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HIGHLIGHTS

(The figures in parentheses denote the 90-percent confidence intervals.)

x Estimates for the 1992 calendar year show that 18.1 (±1.2) million persons were uninsured over

that 12-month period. That estimate was not significantly different than the 1991 calendar year

estimate of 17.4 (±1.1) million uninsured persons. Nine point four (±0.9) million were uninsured

for the full 32-month period from early 1991 to mid-1993.

x Over calendar year 1992, 79.7 (±0.7) percent of all persons had continuous health insurance

coverage over the year; thus, 20.3 (±0.7) percent, or 50.7 (±1.8) million persons, lacked

insurance for at least 1 month. This percentage was not significantly different from the 20.6 (±0.7)

percent who experienced a lapse in coverage over calendar year 1991.

x Over a 32-month period during 1991 to 1993, 73.5 (±0.8) percent of all persons had continuous

health insurance coverage; therefore, 26.5 (±0.8) percent, or 64.0 (±2.0) million persons, lacked

insurance for at least 1 month.

x Young adults (those between the ages of 18 and 24 years old) were the most likely of any age

group to lack insurance for at least 1 month. About one-half, or 48.1 (±3.0) percent, of the

persons of this age group lacked health insurance for at least 1 month during the 32-month

period.

x Work experience has a significant effect on health insurance coverage. Eighty six point seven

(±1.4) percent of persons who worked full-time for the entire period were covered continuously

by health insurance, compared with 72.5 (±5.9) percent for full-period, part-time workers, and

59.9 (±1.7) percent for workers with one or more job interruptions.

x Those who were poor or near poor were less likely to have continuous health insurance

coverage than others. Eighty three point three (±0.8) percent of those with an income-to-poverty

ratio of 2.0 or greater had continuous coverage, compared to 50.3 (±1.8) percent of those with

an income-to-poverty ratio below 2.0.

x Twenty six point five (± 0.8) percent of all persons experienced at least one period of time without

health insurance coverage during the 32-month survey period in 1991 to 1993. Of all observed

spells without health insurance, half lasted for 7.1 months or longer. This estimate was

significantly longer than the 6.0 months of noncoverage for the 1990 to 1992 period.

ACKNOWLEDGMENTS

This report was prepared under the general direction of Kathleen Short, Chief, Poverty and

Wealth Statistics Branch, Housing and Household Economic Statistics Division. The tabulations of

estimates in this report were programmed under the general direction of Angela M. FeldmanHarkins, Chief, Computer Programming and Applications Staff; Caroline Carbaugh programmed

the tabulations on spells without health insurance coverage. Statistical assistance and word

processing assistance were provided by Jean Tash.

Content review was provided by John McNeil, Special Assistant and Carmen DeNavas,

Income Statistics Branch.

Sampling and estimation were performed by Vicki Huggins, Chief, Survey of Income and

Program Participation Branch, Demographic Statistical Methods Division; Tracy James conducted

the sampling review.

Survey design and data operations were coordinated by Enrique Lamas, Chief, Income

Surveys Branch, Demographic Surveys Division.

Data collection activities were carried out by Bureau of the Census field representatives under

the general direction of Field Division.

The staff of the Administrative and Publications Services Division, Walter C. Odom, Chief,

performed publication planning, design, composition, editorial review, and printing planning and

procurement. Cynthia G. Brooks provided publication coordination and editing.






	

	

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)&*+$#$"#&$&"&(  %( $#

U.S. Department of Commerce

Ronald H. Brown, Secretary

David J. Barram, Deputy Secretary

Economics and Statistics Administration

Everett M. Ehrlich, Under Secretary

for Economic Affairs

BUREAU OF THE CENSUS

Martha Farnsworth Riche, Director
HOUSING AND HOUSEHOLD

ECONOMIC STATISTICS DIVISION

Daniel H. Weinberg, Chief

SUGGESTED CITATION

Bennefield, Robert L., Dynamics of Economic Well-Being: Health Insurance, 1991 to 1993

U.S. Bureau of the Census. Current Population Reports, P70-43

U.S. Government Printing Office, Washington, DC, 1995.

For sale by Superintendent of Documents, U.S. Government Printing Office, Washington, DC 20402.

BUREAU OF THE CENSUS

Martha Farnsworth Riche, Director

Bryant Benton, Deputy Director

Paula J. Schneider, Principal Associate

Director for Programs

Nancy M. Gordon, Associate Director

for Demographic Programs

ECONOMICS

AND STATISTICS

ADMINISTRATION

Economics and Statistics

Administration

Everett M. Ehrlich, Under Secretary

for Economic Affairs
Introduction......................................................................................... 1

Highlights ........................................................................................... 1

Estimates of Health Insurance Coverage ........................................................ 3

Comparisons Over Different Time Periods .................................................... 4

Sex, Race, and Hispanic Origin ................................................................ 6

Age ............................................................................................... 8

Years of School Completed .................................................................... 8

Type of Residence and Region ................................................................ 8

Months With Low Income....................................................................... 11

Income-to-Poverty Ratios ....................................................................... 11

Employment Status.............................................................................. 13

Spells of Noncoverage .......................................................................... 14

Education...................................................................................... 15

Age and Employment Status................................................................. 15

Race and Hispanic Origin .................................................................... 15

Residence and Region ....................................................................... 15

User Comments.................................................................................... 16

TEXT TABLES

A. All Persons by Sex, Race, Hispanic Origin, and Health Insurance Coverage:

Calendar Years 1991 and 1992 From the 1991 SIPP Panel .......................... 2

B. All Persons by Sex, Race, Hispanic Origin, and Health Insurance Coverage: 1991

to 1993 .................................................................................... 4

C. All Persons by Sex, Race, Hispanic Origin, and Health Insurance Coverage: 1990

to 1993 .................................................................................... 5

D. All Persons by Age and Health Insurance Coverage: 1991 to 1993 .................. 7

E. All Persons by Years of School Completed and Health Insurance Coverage: 1991

to 1993 .................................................................................... 8

F. All Persons by Residence, Region, and Health Insurance Coverage: 1991 to 1993. 10

G. All Persons by Months With Low Income and Health Insurance Coverage: 1991 to

1993 ....................................................................................... 10

H. All Persons by Income-to-Poverty Ratios and Health Insurance Coverage: 1991 to

1993 ....................................................................................... 11

I. Continuous Health Insurance Coverage of Wage and Salary Workers by Sex, Race,

Hispanic Origin, and Labor Force Status: 1991 to 1993.............................. 13

J. Continuous Health Insurance Coverage of Wage and Salary Workers by Age and

Labor Force Status: 1991 to 1993 ..................................................... 14

K. Spells Without Health Insurance Coverage by Selected Characteristics: 1990 and

1991 Panels............................................................................... 15

iii

Contents
FIGURES

1. Health Insurance Coverage: 1991 to 1993.............................................. 3

2. Health Insurance Coverage by Race and Hispanic Origin: 1991 to 1993............. 6

3. Health Insurance Coverage by Age: 1991 to 1993..................................... 6

4. Health Insurance Coverage by Years of School Completed: 1991 to 1993 .......... 9

5. Health Insurance Coverage by Months With Low Income: 1991 to 1993............. 9

6. Health Insurance Coverage by Income-to-Poverty Ratios: 1991 to 1993 ............. 12

7. Distribution of Spells Without Health Insurance by Spell Length: 1991 to 1993...... 12

APPENDIXES

A. Definitions and Explanations............................................................... A–1

B. Source and Accuracy of the Estimates ................................................... B–1

Symbols Used in Tables

– Represents zero or rounds to zero.

(X) Not applicable.

(B) Base is less than 200,000.

iv
Dynamics of Economic Well-Being:

Health Insurance, 1991 to 1993

INTRODUCTION

This report uses data from the Survey of Income and

Program Participation (SIPP) to examine issues related

to health insurance coverage. It focuses primarily on the

extent to which people are covered by health insurance

over a 32-month period beginning in early 1991. The

source of this information is the 1991 panel of the SIPP,

which contains records for each survey person for whom

a reasonably complete set of data for a 32-month period

was obtained. Efforts were made during the life of the

panel to follow persons that moved to ensure that the

sample remained representative of the noninstitutional

population of the United States.

It should be noted that longitudinal estimates presented here are based on persons who were interviewed in all waves1 of the reference period or for whom

imputed wave information exists.2 Insofar as persons

who left the panel were differentially covered by health

insurance, estimates on months covered across the

panel may be biased. Additionally, there may be a

time-in-sample bias present in the longitudinal estimates.

All demographic surveys, including Current Population Survey (CPS) and SIPP, suffer from undercoverage

of the population. This undercoverage results from

missed housing units and missed persons within sample

households. Compared to the level of the 1980 decennial census, overall CPS and SIPP undercoverage is

about 7 percent. Undercoverage varies with age, sex,

and race. For some groups, such as 20 to 24 year old

Black males, the undercoverage is as high as about 27

percent. The weighting procedures used by the Census

Bureau partially correct for the bias due to undercoverage. However, its final impact on estimates is unknown.

During each SIPP interview, information is collected

on health insurance coverage (along with other information on income, labor force, and program participation)

for each month in the 4-month reference period. It is,

therefore, possible to classify persons by the number of

months over the 32-month period that the person was

covered by one or more types of health insurance. It is

also possible to measure the number of months continuously spent without insurance coverage; that is, spells of

noncoverage.

Health insurance in this report refers to the following

types of coverage:

1. Employer- or union-provided insurance

2. Other privately-purchased health insurance

3. Medicare

4. Military health care

5. Medicaid

HIGHLIGHTS

(The figures in parentheses denote the 90-percent

confidence intervals.)

x Estimates for the 1992 calendar year show that 18.1

(±1.2) million persons were uninsured over that 12-month

period. That estimate was not significantly different

than the 1991 calendar year estimate of 17.4 (±1.1)

million uninsured persons. Nine point four (±0.9)

million were uninsured for the full 32-month period

from early 1991 to mid-1993.

x Over calendar year 1992, 79.7 (±0.7) percent of all

persons had continuous health insurance coverage

over the year; thus, 20.3 (±0.7) percent, or 50.7 (±1.8)

million persons, lacked insurance for at least 1 month.

This percentage was not significantly different from

the 20.6 (±0.7) percent who experienced a lapse in

coverage over calendar year 1991.

x Over a 32-month period during 1991 to 1993, 73.5

(±0.8) percent of all persons had continuous health

insurance coverage; therefore, 26.5 (±0.8) percent, or

64.0 (±2.0) million persons, lacked insurance for at

least 1 month.

x Young adults (those between the ages of 18 and 24

years old) were the most likely of any age group to

lack insurance for at least 1 month. About one-half, or

48.1 (±3.0) percent, of the persons of this age group

lacked health insurance for at least 1 month during

the 32-month period.

1

Sample households within a given panel are divided into four

subsamples of nearly equal size. These subsamples are called

rotation groups and one rotation group is interviewed each month. In

general, one cycle of four interviews covering the entire sample, using

the same questionnaire, is called a ware. 2

A ‘‘missing wave imputation’’ procedure was used for persons

who missed an interview but had completed interviews before and

after the missing wave. See appendix B.

