Characteristics of Low-Wage Workers and Their Labor Market Experiences: Evidence from the Mid- to Late 1990s. Subgroup Results

04/30/2004

There is substantial diversity in job and employment spell durations among low-wage workers. Is it possible to identify subgroups of workers across whom spell durations differ? Identifying these subgroups can provide policy-relevant information as to which subgroups of low-wage workers fare best in the labor market. Furthermore, the analysis can be used to check the robustness of our previous subgroup findings from the overall employment and wage progression analyses.

To keep our presentation manageable, we present subgroup findings on (1) exit rates from low-wage job spells within 12 months after job start by type of exit; and (2) cumulative exit rates from employment spells within 4, 12, and 24 months after job start. We estimated life tables, one at a time, for key subgroups of males and females defined by individual, household, and initial job characteristics.

Because our findings strongly support those presented in previous chapters, we provide less detail on the results than before. In particular, we find that the same subgroups of workers who typically had the best overall employment experiences and wage growth also had the best spell-related outcomes. The concurrence of the subgroup results is not surprising, because we

expected that subgroups of low-wage workers who experienced the most wage progression over the medium term would also be the ones most likely to exit low-wage job spells into higher-wage employment and to have the longest overall employment spells.

a. Overall Duration of Low-Wage Job Spells

Low-wage job spells are typically short across all subgroups defined by worker and initial job characteristics (last column in Tables VI.7 and VI.8). For example, during the mid- to late 1990s, 12-month cumulative exit rates for males in most subgroups ranged from 78 to 85 percent. Similarly, the cumulative exit rates for females typically ranged from 73 to 80 percent.

Nonetheless, some patterns are evident. Low-wage spells were typically longer for older than for younger workers, but as discussed in the next section, this finding masks important age differences in the states into which workers exited. More intuitively, spell durations were likely to be longer for Hispanics, those who did not attend college and those with low wages than for their counterparts. However, exit rate differences across these subgroups are not large.

b. Types of Exits from Low-Wage Job Spells

We find larger subgroup differences in exit types from low-wage job spells:

  • The low-wage job spells of workers between the ages of 30 and 60 are much more likely to result in higher-wage employment than for those younger or older. Only about 20 percent of male teenagers in our sample and 8 percent of female teenagers obtained higher-wage jobs within 12 months after job start (either with the same employer or a different one; Tables VI.7 and VI.8). In contrast, the corresponding figures for males and females between ages 30 and 60 were about 40 percent and 25 percent, respectively. Similarly, the younger workers were much more likely than those older to exit into another low-wage job and nonemployment. Thus, it is not surprising that in previous analyses we found that younger low-wage workers typically experience less wage growth than those older.

Table VI.7.
12-Month Cumulative Exit Rates From Low-Wage Job Spells
For Males, By Type Of Exit And Subgroup
(Percentages)
Subgroup 12-Month Cumulative Exit Rate for Males, by Exit Type Total
Another Low-Wage Job Higher-WagehJob with the Same Employer Higher-Wage Job with a Different Employer Nonemploy-ment
Overall 20 21 12 29 81
Individual and Household Characteristics
Age (in Years)
   Younger than 20 25 13 7 43 88
   20 to 29 24 18 13 29 83
   30 to 39 15 25 14 25 79
   40 to 49 14 28 11 25 78
   50 to 59 13 27 12 22 75
   60 or older 10 19 8 25 62
Race/Ethnicity
   White and other non-Hispanic 21 22 13 26 83
   Black, non-Hispanic 14 18 9 39 80
   Hispanic 21 17 7 32 77
Educational Attainment
   Less than high school/GED 20 16 7 37 79
   High school/GED 20 18 11 30 80
   Some college 19 27 12 26 84
   College graduate or more 19 27 20 19 84
Has a Health Limitation
   Yes 17 17 7 45 85
   No 20 21 12 28 81
Household Type
   Single parent with children 19 15 8 39 81
   Married couple with children 20 23 13 27 82
   Married couple without children 20 22 10 26 78
   Other adults without children 19 18 14 32 83
Household Income as a Percentage of the Poverty Level
   100 percent or less 22 14 11 34 82
   101 to 200 percent 20 19 10 31 80
   More than 200 percent 19 23 13 27 82
Job Characteristics
Hourly Wages
   Less than $5.00 20 18 13 30 81
   $5.00 to $5.99 23 11 9 33 75
   $6.00 to $6.99 22 18 11 30 81
   $7.00 to $7.50 14 33 15 25 87
Hours Worked per Week
   1 to 19 26 9 15 35 86
   20 to 34 24 13 10 33 81
   35 to 40 18 20 11 30 79
   More than 40 17 33 15 20 86
Weekly Earnings
   Less than $150 27 11 13 32 83
   $150 to $299 20 18 11 30 79
   $300 to $600 13 38 14 24 88
Owns Business
   Yes 14 40 25 12 90
   No 20 20 11 30 81
Health Insurance Coverage(a)
   Yes 18 26 14 24 82
   No 21 17 10 33 81
Occupation
   Professional/technical 15 35 18 17 86
   Sales/retail 23 27 10 20 81
   Administrative support/clerical 17 20 11 30 79
   Service professions/ handlers/cleaners 22 14 10 35 80
   Machine/construction/production/transportation 17 25 13 27 83
   Farm/agricultural/other workers 22 15 10 35 82
Industry
   Agriculture/forestry/ fishing/hunting 20 20 12 31 83
   Mining/manufacturing/construction/transportation/utilities 18 25 13 28 83
   Wholesale/retail trade 22 17 10 29 79
   Personal/health/other services 19 18 11 32 81
   Other 14 40 22 12 89
Source: 1996 SIPP longitudinal files using the entry cohort sample of 4,489 low-wage job spells for males. Left-censored spells were excluded from the sample.
Note: All figures are weighted using the longitudinal panel weight.
a. These figures pertain to health insurance coverage from all sources, including coverage through the employer as well as from other sources. We used this variable instead of the employer-based health insurance coverage variable, because data on overall health insurance coverage is available monthly, whereas the employer-based coverage variable pertains only to jobs in progress at the time of the interview. Thus, the employer-based health insurance variable could not always be linked to the job under investigation, which led to a significant number of missing values. However, the subsets of health insurance variables overlap considerably: the source of health insurance coverage was the employer for 80 percent of those with any coverage.

