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August 6, 2004

Effects of Job Changing on Payroll Survey Employment 

Trends 

Background

Differences in employment trends between the Bureau of Labor Statistics (BLS) 

household and payroll employment series over the past several years have given rise 

to a number of theories about the source of the differences. One theory is that the rate 

at which workers change jobs may have a significant influence on measured 

employment growth in the payroll survey (also known as the Current Employment 

Statistics or CES), but not the household survey (the Current Population Survey or 

CPS). Because CES is a count of jobs not workers, if workers change jobs within the 

payroll survey reference period, both jobs are counted. Because CPS is a count of 

persons, this phenomenon does not affect that survey’s estimates. If job changer rates 

are steady over time, this effect would raise the level of the payroll employment 

series, but not affect the trends. If the job changer rate is variable however, especia lly 

if it is cyclically sensitive, it could affect reported job growth trends from the payroll 

survey in a way that is not mirrored by the household survey. This effect might then 

help explain some of the recent divergences between the household and payroll 

survey employment trends. Specifically the CES grew faster than the CPS during the 

rapid expansion period of the mid-to-late 1990s, and the CES has shown slower 

growth than the CPS since the last official business cycle peak in March 2001. If job 

changer rates increase during expansionary periods and decline during recessionary 

and slow growth times, the job changer effect may explain some of the apparently 

cyclical nature of CES and CPS divergences. 

As an example of how this phenomenon could work, consider that if a worker is 

employed by a firm with a weekly pay period and leaves in the middle of the week to 

immediately start work at another firm with a weekly payroll, both of his jobs would 

be counted by the payroll survey. If on the other hand, the worker leaves the first 

employer at the end of the week, and goes to work for the second employer at the 

beginning of the next week, he will not be double counted. He will be counted at the 

first job in month one and at the second job in the following month. If there are more 

workers changing jobs during expansionary periods than during recessionary periods, 

the reported payroll survey employment trends will be affected by this phenomenon. 

There are no data available to indicate how frequently workers change jobs within 

payroll periods, as opposed to between pay periods; however, there are data on job 

changing rates available from the household survey which can be used to approximate 

the possible effect of job changing rates on payroll survey employment trends. 

The source of the job changer series is a question in the monthly CPS interview 

which asks: “Last month, it was reported that you worked for (name provided by 

respondent in previous month). Do you still work for (name provided by respondent 

in previous month)?” The phrase “at your main job” is tagged onto the end of the 
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question for persons who report being multiple job holders during the week of the 

12th of the month. The question is asked only of persons who report being employed 

in consecutive months. The job changer series is available only back to February 

1994, when the above question was added to the CPS interview.

Using this information, BLS has completed preliminary research into possible job 

changer effects on the payroll survey employment trends; results are presented here. 

Additional research is also underway. Although results are not yet available from the 

second phase of the research, the approach is briefly described in this paper, along 

with results from the first stage research. 

An Initial Method for Estimating Job Changer Effects

The first method of estimating the effect of job changing on the CES employment 

trends uses the job change rates from the CPS to make a rough estimate of this 

potential effect. The method is rough because there is no hard information about how 

frequently workers change jobs within payroll reference periods as opposed to 

between payroll reference periods. It is mainly when workers change jobs within 

payroll reference periods that the potential for counting both jobs exists. There could 

also be some effect if a worker changes between reference periods, but is still on the 

payroll of the first employer because he is in a paid leave status at the first job for 

some period of time after starting the new job. Again, as with the first issue, there is 

no hard data on the extent of this phenomenon. The approach and results presented 

here are similar to the method used by researchers at the Council of Economic 

Advisors to estimate a job changer effect on the payroll employment series.

The basic approach was to adjust the published CES total nonfarm employment series 

using CPS job changer data, along with CES length of pay period information, and 

assumptions about the probability of a worker appearing on two payrolls within one 

pay period. The CPS job changer rate indicates how many workers change jobs from 

one month to the next; however the shorter the pay period, the less likely that the job 

change occurred within the payroll survey reference period, which is defined as the 

pay period that includes the 12th of each month. For example, if a worker is on a 

weekly pay period, the method used here assumes a one in four chance that he 

changed jobs during the reference week. If the pay period is monthly the assumption 

is that there is a 100% chance.

The length of pay period distributions for the CES sample members and subsequent 

adjustment to the CPS job changer rate are as follows:

Length of pay period Frequency 

in CES 

sample

Probability of change 

within reference 

period

Weighted 

average

calculation

Weekly 45% .25 .11

Bi-weekly or semi-monthly 43.4% .50 .22

Monthly 11.6% 1.0 .12

Total 100% 45%
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The next step in the process was to adjust the CES published employment series, 

using the following calculation for each month to derive a monthly time series:

Adjusted CES Employment = published CES employment level –((.45) * (CPS job change rate) 

* (published CES employment level))

Results 

The calculations to derive an adjusted nonfarm employment series were done both 

directly at the total nonfarm level and at the industry sector level with the results 

aggregated to form an estimate for total nonfarm. Both methods yielded similar results, 

although the industry specific method generated a more variable series, as expected 

because the CPS job changer rates are more variable at industry levels than at the total 

nonfarm level.

