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Impact of the coronavirus (COVID-19) pandemic on The Employment Situation for December 2020

The material below addresses some questions about the effect of the pandemic on The Employment Situation for December 2020, which presents national-level estimates from the establishment (Current Employment Statistics, or CES) and household (Current Population Survey, or CPS) surveys.

The December estimates are also discussed in the BLS Commissioner’s statement on The Employment Situation. Also see prior assessments of the pandemic’s impact on The Employment Situation and historical data from the establishment survey and the household survey (including the unemployment rate).

Additional detail at the state and local area level will be available in forthcoming releases with data from the CES State and Metro Area and the Local Area Unemployment Statistics programs.

  1. Establishment survey: Was there an impact on data collection in the establishment survey?
  2. Household survey: What was the impact on data collection in the household survey?
  3. Household survey: How many employed people were not at work during the reference week?
  4. Household survey: What is the misclassification issue?
  5. Household survey: What would the unemployment rate be if the misclassified workers were included among the unemployed?

1. Establishment survey: Was there an impact on data collection in the establishment survey?

Yes. Data collection for the establishment survey was impacted by the pandemic. Approximately one-fifth of the establishments are assigned to four regional data collection centers for collection. Although these centers were closed during the collection period, interviewers at these centers worked remotely to collect data by telephone. Additionally, BLS encouraged businesses to report their data electronically. About 15 percent of the data that are typically collected by the data collection centers were instead collected by web this month. As a result, web collection represented 26 percent of December data, and Computer Assisted Telephone Interviewing (CATI) represented 16 percent.

Table A. Establishment survey data by collection method at first preliminary release, December 2020 and recent months (percent distribution)
Collection method December 2019 Average for 12 months
ending February 2020
November 2020 December 2020

All methods

100 100 100 100

Computer Assisted Telephone Interviewing (CATI)

24 26 14 16

Web

19 20 26 26

Electronic Data Interchange (EDI)

48 47 49 49

Touchtone Data Entry (TDE)

2 2 2 2

Fax

1 1 1 1

Other

6 3 8 7

Note: Estimates may not sum to 100 due to rounding.

The collection rate for the establishment survey was 76 percent in December. This is about the same as the average for the 12 months ending in February 2020, before data collection was impacted by the pandemic, and higher than November (74 percent). Collection rates may have been impacted slightly by pandemic-related issues. As in the past, a larger influence on the establishment survey collection rates is the length of the collection period, which can range between 10 and 16 days. The December collection period had 13 days. Additional information and a full time series is available in the establishment survey collection rate documentation.

When compared with the average for the 12 months ending in February 2020, the December collection rates for transportation and warehousing declined by more than 20 percentage points. The collection rates for all other major industries were within 10 percentage points of the average.

The second preliminary collection rate for November and the final collection rate for October were both slightly below average.

2. Household survey: What was the impact on data collection in the household survey?

The household survey is conducted by the Census Bureau and normally includes both in-person and telephone interviews, with the majority of interviews collected by telephone. Interviewing for the household survey began on December 13, 2020.

Households are in the survey’s sample for a total of 8 months, meaning that interviewers attempt to interview someone in the household each of those 8 months. Generally, households entering the sample for their first month are interviewed through a personal visit, and households in their fifth month also often receive a personal visit. Interviews for other months are generally conducted by telephone.

For the safety of both interviewers and respondents, in-person interviews were suspended on March 20, 2020. Starting in July, interviewers resumed conducting some in-person interviews on a limited basis in certain areas of the country. In December, interviewers in most areas of the country conducted in-person interviews, though only after first attempting to reach households by telephone. Also, a relatively small number of telephone interviews were conducted through two call centers in December. These call centers, which generally assist with telephone interviewing, had resumed activity on a limited basis in July.

The response rate for the household survey edged down to 77 percent in December 2020. While the rate was lower than the average of 83 percent for the 12 months ending in February 2020, it was considerably higher than the low of 65 percent in June 2020. (See table B.)

In December, the response rate for households entering the sample for their first month, which has a direct impact on response rates in successive months, remained lower than average. The response rate for these households, which normally are interviewed in person, was 11 percentage points lower than the average for the 12 months ending in February 2020. However, this was a considerable improvement over the initial months of the pandemic.

