CPS, September 1997: Veteran's Supplement, Source and Accuracy Statement

Current Population Survey,
September 1997: Veteran's Supplement

ATTACHMENT 17
Source and Accuracy Statement

The data in this microdata file come from the September 1997 Current Population Survey (CPS). The Bureau of the Census conducts this survey every month, although this file has only September data. The September survey uses two sets of questions, the basic CPS and the supplement.

Basic CPS. The basic CPS collects primarily labor force data about the civilian noninstitutional population. Interviewers ask questions concerning labor force participation about each member 15 years old and over in every sample household.

Sample Design. The present CPS sample was selected from the 1990 Decennial Census files with coverage in all 50 states and the District of Columbia. The sample is continually updated to account for new residential construction. The United States was divided into 2,007 geographic areas. In most states, a geographic area consisted of a county or several contiguous counties. In some areas of New England and Hawaii, minor civil divisions are used instead of counties. A total of 792 geographic areas was selected for sample. About 50,000 occupied households are eligible for interview every month. Interviewers are unable to obtain interviews at about 3,500 of these units because the occupants are not home after repeated calls or are unavailable for some other reason.

Since the introduction of the CPS, the Bureau of the Census has redesigned the CPS sample several times. These redesigns have improved the quality and accuracy of the data and have satisfied changing data needs. The most recent changes were completely implemented in July 1995.

September Supplement. In addition to the basic CPS questions, interviewers asked supplementary questions in September of veterans. Questions asked of veterans mainly concern period of service and disability.

Estimation Procedure. This survey's estimation procedure inflates weighted sample results to independent estimates of the civilian noninstitutional population of the United States by age, sex, race, Hispanic/non-Hispanic origin, and state of residence. The independent estimates are calculated based on information from four primary sources:

The independent population estimates include some, but not all, undocumented immigrants. The September supplement's estimation procedure adjusts estimates of veterans by age, sex, and period of service. The monthly veteran controls for ratio estimates are nonveterans, other war veterans, Vietnam era veterans and other service veterans.

Since the CPS estimates come from a sample, they may differ from figures from a complete census using the same questionnaires, instructions, and enumerators. A sample survey estimate has two possible types of errors: sampling and nonsampling. The accuracy of an estimate depends on both types of errors, but the full extent of the nonsampling error is unknown. Consequently, one should be particularly careful when interpreting results based on a relatively small number of cases or on small differences between estimates. The standard errors for CPS estimates primarily indicate the magnitude of sampling error. They also partially measure the effect of some nonsampling errors in responses and enumeration, but do not measure systematic biases in the data. (Bias is the average over all possible samples of the differences between the sample estimates and the desired value.)

Nonsampling Variability. There are several sources of nonsampling errors including the following:

The nonresponse rate was 6.1% for the September 1997 basic CPS, and an additional 1.1% for the Veterans supplement, for a total supplement nonresponse rate of 7.1%.

CPS undercoverage results from missed housing units and missed persons within sample households. Compared to the level of the 1990 Decennial Census, overall CPS undercoverage is about 8 percent. CPS undercoverage varies with age, sex, and race. Generally, undercoverage is larger for males than for females and larger for Blacks and other races combined than for Whites. The post-stratification ratio estimation described previously partially corrects for bias due to undercoverage. However, biases exist in the estimates to the extent that missed persons in missed households or missed persons in interviewed households have different characteristics from those of interviewed persons in the same age-sex-race-origin-state group.

A common measure of survey undercoverage is the coverage ratio, the estimated population before ratio adjustment divided by the independent population control. Table A shows CPS coverage ratios for age-sex-race groups for a recent month. 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 experience similar coverage.

**Table A. CPS Coverage Rations**
Age	Non-Black	Black	All Persons
Male	Female	Male	Female	Male	Female	Total
0-14	0.929	0.964	0.850	0.838	0.916	0.943	0.929
15	0.933	0.895	0.763	0.824	0.905	0.883	0.895
16-19	0.881	0.891	0.711	0.802	0.855	0.877	0.866
20-29	0.847	0.897	0.660	0.811	0.823	0.884	0.854
30-39	0.904	0.931	0.680	0.845	0.877	0.920	0.899
40-49	0.928	0.966	0.816	0.911	0.917	0.959	0.938
50-59	0.953	0.974	0.896	0.927	0.948	0.969	0.959
60-64	0.961	0.941	0.954	0.953	0.960	0.942	0.950
65-69	0.919	0.972	0.982	0.984	0.924	0.973	0.951
70+	0.993	1.004	0.996	0.979	0.993	1.002	0.998
15+	0.914	0.945	0.767	0.874	0.898	0.927	0.918
0+	0.918	0.949	0.793	0.864	0.902	0.931	0.921

For additional information on nonsampling error including the possible impact on CPS data when known, refer to Statistical Policy Working Paper 3, An Error Profile: Employment as Measured by the Current Population Survey, Office of Federal Statistical Policy and Standards, U.S. Department of Commerce, 1978 and Technical Paper 40, The Current Population Survey: Design and Methodology, Bureau of the Census, U.S. Department of Commerce.

