U.S. Department of Commerce Economics and Statistics Administration

Current

Population

Household Economic Studies

 Reports

Dynamics of Economic Well-Being:

Labor Force, 1991 to 1993

By Paul Ryscavage

C E N S U S B U R E A U P70-48

 August 1995

Introduction transitions in the 1991-93 period. of total turnover actions of 

A concluding section examines all industries. This report examines various

the labor turnover process during dynamic aspects of the Nation’s  Average monthly labor turnover

1991. labor force during the 1991-93 in 1991 was highest for young

period. Although much of this workers age 16 to 24 at 15.8 

period of time was characterized Highlights ( 1.3) percent.

by weak employment growth and (Note: The figures in parentheses Spells of Unemployment high levels of unemployment, mil- signify the 90-percent confidence According to the Bureau of 

lions of persons continued to intervals of the estimates.) Labor Statistics (BLS), the monthmove into and out of the labor ly unemployment rate in the

force and between jobs. Statistics  The median spell length of un- country averaged 6.7 percent in

reflecting these movements can employment in the 1991-93 1991, 7.4 percent in 1992, and

provide important insights into the period was 2.6 ( .1) months, 6.8 percent in 1993. These rates

operation of this country’s labor not significantly different from of unemployment were the highest market and supplement more the comparable 1990-92 esti- they had been since the midtraditional measures of employ- mate. 1980’s. Underlying these estiment, unemployment, wages, and

 Of the men age 25 to 54 who mates, of course, are persons

so on. found full-time jobs in the 1991- who experienced spells of unem-

 The data in this report were 93 period, 23 ( 2.8) percent ployment, some which may have

collected in the Survey of Income were paid less than $215 a lasted only a week or two and othand Program Participation (SIPP), week but another 23 ( 2.6) ers which extended for many

a longitudinal survey which follows percent were paid $600 a week months.

the same persons over a period of or more. In the 1991-93 period, the 

time. Most of the data discussed The proportion of women age median length of a completed here were obtained from the 1991



25 to 54 entering full-time jobs spell of unemployment was 2.6

panel of SIPP and relate to the la- 2 paying $400 a week or more months as is shown in table A. bor market activities of persons rose from about 15 ( 2.4) per- This estimate was not significantly during the October 1990 to Au- cent in the 1984-86 period to 23 different from the median of 2.4

gust 1993 period. ( 3.1) percent in the 1991-93 months for the 1990-92 period

 Previous reports from the period. (presented in a previous SIPP reSIPP (the most recent covering port), but much higher than the

 The proportion of men age 25 the 1990-92 period) have also median of 1.8 months in the to 54 experiencing a full-time dealt with the dynamic aspects of 1987-89 period. The increase, of job change and covered by the labor force.1 In this report, course, reflects the change in the health insurance provided attention is focused on spells of demand for labor between the late through an employer fell from

unemployment, earnings on new 1980’s and early 1990’s. 49 ( 4.2) percent on the old jobs, and changes in health insur- job to 32 ( 3.9) percent on the Table A also shows median

ance status related to persons job new job. spell lengths of unemployment for

2

1  In 1991, persons entering or These median spells of unemployment

See Dynamics of Economic Well-Being: were estimated using a survival data

Labor Force and Income, 1990 to 1992, leaving jobs or transferring jobs analysis technique (See Martina Shea,

Current Population Reports, Household between industries (labor turn- Dynamics of Economic Well-Being: 

Economic Studies, Series P70-40, No- over) averaged 7.5 million or Program Participation, 1990-92, Current

vember 1994; Job Creation During the Population Reports, P70-41, U.S. Bureau

Late 1980’s: Dynamic Aspects of Em- 7.1 percent of average monthly of the Census, Washington, DC: USGployment Growth, Current Population wage and salary employment. PO, January 1995). Spells of unemployReports, Household Economic Studies, ment were identified when respondents

Series P70-27, January 1992; and Spells  Average monthly labor turnover indicated that they had either been lookof Job Search and Layoff... and Their in 1991 in retail trade was ing for work or on layoff an entire month

Outcomes, Current Population Reports, or had been looking for work or on layoff

Household Economic Studies, Series 9.8 percent and this industry and not in the labor force for the entire

P-70-16, RD-2, July 1989. accounted for the largest share month.
2 P70-48

Table A.

