The Midyear CE Data Quality Profile -

2021

April 29, 2022

Grayson Armstrong, Gray Jones, Tucker Miller, and Sharon Pham

Consumer Expenditure Surveys Program Report Series
Contents

Overview.............................................................................................................................................1

Highlights............................................................................................................................................2

1. Final disposition rates of eligible sample units (Diary and Interview Surveys)......................................................3

2. Records Use (Interview Survey)..............................................................................................................9

3. Information Bookletuse (Diary and Interview Surveys)............................................................................... 11

4. Expenditure edit rates (Diary and Interview Surveys) ................................................................................. 15

5. Income imputation rates (Diary and Interview Surveys).............................................................................. 19

6. Respondent burden (Interview Survey) .................................................................................................. 23

7. Survey mode (Interview Survey)........................................................................................................... 25

8. Survey Response Time (Diary and Interview Surveys)................................................................................. 28

Conclusion......................................................................................................................................... 31

References........................................................................................................................................ 32
Consumer Expenditure Surveys - 2021 Data Quality Profile | 1

Overview

The Bureau of Labor Statistics (BLS) is committed to producing data that are of consistently high quality (i.e., 

accurate, objective, relevant, timely, and accessible)in accordance with Statistical Policy Directive No. 11. This 

Directive, issued by the Office of Management and Budget, affirms the fundamental responsibilities of Federal 

Statistical Agencies, and recognized statistical units in the design, collection, processing, editing, compilation, 

storage, analysis, release, and dissemination of statistical information. The BLSConsumer Expenditure Surveys 

(CE) program provides data users with a variety of resourcesto assist them in analyzing overall CE data quality. 

CE data users can evaluate quality on their own by utilizing the following:

• Standard errors provided for the official CE tables.

• BLS-provided CE response rates(provided for all BLS household surveys).

• Published data comparisons between CE and other household survey estimates.

• Published results of nonresponse bias studies.

• CE Public-use microdata datasets with variables and flags necessary to create quality metrics.

In addition, the Data Quality Profile (DQP) provides a comprehensive set of quality metrics that are timely, 

routinely updated, and accessible to users. For data users, DQP metrics are an indication of quality for both the 

Interview Survey and the Diary Survey. For internal stakeholders, these metrics signal areas for improvements 

to the surveys.

This DQP includes, for each metric, a brief description of each metric, along with the results, which are 

tabulated and graphed. The DQP Reference Guide (Armstrong, Jones, Miller & Pham 2022) gives detailed 

descriptions of the metrics, computations, and methodology.

Prior DQPs are available on the CE External Research Library Page. BLS began publishing DQPs every year 

beginning with the 2017 data, though prototype DQPs are available for 2013 and 2015. Midyear DQPs started 

with the 2020 midyear data release.

The data quality metrics are reported in quarterly format, where the quarter is the three-month period in 

which the survey data were collected. For example, “2021q1” refers to the surveys fielded in the months of 

January, February, and March of 2021. Because the respondents to the Interview Survey are asked to recall 

their expenditures from the prior three months, the data collected in 2021q1 correspondto expenditures 

made in 2020q4. In contrast, respondents to the Diary Survey report expenditures on the days they were 

transacted. This is the reason why the Interview Survey metrics appear to be “ahead” of the Diary Survey by a 

quarter (e.g., 2021q3 for the Interview Survey and 2021q2 for the Diary Survey). Where annual rates are used 

to describe metric trends in this report, the annual rate was computed as the average of quarterly rates from 

the same calendar year weighted by the number of consumer units in that quarter. 

1 The Office of Management and Budget has oversight over all Federal surveys and provides the rules under which they 

operate. See the Federal Register noticefor moredetails.
Consumer Expenditure Surveys - 2021 Data Quality Profile | 2

Highlights

In this section, we highlight some of the metric trends from the past three years. This time frame covers 

the final quarters of the 2018 collection period to the first quarters of the 2021 collection period. 

Because the respondents to the Interview Survey are asked to recall their spending over the prior three 

months, data collected in one calendar quarter include some expenditures made in the prior quarter. 

Hence, the Interview Survey metrics in this profile cover the data collection time period of 2018q4 

through 2021q3, which includes expenditures transacted from 2018q3 to 2021q3. Respondents to the 

Diary Survey are asked to report their spending as it occurs, so Diary Survey metrics in this profile cover 

the time period of 2018q3 through 2021q2. Subsequent sections describe the individual metrics with 

detailed data tables.

Recent Trends of Note:

• The final disposition rate for the Diary Survey has continued to recover following the onset of the COVID19 pandemic in March 2020. 

• Use of the Information Bookletfor both the Interview and Diary Surveys have continued to improve after 

falling substantially in 2020q2. 

• Despite a slight increasein 2021q2,the rate of respondents who report perceiving noburden has also 

generally declined.
Consumer Expenditure Surveys - 2021 Data Quality Profile | 3

1. Final disposition rates of eligible sample units (Diary and Interview Surveys)

Final disposition rates of eligible sample units report the final participation outcomes of field staff’s 

survey recruitment efforts. The BLS classifies the final outcome of eligible sample units into the 

following four main categories: 

1. Completed interview

2. Nonresponse due to refusal

3. Nonresponse due to noncontact

4. Nonresponse due to otherreasons

Completed interviews reclassified to a nonresponse by BLS staff are included within the other 

nonresponse category and are presented in the nonresponse reclassification tables (Tables 1.2 and 1.4). 

More information on the nonresponse reclassification edit, along with information on how we calculate 

response rates can be found in the DQP Reference Guide (Armstrong, Jones, Miller, and Pham, 2022). 

The key point of interest regarding response ratesis that low response rates canindicate nonresponse 

bias of an expenditure estimate if the nonresponse is correlated with that expenditure category. While 

recently published research on nonresponse bias has not shown statistically significant bias in the CE 

survey estimates during the COVID 19 pandemic (Ash, Nix, and Steinberg, 2022), BLS continues to 

monitor this risk. 

