1
Dixon_J@bls.gov
Keywords: Survey nonresponse, Gross Flows, Unemployment
Introduction
In the Current Population Survey, a
household survey from which labor force
estimates are produced, selected housing units
remain in sample during a 16-month period. The
households are interviewed during the first 4 and
last 4 months of this period. These interview
months are referred to as month-in-sample
(MIS) 1 to 8.
Matching households between months allows
an analysis of the relationship between
nonresponse and estimates of the employment
rate. Since change in employment may be
related to the households participation, the
estimates of employment status may be affected.
A recent study by Tucker and Kojetin (1997)
showed that unemployment rates were related to
nonresponse in the CPS. Converts
(households that do not participate in the prior
month) do not completely make up for the
number of Attriters (households that do not
participate in the following month), so their
relative effect may not be offset. Moreover, they
may differ on important characteristics, e.g.;
race, ethnicity, or gender. The current study
examines the nature of this relationship through
an analysis of demographics and nonresponse
and their resulting effect on labor force
estimates.
Gross Flows
In this study gross flows uses the
availability of information on one month to
contrast the estimates from another month. For
example, labor force estimates in month 1 are
contrasted based on whether a household
responded in month 2, and labor force estimates
in month 2 are contrasted based on whether a
household responded in month 1. For example;
if the unemployment rate for month 1 is different
for households who continued to respond in
month 2 compared to those who did not respond,
and this was not balanced by a difference in the
other direction for those who responded in
month 2 but did not respond in month 1, then
some the estimates would be biased due to
nonresponse.
Design
The CPS is a the monthly household labor
force survey for the United States conducted by
the U.S. Census Bureau for the U.S. Bureau of
Labor Statistics. Approximately 48,000 eligible
households are sampled each month in a two-
stage clustered design. Households were
matched for the years 1996 through 1999.
Persons in the household who were not eligible
for the labor force (e.g. under 16 years old) were
excluded.
Analysis
The following tables are based on CPS
adjacent months-in-sample data weighted by the
base weight, which reflects the probability of
selection, but does not adjust for non-response.
Because of the differences in weighting, the
labor force estimates will not be comparable to
published estimates. The percentages reported
are relative to the other categories, not the
traditional unemployment rate, which is only
relative to those in the labor force. The Mantel-
Haenszel test provides a comparison of the
availability of the data (non-response status for
each month separately).
The Cochran-Mantel-Haenszel test provides a
test of the comparability of tables contrasting
months, and can be used as an indicator of the
gross flow effect. None of the p-values are
adjusted for multiple testing. The complex
sampling used by the CPS was not accounted for
in the p-values of the models.
Linear models provide a comparison of the
means for unemployment for a number of
demographic variables. The interaction of the
interview status variable (response or
nonresponse) and the flow variable (adjacent
months) gives an estimate of the gross flow.
Higher order interactions with the demographic
variables show if they are related to any bias
estimated by gross flows. Although none of the
p-values are adjusted for multiple testing, the
complex sampling is accounted for using the
SAS procedure surveyreg. The correlation
between months was ignored in the design.
Tables are provided for total nonresponse as well Any opinions expressed in this paper are those of the author and do not constitute policy of the Bureau of
Labor Statistics.
as for refusal and noncontact. The theory of
nonresponse suggests that different causes may
produce refusal and noncontact, but the
combined effect is also of interest here, since that
would produce the aggregate effect on estimates.
Results
An overall test of the impact of non-response
on labor force estimates was examined in Table
1 by comparing two 3 by 2 tables (labor force by
month). The 2nd month non-response was
related to the 1st month labor force status
(Mantel-Haenszel=172.009, p<0.001).
Unemployment and employment were higher
while those not in the labor force were lower for
the non-response group. Similarly, the 1st
month non-response was related to the 2nd
month labor force status (Mantel-Haenszel-
8.620, p<0.003). Employment was higher while
unemployment and not-in-labor-force were
lower. This difference between the two tables is
reflected in the Cochran-Mantel-Haenszel test
(623.421, df=2, p<0.0001) which contrasts the
rows of the two tables. The gross flow of
employment status from month to month is
impacted by non-response, with unemployment
reversing direction depending on whether the
non-response occurred in the first or second
month.
Table
1
Labor Force Status by Interview Status
1
st
Month Labor Force
2
nd
Month interview
2
nd
Month nonresponse
Not in labor force
34.48%
30.08%
Employed
62.08%
65.95%
Unemployed
3.43%
3.98%
Mantel-Haenszel=
632.373, p<
0.0001
2
nd
Month Labor Force
1
st
Month interview
1
st
Month nonresponse
Not in labor force
34.57%
31.46%
Employed
62.02%
65.00%
Unemployed
3.41%
3.54%
Mantel-Haenszel=
365.398, p<
0.0001
Cochran-Mantel-Haenszel (row mean scores)=
2098.591 (df=2) p< 0.0001
A simpler form of the gross flow matrix using just the
unemployed relative to the employed would be:
Table 2

Interview
Status

I N All

unem-unem-unem-
prat prat prat

Mean Mean Mean

flow

Month 1 0.0680.0730.068

Month 2 0.0700.0690.070

All 0.0690.0710.069

In this table the unemployment ratio relative to
employed was contrasted by whether they were
interviewed in the adjacent month or not. This
shows the higher unemployment rate of those
who dropped out relative to those who stayed in.
Those who converted the second month had a
lower unemployment rate. Because more
dropped out than were converted, the impact is
almost entirely from the dropouts. This simpler
table makes the display of effects relative to
unemployment clearer for more complex gross
flows. It also shows that the interviewed persons
(I column) have the same rates as the aggregate
column (ALL) which adds in the estimated effect
for nonresponse (N column). This lack of effect
on the estimates is due to the very small amount
of nonresponse in the CPS. These numbers are
weighted by the baseweight, which adjusts for
the design, but doesnt adjust for nonresponse.
The nonresponse adjustment would reduce the
effect further. Models which estimate
parameters for the tables presented here are in
Appendix A (available in the long version of this
paper). Any opinions expressed in this paper are those of the author and do not constitute policy of the Bureau of
Labor Statistics.
Table 3: Type of nonresponse effect
.

Nonresponse Type

I N R All

unem-unem-unem-unem-
prat prat prat prat

Mean Mean Mean Mean

flow

Month 1 0.0680.0830.0670.068

Month 2 0.0700.0760.0650.070

All 0.0690.0800.0660.069

Table 3 shows the flow relative to the type of
nonresponse (I: interview, N: noncontact, R:
refusal). Refusals show lower unemployment
while noncontact shows higher unemployment.
The effect would tend to cancel one another out,
reducing the bias problem. Noncontact shows a
stronger effect.
Table 4a: Gender effects
.


Interview Nonresponse

SEX SEX

M F M F

unem-unem-unem-unem-
prat prat prat prat

Mean Mean Mean Mean

flow

Month 1 0.0630.0720.0760.083

Month 2 0.0650.0750.0680.075

The gross flows relative to gender shows higher
unemployment for attrition, but a negligible
effect for those who responded in the second
month in sample. The effect appeared consistent
for both genders.
Table 4b: Gender effects
.

SEX

Male Female

Nonresponse type Nonresponse type

I N R All I N R All

unem-unem-unem-unem-unem-unem-unem-unem-
prat prat prat prat prat prat prat prat

Mea