Median Duration of Spells of

Looking for a Job or Layoff for

Persons Who Experienced at

Least One Separation from a

Wage and Salary Job by Age,

Sex, and Education: 1991 to 1993

(In months)

Standand

Group Median error

Total 2.6 .10

MEN 2.8 .13

16 to 19 years 2.1 25

20 to 24 years 2.7 .33

25 to 34 years 2.8 .25

35 to 54 years 3.3 .21

55 years or more 3.3 .26

WOMEN 2.3 .15

16 to 19 years 1.7 .15

20 to 24 years 1.9 .21

25 to 34 years 2.7 .32

35 to 54 years 3.0 .28

55 years or more 3.2 .37

EDUCATION 

(age 21 or over)

High school or less 3.1 .11

1 to 3 years of college 2.7 .21

College or more 2.5 .33

various groups of workers. Men

age 35 to 54 experienced a median spell of unemployment of 3.3

months in the 1991-93 period,

while for persons with 4 or more

years of college the median was

2.5 months. Both medians were

higher than their comparable medians in the 1987-89 period (2.5

and 1.6 months, respectively).

Earnings on New Jobs

 Despite the weak demand for

labor and mediocre employment

growth during the years under investigation, the dynamic labor

force data from SIPP indicate that

millions of persons were moving

into jobs—job accessions—and

out of jobs—job separations. The

job accession data, in particular,

provide some insight into one important aspect of the kinds of jobs

the economy was generating during the 1991-93 period, that is, the

amount of the paycheck received

from these jobs.

 Table B shows distributions of

men and women age 25 to 54

who moved into full-time (35 hours

or more a week) wage and salary

jobs in the 1991-93 period by their

weekly earnings on the new period). Among women, 

jobs.3 Average weekly earn- approximately 47 percent of the

ings for the men who entered 4.4 million women moved into

jobs was $459 compared with full-time jobs that paid less than

$306 for women. Similar data $215 a week. It should be refrom earlier SIPP panels for membered that these earnings

the 1987-89 period and represent average weekly earn1984-86 period are also dis- ings received during the first

played.4 month an individual entered a 

job and, therefore, in many cases, One obvious fact in these the averages reflect “entry” level data is that a substantial pro- earnings. portion of the jobs that were

entered in the 1991-93 period The data in table B also 

were paying relatively low show that a significant proportion

amounts (these are earnings of workers, especially among the

before taxes and other deduc- men, found jobs that paid on avertions). Of the 6.3 million adult age $600 or more a week. In the

men moving into full-time 1991-93 period, almost 23 percent

jobs, about 23 percent of of the men found full-time jobs

them received weekly pays of which paid this amount or more.

less than $215 a week (this Consequently, relatively good-paylevel is comparable to the ing jobs were created during this

average poverty threshold of period as well as low-paying jobs.

a three-person family of Another aspect of these data is

$11,189 in the 1991-93 the small proportions of men who

3Some persons may have entered more entered jobs in the $400 to $500

than one job during this period; the data range (9.6 percent) and $500 to

presented here relate to the first job that

was entered. $600 range (8.6 percent) relative

4The data were adjusted for inflation by to adjacent earnings intervals (the

the CPI-U of the BLS and the earnings proportions in these intervals were

intervals are expressed in terms of

1991-93 dollars.Earnings in the 1987-89 not significantly different from one

period were adjusted by using the aver- another). This pattern of job

age of the CPI-U over the October growth for men, that is, jobs pay- 1986-April 1989 period and in the

1984-86 period by the average of the ing low wages and high wages but

June 1983-July 1986 period. few jobs in the mid-wage level,

Table B. Distribution of Men and Women Age 25 to 54

Who Entered Full-Time Wage and Salary Jobs 

by Their Average Weekly Earnings 

(in 1991 to 1993 dollars): 1991 to 1993, 1987 to 1989, and 1984 to 1986

(Numbers in thousands)

