June 2021 1

COVID-19 CE DIARY PRELIMINARY REPORT: 

Response and Data Quality Impacts

Brett McBride & Nikki L. Graf 

Melissa Edwards & Meaghan Smith, Consultants 

Consumer Expenditure Surveys Program Report Series

I. Introduction

Following the outbreak of the COVID-19 virus in the U.S. in early 2020, the Census Bureau was forced 

to adopt a number of measures to revise data collection for surveys, including for the Consumer 

Expenditure (CE) Diary Survey. Normal diary collection involved respondents handing over diaries with 

two weeks of their expenditures to the interviewer. Given quarantine and other pandemic measures, 

starting around March 19, 2020, the Census Bureau suspended personal visits, and interviewers instead 

began calling to recruit respondents and verbally collect expenditures (twice over the two-week period) 

with the aid of receipts and a diary form sent by mail or email. In a second period, starting in June 2020, 

interviewers started to provide URLs to English-speaking respondents who access the internet at least a 

few times a week to enable them to enter expenditures in an online diary. For those without internet or 

who preferred not to use an online diary, interviewers used phone transcription to record expenditures. 

This report documents how the pandemic and these revised data collection procedures affected spending 

behavior, diary reporting, and data quality in the first half of 2020. 

II. Data and Methods

In this report, we examined data from January 2020 through June 2020, which cover months included in 

CE’s midyear data release. The pandemic fully affected the last part of the data we examined (March 19 

through June 30, 2020). The data we analyzed mostly consisted of those that had undergone some editing. 

To assess the effect of COVID-19 on data quality, the analysis items compared data segmented into the 

following periods that align with changes in Census data collection protocols: 

 Baseline – January 1-March 18, 2020.1 This period involved normal procedures for diary

placement and interviewer pickup. With few exceptions, most diaries involved normal respondent

entry procedures. This was considered the baseline dataset for comparison with subsequent

COVID-19-affected time periods.

 Period 1 – March 19-May 31, 2020. In this period, personal visits ceased, and diary collection

involved interviewers calling respondents to collect expenditures respondents had been tracking.

1

 Any household with a diary placed in March with a pick-up date preceding March 19 was in the baseline period. 

(Six households with diaries placed in February that had pick-up dates on March 19 or later were also in the baseline 

period based on their diary keeping time period).
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Interviewers then transcribed entries into a paper diary. Period 1 also included phone transcription 

from a segment of completed paper diaries that interviewers could not pick up. The Bureau of 

Labor Statistics also reclassified some outcomes to designate COVID-19-related nonresponse. 

 Period 2 – June 1-30, 2020. In period 2, interviewers referred eligible respondents to online 

diaries with an alternative of phone transcription.2

A subsequent report will examine data from the second half of 2020, during which there was a phased 

resumption of in-person diary placement and pickup, in addition to the collection modes described above. 

For the data quality analysis in this report, we subset diary weeks to Consumer Units (CUs) considered 

complete for publication.3

The counts of CUs completing the interview in each time period are shown below (Table 1). 

Table 1. Sample of CUs by time period 

Month (2020) Baseline Period 1 Period 2 Total

January 614 - - 614

February 594 - - 594

March 60 399 - 459

April - 334 - 334

May - 341 - 341

June - - 318 318

Total 1,268 1,074 318 2,660

CUs having at least one week with a complete diary disposition did not always provide expenditures for 

both weeks of diary reporting, resulting in the diary counts shown below (Table 2).4

Table 2. Count of diaries having a complete disposition with entry status by time period and mode 

Diaries

With 

entries

No 

entries

Baseline 2,496 2,402 94

Period 1 2,097 2,037 60

Period 2 628 600 28

 Telephone 424 401 23

 Online 204 199 5

 

2

 There were six respondents receiving personal visits in period 2. However these were not categorized as a separate 

mode as they only involved a personal visit for diary pickup and assumedly involved diary recording processes 

similar to others in period 2 (e.g., online for one and using phone transcription for the others). 

3

 A Consumer Unit consists of families, single persons living alone or sharing a household with others but who are 

financially independent, or two or more unrelated persons living together who pool their income to make joint 

expenditure decisions. Complete diaries include CUs that were ‘temporarily absent’ during the reporting period, but 

do not include some diaries that have low or no reported expenditure amounts. 

