On the Importance of Measurement

Error in Estimating Displacement and

the Cost of Job Loss:

Lessons using Matched Micro Employer-

Employee Data.

Andrew K. G. Hildreth (UC

Berkeley)

DTI/PSI Workshop, London, September 16h 2005

The Incidence and Cost of Job Loss?

Obtain Correct Estimates

Hardship of Displaced WorkersCosts of Economic

Adjustment

Government Assistance Programs JTPA. WARN

Modelling of Labour Market Adverse

Selection, Wage Structure

International Comparisons

Problem of comparison: unknown if differences in definitions,

data collected, or institutions. [Table 1 here].

The Incidence and Cost of Job Loss?

Paper controls for a number of variations in estimating

displacement and the cost of job loss. Use 2 main data

sources in the US:

Matched Data from the 2 Main Data Sources

Displaced Worker Survey (DWS)Monthly Labor Review/BLS

Unempl. Insurance Records (UI)Quarterly Workforce

Indicators (QWI)/Census

Matched data set from DWS & UIImportance of secure data

centers (CCRDC).

Same Period and Region: California 1991-2000

Displaced Worker Survey (e.g.,

Farber 1993, 1997, 2003)

Displacement Rate 8.4%

3 Year Wage Loss -7.3%

UI Records (e.g., Jacobson, Lalonde, Sullivan

1993)

Displacement Rate 16.2%

3 Year Wage Loss -13.8%

Difference typically found in literature

Conflicting Estimates of Cost and Incidence

DWS – Retrospective Survey Data

Isolate involuntary job lossDifficult concepts (main

job, …)

Recall bias + Measurement

error

Demographic information Limited job history

UI – Longitudinal Administrative Data

Information on employers Definition of job loss

Detailed career history

Improved wage data No demographic information

Which is Correct?

Create a New Matched Data Set

February CPS (DWS) + March CPS + UI Records

Compare Estimates Based on SAME Workers

Eliminate some sources of error (time, geography,

groups)

Focus on Questions of Definition and Measurement

1. Definition and misclassification of displacement

2. Correct costs of job loss for measurement error

Approach here: Unique Match of DWS and UI

Incidence of Job Loss

Most DWS job loss is found in UI (mis-reporting by age)

For matched job loss, discrepancy in timing and type

UI over-counts or DWS under-counts job loss

Cost of Job Loss

DWS wage measurement error (increasing with age)

Effects of definition of job loss in UI

M.E. correction suggests DWS under-states wage loss

Preliminary Results

1. Describe the two data files:

• DWS

• UI Base Wage File

2. Matched Data File

• Creation of matched data

• Incidence and cost of job loss in matched

data

3. Measurement Error and the Cost of job

loss.

Outline of Talk

Bi-Annual Supplement to the Current Population Survey

– Collected January (1984-92, 2002+) or February (1994-

2000)

– Collects information from workers lost their main job due to

plant closing, slack work, or layoffs in past three years

– Collects only information on current job and lost main job

Known measurement and definition problems

– Recall bias, telescoping (Topel 1991)

– Definition of main job (longest high paying job)

– Definition of employer (establishment vs. firm)

Displaced Worker Survey (DWS)

Administrative Data Base

– Contains SSN, SEIN and quarterly earnings since 1991

– Near universe of workers (no self-employed, federal,

military)

– Well-measured earnings (including bonuses and over time)

Restrict and Recode 5% Random Sample

– Restrict minimal firm-size to be 50

– Keep only highest paying job for multiple job holders

– Smooth key-stroke errors in SSN (Abowd & Vilhuber 2004)

– Fix coding errors of SEIN using worker flows

UI Base Wage File (UI-BW)

Missing Information – Cause of Job Transitions

Step 1: impose minimal job tenure

require 6 (16) quarters tenure – job loss in

1993.1 (1995.2)

Step 2: generate ‘mass-layoff’ sample

Mass lay-off = firm size 30% below peak

employment in initial period in year after job loss

Alternatives - 60% drop below peak

- require drop near displacement date

Plant closing - SEIN disappears

Define Job Loss in UI-BW

Step 1: Merge February DWS to March CPS

Match ¾ of rotation groups

1994 (probabilistic), 1996, 1998, 2000 (CPS

identifiers)

Step 2: Transfer SSNs in UI-BW to unique person identifiers

used in CPS (PUIK)

Step 3: Merge February/March CPS file to quarterly

employment histories and mass-layoff information

in 1991-2000 UI-BW

Step 4: Create sub-samples – valid match on job loss and

wages

Match DWS and UI-BW for CA

[Table 2 here]

Compare Matched Samples

[Figure 1 and 2 here]

[Table 3 here].

