1

COVID-19 Response and Data Quality Impacts in the 

CE Interview Survey 

October 2021

Yezzi Angi Lee & David Biagas

Consumer Expenditure Surveys Program Report Series

I. Introduction

The COVID-19 pandemic placed new challenges on the Bureau of Labor Statistics’ data collection 

efforts. For example, with personal contact restricted in accordance with health policy or law, surveys 

traditionally collected in-person have had to rely on other modes of collection (e.g., telephone). This 

report describes how the pandemic-induced changes in collection methods have affected data quality in 

the Interview component of the Consumer Expenditure Surveys (CE).

The CE is comprised of two household surveys, the Interview Survey and the Diary Survey, that collect 

expenditures, income, and demographic characteristics of consumers in the United States and are 

collected by the U.S. Census Bureau on behalf of the Bureau of Labor Statistics. The Interview Survey, 

which is the focus of this report, is a rotating, four-quarter panel (wave 1 through wave 4) designed to 

collect large and recurring expenditures that consumers can be expected to recall for a period of three 

months or longer. The Diary Survey, the subject of a different report on quality during the COVID-19 

pandemic1, is a two-week survey in which respondents record daily expenditures and is particularly 

important for collecting data on frequently purchased or “small-ticket” items for which expenditures are 

not likely to be recalled for long periods (e.g., detailed food expenditures, such as white bread or lettuce, 

and personal care products, such as hair care products and shaving needs).

1 For a report on the effects of the pandemic on Diary Survey data, see McBride and Graf (2021).
2

The Interview Survey is designed to be an in-person interview. Although telephone interviews are 

allowed to accommodate the respondents’ situations and to avoid refusals, they are generally limited to 

ensure better data quality. Between 2018 and 2019, the percent of wave 1 responding consumer units

2

completed via personal interview in a quarter ranged between 71.9 and 77.6 percent and the 

corresponding percent of wave 2 through 3 responding consumer units ranged between 57.9 and 60.8 as 

reported in the CE Data Quality Profile (DQP) (Knappenberger et al., 2021).

However, the COVID-19 pandemic placed new challenges on CE’s data collection efforts, causing an 

abrupt change in procedures. For example, in response to the pandemic, the Census Bureau stopped all 

personal visits in mid-March 2020 for the health and safety of both interviewers and respondents and 

shifted to telephone interviewing for the CE. In addition, the Census Bureau temporarily suspended 

mailing out advance letters notifying households of their selection for the survey. As a result, nearly all 

interviews were collected by telephone3regardless of wave in the middle of March 2020.

The DQP provides overall estimates of data quality metrics (e.g. response rates, information book usage 

rates, respondent burden etc.) over time, up to and including the onset of the COVID-19 pandemic. In this 

research, we focused on the same data quality metrics to investigate the effect of the COVID-19 on 

Interview Survey’s data quality, but we attempt to isolate data quality changes due to the change in 

protocol and not the pandemic. As part of this, we look at respondent demographics and data quality 

metrics by changes in mode of the interview. Note that, like the DQP, this report is a descriptive study,

and we provided these data for the reader to interpret. Therefore, we attempted to move away from 

performing complicated statistical analysis. In a forthcoming report, we examine the effect of the 

COVID-19 pandemic using a discontinuous growth curve model to control for consumer unit

characteristics and the changes in mode collection.

2 Although a household refers to all people who live together in the same living quarters, “consumer unit” refers to the people

living therein who are a family, or others who share in specific financial arrangements. For example, two roommates living in an 

apartment constitute one household. However, if they are financially independent, they each constitute separate consumer units

within the household. Similarly, although families are related by blood, marriage, or legal arrangement, unmarried partners who 

live together and pool income to make joint expenditure decisions constitute one consumer unit within the household. For a 

complete definition, see the CE glossary at https://www.bls.gov/cex/csxgloss.htm. 

