The Annual CE Data Quality Profile - 

2020

September 09, 2021 

Clayton Knappenberger, Yezzi Lee, Sharon Pham, & Grayson Armstrong 

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 Book use (Diary and Interview Surveys) ....................................................................................... 11

4. Expenditure edit rates (Diary and Interview Surveys) ...................................................................................... 16

5. Income imputation rates (Diary and Interview Surveys) .................................................................................. 20

6. Respondent burden (Interview Survey) ............................................................................................................ 24

7. Survey mode (Interview Survey)....................................................................................................................... 26

8. Survey Response Time (Diary and Interview Surveys)...................................................................................... 29

Conclusion............................................................................................................................................................. 33

References............................................................................................................................................................. 34
Consumer Expenditure Surveys - 2020 Data Quality Profile | 1

Overview 

In keeping with Statistical Policy Directive No. 1, covering the Fundamental Responsibilities of Federal 

Statistical Agencies, the Bureau of Labor Statistics (BLS) is committed to consistently producing high quality 

data , i.e., accurate, objective, relevant, timely, and accessible. The Consumer Expenditure Surveys (CE) 

Program provides data users with a variety of metrics to assist them in evaluating overall data quality

including: official tables with standard errors, response rates, data comparisons with other household survey 

estimates, as well as the results of nonresponse bias studies. Additionally, the public-use microdata (PUMD) 

provide variables and flags for users to create their own quality measures. 

Adding to these resources, the Data Quality Profile (DQP) provides a comprehensive set of metrics that 

are timely, routinely updated, and accessible to users. Prior DQPs are available on our Data Quality and Data 

Comparisons page. BLS began providing DQPs every year beginning with the 2017 data, and began providing 

midyear DQPs with the 2020 midyear data release. For data users, the DQP metrics are an indication of quality

covering both the Interview and Diary Surveys. For internal stakeholders, they can signal areas for survey 

improvements. Since the quality of survey estimates is affected by errors that can occur throughout the survey 

lifecycle, we expect that the set of DQP metrics will evolve over time as the BLS continually researches 

methods to monitor and improve data quality. For each metric, a brief description is provided along with the 

results, which are tabulated and graphed. The DQP Reference Guide (Knappenberger, Lee, Pham, and 

Armstrong, 2021) provides detailed descriptions of the metrics, computations, and methodology.

The metrics are reported quarterly, where each quarter is the three-month period in which the survey 

data were collected. Because the respondents to the Interview Survey are asked to recall their expenditures 

over the prior three months, data collected in January refer to expenditures made in October, November, and 

December in the previous year. In contrast, Diary Survey expenditures are reported as they occur. This is why 

the PUMD Getting Started Guide recommends using 5 quarters of Interview Survey data, and it is why this 

profile provides metrics up to 2021q1 for the Interview Survey and up to 2020q4 for the Diary Survey.
Consumer Expenditure Surveys - 2020 Data Quality Profile | 2

Highlights

This section summarizes the trends in metrics over the past three years. This time frame covers the first 

quarters of the 2018 collection period to the first quarter 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 January refer to expenditures made in October, November, and December of the previous 

year. Hence, the Interview Survey metrics in this profile cover the time period of 2018q2 through 

2021q1. Respondents to the Diary Survey report their spending as it occurs, so Diary Survey metrics in 

this profile cover the time period of 2018q1 through 2020q4. Subsequent sections describe the 

individual metrics with detailed data tables.

Trends that are encouraging

 Diary and Interview Survey response rates show signs of recovering in July of 2020 with the 

resumption of in-person interviews (Section 1).

 Nonresponse reclassifications for both the Diary and Interview Surveys recovered from the 

impacts of the COVID-19 suspension of in-person interviews (Section 1).

 Roughly half of respondents used records, and this trend continues to be stable (Section 2).

 Information Book use rates began recovering in July of 2020 as in-person interviews and as 

Interview Survey respondents were provided with disposable copies (Section 3).

Trends that cause concern

 Diary and Interview Survey response rates remain at historical lows, and saw their largest singlequarter declines with the beginning of the COVID-19 pandemic (Section 1). 

 Information Book usage saw large declines for both the Diary and Interview Survey following the 

onset of the COVID-19 pandemic. A large portion of Interview Survey cases report not having 

access to the Information Book (Section 3).