Earnings Men Women

intervals 1991–93 1987–89 1984–86 1991–93 1987–89 1984–86

Total 6,314 5,686 5,782 4,373 4,752 5,087

Total (in percent) 100.0 100.0 100.0 100.0 100.0 100.0

Less than $100 4.0 3.0 4.0 9.3 11.9 12.1

$100 to $214 19.3 20.6 19.5 37.9 32.6 37.5

$215 to $299 19.3 17.2 18.4 17.3 19.6 19.8

$300 to $399 16.8 15.8 15.2 12.5 16.2 15.8

$400 to $499 9.6 11.2 11.0 7.5 7.1 5.2

$500 to $599 8.6 8.7 9.5 6.1 5.2 4.2

$600 and over 22.5 23.5 22.4 9.4 7.4 5.4

Mean $459 $498 $480 $306 $299 $269

Standard error $49 $76 $42 $36 $41 $20
P70-48 3

has been evident for many years

and the subject of much research.

 Another dimension of the data

shown in table B concerns the

women’s distributions over time.

While the majority of women moving into full-time jobs over time

have done so in jobs paying less

than $300 a week, upward shifts

in the top-half of the distribution

are observable as well. The proportion of women entering full-time

jobs paying $400 a week or more

rose from about 15 percent in the

1984-86 period to 23 percent in

the 1991-93 period. Changes of

this type have been observed in

wage distributions for women from

other data as well.5

Health Insurance

and Job Change

 Because so many Americans

obtain health insurance through

their own or someone else’s employment, much attention has

focused on the nature of the linkage between jobs and health

insurance coverage. Indeed, a

large part of the rising anxiety

over job security stems from a

concern over the strength of this

linkage.

 With the data from SIPP, it 

is possible to examine the consequences of a job change, whether

it be voluntary or involuntary, on

the health insurance status of

adult men and women. The data

displayed in table C relate to men

and women age 25 to 54 who, at

some time in the 1991-93 period,

left a full-time job and then, after a

period of time, entered a full-time

job. The data show what their

health insurance status was at the

time of both jobs, that is, what

proportion (1) had health insurance in their own name through

their employer or some other

means, or (2) did not have coverage in their own name or had no

coverage at all.

 The data demonstrate that

leaving one job and then entering

5See Paul Ryscavage, “Gender-Related

Shifts in the Distribution of Wages,”

Monthly Labor Review, July, 1994, 

pp. 3-15.

another does jeopardize one’s about by theinteraction of the dehealth insurance coverage if it had mand for and supply of labor.

been obtained through an employ- One of the more specific uses

er. Among adult men, 49 percent of information on labor turnover

of the 3.4 million involved in full- relates to the “costs” associated time job changes had health with this turnover. These costs insurance coverage in their own are frequently thought of as 

name through their employer accruing to the employer (e.g., when they left their job. Upon recruitment, training), but they finding another full-time job, can also be thought of as costs to however, only 32 percent had workers (e.g., lost wages and employer-provided health insur- benefits) and costs to society ance in their own name. (e.g., unemployment compensa-

 For the 1.8 million adult tion, retraining programs).

women involved in full-time job The measurement of labor changes, the comparable propor- turnover is difficult because it in- tions were 46 and 30 percent. volves observing and recording These differences in percentages changes in labor force or job sta- do not necessarily suggest that tus. The BLS measured labor these persons went without health turnover in manufacturing (and to insurance (although no doubt some extent in mining and commany did) since they could have munications) for many years by obtained coverage through some- means of an establishment survey one else’s plan or were only but discontinued it in the early waiting to pick-up coverage from 1980’s because of budgetary their new employer. But the fact cutbacks.6 Since then, motivated remains that job changing in by interest in the job creationthe1991-93 period did involve the job destruction process, various risk of losing one’s health insur- researchers have developed meaance coverage. sures of labor turnover primarily Labor Turnover from data collected in establish-

 The aggregate movement of 6From a survey of establishments, the

persons into and out of jobs and BLS collected data on job accessions

between jobs, or labor turnover, which consisted of new hires, recalls, and

other accessions, as well as job separa- represents an important labor tions which consisted of layoffs, quits, dismarket indicator. In a very broad charges, and other separations. See

sense, it reflects the degree of Carol M. Utter, “Labor Turnover in

Manufacturing: The Survey in Retro- flexibility or fluidity in the market- spect,” Monthly Labor Review, June

place for human labor brought 1982, pp. 15-17.