3 According to the DQP report (Knappenberger et al., 2021)), 98 percent of respondents were interviewed by telephone. (See 

page 27)
3

II. Data and Methods 

We used data from July 2019 to June 2020, restricted to those who completed at least two interviews with 

mode information recorded4resulting in a sample size of 13,246. Table 1 shows the counts of completed 

interviews by month.

Table 1. Sample of consumer units by time period 

(N=13,246)

Type Month Count

Pre COVID-19 

2019

 July 1,182

 August 1,110

 September 1,084

 October 1,168

 November 1,123

 December 1,088

2020

 January 1,194

 February 1,089

 March 1,065

DuringCOVID19 

 April 1,068

 May 1,051

 June 1,024

1. Interview Schedule

The Interview Survey covers three months of expenditures, with each consumer unit interviewed up to 

four times over a period of consecutive quarters. For example, consumer units that were interviewed in 

January of a given year (wave 1), are interviewed again in April (wave 2), July (wave 3), and October

(wave 4); whereas consumer units interviewed in February are interviewed again in May, August, and 

November. Each wave collects the past three months of expenditures, excluding the interview month.

(That is, those interviewed in January report expenditures in October, November, and December of the 

prior year.)This study evaluates data quality across all four waves of data collection starting in July of 

2019 through June of 2020 (Figure 6 in Appendix).

4 There were 20,645 completed cases from July 2019-June 2020. Of those who completed the interview, 7,326 were removed 

because they had only one interview wave during the time period. An additional 73 cases were removed because the mode of 

interview was missing.
4

2. Definitions

We define Pre-COVID-19 as the interval from July 2019 through March 2020, a period before the start of 

the COVID-19 pandemic. During COVID-19 is a time period after the start of the COVID-19 pandemic 

and consists of data collected from April 2020 to June 2020. The change of collection methods was 

defined by using the respondent’s mode of completion from the last completed wave and compared with 

the mode of completion for the current wave. So, if a respondent completes wave 1 in-person and wave 2 

over the telephone, then that respondent would be in the in person - telephone group in wave 2. If they 

refuse to participate in wave 3, but return to the survey in wave 4 via the telephone, then they would be 

classified in the telephone-telephone group for wave 4 (and excluded from the sample in wave 3). The 

distribution of change of collection methods are shown in Table 2. Lastly, Table 3 shows counts of 

change of collection methods by prior to and during the COVID-19 pandemic. For the purpose of this 

study, we will remove 45 cases of in-person to in-person and 9 cases of telephone to in-person identified 

during the COVID-19 pandemic5.

Table 2. Count of change of collection methods (N=13,246)

Type Count

In-person to In-person 5,027

Telephone to Telephone 4,462

In-person to Telephone 3,287

Telephone to In-person 470

Table 3. Count of change of collection methods by time period (N=13,246)

COVID-19 Collection Changes Count

Pre COVID-19 

In-person to In-person 4,982

Telephone to Telephone 3,050

In-person to Telephone 1,610

Telephone to In-person 461

DuringCOVID-19 

In-person to In-person 45

Telephone to Telephone 1,412

In-person to Telephone 1,677

Telephone to In-person 9

5 Although the CE survey changed to all telephone interview during the COVID-19 pandemic, there were 54 cases in total that 

were recorded as in-person interview during COVID-19. One possible explanation for these cases is interviewers misrecorded the 

mode of collection as in-person when it was a telephone interview.
5

3. Purpose Statement

The purpose of this study is to compare the data quality metrics of the Interview Survey before and after 

the onset of the COVID-19 pandemic. Earlier research has found differences in reporting behavior and 

data quality based on mode of data collection (Biagas 2020). Since the Census Bureau switched the 

method of collection to all telephone interviewing in March 2020 in response to the COVID-19 pandemic, 

we examine whether or not the change in the collection methods affected the quality of data. However, 

due to the pandemic, it is inherently difficult to isolate changes in reports resulting from the economic 

shock from changes due to differences in mode of collection. For example, changes in spending behavior 

due to the pandemic would results in a change in total expenditures, but past research has demonstrated 

that reports of total expenditures are also associated with differences in mode. We attempt to isolate the 

changes resulting from the pandemic by treating the telephone to telephone group as a control group since 

it was not impacted by the change of collection methods due to the COVID-19 pandemic. We make a 

naïve assumption6that respondents who remained in the telephone interview shows only the effect of the 

COVID-19 pandemic on changes in data quality and not the effect of a mode change.