 Income imputation rates rose for both the Diary and Interview Surveys (Section 5). 

 Perceived burden (Section 6) increased for the Interview Survey, along with median time spent 

taking the survey (Section 8). 
Consumer Expenditure Surveys - 2020 Data Quality Profile | 3

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

Final disposition rates of eligible sample units (often called response rates) report the final outcome of 

field staff’s survey participation recruitment effort. The BLS classifies the final outcome of eligible 

sample units into four main categories: completed interview, nonresponse due to refusal, nonresponse 

due to noncontact, and nonresponse due to other reasons. 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 1.1 and 1.3). More information on the non-response 

reclassification edit, along with information on how we calculate response rates can be found in the 

DQP Reference Guide (Knappenberger, Lee, Pham, and Armstrong, 2021). 

Low response rates, examined with other indicators, may indicate non-response bias of an

expenditure estimate if nonresponse is correlated with expenditures. A nonresponse study conducted 

by the BLS showed no meaningful bias in survey estimates (King, Chopova, Edgar, Gonzalez, McGrath, 

and Tan, 2009), but in a world of declining response rates, BLS continues to evaluate 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 have previously calculated weighted response rates, they showed no meaningful 

difference from the unweighted rates.

Diary Survey

Pre-COVID-19 trends (2018q1 – 2019q4)

 Response rates declined 6.6 percentage points from 55.5 to 48.9 percent (Table 1.1).

 Refusal rates rose 4.9 percentage points from 25.0 to 29.9 percent and accounted for the largest 

share of the decline in response rates (Table 1.1).

 Noncontact rates rose from 6.9 to 7.6 percent and accounted for 0.7 percentage points of the 

decline in response rates (Table 1.1).

COVID-19 lockdown impacts (2020q1 and 2020q2)

 In mid-March 2020, the Census Bureau suspended all in-person interviews, causing response 

rates to drop 22.8 percentage points from 2019q4 to 2020q2 (Table 1.1).

 Other nonresponse rates rose 45.6 percentage points, but were partially offset by a 17.8

percentage point decline in refusal rates and a 4.9 percentage point decline in noncontact rates

(Table 1.1).
Consumer Expenditure Surveys - 2020 Data Quality Profile | 4

 Nonresponse reclassifications increased by 3,205 cases as the BLS reclassified a large number of 

interviews from ineligible to eligible nonrespondents (Table 1.2).

1

COVID-19 post-lockdown impacts (2020q3-2020q4)

 Beginning in July 2020, interviewers resumed in-person interviews in some locations. As a result, 

other nonresponse rates decreased 40.3 percentage points from 2020q2 to 2020q4 (Table 1.1).

 This was partially offset by a 22.6 percentage point increase in refusal rates, and a 7.4

percentage point increase in noncontact rates from 2020q2 to 2020q4 (Table 1.1).

 As in-person interviews began to resume, the number of reclassifications declined by 3,145 

cases from 2020q2 to 2020q4 (Table 1.2).

 

1 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 (Knappenberger, Lee, 

Pham, and Armstrong, 2021). 
Consumer Expenditure Surveys - 2020 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

2018q1 5,032 55.5 25.0 6.9 12.7

2018q2 5,015 55.5 25.9 6.4 12.2

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 7,4742 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

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

2018q1 5,032 227 0 227

2018q2 5,015 241 0 241

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 7,474 855 562 293

2020q2 7,409 3,393 3,202 191

2020q3 7,784 250 34 216

2020q4 7,774 248 10 238

 

2 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 - 2020 Data Quality Profile | 6

Interview Survey

Pre-COVID-19 trends (2018q2 – 2019q4)

 Response rates declined 7.0 percentage points from 58.6 to 51.6 percent (Table 1.3).

 Refusal rates rose 5.7 percentage points from 31.1 to 36.8 percent and accounted for the largest 

share of the decline in response rates (Table 1.3).

 Other nonresponse rates rose from 4.8 to 5.5 percent, accounting for 0.7 percentage points of 

the decline in response rates (Table 1.3).

COVID-19 lockdown impacts (2020q1 – 2020q2)

 In mid-March 2020, the Census Bureau suspended all in-person interviews, causing response 

rates to drop 5.7 percentage points from 2019q4 to 2020q2 (Table 1.3).

 Refusal and noncontact rates also declined in the first two quarters of 2020 but this was offset 

by large increases in other nonresponse rates (Table 1.3).