Table C. Men and Women Age 25 to 54 Who Left Full-Time Jobs 

and Then Entered Full-Time Jobs by Method of Health 

Insurance Coverage at the Time of Leaving and Entering 

Jobs: 1991 to 1993

(Numbers in thousands)

Method of Men Women

coverage Left Entered Left Entered

Total 3,449 3,449 1,846 1,846

Total (percent) 100.0 00.0 100.0 100.0

Covered in own name:

 Employer provided 49.3 32.3 45.7

 Other means 8.8 7.0 3.7

Not own name or none 41.9 60.7 50.7

30.2

5.4

64.4
4 P70-48

ment surveys.7 It is also possible

to estimate labor turnover from the

SIPP (although without the precision of establishment-based data)

for persons by various demographic and economic

characteristics, something which is

more difficult to do with data from

establishment surveys.

 The following sections present

labor turnover estimates for 1991.

The estimates are based on three

possible changes in job status

over two consecutive months as

reported by survey respondents:

(1) a person went from no job in

one month to a job in a specific

industry group in the next

month—a job accession; 

(2) a person went from a job in 

a specific industry group in one

month to no job in the following

month—a job separation; and 

(3) a person went from a job in

one industry group to a job in

another industry group between

the two months—an interindustry

transfer. Obviously, these turnover actions represent an underestimate of the true amount of 

labor turnover because, for 

example, they exclude job

7See, for example, Steve J. Davis and

John Haltiwanger, Gross Job Creation,

Gross Job Destruction, and Employment

Reallocation, Center for Economic Studies: Discussion Paper, U.S. Bureau of the

Census, CES 90-4, February 1990.

changes occurring within a 

month or within an industry.

Turnover in 1991

 Table D displays the labor turnover estimates for pairs of months

covering calendar year 1991.8

The number of turnover actions

(the sum of job accessions, job

separations, and interindustry

transfers, the latter which involve

both a job separation and job accession for the same individual)

between two consecutive months

averaged 7.5 million in 1991 for a

rate of 7.1 percent, or 71 turnover

actions per 1,000 workers. The

proportion of these actions which

were job accessions and job

separations (28 versus 29 percent, and not significantly different

from one another) suggests little

change in wage and salary employment during the year.

8Estimates for 1992 and part of 1993

from the remainder of the SIPP 1991

panel are not presented since the rates of

labor turnover appeared to be downwardly biased. Such a bias might be expected in a longitudinal survey of this type

because of sample attrition and panel

conditioning. In the first instance, persons

who leave the survey are most likely to

be in an out of the labor market; in the

second instance, some persons in the

survey may find that after several interviews the quickest way to get through the

interview is to report little change in job

status. These two survey effects would

be particularly evident in estimates of labor turnover.

 Labor turnover during a year

contains a seasonal component.

As shown in table D, the rate rose

from its January-February level of

5.3 percent to 7.7 percent in the

May-June period. This increase is

associated with improving weather

conditions across the country and

the influx of young workers into

the labor force at the end of the

school year. Job accessions rose

from 30 percent of all job changes

in the January-February period to

43 percent as of the April-May period.

 Labor turnover peaked again in

late summer and early fall. In the

August-September period, the rate

was 8.3 percent. At this time of

year, job separations typically rise

because of the return to school of

young workers. In 1991, the 

rate of turnover continued to 

rise reaching 9.3 percent in the

September-October period, as 

interindustry transfers began to 

increase, accounting for over half

of all the turnover actions for the

rest of the year. Whether or 

not this latter development 

was related to the worsening unemployment situation in that year,

seasonality, or the operation of 

the survey, is a matter for further

investigation.9

Turnover by Industry

 The turnover data in table E

show that the degree of labor

turnover varies by industry group

and is influenced by the kinds of

workers (i.e., their demographic,

skill, and educational backgrounds) employed, economic

conditions, seasonality, and so on.

Retail trade has a relatively high

rate of turnover—almost 

9The Nation’s civilian unemployment rate

averaged 6.9 percent (seasonally adjusted) of the labor force in the fourth

quarter of 1991 compared with 6.5 percent (seasonally adjusted) in the first

quarter. With respect to seasonality, the

increase in interindustry transfers as a

proportion of all turnover actions did not

occur in the latter part of 1992, but the

proportion did decline dramatically as

1992 opened (to levels like those of the

summer of 1991). Regarding possible

survey-related problems, the sudden

growth in interindustry transfers in the latter part of 1991 was also evident in the

data for 1990 from the 1990 SIPP panel.