Table VI.8.
12-Month Cumulative Exit Rates From Low-Wage Job Spells
For Females, By Type Of Exit And Subgroup
(Percentages)
Subgroup 12-Month Cumulative Exit Rate for Females, by Exit Type Total
Another Low-Wage Job Higher-WagehJob with the Same Employer Higher-Wage Job with a Different Employer Nonemploy-ment
Overall 22 14 8 33 76
Individual and Household Characteristics
Age (in Years)
   Younger than 20 29 4 4 44 82
   20 to 29 25 13 8 35 81
   30 to 39 21 15 7 31 75
   40 to 49 19 18 8 24 70
   50 to 59 15 17 9 26 67
   60 or older 14 14 1 33 62
Race/Ethnicity
   White and other non-Hispanic 23 15 8 30 76
   Black, non-Hispanic 20 12 5 39 76
   Hispanic 20 12 6 37 74
Educational Attainment
   Less than high school/GED 23 6 3 43 76
   High school/GED 22 13 6 33 73
   Some college 25 17 9 30 80
   College graduate or more 19 22 14 24 80
Has a Health Limitation
   Yes 23 8 5 46 81
   No 22 15 8 31 76
Household Type
   Single parent with children 24 11 6 37 78
   Married couple with children 19 15 6 34 76
   Married couple without children 23 15 8 27 73
   Other adults without children 26 15 11 27 79
Household Income as a Percentage of the Poverty Level
   100 percent or less 25 7 5 40 77
   101 to 200 percent 22 11 6 36 76
   More than 200 percent 21 18 9 28 76
Job Characteristics
Hourly Wages
   Less than $5.00 24 10 7 37 78
   $5.00 to $5.99 26 6 5 37 74
   $6.00 to $6.99 22 13 7 31 73
   $7.00 to $7.50 15 31 11 24 82
Hours Worked per Week
   1 to 19 24 10 7 38 80
   20 to 34 26 9 7 35 77
   35 to 40 19 17 7 30 74
   More than 40 21 21 11 27 80
Weekly Earnings
   Less than $150 26 9 7 38 79
   $150 to $299 22 14 7 31 73
   $300 to $600 12 40 13 22 87
Owns Business
   Yes 15 27 20 19 81
   No 22 14 7 33 76
Health Insurance Coverage(a)
   Yes 18 19 10 28 74
   No 26 10 5 37 78
Occupation
   Professional/technical 17 29 11 24 80
   Sales/retail 25 10 7 35 78
   Administrative support/clerical 19 23 10 26 77
   Service professions/ handlers/cleaners 25 9 6 34 74
   Machine/construction/ production/transportation 17 12 5 38 73
   Farm/agricultural/other workers 21 7 5 49 82
Industry
   Agriculture/forestry/ fishing/hunting 15 17 13 35 81
   Mining/manufacturing/ construction/ transportation/utilities 17 16 5 36 75
   Wholesale/retail trade 26 9 6 35 77
   Personal/health/other services 21 17 8 29 75
   Other 18 31 17 10 77
Source: 1996 SIPP longitudinal files using the entry cohort sample of 7,401 low-wage job spells for females. Left-censored spells were excluded from the sample.
Note: All figures are weighted using the longitudinal panel weight.
a. These figures pertain to health insurance coverage from all sources, including coverage through the employer as well as from other sources. We used this variable instead of the employer-based health insurance coverage variable, because data on overall health insurance coverage is available monthly, whereas the employer-based coverage variable pertains only to jobs in progress at the time of the interview. Thus, the employer-based health insurance variable could not always be linked to the job under investigation, which led to a significant number of missing values. However, the subsets of health insurance variables overlap considerably: the source of health insurance coverage was the employer for 80 percent of those with any coverage.
  • White workers are more likely to obtain higher-paying jobs than minority workers. During the mid- to late 1990s, the 12-month cumulative exit rate into higher-wage jobs was 39 percent for white males, compared to 27 percent for African American males, and 24 percent for Hispanic males. A similar pattern holds for females. In addition, more minorities exited into nonemployment, which we have seen is a state from which many return to the low-wage labor market.
  • Education level is strongly associated with entry into the higher-wage labor market for both men and women. Nearly one-half of low-wage job spells for males who completed some college ended in a higher-paying job, compared to 29 percent for those with a high school credential only, and 23 percent for those who did not complete high school. Differences in cumulative exit rates by education level are even larger for females (ranging downward from 36 percent for college graduates to 9 percent for high school dropouts). Correspondingly, rates of exit into nonemployment substantially decreased with education level.
  • Those with health limitations tend to have poor spell-related outcomes. Workers with health problems are likely to exit their low-wage jobs into nonemployment, and only a small percentage exit directly into higher-wage jobs. Thus, it is not surprising that our previous subgroup analyses found that those with health limitations are at particular risk of poor labor market outcomes.
  • Entry into higher-paying jobs is less prevalent for lower-income households than for wealthier ones. Within a year after job start, about 27 percent of female sample members in households with incomes more than twice the poverty level experienced exits into high-wage employment, compared to only 12 percent for females in households with incomes below the poverty level. Consistent with these results, we find poorer spell outcomes for females in single-parent households than for females in other types of households. However, as has been the case throughout our study, there is considerable diversity in spell outcomes within household income groups; for example, nearly 30 percent of females in the wealthiest households exited their low-wage job spells into nonemployment, and 21 percent exited their jobs into another low-wage job.
  • Job quality matters: those with better jobs tend to have more positive spell outcomes than those in lower-quality jobs. Those whose initial jobs offer higher hourly wages, more work hours, and health benefits are more likely to move into higher-paying jobs than those in lower-quality jobs. For example, during the mid- to late 1990s, 29 percent of female workers with available health insurance coverage entered high-wage employment, compared to only 15 percent of female workers without this fringe benefit. The corresponding figures for males are 40 percent and 27 percent, respectively.
  • Entry rates into higher-paying jobs are much higher for the self-employed than for jobholders. For example, nearly two-thirds of male business owners in our sample became higher-wage workers within one year, compared to only 31 percent of jobholders. These findings are consistent with earlier results that the wages of self-employed workers grow substantially faster than those of other workers, even though they start their jobs with lower wages.
  • Those in professional or technical occupations experience the most movement into higher-wage employment. Among males, those in sales occupations experience the next best spell-related outcomes, and those in service occupations experience the worst ones. Among females, those in clerical positions perform nearly as well as those in professional positions, although there are few differences in performance across those in other occupations. These results are identical to those found in our previous subgroup analyses.