Accuracy of Information from DWS Job Losers

(Mis) Measurement of Job Loss UI-BW vs. DWS

   Displaceme

nt Rate  Conditional Probability  

Conditional Probability

          UI-BW = 1   DWS = 1

   UI-BW

DWS  

DWS=1

DWS=0  

UI-BW = 1

UI-BW =

0

Overall   0.1620.08

4  0.46

3 0.537   0.892 0.108

Plant Closing   0.081

0.036  

0.325 0.657   0.728 0.148

Correlated Mis-Measurement of Job Loss

   Displacement Rate

Conditional Probability

Conditional Probability

        UI-BW = 1 DWS = 1

   UI-BW

DWS

DWS=1

DWS=0

UI-BW=1

UI-BW=0

Age 20-350.08

10.036 0.413 0.587 0.926 0.074

Age 36-450.04

50.025 0.498 0.502 0.904 0.096

Age 46-640.03

60.023 0.531 0.469 0.826 0.174

No High School0.06

30.033 0.468 0.532 0.895 0.105

High School0.05

90.030 0.449 0.551 0.894 0.106

Beyong High School

0.051

0.027 0.474 0.526 0.885 0.115

Female0.07

40.036 0.431 0.569 0.888 0.113

Male  

0.089

0.048 0.490 0.510 0.895 0.105

White0.13

40.073 0.483 0.517 0.893 0.107

Nonwhite0.03

50.020 0.481 0.519 0.837 0.163

Difference-in-Difference Model Based on UI Wages

Job Loss Indicator is Measured with Error

Measurement Error Correlated With Age

Problem: Have No True Measure of Job Loss

Bound cost of job loss using two available

measures

Estimating the Cost of Job Loss

iidxDw iiiiiuibw ,*,

Step 1: Extend Model of Freeman (1984),

Card (1996) to Mis- Classification Bias

Correlated with Characteristics:

Step 2: Use both DWS indicator and UI

indicator as “true” measure of

displacement respectively to obtain

Mis-Classification Bias in Job Loss Dummy

iidxDw iiiiiuibw ~,~~,

iidxDD iiiii ,*

No Covariates, Random Error

With Covariates, Correlated Error

Attenuation Coefficient of Mis-Classification Bias

)var(),cov( *

0i

ii

DDD

))|(var(

)|(),|(cov **

xDEDxDEDxDED

ii

iiiix

[Table 5 here]

Estimates of ‘True’ Cost of Job Loss

Main Results

DWS understates and UI-BW overstates job loss.

Recall bias in the DWS correlated with age,

previous tenure.

Correlated measurement error in wages and job

loss indicators. Preliminary correction

reduces differences in cost of job loss.Plant-closing

is a ‘better defined’ job loss event.