 The other nonresponse rate rose 32.4 percentage points from 2019q4 to 2020q2 (Table 1.3) and 

nonresponse reclassifications increased by 2,944 cases through 2020q2 (Table 1.4).

3

 These impacts were largest for Wave 1 interviews because interviewers were less likely to have 

a working telephone number for these cases.

COVID-19 post-lockdown impacts (2020q3-2021q1)

 Beginning in July 2020, interviewers were resumed in-person interviews in some locations. As a 

result, other nonresponse rates decreased 29.6 percentage points while refusal rates increased 

23.5 percentage points, and noncontact rates increased 6.0 percentage points from 2020q2 to 

2021q1 (Table 1.3).

 As in-person interviews began to resume, the number of reclassifications declined by 2,883

cases from 2020q2 to 2021q1 (Table 1.4).

 

3 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 (Knappenberger, Lee, 

Pham, and Armstrong, 2021). 
Consumer Expenditure Surveys - 2020 Data Quality Profile | 7

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

2018q2 10,075 58.6 31.1 5.5 4.8

2018q3 10,053 57.4 32.6 5.5 4.5

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 10,5814 45.9 15.4 0.8 37.9

2020q3 11,190 44.5 24.2 3.9 27.4

2020q4 11,185 46.5 36.8 6.3 10.4

2021q1 11,125 46.0 38.9 6.8 8.3

 

4 The Interview Survey sample size increased in 2020q2 to support the Consumer Price Index’s 

Commodities and Services Survey sample frame. 
Consumer Expenditure Surveys - 2020 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

2018q2 10,075 1 0 1

2018q3 10,053 8 0 8

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 19

2021q1 11,125 72 2 70

 
Consumer Expenditure Surveys - 2020 Data Quality Profile | 9

2. Records Use (Interview Survey)

The records use metric measures the proportion of respondents who used records while answering the 

Interview Survey questions. Examples of records include receipts, bills, checkbooks, and bank 

statements. Interviewers record whether the respondent used records at the end of the interview. Past 

research has shown that respondents who use expenditure records reported more items with lower

levels of missingness (Abdirizak, Erhard, Lee, and McBride, 2017), so a higher prevalence of records use 

is desirable.

Interview Survey

 Records use temporarily rose in 2016 for Wave 1 respondents concurrently with a field test in 

which a subset of respondents received monetary incentives to use records.

 Since 2017, records use has been stable across interview waves.
Consumer Expenditure Surveys - 2020 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

2018q2 Wave 1 1,529 50.2 48.7 1.1

2018q2 Waves 2 & 3 2,884 47.4 52.0 0.6

2018q2 Wave 4 1,486 50.1 49.4 0.5

2018q3 Wave 1 1,494 50.3 48.9 0.9

2018q3 Waves 2 & 3 2,815 48.8 50.9 0.4

2018q3 Wave 4 1,464 48.9 50.2 0.9

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 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 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
Consumer Expenditure Surveys - 2020 Data Quality Profile | 11

3. Information Book use (Diary and Interview Surveys)

The Information Book is a recall aide the interviewer provides for respondents’ references while 

completing the interview. The Interview and Diary Surveys have separate Information Books, and each

provides the response options for demographic questions and the income bracket response options. In 

addition, the Interview Information Book provides examples of the kinds of expenditures that each 

section is intended to collect. The Information Book use metric measures how many respondents used 

the Information Book during their interviews. For interviews conducted over the phone, the Information

Book is typically only available to the respondent through the BLS website, so this metric should be 

interpreted in conjunction with the rising prevalence of telephone interviews described in Section 7. At 

the end of the interview, the interviewer records how often the respondent used the Information Book. 

Using the Information Book can improve reporting quality by clarifying concepts with concrete 

examples, and help recall. Therefore, higher rates of Information Book usage are preferred.

Diary Survey

Pre-COVID-19 trends (2018q1 – 2019q4)

 The prevalence of Information Book use among Diary Survey respondents declined 4.9

percentage points from 42.0 percent in 2018q1 to 37.1 percent in 2019q4 (Table 3.1).

COVID-19 lockdown impacts (2020q1 – 2020q2)

 In mid-March 2020, the Census Bureau suspended all in-person interviews and Information 

Book use declined by 33.0 percentage points from 2019q4 to 2020q2 (Table 3.1).