One of the limitation of this study is we do not have respondent’s true preference of mode (i.e. telephone 

or in-person) during the COVID-19 period. Since during the pandemic the CE Interview Survey was 

limited to telephone collection, in-person to in-person and telephone to in-person groups are missing 

during COVID-19 period. Therefore, we hypothesize that the majority of respondents who remained 

would have been classified as in-person to in-person in the pre COVID-19 period would likely fall in the

in-person to telephone group in the during COVID-19 period along with those that would have naturally 

been in the in-person to telephone group as shown in Figure 1. We expect the telephone to telephone

group to remain unchanged over the time periods. Therefore, we focus on the data quality trends of the inperson to telephone group during the COVID-19 period from in-person to in-person and in-person to 

telephone groups in the pre COVID-19 period.

6

In the pre-pandemic period, there was 4.56 percent of consumer units who changed their mode from telephone to 

in-person. 
6

Figure 1. Hypothesis 

Pre COVID-19 During COVID-19

In-person to In-person

In-person to Telephone (Shift to all telephone interview)

In-person to Telephone

Telephone to Telephone Telephone to Telephone

(Remain all telephone interview)

4. Demographic Characteristics 

Table 4 displays the demographic and socio-economic characteristics by change of collection methods in 

the pre and during COVID-19 periods. A study done by Biagas (2020) found that telephone respondents 

tend to have higher salaries and level of education than in-person respondents. We find similar results, as

the telephone to telephone respondents from pre and during COVID-19 periods reported higher income 

and own higher level of education. Next, the in-person to telephone respondents were more likely to be

older, white, and homeowners. We hypothesize the majority of respondents from in-person to in-person

group in the pre COVID-19 period would likely shift to the in-person to telephone group in the during 

COVID-19 period due to protocol change. Table 4 supports this hypothesis, as the trend for most

demographic and socio-economic characteristics in the in-person to telephone group during the COVID 

period are either similar to or falls between the averages of the in-person to in-person group and the inperson to telephone group for pre COVID-19 period. When we assume that the in-person to in-person

group during the COVID-19 period shifted to the in-person to telephone after the onset of the COVID-19 

pandemic, the increase in age of respondents for the in-person to telephone group during COVID-19 

period seems reasonable. The same reasoning can be applied for mean income, in that the decreases in the 

in-person to telephone group from pre to during COVID-19 period can be explained by the shift of the inperson to in-person group in the pre COVID-19 period to the in-person to telephone group during 

COVID-19.
7

Table 4. Sample characteristics by change of collection methods and time period 

Pre COVID-19 During COVID-197

Demographic In-person to

In-person

In-person to 

Telephone

Telephone to

In person

Telephone to

Telephone

In-person to

Telephone

Telephone to

Telephone

N 4,982 1,610 461 3,050 1,677 1,412

Mean Age

(SE)

56.1

0.3

52.7

0.4

52.8

0.8

52.4

0.3

56.7

0.4

53.3

0.4

Mean Income

(SE)

$77,750.49

$3,172.47

$83,167.43

$2,205.94

$76,458.57

$3,677.77

$91,727.41

$1,772.53

$80,153.66

$2,048.45

$91,619.63

$2,423.63

Mean Family Size

(SE)