1
Table A. All Persons by Sex, Race, Hispanic Origin, and Health Insurance Coverage: Calendar Years

1991 and 1992 From the 1991 SIPP Panel

Health insurance coverage

Both

sexes Male Female

White

Black

Hispanic

origin1

Not of

Hispanic

Total origin

Not of

Hispanic

origin

1992 CALENDAR YEAR

All persons (in thousands). . . . . . . . . 250 020 121 572 128 448 208 483 188 798 31 237 24 442 225 578

(100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0)

Percent covered by private or

government health insurance:

Less than 12 months ...................... 20.3 22.0 18.6 18.9 16.3 27.9 41.4 18.0

No months . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 8.4 6.2 6.8 5.7 9.9 15.5 6.4

1 to 11 months......................... 13.0 13.7 12.4 12.1 10.6 18.0 25.9 11.6

1 to 4 months. . . . . . . . . . . . . . . . . . . . . . . . 4.2 4.5 3.9 3.9 3.2 5.2 10.2 3.6

5 to 8 months. . . . . . . . . . . . . . . . . . . . . . . . 4.9 5.1 4.7 4.6 4.0 6.8 9.8 4.3

9 to 11 months. . . . . . . . . . . . . . . . . . . . . . . 4.0 4.1 3.8 3.7 3.4 6.0 6.0 3.7

12 months................................ 79.7 78.0 81.4 81.1 83.7 72.1 58.6 82.0

1 to 12 months............................ 92.8 91.6 93.8 93.2 94.3 90.1 84.5 93.6

Percent covered by private health

insurance:

Less than 12 months ...................... 31.2 31.1 31.3 27.7 24.3 52.7 58.9 28.2

No months ............................ 17.2 16.6 17.9 14.6 12.1 33.7 37.5 15.0

1 to 11 months......................... 14.0 14.5 13.4 13.1 12.2 19.0 21.4 13.2

1 to 4 months. . . . . . . . . . . . . . . . . . . . . . . . 5.1 5.4 4.9 4.6 4.0 7.3 10.2 4.6

5 to 8 months. . . . . . . . . . . . . . . . . . . . . . . . 5.2 5.3 5.0 5.0 4.8 6.7 7.1 5.0

9 to 11 months. . . . . . . . . . . . . . . . . . . . . . . 3.6 3.8 3.5 3.5 3.4 5.0 4.1 3.6

12 months................................ 68.8 68.9 68.7 72.3 75.7 47.3 41.1 71.8

1 to 12 months............................ 82.8 83.4 82.1 85.4 87.9 66.3 62.5 85.0

Percent covered by medicaid:

Less than 12 months ...................... 93.1 94.8 91.5 95.0 96.0 81.3 85.9 93.9

No months ............................ 87.8 90.4 85.4 90.5 92.2 70.8 74.0 89.3

1 to 11 months. . . . . . . . . . . . . . . . . . . . . . . . . 5.3 4.4 6.0 4.5 3.7 10.5 12.0 4.5

1 to 4 months. . . . . . . . . . . . . . . . . . . . . . . . 2.4 2.0 2.8 2.2 1.8 4.1 5.4 2.1

5 to 8 months. . . . . . . . . . . . . . . . . . . . . . . . 1.8 1.4 2.0 1.5 1.2 3.6 4.1 1.5

9 to 11 months. . . . . . . . . . . . . . . . . . . . . . . 1.1 1.0 1.2 0.9 0.7 2.7 2.5 1.0

12 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.9 5.2 8.5 5.0 4.0 18.7 14.1 6.1

1 to 12 months............................ 12.2 9.6 14.6 9.5 7.8 29.2 26.0 10.7

1991 CALENDAR YEAR

All persons (in thousands). . . . . . . . . 247 187 120 193 126 994 205 820 187 357 30 878 22 885 224 301

(100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0)

Percent covered by private or

government health insurance:

Less than 12 months ...................... 20.6 22.6 18.7 18.8 16.3 29.9 41.8 18.4

No months . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.0 8.0 6.1 6.6 5.5 8.8 15.6 6.1

1 to 11 months......................... 13.6 14.6 12.5 12.2 10.8 21.1 26.2 12.3

1 to 4 months. . . . . . . . . . . . . . . . . . . . . . . . 4.1 4.5 3.6 3.6 3.1 6.0 9.2 3.5

5 to 8 months. . . . . . . . . . . . . . . . . . . . . . . . 5.2 5.9 4.6 4.6 4.0 8.8 10.5 4.7

9 to 11 months. . . . . . . . . . . . . . . . . . . . . . . 4.3 4.2 4.3 4.0 3.7 6.4 6.5 4.0

12 months................................ 79.4 77.4 81.3 81.2 83.7 70.1 58.2 81.6

1 to 12 months............................ 93.0 92.0 93.9 93.4 94.5 91.2 84.4 93.9

Percent covered by private health

insurance:

Less than 12 months ...................... 31.0 31.2 30.8 27.1 23.8 53.6 59.4 28.1

No months ............................ 16.6 15.9 17.2 14.1 11.6 31.5 36.7 14.5

1 to 11 months......................... 14.4 15.3 13.6 13.0 12.2 22.1 22.7 13.6

1 to 4 months. . . . . . . . . . . . . . . . . . . . . . . . 4.9 5.2 4.7 4.2 3.8 8.8 9.5 4.5

5 to 8 months. . . . . . . . . . . . . . . . . . . . . . . . 5.4 5.9 4.9 4.8 4.6 8.3 8.4 5.1

9 to 11 months. . . . . . . . . . . . . . . . . . . . . . . 4.1 4.2 3.9 3.9 3.9 5.0 4.8 4.0

12 months................................ 69.0 68.8 69.2 72.9 76.2 46.4 40.6 71.9

1 to 12 months............................ 83.4 84.1 82.8 85.9 88.4 68.5 63.3 85.5

See footnotes at end of table.

2
x Work experience has a significant effect on health

insurance coverage. Eighty six point seven (±1.4)

percent of persons who worked full-time for the entire

period were covered continuously by health insurance, compared with 72.5 (±5.9) percent for fullperiod, part-time workers, and 59.9 (±1.7) percent for

workers with one or more job interruptions.

x Those who were poor or near poor were less likely to

have continuous health insurance coverage than others. Eighty three point three (±0.8) percent of those

with an income-to-poverty ratio of 2.0 or greater had

continuous coverage, compared to 50.3 (±1.8) percent of those with an income-to-poverty ratio below

2.0.

x Twenty six point five (± 0.8) percent of all persons

experienced at least one period of time without health

insurance coverage during the 32-month survey period

in 1991 to 1993. Of all observed spells without health

insurance, half lasted for 7.1 months or longer. This

estimate was significantly longer than the 6.0 months

of noncoverage for the 1990 to 1992 period.

ESTIMATES OF HEALTH INSURANCE

COVERAGE

Health insurance coverage is commonly associated

with other life circumstances, such as employment,

retirement, and program participation. As a result, there

exists a strong likelihood that for some segments of the

population health insurance status will change over

time. Through the use of longitudinal estimates, it is

possible to examine the dynamics of health insurance

coverage, and the extent to which persons experience a

lapse in coverage during a given time period.

The 1991 SIPP panel file was used to examine the

number of months persons were covered by health

insurance during a 32-month period. Interviews from this

panel were conducted between February 1991 and

September 1993, allowing examination of health insurance coverage for 2 full calendar years: 1991 and 1992.

During the 1991 calendar year, 79 percent of all persons

had health insurance coverage for the entire year; 21

percent, or 51 million persons, lacked coverage for at

least 1 month. Seven percent, or 17 million persons,

were never covered in 1991. The 1992 calendar year

estimates were similar, showing 80 percent, 20 percent,

and 7 percent, respectively. (See table A and figure 1.)

Continuous

coverage

Figure 1.

Health Insurance Coverage: 1991 to 1993

1991

(12 months)

Lapse in

coverage

Percent

1992

(12 months)

1991 to 93

(32 months)

79.4 79.7 73.5

20.6 20.3 26.5

Table A. All Persons by Sex, Race, Hispanic Origin, and Health Insurance Coverage: Calendar Years

1991 and 1992 From the 1991 SIPP Panel—Con.

Health insurance coverage

Both

sexes Male Female

White

Black

Hispanic

origin1

Not of

Hispanic

Total origin

Not of

Hispanic

origin

1991 CALENDAR YEAR—Con.

Percent covered by medicaid:

Less than 12 months ...................... 93.6 95.2 92.1 95.5 96.4 81.8 86.3 94.3

No months ............................ 88.5 90.7 86.5 91.3 92.9 71.0 74.8 89.9

1 to 11 months. . . . . . . . . . . . . . . . . . . . . . . . . 5.0 4.5 5.6 4.2 3.5 10.8 11.5 4.4

1 to 4 months. . . . . . . . . . . . . . . . . . . . . . . . 2.1 1.9 2.3 1.7 1.5 4.6 4.2 1.9

5 to 8 months. . . . . . . . . . . . . . . . . . . . . . . . 1.8 1.6 1.9 1.5 1.1 3.6 4.9 1.4

9 to 11 months. . . . . . . . . . . . . . . . . . . . . . . 1.2 1.0 1.4 1.0 0.8 2.6 2.4 1.1

12 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 4.8 7.9 4.5 3.6 18.2 13.7 5.7

1 to 12 months............................ 11.5 9.3 13.5 8.7 7.1 29.0 25.2 10.1

1

Persons of Hispanic origin may be of any race. The information on the Hispanic population shown in this report was collected in the 50 States

and the District of Columbia, and therefore, does not include residents of Puerto Rico.

3
Between 1991 and 1993, 74 percent of all persons had

continuous health insurance coverage over the entire

32-month period; 26 percent lacked health insurance for

at least 1 month. (See table B.) Seven percent of all

persons were covered by insurance for 6 months or less

(4 percent lacked coverage for the entire period, and

another 3 percent were covered for 1 to 6 months). Eighty

six percent of those with continuous coverage over the

32-month period were covered by private health insurance; 7 percent were covered by medicaid. The remaining 7 percent represent those covered by medicare, the

military, or a combination of various types of coverage.

Comparisons Over Different Time Periods

The proportion of persons with lapses in coverage is

greater when measured over a longer time period. For

example, proportions of those with lapses in coverage

were similar for calendar years 1991 and 1992; 21 and

20 percent, respectively. However, over the full 32-month

period the proportion of those with a lapse in coverage

increased to 27 percent. (See figure 1.)

Table B. All Persons by Sex, Race, Hispanic Origin, and Health Insurance Coverage: 1991 to 1993

Health insurance coverage

Both

sexes Male Female

White

Black

Hispanic

origin1

Not of

Hispanic

Total origin

Not of

Hispanic

origin

All persons (in thousands). . . . . . . . . . . . 241 955 117 061 124 894 201 822 184 021 30 086 22 221 219 734

(100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0)

Percent covered by private or

government health insurance:

Less than 32 months ...................... 26.5 28.3 24.7 24.6 22.1 36.4 49.5 24.1

No months . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9 4.6 3.2 3.7 3.1 5.0 8.6 3.4

1 to 31 months......................... 22.6 23.7 21.5 21.0 19.0 31.3 40.9 20.7

1 to 6 months. . . . . . . . . . . . . . . . . . . . . . . . 2.6 3.0 2.2 2.5 2.0 3.3 6.9 2.2

7 to 12 months. . . . . . . . . . . . . . . . . . . . . . . 3.5 3.9 3.3 3.2 2.6 4.9 9.0 3.0

13 to 18 months . . . . . . . . . . . . . . . . . . . . . 2.9 3.0 2.8 2.6 2.4 4.0 4.9 2.7

19 to 24 months . . . . . . . . . . . . . . . . . . . . . 5.1 5.2 5.0 4.6 4.3 7.9 8.3 4.7

25 to 30 months . . . . . . . . . . . . . . . . . . . . . 7.4 7.6 7.3 7.0 6.7 10.1 10.9 7.1

31 months. . . . . . . . . . . . . . . . . . . . . . . . . . . 1.0 1.1 1.0 1.0 1.1 1.1 0.8 1.0

32 months................................ 73.5 71.7 75.3 75.4 77.9 63.6 50.5 75.9

1 to 32 months............................ 96.1 95.4 96.8 96.3 96.9 95.0 91.4 96.6

Percent covered by private health

insurance:

Less than 32 months ...................... 37.1 37.0 37.2 33.4 30.2 59.6 65.4 34.3

No months ............................ 12.7 11.9 13.4 10.5 8.4 26.9 29.8 10.9

1 to 31 months......................... 24.5 25.1 23.8 22.9 21.9 32.8 35.6 23.3

1 to 6 months. . . . . . . . . . . . . . . . . . . . . . . . 4.1 4.1 4.2 3.6 3.0 7.1 9.5 3.6

7 to 12 months. . . . . . . . . . . . . . . . . . . . . . . 3.9 4.2 3.7 3.6 3.2 5.7 7.8 3.5

13 to 18 months . . . . . . . . . . . . . . . . . . . . . 2.8 2.9 2.8 2.6 2.5 3.5 3.5 2.7

19 to 24 months . . . . . . . . . . . . . . . . . . . . . 5.2 5.3 5.1 4.9 4.9 7.3 6.1 5.1

25 to 30 months . . . . . . . . . . . . . . . . . . . . . 7.4 7.7 7.2 7.3 7.4 8.1 7.8 7.4

31 months. . . . . . . . . . . . . . . . . . . . . . . . . . . 0.9 1.0 0.9 0.9 1.0 1.1 0.8 0.9

32 months................................ 62.9 63.0 62.8 66.6 69.8 40.4 34.6 65.7

1 to 32 months............................ 87.3 88.1 86.6 89.5 91.6 73.1 70.2 89.1

Percent covered by medicaid:

Less than 32 months ...................... 94.9 96.3 93.5 96.6 97.3 84.2 89.1 95.4

No months ............................ 85.7 88.3 83.2 88.7 90.6 66.1 68.7 87.4

1 to 31 months. . . . . . . . . . . . . . . . . . . . . . . . . 9.2 8.0 10.3 7.8 6.7 18.1 20.4 8.0

1 to 6 months. . . . . . . . . . . . . . . . . . . . . . . . 2.8 2.8 2.7 2.6 2.3 4.2 5.0 2.5

7 to 12 months. . . . . . . . . . . . . . . . . . . . . . . 2.1 1.7 2.6 1.8 1.5 4.2 5.4 1.8

13 to 18 months . . . . . . . . . . . . . . . . . . . . . 1.2 1.0 1.3 1.0 0.8 2.7 2.3 1.1

19 to 24 months . . . . . . . . . . . . . . . . . . . . . 1.5 1.1 1.9 1.2 0.9 3.8 3.8 1.3

25 to 30 months . . . . . . . . . . . . . . . . . . . . . 1.5 1.2 1.7 1.2 1.0 3.2 3.7 1.2

31 months. . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.1

32 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 3.7 6.5 3.4 2.7 15.8 10.9 4.6

1 to 32 months............................ 14.3 11.7 16.8 11.3 9.4 33.9 31.3 12.6

1

Persons of Hispanic origin may be of any race. The information on the Hispanic population shown in this report was collected in the 50 States

and the District of Columbia, and therefore, does not include residents of Puerto Rico.