COVID-19 post-lockdown impacts (2020q3 – 2020q4)

 Beginning in July 2020, interviewers resumed in-person interviews in some locations. As a result, 

Information Book use increased 6.4 percentage points from its lowest value of 4.1 percent in 

2020q2 to 10.5 percent in 2020q4 (Table 3.1).
Consumer Expenditure Surveys - 2020 Data Quality Profile | 12

Table 3.1 Diary Survey: prevalence of Information Book use among 

respondents

Row percentage

Quarter Number of 

respondents

Used Did not use Missing

response

2018q1 2,791 42.0 54.3 3.8

2018q2 2,781 37.7 59.2 3.1

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
Consumer Expenditure Surveys - 2020 Data Quality Profile | 13

Interview Survey

Pre-COVID-19 trends (2018q2 – 2019q4)

 Information Book use in Wave 1 declined 0.8 percentage points from 47.5 percent in 2018q2 to 

46.7 percent in 2019q4 (Table 3.2).

 The rate of Wave 1 respondents who did not have access to the Information Book increased by 

2.3 percentage points from 33.6 percent in 2018q2 to 35.9 percent in 2019q4 (Table 3.2).

 In subsequent waves, the rate of Information Book use was at least 10 percentage points lower 

than in Wave 1, and about half of respondents did not have access to the Information Booklet

(Table 3.2).

COVID-19 lockdown impacts (2020q1 – 2020q2)

 In mid-March 2020, the Census Bureau suspended all in-person interviews and referred

respondents to the Information Book on the BLS website. Information Book use rate declined 

44.1 percentage points for Wave 1 respondents from 2019q4 to 2020q2 (Table 3.2).

 Declines in Information Book use were similar for subsequent waves and about 95 percent of all 

respondents in 2020q2 did not have access to the Information Book (Table 3.2).

COVID-19 post-lockdown impacts (2020q3 – 2021q1)

 Beginning in July 2020, interviewers resumed in-person interviews in some locations and 

provided respondents with disposable copies of the Information Book. As a result, Information 

Book use rose 4.8 percentage points from an average of 5.3 percent for all waves in 2020q3 to 

an average of 10.1 percent for all waves in 2021q1 (Table 3.2).

 Nevertheless, roughly 85.2 percent of respondents continue to not have access to the 

Information Book (Table 3.2). 
Consumer Expenditure Surveys - 2020 Data Quality Profile | 14
Consumer Expenditure Surveys - 2020 Data Quality Profile | 15