2.4

0.02

2.5

0.04

2.5

0.07

2.3

0.03

2.4

0.03

2.4

0.04

Respondent’s Race*

 White 70.1% 69.2% 67.0% 70.3% 72.2% 70.9%

 Black 8.9% 10.4% 11.1% 10.3% 8.4% 9.1%

 Asian Pacific 4.9% 5.9% 5.0% 6.9% 4.4% 7.0%

 Hispanic 14.4% 12.5% 15.2% 10.6% 13.5% 10.8%

 Other 1.7% 1.9% 1.7% 1.9% 1.5% 2.2%

Respondent’s Sex

 Female 50.7% 53.5% 52.5% 51.4% 50.7% 50.5%

 Male 49.3% 46.5% 47.5% 48.6% 49.3% 49.5%

Respondent’s 

Education*

 Less than HS 11.1% 8.1% 9.1% 7.0% 9.1% 6.7%

 High School 24.5% 22.4% 22.6% 19.5% 25.5% 20.7%

 Some College 20.9% 21.8% 21.9% 18.8% 19.4% 19.8%

 Undergraduate 30.2% 33.7% 32.8% 37.7% 31.7% 35.4%

 Postgraduate 13.3% 14.0% 13.7% 17.0% 14.3% 17.4%

Housing Tenure* 

 Owner 66.7% 65.0% 64.6% 68.1% 71.8% 67.6%

 Other 33.3% 35.0% 35.4% 31.9% 28.2% 32.4%
8

III. Findings

To assess data quality changes, we compare the following factors before and after the onset of the 

COVID-19 pandemic: average total expenditures, survey length, record usage rates, information booklet8

usage rates, number of entries, number of missing items, number of rounded items, edit flag rates, and 

perceived burden before and after COVID-19 data collection changes and based on mode of survey 

response. As shown in Table 5, the respondents who switched their mode from in-person to telephone

during the COVID-19 period have the lowest median expenditures. Independent of time period, there was

a high percentage of respondents who did not have any access to the information booklet for telephone 

interviews.

8

Interview Survey respondents are supplied with an information booklet to assist them in answering survey questions. The 

information booklet provides examples that can clarify the kinds of expenditures that each section and item is intended to collect, 

and it also provides response options for demographic questions and bracketed response options.
9

Table 5. Data Quality metrics by change of collection method and time period 

Pre COVID-19 DuringCOVID-19

Demographic In-person to

In-person

In-person to 

Telephone 

Telephone to

In-person

Telephone to

Telephone

In-person to

Telephone

Telephone to

Telephone

N 4,982 1,610 461 3,050 1,677 1,412

Mean Survey Length in min

(SE)

65.3

0.5

57.8

0.7

59.2

1.5

57.7

0.5

59.9

0.7

60.0

0.8

Mean Expenditures

(SE)

$14,169.66

$175.71

$14,666.32

$307.11

$13,776.50

$512.10

$15,331.94

$213.45

$13,277.40

$275.10

$14,724.68

$381.19

Mean Number of Entries

(SE)

38.0

0.2

35.8

0.3

35.2

0.7

36.6

0.3

34.3

0.3

34.2

0.3

Mean # of Item-nonresponse

(SE)

0.6

0.03

0.7

0.05

0.8

0.12

0.6

0.03

0.6

0.05

0.6

0.05

Mean # of Roundings

(SE)

20.0

0.1

19.3

0.2

19.3

0.5

19.8

0.2

17.4

0.2

17.7

0.2

Mean Edit Rates

(SE)

6.7

0.1

7.2

0.2

7.5

0.3

7.8

0.1

6.7

0.1

7.2

0.2

Perceived Burden

 No Burden 38.0% 26.4% 32.5% 24.2% 35.4% 28.1%

 Burden 62.0% 73.6% 67.5% 75.8% 64.6% 71.9%

Infobook Usage

 Did not use 24.6% 2.6% 27.5% 2% 2.2% 0.8%

 Used 57.2% 3.7% 42.1% 1.8% 3.5% 2.2%

 No Access 18.2% 93.7% 30.4% 96.2% 94.4% 97.0%

Record Usage 

 Never Used 45.5% 50.9% 52.3% 49.2% 47.9% 49.7%

 Used 54.5% 49.1% 47.7% 50.8% 52.1% 50.3%

Income Impute

 Not imputed 62.5% 59.9% 57.4% 55.0% 62.5% 56%

 Imputed 37.5% 40.1% 42.6% 45.0% 37.5% 44%
10

Next, we display the visual representations of data quality metrics (median total expenditures, median 