4
Table C. All Persons by Sex, Race, Hispanic Origin, and Health Insurance Coverage: 1990 to 1993

Health insurance coverage

Both

sexes Male Female

White

Black

Hispanic

origin1

Not of

Hispanic

Total origin

Not of

Hispanic

origin

1991 to 1993

All persons (in thousands) . . . . . . . . . . . . 241 955 117 061 124 894 201 822 184 021 30 086 22 221 219 734

(100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0)

Percent covered by private or

government health insurance:

Less than 32 months ...................... 26.5 28.3 24.7 24.6 22.1 36.4 49.5 24.1

No months . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9 4.6 3.2 3.7 3.1 5.0 8.6 3.4

1 to 31 months......................... 22.6 23.7 21.5 21.0 19.0 31.3 40.9 20.7

32 months................................ 73.5 71.7 75.3 75.4 77.9 63.6 50.5 75.9

1 to 32 months............................ 96.1 95.4 96.8 96.3 96.9 95.0 91.4 96.6

Percent covered by private health

insurance:

Less than 32 months ...................... 37.1 37.0 37.2 33.4 30.2 59.6 65.4 34.3

No months ............................ 12.7 11.9 13.4 10.5 8.4 26.9 29.8 10.9

1 to 31 months......................... 24.5 25.1 23.8 22.9 21.9 32.8 35.6 23.3

32 months................................ 62.9 63.0 62.8 66.6 69.8 40.4 34.6 65.7

1 to 32 months............................ 87.3 88.1 86.6 89.5 91.6 73.1 70.2 89.1

Percent covered by medicaid:

Less than 32 months ...................... 94.9 96.3 93.5 96.6 97.3 84.2 89.1 95.4

No months ............................ 85.7 88.3 83.2 88.7 90.6 66.1 68.7 87.4

1 to 31 months. . . . . . . . . . . . . . . . . . . . . . . . . 9.2 8.0 10.3 7.8 6.7 18.1 20.4 8.0

32 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 3.7 6.5 3.4 2.7 15.8 10.9 4.6

1 to 32 months............................ 14.3 11.7 16.8 11.3 9.4 33.9 31.3 12.6

1990 to 1992

All persons (in thousands). . . . . . . . . . . 235 811 113 681 122 131 198 579 182 646 28 982 18 565 217 246

(100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0)

Percent covered by private or

government health insurance:

Less than 32 months ...................... 25.3 26.6 24.0 23.5 21.2 36.0 48.0 23.3

No months . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 4.3 3.3 3.5 2.9 5.1 10.1 3.3

1 to 31 months......................... 21.5 22.3 20.7 19.9 18.3 31.0 37.8 20.1

32 months................................ 74.7 73.4 76.0 76.5 78.8 64.0 52.0 76.7

1 to 32 months............................ 96.2 95.7 96.7 96.5 97.1 94.9 89.9 96.7

Percent covered by private health

insurance:

Less than 32 months ...................... 35.4 34.8 35.9 31.6 28.7 58.5 63.9 33.0

No months ............................ 11.6 10.7 12.4 9.3 7.6 25.3 28.5 10.2

1 to 31 months......................... 23.8 24.1 23.5 22.3 21.1 33.3 35.4 22.8

32 months................................ 64.6 65.2 64.1 68.4 71.3 41.5 36.1 67.0

1 to 32 months............................ 88.4 89.3 87.6 90.7 92.4 74.7 71.5 89.8

Percent covered by medicaid:

Less than 32 months ...................... 95.3 96.7 94.1 97.0 97.6 85.1 89.5 95.8

No months ............................ 87.7 90.3 85.3 90.7 92.1 68.8 72.2 89.0

1 to 31 months. . . . . . . . . . . . . . . . . . . . . . . . . 7.6 6.4 8.8 6.4 5.5 16.3 17.3 6.8

32 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7 3.3 5.9 3.0 2.4 14.9 10.5 4.2

1 to 32 months............................ 12.3 9.7 14.7 9.3 7.9 31.2 27.8 11.0

1

Persons of Hispanic origin may be of any race. The information on the Hispanic population shown in this report was collected in the 50 States

and the District of Columbia, and therefore, does not include residents of Puerto Rico.

5
Comparisons of estimates over a 32-month period

from the 1991 panel with those from the 1990 panel

show similar patterns of health insurance coverage

between the 1990-92 period and the 1991-93 period.

(See table C.) A slightly lower proportion of persons had

continuous coverage in the later period—the percent

covered for the entire 32-month period dropped from

75 percent in the 1990-92 period to 74 percent from

1991-93. This decrease was primarily due to a decrease

in continuous private health insurance coverage, which

dropped from 65 to 63 percent.

Sex, Race, and Hispanic Origin

Over the 32-month period beginning in February

1991, women were more likely than men to have

continuous health insurance coverage. (See table B.)

Twenty eight percent of all men lacked health insurance

for 1 or more months; the comparable figure for women

was 25 percent. The difference between the percentages of men and women with continuous private health

insurance coverage was not significant. The difference

between men and women in overall health insurance

coverage is partially attributable to differences in economic status. Women are more likely than men to live in

Figure 2.

Health Insurance Coverage by Race

and Hispanic Origin: 1991 to 1993

White, NHO

No months

1–31 months

Percent

Black Hispanic origin

32 months

3.1

19.0

77.9

5.0

31.3

63.6

8.6

40.9

50.5

Months covered

Figure 3.

Health Insurance Coverage by Age: 1991 to 1993

Under 18 18–24

Percent

25–34 65+

1–31 months

32 months

35–44 45–64

No months

3.2

25.8

71.0

5.6

42.4

51.9 65.5

28.8

5.7 4.5 4.5

19.8 16.1

75.7 80.1 99.3

0.7

Months covered

Age

6
families with incomes below poverty3 and are more likely

to participate in means-tested assistance programs.4

Thus, women were more likely than men to take part in

medicaid, both in terms of continuous coverage (6

percent) and coverage for at least 1 month (17 percent).

The comparable figures for men were 4 percent and 12

percent, respectively.

A second factor contributing to the difference in

health insurance coverage between men and women is

age. More women than men are 65 years old and over,

and virtually everyone in that age group is covered by

medicare.

The relationship between race or Hispanic origin and

health insurance was a strong one. The percentages

of persons who spent at least 1 month without health

insurance were 22 percent for Whites (not of Hispanic

origin), 36 percent for Blacks, and 50 percent for

persons of Hispanic origin. (See table B and figure 2.)

Whites were also much more likely than Blacks or those

of Hispanic origin to be covered by private health

insurance. Ninety two percent of all Whites (not of

Hispanic origin) were covered by private health insurance for at least 1 month. The comparable figures for

Blacks and persons of Hispanic origin were about 73

3

In 1993, the official poverty rate was 13.3 percent for males and

16.9 percent for females. See Current Population Reports, Series

P60–188, Income, Poverty, and Valuation of Noncash Benefits: 1993. 4

From the 1990 SIPP panel file, 18.5 percent of all females

participated in means-tested public assistance programs compared

with 14.3 percent of all males.

Table D. All Persons by Age and Health Insurance Coverage: 1991 to 1993

Health insurance coverage

Under 18 years 18 to 24 years

25 to 34

years

35 to 44

years

45 to 64

years

65 years

Total and over

Under 6

years Total

18 to 21

years

22 to 24

years

All persons (in thousands). . . . . . . . . . . 67 420 24 124 24 182 13 480 10 703 42 193 38 240 44 208 25 711

(100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0)

Percent covered by private or

government health insurance:

Less than 32 months ...................... 29.0 27.4 48.1 48.9 47.1 34.5 24.3 19.9 0.7

No months . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 2.2 5.6 5.0 6.4 5.7 4.5 3.8 0.0

1 to 31 months......................... 25.8 25.2 42.4 43.8 40.6 28.8 19.8 16.1 0.7

1 to 6 months. . . . . . . . . . . . . . . . . . . . . . . . 2.8 2.2 4.8 4.0 5.8 3.5 2.5 1.8 0.1

7 to 12 months. . . . . . . . . . . . . . . . . . . . . . . 3.9 3.8 6.6 6.5 6.8 4.7 2.8 2.9 0.1

13 to 18 months . . . . . . . . . . . . . . . . . . . . . 3.4 3.1 5.3 5.7 4.8 3.9 2.3 1.9 0.1

19 to 24 months . . . . . . . . . . . . . . . . . . . . . 6.1 5.7 9.8 11.0 8.2 6.1 4.4 3.4 0.1

25 to 30 months . . . . . . . . . . . . . . . . . . . . . 8.5 9.1 14.1 15.1 12.9 9.0 6.7 5.5 0.3

31 months. . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 1.3 1.8 1.6 2.2 1.6 1.0 0.6 0.0

32 months................................ 71.0 72.6 51.9 51.1 52.9 65.5 75.7 80.1 99.3

1 to 32 months............................ 96.8 97.8 94.4 95.0 93.6 94.3 95.5 96.2 100

Percent covered by private health

insurance:

Less than 32 months ...................... 40.5 43.4 53.7 53.8 53.6 40.0 28.4 26.4 39.5

No months ............................ 17.2 20.0 12.4 11.1 13.9 12.4 9.0 9.8 12.2

1 to 31 months......................... 23.3 23.4 41.3 42.6 39.8 27.6 19.5 16.7 27.3

1 to 6 months. . . . . . . . . . . . . . . . . . . . . . . . 4.5 5.0 7.2 7.0 7.3 4.7 3.1 2.8 3.1

7 to 12 months. . . . . . . . . . . . . . . . . . . . . . . 4.1 4.2 6.2 6.1 6.4 4.2 2.9 2.7 4.5

13 to 18 months . . . . . . . . . . . . . . . . . . . . . 2.8 2.6 4.8 5.0 4.6 3.6 2.1 1.9 2.3

19 to 24 months . . . . . . . . . . . . . . . . . . . . . 4.8 4.1 9.0 10.0 7.7 5.5 4.2 3.5 7.0

25 to 30 months . . . . . . . . . . . . . . . . . . . . . 6.2 6.5 12.5 13.2 11.6 8.1 6.2 5.3 10.3

31 months. . . . . . . . . . . . . . . . . . . . . . . . . . . 0.9 1.1 1.7 1.4 2.2 1.5 0.9 0.5 0.2

32 months................................ 59.5 56.6 46.3 46.2 46.4 60.0 71.6 73.6 60.5

1 to 32 months............................ 82.8 80.0 87.6 88.9 86.1 87.6 91.0 90.2 87.8

Percent covered by medicaid:

Less than 32 months ...................... 91.4 88.0 95.9 96.4 95.1 96.2 97.4 97.3 93.0

No months ............................ 73.8 67.0 85.6 85.7 85.4 88.5 93.0 92.8 89.1

1 to 31 months......................... 17.6 21.0 10.3 10.7 9.7 7.7 4.3 4.4 3.9

1 to 6 months. . . . . . . . . . . . . . . . . . . . . . . . 5.4 5.6 2.4 2.2 2.7 2.2 1.5 1.3 1.3

7 to 12 months. . . . . . . . . . . . . . . . . . . . . . . 3.7 4.7 2.7 2.8 2.6 2.3 1.0 1.2 0.6

13 to 18 months . . . . . . . . . . . . . . . . . . . . . 2.3 2.8 1.7 1.9 1.4 1.0 0.6 0.5 0.4

19 to 24 months . . . . . . . . . . . . . . . . . . . . . 3.0 3.7 2.0 2.1 1.8 1.2 0.6 0.5 0.7

25 to 30 months . . . . . . . . . . . . . . . . . . . . . 3.0 3.9 1.3 1.5 1.1 1.0 0.6 0.8 0.8

31 months. . . . . . . . . . . . . . . . . . . . . . . . . . . 0.2 0.3 0.2 0.2 0.1 0.1 0.1 0.1 0.1

32 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.6 12.0 4.1 3.6 4.9 3.8 2.6 2.7 7.0

1 to 32 months............................ 26.2 33.0 14.4 14.3 14.6 11.5 7.0 7.2 10.9

7
percent and 70 percent, respectively. These estimates

are not significantly different.