In addition, higher response rates are preferred for more precise estimates. We present unweighted 

response rates in this report because unweighted rates measure the effectiveness of our data collection 

efforts. When we previously calculated weighted response rates, they showed no meaningful difference 

from the unweighted rates.

Diary Survey Summary

• In March 2020, the Census Bureau suspended in-person diary placement interviews due to the COVID-19 

pandemic, causing response rates to drop to 26.1 percent in 2020q2 (Table 1.1). Since then, response 

rates have slowly recovered, rising to 42.5 percent in 2021q2 (Table 1.1). Overall, response rates declined 

15.3 percentage points from 57.8 in 2018q3 to 42.5 in 2021q2 (Table 1.1).

• Refusal rates contributed most to the decline in response rates with an increase of 10.1 percentage points 

from 24.8 to 34.9 percent (Table 1.1).

• Noncontact rates rose 2.6percentage points from 6.2 to 8.8 percent (Table 1.1).

• Other nonresponse rates increased by a modest 2.6 percentage points overall from2018q3to 2021q3 but 

rose outside of the normal range to 26.3 percent in 2020q1 and jumped to a historical high of 59.1 

percent in 2020q2 (Table 1.1). This was largely driven by othernonresponse reclassifications,which 

increased by 3,205 cases between 2019q4 and 2020q2, as the BLS reclassified a large number of
Consumer Expenditure Surveys - 2021 Data Quality Profile | 4

interviews from ineligible to eligible nonrespondents at the start of the COVID-19 pandemic (Table 1.2).

Other nonresponse rates fell from 2020q3 to 2021q2, but remained relatively high until 2021q2 when 

they settled back to 13.8 percent(Table 1.2)2

Graph 1.1Diary Survey Final Disposition Rates 

2 Many respondents could not be reached by telephone because interviewers did not have a working

telephone number for the respondent. Interviewers were instructed to classify these cases as ineligible

nonrespondents and BLS elected to reclassify the majority as eligible other nonrespondents. For more

information on this nonresponse reclassification, see the DQP Reference Guide(Armstrong, Jones, Miller, and 

Pham, 2022).
Consumer Expenditure Surveys - 2021 Data Quality Profile | 5

Table 1.1 Diary Survey: distribution of final dispositions for eligible sample units

(unweighted)

Row percentage

Quarter Number of 

eligible 

sample units

Interview Refusal Noncontact Other 

Nonresponse

2018q3 5,014 57.8 24.8 6.2 11.2

2018q4 5,072 51.5 27.9 7.3 13.3

2019q1 4,926 54.2 28.5 4.9 12.4

2019q2 5,082 53.4 27.2 6.1 13.2

2019q3 5,020 54.7 25.8 6.1 13.4

2019q4 5,216 48.9 29.9 7.6 13.5

2020q1 7,474 44.0 22.5 7.3 26.3

2020q2 7,409 26.1 12.1 2.7 59.1

2020q3 7,784 32.9 22.2 7.2 37.7

2020q4 7,774 36.5 34.7 10.1 18.8

2021q1 7,488 39.4 34.4 7.6 18.6

2021q2 7,584 42.5 34.9 8.8 13.8

Table 1.2 Diary Survey: prevalence of nonresponse reclassifications

Number of nonresponse reclassifications

Quarter Number of 

eligible sample 

units

Total 

reclassifications

COVID 19 

reclassifications

Other 

reclassifications

2018q3 5,014 247 0 247

2018q4 5,072 205 0 205

2019q1 4,926 232 0 232

2019q2 5,082 243 0 243

2019q3 5,020 229 0 229

2019q4 5,216 188 0 188

2020q1 7,4743 855 562 293

2020q2 7,411 3,393 3,202 191

2020q3 7,784 250 34 216

2020q4 7,774 248 10 238

2021q1 7,488 374 2 372

2021q2 7,584 353 0 353

3

 The Diary Survey’s sample size increased in 2020q1 to support the Consumer Price Index’s Commodities and

Services Survey sample frame.
Consumer Expenditure Surveys - 2021 Data Quality Profile | 6

Interview Survey Summary

• In March 2020, the Census Bureau suspended all in-person interviews due to the COVID-19 pandemic.

Post suspension response rates fell 6.3percentage points from 2020q1to 2020q2 (Table 1.3). Since then, 

this rate hasstagnated, only increasing from 45.9 to 46.1 percent between 2020q2 and 2021q3, still well 

below pre-pandemic levels(Table 1.3).

• Refusal rates generally rose, being 8.3 percentage points higher in 2021q3 (43.0 percent) than in 2018q4 

(34.7 percent);however,they were sharply lower in 2020q2 and 2020q3 due to a large jump in the 

number of COVID-19 pandemic related other nonresponse cases(Table 1.3).

• In the quarters prior to 2020q2, noncontact rates remained fairly steady butfell to near zero in 2020q2 

(0.8 percent) due to the onset of the COVID-19 pandemic and the resulting large increase in the number 

of other nonresponse cases. Noncontact rates rose back to 4.0 percent in 2020q3, but in the subsequent 

quarters (2020q4 to 2021q3), continued to increase past the pre-pandemic norm(Table 1.3).