4

 Diaries with no entries could occur based on survey editing (e.g., if the CU was temporarily absent during the 

reporting period, in which case expenditures do not reflect the location of their sampled address). 
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The assessments of the effects of COVID-19 on the Consumer Expenditure Diary Survey are based on the 

following analyses and methods:5

1) Demographic Analysis. We investigated whether COVID-19 and related procedural changes had an 

impact on the composition of the participating sample, which could have affected data quality. We 

examined demographic characteristics at the CU-level, including CU size, housing tenure, and the 

following characteristics of the reference person:6age, gender, race, Hispanic origin, and educational 

attainment. 

2) Spending Changes: Legitimate Blank Diaries. To examine the lack of expenditures among the CUs we 

analyzed, we calculated the proportion of complete diaries that were legitimate blank diaries. Among 

those interviews considered complete by processing, a legitimate blank diary was indicated by the CU 

reporting to the interviewer that they did not have expenditures that week or, for online diaries, by the CU 

marking a checkbox indicating no expenditures. Legitimate blank diaries included only those diaries 

where the calculated number of entries was zero (also referred to as a ‘blank diary’). 

In addition to analyzing legitimate blank diaries across time periods, we analyzed differences by mode for 

diaries in period 2. 

3) Expenditure Counts: Section and Mode. One indicator of a potential reduction in data quality would be 

less comprehensive reporting behavior. We examined this through statistics on the number of entries by 

diary week, broken out by section. To examine the impact of different modes on reporting, we broke out 

weekly expenditure counts by mode in period 2. For the calculation of overall diary counts we subset to 

diary weeks containing one or more entries, but for section-level analysis, we created zero counts to 

account for sections with no expenditures. Some other factors not examined in this report, such as CUs 

receiving the initial round of stimulus checks distributed under the Coronavirus Aid, Relief, and 

Economic Security Act (also known as the “CARES Act”) of 2020, may have also affected the counts of 

respondent entries.7 Additionally, we examined the extent to which interviewers prompted respondents to 

recall forgotten expenditures across time periods. 

4) Drop-Off in Weekly Reporting Behavior. We analyzed respondent reporting behavior over the twoweek period by examining the drop-off in expenditure entries over time. We measured this by calculating 

the percentage of two-week diary expenditure entries reported in week 1 (i.e., number of expenditure 

entries in week 1 over total number of expenditure entries reported over both weeks) for each CU that had 

at least 1 entry in each week, and then averaging that percentage across CUs. By limiting the analysis to 

CUs with entries in each week, we control for CUs only participating in one or the other diary weeks. 

Percentages greater than 50 reflected a drop-off in entries across the 2 weeks, potentially signaling a 

reduction in data quality. Additionally, we examined what the number of CUs with blank diary weeks 

suggested about reporting consistency. 

 

5

 For details on the methods we used, please see the appendix. 

6

 In CE, the reference person is the first member mentioned by the respondent when asked to “Start with the name of 

the person or one of the persons who owns or rents the home.” 

7

“CARES” is the official acronym for the act. See “Section 1: Short Title” of H. R. 748, “An Act: To amend the 

Internal Revenue Code of 1986 to repeal the excise tax on high cost employer-sponsored health coverage,” 116th

Congress, second session (begun 1/3/2020), https://www.congress.gov/116/bills/hr748/BILLS-116hr748enr.pdf. 
June 2021 4

5) Item Non-Response. We examined fields requiring a response, identifying those where the respondent 

did not know the answer or refused to provide one. We also analyzed the rate of item non-response in the 

cost and item description fields (excluding the Meals section8

) across the time periods, and carried out 

significance testing by mode for diaries in period 2. (For more information on statistical methods, see the 

appendix). 

III. Findings

1. Demographic Analysis 

The share of CUs that agreed to participate in the CE Diary survey was affected by COVID-19, with 

increasing rates of nonresponse observed over the quarters included in the CE midyear release. More 

information on changes in overall nonresponse and nonresponse category (e.g., noncontact, refusal) is 

available in a separate document profiling changes in the quality of CE data.9

To explore whether COVID-19 had an impact on the composition of the responding sample because of 

differential nonresponse, we examined demographic characteristics (Table 5). Reference persons in 

periods 1 and 2 generally had higher levels of education10 and were more likely to be homeowners than 

those in the baseline period. For example, 65.4 percent of those in the baseline period were homeowners, 

compared with 71.7 percent and 74.0 percent in periods 1 and 2, respectively.11 Reference persons in 

periods 1 and 2 also tended to be older than those in the baseline period.12 In addition, the sample in 

periods 1 and 2 had somewhat lower proportions of Hispanic respondents than in the baseline period.13

These differences could have been related to the change from in-person to telephone recruitment, 

prompted by COVID-19, which required more reliance on Census resources to obtain phone numbers for 

sample addresses. 