Table 3.2 Prevalence of Infobook use among Interview Survey respondents

Row percentage

Quarter Wave Number of 

respondents

Used Did not use No 

Infobook 

available

Missing 

response

2018q2 Wave 1 1,529 47.5 17.7 33.6 1.1

2018q2 Waves 2 & 3 2,884 36.4 16.3 46.7 0.6

2018q2 Wave 4 1,486 34.5 16.8 48.1 0.5

2018q3 Wave 1 1,494 48.1 20.6 30.5 0.9

2018q3 Waves 2 & 3 2,815 36.8 15.9 47.0 0.4

2018q3 Wave 4 1,464 33.9 14.9 50.3 0.9

2018q4 Wave 1 1,399 49.0 17.3 32.8 0.9

2018q4 Waves 2 & 3 2,782 35.6 15.9 48.1 0.4

2018q4 Wave 4 1,390 32.4 16.7 49.9 1.1

2019q1 Wave 1 1,465 46.3 15.8 36.9 1.0

2019q1 Waves 2 & 3 2,730 36.2 14.0 49.3 0.5

2019q1 Wave 4 1,428 32.8 14.6 52.2 0.4

2019q2 Wave 1 1,443 49.5 17.3 32.4 0.8

2019q2 Waves 2 & 3 2,653 35.6 15.9 48.1 0.4

2019q2 Wave 4 1,397 33.9 16.7 48.5 0.9

2019q3 Wave 1 1,401 47.5 18.0 33.3 1.2

2019q3 Waves 2 & 3 2,651 35.6 15.2 48.4 0.8

2019q3 Wave 4 1,285 35.0 13.8 50.6 0.6

2019q4 Wave 1 1,318 46.7 16.5 35.9 0.8

2019q4 Waves 2 & 3 2,637 33.7 14.9 51.2 0.2

2019q4 Wave 4 1,293 32.3 15.3 51.9 0.5

2020q1 Wave 1 1,239 37.8 15.7 45.4 1.2

2020q1 Waves 2 & 3 2,601 28.1 13.9 57.6 0.4

2020q1 Wave 4 1,362 28.8 13.7 57.0 0.4

2020q2 Wave 1 965 2.6 1.8 94.8 0.8

2020q2 Waves 2 & 3 2,559 2.9 1.8 95.0 0.3

2020q2 Wave 4 1,334 3.4 0.8 95.2 0.5

2020q3 Wave 1 1,143 6.7 2.4 89.5 1.4

2020q3 Waves 2 & 3 2,444 4.8 2.7 92.2 0.3

2020q3 Wave 4 1,393 5.2 2.1 92.4 0.4

2020q4 Wave 1 1,230 12.4 6.7 80.7 0.3

2020q4 Waves 2 & 3 2,589 9.4 3.6 86.5 0.2

2020q4 Wave 4 1,386 7.4 3.8 88.6 0.2

2021q1 Wave 1 1,250 13.3 6.2 79.9 0.6

2021q1 Waves 2 & 3 2,515 9.3 3.3 87.1 0.4

2021q1 Wave 4 1,350 8.5 4.2 86.6 0.7
Consumer Expenditure Surveys - 2020 Data Quality Profile | 16

4. Expenditure edit rates (Diary and Interview Surveys)

Edits to expenditure data are changes made to the reported expenditure data during CE data 

processing, excluding calculations (e.g. conversion of weekly value to quarterly value) and top-coding or 

suppression of reported values. Top-coding and suppression are done to protect respondent 

confidentiality in the PUMD and more information is available on the BLS Website. Expenditure edit 

rates for the Interview Survey are broken down into three categories: Imputation, allocation, and

manual edits:

 Imputation replaces missing or invalid responses with an estimate of the true value.

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

requirements. For example, if a respondent reports a non-itemized total expenditure 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 CE economists based on their 

analysis and expert judgment. 

Expenditure edit rates for the Diary Survey are only broken down into two categories: allocations and 

other edits. Almost all edits in the Diary survey are allocations. The “other edits” category encompasses 

all other expenditure edits including imputation and manual edits, though table 4.1 below shows that

these are 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 in 

general since that 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 are available in the DQP 

Reference Guide (Knappenberger, Lee, Pham, and Armstrong, 2021). 

Diary Survey

 Beginning in January 2020, CE’s sample size increased and led to an increase of over 22,000 

reported expenditures. 5 However, as response rates dropped in 2020q2, so did the number of 

expenditures (Table 4.1). 

 

5 This increase in sample size was made to support of the Consumer Price Index’s Commodities and 

Services Survey sample frame.
Consumer Expenditure Surveys - 2020 Data Quality Profile | 17

 The total rate of unedited expenditure amounts decreased 0.8 percentage points from 90.1 in 

2018q1 to 89.3 in 2020q4 (Table 4.1).

 Allocation rates rose 0.9 percentage points and drove the increase in edit rates (Table 4.1).

Table 4.1 Diary Survey: reported expenditure records 

Row percentage

Quarter Number of 

expenditures

Allocated Other edit Unedited

2018q1 86,798 9.8 0.1 90.1

2018q2 87,649 10.0 0.1 89.9

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
Consumer Expenditure Surveys - 2020 Data Quality Profile | 18

Interview Survey

 The total rate of unedited expenditure amounts increased 0.1 percentage points from 83.9

percent in 2018q2 to 84.0 percent in 2021q1 (Table 4.2).

 Even with slight fluctuation in this time period, imputation rates remained stable at 3.9 percent 

between 2018q2 and 2021q1 (Table 4.2).

6

 Decreasing edit rates were primarily driven by declines in the allocation rate from 12.0 percent 

in 2018q2 to 11.2 percent in 2021q1 (Table 4.2).

 Manual edit rates increased by 0.5 percentage points from 0.1 percent in 2018q2 to 0.6 percent 

in 2021q1 (Table 4.2).

 The rate of expenditures that were both imputed and allocated was steady at 0.2 from 2018q2

through 2021q1 (Table 4.2).