Summary

• Figure 1: Extent of Measurement Error when a Worker was displaced from their Main Job• because of Plant Closing, Slack Work, or Position Abolished.• Figure 2: Extent of Measurement Error when a Worker was displaced from their Main Job• because of Plant Closing.• 0.000• 0.050• 0.100• 0.150• 0.200• 0.250• 0.300• 0.350• 0.400• 0.450• 0.500• -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8• Years difference• Any displacement• Displacement/valid w.• 0.000• 0.100• 0.200• 0.300• 0.400• 0.500• 0.600• 0.700• -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8• Years difference• Any displacement• Displacement/valid w.• Table 1: Comparing Estimates of Displacement and the Cost of Job Loss Across Various Countries.• Country Data Type Time Displacement Definition Displacement Rate Cost of Job Loss• Britain Survey 1990-96 Job to job displaced 4.7 -0.054• Exit and displaced -0.169• France Administrative 1984-89 Plant closing 4.2 -0.048• Germany Administrative 1984-90 Plant closes in 1 year 6.7 -0.209• Plant closes in 2 years -0.216• Plant contracts 40% in 2 years -0.232• Belgium Administrative 1978-85 Plant contracts 30% in reference year 4.8 -0.090• Denmark Administrative 1980-91 Plant contracts 30% in reference year 6.6 -0.168• Netherlands Administrative 1993-96 Plant contracts 20% in reference year 4.8 -0.003• Plant contracts 30% in reference year 3.8• Plant contracts 40% in reference year 3.5• Canada Administrative 1995 Permanent layoffs 6.1 -0.004• Japan Survey 1995 Management Convenience & Contract Finished 2.7 -0.043• USA Survey 1991-2000 Plant closed, slack work, position abolished 8.1 -0.102• Administrative (CA) 1991-2000 Plant contracts 30% in reference year 20.2 -0.138• Administrative (PA)* 1976-84 Plant contracts 30% in reference year 41.0 -0.352• Notes• Estimates for Britain from Borland, Gregg, Knight, and Wadsworth (1999); estimates for France and Germany from Bender, Dustmann, Margolis, and Meghir (1999);• estimates for Belgium and Denmark from Albaek, Van Audenrode, and Browning (1999); estimates for Netherlands from Abbring, van den Berg, Gautier• van Lomwel, van Ours, and Ruhm (1999); estimates for Canada and Japan from Abe, Higuchi, Kuhn, Nakamura, and Sweetman, (1999); estimates for USA• Survey) from Hildreth, von Wachter, and Weber (2005); estimates for USA (Administrative (CA)) from Hildreth, von Wachter, and Weber (2005); estimates for• USA (Administrative (PA)) from Jacobson, Lalonde, and Sullivan (1993).• * Estimates of displacement for Administrative (PA) are probably inflated because of sample selection on the stayers as a comparison (or control) group.• Table 2: Descriptive Statistics for the Matched March CPS/February DWS - California UI-BW File.• Overall Sample Displaced Sample Displaced Sample Displaced Sample• DWS wage DWS wage/Plant Close• N 5068 603 492 196• Age1 0.397 0.450 0.447 0.399• [0.489] [0.498] [0.498] [0.491]• Age2 0.297 0.289 0.293 0.272• [0.457] [0.439] [0.455] [0.446]• Age3 0.305 0.260 0.260 0.329• [0.460] [0.439] [0.439] [0.471]• Education1 0.382 0.402 0.384 0.380• [0.486] [0.491] [0.487] [0.487]• Education2 0.323 0.348 0.352 0.380• [0.468] [0.477] [0.478] [0.487]• Education3 0.357 0.313 0.317 0.319• [0.479] [0.464] [0.466] [0.467]• Female 0.497 0.440 0.431 0.507• [0.500] [0.497] [0.496] [0.501]• Nonwhite 0.180 0.157 0.140 0.178• [0.384] [0.364] [0.348] [0.384]• Union_t 0.057 0.058 0.080 0.090• [0.075] [0.091] [0.139] [0.189]• Union_t-j 0.089 0.118 0.056• [0.286] [0.323] [0.231]• Job tenure t-j 6.649 6.705 7.065• [7.251] [7.261] [7.503]• Jobs held since 1.571 1.569 1.540• [1.131] [1.103] [0.989]• Displaced 0.119 1.000 1.000 1.000• Plant closure 0.375 0.398 1.000• Slack work 0.402 0.375• Position abolished 0.223 0.227• Ln wage (dws)t 6.110 6.112 6.050• [0.745] [0.766] [0.788]• Ln wage (dws)t-j 6.185 6.089• [0.771] [0.737]• Ln wage (ui-bw)t 4.809 4.860 4.569• [1.722] [1.851] [2.131]• Ln wage (ui-bw)t-j 5.037 4.678• [1.370] [1.313]• CPS/DWS 1994 0.280 0.284 0.315 0.319• CPS/DWS 1996 0.206 0.246 0.242 0.244• CPS/DWS 1998 0.270 0.257 0.250 0.225• CPS/DWS 2000 0.244 0.213 0.193 0.211• Notes:• Standard deviations in parentheses. All wage measures in 1982-84 prices.• Variable definitions:• Age1=1 if an individual's age is equal to or greater than 20 and equal to or less than 35; 0 otherwise.• Age2=1 if an individual's age is equal to or greater than 36 and equal to or less than 45; 0 otherwise.• Age3=1 if an individual's age is equal to or greater than 46 and equal to or less than 64; 0 otherwise.• Education1=1 if an individual's education level was greater than or equal to 31 and equal to or less than 39; 0 otherwise. These are• individuals who did not graduate high school.• Education2=1 if an individual's education level was greater than or equal to 40 and equal to or less than 42; 0 otherwise. These are• individuals with an education where they graduated high school.• Education3=1 if an individual's education level was greater than or equal to 42; 0 otherwise. These are individuals who completed• an education above graduating from high school.