• Other nonresponse rates declined from 5.0 in 2018q4 to 2.5 in 2021q3, a significant drop from 37.9 

percent in 2020q2 due to COVID-19 reclassifications at BLS (Table 1.3). Eventually, the COVID-19 

reclassifications declined to 0 due to the BLS transferring the reclassification process to the Census Bureau

in 2021q2.4

4 It should also be noted that in the nonresponse reclassification tables, the COVID 19 reclassifications dropped to 

zero for both the Diary Survey and the Interview Survey in 2021q2 due to the Census Bureautaking over the 

reclassification process.Now, BLS receives the data with the correct final outcomes, so there is no in-house 

reclassification process that would present itself in these tables.
Consumer Expenditure Surveys - 2021 Data Quality Profile | 7

Graph 1.2 Interview Survey Final Disposition Rates 

Table 1.3 Interview Survey: distribution of final dispositions for eligible sample 

units(unweighted) 

Row percentage

Quarter Number of 

eligible 

sample units

Interview Refusal Noncontact Other 

nonresponse

2018q4 10,161 54.8 34.7 5.5 5.0

2019q1 10,108 55.6 34.3 4.8 5.2

2019q2 10,075 54.5 35.5 5.0 5.0

2019q3 10,036 53.2 36.5 5.6 4.8

2019q4 10,170 51.6 36.8 6.1 5.5

2020q1 9,956 52.2 33.8 4.7 9.3

2020q2 10,581 45.9 15.4 0.8 37.9

2020q3 11,189 44.5 24.2 4.0 27.4

2020q4 11,185 46.5 36.8 6.3 10.4

2021q1 11,125 46.0 38.9 6.8 8.3

2021q2 11,120 46.7 41.1 9.5 2.7

2021q3 11,117 46.1 43.0 8.4 2.5
Consumer Expenditure Surveys - 2021 Data Quality Profile | 8

Table 1.4 Interview Survey: prevalence of nonresponse reclassifications

Number of nonresponse reclassifications

Quarter Number of 

eligible 

sample 

units

Total 

reclassifications

COVID 19 

reclassifications

Other 

reclassifications

2018q4 10,161 5 0 5

2019q1 10,108 8 0 8

2019q2 10,075 2 0 2

2019q3 10,037 9 0 9

2019q4 10,170 14 0 14

2020q1 9,956 197 186 11

2020q2 10,581 2,955 2,944 11

2020q3 11,190 88 74 14

2020q4 11,185 32 14 18

2021q1 11,125 72 2 70

2021q2 11,120 522 0 522

2021q3 11,117 156 0 156
Consumer Expenditure Surveys - 2021 Data Quality Profile | 9

2. Records Use (Interview Survey)

The Records Usemetric measures the proportion of respondents who refer to records while answering 

the Interview Survey questions, according to the interviewer. Examples of records include, but are not 

limited to, receipts, bills, checkbooks, and bank statements. Records use is retrospectively recorded by 

the interviewer at the end of the interview. Past research has shown that respondents who use 

expenditure records reported more items with lower rates of missingness (Abdirizak, Erhard, Lee, and 

McBride, 2017), so a higher prevalence of records use is desirable. Metricsin this section are presented 

by survey wave5.

Interview Survey Summary

• Records usage temporarily rose in 2016 for Wave 1 respondents, and this is likely a result of a field test

conducted during this period that gave a subset of respondent’smonetary incentives to use records.

• Since 2017, records use has been stable across interview waves.

Graph 2.1 Interview Survey Records Used by Interview Wave

5 In the Interview Survey, each family in the sample is interviewed every 3 months over four calendar quarters. 

These interviews are commonly referred to as waves. For more information on survey administration pleasesee

the CE handbook of methods.
Consumer Expenditure Surveys - 2021 Data Quality Profile | 10

Table 2.1 Interview Survey: prevalence of records use among 

respondents

Row percentage

Quarter Wave Number of 

respondents

Used Did not use Missing 

response

2018q4 Wave 1 1,399 53.3 45.7 0.9

2018q4 Waves 2 & 3 2,782 48.7 50.8 0.4

2018q4 Wave 4 1,390 51.5 47.4 1.1

2019q1 Wave 1 1,465 55.2 43.8 1.0

2019q1 Waves 2 & 3 2,730 51.1 48.4 0.5

2019q1 Wave 4 1,428 52.7 46.9 0.4

2019q2 Wave 1 1,443 51.6 47.6 0.8

2019q2 Waves 2 & 3 2,653 51.7 47.9 0.4

2019q2 Wave 4 1,397 53.6 45.5 0.9

2019q3 Wave 1 1,401 50.1 48.7 1.2

2019q3 Waves 2 & 3 2,651 49.0 50.2 0.8

2019q3 Wave 4 1,285 51.3 48.1 0.6

2019q4 Wave 1 1,318 53.0 46.2 0.8

2019q4 Waves 2 & 3 2,637 48.8 51.0 0.2

2019q4 Wave 4 1,293 53.1 46.3 0.5

2020q1 Wave 1 1,239 53.6 45.2 1.2

2020q1 Waves 2 & 3 2,601 50.7 48.9 0.4

2020q1 Wave 4 1,362 53.4 46.2 0.4

2020q2 Wave 1 965 51.9 47.3 0.8

2020q2 Waves 2 & 3 2,559 50.0 49.7 0.3

2020q2 Wave 4 1,334 52.4 47.1 0.5

2020q3 Wave 1 1,143 49.3 49.3 1.4

2020q3 Waves 2 & 3 2,444 49.4 50.3 0.3

2020q3 Wave 4 1,393 51.0 48.7 0.4

2020q4 Wave 1 1,230 50.1 49.6 0.3

2020q4 Waves 2 & 3 2,589 50.1 49.3 0.5

2020q4 Wave 4 1,386 51.9 47.8 0.2

2021q1 Wave 1 1,250 52.0 47.4 0.6

2021q1 Waves 2 & 3 2,515 50.3 49.4 0.4

2021q1 Wave 4 1,350 52.4 47.0 0.7

2021q2 Wave 1 1,325 49.8 49.6 0.6

2021q2 Waves 2 & 3 2,534 47.8 51.4 0.7

2021q2 Wave 4 1,337 50.5 48.9 0.6

2021q3 Wave 1 1,352 53.0 46.1 1.0

2021q3 Waves 2 & 3 2,488 48.6 50.6 0.8

2021q3 Wave 4 1,281 49.6 49.6 0.8
Consumer Expenditure Surveys - 2021 Data Quality Profile | 11

3. Information Booklet use (Diary and Interview Surveys)

The Information Booklet is a recall aide the interviewer provides for respondentsfor both the Interview 

and Diary surveys, and each provides the response options for demographic questions and the income 

bracket response options. In addition, the Interview Information Booklet provides clarifying examples 

for the kinds of expenditures that each section/item code is intended to collect. 