 

6

Imputation rates fell sharply in 2017q2 and allocation rates rose by an almost equal amount. Both were 

the result of a change in how BLS processes cable, internet, and telephone utility expenditures. These 

had previously been imputed, but are now allocated to preserve more of the data provided by 

respondents.
Consumer Expenditure Surveys - 2020 Data Quality Profile | 19

Table 4.2 Interview Survey: reported expenditure records

Row percentage

Quarter Number of 

expenditures

Allocated Imputed Imputed 

& 

allocated

Manual

Edit

Unedited

2018q2 270,726 12.0 3.9 0.2 0.1 83.9

2018q3 269,909 12.1 3.8 0.2 0.1 83.8

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
Consumer Expenditure Surveys - 2020 Data Quality Profile | 20

5. Income imputation rates (Diary and Interview Surveys)

This metric describes the rate of editing performed on a consumer unit’s nonresponse to at least one 

source of income. Edits made during the income imputation process covers three types of imputation 

methods, applicable to both the Interview and Diary Surveys:

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

to report the amount or to specify the range in which it falls.

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, the sum of each income component source computes total income before taxes. In 

the text that follows, income before taxes is defined as unimputed if no source of total income required 

imputation.

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 Reference Guide (Knappenberger, Lee, Pham, and 

Armstrong, 2021) and the User’s Guide to Income Imputation in the CE (Paulin, Reyes-Morales, and 

Fisher, 2018).

Diary Survey

 The rate of unimputed total income before taxes declined from 56.5 percent in 2018q1 to 53.3 

in 2020q4 (Table 5.1). 

 The number of respondents requiring both model-based and bracket response imputation 

increased 1.9 percent from 4.1 to 6.0 percent from 2018q1 to 2020q4, and contributed the most 

to the decline in unimputed income (Table 5.1).

 Model-based imputation rates are responsible for a further increase of 1.2 percentage points 

from 18.7 percent in 2018q1 to 19.9 percent in 2020q4 (Table 5.1).
Consumer Expenditure Surveys - 2020 Data Quality Profile | 21

 Bracket response imputation rates remained stable at 18.9 percent, and AVB conversion rates 

also remained stable at 1.9 percent from 2018q1 to 2020q4 (Table 5.1).

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

Row percentage

Quarter Number of 

respondents

AVB

conversions

Bracket 

imputation

Model 

imputation

Model & 

bracket 

imputation

Unedited

2018q1 2,791 1.9 18.9 18.7 4.1 56.5

2018q2 2,781 1.9 17.4 19.6 4.5 56.7

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
Consumer Expenditure Surveys - 2020 Data Quality Profile | 22

Interview Survey

 The rate of unimputed total income before taxes declined 4.3 percentage points from 59.8 in 

2018q2 to 55.5 percent in 2021q1 (Table 5.2).

 Model-based imputation rates rose 2.8 percentage points from 17.1 percent in 2018q2 to 19.9

percent in 2021q1, which accounted for the largest share of the decline in unimputed income

(Table 5.2).

 Bracket response imputation also contributed to the decline in unimputed income, rising 1.0 

percent points from 16.8 in 2018q2 to 17.8 in 2021q1 (Table 5.2). 

 The proportion of respondents requiring both model-based and bracket response imputation 

rose 0.3 percentage points from 5.2 percent in 2018q2 to 5.5 percent in 2021q1 (Table 5.2).

 The 0.2 percentage point increase in AVB conversion rates from 1.2 in 2018q2 to 1.4 in 2021q1,

contributes the least to the decline in unimputed income (Table 5.2). 
Consumer Expenditure Surveys - 2020 Data Quality Profile | 23

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

Row percentage

Quarter Number of 

respondents

AVB

conversions

Bracket 

imputation

Model 

imputation

Model & 

bracket

Unedited

2018q2 5,899 1.2 16.8 17.1 5.2 59.8

2018q3 5,773 1.4 17.9 16.6 4.7 59.4

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
Consumer Expenditure Surveys - 2020 Data Quality Profile | 24

6. Respondent burden (Interview Survey)

Respondent burden relates to the respondent’s perceived level of effort exerted to answer survey 

questions. BLS is concerned about respondent burden because higher levels of burden could negatively 

impact response rates and the quality of responses. 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 Reference Guide (Knappenberger, Lee, Pham, and Armstrong, 2021) 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 only comes at the 

end of Wave 4, the metric likely underestimates survey burden due to self-selection bias. Respondents 

who agree to participate through the final wave of the survey likely find the survey less burdensome 

than respondents who dropped out of the survey prior to completing the final survey wave. It is also 

possible that the respondent answering this question did not participate in prior interview waves. For 

example, a respondent who participates in the first three survey waves might move out of the sampled 

address prior to the final interview. If someone else moves into the sampled address in time for the final 

wave, then they would be asked these questions. 