• Female=1 if an individual was female; 0 otherwise (male).• Nonwhite=1 if an individual answer that they were not white in a question concerning racial origin; 0 otherwise.• Union_t=1 if an individual responded they were a union member in their current job; 0 otherwise.• Union_t-j=1 if an individual responded they were a union member on their previous job; 0 otherwise.• Job tenure_t-j is a continuous variable indicating the reported years of tenure on the previous job.• Jobs held since is a count variable on the number of jobs held by an individual between current and previous main job.• Displaced=1 if an individual responded in the DWS that they were displaced from their last main job; 0 otherwise.• Plant closure=1 if the individual reported in the DWS that they were displaced for the reason of plant closure; 0 otherwise.• Slack work=1 if the individual reported in the DWS that they were displaced for the reason of slack work; 0 otherwise.• Position abolished=1 if the individual reported in the DWS that they were displaced for the reason of position abolished; 0 otherwise.• Ln wage (dws)t is the natural log of the weekly wage measure from the Febuary CPS for the current job.• Ln wage (dws)t-j is the natural log of the weekly wage measure from the Febuary DWS for the previous main job.• Ln wage (ui-bw)t is the natural log of the weekly wage measure from the UI-BW file for the current job.• Ln wage (ui-bw)t-j is the natural log of the weekly wage measure from the UI-BW file for the previous main job.• CPS/DWS 1994=1 if the observations were from the 1994 DWS matched file.• CPS/DWS 1996=1 if the observations were from the 1996 DWS matched file.• CPS/DWS 1998=1 if the observations were from the 1998 DWS matched file.• CPS/DWS 2000=1 if the observations were from the 2000 DWS matched file.• Table 3: Displacement in the DWS and UI-BW files.• All Displaced• UI-BW• 0 1• DWS 0 0.602 0.202• 1 0.021 0.174• Plant Closing• UI-BW• 0 1• DWS 0 0.753 0.155• 1 0.016 0.077• Table 4: Measurement Error in Displacement for DWS - UI-BW Matched File Individuals.• UI-BW/DWS Displacement* Displacement Rate Conditional Probability Conditional Probability• UI_BW=0 UI-BW=0 UI-BW=1 UI-BW=1 UI-BW Coverage = 1 DWS Coverage = 1• DWS=0 DWS=1 DWS=0 DWS=1 UI-BW DWS DWS=1 DWS=0 UI-BW=1 UI-BW=0• Overall 25.96 0.91 8.73 7.52 0.162 0.084 0.463 0.537 0.892 0.108• Plant Closing 25.96 0.54 5.34 2.64 0.081 0.036 0.325 0.657 0.728 0.148• Age 1 5.85 0.27 4.77 3.36 0.081 0.036 0.413 0.587 0.926 0.074• Age 2 8.16 0.24 2.27 2.25 0.045 0.025 0.498 0.502 0.904 0.096• Age 3 11.95 0.40 1.69 1.91 0.036 0.023 0.531 0.469 0.826 0.174• Education 1 9.40 0.34 3.33 2.92 0.063 0.033 0.468 0.532 0.895 0.105• Education 2 8.04 0.31 3.25 2.66 0.059 0.030 0.449 0.551 0.894 0.106• Education 3 10.27 0.31 2.69 2.42 0.051 0.027 0.474 0.526 0.885 0.115• Female 12.82 0.40 4.19 3.18 0.074 0.036 0.431 0.569 0.888 0.113• Male 13.15 0.51 4.52 4.34 0.089 0.048 0.490 0.510 0.895 0.105• White 20.16 0.78 6.94 6.49 0.134 0.073 0.483 0.517 0.893 0.107• Nonwhite 4.31 0.33 1.82 1.69 0.035 0.020 0.481 0.519 0.837 0.163• Notes• * Note that this is an deflated displacement rate figure. The numbers do not sum to 100 as there is a large number of• individuals who change employer (change in SEIN), but are not displaced according to the JLS definition.• Table 5: Estimates of the Cost of Job Loss, Attenuation Bias, and the 'True' Cost of Job Loss• All Displaced• Assume that the DWS measure for displaced is 'true'.• ψλ ψ0 ψ λχ λ N• No Covariates -0.265 1.010 -0.263 2390• [0.081]• Covariates (no correlation with x) -0.218 1.008 1.007 -0.216 2390• [0.050]• Covariates (correlation with x) -0.218 1.008 1.348 -0.162 2390• [0.050]• Assume that the UI-BW measure for displaced is 'true'• ψλ ψ0 ψ λχ λ N• No Covariates -0.065 0.245 -0.265 2390• [0.024]• Covariates (no correlation with x) -0.076 0.232 0.471 -0.161 2390• [0.021]• Covariates (correlation with x) -0.076 0.232 0.642 -0.118 2390• [0.021]• Plant Closing• Assume that the DWS measure for displaced is 'true'.• ψλ ψ0 ψ λχ λ N• No Covariates -0.241 1.012 -0.238 2311• [0.110]• Covariates (no correlation with x) -0.161 1.012 1.574 -0.102 2311• [0.102]• Covariates (correlation with x) -0.161 1.012 6.825 -0.024 2311• [0.102]• Assume that the UI-BW measure for displaced is 'true'• ψλ ψ0 ψ λχ λ N• No Covariates -0.039 0.347 -0.112 2311• [0.007]• Covariates (no correlation with x) -0.038 0.347 1.114 -0.034 2311• [0.008]• Covariates (correlation with x) -0.038 0.347 1.524 -0.025 2311• [0.008]• Notes• Column headings correspond to the definitions in the text. The number of observations corresponds to all individuals• who were in the February DWS and either recorded no job displacement (DWS=0, UI-BW=0) or a displacement in either• file (DWS=1) or (UI-BW=1).• All wage equations, and linear probability models had the same type and control variables as found in the results• on Table 3.• Dependent variable for all wage regressions was the difference in the log wage from the UI-BW file.