(Table D. Labor Turnover in 1991 by Month

(Numbers in thousands) Composition of Turnover

Turnover Acces- Sepa- Interindustry

Average Turnover Actions sions rations Transfers RATE

Months Employment Actions (%) (%) (%) (%) (%)

Jan.–Feb. 105,186 5,618 100.0 30.3 40.1 29.5 5.3

Feb.–Mar. 104,805 5,282 100.0 32.6 36.7 30.7 5.0

Mar.–Apr. 105,089 6,068 100.0 41.1 28.2 30.7 5.8

Apr.–May 106,197 6,941 100.0 42.8 22.1 35.9 6.5

May–Jun. 107,099 8,243 100.0 33.4 28.9 37.7 7.7

Jun.–Jul. 107,382 7,559 100.0 35.2 32.6 32.2 7.0

Jul.–Aug. 107,129 6,499 100.0 25.1 35.9 39.0 6.1

Aug.–Sep. 105,982 8,796 100.0 25.1 43.3 31.6 8.3

Sep.–Oct. 105,314 9,833 100.0 23.5 20.9 55.6 9.3

Oct.–Nov. 105,103 8,829 100.0 16.5 24.2 59.3 8.4

Nov.–Dec. 104,473 8,368 100.0 18.1 25.0 56.9 8.0

Dec.–Jan 104,162 8,463 100.0 22.6 23.1 54.4 8.1

Average 105,660 7,542 100.0 28.0 29.4 42.5 7.1
Table E. Average Monthly Labor Turnover in 1991 by Industry Group

(Numbers in thousands)

Composition of Turnover InterIndustry Transfers Turnover Acces- SepaAverage Turnover Actions Group Employment Actions (%)

sions rations Inflow Outflow RATE

(%) (%) (%) (%) (%)

Ag., For., Fish. 1,698 245 100.0 35.1 37.6 13.9 13.5 14.4

Mining 623 38 100.0 18.4 34.2 31.6 13.2 6.0

Construction 4,973 529 100.0 30.4 35.2 16.6 17.6 10.6

Manufacturing 20,863 975 100.0 24.0 30.6 25.2 20.3 4.7

Trans.,Com.,PU 7,463 350 100.0 24.3 25.4 27.4 22.9 4.7

Wholesale Trade 4,421 283 100.0 17.7 25.8 31.1 25.4 6.4

Retail Trade 17,641 1,737 100.0 32.5 30.5 16.4 20.7 9.8

Fin., Ins., RE 6,621 387 100.0 21.4 28.7 26.4 23.3 5.8

Bus. & Rep. Ser. 5,589 712 100.0 24.4 22.3 26.1 27.1 12.7

Personal Services 2,825 330 100.0 29.1 30.3 20.3 20.3 11.7

Enter. & Rec. 1,241 218 100.0 33.9 27.1 17.4 21.6 17.6

Pro. & Rel. Ser. 25,441 1,431 100.0 30.2 30.8 19.4 19.6 5.6

Public Admin. 5,639 270 100.0 23.0 24.4 30.0 22.6 4.8

Table F. Average Monthly Labor Turnover in 1991 for Selected Groups

(Numbers in thousands) Composition of Turnover

Turnover Acces- Sepa- Interindustry Average Turnover Actions sions rations Transfers Groups Employment Actions (%) (%) (%) (%)

RATE

(%)

Age & Sex

Both Sexes, 

 16 to 24 19,366 3,061 100.0 30.3 27.8 41.9 15.8

Men, 

 25 to 54 39,892 1,952 100.0 24.9 27.6 47.5 4.9

Women

 25 to 54 37,172 2,150 100.0 26.7 28.7 44.6 5.8

Both Sexes,

 55+ 10,562 513 100.0 28.5 49.8 21.7 4.9

Education

Both Sexes,

 21 to 29, Col. 6,336 515 100.0 22.3 22.3 55.3 8.1

Men,

 College 

 25 to 54, 11,837 476 100.0 22.2 24.7 53.0 4.0

 High School

 25 to 54, 19,692 1,080 100.0 26.6 28.8 44.5 5.5

P70-48 5

10 percent—and in terms of abso- significantly different from one

lute numbers accounted for the another). Their rates are inlargest share of all turnover ac- fluenced by seasonal changes to

tions. The entertainment and a large extent.