This metric measures the prevalence of Information Booklet use among respondents during their 

interviews, according to interviewers. For interviews conducted over the phone, the Information Booklet

is typically not directly available to the respondent (although a PDF version is available on the BLS 

website),so this metric should be interpreted in conjunction with the rise in telephone interviews during 

the COVID-19 pandemic. Higher rates of Information Booklet usage are encouraged, as use can improve 

reporting quality by clarifying concepts and providing examples.

Diary Survey Summary

• The prevalence of Information Bookletuse among Diary Survey respondents remained fairly constant 

from 2018q3 to 2019q4.

• In mid-March 2020, CE suspended all in-person interviews and Information Bookletuse declined by 29

percentage points from 2020q1 to 2020q2.
Consumer Expenditure Surveys - 2021 Data Quality Profile | 12

Graph 3.1 Diary Survey Information BookletUse

Table 3.1 Diary Survey: prevalence of Information Booklet use among 

respondents

Row percentage

Quarter Number of 

respondents

Used Did not use Missing 

response

2018q3 2,896 39.5 56.5 4.0

2018q4 2,611 38.3 58.6 3.1

2019q1 2,671 42.0 54.9 3.1

2019q2 2,713 40.6 56.3 3.1

2019q3 2,745 39.2 58.1 2.7

2019q4 2,553 37.1 59.6 3.3

2020q1 3,285 33.1 64.0 3.0

2020q2 1,936 4.1 94.0 1.9

2020q3 2,559 7.3 90.8 1.9

2020q4 2,835 10.5 86.4 3.1

2021q1 2,952 12.7 84.2 3.1

2021q2 3,224 16.7 79.6 3.7
Consumer Expenditure Surveys - 2021 Data Quality Profile | 13

Interview Survey Summary

• In mid-March 2020, BLS temporarily discontinued the use of physical copies of the Information Booklet

due to the COVID-19 pandemic and referred respondents to the online version. As a result, the 

Information Bookletuse rate declined 44.1percentage points for Wave 1 respondents from 2019q4 to 

2020q2.

• Declines in Information Bookletuse were similar for subsequent waves and about 95 percent of all

respondents in 2020q2 did not have access to the Information Booklet.

• In the beginning in July 2020, disposable copies of the Information Booklets were provided to respondents 

and Information Bookletuse rose to an average of 5.3 percent for all waves in 2020q3.

• Since then, Information Bookletuse across all waves has continued to recover from the 2020q2low.

• Information Bookletuse for Wave 1 respondents improved 16.7 percentage pointsfrom 2020q2 to 

2021q3, but still remains well below pre-pandemic highs of 50 percent. 

Graph 3.2 Interview Survey Information Booklet Use
Consumer Expenditure Surveys - 2021 Data Quality Profile | 14

Table 3.2 Prevalence of Information Booklet use among Interview Survey respondents 

Row percentage

Quarter Wave Number of 

respondents

Used Did not use 6 Missing 

response

2018q4 Wave 1 1,399 49.0 17.3 0.9

2018q4 Wave 2 & 3 2,782 35.6 15.9 0.4

2018q4 Wave 4 1,390 32.4 16.7 1.1

2019q1 Wave 1 1,465 46.3 15.8 1.0

2019q1 Wave 2 & 3 2,730 36.2 14.0 0.5

2019q1 Wave 4 1,428 32.8 14.6 0.4

2019q2 Wave 1 1,443 49.5 17.3 0.8

2019q2 Wave 2 & 3 2,653 35.6 15.9 0.4

2019q2 Wave 4 1,397 33.9 16.7 0.9

2019q3 Wave 1 1,401 47.5 18.0 1.2

2019q3 Wave 2 & 3 2,651 35.6 15.2 0.8

2019q3 Wave 4 1,285 35.0 13.8 0.6

2019q4 Wave 1 1,318 46.7 16.5 0.8

2019q4 Wave 2 & 3 2,637 33.7 14.9 0.2

2019q4 Wave 4 1,293 32.3 15.3 0.5

2020q1 Wave 1 1,239 37.8 15.7 1.2

2020q1 Wave 2 &3 2,601 28.1 13.9 0.4

2020q1 Wave 4 1,362 28.8 13.7 0.4

2020q2 Wave 1 965 2.6 1.8 0.8

2020q2 Wave 2 &3 2,559 2.9 1.8 0.3

2020q2 Wave 4 1,334 3.4 0.8 0.5

2020q3 Wave 1 1,143 6.7 2.4 1.4

2020q3 Wave 2 &3 2,444 4.8 2.7 0.3

2020q3 Wave 4 1,393 5.2 2.1 0.4

2020q4 Wave 1 1,230 12.4 6.7 0.3

2020q4 Waves 2 & 3 2,589 9.4 3.6 0.5

2020q4 Wave 4 1,386 7.4 3.8 0.2

2021q1 Wave 1 1,250 13.3 6.2 0.6

2021q1 Waves 2 & 3 2,515 9.3 3.3 0.4

2021q1 Wave 4 1,350 8.5 4.2 0.7

2021q2 Wave 1 1,325 14.9 7.8 0.6

2021q2 Waves 2 & 3 2,534 11.1 7.0 0.7

2021q2 Wave 4 1,337 9.6 5.2 0.6

2021q3 Wave 1 1,352 19.3 11.7 1.0

2021q3 Waves 2 & 3 2,488 12.7 7.4 0.8

2021q3 Wave 4 1,281 10.8 7.2 0.8

6 This “Did not use” category does not include records where there was no Information Booklet available. 
Consumer Expenditure Surveys - 2021 Data Quality Profile | 15

4. Expenditure edit rates (Diary and Interview Surveys)

The Expenditure edit rates metric measures the proportion of reported expenditure data that are 

edited. These edits are changes made to the reported expenditure data during CE data processing, 

excluding changes due to time period conversion calculations and top-coding or suppression of reported

values. Top-coding and suppression are done to protect respondent confidentiality in the public-use 

microdata. More information on these concepts is available on the CE Website.