 

8

 For this section, respondents do not enter a description beyond providing the name of the vendor. 

9 The Midyear CE Data Quality Profile - 2020 

10 For more details on the tests used to determine significance, see appendix. Test for the equality of proportions of 

reference persons with a bachelor’s degree or higher – Baseline vs. Period 1: Z = -2.35, two-sided (p = 0.02); 

Baseline vs. Period 2: Z = -1.78, two-sided (p = 0.08). 

11 Baseline vs. Period 1: Z = -3.26, two-sided (p = 0.001). Baseline vs. Period 2: Z = -2.89, two-sided (p = 0.004). 

12 Test for the equality of proportions of reference persons ages 50 and older – Baseline vs. Period 1: Z = -2.40, twosided (p = 0.02); Baseline vs. Period 2: Z = -2.16, two-sided (p = 0.03). 

13 Baseline vs. Period 1: Z = 2.74, two-sided (p = 0.006). Baseline vs. Period 2: Z = 1.81, two-sided (p = 0.07).
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Table 5. Sample characteristics by time period and mode (excludes CUs with no expenditure entries) 

In Period 2:

Baseline Period 1 Period 2 Online Telephone

Number of Consumer Units 1,237 1,065 315 102 213

Reference person characteristics:

Race % % % % %

 White 80.6 81.7 85.1 81.4 86.9

 Black 9.6 9.0 7.3 6.9 7.5

 Other (incl. Asian, multi, other) 9.8 9.3 7.6 11.8 5.6

Hispanic origin

 Hispanic or Latino 13.7 10.0 9.8 5.9 11.7

 Not Hispanic or Latino 86.3 90.0 90.2 94.1 88.3

Gender

 Female 51.2 54.2 57.1 56.9 57.3

 Male 48.7 45.8 42.9 43.1 42.7

Age

 18-24 4.4 2.3 1.3 2.0 0.9

 25-34 15.4 12.4 11.1 13.7 9.9

 35-49 25.1 25.3 25.7 35.3 21.1

 50-64 27.8 28.5 32.7 27.5 35.2

 65 and older 27.3 31.5 29.2 21.6 32.9

Education

 Less than high school 7.7 5.6 7.9 1.0 11.3

 High school graduate 19.6 18.7 17.1 13.7 18.8

 Some college or associate's deg. 32.2 30.3 28.9 26.5 30.0

 Bachelor's degree or higher 40.5 45.4 46.0 58.8 39.9

CU characteristics:

CU size

 One person 29.6 32.5 28.3 21.6 31.5

 2-3 persons 48.2 47.3 51.4 51.0 51.6

 4+ persons 22.2 20.2 20.3 27.5 16.9

Housing tenure*

 Renter 33.5 28.3 25.7 21.6 27.7

 Owner 65.4 71.7 74.0 78.4 71.8

*For housing tenure, college student housing CUs (13 CUs in baseline and 1 CU in period 2) are not 

shown. 

Starting in period 2, interviewers gave eligible respondents the option of using an online diary, rather than 

telephone transcription, to record their expenditures. Looking at demographic differences by self-selected 

mode within period 2, reference persons in CUs completing online diaries were far more likely to be 

college graduates than those in CUs with diaries requiring telephone transcription (58.8 percent vs. 39.9 

percent).14 Reference persons in the online diary group were also generally younger – 51.0 percent were 

under age 50, compared with 31.9 percent in the telephone transcription group.15 In addition, CUs with 

 

14 Z = 3.15, two-sided (p = 0.002). 

15 Z = 3.26, two-sided (p = 0.001). 
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online diaries tended to be larger (27.5 percent had 4 or more persons vs. 16.9 percent in the telephone 

transcription group).16

2. Spending Changes: Legitimate Blank Diaries

The impact of COVID-19 on CE diary reporting resulted from both changes in spending patterns as well 

as potential deterioration in the quality of data collected. Using post-processed data to maintain 

consistency with the analysis sample used throughout this report, we identified CUs that experienced a 

one-week period without expenditures.17 To examine this, we calculated the proportion of complete 

diaries that were legitimate blank diaries. It should be noted that some blank diaries are removed during 

CE processing and therefore are not included in the findings presented below.18

Among those interviews considered complete by processing, legitimate blank diaries are defined as those 

in which, for a given week, a CU reported to the interviewer that its members had no expenditures. 