Comparability of Data. Data obtained from the CPS and other sources are not entirely comparable. This results from differences in interviewer training and experience and in differing survey processes. This is an example of nonsampling variability not reflected in the standard errors. Use caution when comparing results from different sources.

A number of changes were made in data collection and estimation procedures beginning with the January 1994 CPS. The major change was the use of a new questionnaire. The questionnaire was redesigned to measure the official labor force concepts more precisely, to expand the amount of data available, to implement several definitional changes, and to adapt to a computer-assisted interviewing environment. The supplemental questions are also computerized. Due to these and other changes, one should use caution when comparing estimates from data collected in 1994 and later years with estimates from earlier years.

For more information on the introduction of the new questionnaire and the modernized data collection methods, see "Revisions in the Current Population Survey Effective January 1994" in the February 1994 issue of Employment and Earnings published by the Bureau of Labor Statistics.

Data users should be aware of the effect of the redesigned CPS sample phase-in period from April 1994 through June 1995 on the metropolitan/nonmetropolitan estimates. During this phase-in period, CPS data were collected from sample designs based on both the 1980 and 1990 censuses. While most CPS estimates have been unaffected by this mixed sample, metropolitan and nonmetropolitan estimates have been affected. The 1990 sample cases were recoded to reflect the 1980 metropolitan/nonmetropolitan definitions to allow the estimates to be comparable with earlier data. The gross error rate for the conversions of central cities/suburbs is not expected to exceed 5%.

Since no independent population control totals for persons of Hispanic origin were used before 1985, compare Hispanic estimates over time cautiously.

Caution should also be used when comparing data from this microdata file, which reflects 1990 census-based population controls, with microdata files from 1993 and earlier years, which reflect 1980 census-based population controls. This change in population controls had relatively little impact on summary measures such as means, medians, and percentage distributions. It did have a significant impact on levels. For example, use of 1990 based population controls results in about a 1-percent increase in the civilian noninstitutional population and in the number of families and households. Thus, estimates of levels for data collected in 1994 and later years will differ from those for earlier years by more than what could be attributed to actual changes in the population. These differences could be disproportionately greater for certain subpopulation groups than for the total population.

Note When Using Small Estimates. Because of the large standard errors involved, summary measures (such as medians and percentage distributions) probably would not reveal useful information when computed on a base smaller than 75,000. Take care in the interpretation of small differences. For instance, even a small amount of nonsampling error can cause a borderline difference to appear significant or not, thus distorting a seemingly valid hypothesis test.

Sampling Variability. Sampling variability is variation that occurred by chance because a sample was surveyed rather than the entire population. Standard errors, as calculated by methods described below in "Standard Errors and Their Use," are primarily measures of sampling variability, although they may include some nonsampling error.

Standard Errors and Their Use. A number of approximations are required to derive, at a moderate cost, standard errors applicable to estimates in this microdata file. Instead of providing an individual standard error for each estimate, parameters are provided to calculate standard errors for various types of characteristics.

Table B shows parameters to use for basic CPS monthly labor force estimates. Table C shows parameters for September supplement data including the Veterans supplement.

The sample estimate and its standard error enable one to construct a confidence interval, a range that would include the average result of all possible samples with a known probability. For example, if all possible samples were surveyed under essentially the same general conditions and using the same sample design, and if an estimate and its standard error were calculated from each sample, then 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.

A particular confidence interval may or may not contain the average estimate derived from all possible samples. However, one can say with specified confidence that the interval includes the average estimate calculated from all possible samples.

Standard errors may also be used to perform hypothesis testing, a procedure for distinguishing between population parameters using sample estimates. One common type of hypothesis is that the population parameters are different. An example of this would be comparing the employment rate of veterans to that of nonveterans for 1997. An illustration of this is included in the following pages.

Tests may be performed at various levels of significance. A significance level is the probability of concluding that the characteristics are different when, in fact, they are the same. To conclude that two parameters are different at the 0.10 level of significance, for example, the absolute value of the estimated difference between characteristics must be greater than or equal to 1.645 times the standard error of the difference.

The Census Bureau uses 90-percent confidence intervals and 0.10 levels of significance to determine statistical validity. Consult standard statistical textbooks for alternative criteria.

Standard Errors of Estimated Numbers. The approximate standard error, sx, of an estimated number from this microdata file can be obtained by using the formula

Here x is the size of the estimate and a and b are the parameters in Table B or C associated with the particular type of characteristic. When calculating standard errors for numbers from cross-tabulations involving different characteristics, use the set of parameters for the characteristic which will give the largest standard error.

Suppose there were 3,500,000 unemployed men in the civilian labor force. Use the appropriate parameters from Table B and formula (1) to get

The 90-percent confidence interval is calculated as 3,500,000 ñ 1.645 96,000. A conclusion that the average estimate derived from all possible samples lies within a range computed in this way would be correct for roughly 90 percent of all possible samples.

