138

Table 11. Consumer unit income

Journal of Official Statistics

Variables: Recall effects in Qtr 843 and income.

CU income before taxes
Less than U.S.$15000
U.S.$15 000-30 000
U.S.$30.000 or more
Reported incompletely

Jackknifed chi-square test
CU income before taxes

Apparel recall effects

None Moderate Great
Standardized values

1.43 —4.97 2.81

0.34 0.99 — 1.65
— 0.88 5.10 —4.18
—0.46 —1.71 1.97
Test value DF

6.1 6

income, and this is often considered an indi-
cation of lower cooperation to the survey.

4.4. Interview aspects

Specific subsets of respondents were selected
to facilitate the analysis of variables dealing
with interview aspects. Husband-wife con-
sumer units were analyzed in terms of who
participates as respondent, whether the
husband, the wife, or both; (the few cases
that did not have either spouse as the main
respondent were excluded). This model
takes into account the respondent’s age,
collapsed in two levels: less than 40 years
old, and 40 and over (values shown for this
level). The presence or absence of other
members in the CU is another variable in
the model. (See Table 12.)

The effect of CUs with old respondents
and scant reports, which accentuates the
extremes of the recall variable, is reduced in
this model, due to the specific set of families
selected. A significant relationship shows
that respondents in the 40 and over age
group tend to exhibit greater recall effects
than respondents in the younger age group.

Husband-wife CUs exhibit moderate
recall effects if both husband and wife
participate, and no effects if only the
husband does. The interactions of the

independent variables (values not shown)
indicate the wife alone (more often in the
younger age group) is more likely to be the
respondent for CUs with children or others,
whereas both spouses are more likely to
answer in husband-wife CUs with no other
members.

The number of respondents and the use of
records were tested simultaneously in
another model for CUs (of any type) with
more than one member (Table 13). Reports
with more than one respondent tend to be
associated with relatively higher (moderate)
effects when compared to reports by a single
respondent; moderate recall effects are also
associated with the use of records. Other
interactions in this model (values not
shown) indicate that records are more likely
to be used by CUs with two people when
compared to CUs of other sizes, and when
more than one respondent participates.

5. Conclusions

The findings confirm the fact that recall
effects in surveys are not a sole function of
recency; the type of respondent, the family
setting and the resultant level of interest
affect the quality of responses. It is also
evident that in order to have an effective
interview in reporting family expenses, a


Silberstein: Recall Effects in the U.S. Consumer Expenditure Interview Survey

Expenses reported for the “current
month” in one wave refer to an overlap
period with the third recall month of
the next wave, which is usually not well
reported. Interviews conducted late in the
month capture many of these expenses and
this tends to produce higher reports in the
next wave; as Table 4 shows, these inter-
views (OTHER) have higher means and
lower first month “bias” ratio. The lowest
bias and the highest mean expenditure were
observed when the previous interview was in
the second half of the month and the current
interview was in the second week of the
month; this is also one of the shortest
reporting periods, not surprisingly.

3.2. Independent variables

The topic of respondent effects in survey
methodology involves many issues: dif-
ferential understanding of the response task
and varying degree of motivation in answer-
ing survey questions are just two examples.
The study of these effects tends to produce
results bound to a specific survey setting.
Sudman and Bradburn (1977) point out that
age of respondent might be expected to be
the major characteristic related to memory
error variation, but several interview con-
ditions tend to reduce these effects. Cannel,
Marquis, and Laurent (1977) reported that
forgetting curves were similar for both male
and female respondents in hospitalization
surveys that were validated by record
checks; self-reports appeared less affected
by recall bias than reports given by another
family member, while age and education
were found to yield less conclusive results.

The direction of the relationship of a
specific variable to reporting quality may
reflect the survey subject matter and
administration. Response from young
people (college age) as well as from the

129

elderly (65 and over) appear to be of lower
quality in the U.S. Diary Survey (Tucker
(1986)). Attempts have been made to pro-
vide generalized results from several
surveys. Andrews and Herzog (1986) con-
cluded that older respondents tend to give
less precise answers, judging from a study of
six opinion surveys that included method-
ological supplements.