Age

Young adults (those between the ages of 18 and 24)

were the most likely of any age group to spend at least

1 month without health insurance coverage. (See table

D.) About one-half (48 percent) of all persons between

the ages of 18 and 24 lacked health insurance for at

least 1 month; 10 percent were covered for less than 7

months.

Generally, for persons 18 years old and over, there

was a positive relationship between age and continuous

health insurance coverage. Continuous health insurance coverage rates for persons by age group from 18

to 24 to 65 years old and over monotonically increased

from 52 percent to 99 percent, respectively. (See figure

3.)

Years of School Completed

Persons completing at least 1 year of college were

less likely to spend at least 1 month without health

insurance coverage than those with lower levels of

educational attainment. (See table E and figure 4.) For

example, about 19 percent of those (18 years old and

over) completing at least 1 year of college were without

health insurance coverage for at least 1 month, compared to 28 percent for those who completed high

school (no college) and 32 percent for those with less

than a high school education.

As for continuous health insurance coverage rates,

those completing high school (no college) and those

with less than a high school education also differed in

their private health insurance and medicaid coverage

rates. Sixty three percent of the high school graduates

(no college) were covered by private health insurance

for each of the 32 months, and 90 percent were covered

by private health insurance for at least 1 month. The

comparable percentages for nonhigh school graduates

were 41 and 73 percent, respectively.

Type of Residence and Region

Persons living in suburban areas5 were more likely to

have continuous health insurance coverage over the

32-month period than persons living in central cities or

outside of metropolitan areas. (See table F.) About

one-fifth (22 percent) of persons living in suburban areas

experienced 1 or more months without health insurance

coverage, compared with 30 percent for both those

5

Refers to portions of metropolitan areas outside of central cities.

Table E. All Persons by Years of School Completed and Health Insurance Coverage: 1991 to 1993

Health insurance coverage Persons 18 years

and over

Years of school completed

Less than

high school

High school,

no college

College, 1 year

or more

All persons (in thousands). . . . . . . . . . . 174 535 35 533 67 239 71 762

(100.0) (100.0) (100.0) (100.0)

Percent covered by private or

government health insurance:

Less than 32 months ...................... 25.5 32.4 28.2 19.4

No months . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 7.0 4.5 2.3

1 to 31 months......................... 21.3 25.5 23.7 17.1

32 months................................ 74.5 67.6 71.8 80.6

1 to 32 months............................ 95.9 93.0 95.5 97.7

Percent covered by private health

insurance:

Less than 32 months ...................... 35.8 59.2 36.7 23.4

No months ............................ 10.9 26.7 9.8 4.2

1 to 31 months......................... 24.9 32.6 27.0 19.2

32 months................................ 64.2 40.8 63.3 76.6

1 to 32 months............................ 89.1 73.3 90.2 95.8

Percent covered by medicaid:

Less than 32 months ...................... 96.2 88.6 97.0 99.2

No months ............................ 90.3 76.3 91.0 96.5

1 to 31 months. . . . . . . . . . . . . . . . . . . . . . . . . 5.9 12.3 6.0 2.7

32 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 11.4 3.0 0.8

1 to 32 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.7 23.7 9.0 3.5

8
living in central cities and those living outside metropolitan areas. Medicaid coverage was more prevalent in

central cities and nonmetropolitan areas. Nineteen percent of central city residents spent at least 1 month with

medicaid coverage, 17 percent for those living outside

metropolitan areas6 and only 10 percent for those living

in suburban areas.

Persons residing in the South and West were more

likely to experience 1 or more months without health

insurance coverage than those living in the Northeast or

Midwest. The percentages of persons with 1 or more

months without health insurance coverage were 31

percent in the South, 30 percent in the West, 21 percent

in the Midwest, and 22 percent in the Northeast7.

Perhaps the higher noncoverage rates in the South and

West can be partially attributed to higher concentrations

of Blacks in the South and persons of Hispanic origin in

the West. These groups had higher noncoverage rates

than Whites (not of Hispanic origin).

6

There was no significant difference in the medicaid coverage rate

of 19 percent for those in the central city and the 17 percent for those

outside metropolitan areas. 7

The percentage for those who live in the South (30 percent) was

not significantly different from the percentage for those who live in the

West (31 percent). There was also no significant difference between

the percentage for those who live in the Northeast (22 percent) and the

percentage for those who live in the Midwest (21 percent).

Figure 4.

Health Insurance Coverage by Years

of School Completed: 1991 to 1993

Less than

high school

No months

1–31 months

Percent

High school,

no college

College, 1 year

or more

32 months

7.0

25.5

67.6 71.8

23.7

 4.5

80.6

17.1

2.3

Months covered

Figure 5.

Health Insurance Coverage by Months With Low Income: 1991 to 1993

Percent

1–31 months

32 months

No months

1.6

12.5

85.9

6.0

40.7

53.2

8.5

51.3

40.2

12.7

57.8

29.5

13.8

53.2

33.0

47.0

41.5

11.5 8.8

24.3

66.9

No months 1–6 7–12 13–18 19–24 25–31 32

Months covered

Months with low income

9
Table F. All Persons by Residence, Region, and Health Insurance Coverage: 1991 to 1993

Health insurance coverage

Central city Suburbs

Outside of

metropolitan

areas Northeast Midwest South West

All persons (in thousands). . . . . . . . . . . 68 726 114 894 58 335 50 029 63 321 78 335 50 269

(100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0)

Percent covered by private or

government health insurance:

Less than 32 months ...................... 30.1 22.4 30.2 22.2 20.8 31.2 30.4

No months . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 3.1 4.9 2.4 2.7 5.4 4.5

1 to 31 months......................... 25.8 19.3 25.3 19.8 18.1 25.9 25.9

32 months................................ 69.9 77.6 69.8 77.8 79.2 68.8 69.6

1 to 32 months............................ 95.7 96.9 95.1 97.6 97.3 94.6 95.5

Percent covered by private health

insurance:

Less than 32 months ...................... 45.1 30.2 41.4 34.3 28.7 42.9 41.5

No months ............................ 16.9 9.1 14.9 11.3 8.6 15.9 14.1

1 to 31 months......................... 28.2 21.1 26.6 23.0 20.1 27.0 27.4

32 months................................ 54.9 69.8 58.6 65.7 71.3 57.1 58.5

1 to 32 months............................ 83.1 90.9 85.1 88.7 91.4 84.1 85.9

Percent covered by medicaid:

Less than 32 months ...................... 91.6 96.8 94.9 93.6 96.2 94.8 94.6

No months ............................ 81.0 89.9 82.9 85.5 88.7 84.5 83.9

1 to 31 months......................... 10.5 6.9 12.1 8.1 7.4 10.3 10.7

32 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4 3.2 5.1 6.4 3.8 5.2 5.4

1 to 32 months............................ 19.0 10.1 17.1 14.5 11.3 15.5 16.1

Table G. All Persons by Months With Low Income and Health Insurance Coverage: 1991 to 1993

Health insurance coverage

No

months

1 low-income month or more

Total

1 to 12 months 13 to 24 months

25 to 31

months

32

Total months

1 to 6

months

7 to 12

months Total

13 to 18

months

19 to 24

months

All persons (in thousands). . . . . 163 907 78 047 45 262 32 634 12 628 14 234 7 806 6 428 8 501 10 051

(100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0)

Percent covered by private or

government health insurance:

Less than 32 months ................ 14.1 52.4 50.4 46.8 59.8 68.9 70.5 67.0 58.5 33.1

No months . . . . . . . . . . . . . . . . . . . . . . 1.6 8.7 6.7 6.0 8.5 13.2 12.7 13.8 11.5 8.8

1 to 31 months................... 12.5 43.7 43.7 40.7 51.3 55.7 57.8 53.2 47.0 24.3

32 months.......................... 85.9 47.6 49.6 53.2 40.2 31.1 29.5 33.0 41.5 66.9

1 to 32 months...................... 98.4 91.3 93.3 94.0 91.5 86.8 87.3 86.2 88.5 91.2

Percent covered by private health

insurance:

Less than 32 months ................ 20.3 72.5 59.1 54.4 71.1 86.3 85.7 87.0 94.6 94.8

No months . . . . . . . . . . . . . . . . . . . . . . 3.9 31.1 12.9 10.9 18.0 37.1 30.7 44.9 63.3 77.7

1 to 31 months................... 16.4 41.4 46.2 43.5 53.1 49.1 55.0 42.0 31.4 17.2

32 months.......................... 79.7 27.5 40.9 45.6 28.9 13.7 14.3 13.0 5.4 5.2

1 to 32 months...................... 96.1 68.9 87.1 89.1 82.0 62.9 69.3 55.1 36.7 22.3

Percent covered by medicaid:

Less than 32 months ................ 98.9 86.3 97.0 97.7 95.3 90.9 93.5 87.8 70.4 44.9

No months ...................... 95.9 64.3 83.2 86.7 74.0 55.6 62.5 47.3 28.5 21.6

1 to 31 months. . . . . . . . . . . . . . . . . . . 3.1 22.0 13.8 10.9 21.3 35.3 31.0 40.5 41.8 23.4

32 months. . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 13.7 3.0 2.4 4.7 9.1 6.5 12.2 29.6 55.1

1 to 32 months. . . . . . . . . . . . . . . . . . . . . . 4.1 35.7 16.8 13.3 26.0 44.4 37.5 52.7 71.5 78.4

10
Months With Low Income

One way to examine differences in economic status

between individuals over time is to characterize those

persons by the number of months in which the person or

family income was below their monthly poverty threshold. As would be expected, persons living above the

poverty line (no low-income months) were much more

likely to have continuous health insurance coverage

than persons who experienced 1 or more low-income

months. Only 14 percent of those above the poverty line

spent 1 or more months without health insurance,

compared with over one-half (52 percent) of those with

1 or more low-income months. (See table G.)

However, the relationship between lack of health

insurance coverage and months with low income is not

a linear one. Those who experienced a moderate number of months (13 to 24 months) in poverty were more

likely to go without health insurance for at least 1 month

than those who experienced a shorter (1 to 12) or longer

(25 or more) number of months in poverty. Sixty nine

percent of those with 13 to 24 low- income months went

without health insurance for 1 month or more, compared

to 50 percent for those with 1 to 12 low income months

and 45 percent for those with 25 or more low income

months. (See figure 5.) The higher health insurance

coverage rates of those with more low-income months is

attributable to their level of medicaid coverage. Seventy

five percent of those with 25 or more low-income months

were covered by medicaid for at least 1 month; 43

percent were covered every month. The comparable

figures for those with 13 to 24 low-income months were

44 and 9 percent, respectively. The group with 13 to 24

low-income months were as likely to be covered by

medicaid for at least 1 month as those with 25 or more

low-income months were likely to be covered by medicaid every month.

Income-to-Poverty Ratios

Income-to-poverty ratios represent another way of

characterizing individuals by their relative economic

status. These ratios are computed by summing the

personal or family income over the entire 32-month

period, and dividing this total by the summed monthly

poverty thresholds. Thus, a ratio of under 1.0 indicates

that an individual’s family income over the 32-month

period was less than the sum of that family’s poverty

threshold over that time. In the 32-month period covered

here, 10 percent of persons had an income-to-poverty

ratio less than 1.0. More than one-half (51 percent) of

these persons lacked continuous health insurance, and

11 percent were not covered at all during the 32-month

period, compared to 24 and 3 percent, respectively, for

all others. (See table H.)

