text]
(35) Leete, L. & N. Bania (1999) [Back To Text]
(36) Lerman, R., P. Loprest, & C. Ratcliffe (1999). [Back To Text]
(37) Bartik, T. J. (1999). Displacement and Wage Effects of Welfare Reform. W.E. Upjohn Institute for Employment Research. Kalamazoo, MI. [Back To Text]
(38) Mishel, L. & J. Schmitt (1995). Cutting Wages By Cutting Welfare. Economic Policy Institute. Washington, DC. [Back To Text]
(39) Holzer, H. J. (1996). Employer Demand, AFDC Recipients, and Labor Market Policy. Institute for Research on Poverty Discussion Paper No. 1115-96. Michigan State University. East Lansing, MI. [Back To Text]
(40) Bernstein, J. (1997). Welfare Reform and the Low-Wage Labor Market: Employment, Wages, and Wage Policies. Economic Policy Institute Technical Paper #226. Washington, DC. [Back To Text]
(41) If we assume there are two groups — leavers (C0 – C1) and stayers (C1) — and each group has an average employment rate at time(0) of WL0 and WS0, respectively, then the following equation measures the increase in total employed from time(0) to time(1):
(vii) (C0 – C1) * (L1 – WL0) + C1 * (W1 – WS0).
The following identity also holds:
(viii) ( C0 – C1) * WL0 + C1 * WS0 = W0 * C0 {total employed at time(0)}
Substituting the right-hand side of Eq. (viii) in Eq. (vii), yields the following:
(C0 – C1) * L1 + C1 * W1 – W0 * C0, which is equal to Eq. (vi) [Back To Text]
(42) Loprest, P. (1999). Families Who Left Welfare: Who Are They and How Are They Doing? Washington, DC: The Urban Institute. [Back To Text]
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