Additionally, in online diaries, respondents could indicate that they had no expenses by checking a 

checkbox, which appeared on the last day of the week. For the online mode, diaries with no expenditure 

entries were counted as legitimate blank diaries if either (1) the CU reported to the interviewer that they 

did not have expenditures, or (2) the CU checked the “no expenses” checkbox for that week. Legitimate 

blank diaries include only those diaries where the calculated number of entries was zero.19

Table 6 shows the proportion of legitimate blank diaries across time periods and modes of data collection, 

both overall and by diary week. The share of legitimate blank diaries remained very low across the time 

periods analyzed. Overall, just 1.4 percent of complete diaries in the baseline period were legitimate blank 

diaries, compared with 1.1 percent in period 1 and 2.1 percent in period 2.20 In both the baseline period 

and period 1, the proportion of legitimate blank diaries increased from week 1 to week 2.21 However, in 

period 2, this pattern by week is not evident – the share of legitimate blank diaries overall remained 

roughly stable between weeks 1 (1.9 percent) and 2 (2.2 percent).22

 

16 Z = 2.18, two-sided (p = 0.03).

17 In contrast to a reduction in spending (i.e., actual dollars spent), the pandemic could have led to respondents 

buying larger amounts with less frequency, an outcome that would also be consistent with a given one-week period 

not having any expenditures recorded. 

18 See the “Reference Guide CE Data Quality Profile” under the section “Final disposition rates of eligible units” 

discussing nonresponse reclassification for details.

19 Among complete diaries, there were 21 diaries in the baseline period, 21 diaries in period 1, and 4 diaries in 

period 2 that had entries, even though the interviewer reported that there were no entries and the CU reported that 

they did not have expenditures. Since they had entries, these diaries were not included in the counts of legitimate 

blank diaries in Table 6. 

20 These differences are not statistically significant at the .05 level. Baseline vs. Period 1: Z = 0.66, two-sided (p = 

0.51). Baseline vs. Period 2: Z = -1.31, two-sided (p = 0.19). Period 1 vs. Period 2: Z = -1.76, two-sided (p = 0.08). 

21 Week 1 vs. Week 2 in Baseline: Z = -2.74, two-sided (p = 0.006). Week 1 vs. Week 2 in Period 1: Z = -3.71, twosided (p = 0.0002).

22 Week 1 vs. Week 2 in Period 2: Z = -0.27, two-sided (p = 0.79). 
June 2021 7

Table 6. Percent of legitimate blank diaries by time period and mode 

N (diaries) Total Week 1 Week 2

Baseline 2,496 1.4% 0.7% 2.0%

Period 1 2,097 1.1% 0.3% 2.0%

Period 2 628 2.1% 1.9% 2.2%

 Telephone 424 2.6% 2.8% 2.3%

 Online 204 1.0% 0.0% 2.0%

Within period 2, we also examined differences by mode. The share of legitimate blank diaries was 2.6 

percent for diaries involving telephone transcription and 1.0 percent for online diaries.23 24 These data 

should be interpreted with caution due to the relatively small number of online diaries available for 

analysis at this stage, which, when combined with the low incidence of legitimate blank diaries, makes it 

difficult to draw conclusions. Future analysis with additional months of data involving online diaries will 

further explore mode comparisons, as well as patterns across weeks and what these may signal for data 

quality. 

3. Expenditure Counts: Section and Mode 

With the assumption that a higher number of diary entries, beyond signifying more actual expenditures, 

may indicate better data quality, we examined diary entries both at the week-level and by section, for nonblank diaries. Table 7 displays the change in entries over time and by mode of data collection. 

Table 7. Count of weekly diary entries by time period and mode 

N (diaries) Mean Median Min Max

Baseline 2,402 33.1 28 1 194

Period 1 2,037 26.2 18 1 206

Period 2 600 21.1 15 1 137

 Telephone 401 19.5 14 1 137

 Online 199 24.3 17 1 111

We can see that, whether due to actual pandemic-induced changes in spending patterns or deterioration in 

reporting behavior, CE diary CUs reported a significantly lower average number of expenditures in each 

subsequent time period, with a 21 percent decline in period 1 (33.1 to 26.2) followed by another 19 

percent decline in period 2 (26.2 to 21.1).25 Although we do not control for demographic changes, this 

series of declines came despite an increase over time in homeowner CUs, which usually have higher 

expenditures than renter CUs. Within period 2, respondents recording expenditures using online diaries 

provided a significantly higher number of entries than those providing them through phone 

 

23 This difference was not statistically significant: Z = -1.33, two-sided (p = 0.18). 

24 The Proof of Concept Test report (2018) appeared to find a similar pattern by mode – the share of legitimate blank 

diaries was 2.6 percent among paper diaries and 0.3 percent among online diaries (there are several methodological 

differences between the Proof of Concept Test and the production data analyzed in this report, however). Future 

analysis of legitimate blank diaries may provide additional insight into these mode comparisons. 