c. Duration of Employment Spells

The ordering of subgroups for those with the longest to shortest employment spells (of any wage type) are similar to the ordering of subgroups discussed above. This occurs because subgroups most likely to exit into higher-wage employment were also those least likely to exit into nonemployment. Consequently, subgroups that tended to obtain higher-paying jobs also tended to have the longest employment spells. The life table results for employment spells are presented in Tables E.5 and E.6, which also show log-rank statistics to test differences in hazard rate distributions across subgroup levels. Many of the subgroup differences are statistically significant.

Endnotes

(45) This job mobility, however, is not necessarily a negative result, because as discussed in the previous two chapters, among workers who were continuously employed during the follow-up period, those who switched jobs tended to have more positive labor market outcomes than those who remained with their initial employers. Thus, it appears that job mobility is an avenue for wage growth for some low-wage workers.

(46) The log-rank statistic compares the actual to expected monthly hazards, where the expected hazards are calculated under the null hypothesis that the monthly hazard rates are the same for each level of the subgroup. The log-rank statistic has a chi-squared distribution with the degrees of freedom equal to one less than the number of life tables being compared.

(47) The mean spell lengths pertain to those observed during the panel period, including the right-censored spells. Thus, the figures are shorter than the ultimate mean lengths of the spells. The spell durations for left-censored spells include the time spent in the spell during the prepanel period.

(48) We did not include left-censored spells when examining the durations of low-wage job and employment spells, because most of these spells ended during the panel period. Thus, the inclusion of the left-censored spells would not provide any new information.

View full report

Preview
Download

"report.pdf" (pdf, 1.02Mb)

Note: Documents in PDF format require the Adobe Acrobat Reader®. If you experience problems with PDF documents, please download the latest version of the Reader®