interview time, median number of entries, and median number of rounded entries) by collection changes

across months as shown in Figures 2 through 5. Before we move on the result, the authors would like to 

acknowledge that a limitation of this study is that we do not know the respondent’s true preference of the 

mode during the COVID-19 period, since the CE Interview Survey was limited to telephone collection. 

As we show in Figure 1, we hypothesize that the pre COVID-19 in-person to in-person group will likely 

fall into the in-person to telephone group during the COVID-19 period since in-person interviewing was 

restricted. In Figure 2, the median total expenditure for the in-person to telephone group decreases at 

faster rate than the telephone to telephone group. Since we assume that the respondents from in-person to 

in-person group before the COVID-19 pandemic are included in the in-person to telephone group during 

the COVID-19 period, when we consider the trend line for this group and the in-person to telephone 

group in the pre COVID-19 periods combined, then the trend seems more flattened. This suggests that 

overall, the data quality has not decreased. As shown in Figure 3, the median total interview time for 

respondents who remained in-person to in-person for pre COVID-19 period was almost always longer 

than all other groups. When the Census Bureau switched to all telephone interviewing after the start of the 

COVID-19 pandemic, the median interview time decreased for the in-person to telephone group. The

trend for telephone to telephone group remains constant, which implies that the interview time was not 

much affected by COVID-19. Finally, the trend of the median number of entries (Figure 4) and median 

proportion of rounded values (Figure 5) remains relatively stable for both in-person to telephone group 

and telephone to telephone across the months. 
11

Figure 2. Median Total Expenditures by collection changes 

Figure 3. Median interview time by collection changes
12

Figure 4. Median number of entries by collection changes

Figure 5. Median proportion of rounded values by collection changes
13

IV. Conclusion

In this research, we investigated the effect of the COVID-19 pandemic and the resulting mode changes on

various data quality metrics in the CE Interview Survey. We discovered that respondents who switched

from an in-person to a telephone interview after the start of the COVID-19 pandemic were more likely to 

be older, white, and homeowners and assumed these were those that would have otherwise remained in 

person prior to the pandemic. We also discovered the median total expenditures decreased for the inperson to telephone group across the months. However, when we considered that the in-person to inperson group in pre COVID-19 period shifted to the in-person to telephone after the onset of the COVID 

19 pandemic, then the combined trend is flatter. The median survey length increased for the in-person to 

telephone group since the start of the COVID-19 pandemic while for the telephone to telephone group, 

the median was constant across the months. The median number of entries and the median proportion of 

rounded values displayed consistent trends across the months. There were substantial differences in the 

following data quality metrics between the collection change groups and the pre vs during COVID-19

periods: record usage rate and perceived burden, the number of entries, the number of missing entries, the 

number of rounded entries, survey length, total expenditures, information booklet usage rates and edit 

rates. (See table 5.)

Overall, we cannot draw a conclusion as to whether CE’s data quality was affected by the change in mode 

due to COVID-19. However, it appears that the changes in data quality metrics were driven by the 

underlying characteristics of the respondents rather than the change in mode. In a forthcoming CE report,

we will further look for differences in data quality resulting from the change in protocols due to the 

COVID-19 pandemic while controlling for consumer unit characteristics and the economic impact of the 

COVID-19 pandemic.
14

V. Reference 

Knappenberger, Clayton, Yezzi Lee, Sharon Pham, and Grayson Armstrong. 2020. The 2019 CE 

Data Quality Profile. Consumer Expenditure Surveys Program Report Series. 

Washington DC: U.S. Bureau of Labor Statistics. September 9, 2021.