Certain variables, especially the age
distribution, are sensitive to exclusions due
to the scope of the study. Weighted percent
distributions of the major variables are
given in Table 5. About 40% of respondents
less than 25 years old did not participate in
the previous wave, due mainly to mobility;
this group decreased from 10% to 7% of the
total, as a result. Older respondents (65
years old and over) presented a different
situation: only 6% did not participate in a
previous wave, but 26% did not report any
apparel expenses (compared to 13%, on
average).

The number and type of respondents, and
record usage are variables pertaining to
interview aspects of the recall process.
Record usage refers to use of records during
the interview rather than to a_ specific
questionnaire section. It can be assumed
that if no records are used, the recall process
for all sections is done without records. The
use of records eliminates telescoping effects
and tends to decrease omissions (Sudman
and Bradburn (1977)).

3.3. Models

Log-linear models were fitted to the cross-
classified, categorical data using the com-
puter program “Contingency Table Analy-
sis for Complex Sample Designs (CPLX)”
developed by Fay (1987); the program com-
putes maximum likelihood estimates of the
parameters and their standard errors. Many


142
Science and Technology”, Source
Materials, Vol. 2. National Science

Foundation. Washington, D.C.

Tucker, C. (1986): An Analysis of the
Dynamics in the CE Diary Survey.
American Statistical Association,
Proceedings of the Survey Research
Methods Section, pp. 18-27.

Journal of Official Statistics

Turner, C.F. and Martin, E. (1984): Survey-
ing Subjective Phenomena. Russel Sage
Foundation, New York.

U.S. Bureau of Labor Statistics (BLS)
(1986): Consumer Expenditure Survey:
Interview Survey, 1984. Bulletin 2267.

Received November 1987
Revised February 1989


134

grouped in two levels, first half and second
half of the month (values shown for the
second). CUs interviewed later in the month
in the previous wave exhibit no recall effects
in the current wave (z = 2.33). By contrast,
great recall effects are exhibited when the
previous interview was in the first half of the
month. Opposite results can be seen for the
interview week of the current wave.

4.2. Apparel and house furnishings effects

The relationship of recall effects in two parts
of the questionnaire, apparel (Section 9) and
house furnishings (Sections 6 to 8), was
tested in a model that included previous and
current week of interview, as controls. (See
Table 7.)

It was expected that recall effects would
be less for house furnishings than for
apparel, since that category comprises
several salient large expenditure items. The
interaction between the two categories
shows a consistent direction: moderate
apparel recall effects are exhibited when
house furnishings are reported with
moderate or no recall effects. When no
house furnishing expenses are reported,
greater recall effects for apparel are
observed.

4.3. Respondent characteristics

Significant relationships with recall effects
were found for age and education of respon-
dent, but not for sex or race of respondent.
Respondents between the ages of 25 and 44
exhibit moderate effects, whereas older
respondents (65 and over) exhibit either no
effects or extreme effects. No significant
relationships were noted for other age
groups (less than 25, 45 to 54, and 55 to 64).
Respondents with less than high school edu-
cation are the most likely to exhibit great
recall effects, respondents with more than

Journal of Official Statistics

high school education are the least likely to
exhibit these effects.

Age and education were tested simul-
taneously, and their effects were both sig-
nificant, as shown in Table 8. The inter-
action of age and education indicates that
less than high school education is highly
correlated with older respondents, as
reported in other studies. This relationship
is reflected in the results: no recall effects are
evident for older respondents when the
model controls for education. The noted
results for education, instead, are retained in
this model.

The respondent’s family setting is impor-
tant in relationship to recall effects; size and
type of the consumer unit are especially
noteworthy. The findings suggest what
seems logical: it is easier to report when
fewer family members are involved, and
more difficult when there are more mem-
bers. No effects are exhibited by CUs with
one or two members, moderate effects are
exhibited by CUs with three or four mem-
bers, and moderate to great effects can be
observed for larger families (Table 9).

