exploring differences in employment between household and establishment data
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Exploring Differences in Employment between Household and Establishment Data. Katharine G. Abraham University of Maryland and NBER John C. Haltiwanger University of Maryland and NBER Kristin Sandusky U.S. Census Bureau James R. Spletzer U.S. Bureau of Labor Statistics - PowerPoint PPT PresentationTRANSCRIPT
Exploring Differences in Employment between Household and Establishment Data
Katharine G. Abraham University of Maryland and NBER
John C. Haltiwanger University of Maryland and NBER
Kristin Sandusky U.S. Census Bureau
James R. Spletzer U.S. Bureau of Labor Statistics
2008 World Congress (May 15, 2008)
Motivation
• Each month, the U.S. Bureau of Labor Statistics releases data on current employment. The data come from two different surveys:
– the Current Population Survey (CPS), also known as the household survey, and
– the Current Employment Statistics survey (CES), also known as the payroll survey or the establishment survey.
• Despite their different definitions, samples, estimation procedures, and concepts, the CPS and CES employment series track well over long periods.
• However, at times, their rates of growth and decline can differ significantly.
CES & CPS data used in previous chart
Adjusted CPS Household Survey
• Published every month by the BLS
• Make the CPS look more like the CES
• Subtract CPS employment not in scope to CES:– Unincorporated self employed (9½ million in 2004)
– Agricultural employment, unpaid family workers, private HH workers, workers on unpaid absences (5 million in 2004)
• Make the CPS on a jobs concept similar to CES:– Add multiple jobholders (7 million in 2004)
CES & CPS data used in previous chart
CES (Establishment Survey)• Monthly sample survey of 160,000
businesses (400,000 worksites)• Designed to measure employment
with industrial and geographical detail
• Employment measures the number of nonfarm payroll jobs
• Reference period is the pay period that includes the 12th of the month
• Employees of all ages are included• Self-employed are excluded• Multiple jobholders are counted for
each job• Agricultural sector and private
household workers are excluded• Workers on leave without pay are
excluded• Employment estimates are
benchmarked annually to universe counts
CPS (Household Survey)• Monthly sample survey of
approximately 60,000 households• Designed to measure employment
and unemployment with demographic detail
• Employment measures the number of employed persons
• Reference period is the week that includes the 12th of the month
• Workers aged >16 are included• Self-employed are included• Multiple jobholders are counted
once• Agricultural sector and private
household workers are included• Workers on leave without pay are
included• Employment estimates are
controlled to estimates of the civilian noninstitutional population
Motivation
• As is evident from the previous chart, employment from the establishment and household surveys had diverging trends during the late 1990s and early 2000s
• During the past 60 years, this late 1990s and early 2000s discrepancy was unprecedented in size and duration
0.98
0.99
1.00
1.01
1.02
1.03
1.04
1.05
1.06
1948 1952 1956 1960 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004
0.98
0.99
1.00
1.01
1.02
1.03
1.04
1.05
1.06
Ratio of establishment survey employment to household survey nonagricultural wage and salary employment, 1948-2004
Motivation
• Although many theories about the recent CPS-CES divergence have been put forth, complete explanations have never been found
– Sampling error– Household population controls– Missed births in the CES– Age minimum (16+) in CPS– Persons with more than two jobs– 2nd civilian jobs of armed forces– Employment of noninstitutional population– Welfare to work programs– Foreign commuters– Undocumented immigrant workers
Motivation
• Other possible explanations for the CPS-CES divergence (continued)
– Worker classification• Measurement error in self-employment
– “Off-the-books” employment• Employers not reporting workers that would be measured as
employed in the CPS
– Marginal employment (informal jobs)• Short duration or low earning jobs that are not reported by
household survey respondents
– Job Changing• If a person changes jobs during the survey reference period,
both jobs would be counted in the CES but only once in the CPS
Motivation
• Our research strategy is to match CPS microdata to UI wage records for the same individuals to learn whether differences in household versus employer reports of individuals’ employment histories can offer an explanation
• Our research today focuses on:– “Off-the-books” nonstandard employment– Marginal (low-earnings) short-duration jobs
• These explanations would need business cycle properties in order to explain the divergence – We believe this is plausible
Measurement Framework
Linked CPS – UI wage records microdata
Individual holds job inUI wage records
Yes No
Individualholds jobin CPS
Yes X1 X2
No X3 X4
Measurement Framework
Number of persons employed in CPS & UI
CPS number of persons employed
X1 + X2
UI wage records number of persons employed
X1 + X3
Difference (CPS - UI) number of persons employed
X2 – X3
Measurement Framework
Linked CPS – UI wage records microdata
Individual holds job inUI wage records
Yes1 Job
Yes2+ Jobs
No
Individualholds jobin CPS
Yes1 Job
Y1 Y2 Y3
Yes2+ Jobs
Y4 Y5 Y6
No Y7 Y8 Y9
Measurement Framework
Number of jobs in CPS & UI
Assume: multiple jobholders in CPS hold (1+m) jobs
multiple jobholders in UI hold (1+n) jobs
m>1, n>1
CPS number of jobs:
Y1 + Y2 + Y3 + m(Y4 + Y5 + Y6)
UI number of jobs:
Y1 + Y4 + Y7 + n(Y2 + Y5 + Y8)
Measurement Framework
Our goal: estimate each of the components underlying the CES-CPS employment trend discrepancy and examine their cyclical properties
For example, (X2 - X3)
X2: employed in CPS but not in UI wage records
“Off-the-books” nonstandard employment
X3: employed in UI wage records but not in CPS
Marginal short duration jobs
“Off-the-books” nonstandard employmentarrangements that are not reported byemployers shrinks in relative importanceduring business cycle expansions
X2 countercyclical
X1 procyclical
Y4 countercyclical
Y5 procyclical
Marginal (low earnings) short duration jobsthat are not reported by household surveyrespondents grow in number duringbusiness cycle expansions
X3 procyclical
Y2 procyclical
Increases in the job-changing rate duringbusiness cycle expansions leads to relativeincreases in employment counts
Y2 procyclical
Measurement Framework
Data: CPS
• Monthly household survey that collects information about the labor force status of those aged 16+
• Survey conducted in person or by telephone
• Approximately 60,000 households interviewed each month, with a single respondent generally reporting for all members of the household
• Households are in the sample for 4 months, out for 8 months, and in for another 4 months
• Survey sample in each month represents the civilian non-institutionalized population
Data: CPS
Vitally important to our research is the ability to match individuals in the CPS to various administrative datasets at the U.S. Census Bureau
Approximately 70-80% (the exact number varies by year) of individuals in the March supplement have what is called a Protected Identity Key (PIK). The PIK is a unique internal Census Bureau identification number for the individual.