Interview Survey

 The rate of respondents who report feeling no burden declined 6.4 percentage points from 32.4

percent in 2018q2 to 26.0 percent in 2021q1 (Table 6.1). 

 Rising rates of respondents who felt that the survey was very burdensome accounted for 3.4

percentage points of this change, rising from 12.2 percent in 2018q2 to 15.6 percent in 2021q1

(Table 6.1).

 Respondents who felt some burden participating in the survey also increased 2.2 percentage 

points from 52.8 percent in 2018q2 to 55.0 percent in 2021q1 (Table 6.1).
Consumer Expenditure Surveys - 2020 Data Quality Profile | 25

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

2018q2 1,486 32.4 52.8 12.2 2.6

2018q3 1,464 33.7 51.4 13.0 1.9

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
Consumer Expenditure Surveys - 2020 Data Quality Profile | 26

7. Survey mode (Interview Survey)

This metric measures the share of interviews collected in-person. 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. 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 COVID19 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. Some 

locations may return to in-person interviews more quickly than others, but local conditions and 

interviewer safety will set the pace. Additionally, BLS is investigating the impacts of this shift to 

telephone interviews. Early results from Lee et al. (2021) suggest that households who switched from inperson to telephone did not meaningfully change the amount of time spent on the interview or the 

number of entries reported. The proportion of rounded entries also did not change for these 

respondents. Total expenditures reported however, did decrease, and more research is forthcoming. 

Interview Survey

Pre-COVID-19 trends (2018q2 – 2019q4)

 The rate of Wave 1 respondents whose interviews were conducted in-person declined 2.1

percentage points from 76.3 percent in 2018q2 to 74.2 percent in 2019q4 (Table 7.1).

 In all but two quarters (2019q1 and 2019q4) the rate of Wave 1 telephone interviews remained 

below the 24 percent threshold (Table 7.1).

 The rate of subsequent interviews conducted in-person declined 1.8 percentage points from an 

average of 58.7 percent in 2018q2 to an average of 56.9 percent in 2019q4 (Table 7.1).

 In every quarter the rate of Wave 2 through 4 telephone interviews remained below the 48 

percent threshold (Table 7.1).
Consumer Expenditure Surveys - 2020 Data Quality Profile | 27

COVID-19 lockdown impacts (2020q1 – 2020q2)

 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 (Table 7.1).

COVID-19 post-lockdown impacts (2020q3 – 2021q1)

 Beginning in July 2020, interviewers resumed in-person interviews in some locations and the 

rate of telephone interviews declined 16.3 percentage points from an average of about 98 

percent across all waves in 2020q2 to an average of 81.7 percent across all waves in 2021q1

(Table 7.1).
Consumer Expenditure Surveys - 2020 Data Quality Profile | 28

Table 7.1 Interview Survey: survey mode

Row percentage

Quarter Wave Number of 

respondents

In-person Telephone Missing

2018q2 Wave 1 1,529 76.3 22.3 0.7

2018q2 Waves 2 & 3 2,884 59.4 39.8 0.5

2018q2 Wave 4 1,486 57.2 41.9 0.3

2018q3 Wave 1 1,494 77.6 20.1 0.7

2018q3 Waves 2 & 3 2,815 60.8 38.5 0.3

2018q3 Wave 4 1,464 56.8 42.3 0.5

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 2 & 3 2,601 50.1 49.7 0.2

2020q1 Wave 4 1,362 48.8 51.1 0.1

2020q2 Wave 1 965 1.5 98.2 0.3

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

2020q2 Wave 4 1,334 1.9 97.9 0.2

2020q3 Wave 1 1,143 13.0 86.4 0.6

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

2020q3 Wave 4 1,393 7.4 92.4 0.2

2020q4 Wave 1 1,230 28.9 71.1 0.1

2020q4 Waves 2 & 3 2,589 17.6 82.1 0.3

2020q4 Wave 4 1,386 14.6 85.3 0.1

2021q1 Wave 1 1,250 28.7 70.9 0.4

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

2021q1 Wave 4 1,350 12.2 87.5 0.3
Consumer Expenditure Surveys - 2020 Data Quality Profile | 29