The Interview Survey expenditure edit rates are broken down into three categories: Imputation, 

Allocation, and Manual Edits:

• Imputation replaces missing or invalid responses with a valid value.

• Allocation edits are applied when respondents provide insufficient detail to meet tabulation 

requirements. For example, if a respondent provides a non-itemized total expenditure report for the 

category of fuels and utilities, that total amount will be allocated to the target items mentioned by the 

respondent (such as natural gas and electricity). 

• Manual edits occur whenever responses are directly edited by BLS economists based on their analysis and 

expert judgment. 

The Diary survey expenditure edit rates are only broken down into two categories: Allocations and Other 

Edits. Most edits in the Diary surveyare allocations. Table 4.1 below shows the “other edits” category, 

which covers all other expenditure edits including imputation and manual edits, and we can see from 

the data that these edits are relatively rare. 

Imputation in CE data results from expenditure amount nonresponse. Allocation is a consequence of 

responses lacking the required details for items asked by the survey. Lower edit rates are preferred, as it

lowers the risk of processing error. However, edits based on sound methodology can improve the 

completeness of the data, and thereby reduce the risk of measurement error and nonresponse bias in 

survey estimates. Additional information on expenditure edits is available in the DQP Reference Guide

(Armstrong, Jones, Miller, and Pham, 2022).
Consumer Expenditure Surveys - 2021 Data Quality Profile | 16

Diary Survey Edit Summary

• In the beginning of January 2020, an increase in CE’s sample size resulted in the number of reported

expenditures rising by over 22,000, but as response rates dropped in 2020q2, so did the number of 

expenditures.7

• The total rate of unedited expenditure amounts fell 1 percentage point from 89.7percent in

2018q3 to 88.7 percent in 2021q2.

• Increasing edit rates were driven by a 1.1 percentage point increasein allocation rates from 2018q3 to

2021q2.

Graph 4.1 Diary Survey Expenditure Edit Rates

7 This increase in sample size was made possible by increased funding to accommodate collection of outlet

information needed for calculating the Consumer Price Index.
Consumer Expenditure Surveys - 2021 Data Quality Profile | 17

Table 4.1 Diary Survey:reported expenditure records 

Row percentage

Quarter Number of 

expenditures

Allocated Other edit Unedited

2018q3 88,342 10.0 0.3 89.7

2018q4 80,129 10.3 0.2 89.5

2019q1 79,626 10.2 0.0 89.7

2019q2 85,329 9.1 0.1 90.8

2019q3 83,639 10.5 0.0 89.5

2019q4 80,510 9.5 0.0 90.4

2020q1 102,693 9.2 0.0 90.7

2020q2 41,257 10.2 0.1 89.6

2020q3 56,071 11.6 0.0 88.3

2020q4 69,959 10.7 0.0 89.3

2021q1 72,138 10.9 0.1 89.1

2021q2 80,646 11.1 0.2 88.7

Interview Survey Edit Summary

• The total rate of unedited expenditure amounts increased 1.2 percentage points from 84.0 percent in

2018q4 to 85.2 percent in 2021q3.

• This was primarily driven by allocation rates declining 1.9 percentage points from 12.0percent in 2018q4

to 10.1 percent in 2021q3.

• Declines in allocation rates were partially offset by increases in the manual edit rate from 0.1 percent in

2018q4 to 0.5 percent in 2021q3.
Consumer Expenditure Surveys - 2021 Data Quality Profile | 18

Graph 4.2 Interview Survey Expenditure Edit Rates

Table 4.2 Interview Survey: reported expenditure records

Row percentage

Quarter Number of 

expenditures

Allocated Imputed Imputed 

&

allocated

Manual 

Edit

Unedited

2018q4 259,508 12.0 3.8 0.2 0.1 84.0

2019q1 264,424 11.8 3.6 0.2 0.1 84.3

2019q2 255,037 11.7 3.7 0.2 0.1 84.2

2019q3 251,370 11.6 3.7 0.2 0.2 84.3

2019q4 244,834 11.6 3.8 0.2 0.2 84.2

2020q1 246,488 11.6 3.9 0.2 0.2 84.1

2020q2 217,785 11.9 4.1 0.2 0.1 83.6

2020q3 224,639 11.6 4.3 0.2 0.3 83.6

2020q4 232,195 11.6 4.3 0.2 0.3 83.6

2021q1 231,850 11.2 3.9 0.2 0.6 84.0

2021q2 232,282 10.1 4.5 0.2 0.2 85.0

2021q3 231,351 10.1 4.0 0.2 0.5 85.2
Consumer Expenditure Surveys - 2021 Data Quality Profile | 19

5. Income imputation rates (Diary and Interview Surveys)

The Income imputation rates metric describes edits performed on a consumer unit’s nonresponse to at 

least one source of income. This edit is based on three imputation methods, applicable to both CE

Surveys:

1. Model-based imputation: when the respondent mentions receipt of an income source but fails 

to report the amount.

2. Bracket response imputation: when the respondent mentions receipt of an income source, but 

only reports that income as falling within a specified range.

3. All valid blank (AVB) conversion: when the respondent reports no receipt of income from any 

source, but the CE imputes receipt from at least one source.