25 For more details on the tests used to determine significance, see appendix. Wilcoxon Rank-Sum two sample test; 

Baseline to Period 1, Z = -12.40, two-sided (p < 0.0001). Period 1 to Period 2, Z = -3.91, two-sided (p < 0.0001). 
June 2021 8

transcription.26 Reduced reporting in period 2 among telephone respondents could indicate the presence of 

underreported expenditures due to recall error among those respondents, compared to the more 

contemporaneous reporting made possible via online diaries. However, it is likely that the difference in 

size between CUs placed with online diaries (larger) and CUs involving telephone transcription (smaller) 

explains this gap between modes. This mode difference will be examined further as part of a future report, 

to see whether controlling for factors other than mode (e.g., size of CU) explains the difference. To 

further investigate changes in expenditure counts, we examined data by Diary section across the time 

periods (Table 8).27

Table 8. Count of weekly Diary section entries by time period and mode 

Food for Home Meals Away Clothing Other

N (diaries) Mean Median Mean Median Mean Median Mean Median

Baseline 2,402 19.6 16 4.1 3 0.9 0 8.5 7

Period 1 2,037 17.1 11 1.7 1 0.4 0 6.9 5

Period 2 600 12.7 5.5 1.9 1 0.5 0 6.0 4

 Telephone 401 12.1 6 1.6 1 0.4 0 5.4 4

 Online 199 13.9 4 2.3 1 0.9 0 7.2 6

These counts show a decline in the median entries over time, for all sections except clothing. In addition 

to the section counts presented above, we can focus on the change in counts for specific section 

combinations for which the pandemic was expected to have differential impacts (Table 9). 

Table 9. Percent of decline in average diary entries by section reported in subsequent time periods relative 

to baseline time period 

N (diaries) Food for Home

Meals Away and 

Clothing Other

Baseline 2,402 19.6 entries 5 entries 8.5 entries

Period 1 2,037 -12.8% -58.0% -18.8%

Period 2 600 -35.2% -52.0% -29.4%

From this table, we can see the declines in entries were likely due, at least in part, to changes in spending 

behavior prompted by COVID-19. Among the Diary sections most affected by COVID-19-prompted 

closures (e.g., fewer clothing purchases due to the increase in shuttered stores, fewer restaurant meal 

purchases), CUs reported 58.0 percent fewer entries in period 1 than in the baseline period. This change in 

pattern from the baseline period for Meals Away, Clothing, and Other expenditures provides evidence 

that some of the diary reporting declines reflected an actual curtailing of purchases. At the same time, 

there was a decline of 12.8 percent in total entries in the Food for Home section in which grocery 

purchases are collected. This is counter to what would be expected during a period when at-home food 

expenditures were noted to have increased and the decline in this section’s entries offers evidence for a 

 

26 Wilcoxon Rank-Sum two sample test; Z = 2.98, two-sided (p = 0.03).

27 The Consumer Expenditure Diary consists of four sections: “Food and Drinks for Home Consumption” (or “Food 

for Home”), “Meals, Snacks, and Drinks Away from Home” (or “Meals Away”) which includes delivered or takeout food, “Clothing, Shoes, Jewelry, and Accessories” (or “Clothing”), and “All Other Products, Services, and 

Expenses” (or “Other”). 
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change in diary reporting behavior.28 Further examination of this, presented below, reveals that the 

incidence of unitemized expenditures (e.g., “groceries” instead of the preferred itemized descriptions 

“milk,” “bread,” etc.) in the Food for Home section increased across time periods (Table 10). 

Table 10. Share of diary weeks with ‘groceries’ as unitemized Food for Home section entry and 

associated costs 

N (diaries) % 'groceries'

Median 

('groceries')

Median

(all other)

Baseline 2,402 6.0% $53.51 $3.15 

Period 1 2,037 11.2% $71.49 $3.56 

Period 2 600 12.5% $79.06 $3.85 

 Telephone 401 10.7% $76.00 $3.68 

 Online 199 16.1% $88.78 $3.99 

From the baseline period through period 2 the percentage of diaries containing “groceries” as a descriptor 

more than doubled in that section – from 6.0 percent to 12.5 percent of diaries. Furthermore, the median 

for respondent-reported unitemized expenses for “groceries” increased over the time periods while the 

medians for itemized expenses remained in a range of $3 to $4.29 This pattern suggests that some or all of 

the reduction in entries in Table 9 was associated with poorer reporting behavior among respondents who 

may have incurred unusually large grocery expenses in these later time periods. Additionally, this general 

“groceries” entry occurred more in online diaries than in phone transcription. In summary, then, changes 

in both spending and reporting behavior were likely contributors to the decline in expenditure counts. 