Moderate effects are likely in reports by
husband-wife families with children or
other members. No recall effects are more
likely for single-person and husband-wife
CUs without any other members. These
relationships are maintained when the
expenditure level and interview week are
included as control variables (Table 10).

Other CU characteristics are associated
to recall effects. The relationship to home
tenure suggests that renters exhibit greater
effects than home owners do. Recall effects
appear to differ by family income. As
Table 11 shows, greater recall effects are
experienced by CUs with lower incomes.
CUs with incomplete income reporting are
also associated with greater effects; these
reporters refuse to disclose major sources of


Silberstein: Recall Effects in the U.S. Consumer Expenditure Interview Survey

sources are available describing log-linear
models (Bishop, Fienberg, and Holland
(1975), Goodman (1978) and Fienberg
(1980)). ““CPLX interprets these models as
statements about the proportions in the
underlying population from which the
sample is drawn” (Fay (1987), 1.1), and is
designed for analysis of data derived from
complex sample surveys. Weighted fre-
quencies were derived with the method of
balanced repeated replication. This method
takes into account design effects, and is one
of the options in CPLX; the 1984 Interview
Survey had 20 half-sample replicates.

Following an analysis of the individual
relationships of the independent variables to
recall effects (test of independence), models
were developed using sets of variables found
to be significantly related to recall ‘effects,
adding interaction terms up until a good fit
was obtained. The overall fit of a model and
the contribution made by additional par-
ameters were tested through the jackknifed
chi-square tests developed by Fay (1985).
The three and four variable models shown
below were used in the analysis

log (Fin,) = & + AE + AY

HO + GT HOA OM
and
log Fink) = ht Ai + Ay + + OE

JH 4 QIK 4 QHK
uh te + i

FORE bay tO + ME
where i is the dependent variable, j, h, and k
are independent variables.

The models measure the type of inter-
actions of each independent variable with
the dependent variable, after eliminating the
effects of the interactions between the
independent variables. No more than three
independent variables were included in any

131

model, due to sample size limitations; zero
frequencies were not allowed in the com-
plete cross-classification, although this is
not a requirement in CPLX.

Most of the findings were derived from
models fitted to apparel data since a larger
sample was available for that category. Test
results are displayed in Tables 6 to 13; with
the exception of Table 6, which pertains to
recall effects in two consecutive quarters, the
tables refer to Qtr 843. Standardized values
for the significant interaction terms involv-
ing the dependent variable are shown in
the tables; these values are the ratios of
parameter estimates to their estimated
standard errors.

Some variables were defined in a dichot-
omous way, and the standardized values are
only shown for one of the levels; the level
not shown has the opposite sign. Standard-
ized values {z| = 1.96 or larger can be con-
sidered significant at the .05 level. Critical
values (.05 level) for the jackknifed chi-
square test are: 1.5 for DF = 2to9, and 1.6
for DF = 10 to 20.

4. Test Results

4.1. Previous and current waves

Recall effects for the same respondents in
two consecutive waves were compared; data
for the second wave were excluded in this
test, since the previous wave for those
reports was the first wave. The results,
shown in Table 6, indicate that consistent
‘recall effects can be expected from one wave
to the next, especially for respondents with
moderate recall effects (z = 4.0). CUs that
do not report apparel expenses in the
previous wave exhibit greater recall effects
in the current wave.

The relationship of week of previous and
current interviews to recall effects is signifi-
cant, as expected. The interview weeks were


Journal of Official Statistics

130

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Silberstein: Recall Effects in the U.S. Consumer Expenditure Interview Survey

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Journal of Official Statistics
Vol. 5. No. 2, 1989, pp. 125-142
Statistics Sweden

Recall Effects in the U.S. Consumer Expenditure
Interview Survey!