After imputation, income from each component source is summed to compute total income before 

taxes. In the text that follows, income before taxes is defined as “unimputed” if no source of total 

income required imputation for one of the three reasons identified above. Again, this applies to both 

the Diary and Interview Surveys.

Since the need for imputation reflects either item nonresponse or that insufficient item detail was 

provided, lower imputation rates are desirable for lowering measurement error. However, imputation 

based on sound methodology can improve the completeness of the data and reduce the risk of 

nonresponse bias due to dropping incomplete cases from the dataset. Further details on the income 

imputation methodology can be found in the DQP Reference Guide (Armstrong, Jones, Miller, and Pham, 

2022) and the User’s Guide to Income Imputation in the CE (Paulin, Reyes-Morales, and Fisher, 2018).

Diary Survey Summary

• The rate of unimputed total income before taxes rose slightly from53.8 percent in 2018q3 to 54.9

percent in 2021q2.

• Model-based imputation rates declined 1.4percentage points from 21.3 percent in 2018q3 to 19.9

percent in 2021q2.
Consumer Expenditure Surveys - 2021 Data Quality Profile | 20

Graph 5.1 Diary Survey Income Imputation Rates

Table 5.1 Diary Survey: income imputation rates for total amount of family income before taxes

Row percentage

Quarter Number of 

respondents

Valid blanks 

converted 

(AVB)

Bracket 

imputation

Model 

imputation

Model & 

bracket 

imputation

Unedited

2018q3 2,896 1.5 18.4 21.3 5.1 53.8

2018q4 2,611 2.4 19.1 18.3 6.0 54.3

2019q1 2,671 1.8 18.7 17.8 4.9 56.8

2019q2 2,713 2.9 20.2 17.6 5.0 54.3

2019q3 2,745 2.1 22.1 18.5 4.9 52.4

2019q4 2,553 2.6 19.2 15.2 6.5 56.4

2020q1 3,285 1.9 20.0 17.5 5.1 55.5

2020q2 1,936 1.5 20.8 16.5 6.2 55.5

2020q3 2,559 2.6 18.1 19.5 6.7 53.1

2020q4 2,835 1.9 18.9 19.9 6.0 53.3

2021q1 2,952 2.0 18.7 18.4 5.6 55.2

2021q2 3,224 2.1 17.5 19.9 5.6 54.9
Consumer Expenditure Surveys - 2021 Data Quality Profile | 21

Interview Survey Summary

• The rate of unimputed total income before taxes declined 3 percentage points from 58.5in 2018q4 to

55.5 percent in 2021q3.

• Model-based imputation rates rose 2.4percentage points from 17.3 percent in 2018q4to 19.7 percent in

2021q3and accounted for the largest share of the decline in unimputed income.

• The proportion of respondents requiring both model-based and bracket response imputation rose a

further 0.9 percentage points from 4.5 percent in 2018q4to 5.4 percent in 2021q3.

Graph 5.2 Interview Survey Income Imputation Rates
Consumer Expenditure Surveys - 2021 Data Quality Profile | 22

Table 5.2 Interview Survey:income imputation rates for total amount of family income before taxes

Row percentage

Quarter Number of 

respondents

Valid blanks 

converted 

(AVB)

Bracket 

imputation

Model 

imputation

Model & 

bracket

Unedited

2018q4 5,571 1.4 18.2 17.3 4.5 58.5

2019q1 5,623 1.9 18.0 17.0 4.3 58.8

2019q2 5,493 1.4 18.3 17.5 4.4 58.4

2019q3 5,337 1.2 17.8 17.7 4.6 58.7

2019q4 5,248 1.4 18.9 17.2 5.0 57.5

2020q1 5,202 1.3 18.6 17.6 4.5 58.1

2020q2 4,858 1.2 18.1 18.7 4.9 57.1

2020q3 4,980 1.1 18.2 19.0 5.1 56.6

2020q4 5,205 1.3 18.2 20.3 5.5 54.7

2021q1 5,115 1.4 17.8 19.9 5.5 55.5

2021q2 5,196 1.3 17.4 20.5 5.8 55.0

2021q3 5,121 1.2 18.1 19.7 5.4 55.5
Consumer Expenditure Surveys - 2021 Data Quality Profile | 23

6. Respondent burden (Interview Survey)

Response burden in the Interview survey relates to the perceived level of effort exerted by respondents 

in answering the survey question. Survey designers are concerned about response burden as it has the 

potential to negatively impact response rates and the overall response quality. Beginning in April 2017, 

the Interview Survey introduced a response burden question with response options describing five 

different levels of burden at the end of the Wave 4 interview. The respondent burden metric is based on 

this question and maps the five burden categories to three metric values: not burdensome, some 

burden, and very burdensome. Please see the DQP Reference Guide (Armstrong, Jones, Miller, and 

Pham, 2022) for more details on the question wording and the burden categories.

A caveat to the interpretation of this metric is that since the burden question is only asked at the end of 

Wave 4, the metric likely underestimates survey burden due to self-selectionbias. That is, respondents 

who have agreed to participate through the final wave of the survey tend to find the survey less 

burdensome than sample units who had dropped out at any point prior to completing the final survey 

wave.

However, it is also possible that the respondent answering this question did not participate in prior 

interview waves. For example, the respondent who participated in the first three survey waves might 

move out of the sampled address prior to the final interview. This is not a common occurrence, but if 

someone else moves into the sampled address in time for the final wave, then they would be asked 

these questions. 

Interview Survey Summary

• The rate of respondents who report perceiving no burden declined 6.3 percentage points from 34.2 

percent in 2018q4 to 27.9percent in 2021q3.

• Rising rates of respondents who felt that the survey was very burdensome accounted for 3.3 percentage

points of this change, rising from 12.1 percent in 2018q4 to 15.4 percent in 2021q3.