recreation services industry had At the other end of the turn- the highest turnover in 1991—a over spectrum are the industry rate of nearly 18 percent. Both 

groups of manufacturing and industries, of course, represent transportation, communication, sources of employment for miland public utilities. In 1991, lions of younger workers. monthly turnover in these indus-

 Other industry groups with rel- tries averaged 4.7 percent.

atively high turnover rates are the Turnover in public administration

construction industry and the agri- was 4.8 percent (this rate was not

culture, forestry, and fisheries significantly different from the

industries. The rates in these in- rates in manufacturing and transdustries were 10.6 percent and portation, communication, and

14.4 percent, respectively (not public utilities). Many of the industries with relatively low turnover

tend to pay above average

wages.

Turnover by Group

 Table F presents labor turnover

data for various groups of workers

classified by age, gender, and educational attainment. Within these

groups, young workers age 16 to

24 had the highest rate of labor

turnover at 15.8 percent. Adult

men age 25 to 54 have somewhat

lower labor turnover rates than

women of the same age

group—4.9 percent versus 5.8

percent.

 Although older workers age 

55 and over had the same rate 

of labor turnover as adult men—

4.9 percent—the composition of

the turnover actions was different.

Almost 50 percent of the turnover

actions for the older workers were

job separations compared with

only 28 percent for adult men.

 The data also reflect some 

interesting differences in turnover

for college-educated workers.

Adult men with college educations

had a low rate of turnover—

4.0 percent—and the data also

show that over half of their turnover actions consisted of moving

from one industry to another.

Young persons age 21 to 29 with

college educations also exhibited

a similar proportion of interindustry

transfers at that time, but their

overall turnover rate was 8.1 percent—twice as high as that for

adult men with college educations.

This differential represents the

greater intensity of the job search

process on the part of many younger workers who were shopping

for the “right” job in a period of

slack labor demand.

User Comments

The Census Bureau welcomes

the comments and advice of data

users. If you have suggestions or

comments, please write to:

Daniel H. Weinberg

Chief, Housing and Household 

 Economic Statistics Division

U.S. Bureau of the Census

Washington, DC 20233
6 P70-48

Source and Accuracy Statement

Source Of Data (1) Those for whom self, proxy, or probability of selection and applied

imputed responses were obtained adjustments to account for nonin- The SIPP universe is the noninfor each reference month of all terviews.14 stitutionalized resident population eight interviews for the 1991 living in the United States. Field We performed an additional stage panel, and all three interviews for representatives interview eligible of adjustment to longitudinal pereach calendar year; or persons who are at least 15 years son weights to reduce the mean

of age at the time of the interview. (2) Those for whom self or proxy square error of the survey estiNot eligible to be in the survey are responses were obtained for the mates by age, sex, race, and

crew members of merchant ves- first reference month of the inter- ethnicity (Hispanic/non-Hispanic).

sels, Armed Forces personnel view period and responses exist Accuracy of Estimates living in military barracks, institu- for each subsequent month until We base SIPP estimates on a tionalized persons, such as they were known to have died or sample. The sample estimates correctional facility inmates and moved to an ineligible address

may differ somewhat from the nursing home residents, and (foreign living quarters, institutions,

Unite values obtained from administer- d States citizens residing or military barracks). ing a complete census using the abroad. Everyone else is considered non- same questionnaire, instructions, The SIPP sample for the 1991 interview.12 and enumerators. The difference

panel is located in 230 Primary occurs because a sample survey Some estimates are based on Sampling Units (PSUs) each con- monthl estimate is subject to two types y averages from cross-sec- sisting of a county or a group of of errors: nonsampling and sam- tional files. Nonresponse rates for contiguous counties. pling. We can provide estimates the months on the file vary from 8

For the 1991 panel, interviewing of the magnitude of the SIPP percent to 21 percent.