Data: UI Wage Records
• Administrative data are necessary to operate the State Unemployment Insurance (UI) programs
– UI provides unemployment benefits to eligible workers who are unemployed through no fault of their own
– In general, UI benefits are based on a percentage of an individual’s earnings over a recent 52 week period
– To determine benefits for UI claimants, States need an individual’s earnings history
– Wage records are the employer-reported administrative data underlying the State UI programs
• Wage records are essentially a quarterly universe of employed persons on nonfarm payrolls
– 3 data elements: SSN, UI number, quarterly earnings
Data: UI Wage Records
• UI wage records “related” to CES employment
– Employers subject to State UI laws are required to file two forms every quarter:
1) Quarterly Contributions Report (QCR)The foundation of the QCEW data, 9 million estabs
2) Quarterly Wage Record (QWR), 136 million employees
– CES employment is benchmarked annually to the QCEW employment counts
• We believe that comparisons of CPS to UI wage records for the same individuals will be potentially informative about reasons for CPS versus CES discrepancy
Data: Analysis Sample
• Census LEHD program has UI wage record data for 17 states from 1996 to present
• CPS restrictions:– Because a quarterly CPS employment variable is needed for an
“apples to apples” comparison to UI wage records, we limit the sample to CPS respondents who responded to the January, February, and March basic CPS
– Because we will be matching CPS microdata to the UI wage records, we limit the sample to CPS respondents with a PIK
– Propensity score methods used to adjust the weights for both of these sample restrictions
• Finally, need to adjust CPS employment series for population adjustments
Data: Analysis Sample
Constructing CPS quarterly employment records
• Individuals who report any wage and salary job over the quarter are categorized as employed in CPS
• Information on multiple jobs held simultaneously and job changes used to categorize people as holding one job or two plus jobs in CPS– Most certain a job change has occurred if question asked
and answered directly, but not always asked– Multiple job question asked every month, but class of
second job asked only in outgoing rotation group– Results displayed for more restrictive of two criteria
Empirical Results
Overall %
Row %
Column %
Individual holds wage & salaryjob in UI wage records
Yes No
Individualholdswage &salary jobin CPS
Yes 52.5% 82.1% 94.4%
11.5% 17.9% 25.9%
No 3.1% 8.7% 5.6%
32.9% 91.3% 74.1%
Empirical Results
Overall %
Row %
Column %
Individual holds wage & salaryjob in UI wage records
Yes: 1 job Yes: 2+ jobs
Individualholdswage &salary jobin CPS
Yes:1 job
83.9% 91.5% 95.7%
7.8% 8.5% 63.5%
Yes:2+jobs
3.7% 45.4% 4.3%
4.5% 54.6% 36.5%
Empirical Results
• Previous two tables show:– Substantial discrepancies in employment status:
• 17.9% of CPS workers not working in UI
• 5.6% of UI workers not working in CPS
– Even larger discrepancies for multiple jobholder status (conditional on working in both datasets):
• 45.4% of MJH workers in CPS not MJH in UI
• 63.5% of MJH workers in UI not MJH in CPS
– These discrepancies are large enough to be relevant for the 1-2% topside employment trend discrepancy between the CES and CPS
Summary & Next Steps
• The results presented are preliminary and should be considered work in progress. We have found:– Substantial discrepancies in employment status and the number
of jobs in a quarter when matching CPS and UI wage records for same people
– We have modeled these discrepancies as “off the books” nonstandard employment measured in the CPS but not in the UI wage records {X2}, and marginal short duration jobs measured in the UI wage records but not in the CPS {X3}
– The off-diagonals are related to characteristics of workers and jobs in ways that we believe make sense (not presented here)
• Our next step is to look at whether the discrepancies move in such a way that they could account for CPS versus CES discrepancies (work in progress)