• Respondents perceiving some burden also increased 3.1 percentage points from 50.8 percent in 2018q4

to 53.9 percent in 2021q3.
Consumer Expenditure Surveys - 2021 Data Quality Profile | 24

Graph 6.1 Interview Survey Respondent Burden

Table 6.1 Interview Survey:respondents’ perceived burden in the final survey wave 

Row percentage

Quarter Number of 

respondents

Not 

burdensome

Some burden Very 

burdensome

Missing 

response

2018q4 1,390 34.2 50.8 12.1 2.9

2019q1 1,428 30.5 55.1 12.7 1.6

2019q2 1,397 30.9 52.4 13.7 2.9

2019q3 1,285 29.4 54.3 13.4 2.9

2019q4 1,293 32.9 53.8 11.3 2.0

2020q1 1,362 30.8 54.0 12.0 3.2

2020q2 1,334 30.7 54.3 12.5 2.5

2020q3 1,393 30.5 54.1 12.8 2.7

2020q4 1,386 29.7 53.5 14.9 1.9

2021q1 1,350 26.0 55.0 15.6 3.4

2021q2 1,337 29.0 55.8 12.3 2.9

2021q3 1,281 27.9 53.9 15.4 2.7
Consumer Expenditure Surveys - 2021 Data Quality Profile | 25

7. Survey mode (Interview Survey)

This metric measures the prevalence of the mode of data collection. The Interview Survey was designed 

to be an in-person interview. However, the interviewer can also collect data for the Interview Survey

over the phone, or by a combination of the two modes. Higher prevalence of in-person data collection 

is preferred since the interviewer can actively prompt the respondent, as well as encourage the use of 

recall aids, thereby reducing the risk of measurement error. Conducting first wave interviews in-person 

is important because this is typically the respondent’s first experience with the survey. Additionally, BLS 

has agreements with the Census Bureau that no more than 24 percent of first interviews or 48 percent 

of subsequent interviews will be collected over the phone. This agreement is still in effect, but the 

COVID-19 pandemic has made collecting in-person interviews unsafe for respondents and interviewers. 

BLS expects to return to the agreed upon rates as it becomes safer for in-person interviews to resume. 

Interview Survey Summary

• Prior to the onset of the COVID-19 pandemic, for all but two quarters (2019q1 and 2019q4),the rate of 

Wave 1 telephone interviews remained below the 24 percent threshold.

• In every quarter prior to COVID 19, the rate of Wave 2 through 4 telephone interviews remained below 

the 48 percentthreshold.

• In mid-March 2020, the Census Bureau suspended all in-person interviews, and by April, close to 98

percent of all interviews were conducted over the phone regardless of wave.

• Beginning in July 2020, interviewers were allowed to resume in-person interviews, depending on local 

rules.

• Since July of 2020the rate of in-person interviews has increased across all waves, with at least 24 percent 

of interviews being conducted in-person regardless of wave in 2021Q3.

• For Wave 1 interviews in particular, in-person interviews have risen 44.6 percentage points from 1.5 

percent in 2020Q2 to 46.1 percent in 2021Q3. 
Consumer Expenditure Surveys - 2021 Data Quality Profile | 26

Graph 7.1 Interview Survey Mode
Consumer Expenditure Surveys - 2021 Data Quality Profile | 27

Table 7.1 Interview Survey:survey mode

Row percentage

Quarter Wave Number of 

respondents

In-person Telephone Missing

2018q4 Wave 1 1,399 76.1 21.9 0.7

2018q4 Waves 2 & 3 2,782 60.1 38.9 0.4

2018q4 Wave 4 1,390 57.3 42.0 0.3

2019q1 Wave 1 1,465 71.9 25.4 1.0

2019q1 Waves 2 & 3 2,730 59.0 40.3 0.3

2019q1 Wave 4 1,428 56.7 42.6 0.3

2019q2 Wave 1 1,443 75.6 22.7 0.5

2019q2 Waves 2 & 3 2,653 60.0 39.2 0.2

2019q2 Wave 4 1,397 58.3 40.9 0.2

2019q3 Wave 1 1,401 77.3 21.1 0.6

2019q3 Waves 2 & 3 2,651 59.7 39.5 0.4

2019q3 Wave 4 1,285 57.7 41.6 0.5

2019q4 Wave 1 1,318 74.2 24.6 0.4

2019q4 Waves 2 & 3 2,637 57.9 41.5 0.2

2019q4 Wave 4 1,293 55.0 43.9 0.4

2020q1 Wave 1 1,239 64.2 34.7 1.0

2020q1 Wave 4 1,362 48.8 51.1 0.1

2020q1 Waves 2 & 3 2,601 50.1 49.7 0.2

2020q2 Wave 1 965 1.5 98.2 0.3

2020q2 Wave 4 1,334 1.9 97.9 0.2

2020q2 Waves 2 & 3 2,559 1.8 97.9 0.3

2020q3 Wave 1 1,143 13.0 86.4 0.6

2020q3 Wave 4 1,393 7.4 92.4 0.2

2020q3 Waves 2 & 3 2,444 8.6 91.3 0.2

2020q4 Wave 1 1,230 28.9 71.1 0.1

2020q4 Waves 2 & 3 1,386 14.6 85.3 0.1

2020q4 Wave 4 2,589 17.6 82.1 0.3

2021q1 Wave 1 1,250 28.7 70.9 0.4

2021q1 Wave 4 1,350 12.2 87.5 0.3

2021q1 Waves 2 & 3 2,515 15.9 83.9 0.2

2021q2 Wave 1 1,325 36.7 62.9 0.4

2021q2 Wave 4 1,337 20.5 79.3 0.2

2021q2 Waves 2 & 3 2,534 24.0 75.7 0.4

2021q3 Wave 1 1,352 46.1 53.3 0.6

2021q3 Wave 4 1,281 24.0 75.8 0.2

2021q3 Waves 2 & 3 2,488 28.1 71.5 0.5
Consumer Expenditure Surveys - 2021 Data Quality Profile | 28

8. Survey Response Time (Diary and Interview Surveys)

For both Interview and Diary Surveys, survey response time is the number of minutes needed to 

complete an interview. For the Interview Survey, the survey response time metric is the median number 

of minutesto complete the interview. For the Diary Survey, the survey response time metric is the 

median number of minutes to complete the personal interview component that collects information on

income and demographics. Survey response time has been used as an objective indicator for respondent 

burden: the longer the time needed to complete the survey, the more burdensome the survey. Fricker, 

Gonzalez, and Tan (2011) find that higher respondent burden negatively affects both response rates and 

data quality. However, survey response time could also reflect the respondent’s degree of engagement.