As would be expected, there is a strong correlation

between income-to-poverty ratios and the likelihood of

continuous health insurance. The percentage of persons

Table H. All Persons by Income-to-Poverty Ratios and Health Insurance Coverage: 1991 to 1993

Health insurance coverage

Total

Income-to-poverty ratio

less than 1.0

1.0 to

1.99

2.0 to

2.99

3.0 to

3.99

4.0 to

4.99

5.0 to

5.99

6.0 and

Total over

Less

than .5

.5 to

.99

All persons (in thousands). . . . . . . . . . . 241 955 24 579 6 928 17 651 46 959 50 121 40 960 28 106 18 221 33 008

(100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0)

Percent covered by private or

government health insurance:

Less than 32 months ...................... 26.5 50.8 48.5 51.8 49.0 27.8 17.0 13.3 9.6 6.4

No months . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9 11.4 11.5 11.4 8.3 3.0 1.3 1.2 0.7 0.4

1 to 31 months......................... 22.6 39.4 37.0 40.4 40.8 24.8 15.7 12.0 8.9 6.0

32 months................................ 73.5 49.2 51.5 48.2 51.0 72.2 83.0 86.7 90.4 93.6

1 to 32 months............................ 96.1 88.6 88.5 88.6 91.7 97.0 98.7 98.8 99.3 99.6

Percent covered by private health

insurance:

Less than 32 months ...................... 37.1 93.8 94.6 93.4 65.5 35.7 21.0 16.9 11.9 8.0

No months ............................ 12.7 66.6 75.2 63.2 20.0 5.8 2.2 2.3 1.2 0.7

1 to 31 months......................... 24.5 27.1 19.4 30.2 45.5 30.0 18.7 14.6 10.8 7.3

32 months................................ 62.9 6.2 5.4 6.6 34.5 64.3 79.0 83.1 88.1 92.0

1 to 32 months............................ 87.3 33.4 24.8 36.8 80.0 94.2 97.8 97.7 98.8 99.3

Percent covered by medicaid:

Less than 32 months ...................... 94.9 63.8 56.3 66.7 94.5 98.8 99.6 99.6 99.6 99.9

No months ............................ 85.7 29.8 23.7 32.2 76.0 93.3 96.5 97.6 98.5 98.9

1 to 31 months. . . . . . . . . . . . . . . . . . . . . . . . . 9.2 33.9 32.6 34.4 18.6 5.6 3.1 2.0 1.2 1.0

32 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 36.2 43.7 33.3 5.5 1.2 0.4 0.4 0.4 0.1

1 to 32 months............................ 14.3 70.2 76.3 67.8 24.0 6.7 3.5 2.4 1.5 1.1

11
Figure 6.

Health Insurance Coverage by Income-to-Poverty Ratios: 1991 to 1993

Percent

1–31 months

32 months

No months

11.5 11.4 8.3

3.0 1.3 1.2 0.7 0.4

37.0

40.4 40.8

24.8

15.7

12.0 8.9 6.0

51.5

48.2

51.0

72.2

83.0

86.7 90.4

93.6

0.0–0.49 0.5–0.99 1.0–1.99 2.0–2.99 3.0–3.99 4.0–4.99 5.0–5.99 6.0 and over

Months covered

Income-to-poverty ratios

Figure 7.

Distribution of Spells Without Health Insurance

by Spell Length: 1991 to 1993

0

10

20

30

40

50

Percent

Months without health insurance

1–4 5–8 9–12 13–16 17–20 21–24 >24

12
with health insurance for the entire 32 months rose from

50 percent for those with ratios under 2.0 to 94 percent

for those with ratios of 6.0 and over. Differences in

continuous private health insurance coverage by incometo-poverty ratio are even more dramatic, from 6 percent

for persons with ratios under 1.0 to 92 percent for those

with ratios of 6.0 or more. (See figure 6.) For those with

ratios of 6.0 and over, the percentage of those with

continuous health insurance coverage (94 percent) was

not significantly different from the percentage of those

with continuous private health insurance coverage (92

percent).

Employment Status

The relationship between health insurance coverage

and employment is an important one, given the fact that

such a large proportion of total health insurance is

derived through an employer (either as a primary policyholder or as a dependent). In order to examine the

relationship between health insurance coverage and

employment status, wage and salary workers 18 to 64

years old were separated into three groups.

1. Those who worked full-time for the entire period

2. Those who worked part-time for the entire period

3. Those with one or more job interruptions.

Workers were characterized by their private or government health coverage, their private coverage, and

their own employer-provided coverage. This latter type

of coverage is a subset of private health insurance

coverage.

Eighty seven percent of all full-time, full-period workers were covered by health insurance for the entire

period, and 64 percent were covered through their own

employer-provided plans (table I). There was a significant difference in the continuous health insurance coverage rates of White and Black full-time, full-period

Table I. Continuous Health Insurance Coverage of Wage and Salary Workers by Sex, Race, Hispanic

Origin, and Labor Force Status: 1991 to 1993

[In thousands. Based on workers 18 to 64 years old]

Health insurance coverage

Both

sexes Male Female

White

Black

Hispanic

origin1

Not of

Hispanic

Total origin

Not of

Hispanic

origin

FULL-TIME, FULL-PERIOD WORKERS

All persons . . . . . . . . . . . . . . . . . . . . . . . . 53 232 31 938 21 295 45 610 42 738 5 731 3 868 49 365

(100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0)

Percent continuously covered for 32

months by:

Private or government health insurance ...... 86.7 86.2 87.4 88.0 89.3 76.6 67.0 88.2

Private health insurance.................... 86.0 85.4 86.9 87.4 88.9 75.4 65.5 87.6

Employer-provided health insurance ......... 64.3 67.6 59.4 65.4 66.5 57.7 48.9 65.5

PART-TIME, FULL-PERIOD WORKERS

All persons . . . . . . . . . . . . . . . . . . . . . . . . 5 092 1 140 3 952 4 544 4 346 328 242 4 850

(100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0)

Percent continuously covered for 32

months by:

Private or government health insurance ...... 72.5 61.5 75.6 75.2 76.5 39.9 52.0 73.5

Private health insurance.................... 70.3 56.0 74.5 73.2 74.4 38.5 49.1 71.4

Employer-provided health insurance ......... 21.4 29.6 19.1 22.1 22.3 21.0 26.3 21.2

WORKERS WITH ONE OR MORE JOB INTERRUPTIONS

All persons . . . . . . . . . . . . . . . . . . . . . . . . 77 034 31 619 45 416 63 769 57 365 9 727 7 790 69 244

d(100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0) (100.0)

Percent continuously covered for 32

months by:

Private or government health insurance ...... 59.9 51.5 65.7 61.7 64.5 50.1 38.6 62.3

Private health insurance.................... 50.7 45.1 54.6 54.4 57.6 28.9 26.2 53.4

Employer-provided health insurance ......... 14.1 20.8 9.5 14.7 15.5 11.4 8.3 14.8

1

Persons of Hispanic origin may be of any race. The information on the Hispanic population shown in this report was collected in the 50 States

and the District of Columbia, and therefore, does not include residents of Puerto Rico.

13
workers. Hispanic-origin workers in this category were

less likely than Whites (not of Hispanic origin) or Blacks

to have continuous coverage; the comparable rates for

these groups are 67, 89, and 77 percent, respectively.

Part-time workers were less likely than their full-time

counterparts to have continuous health insurance coverage. Twenty eight percent of these workers lacked

continuous coverage, compared with 13 percent of

full-time workers.

There was a major difference between full- and

part-time workers in their levels of own employer-provided

coverage. Of part-time workers with continuous coverage, only 21 percent were covered through their own

employer-provided plans. The comparable figure for

full-time workers was 64 percent. The difference between

the private and employer-provided health insurance

rates for this group implies that many of these workers

are covered as dependents (78 percent of part-time,

full-period workers were women).

Less than one-half (40 percent) of workers with one

or more job interruptions experienced 1 or more months

without health insurance coverage. Men in this category

were more likely than women to lack health coverage for

at least 1 month (48 to 34 percent), and men in this

category were more likely than women to be covered

continuously by their own employer-provided plan (21 to

10 percent).

Younger full-time, full-period workers were less likely

than their older counterparts to have been covered by

health insurance continuously. Forty percent of full-time,

full-period workers 18 to 21 years old spent 1 or more

months without health insurance. (See table J.) For

workers 22 years old and over, comparable percentages

ranged from 9 percent (workers 45 to 64 years old) to 24

percent (workers 22 to 24 years old).

Spells of Noncoverage

One of the major questions asked in the health care

debate is how long do Americans go without health

insurance. Using a technique known as survival analysis,8 it is possible to estimate the duration of spells

8

See appendix B for a technical note explaining the use of survival

analysis in deriving duration of spells without health insurance.

Table J. Continuous Health Insurance Coverage of Wage and Salary Workers by Age and Labor Force

Status: 1991 to 1993

[In thousands. Based on workers 18 to 64 years old]

Health insurance coverage 18 to 21

years

22 to 24

years

25 to 34

years

35 to 44

years

45 to 64

years

FULL-TIME, FULL-PERIOD WORKERS

All persons . . . . . . . . . . . . . . . . . . . . . . . . 1 737 3 166 17 473 18 863 16 636

(100.0) (100.0) (100.0) (100.0) (100.0)

Percent continuously covered for 32

months by:

Private or government health insurance ...... 60.1 75.8 82.0 87.6 91.5

Private health insurance.................... 59.2 75.4 81.1 87.1 90.7

Employer-provided health insurance ......... 33.8 54.8 59.5 60.5 63.3

PART-TIME, FULL-PERIOD WORKERS

All persons . . . . . . . . . . . . . . . . . . . . . . . . 599 303 1 495 1 592 1 859

(100.0) (100.0) (100.0) (100.0) (100.0)

Percent continuously covered for 32

months by:

Private or government health insurance ...... 63.4 33.0 73.2 76.3 75.6

Private health insurance.................... 63.4 28.4 71.7 75.3 71.6

Employer-provided health insurance ......... 11.6 6.3 23.9 18.3 20.6

WORKERS WITH ONE OR MORE JOB INTERRUPTIONS

All persons . . . . . . . . . . . . . . . . . . . . . . . . 11 144 7 234 23 225 17 785 25 713

(100.0) (100.0) (100.0) (100.0) (100.0)

Percent continuously covered for 32

months by:

Private or government health insurance ...... 49.1 43.8 52.7 63.1 73.1

Private health insurance.................... 43.3 34.4 43.4 54.7 62.6

Employer-provided health insurance . . . . . . . . . 2.0 8.5 12.6 15.1 18.2

14
without health insurance. A median spell duration of 7.1

months without health insurance was observed for persons (losing health insurance after February 1991) over

the 32-month period of the 1991 panel. (See table K.) In

other words, of all spells without health insurance (experienced by 27 percent of persons), half of them lasted for

7.1 months or longer. This estimate was significantly

longer than the 6.0 month median duration of noncoverage for the earlier period from 1990 to 1992. Figure 7

shows the distribution of spells without health insurance

by spell length. The increase in the final category

represents all spells without insurance that had not

ended within 2 years.

Education. Attaining a high level of education appears

to have a major impact on how long someone goes

without health insurance. For example, the median spell

duration of 10.0 months without health insurance coverage for those without a high school diploma was longer

than the 5.1 months of noncoverage for those with at

least 1 year of college. High school (but not college)

graduates also had a longer median spell duration of

noncoverage (7.2 months) than those with at least 1

year of college. No statistical difference was observed

between median spells for high school graduates and

nongraduates.

Age and employment status. Generally, comparisons of median spell durations of noncoverage between

age groups are not statistically different. It was observed,

however, that the median spell duration of 5.1 months

without coverage for children less than 18 years of age

was much shorter than spells for other age groups. Spell

durations for other age groups ranged from 7.1 months

for those between the ages of 25 to 34 to 7.7 months for

those between 45 and 64. These differences were not

significant.

As expected, full-time workers had a shorter median

spell duration without health insurance than those unemployed. The median spell durations for these groups

were 5.7 months and 7.7 months, respectively.

Race and Hispanic origin. The median spell duration

without health insurance of 7.1 months for Blacks was

not longer than the 7.0 months for Whites or for Whites,

not of Hispanic origin (6.0 months). Persons of Hispanic

origin had a median spell duration without health insurance of 7.7 months, which was significantly longer than

that of Blacks or Whites.9

Residence and region. Central city residents experienced longer spells without health insurance (7.4 months)

than those living in the suburbs (5.8 months). The

median spell duration of 7.5 months for those living in

the South was longer than the 4.7 month median spell

9

No significant difference was observed between median spell

durations by other race or Hispanic origin comparisons.