Adriana R. Silberstein’

Abstract: The three month recall of apparel
and house furnishing expenses from the
1984 U.S. Consumer Expenditure Interview
Survey is analyzed by type of respondent.
Main effects and interactions are tested
for such variables as family type, age of
respondent, and use of records, with a
dependent variable derived by comparing
the expenses reported for the most recent

1. Introduction

The U.S. Consumer Expenditure Interview
Survey is an ongoing panel survey collecting
expenditure data from a national sample of
households interviewed five times at three
month intervals (waves). The interview
covers all household expenditures in great
detail, for the most part. Only summary
questions are asked for frequently pur-
chased items, such as food items, which are
collected in detail by a diary method with a
separate sample of households. Panel effects
due to repeated interviews have been found
to be small, but recall effects are evident.

* An earlier version of this article was presented at the
Annual Meeting of the American Statistical Associ-
ation, San Francisco, 1987.

? Mathematical Statistician, Office of Prices and Living
Conditions, Statistical Methods Division, U.S. Bureau
of Labor Statistics, Washington, D.C. 20212, U.S.A.

Acknowledgements: Thanks are extended to Clyde
Tucker, Stuart Scott, the referees, and David Mingay
for their helpful comments.

month to expenses reported for the three
month period; the variable is interpreted as
an indicator of potential underreporting.
Results show that significant variation can
be expected in the degree this phenomenon
manifests itself with different respondents.

Key words: Response error; expenditure
data; type of respondent.

These effects were analyzed at the macro-
level in a study by Silberstein and Jacobs
(1989).

This article discusses differential effects in
quality of responses. The study analyzes
data reported in 1984 for two expense
categories, apparel and house furnishings,
using log-linear models. The task of report-
ing this type of expenses, while easily
understood by the respondents, is often
difficult for a three month recall period. The
general conclusions from the study are that
recall effects tend to be consistent from one
wave to the next and are likely to be
heightened by certain interview and respon-
dent characteristics.

Section 2 describes relevant aspects of the
response process and major factors affecting
quality. In Section 3, the model method-
ology and the variables used are discussed.
Section 4 reports on the findings, and
Section 5 concludes.


Journal of Official Statistics

136

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135

Recall Effects in the U.S. Consumer Expenditure Interview Survey

Silberstein

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Journal of Official Statistics

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128

Journal of Official Statistics

Table 3. Number of items reported: Apparel (Qtr 843)

Number of Number of Distribution by recall effects Ist month
records! CUs ratio?
% None Moderate Great
ALL 3408 100 45 29 27 128
1 333 100 53 ~ 47 130
2to4 994 100 44 21 35 141
5Sto9 876 100 46 30 24 134
10 to 19 806 100 41 39 20 125
20+ 399 100 41 49 10 124

' One record may include multiple purchases when the same type of item is reported for the

same person and month.

? Percent ratio of first month expenses to three-month average.

expenses or comprised up to about a third of
the reported expenses. A fourth level,
EXTREME, was included in some models:
it separates CUs that reported expenses only
for the first recall month (half of the CUs in
the third level).

The variable is referred to as recall effects,
rather than recency effects, as otherwise
called (Biderman and Linch (1981)), to
emphasize the complexity of the recall task.
While it is difficult to interpret the recall
variable in terms of quality, it seems reason-
able to assume that greater recall effects are
symptomatic of greater underreporting.
Greater effects were found for respondents
(in bounded interviews) that did not report
for the whole length of the panel, compared
to reporters in all five waves.

Two reporting aspects appear to influence
the dependent variable directly: the number
of expenses and the interview week. The
fewer items purchased the easier recalling
should be. However, it is apparent that
recall effects tend to decrease with increas-
ing number of items reported (Table 3). A
more even distribution by recall month
results when more expenses are reported,
partly due to the fact that more than one
month is often involved. The data in this
table refer to the number of “records.” A
record may include multiple purchases when
the same type of item is reported for the
same person and month. A categorical vari-
able derived by using this variable, rather
than the dollar value, produced consistent
results in the analysis.