Recalled Expenses 

The number of diary entries is composed of those expenditures respondents reported throughout the week 

as well as forgotten expenditures that interviewers are instructed to collect (or prompt respondents to 

enter) through ‘recall’ at the end of the reporting period. Recalled expenditures are normally entered into 

the respondent’s diary at pickup, but after the suspension of personal visits, they were collected as part of 

the phone transcription process by the interviewer. In the case of CUs placed with online diaries, 

interviewers were instructed to enter recalled expenses in a separate paper diary, especially if the CU 

decided to discontinue online diary entry. Interviewers were asked to record among their notes about the 

interview whether CUs: 1) provided any entries in the diary, and 2) had any entries to be collected by 

recall. In this analysis, a diary with no entries except for those collected by recall was defined as a “total 

recall” diary, and one that had initial and recalled-entries was a “partial recall” diary. Our analysis also 

verified the interviewer reports of recall against the actual number of entries contained in diaries and 

found only minor inconsistencies. There was a range of 0.5 percent to 1.5 percent of diaries that involved 

interviewer reports of entries (initially or by recall) without any entries actually captured. This error 

increased over time periods, but occurred with similar frequency by mode. An examination of the rate of 

interviewer-reported recall is shown below (Table 11).

 

28 See USDA Economic Research Service’s “COVID-19 Economic Implications for Agriculture, Food, and Rural 

America.” 

29 Medians are reported due to the potential for outliers at this stage of CE processing; some additional unitemized 

entries (e.g., ‘grocery receipt,’ ‘food,’ ‘grocerys’ [sic]) are also among those categorized as ‘all other.’ 
June 2021 10 

Table 11. Percent of diaries with total and partial recall30 by time period and mode 

Any Recall

Total

Recall

Partial 

Recall

Baseline (n=2,446) 17.2% 7.1% 10.1%

Period 1 (n=2,072) 30.6% 11.7% 19.0%

Period 2 (n=622) 20.7% 9.2% 11.6%

 Telephone (n=418) 25.8% 11.7% 14.1%

Online (n=204) 10.3% 3.9% 6.4%

The table indicates that recall initially became more prevalent after the suspension of personal visits. For 

context, we examined the share of diaries involving data collected mainly from telephone (Table 12). 

Table 12. Percent of diaries by mode in which majority of data collected (excluding missing) 

Mainly 

telephone

Mainly inperson

Baseline (n=2,426) 5.2% 94.8%

Period 1 (n=2,050) 89.8% 10.2%

Period 2 (n=610) 98.2% 1.8%

 Telephone (n=412) 97.8% 2.2%

Online (n=198) 99.0% 1.0%

In the baseline period, 17.2 percent of diaries for which information was provided contained at least some 

recalled entries. In this time period, only 5.2 percent of diaries involved a majority of data collection by 

phone (when excluding missing values for collection mode). The rate of any recall increased to 30.6 

percent of diaries in the period immediately following the suspension of personal visits, a time period 

when 89.8 percent of diaries were mainly collected by phone. Some interviewers may have classified the 

standard expenses recorded via phone transcription as recalled expenses. The lower rate of recall in period 

2, in which 98.2 percent of diaries involved mainly phone collection,31 was partially a result of less recall 

among CUs placed with online diaries (with a rate of recall of only 10.3 percent and only 3.9 percent of 

diaries involving total recall).32 The prevalence of recall among online diaries was roughly half of that for 

a prior test of this mode (although that test differed procedurally in involving a dedicated location for 

interviewers to supply recalled expenses). We further examined the specific expenditures recorded for the 

21 online diaries containing at least some recalled entries (the 10.3 percent of all diaries that were placed 

online). For online diaries, interviewers were instructed to enter the expenses respondents recalled in a 

paper diary. Examining the mode associated with entries, it was observed that 12 of the diaries had some 

or all of their entries entered by paper form,33 with the remaining 9 having only online entries. 