A comparison of the published total nonfarm employment series with the job changer 

adjusted series is shown on chart 1 for February 1994 through June 2004. Adjusting for 

job changers lowers the overall level of the nonfarm employment series because it 

removes the assumed double count of workers who changed jobs during the payroll 

reference period. The adjusted series however shows the same overall trend as the 

published nonfarm employment series, as shown by chart 1 below (please see Appendix 

A for the data series).

Chart 1 - CES Published Employment and CES Adjusted for CPS Job Changer 

Rate (Seasonally Adjusted)

110,000

115,000

120,000

125,000

130,000

135,000

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

(Employment, in thousands)

Payroll 

Published 

Employment

Payroll Adjusted 

for CPS Job 

Changer Rates

Payroll Adjusted for CPS Job Changer Rates directly at the TNF level. Payroll Adjusted from Summed Industries, 

which accounts for industry specific information and sums to TNF, is available only from 1999 forward.

Payroll Adjusted 

from Summed 

Industries

In comparing specific time periods, the employment change measured by the published 

series differs somewhat from the adjusted series. The amount of the difference depends

on the time period referenced. Table 1 shows several comparison points coinciding with 

business cycle and employment series peaks and troughs. The job changer adjusted 

series gives a slightly different picture of the trends during the most recent recession and 
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for the time period after the recession, but does not change the overall trends presented by 

the published nonfarm employment series. 

Table 1: Comparison of published nonfarm employment series changes with series 

adjusted for job changer effects

Numbers in thousands

Reference period Seasonally adjusted 

total nonfarm 

employment change

as published

Seasonally adjusted 

total nonfarm 

employment change 

after estimated 

adjustment for job 

changers

Difference

Business cycle peak 

to trough: March 

2001-November 

2001

-1,636 -1,516 120

Business cycle peak 

to current: March 

2001 –June 2004

-1,267 -1,016 251

Business cycle 

trough to current:

November 2001 –

June 2004

369 500 -131

Employment series 

peak to trough: 

March 2001 –

August 2003

-2,718 -2,383 335

Employment series 

trough to current: 

August 2003 – June 

2004

1,451 1,367 84

The largest effect is in the measurement of change from the employment series peak in 

March 2001 to its trough in August 2003. The published series shows a decline of 2.7 

million while the adjusted series shows a decline of 2.4 million.

The CES/CPS Gap

In terms of the CES/CPS employment series gap that emerged most prominently 

following the March 2001 business cycle peak, adjusting for job changer rates in the 

payroll survey closes the gap only slightly for a short period up until 2002. 

Overall, using the adjusted CES series does not help explain the gap of the mid to later 

1990s when published CES data were showing stronger growth than the CPS 

employment series, as indicated by table 2 below.
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Table 2: Comparison of nonfarm employment series changes with series adjusted for job 

changer effects

Numbers in thousands

Reference 

period

Seasonally 

adjusted total 

nonfarm 

employment 

change, as 

published

Seasonally 

adjusted total 

nonfarm 

employment 

change, after 

estimated 

adjustment for job 

changer effects

Published 

payroll total 

nonfarm 

employment 

change less 

CPS adjusted 

employment 

change

Adjusted total 

nonfarm 

payroll 

employment 

change less 

CPS adjusted 

employment 

change

February 1994-

January 1996

5,527 5,849 2,031 2,353

January 1996 –

January 1998

6,437 6,331 -748 -854

January 1998 –

January 2000

6,101 5,923 1,244 1,066

February 1994 –

March 2001

19,842 20,034 2,941 3,133

As a summary view, Chart 2 shows a comparison of the CES adjusted for job changer 

rates against the CPS employment series smoothed and adjusted to CES scope from 1994 

to the present. The chart illustrates that overall, adjusting for job changer effects is not a 

major factor in explaining the CES/CPS gap.

Chart 2 - Household and payroll survey employment, seasonally adjusted, 1994 - 2004

100000

105000

110000

115000

120000

125000

130000

135000

140000

145000

150000

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

Employment, in thousands

Household 

Survey

Payroll Survey

Adjusted 

Household 

Survey

Payroll Survey 

Adjusted for Job 

Changer Rates

NOTE: The household series presented here has been smoothed for population control revisions. The “adjusted” household 

series has been smoothed for population control revisions and adjusted to an employment concept more similar to the payroll 

survey. The "adjusted" payroll series is derived by applying job changer rates supplied by the household survey to the original 

payroll series. Shaded area indicates recession.