Table K. Spells Without Health Insurance

Coverage by Selected

Characteristics: 1990 and 1991 Panels

Characteristic

1991 panel

(1991-93)

1990 panel

(1990-92)

Median

duration

Standard

error

Median

duration

Standard

error

All spells ............ 7.1 0.2 6.0 0.6

Race and Hispanic origin

White . . . . . . . . . . . . . . . . . . . . . . . . 7.0 0.2 5.4 0.6

Not of Hispanic origin . . . . . . . . 6.0 1.0 4.9 0.8

Black . . . . . . . . . . . . . . . . . . . . . . . . 7.1 0.2 7.3 0.1

Hispanic1. . . . . . . . . . . . . . . . . . . . . 7.7 0.3 7.2 0.2

Not of Hispanic origin . . . . . . . . . . 6.1 1.0 5.7 0.6

Age

Under 18 years . . . . . . . . . . . . . . . 5.1 1.0 4.8 1.5

18 to 24 years . . . . . . . . . . . . . . . . 7.3 0.4 6.4 1.3

25 to 34 years . . . . . . . . . . . . . . . . 7.1 0.4 5.4 1.1

35 to 44 years . . . . . . . . . . . . . . . . 7.2 0.5 7.4 0.5

45 to 64 years . . . . . . . . . . . . . . . . 7.7 0.5 6.4 1.5

65 years and over . . . . . . . . . . . . . (B) (X) (B) (X)

Sex

Male . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 0.2 6.6 0.9

Female. . . . . . . . . . . . . . . . . . . . . . . 6.6 1.4 5.5 0.8

Educational attainment

(persons 18 years and over)

Less than 4 years of high

school ...................... 10.0 2.1 7.6 0.4

High school graduate, no

college. . . . . . . . . . . . . . . . . . . . . . 7.2 0.4 7.1 0.3

1 or more years of college. . . . . . 5.1 1.1 4.0 0.1

Residence

Metropolitan . . . . . . . . . . . . . . . . . . 7.0 0.2 5.8 0.6

Central city . . . . . . . . . . . . . . . . . 7.4 0.3 6.2 1.2

Suburbs. . . . . . . . . . . . . . . . . . . . 5.8 0.9 5.4 1.0

Nonmetropolitan. . . . . . . . . . . . . . . 7.2 0.3 6.7 1.1

Region

Northeast. . . . . . . . . . . . . . . . . . . . . 7.1 0.3 5.1 0.8

Midwest . . . . . . . . . . . . . . . . . . . . . . 4.7 1.6 4.7 1.0

South . . . . . . . . . . . . . . . . . . . . . . . . 7.5 0.3 7.2 0.2

West. . . . . . . . . . . . . . . . . . . . . . . . . 6.8 1.3 5.3 1.5

Employment status

(persons 18 years and over)

Employed full time. . . . . . . . . . . . . 5.7 1.1 4.6 0.9

Employed part time. . . . . . . . . . . . 7.5 0.5 6.8 1.6

Unemployed . . . . . . . . . . . . . . . . . . 7.7 0.5 7.8 0.7

Not in labor force. . . . . . . . . . . . . . 8.8 3.2 7.2 0.3

Receipt of public assistance

Received public assistance . . . . . 6.5 1.9 7.4 0.3

Did not receive public

assistance. . . . . . . . . . . . . . . . . . . 7.1 0.2 5.7 0.6

Poverty status

Below poverty. . . . . . . . . . . . . . . . . 7.5 0.3 7.2 0.2

Above poverty . . . . . . . . . . . . . . . . 6.3 1.3 4.9 0.7

1

Persons of Hispanic origin may be of any race. The information on

the Hispanic population shown in this report was collected in the 50

States and the District of Columbia, and therefore, does not include

residents of Puerto Rico.

Note: These estimates represent those persons observed to

begin a spell of noncoverage during the 32-month period of the 1990

and 1991 panels.

15
duration for those in the Midwest. Median spells of

noncoverage for other regions were 7.1 months for

those living in the Northeast and 6.8 months for those in

the West.10 11

USER COMMENTS

We are interested in your reaction to the usefulness

and content of this report. We welcome your recommendations. If you have any suggestions or comments,

please send them to:

Charles T. Nelson

Housing and Household Economic Statistics Division

U.S. Bureau of the Census

Washington, DC 20233-8500

10No significant difference was observed between median spell

durations of those residing in other regions. 11For an examination of the dynamics of health insurance for

cohorts of privately insured and uninsured persons, see A.C. Monheit

and C.L. Schur, The Dynamics of Health Insurance Loss: A Tale of

Two Cohorts, Inquiry 25 (Fall 1988): 315-327 and K. Swartz and T.D.

McBride, Spells Without Health Insurance: Distribution of Durations

and Their Link to Point-in-Time Estimates of the Uninsured, Inquiry 27

(Fall 1990): 281-288.

16
Appendix A.

Definitions and Explanations

Population coverage. The estimates in this report are

restricted to the civilian noninstitutional resident population

of the United States and members of the Armed Forces

living off post or with their families on post.

Age. Age classification is based on age at the beginning of

the 32-month period.

Race. The population is divided into three groups on the

basis of race: White, Black, and ‘‘‘other races.’’ The last

category includes American Indians, Asian/Pacific Islanders, and any other race except White and Black.

Hispanic origin. Persons of Hispanic origin were determined on the basis of a question that asked for selfidentification of the person’s origin (or the origin of some

other household member) from a ‘‘‘flashcard’’’ listing ethnic

origins. Hispanics were those who indicated that their

origin was Mexican, Puerto Rican, Cuban, Central or South

American, or some other Hispanic origin. It should be noted

that persons of Hispanic origin may be of any race. The

information on the Hispanic population shown in this report

was collected in the 50 States and the District of Columbia,

and therefore, does not include residents of Puerto Rico.

Metropolitan areas. The population residing in metropolitan statistical areas (MSA’s) as defined in June 1984

constitutes the metropolitan population. MSA’s are defined

by the Office of Management and Budget for use in the

presentation of statistics by agencies of the Federal Government. An MSA is a geographic area consisting of a

large population nucleus, together with adjacent communities which have a high degree of economic and social

integration with that nucleus. The definitions specify a

boundary around each large city to include most or all of its

suburbs. Entire counties form the MSA building blocks,

except in New England where cities and towns are used.

The former term SMSA was changed to MSA in 1983. An

area qualifies for recognition as an MSA if (1) it includes a

Census Bureau-defined urbanized area of at least 50,000

with a total metropolitan population of at least 100,000

(75,000 in New England). In addition to the county containing the main city or urbanized area, an MSA may include

other counties having strong commuting ties to the central

county. If specified conditions are met, certain large MSA’s

are designated as consolidated MSA’s (CMSA’s) and

divided into component primary MSA’s (PMSA’s).

Nonmetropolitan areas. The territory outside metropolitan statistical areas is referred to as nonmetropolitan.

Central cities. The largest city in each MSA is always

designated a central city. There may be additional central

cities if specified requirements, designed to identify places

of central character within the MSA, are met. Although the

largest central cities are generally included in the title of the

MSA, there may be central cities that are not part of the

title. The balance of the MSA outside the central city or

cities often is regarded as equivalent to ‘‘‘suburban areas.’’

Noncentral cities. The territory outside central cities of

metropolitan statistical areas but within MSA’s is referred to

as noncentral cities or ‘‘suburban areas.’’

Labor force and employment status. The definitions of

labor force and employment status relate to persons 18

years old and older.

Full-time worker. A person was employed full-time in a

given month if he or she worked at least 1 week during that

month and at least 35 hours during a usual week of

employment.

Part-time worker. A person was employed part-time in a

given month if he or she worked at least 1 week during that

month and less than 35 hours during a usual week of

employment.

Unemployed. A person was unemployed in a given month

if he or she had no job during the month and spent 1 or

more weeks looking for employment or on layoff.

Not in the labor force. A person was not in the labor force

in a given month if he or she held no job during the month

and spent no time looking or on layoff.

Poverty definition. The poverty definition used in this

report is based on the Government’s official definition but

was calculated on a monthly basis using the family composition at that time rather than fixing it throughout the year

as is done in the Current Population Survey. These data

differ from the official figures and are not part of the

standard data series on poverty established by Directive 14

from the Office of Management and Budget. Official figures

are published annually from the March Current Population

Survey in the P60 Series of Current Population Reports.

A person’s poverty status in this report was determined

by comparing the sum of the person’s family income each

month against the sum of the appropriate monthly poverty

A–1
thresholds. If the person’s family income (personal income

if an unrelated individual) was below the sum of the

monthly poverty thresholds, the person was classified as

below the poverty level for the year shown.

For further discussion of the poverty definition, see

Current Population Reports, Series P60-188, Income, Poverty, and Valuation of Noncash Benefits: 1993.

Income-to-poverty ratio. The income-to-poverty ratio used

in this report incorporates an adjustment in every month for

family size and composition. The poverty threshold for

each family is calculated based on the size and composition of that family in each month. For unrelated individuals,

individual income is divided by the appropriate one-personfamily poverty threshold. In order to obtain the income-topoverty ratio during a certain period, the family income of a

person is summed over each month of that period and

divided by the sum of the respective monthly poverty

thresholds.

Low-income status. The low-income definition used in

this report is based on the Government’s official poverty

definition. A person’s monthly low-income status in this

report was determined by comparing the person’s family

income in a month against the appropriate monthly poverty

thresholds (one-twelfth of the annual poverty threshold). If

the person’s family income was below the monthly poverty

thresholds, the person was classified as having low-income

for the month.

Public assistance. AFDC or other cash assistance includes

payments under the Aid to Families with Dependent Children (AFDC or ADC) Program and payments often categorized as general or public assistance.

General assistance consists of a host of State and local

programs to provide cash assistance to needy persons not

qualifying for AFDC or Supplemental Security Income

(SSI). Eligibility rules vary from State to State, and often

from county to county within a State, ranging from aid to

mostly unemployable single adults (District of Columbia),

to workfare programs, where recipients work in exchange

for the assistance (New York).

Persons are considered participants in AFDC or general

assistance if they are identified as primary recipients or if

they are covered under another persons’ allotment.

Medicare. The medicare program is designed to provide

medical care for the aged and disabled. The Basic Hospital

Insurance Plan (Part A) is designed to provide basic

protection against hospital costs and related post-hospital

services. This plan also covers many persons under 65

years old who receive Social Security or railroad retirement

benefits based on long-term disability. Part A is financed

jointly by employers and employees through Social Security payroll deductions. Qualified persons 65 years old and

over who are not otherwise eligible for Part A benefits may

pay premiums directly to obtain this coverage. The Medical

Insurance Plan (Part B) is a voluntary plan which builds

upon the hospital insurance protection provided by the

basic plan. It provides insurance protection covering physicians’

and surgeons’ services and a variety of medical and other

health services received either in hospitals or on an

ambulatory basis. It is financed through monthly premium

payments by each enrollee and subsidized by Federal

general revenue funds.

The term ‘‘covered’’ means enrolled in the medicare

program. In order to be counted, the person did not

necessarily have to receive medical care paid for by

medicare.

Medicaid. The medicaid program is designed ‘‘to furnish

medical assistance on behalf of needy families with dependent children, and of aged, blind, or permanently and totally

disabled individuals whose incomes and resources are

insufficient to meet the costs of necessary medical services.’’1 The program is administered by State agencies

through grants from the Health Care Financing Administration of the Department of Health and Human Services.

Funding for medical assistance payments consists of a

combination of Federal, State, and in some cases, local

funds.

The medicaid question on the SIPP attempted to identify

all adults who were covered by medicaid. The term ‘‘covered’’ means enrolled in the medicaid program; e.g., had a

medicaid medical assistance card or incurred medical bills

which were paid for by medicaid. In order to be counted,

the person did not have to receive medical care paid for by

medicaid.

Spells of noncoverage. Using longitudinal data, it is

possible to estimate the distribution of lengths of spells

without health insurance coverage for individuals by various characteristics.

Technical note. A technique known as survival analysis

was used to derive distributions of spell duration, as well as

the resulting estimates of medial spell duration without

health insurance. These analyses are based on data for

persons observed over a 32-month period of the 1990 and

1991 panels. Only those persons who were present during

the entire period were considered. A spell is defined as a

period without health insurance coverage, which was preceded by at least 1 month or more with coverage. The spell

is observed either until it ends or is right-censored. Since

an individual must have completed interviews for all months

of the panel in order to be included in the sample, right

censoring occurs only if an individual is still participating

the last month of the panel. The probability of noncoverage

1

From title XIX of the 1965 Amendments to P.L. 89-97, The Social

Security Act, ‘‘Grants to States for Medical Assistance Programs,’’

declaration of policy.

A–2
in month t given that the person was covered in the

beginning of that month, is defined as

h~t! 5 exits~t!

prog~t! 2 ~rcens~t!/2!

where exits(t) denotes the number of spell exits in month

t, prog(t) is the number of spells that were in progress in the

beginning of month t, and rcens(t) is the number of spells

which were right-censored in month t.2

The survival rate in month t, which is the probability that

a spell lasts longer than t months, can then be written as

S~t! 5

t

pi ~12h~k!!.

k51

The survival function evaluated at t gives the probability

that a noncovered entrant is still not covered t time periods

later. The median survival time or spell duration M can be

estimated by linear interpolation.3 4 Let (t,t+1) be the

interval such that S (t)>=.5 and S(t+1)<.5, therefore,

M

ˆ = t 1

S~t!21/2

S~t!2S~t11!

Since a spell must be preceded by at least 1 month of

health insurance coverage, left-censored spells of noncoverage are not included in this analysis. Observations are

left-censored when the beginning of a spell of interest is not

observed; that is, a spell began at some time before the

reference period.

While dynamic estimates may be unbiased for spells

observed at the beginning of a reference period, there

remains concern about the deletion of left-censored spells

from such analyses. There may be particular characteristics of persons, associated with the experience of very long

spells, that precludes their inclusion in the sample. For

example, in our analysis, which is restricted to persons in

the sample the entire period, selecting spells with observed

beginnings leads to a sample without those persons who

were without health insurance from the beginning of the

panel. Persons with chronically long spells without coverage or persons who were never covered (e.g., those

working in an industrial sector that has traditionally not had

health insurance benefits) may not be proportionately

represented in a sample restricted to spells with observed

beginnings. Studies of spells with observed beginnings

might result in reasonable estimates of spell distribution

and median duration for such spells with observed beginnings, but it might result in downward biased estimates of

median duration of all spells.