McBride, Brett and Nikki Graf. COVID-19 CE DIARY PRELIMINARY REPORT:

Response and Data Quality Impacts. Consumer Expenditure Surveys Program Report 

Series. Washington DC: U.S. Bureau of Labor Statistics. June 2021.

Biagas, David. 2020. Investigating the Effect of Increasing Telephone Completion Thresholds on 

the Reporting of Expenses on the Consumer Expenditure Survey. Washington DC: U.S. 

Bureau of Labor Statistics
15

VI. Appendix

Figure 6. Interview Wave by Month

 

Panel 1 Panel 2 Panel 3 Panel 4 Panel 5 Panel 6 Panel 7 Panel 8 Panel 9 Panel 10 Panel 11 Panel 12 Panel 13 Panel 14 Panel 15 Panel 16 Panel 17 Panel 18 Panel 19 Panel 20 Panel 21 Panel 22 Panel 23 Panel 24 Panel 25 Panel 26 Panel 27 Panel 28 Panel 29 Panel 30 Panel 31 Panel 32 Panel 33 Panel 34 Panel 35 Panel 36 Panel 37

2018 Jan

2018 Feb

2018 March

2018 April

2018 May

2018 June

2018 July

2018 August

2018 September

2018 October 

2018 November 

2018 December

2019 Jan

2019 Feb

2019 March

2019 April

2019 May

2019 June

2019 July

2019 August

2019 September

2019 October 

2019 November 

2019 December

2020 Jan

2020 Feb

2020 March

2020 April

2020 May

2020 June

2020 July

2020 August

2020 September

2020 October 

2020 November 

2020 December

2021 January

2021 February

2021 March

2021 April

2021 May

2021 June

2021 July

2021 August

2021 September

2021 October 

2021 November 

2021 December

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Table 6. Data Dictionary 

Variable Name Variable from 

CE Interview

Description

CUID NEWID Respondent indicator 

Record Usage RECORDS =1 if used record ( RECORDS = 1,2,3)

=0 if did not used record (RECORDS = 4)

Number of rounded values Sum of the counts of any reported value with 00,25,50 or 75 

as the trailing digits for all expenditures 

Number of entries Sum of counts of reported expenditures

Number of itemnonresponse 

Sum of the counts of reported expenditures with Don’t knows 

or refusal 

Family Size FAM_SIZE Number of Members in CU

Total Expenditures ZTOTAL Total expenditures

Information Booklet Usage INFOBOOK =1 if used infobook ( INFOBOOK = 1,2,3)

=0 if did not used infobook/no access (INFOBOOK = 4,5)

Total Interview Time TOT_TIME Total Interview Time (min)

TOT_TIME/60

Number of Edits COST_ Sum of the counts of edits (COST_ =3,4,5,7,8,9,G,Q,R,S)

Income Imputation FINCBTXI =1 if imputed (FINCBTXI=100)

=0 otherwise 

Perceived Burden RES01 =1 if reported any burden (RES01 = 2,3,4,5)

=0 if reported no burden (RES01 = 1)

Wave INTERI

Month QINTRVMO Interview month

Age of reference person AGE Age of reference person (CU_CODE=1)

Highest education level of 

any member

EDUCA Less than High School (EDUCA = 1,2,3)

High School (EDUCA=4)

Some College (EDUCA=5)

Associate Degree or Bachelor’s Degree (EDUCA=6,7)

Graduate or Professional Degree (EDUCA=8) 

Housing tenure and type of 

area

CUTENURE =1 if owned (CUTENURE =1,2)

=0 otherwise (CUTENURE = 3,4,5,6)

Income before taxes FINCBTXM Total amount of family income before taxes

Race of reference person MEMBRACE

HISPANIC

(CU_CODE=1)

Hispanic (HISPANIC =1) 

White (MEMBRACE=1 & HISPANIC =0)

Black (MEMBRACE=2 & HISPANIC =0)

Asian and Pacific (MEMBRACE=4,5 & HISPANIC =0)

Other (MEMBRACE=3,6,7,8,9 & HISPANIC =0)