SOURCE: Bureau of Labor Statistics, August 6, 2004.
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Limitations of the Research

The premise about the effect of job changing on CES employment data rests with the 

assumption that large numbers of workers are changing jobs within the payroll survey 

reference period. There is no hard data to indicate how frequently workers change jobs 

within as opposed to between reference periods. There is no information available on 

how often workers’ job changes are associated with changes in pay period lengths; for 

example a worker in a weekly payroll job moving to a monthly payroll job. The 

assumption in this research was that workers always stay within the same pay frequency. 

In other words, workers on a weekly payroll will move to another job with a weekly pay 

period. If other assumptions are made, results change somewhat.

Additional Research

BLS also is exploring another method to measure potential job changer effects on the 

payroll survey employment data. This second approach uses regression analysis to 

approximate the extent to which the nonfarm payroll employment series is affected by the 

job changer effect. An advantage of this approach is that it is not necessary to make 

assumptions about the likelihood of workers changing jobs within the payroll survey 

reference period. These assumptions are a major limitation in the initial method 

described above. While the regression work is ongoing, early indications are that it 

produces similar results to those attained from the initial research presented above.
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Appendix A

Date

Job Changer 

Rate

Rate Adjusted for 

Length of Pay 

Period*

Payroll Emp Adj 

for Job Changer 

Rate (All Job 

Holders)

Payroll 

Employment, as 

published (SA)

Feb-94 0.036452876 0.016403794 110817 112665

Mar-94 0.033799499 0.015209774 111412 113133

Apr-94 0.031995026 0.014397762 111856 113490

May-94 0.031837454 0.014326854 112198 113829

Jun-94 0.031342832 0.014104274 112529 114139

Jul-94 0.031625937 0.014231672 112869 114498

Aug-94 0.031142128 0.014013957 113192 114801

Sep-94 0.033830077 0.015223535 113402 115155

Oct-94 0.030070839 0.013531878 113800 115361

Nov-94 0.029681348 0.013356607 114239 115786

Dec-94 0.030711576 0.013820209 114452 116056

Jan-95 0.030551841 0.013748328 114777 116377

Feb-95 0.030558661 0.013751397 114985 116588

Mar-95 0.029732303 0.013379536 115245 116808

Apr-95 0.030813775 0.013866199 115349 116971

May-95 0.031225998 0.014051699 115318 116962

Jun-95 0.031489168 0.014170125 115528 117189

Jul-95 0.02964912 0.013342104 115696 117260

Aug-95 0.029792918 0.013406813 115962 117538

Sep-95 0.029418071 0.013238132 116218 117777

Oct-95 0.031821555 0.0143197 116237 117926

Nov-95 0.031114534 0.01400154 116417 118070

Dec-95 0.028843109 0.012979399 116676 118210

Jan-96 0.028683516 0.012907582 116666 118192

Feb-96 0.028000268 0.01260012 117132 118627

Mar-96 0.028952215 0.013028497 117333 118882

Apr-96 0.029618253 0.013328214 117460 119047

May-96 0.030261557 0.013617701 117750 119376

Jun-96 0.029430415 0.013243687 118062 119647

Jul-96 0.029933201 0.013469941 118260 119875

Aug-96 0.030720398 0.013824179 118418 120078

Sep-96 0.028512755 0.01283074 118753 120296

Oct-96 0.027554882 0.012399697 119039 120534

Nov-96 0.028043777 0.012619699 119301 120826

Dec-96 0.02773806 0.012482127 119493 121003

Jan-97 0.03105374 0.013974183 119538 121232

Feb-97 0.028717425 0.012922841 119956 121526

Mar-97 0.030431909 0.013694359 120174 121843

Apr-97 0.028561711 0.01285277 120564 122134

May-97 0.028204118 0.012691853 120843 122396

Jun-97 0.029395911 0.01322816 121020 122642
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Date

Job Changer 

Rate

Rate Adjusted for 

Length of Pay 

Period*

Payroll Emp Adj 

for Job Changer 

Rate (All Job 

Holders)

Payroll 

Employment, as 

published (SA)