Symbols. A dash (—) represents zero or rounds to zero,

the symbol ‘‘B’’ means that the base for the derived figure

is less than 200,000 and the symbol ‘‘X’’ means not

applicable.

Rounding. Percentages are rounded to the nearest tenth

of a percent; therefore, the percentages in a distribution do

not always add to exactly 100.0 percent. The totals,

however, are always shown as 100.0. Moreover, individual

figures are rounded to the nearest thousand without being

adjusted to group totals, which are independently rounded;

percentages are based on the unrounded numbers.

2

It is assumed that a spell exit occurs in month t if no coverage was

observed in month t and coverage was observed in month t + 1. Also, it is

assumed that a spell is exposed to the risk of exiting for an average of

one-half of a month before right-censoring occurs. 3

Resulting median spell durations are shorter than those based on a

sample of spells at a given point in time. Cross-sectional estimates of

median spell durations can be upwardly biased since longer spells are

more likely to be included in a sample at a point in time than shorter spells. 4

Lee, E.T. (1980) Statistical Methods for Survival Data Analysis,

Wadsworth, Inc., Belmont, CA.

A–3
Appendix B.

Source and Accuracy of the Estimates

SOURCE OF DATA

The SIPP universe is the noninstitutionalized resident

population living in the United States. This population

includes persons living in group quarters, such as dormitories, rooming houses, and religious group dwellings. Not

eligible to be in the survey are crew members of merchant

vessels, Armed Forces personnel living in military barracks, and institutionalized persons, such as correctional

facility inmates and nursing home residents. Also not

eligible are U.S. citizens residing abroad. Foreign visitors

who work or attend school in this country and their families

are eligible; all others are not eligible. With the exceptions

noted above, field representatives interview eligible persons who are at least 15 years of age at the time of the

interview.

The 1990 and 1991 panel SIPP samples are located in

230 Primary Sampling Units (PSU’s) each consisting of a

county or a group of contiguous counties. Within these

PSU’s, we systematically selected expected clusters of two

living quarters (LQ’s) from lists of addresses prepared for

the 1980 decennial census to form the bulk of the sample.

To account for LQ’s built within each of the sample areas

after the 1980 census, we selected a sample containing

clusters of four LQ’s from permits issued for construction of

residential LQ’s up until shortly before the beginning of the

panel.

In jurisdictions that have incomplete addresses or don’t

issue building permits, we sampled small land areas, listed

expected clusters of four LQ’s, and then subsampled. In

addition, we selected a sample of LQ’s from a supplemental frame that included LQ’s identified as missed in the

1980 census.

The 1990 panel differs from other panels as a result of

oversampling for low income households. The panel contains an oversample of Black-headed households, Hispanicheaded households and female-headed family households

with no spouse present and living with relatives.

The first interviews occurred during February, March,

April, or May of the panel year. Interviews for approximately one-fourth of the sample took place in each of these

months creating four subsamples. The four subsamples

distribute interviewing workloads and are called rotation

groups. One round of interviewing for the sample covering

all four rotations is called a wave. For the remainder of the

panel, interviews for each person occurred every 4 months.

At each interview the reference period was the 4 months

preceding the interview month.

Occupants of about 93 percent of all eligible living

quarters participated in the first interview of the panel. For

later interviews, field representatives interviewed only original sample persons (those in wave 1 sample households

and interviewed in wave 1) and persons living with them.

The Census Bureau automatically designated all first wave

noninterviewed households as noninterviews for all subsequent interviews.

For the 1990 panel, field representatives conducted

personal interviews in the first through sixth waves only.

For the 1991 panel, field representatives conducted personal interviews for the first, second, third, and sixth waves

only. The remaining interviews for 1990 and 1991 panels

were designated telephone interviews. Even though headquarters designates a 1990+ interview as personal or

telephone, the field representatives may conduct the other

type depending on the circumstances of a case.

For personal interviews, we followed original sample

persons if they moved to a new address, unless the new

address was more than 100 miles from a SIPP sample

area. If the original sample persons moved farther than 100

miles from a SIPP sample area, we attempted telephone

interviews. When original sample persons moved to remote

parts of the country and were unreachable by telephone,

moved without leaving a forwarding address, or refused the

interview, additional noninterviews resulted.

We classified a person as interviewed or noninterviewed

for the entire panel and both calendar years based on the

following definitions. Interviewed sample persons are—

x those for whom self or proxy response was obtained for

each reference month of all eight interviews for the 1990

and 1991 panels, and all three interviews for each

calendar year; or

x those for whom self or proxy response was obtained for

the first reference month of the interview period and for

each later reference month until they were known to

have died or moved to an ineligible address (foreign

living quarters, institutions, or military barracks).

Noninterviewed persons result when neither a self nor

proxy response is obtainable for one or more reference

months of either the eight interviews for the panel or the

three interviews for each calendar year (but not because

they died or moved to an ineligible address).

Details on interview-status classification are in ‘‘Weighting of Persons for SIPP Longitudinal Tabulations’’ (paper

by Judkins, Hubble, Dorsch, McMillen, and Ernst in the

B–1
1984 Proceedings of the Survey Research Methods Section, American Statistical Association). Details on patterns

of nonresponse are in ‘‘Weighting Adjustment for Partial

Nonresponse in the 1984 SIPP Panel’’ (paper by Lepkowski, Kalton, and Kasprzyk in the 1989 Proceedings of

the Survey Research Methods Section, American Statistical Association).

Table B–1. Sample Size by Panel or Calendar Year

and Interview Status (Persons)

Panel or calendar year

Initially

eligible

Classified

as interviewed

Person

nonresponse

rate

(percent)

90 panel. . . . . . . . . . . . . . . . . . . . . . . . 61 700 43 700 29

90 calendar year . . . . . . . . . . . . . . . . 61 700 49 600 20

91 calendar year . . . . . . . . . . . . . . . . 67 400 47 500 30

91 panel. . . . . . . . . . . . . . . . . . . . . . . . 40 800 30 600 25

91 calendar year . . . . . . . . . . . . . . . . 40 800 33 200 19

92 calendar year . . . . . . . . . . . . . . . . 43 200 32 000 26

Some respondents did not respond to some of the

questions. Therefore, the overall nonresponse rate for

some items, especially sensitive income and money related

items, is higher than the person nonresponse rate. For

more discussion of nonresponse see the Quality Profile for

the Survey of Income and Program Participation, May

1990, by T. Jabine, K. King, and R. Petroni, available from

Customer Services, Data Users Services Division (301-

457-1305).

ESTIMATION

We used several stages of weight adjustments in the

estimation procedure to derive the SIPP longitudinal person weights. We gave each person a base weight equal to

the inverse of his/her probability of selection. We applied

two noninterview adjustment factors. One adjusted the

weights of interviewed persons in interviewed households

to account for households which were eligible for the

sample but which field representatives could not interview

at the first interview. The second compensated for person

noninterviews occurring in subsequent interviews. The

Census Bureau used complex techniques to adjust the

weights for nonresponse, but the success of these techniques in avoiding bias is unknown. For more detail on

noninterview adjustment for longitudinal estimates see

‘‘Nonresponse Adjustment Methods for Demographic Surveys at the U.S. Bureau of the Census, November 1988’’,

Working paper 8823, by R. Singh and R. Petroni.

We applied another factor to each interviewed person’s

weight to account for the SIPP sample areas not having

the same population distribution as the strata they are

from.

We performed an additional stage of adjustment to

longitudinal person weights to reduce the mean square

error of the survey estimates. We accomplished this by

ratio adjusting the sample estimates to agree with monthly

Current Population Survey (CPS) type estimates of the

civilian (and some military) noninstitutional population of

the United States at the national level by demographic

characteristics including age, sex, and race, as of the

specified control date. For the 1990 Panel, the control date

is March 1, 1990. The 1990 calendar year and 1991

calendar year control dates are January 1, 1990, and

January 1, 1991, respectively. For the 1991 Panel, the

control date is March 1, 1991. The 1991 calendar year and

1992 calendar year control dates are January 1, 1991, and

January 1, 1992, respectively. The Census Bureau brought

CPS estimates by age, sex, and race into agreement with

adjusted estimates from the 1980 decennial census. Adjustments to the 1980 decennial census estimates reflect

births, deaths, immigration, emigration, and changes in the

Armed Forces since 1980. Also, we controlled SIPP estimates to independent Hispanic controls.

ACCURACY OF ESTIMATES

We base SIPP estimates on a sample. The sample

estimates may differ somewhat from the values obtained

from administering a complete census using the same

questionnaire, instructions, and enumerators. The difference occurs because a sample survey estimate is subject

to two types of errors: nonsampling and sampling. We can

provide estimates of the magnitude of the SIPP sampling

error, but this is not true of nonsampling error. The next few

sections describe SIPP nonsampling error sources, followed by a discussion of sampling error, its estimation, and

its use in data analysis.

Nonsampling variability. We attribute nonsampling errors

to many sources; they include:

x Inability to obtain information about all cases in the

sample

x Definitional difficulties

x Differences in the interpretation of questions

x Inability or unwillingness on the part of the respondents

to provide correct information

x Inability to recall information

x Errors made in collection (e.g. recording or coding the

data)

x Errors made in processing the data

x Errors made in estimating values for missing data

x Biases resulting from the differing recall periods caused

by the interviewing pattern used

x Undercoverage

B–2
Table B–2. 1992 CPS Coverage Ratios

Age

Non-Black Black All Persons

Males Females Males Females Males Females Total

0-14.................................... 0.963 0.965 0.927 0.926 0.957 0.959 0.958

15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.962 0.949 0.899 0.919 0.952 0.944 0.948

16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.969 0.936 0.923 0.907 0.962 0.932 0.947

17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.981 0.975 0.945 0.862 0.975 0.957 0.966

18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.939 0.926 0.883 0.846 0.930 0.913 0.922

19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.860 0.872 0.754 0.801 0.844 0.861 0.853

20-24................................... 0.913 0.927 0.734 0.832 0.889 0.913 0.901

25-26................................... 0.927 0.940 0.688 0.877 0.897 0.931 0.914

27-29................................... 0.910 0.954 0.707 0.864 0.885 0.941 0.914

30-34................................... 0.893 0.948 0.691 0.883 0.870 0.939 0.905

35-39................................... 0.910 0.949 0.763 0.899 0.895 0.942 0.919

40-44................................... 0.929 0.951 0.824 0.906 0.919 0.946 0.933

45-49................................... 0.956 0.966 0.903 0.956 0.951 0.965 0.958

50-54................................... 0.940 0.961 0.807 0.877 0.927 0.951 0.940

55-59................................... 0.944 0.941 0.826 0.825 0.932 0.928 0.930

60-62................................... 0.965 0.956 0.792 0.850 0.948 0.944 0.946

63-64................................... 0.905 0.907 0.669 0.872 0.884 0.903 0.894

65-67................................... 0.935 0.979 0.783 0.875 0.921 0.969 0.947

68-69................................... 0.925 0.942 0.789 0.831 0.913 0.931 0.923

70-74................................... 0.926 0.993 0.856 1.014 0.920 0.995 0.962

75-99................................... 0.977 0.989 0.764 0.912 0.961 0.983 0.975

15+ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.928 0.953 0.782 0.883 0.912 0.944 0.929

0+ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.936 0.955 0.827 0.895 0.923 0.947 0.935

We used quality control and edit procedures to reduce

errors made by respondents, coders, and interviewers.

More detailed discussions of the existence and control of

nonsampling errors in the SIPP are in the SIPP Quality

Profile.

Undercoverage in SIPP resulted from missed living

quarters and missed persons within sample households. It

is known that undercoverage varies with age, race, and

sex. Generally, undercoverage is larger for males than for

females and larger for Blacks than for non-Blacks. Ratio

estimation to independent age-race-sex population controls partially corrects for the bias due to survey undercoverage. However, biases exist in the estimates when persons in missed households or missed persons in interviewed

households have characteristics different from those of

interviewed persons in the same age-race-sex group.

Further, we didn’t adjust the independent population controls for undercoverage in the census.

A common measure of survey coverage is the coverage

ratio, the estimated population before ratio adjustment

divided by the independent population control. Table B–2

shows CPS coverage ratios for age-sex-race groups for

1992. The CPS coverage ratios can exhibit some variability

from month to month, but these are a typical set of

coverage ratios. Other Census Bureau household surveys

like the SIPP experience similar coverage.

Comparability with other estimates. Exercise caution

when comparing data from this report with data from other

SIPP publications or with data from other surveys. Comparability problems are from varying seasonal patterns for

many characteristics, different nonsampling errors, and

different concepts and procedures. Refer to the SIPP

Quality Profile for known differences with data from other

sources and further discussion.

Sampling variability. Standard errors indicate the magnitude of the sampling error. They also partially measure

the effect of some nonsampling errors in response and

enumeration, but do not measure any systematic biases in

the data. The standard errors mostly measure the variations that occurred by chance because we surveyed a

sample rather than the entire population.

