TABLE 9–6 Comparison of Quarterly Earnings and Employment Rates from UI and Survey Data

 

Treatment Earnings ($)

Control Earnings ($)

Treatment Employment Rate (%)

Control Employment Rate (%)

Adult women (4,943; 18,275; 8,916)

Survey data

1,294

1,141

59.2

54.5

UI data

1,048

922

57.6

54.1

Ratio (survey UI)

1.23

1.24

1.03

1.01

Adult men (3,651; 13,329; 6,482)

Survey data

1,917

1,824

65.8

63.5

UI data

1,456

1,398

61.7

60.7

Ratio (survey/UI)

1.32

1.30

1.07

1.05

Female youth (2,113; 9,452; 4,316)

Survey data

951

949

51.3

50.6

UI data

701

700

50.6

51.2

Ratio (survey/UI)

1.36

1.36

1.01

0.99

Male youths without a prior arrest (1,225; 5,009; 2,442)

Survey data

1,556

1,655

65.5

69.3

UI data

1,015

1,103

61.3

63.2

Ratio (survey/UI)

1.53

1.50

1.07

1.10

Male youths with a prior arrest (386; 1,646; 705)

Survey data

1,282

1,531

58.0

61.3

UI data

759

760

52.8

55.0

Ratio (survey/UI)

1.69

2.01

1.10

1.11

 

SOURCE: Kornfeld and Bloom (1999), Tables 1 and 2. Numbers after each panel heading reflect the number of persons represented (4,943 adult women) with the number of person-quarters in the treatment and control groups.

Kornfeld and Bloom (1999) also condition on whether a JTPA participant was receiving AFDC benefits during a particular quarter and find that, while the level of earnings is lower, the discrepancy between survey and UI data is strikingly similar. Survey earnings reports for adult women and female youth are 24 to 34 percent higher than reported UI earnings levels. There was also wide variation across JTPA sites in the size of earnings discrepancies between survey and UI data, but the survey always yielded larger numbers than did the UI data. The “ratio range” was 1.15 to 1.40 for adult women, 1.16 to 1.72 for adult men, 1.16 to 1.76 for female youth and even larger for male youth. Whatever the mechanism is generating these discrepancies, it exists across all 12 geographically diverse JTPA sites.

The dispersion of earnings discrepancies is very large, so the means mask large variations, across earnings reports. We do not know, of course, which measure of earnings more closely resembles the truth. If survey data tend to be more accurate, however, the discrepancies shown in Table 9–7 would be reason



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