Jul-97 0.029365389 0.013214425 121294 122918

Aug-97 0.029162822 0.01312327 121298 122911

Sep-97 0.031047497 0.013971374 121693 123417

Oct-97 0.031155768 0.014020096 122021 123756

Nov-97 0.031369377 0.01411622 122312 124063

Dec-97 0.03152068 0.014184306 122597 124361

Jan-98 0.029097851 0.013094033 122997 124629

Feb-98 0.030175093 0.013578792 123119 124814

Mar-98 0.029346355 0.01320586 123312 124962

Apr-98 0.029730137 0.013378562 123564 125240

May-98 0.029082285 0.013087028 123997 125641

Jun-98 0.029376421 0.01321939 124182 125846

Jul-98 0.030049112 0.0135221 124264 125967

Aug-98 0.029257874 0.013166043 124659 126322

Sep-98 0.028614929 0.012876718 124914 126543

Oct-98 0.029077499 0.013084874 125077 126735

Nov-98 0.028471808 0.012812313 125393 127020

Dec-98 0.030472044 0.01371242 125618 127364

Jan-99 0.028156527 0.012670437 125862 127477

Feb-99 0.029223233 0.013150455 126191 127873

Mar-99 0.029238311 0.01315724 126313 127997

Apr-99 0.029638909 0.013337509 126667 128379

May-99 0.02910457 0.013097057 126909 128593

Jun-99 0.028891366 0.013001115 127175 128850

Jul-99 0.029022876 0.013060294 127458 129145

Aug-99 0.029438453 0.013247304 127625 129338

Sep-99 0.029331895 0.013199353 127815 129525

Oct-99 0.029680696 0.013356313 128211 129947

Nov-99 0.031479418 0.014165738 128397 130242

Dec-99 0.031186917 0.014034113 128704 130536

Jan-00 0.030774732 0.013848629 128920 130730

Feb-00 0.03011992 0.013553964 129102 130876

Mar-00 0.030621184 0.013779533 129559 131369

Apr-00 0.031223671 0.014050652 129827 131677

May-00 0.032003344 0.014401505 130008 131908

Jun-00 0.031503291 0.014176481 130013 131883

Jul-00 0.02907008 0.013081536 130316 132043

Aug-00 0.029430621 0.013243779 130267 132015

Sep-00 0.02850622 0.012827799 130409 132104

Oct-00 0.030092752 0.013541738 130345 132134

Nov-00 0.029476414 0.013264386 130562 132317

Dec-00 0.027299081 0.012284586 130814 132441

Jan-01 0.030095923 0.013543165 130595 132388

Feb-01 0.030226334 0.01360185 130690 132492

Mar-01 0.027779147 0.012500616 130851 132507

Apr-01 0.028069027 0.012631062 130566 132236
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Date

Job Changer 

Rate

Rate Adjusted for 

Length of Pay 

Period*

Payroll Emp Adj 

for Job Changer 

Rate (All Job 

Holders)

Payroll 

Employment, as 

published (SA)

May-01 0.026941728 0.012123778 130634 132237

Jun-01 0.025823764 0.011620694 130552 132087

Jul-01 0.029007109 0.013053199 130249 131972

Aug-01 0.029727736 0.013377481 130067 131831

Sep-01 0.028581285 0.012861578 129872 131564

Oct-01 0.027074653 0.012183594 129604 131203

Nov-01 0.026076349 0.011734357 129335 130871

Dec-01 0.026377546 0.011869896 129108 130659

Jan-02 0.025825303 0.011621387 128977 130494

Feb-02 0.026605324 0.011972396 128843 130404

Mar-02 0.02639619 0.011878286 128898 130447

Apr-02 0.026125181 0.011756332 128846 130379

May-02 0.025698015 0.011564107 128873 130381

Jun-02 0.027075733 0.01218408 128817 130406

Jul-02 0.026379822 0.01187092 128748 130295

Aug-02 0.024815189 0.011166835 128851 130306

Sep-02 0.024863201 0.01118844 128802 130259

Oct-02 0.025755539 0.011589993 128831 130342

Nov-02 0.024682847 0.011107281 128858 130305

Dec-02 0.024576209 0.011059294 128657 130096

Jan-03 0.025918593 0.011663367 128672 130190

Feb-03 0.023901937 0.010755872 128632 130031

Mar-03 0.024853901 0.011184255 128468 129921

Apr-03 0.024084096 0.010837843 128493 129901

May-03 0.023913123 0.010760905 128475 129873

Jun-03 0.024373211 0.010967945 128435 129859

Jul-03 0.023463561 0.010558602 128443 129814

Aug-03 0.02262208 0.010179936 128468 129789

Sep-03 0.024468738 0.011010932 128426 129856

Oct-03 0.022850262 0.010282618 128608 129944

Nov-03 0.024381428 0.010971643 128600 130027

Dec-03 0.026077867 0.01173504 128509 130035

Jan-04 0.023551167 0.010598025 128814 130194

Feb-04 0.024234877 0.010905695 128856 130277

Mar-04 0.024964682 0.011234107 129162 130630

Apr-04 0.024598317 0.011069243 129504 130954

May-04 0.025718797 0.011573459 129644 131162

Jun-04 0.023784721 0.010703124 129835 131240

* - Rate adjusted for Length of Pay is the Job Changer rate 

multiplied by the probability of any job changer holding two 

positions with different employers across pay periods within the 

same industry (in this case, this is 0.45 for Total nonfarm).