Table 4. Interview week of previous wave: Apparel (Qtr 843)

Interview week Number of — Total 3rd recall month

of previous CUs

wave Monthly lst month Monthly Collected in
mean ratio! mean previous
expenditure expenditure wave

Total 3408 U.S.$102 128 U.S.$78 39%

FIRST 1418 90 132 60 17%

SECOND 1154 108 135 82 36%

OTHER 836 114 115 104 64%

' Percent ratio of first month expenses to three-month average.


139

Silberstein: Recall Effects in the U.S. Consumer Expenditure Interview Survey

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Silberstein: Recall Effects in the U.S. Consumer Expenditure Interview Survey

considerable effort is required, through
record consultation and by participation of
more than one family member. The analysis
is suggestive of the potential effects on esti-
mates derived from recall data.

Reports with most of the expenses relat-
ing to the first recall month are symptomatic
of greater degrees of underreporting. An
example of a family characteristic associ-
ated with this problem is the size of the
family: greater recall effects are found for
larger families. By contrast, no recall effects
are apparent for single and two member
CUs, and this can be interpreted as a con-
sequence of an easier recall process. Edu-
cation of the respondent tends to affect
reporting quality, separately from age of
respondent; the least educated respondents
tend to report with greater recall effects.

Underreporting appears to be present
even under the best interview conditions,
e.g., when more than one respondent
participates and some records are used
during the interview. These reports show
moderate recall effects, rather than no recall
effects; however, reports with moderate
effects display the highest mean expenditure
levels. Husband-wife families with children,
home owners, and respondents between the
ages of 25 and 44 are associated with these
response patterns. This seems to imply that
respondents with relatively more (apparel)
expenses attempt to report more completely
than respondents with less involvement in
these expenses, while still underreporting for
the early portion of the reference period.

6. References

Andrews, F.M. and Herzog, R. (1986): The
Quality of Survey Data as Related to Age
of Respondent. Journal of the American
Statistical Association, 81, pp. 403-410.

Biderman, A.D. and Linch, J.P. (1981):

141

Recency Bias in Data on Self-Reporting
Victimization. | American Statistical
Association, Proceedings of the Social
Statistics Section, pp. 31-40.

Bishop, Y.M.M., Fienberg, S.E., and Hol-
land, P.W. (1975): Discrete Multivariate
Analysis. MIT Press, Cambridge, MA.

Cannel, C.F., Marquis, K.H., and Laurent,
A. (1977): A Summary of Studies of Inter-
viewing Methodology. National Center
for Health Statistics, Vital and Health
Statistics, 2, 69.

Goodman, L.A. (1978): Analyzing Quali-
tative/Categorical Data. MIT Press,
Cambridge, MA.

Fay, R.E. (1985): A Jackknifed Chi-Square
Test for Complex Sample Surveys.
Journal of the American Statistical
Association, 80, pp. 148-157.

Fay, R.E. (1987): Contingency Table
Analysis for Complex Surveys (CPLX),
Program Documentation. Washington
Statistical Society Short Course,
Washington, D.C.

Fienberg, S.E. (1980): The Analysis of
Cross-Classified Data. MIT Press, Cam-
bridge, MA.

Moss, L. and Goldstein, H. (1979): The
Recall Method in Social Surveys. Uni-
versity of London, Institute of Education,
NFER Publishing Co., Great Britain.

Silberstein, A.R. and Jacobs, C.A. (1989):
Symptoms of Repeated Interview Effects
in the Consumer Expenditure Interview
Survey. In Panel Surveys, D. Kasprzyk,
G. Duncan, G. Kalton, and M.P. Singh,
eds., Wiley, New York.

Sudman, S. and Bradburn, N.M. (1977):
Response Effects in Surveys: A Review
and Synthesis. Aldine, Chicago, IL,
pp. 81, 92.