began in February, March, April, sampling error, but this is not true

Some respondents did not re- or May of 1991 for four random of nonsampling error. The next

spond to some of the questions. subsamples, respectively. For the few sections describe SIPP nonTherefore, the overall nonre- remainder of the panel, interviews sampling error sources, followed

sponse rate for some items, for each person occurred every 4 by a discussion of sampling error, especially sensitive income and months for a total of 8 interviews. its estimation, and its use in data

money related items, is higher (One round of interviewing all 4 analysis. than the person nonresponse subsamples is called a wave.) At 13 Nonsampling Variability. We rate. each interview, the reference peri- attribute nonsampling errors to

od was the 4 months preceding Estimation many sources; they include but

the interview month. We are not limited to the following: used several stages of weight

Occupants of about 93 percent of adjustments in the estimation pro-  Inability to obtain information

all eligible living quarters partici- cedure to derive the SIPP about all cases in the sample.

pated in the first interview of the longitudinal person weights. We  Inability or unwillingness on the

panel. For later interviews, field gave each person a base weight part of the respondents to prorepresentatives interviewed only equal to the inverse of his/her vide correct information.

original sample persons and per-  Errors made in collection (e.g. sons living with them. We 11Details on interview-status classification recording or coding the data). followed respondents who moved are in “Weighting of Persons for SIPP

Longitudinal Tabulations,” paper by Jud- Undercoverage. during the panel. The Census Bu-



kins, Hubble, Dorsch, McMillen and Ernst We used quality control and edit reau automatically designated in the 1984 Proceedings of the Survey

noninterviewed h ion, American procedures to reduce errors made ouseholds at the Research Methods Sect

Statistical Association. by respondents, coders, and inter- first wave as noninterviews for 12Details on patterns of nonresponse are viewers.16

subsequent waves.10 in “Weighting Adjustment for Partial Nonresponse in the 1984 SIPP Panel..” paper Undercoverage in SIPP resulted We classified a person as inter- by Lepkowski, Kalton, and Kasprzyk in

viewed for the entire panel and the 1989 Proceeding of the Survey Re- from missed living quarters and

search Methods Section, American Sta- missed persons within sample both calendar years based on the tistical Association.

following two definitions: 11 14 13For more discussion on nonresponse For more details on noninterview adand the existence and control of nonsam- justment for longitudinal estimates, see

pling errors in the SIPP, see the Quality Nonresponse Adjustment Methods for 10Details on nonresponse and Hispanic Profile for the Survey of Income and Pro- Demographic Surveys at the U.S. Bureau

controls are in “SIPP 91: Source and gram Participation, May 1990, by T. Ja- of the Census, November 1988, Working

Accuracy Statement for the Longitudinal bine, K. King and R. Pertoni. Available Paper 8823, by R. Singh and R. Petroni.

Panel File REVISION,” dated October 19, from Customer Services, Data User Ser- 15See footnote 10.

1994 vices Division (301-457–1139) 16See footnote 13.
P70-48 7

households. It is known that un- enable one to construct confi- there are no real differences, it is

dercoverage varies with age, race, dence intervals, ranges that would likely that about 10 erroneous difand sex. Generally, undercover- include the average result of al- ferences will occur. Therefore,

age is larger for males than for possible samples with a known interpret the significance of any

females and larger for Blacks than probability. single test cautiously.

for non-Blacks. Ratio estimation

Approximately 90 percent of the Standard Error Parameters and to independent age-race-sex pop- intervals from 1.645 standard er- Tables and Their Use. ulation controls partially corrects

rors below the estimate to 1.645 for the bias resulting from survey Most SIPP estimates have greater

standard errors above the esti- undercoverage. However, biases standard errors than those obmate would include the average exist in the estimates when per- tained through a simple random result of all possible samples. sons in missed households or sample because we sampled clusmissed persons in interviewed The average estimate derived ters of living quarters for the SIPP.