USES AND COMPUTATION OF STANDARD

ERRORS

Confidence intervals. The sample estimate and its standard error enable one to construct confidence intervals,

ranges that would include the average result of all possible

samples with a known probability. For example, if we

selected all possible samples and surveyed each of these

under essentially the same conditions and with the same

sample design, and if we calculated an estimate and its

standard error from each sample, then:

1. Approximately 90 percent of the intervals from 1.645

standard errors below the estimate to 1.645 standard

errors above the estimate would include the average

result of all possible samples.

2. Approximately 95 percent of the intervals from 1.960

standard errors below the estimate to 1.960 standard

errors above the estimate would include the average

result of all possible samples.

B–3
The average estimate derived from all possible samples

is or is not contained in any particular computed interval.

However, for a particular sample, one can say with a

specified confidence that the confidence interval includes

the average estimate derived from all possible samples.

Hypothesis testing. One may also use standard errors

for hypothesis testing. Hypothesis testing is a procedure for

distinguishing between population characteristics using

sample estimates. The most common type of hypothesis

tested is 1) the population characteristics are identical

versus 2) they are different. One can perform tests at

various levels of significance, where a level of significance

is the probability of concluding that the characteristics are

different when, in fact, they are identical.

Unless noted otherwise, all statements of comparison in

the report passed a hypothesis test at the 0.10 level of

significance or better. This means that, for differences cited

in the report, the estimated absolute difference between

parameters is greater than 1.645 times the standard error

of the difference.

To perform the most common test, compute the difference XA - XB, where XA and XB are sample estimates of the

characteristics of interest. A later section explains how to

derive an estimate of the standard error of the difference

XA - XB. Let that standard error be sDIFF. If XA - XB is

between -1.645 times sDIFF and +1.645 times sDIFF, no

conclusion about the characteristics is justified at the 10

percent significance level. If, on the other hand, XA - XB is

smaller than -1.645 times sDIFF or larger than +1.645 times

sDIFF, the observed difference is significant at the 10

percent level. In this event, it is commonly accepted

practice to say that the characteristics are different. Of

course, sometimes this conclusion will be wrong. When the

characteristics are, in fact, the same, there is a 10 percent

chance of concluding that they are different.

Note that as we perform more tests, more erroneous

significant differences will occur. For example, at the 10

percent significance level, if we perform 100 independent

hypothesis tests in which there are no real differences, it is

likely that about 10 erroneous differences will occur. Therefore, interpret the significance of any single test cautiously.

Note concerning small estimates and small

differences. We show summary measures in the report

only when the base is 200,000 or greater. Because of the

large standard errors involved, there is little chance that

estimates will reveal useful information when computed on

a base smaller than 200,000. Also, nonsampling error in

one or more of the small number of cases providing the

estimate can cause large relative error in that particular

estimate. We show estimated numbers, however, even

though the relative standard errors of these numbers are

larger than those for the corresponding percentages. We

provide smaller estimates primarily to permit such combinations of the categories to serve each user’s needs.

Therefore, be careful in the interpretation of small differences since even a small amount of nonsampling error can

cause a borderline difference to appear significant or not,

thus distorting a seemingly valid hypothesis test.

Standard error parameters and tables and their

use. Most SIPP estimates have greater standard errors

than those obtained through a simple random sample

because we sampled clusters of living quarters for the

SIPP. To derive standard errors at a moderate cost and

applicable to a wide variety of estimates, we made a

number of approximations. We grouped estimates with

similar standard error behavior and developed two parameters (denoted ‘‘a’’ and ‘‘b’’) to approximate the standard

error behavior of each group of estimates. Because the

actual standard error behavior was not identical for all

estimates within a group, the standard errors we computed

from these parameters provide an indication of the order of

magnitude of the standard error for any specific estimate.

These ‘‘a’’ and ‘‘b’’ parameters vary by characteristic and

by demographic subgroup to which the estimate applies.

These tables provide the ‘‘a’’ and ‘‘b’’ parameters which are

used for the following panel estimates:

x Table B–3: 1991 Longitudinal

x Table B–4: 1990 Longitudinal

For users who wish further simplification, we also provide general standard errors in tables B–5 and B–6. Note

that you need to adjust these standard errors by a factor

from tables B–3 and B–4. The standard errors resulting

from this simplified approach are less accurate. Methods

for using these parameters and tables for computation of

standard errors are given in the following sections.

Standard errors of estimated numbers. There are two

ways to compute the approximate standard error, sx, of an

estimated number shown in this report. The first uses the

formula

sx 5 fs (1)

where f is a factor from tables B–3 and B–4, and s is the

standard error of the estimate obtained by interpolation

from table B–5. Alternatively, approximate sx using the

formula,

sx 5 =ax2 1 bx (2)

from which we calculated the standard errors in table B–5.

Here x is the size of the estimate and a and b are the

parameters in tables B–3 and B–4 associated with the

particular type of characteristic. Use of formula 2 will

provide more accurate results than the use of formula 1.

When calculating standard errors for numbers from crosstabulations involving different characteristics, use the factor or

set of parameters for the characteristic which will give the

largest standard error.

B–4
Illustration. SIPP estimates given in table A of the

report show that 18,001,000 persons were uninsured in

1992. The appropriate ‘‘a’’ and ‘‘b’’ parameters are obtained

from table B–3. They are a = -0.0001294 and b = 31,174,

respectively. Using formula (2), the approximated standard

error is

=~20.0001294!~18,001,000!

2 1 ~31,174!~18,001,000! 5 721,000

The 90-percent confidence interval as shown by the data is

from 16,816,000 to 19,186,000. Therefore, a conclusion

that the average derived from all possible samples lies

within a range computed in this way would be correct for

roughly 90-percent of all samples.

Using formula (1), the appropriate ‘‘f’’ factor (f=0.98)

from table B–3 and the standard error of the estimate by

interpolation using table B–5, the approximate standard

error is

sx ~0.98!~734,000! 5 719,000

The 90-percent confidence interval as shown by the data is

from 16,818,000 to 19,184,000.

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. When the numerator

and denominator of the percentage have different parameters, use the parameter (or appropriate factor) from tables

B–3 and B–4 indicated by the numerator.

Calculate the approximate standard error, s(x,p), of an

estimated percentage p using the formula

s~x,p! 5 fs (3)

where p is the percentage of persons/families/households

with a particular characteristic such as the percent of

persons owning their own homes.

In this formula, f is the appropriate ‘‘f’’ factor from tables

B–3 and B–4, and s is the standard error of the estimate

obtained by interpolation from table B–6.

Alternatively, approximate it by the formula:

s~x,p! 5 Îb

x

~p!~100 2 p! (4)

from which we calculated the standard errors in table B–6.

Here x is the total number of persons, families, households, or unrelated individuals in the base of the percentage, p is the percentage (0 ≤ p ≤ 100), and b is the ‘‘b’’

parameter in tables B–3 and B–4 associated with the

characteristic in the numerator of the percentage. Use of

this formula will give more accurate results than use of

formula (3) above.

Illustration. Table A of the report shows that 72.1

percent of Blacks were covered by health insurance for 12

months in calendar year 1992. The base of this percentage

(x) is 31,237,000. The appropriate ‘‘b’’ parameter and ‘‘f’’

factor from table B–3 and the appropriate general standard

error found by interpolation from table B–6 are

b 5 11,533, f 5 0.60, s 5 1.40

Using formula (3), the approximate standard error is

s~x,p! 5 ~0.60!~1.40! 5 0.8%.

Using formula (4), the approximate standard error is

s~x,p! 5 Î 11,533

31,237,000 72.1%~100% 2 72.1%! 5 0.9%.

The 90-percent confidence interval shown by these data is

70.7 to 73.5 percent.

Standard error of a difference. The standard error of a

difference between two sample estimates, x and y, is

approximately equal to

s~x2y! 5 =sx

2 1 sy2

2 2rsxsy (5)

where sx and sy are the standard errors of the estimates x

and y and r is the correlation coefficient between the

characteristics estimated by x and y. The estimates can be

numbers, averages, percents, ratios, etc. Underestimates

or overestimates of standard error of differences result if

the estimated correlation coefficient is overestimated or

underestimated, respectively. In this report, we assume

r is 0.

Illustration. Table B of the report shows 28.3 percent of

males and 24.7 percent of females received health insurance coverage for less than 32 months of the 1991 panel.

The bases of the percentages for males and females are

117,061,000 and 124,894, 000, respectively. The standard

errors for these percentages are computed using formula

4, to be 1.2 percent and 1.1 percent. Assuming that these

two estimates are not correlated, the standard error of the

estimated difference of 3.6 percentage points is

s~x2y! 5 =~1.2%!

2 1 ~1.1%!2 5 1.7%

Suppose that it is desired to test at the 10-percent significance level whether the percentage of males who received

health insurance coverage for less than 32 months was

different than the percentage of females who received

health insurance coverage for less than 32 months. To

perform the test, compare the difference of 3.6 percent to

the product 1.645 x 1.7 = 2.8 percent. Since the difference

is greater than 1.645 times the standard error of the

difference, the data show that the two sex groups are

significantly different at the 10-percent significance level.

B–5
Table B–3. SIPP Generalized Variance Parameters for Estimates Using the 1991 Longitudinal File

Characteristics of persons

1991 panel weights 1991 calendar weights 1992 calendar weights

ab fab fab f

TOTAL OR WHITE

All others

Both sexes ................ –0.0001345 32 413 1.00 –0.0001254 30 228 0.97 –0.0001294 31 174 0.98

Male.................... –0.0002768 32 413 –0.0002582 30 228 –0.0002663 31 174

Female ................. –0.0002613 32 413 –0.0002437 30 228 –0.0002513 31 174

Black

All others

Both sexes ................ –0.0004081 11 992 0.61 –0.0003806 11 183 0.59 –0.0003925 11 533 0.60

Table B–4. SIPP Generalized Variance Parameters for Estimates Using the 1990 Longitudinal File

Characteristics of persons

1990 panel weights 1990 calendar weights

ab fab f

TOTAL

All others

Both sexes ........................... –0.0000985 22 724 0.84 –0.0000882 20 356 0.79

Male............................... –0.0002038 22 724 –0.0001826 20 356

Female ............................ –0.0001908 22 724 –0.0001709 20 356

White

All others

Both sexes ........................... –0.0001093 25 185 0.88 –0.0000979 22 560 0.83

Black

All others

Both sexes ........................... –0.0002202 6 076 0.43 –0.0001972 5 443 0.41

Hispanic

All others

Both sexes ........................... –0.0002931 6 076 0.43 –0.0002626 5 443 0.41

Table B–5. Standard Errors of Estimated Numbers of Persons

(Numbers in thousands)

Size of estimate Standard error Size of estimate Standard error

200 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 26,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 867

300 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 30,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 923

600 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 50,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 133

1,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180 80,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 316

2,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254 100,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 377

3,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310 130,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 393

5,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398 140,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 379

8,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501 150,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 355

11,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 583 200,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 050

13,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 631 220,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 788

15,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 675 230,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 583

17,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 716 235,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 435

22,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 805 240,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179

B–6
Table B–6. Standard Errors of Estimated Percentages of Persons

Base of estimated percentage

(thousands)

Estimated percentages

1 or 99 2 or 98 5 or 95 10 or 90 25 or 75 50

200 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 5.6 8.8 12.1 17.4 20.1

300 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 4.6 7.2 9.9 14.2 16.4

600 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 3.3 5.1 7.0 10.1 11.6

1,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8 2.5 3.9 5.4 7.8 9.0

2,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 1.8 2.8 3.8 5.5 6.4

3,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.0 1.5 2.3 3.1 4.5 5.2

5,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 1.1 1.8 2.4 3.5 4.0

8,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.6 0.9 1.4 1.9 2.8 3.2

11,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.5 0.8 1.2 1.6 2.4 2.7

13,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.5 0.7 1.1 1.5 2.2 2.5

15,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.5 0.7 1.0 1.4 2.0 2.3

17,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.4 0.6 1.0 1.3 1.9 2.2

22,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.4 0.5 0.8 1.2 1.7 1.9

26,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.4 0.5 0.8 1.1 1.5 1.8

30,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.3 0.5 0.7 1.0 1.4 1.6

50,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.3 0.4 0.6 0.8 1.1 1.3

80,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.2 0.3 0.4 0.6 0.9 1.0

100,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.2 0.3 0.4 0.5 0.8 0.9

130,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.2 0.2 0.3 0.5 0.7 0.8

140,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.2 0.2 0.3 0.5 0.7 0.8

150,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1 0.2 0.3 0.4 0.6 0.7

200,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1 0.2 0.3 0.4 0.6 0.6

220,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1 0.2 0.3 0.4 0.5 0.6

230,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1 0.2 0.3 0.4 0.5 0.6

235,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1 0.2 0.3 0.4 0.5 0.6

240,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1 0.2 0.3 0.3 0.5 0.6

B–7