**Parameters from Table B and formula (1)**
Parameter	Result
Number, x	3,500,000
a parameter	-0.000018
b parameter	2,957
Standard error	101,000
90% conf. int.	3,334,000 to 3,666,000

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. Estimated percentages are relatively more reliable than the corresponding estimates of the numerators of the percentages, particularly if the percentages are 50 percent or more. When the numerator and denominator of the percentage are in different categories, use the parameter from Table B or C indicated by the numerator.

The approximate standard error, s_x,p, of an estimated percentage can be obtained by using the formula

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 parameter in Table B or C associated with the characteristic in the numerator of the percentage.

In 1997, 3.1 percent of 6,831,000 Vietnam-era war veterans (all of whom were 35 years old and over) were unemployed. Use the appropriate parameter from Table C and formula (2) to get

Standard Error of a Difference. The standard error of the difference between two sample estimates is approximately equal to

**Parameters from Table C and formula (2)**
Parameter	Result
Percentage, p	2.1
Base, x	6,831,000
b parameter	2,549
Standard error	0.3
90% conf. int.	2.6 to 3.6

where s_x and s_y are the standard errors of the estimates, x and y. The estimates can be numbers, percentages, ratios, etc. This will result in accurate estimates of the standard error of the same characteristic in two different areas, or for the difference between separate and uncorrelated characteristics in the same area. However, if there is a high positive (negative) correlation between the two characteristics, the formula will overestimate (underestimate) the true standard error.

As stated above, in 1997 3.1 percent of 6,831,000 Vietnam-era war veterans were unemployed. Also, 3.4 percent of 68,648,000 nonveterans 35 years old and over were unemployed. The apparent difference between the two groups is 0.3 percent. Use the appropriate parameters from Tables B and C and formulas (2) and (3) to get

The 90-percent confidence around the difference is calculated as 0.3 ± 1.645 x 0.3. Since this interval contains zero, we cannot conclude with 90 percent confidence that the unemployment rate for Vietnam-era war veterans is less than that for nonveterans in the same age range.

**Parameters from Tables B and C and formulas (2) and (3)**
Parameter	x	y	difference
Percentage	31.1	3.4	0.3
Number, x	6,831,000	68,648,000	--
b parameter	2,549	2,957	--
Standard error	0.3	0.1	0.3
90% conf. int.	2.6 to 3.6	3.2 to 3.6	-0.2 to 0.8

**Table B. Parameters for Computation of Standard Errors for Labor Force Characteristics - September 1997**
Characteristics	a	b
Labor Force and Not in Labor Force Data Other than Agricultural Employmentand Unemployment
Total ¹	-0.000018	2,985
Men ¹	-0.000033	2,764
Women	-0.000030	2,530
Both Sexes, 16 to 19 years	-0.000172	2,545
White¹	-0.000020	2,985
Men	-0.000037	2,767
Women	-0.000034	2,527
Both sexes, 16 to 19 years	-0.000204	2,550
Black	-0.000125	3,139
Men	-0.000302	2,931
Women	-0.000183	2,637
Both sexes, 16 to 19 years	-0.001295	2,949
Hispanic origin	-0.000206	3,896
Not In Labor Force (use only for Total, Total Men, and White)	+0.000006	829
Agricultural Employment
Total or White	+0.000782	3,049
Men	+0.000858	2,825
Women or Both sexes, 16 to 19 years	-0.000025	2,582
Black	-0.000135	3,155
Hispanic origin
Total or Women	+0.011857	2,895
Men or Both sexes, 16 to 19 years	+0.015736	1,703
Unemployment
Total or White	+0.000018	2,957
Black	-0.000212	3,150
Hispanic origin	-0.000102	3,576

¹Note: These parameters are to be applied to basic CPS monthly labor force estimates

Characteristics	a	b
Total Employed and Nonagriculture Employed in Labor Force, Occupations, and Disability Status of Employed
Total or Men
All Veterans	-0.000105	2,688
War Veterans	-0.000141	2,688
Other Service Veterans	-0.000407	2,688
Vietnam Era Veterans	-0.000335	2,688
Women
All Veterans	-0.001859	2,688
War Veterans	-0.003845	2,688
Other Service Veterans	-0.003598	2,688
Vietnam Era Veterans	-0.015719	2,688
Unemployed, Duration of Unemployment
Total or Men
All Veterans	-0.000100	2,549
War Veterans	-0.000134	2,549
Other Service Veterans	-0.000386	2,549
Vietnam Era Veterans	-0.000318	2,549
Women
All Veterans	-0.001763	2,549
War Veterans	-0.003647	2,549
Other Service Veterans	-0.003412	2,549
Vietnam Era Veterans	-0.014906	2,549

Current Population Survey, September 1997: Veteran's Supplement

ATTACHMENT 17 Source and Accuracy Statement

Current Population Survey,
September 1997: Veteran's Supplement

ATTACHMENT 17
Source and Accuracy Statement