households have characteristics from all possible samples is or is To derive standard errors at a

different from those of interviewed not contained in any particular moderate cost and applicable to a

persons in the same age-race-sex computed interval. However, for a wide variety of estimates, we

group. Further, we did not adjust particular sample, one can say made a number of approximathe independent population con- with a specified confidence that tions. We grouped estimates with

trols for undercoverage in the the confidence interval includes similar standard error behavior

census.17 the average estimate derived from and developed two parameters

all possible samples. (denoted “a” and “b”) to approxi- Comparability with Other mate the standard error behavior Estimates. Exercise caution Hypothesis Testing. One may of each group of estimates. The when comparing data from this also use standard errors for hy- standard errors we computed from

report with data from other SIPP pothesis testing. Hypothesis these parameters provide an indi- publications or with data from testing is a procedure for distin- cation of the order of magnitude of other surveys. Comparability guishing between population the standard error for any specific problems are from varying sea- characteristics using sample esti- estimate. sonal patterns for many mates. The most common type of

characteristics, different nonsam- hypothesis tested is (1) the popu- Methods for using these paramepling errors, and different concepts lation characteristics are identical ters and tables for computation of

and procedures.18 versus (2) they are different. One standard errors are given in the

can perform tests at various levels Sampling Variability. Standard following sections. To calculate

of significance, where a level of errors indicate the magnitude of standard errors for estimates of

significance is the probability of the sampling error. They also par- persons ever participating or perconcluding that the characteristics tially measure the effect of some sons participating all of two years,

are different when, in fact, they nonsampling errors in response use a = –0.0000483 and b =

are identical. and enumeration, but do not mea- 8,912. The bases for percentages

sure any systematic biases in the Unless noted otherwise, all state- are found in appropriate text

data. The standard errors mostly ments of comparison in the report tables.

measure the variations that oc- passed a hypothesis test at the Standard Errors of Estimated

curred by chance because we 0.10 level of significance or better. Numbers. Approximate sx using

surveyed a sample rather than the This means that, for differences the formula,

entire population. cited in the report, the estimated

absolute difference between pa- s Uses and Computation of x ax2  bx. rameters is greater than 1.645

Standard Errors Here x is the size of the estimate.

times the standard error of the 

Confidence Intervals. The sam- difference. Illustration. As shown in text

ple estimate and its standard error table E, the 1991 SIPP estimates

Note that as we perform more 17 approximately 1.7 million labor More detailed discussions of the population controls are in the SIPP Dynamics tests, more erroneous significant turnover actions occurred in the

of Economic Well-Being: Labor Force differences will occur. For exam- retail trade industry in an average and Income, 1990 to 1992, Report ple, at the 10-percent significance month during 1991. The appropri- P70-40, by Wilfred Masumura and Paul

Ryscavage. level, if we perform 100 indepen- ate “a” and “b” parameters are

18 See footnote 13. dent hypothesis tests in which a = –0.0000483 and b = 8,912
Using the above formula, the approximate standard error is

s

x = (–0.0000483)(1,737,0000)2 + (8,912)(1,737,000) = 123,832

The 90-percent confidence interval is from

1,533,296 to 1,940,704. Therefore, a conclusion

that the average estimate derived from all possible

samples lies within a range computed in this way

would be correct for roughly 90 percent of all samples.

Standard Errors of Estimated Percentages. 

The reliability of an estimated percentage, computed using sample data for both numerator and

denominator, depends on the size of the percentage and its base.

Approximate the standard error by the formula: 

S b (x,p)= (p)(100–p). x

Here x is the total number of persons in the 

base of the percentage and p is the percentage

(0 

p 100).

Illustration. As shown in text table F, the 1991

SIPP estimates that the average monthly labor

turnover rate for men age 25 to 54, was 4.9% in

1991. To find the base for the percentage, use

text table F. In this example, the base is

39,892,000. The appropriate “b” parameter is 

 b = 8,912

Using the above formula, the approximate standard error is

S (x,p)= ( 8,912

39,892,000)(4.9)(100–4.9) = 0.32 percent

The 90-percent confidence interval is from 4.4 to

5.4 percent. Therefore, a conclusion that the average percentage derived from all possible samples

lies within a range computed in this way would be

correct for roughly 90 percent of all samples.

For more information—

Labor Force, 1991 to 1993

Paul Ryscavage

Housing and Household Economic 

 Statistics Division

301-763-8573

Source and Accuracy Statement

Aref Dajani

Demographic Survey Methods Division

301-457-4221

8 P70-48