 

30 This includes blank diaries but excludes diaries where response to the note about recall was blank or missing. 

31 Online collection was not tracked as part of the variable (TELPV) used for Table 12 data. There were only 6 CUs 

(11 diaries) in this period in which personal visits occurred; for the others the mode of data collection was 

undetermined. 

32 Online CUs with recall had a near-average number of entries for CUs in this time period, after including recalled 

entries, averaging 27 and 14 for the diaries with partial and total recall, respectively. 

33 Some of these diaries may have been filled out by respondents who were placed with an online diary, but changed 

their mind and proceeded to report their diary expenses by ‘paper form,’ as collected though phone transcription. 
June 2021 11 

4. Drop-Off in Weekly Reporting Behavior

As an indicator of data quality, drop-off in reporting of expenditures suggests respondent fatigue with the 

diary reporting process over a two-week period, as there is no reason to expect one week would have 

more expenditures than another on average. As measured – the proportion of two-week diary expenditure 

entries reported in week 1 – any percentage higher than 50 percent represents drop-off. To adjust for CUs 

that may have had expenditures in one week but not the other (“blank diaries”) we limited analysis to CUs 

having at least one expenditure in both weeks. Table 13 shows both the average entries per week, and the 

computed average within-CU drop-off. 

Table 13. Weekly entries and within-CU drop-off in weekly reporting (excluding blank diaries) 

Baseline 

(n=1,165)

Period 1 

(n=972)

Period 2 

(n=285)

Week 1 mean entries 35.3 28.0 22.7

Week 2 mean entries 31.8 25.5 20.4

Mean entries (total) 67.1 53.6 43.1

Mean (CU-level) drop-off 53.0% 52.4% 53.6%

This table reveals a very stable rate of drop-off across time periods, suggesting reporting behavior and 

fatigue was not affected by the changes in data collection protocol or the pandemic. The differences from 

one time period to the next were not statistically significant.34 An examination of respondent drop-off 

(and increase) in supplying any entries in a diary from one week to the next is shown in Table 14 below. 

Table 14. Extent of CU weekly participation by time period 

Both non-blank

weeks

1st week only 2nd week only Both weeks blank 

CUs CUs % CUs % CUs % CUs %

Baseline 1,268 1,165 91.9% 40 3.2% 32 2.5% 31 2.4%

Period 1 1,074 972 90.5% 60 5.6% 33 3.1% 9 <0.1%

Period 2 318 285 89.6% 15 4.7% 15 4.7% 3 0.1%

There was a slight increase in CUs that only had entries in the first of the two reporting weeks from the 

baseline to period 1 (3.2 percent to 5.6 percent respectively), but this decreased slightly by period 2 (4.7 

percent). Fewer CUs started recording entries after not doing so the first week, and a small number of the 

CUs being analyzed also had no entries. 

5. Item Non-Response

Item non-response comes from inability or refusal to provide a valid value for one of the collected fields 

of the diary. The rate of item non-response for providing a cost amount is examined in Table 15. 

 

34 Wilcoxon Rank-Sum two sample test; Baseline to Period 1, Z = -0.37, two-sided (p = 0.71). Period 1 to Period 2, 

Z = 1.02, two-sided (p = 0.31).
June 2021 12 

Table 15. Item non-response in the cost field by time period and mode (excluding blank diary weeks) 

N (entries)

Item nonresponse

Baseline 79,541 0.52%

Period 1 53,322 2.07%

Period 2 12,505 1.10%

 Telephone 7,816 1.61%

 Online 4,828 0.23%

Out of all entries, only a half of a percent involved missing cost information during the initial baseline 

period we examined. This low rate increased slightly in period 1, but declined thereafter.35 The decline in 

missing cost data was in part attributable to the improved collection of this among online diary CUs, in 

which only 0.23 percent of entries were blank.36 There was a higher prevalence of missing cost 

information in the Food for Home section among CUs involving telephone transcription than among CUs 

with online diaries. 

For item description, the Meals Away section does not involve respondents entering a description beyond 

providing the name of the vendor, and so this section was excluded from calculations (along with blank 

diary weeks). In Table 16, missing data were designated by the Census-supplied entry ‘BLANK’ (but 

they do not include the few entries that were illegible).