Tanur, J .M. (1981): Advances in Methods
for Large-Scale Surveys and Experi-
ments. In “The 5-Year Outlook on


Silberstein: Recall Effects in the U.S. Consumer Expenditure Interview Survey

127

Table 1. Percent CUs with no expenses in category by recall month

Apparel House furnishings
Qtr: 842 843 842 843

CUs with expenses in three month period 3461 3408 2745 2762
Recall month: % % % %
FIRST 16 17 28 29
SECOND 33 31 45 40
THIRD 41 39 48 45

bounding interview. Expenses reported for
the previous month of the first wave are not
used in the estimates since they are thought
to include expenses incurred in prior months
(as a result of forward telescoping). The
second through fifth waves have three
month recall periods. The reporting period
includes the portion of the current month up
to the interview day; expenses reported for
that month are made available to the inter-
viewer in the following wave, to minimize
duplicate reporting.

3. Methodology

3.1. The dependent variable

The study is based on respondents in two
consecutive waves (90% of all respondents);
CUs that do not participate in a previous
wave experience an unbounded interview.
All data pertain to the urban population.
Study cases are reporters in waves two to

five with at least one expense in the cat-
egories analyzed: 3408 for apparel and 2762
for house furnishings in the third quarter of
1984 (Qtr 843). This quarter, covering
expenses made between April and August,
excludes major seasonal shopping peaks
which would affect comparisons by month.
Table 1 shows how reports with no expenses
are less frequent in the first (most recent)
month compared to the other two months.

The models’ dependent variable is a
categorical variable derived by grouping
CUs according to the expenses (the dollar
value) reported for the first recall month as
percentage of the total expenses reported for
the three recall months. These recall effects
are subdivided into three levels: NONE -0
to 35%, MODERATE - 35% to 75%, and
GREAT-75% to 100%. The distributions
and the mean expenditures are given in
Table 2. The first level indicates that no
recall effects could be observed, since the
first recall month had cither no reported

Table 2. Dependent variable: Recall effects (Qtr 843)

Apparel % CUs Monthly House % CUs Monthly
mean furnishings mean
expenditure expenditure

Recall effects: n = 3408 Recall effects: n = 2762

Total % US.$102 Total % U.S.$141
NONE 44 106 NONE 53 146
MODERATE 29 125 MODERATE 18 163
GREAT 27 7 GREAT 29 119



126

2. Response Process

Recall bias results from the selective recol-
lection of past events: less recent and less
salient events tend to be reported less com-
pletely than more recent or more salient
events. The error is generally greater for
longer reporting periods, and is usually
compounded by “forward telescoping,” i.e.,
a tendency to postdate events when report-
ing them. Certain aspects of the interview,
e.g., respondent fatigue and level of interest,
are widely recognized as primary factors
influencing the retrieval and reporting of
retrospective information. (See Tanur
(1981), Turner and Martin (1984), Moss and
Goldstein (1979).)

Figure 1 illustrates in general terms
various elements of the response process.
The respondent’s attitudes and cooperation
are affected by the type of survey and the
interview procedures; the survey content
and complexity influence the respondent’s
motivation and ability to report accurately.
The interaction between these factors varies

Journal of Official Statistics

by respondent, family, and interview
characteristics, thus differences in data
quality may result.

Major factors in an expenditure interview
survey are the respondent’s knowledge of
the family’s expenses, the length of the
recall period, and the expense records avail-
able during the interview. The respondents
to the Interview Survey answer a single
questionnaire covering all pertinent mem-
bers. There is no set procedure for the choice
of respondents; more than one person may
participate, depending on cooperation.

The unit of analysis is a consumer unit
(CU), which includes those members of a
household who are either related or pool
their income to make joint expenditure
decisions (U.S. Bureau of Labor Statistics
(1986)). More than one CU may be identi-
fied within a sampled household, and report
separately in the panel; new CUs may move
into the sampled household after the begin-
ning of the panel.

The first wave, with one month recall, is a

Introductory letter Respondent Socioeconomic
Phone calls attitudes factors
Type of survey Motivation Family
Content and behavior
Instrument ability to and
Interview aspects report recordkeeping

Data quality

Fig. 1.

Response process


137

Silberstein: Recall Effects in the U.S. Consumer Expenditure Interview Survey

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Journal of Official Statistics

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