8. Survey Response Time (Diary and Interview Surveys)

For both Interview and Diary Surveys, survey response time is the amount of time needed to complete 

an interview. For the Interview Survey, the survey response time metric is the median length of time to 

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

time to complete the computer assisted personal interview (CAPI) component that collects information

about income and demographics. Survey response time is 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

 The time to complete the personal interview component for income and demographics in the 

Diary Survey remained just over one-half hour from 31.2 minutes in 2018q1 to 32.7 minutes in 

2020q4 (Table 8.1).
Consumer Expenditure Surveys - 2020 Data Quality Profile | 30

Table 8.1 Diary Survey: median length of 

time to complete the interview components 

(income and demographics)

Quarter Number of

respondents

Minutes

2018q1 2,791 31.2

2018q2 2,781 32.2

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
Consumer Expenditure Surveys - 2020 Data Quality Profile | 31

Interview Survey

 Median time to complete Wave 1 interviews was, at its lowest, 70.5 minutes in 2018q2, but was 

between 74.1 and 78.8 minutes each quarter thereafter (Table 8.2).

 Median time to complete Waves 2 and 3 interviews rose 5.0 minutes from 49.6 minutes in 

2018q2 to 54.6 minutes in 2021q1 (Table 8.2).

 Wave 4 interviews similarly took 5.3 minutes longer, rising from 56.4 minutes in 2018q2 to 61.7

minutes in 2021q1 (Table 8.2).

 These increases in survey response time can in part be explained by the addition of a new 

extended recall section in 2019q2.
Consumer Expenditure Surveys - 2020 Data Quality Profile | 32

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

Minutes

Quarter Number of 

respondents

Wave 1 Waves 2 & 3 Wave 4

2018q2 5,894 70.5 49.6 56.4

2018q3 5,771 77.0 53.8 60.3

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
Consumer Expenditure Surveys - 2020 Data Quality Profile | 33

Conclusion

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 (Knappenberger, Lee, 

Pham, and Armstrong, 2021) to assist data users as they evaluate CE data quality and as they 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. 

Some trends are encouraging. With the limited resumption of in-person interviews in July of 

2020, several metrics impacted by the COVID-19 pandemic have begun to recover. This includes 

response rates, nonresponse reclassification rates, and Information Book use rates for the Diary and 

Interview Surveys. Additionally, half of respondents used records over the analyzed time frame. On the 

other hand, some trends warrant concern. Over the same time period, response rates and Information 

Book use remained at historical lows due to the COVID-19 pandemic. Additionally, income imputation 

rates increased for both the Diary and Interview Surveys and perceived respondent burden increased for 

the Interview Survey. Despite allowing some in-person interviews to resume, almost every interview 

continues to be conducted over the phone rather than in-person. A few metrics either showed little 

change over this time period, or had trends with an uncertain impact on data quality. Survey time for 

the Diary Survey remained stable around just over half-an-hour. Survey time did increase for the 

Interview Survey, and BLS believes that this is related to the addition of new survey questions requested 

by our customers to improve CE’s fitness for their use. 

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

be released in April 2022 with BLS’s midyear release of CE data and will report on the first half of the

2021 data. 
Consumer Expenditure Surveys - 2020 Data Quality Profile | 34

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. 

King, S., Chopova, B., Edgar, J., Gonzalez, J., McGrath, D., and Tan, L. (2009). Assessing nonresponse 

bias in the Consumer Expenditure Interview Survey. Paper Presented at the Annual Conference 

of the Joint Statistical Meetings, Vancouver, BC.

Knappenberger, C., Lee, Y., Pham, S. & Armstrong, G. (2021). Reference Guide CE Data Quality Profile. 

Program Report Series, the Consumer Expenditure Surveys. U.S. Bureau of Labor Statistics. 

Lee, Y., Biagas, D., Ogden, J., Pham, S., Steinberg, B., Smith, M., & Edwards, M. (2021). Impact of the 

COVID-19 Pandemic on Consumer Expenditure Surveys. Paper Presented at the Annual 

Conference of the American Association for Public Opinion Research, Virtual. 

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

Bureau of Labor Statistics.