Table 16. Item non-response in the item description field by time period and mode (excluding blank diary 

weeks) 

N (entries)

Item nonresponse

Baseline 69,809 0.06%

Period 1 49,815 0.36%

Period 2 11,530 0.41%

 Telephone 7,164 0.27%

 Online 4,366 0.64%

As with cost, there tended to be very low rates of item non-response for the item description field. This 

did significantly increase from 0.06 percent to 0.36 percent across the initial time periods examined 

before leveling off.37 Unlike with cost, there was a larger share of online entries missing an item 

description in period 2.38

 

35 Wilcoxon Rank-Sum two sample test; Baseline to Period 1, Z = 27.04, two-sided (p < 0.0001). Period 1 to Period 

2, Z = -7.04, two-sided (p < 0.0001). 

36 Wilcoxon Rank-Sum two sample test; Telephone and Online, Z = -7.30, two-sided (p < 0.0001). In online diaries, 

respondents must fill out the business name, expenditure category and date fields, as well as one of the other fields. 

As a result, cost and description do not both need to be provided in order for the entry to be saved. 

37 Wilcoxon Rank-Sum two sample test; Baseline to Period 1, Z = 11.63, two-sided (p < 0.0001). Period 1 to Period 

2, Z = 0.77, two-sided (p = 0.44).

38 Wilcoxon Rank-Sum two sample test; Telephone and Online, Z = 3.07, two-sided (p = 0.002).
June 2021 13 

IV. Conclusion 

This report found a significant decline in weekly expenditure entries in diaries across the time periods 

examined. Deeper analysis suggests some of this was attributable to actual changes in spending patterns, 

as there was a 58.0 percent reduction from the baseline period to period 1 in diary entries for Clothing and 

Meals Away sections, compared to only a 12.8 percent decline for Food for Home purchases. The decline 

in the reported number of Food for Home entries was unlikely to be reflecting an actual decline in entries 

for these CUs, as examination of item descriptions indicated that respondents may not have itemized 

grocery expenditures during a period in which they may have had unusually large grocery purchases; 

unitemized reports of “groceries” increased from 6.0 percent to 12.5 percent during these time periods. 

Time periods 1 and 2 involved a shift in the sample composition to include a larger proportion of 

homeowners and college graduates than in the baseline period, which also may have affected the spending 

reported. The unplanned introduction of the online diary as part of routine CE diary data collection was 

necessitated by the COVID-19 pandemic, but did not appear to negatively affect the quality of data 

received. Encouragingly, the extent of entries among CUs placed with online diaries was no less than 

those collected via phone transcription. We must concede that it is hard to disentangle the effects of 

protocol from the actual changes in spending patterns during this time period using these data. We 

explored the prevalence of respondent diaries indicating an absence of spending and found minimal 

differences over time. We plan to produce a subsequent report that will further analyze many of the 

changes examined in this report and include findings related to changes in the expenditure amounts 

reported. 

Our examination of recalled expenditures suggested that changes in protocol or reporting behavior 

associated with COVID-19 were associated with an increasing number of CUs involving recall. This was 

attenuated with the introduction of online diaries, in which recall was carried out less frequently than in 

diaries involving phone transcription. Across these time periods, we found interviewer indication of 

entries/recall to be relatively accurate in association with the presence of entries. That said, the lower 

extent of recall occurring among online diarists may have caused some underreporting. 

Respondent willingness to participate in diary keeping across weeks remained steady despite the changes 

in protocols and the impact of COVID-19. The share of entries provided in the two-week period was only 

slightly higher in the first week, although there was a slight increase in the percent of CUs that only 

completed one of the two diary weeks. Generally, data quality as measured by missing data was good 

throughout the time periods examined, with cost and item description fields missing data for 

approximately 2 percent of the entries, at most. Rates of missing data suggested this was most an issue 

immediately after the onset of the COVID-19 pandemic as it leveled off or declined in period 2. 

Overall, the COVID-19 pandemic and associated procedural and spending changes had a negative effect 

on participation in the CE survey, changing the demographic characteristics of those who participated, 

and reducing the number of entries entered by those participating CUs. Further work will be necessary to 

investigate the extent to which differences in the collected data resulted from procedural changes and how 

much these differences were due to changes in how well respondents reported the expenditures they had. 
June 2021 14 

Methods Appendix 

We used unweighted data for this report, as they intended to refer only to the universe of complete diaries 

presented in Table 2, and not to the larger population. 

To carry out the analysis, we used SAS and Stata software in addition to common computer and 

calculator software. We employed a mix of tests for significance depending on the analysis. For 

demographic analysis, we used a test of the equality of proportions. 

For analysis of data quality, we used the Wilcoxon Rank-Sum two sample test. The Wilcoxon test is a 

non-parametric alternative to the independent samples t-test that can be used for data that is not normally 

distributed.