Engaged and conscientious respondents might take longer to complete the survey because they report 

more thoroughly or use records more extensively. Tracking the median survey response time can be 

useful for assessing the effect of changes in the survey design. 

Diary Survey Summary

• The survey response time in the Diary Survey remained just over one-half hour throughoutthe period:

34.2 minutes in 2018q3 and 32.9 minutes in 2021q2.

Graph 8.1 Diary Survey Median Survey Time
Consumer Expenditure Surveys - 2021 Data Quality Profile | 29

Table 8.1 Diary Survey: median length of 

time to complete the interview components 

(income and demographics)

Quarter Number of 

respondents

Minutes

2018q3 2,896 34.2

2018q4 2,611 33.2

2019q1 2,671 35.0

2019q2 2,713 33.8

2019q3 2,745 34.3

2019q4 2,553 34.4

2020q1 3,281 33.3

2020q2 1,936 34.9

2020q3 2,559 34.9

2020q4 2,835 32.7

2021q1 2,952 32.7

2021q2 3,224 32.9

Interview Survey Summary

• Median time to complete Wave 1 interviews remained fairly stable, ranging from 74.1 minutes (2019q3) 

to 78.8 minutes (2020q2).

• Median time to complete Waves 2 and 3 interviews was 2.6 minutes higher in 2021q3 (54.6 minutes) than 

it was in 2018q1 (52.0 minutes).

• Wave 4 interviews also remained steady, rising from 58.6 minutes in 2018q4 to peak at 62.8 minutes in 

2019q3, and settling at 60.0 minutesin 2021q3.
Consumer Expenditure Surveys - 2021 Data Quality Profile | 30

Graph 8.2 InterviewSurvey Median Survey Time by Interview Wave

Table 8.2 Interview Survey: median length of time to complete survey

Minutes

Quarter Number of 

respondents

Wave 1 Waves 2 & 3 Wave 4

2018q4 5,570 76.7 52.0 58.6

2019q1 5,618 75.8 52.8 58.8

2019q2 5,486 75.9 56.4 60.2

2019q3 5,332 74.1 54.0 62.8

2019q4 5,239 77.4 53.3 60.8

2020q1 5,199 78.8 56.0 59.9

2020q2 4,855 76.4 54.6 62.2

2020q3 4,980 76.8 56.7 62.2

2020q4 5,205 75.0 56.2 60.4

2021q1 5,115 74.4 54.6 61.7

2021q2 5,196 76.7 54.6 58.8

2021q3 5,121 78.0 54.6 60.0
Consumer Expenditure Surveys - 2021 Data Quality Profile | 31

Summary

BLS is committed to producing data that are consistently of high statistical quality. As part of that 

commitment, BLS publishes the DQP and its accompanying Reference Guide (Armstrong, Jones, Miller, 

and Pham, 2022) to assist data users as they evaluate CE data quality and judge whether CE data fit their 

needs. DQP metrics therefore cover both the Interview and Diary Surveys, multiple dimensions of data 

quality, and several stages of the survey lifecycle. Additionally, BLS uses these metrics internally to 

identify areas for potential survey improvement, evaluate the effects of survey changes, and to monitor 

the health of the surveys. 

From the final quarters of 2018 to the first quarters of 2021, response rates for the Diary Survey and 

wave 1 of the Interview Survey recovered from large drop offs due to the COVID-19 pandemic in the first 

two quarters of 2020. Information booklet use for both the Interview and Diary Surveys have also both 

continued to increase. 

Despite a slight decline in 2021q2, respondent burden in the Interview Survey has risen steadily since 

the beginning of 2020. While several metrics have recovered in the direction of their pre-COVID figures, 

some,such as Survey Mode, are still lagging behind. The data show thatit may be some time before inperson and phone interviews are at their pre-2020 levels. Several metrics showed little change. Income 

imputation rates for the Diary Survey and the Interview Survey remained stable, as did Median survey 

time for both surveys. 

BLS will continue to monitor these trends, and the next issue of the CE Data Quality Profile will be 

released in September 2022 with BLS’s annual release of CE data and will report on the remainder of the 

2021 data. 
Consumer Expenditure Surveys - 2021 Data Quality Profile | 32

References

Abdirizak, S., Erhard, L., Lee, Y., & McBride, B. (2017). Enhancing Data Quality Using Expenditure 

Records. Paper Presented at the Annual Conference of the American Association for Public 

Opinion Research, New Orleans LA.

Fricker, S., Gonzalez, J., & Tan, L. (2011). Are you burdened? Let’s find out. Paper Presented at the 

Annual Conference of the American Association for Public Opinion Research, Phoenix AZ. 

Ash, S., B. Nix, and B. Steinberg (2022). Report on Nonresponse Bias during the COVID-19 Period for the 

Consumer Expenditures Interview Survey. Published as part of the Consumer Expenditure 

Surveys Program Report Series.

Armstrong, G., G. Jones, T. Miller, and S. Pham (2022). Reference Guide CE Data Quality Profile

Paulin, G., Reyes-Morales, S., & Fisher, J (2018). User's Guide to Income Imputation in the CE. U.S. 

Bureau of Labor Statistics.