Table B. Household survey response rates by month in sample, December 2020 and recent months (percent)
Measure and period Total Month in sample interview
First Second Third Fourth Fifth Sixth Seventh Eighth

Response rate

Average for the 12 months ending in February 2020

82.5 80.1 83.1 83.7 83.8 80.7 82.4 82.7 83.6

March 2020

73.0 56.8 74.2 77.3 77.5 68.6 75.2 76.0 78.6

April 2020

69.9 46.7 63.5 75.7 78.2 68.6 72.7 76.2 78.1

May 2020

67.4 47.8 56.4 67.7 76.5 68.3 71.4 73.7 77.7

June 2020

64.9 48.4 55.8 60.7 68.9 68.4 70.9 72.0 74.3

July 2020

67.2 54.2 61.0 64.3 66.6 70.4 72.4 73.7 75.1

August 2020

70.2 60.0 65.0 67.5 69.1 72.9 74.8 75.7 76.9

September 2020

79.0 73.4 77.3 77.8 79.2 78.8 81.5 81.4 82.6

October 2020

80.3 75.6 78.1 80.0 80.1 79.8 81.5 83.3 83.6

November 2020

79.3 73.3 77.4 78.8 80.0 78.2 80.7 81.7 84.2

December 2020

76.7 68.7 74.7 77.5 77.6 74.3 78.4 80.0 82.0

Percentage point difference from average for
the 12 months ending in February 2020

March 2020

-9.5 -23.3 -8.9 -6.4 -6.3 -12.1 -7.2 -6.7 -5.0

April 2020

-12.6 -33.4 -19.6 -8.0 -5.6 -12.1 -9.7 -6.5 -5.5

May 2020

-15.1 -32.3 -26.7 -16.0 -7.3 -12.4 -11.0 -9.0 -5.9

June 2020

-17.6 -31.7 -27.3 -23.0 -14.9 -12.3 -11.5 -10.7 -9.3

July 2020

-15.3 -25.9 -22.1 -19.4 -17.2 -10.3 -10.0 -9.0 -8.5

August 2020

-12.3 -20.1 -18.1 -16.2 -14.7 -7.8 -7.6 -7.0 -6.7

September 2020

-3.5 -6.7 -5.8 -5.9 -4.6 -1.9 -0.9 -1.3 -1.0

October 2020

-2.2 -4.5 -5.0 -3.7 -3.7 -0.9 -0.9 0.6 0.0

November 2020

-3.2 -6.8 -5.7 -4.9 -3.8 -2.5 -1.7 -1.0 0.6

December 2020

-5.8 -11.4 -8.4 -6.2 -6.2 -6.4 -4.0 -2.7 -1.6

Note: In the household survey, interviewers attempt to interview each household for 8 months total. The first month is generally an in-person interview; the fifth month is often an in-person interview.

3. Household survey: How many employed people were not at work during the reference week?

In December, 5.6 million workers were classified as employed with a job but not at work during the survey reference week (not seasonally adjusted). This measure for December is higher than the typical level for this time of the year, likely reflecting the impact of the coronavirus pandemic.

There are many reasons why employed people are not at work for the entire survey reference week. Vacation and a person’s own illness are typically the most common reasons people are not at work. (See table C. All data about people with a job but not at work are not seasonally adjusted. See also data on absences from work for more information.)

Of the 5.6 million employed people not at work during the survey reference week in December 2020, one-third—or 1.9 million people—were included in the “own illness, injury, or medical problems” category. This was higher than the level in November, and almost twice as high as the average of 1.0 million for December 2016–2019. People who were not at work to care for a sick family member should be counted in the “other family or personal obligations” category. This measure was in line with the average for December in recent years.

In December 2020, 1.5 million people were included in the “other reasons” category—more than one-fourth of all employed people not at work during the survey reference week. This was higher than the average of 592,000 for December in recent years. As in earlier months, this group not at work for “other reasons” may still include some workers affected by the pandemic who should have been classified as unemployed on temporary layoff. (See item 4.)

Table C. Employed people with a job bu not at work by reason, December, selected years, not seasonally adjusted (numbers in thousands)
Month Total not at work Vacation Own illness, injury, or medical problems Childcare problems Other family or personal obligations Labor dispute Bad weather Maternity or paternity leave School or training Civic or military duty Other reasons

December 2016

3,919 1,358 891 14 367 0 178 344 174 12 579

December 2017

3,823 1,315 1,020 25 308 0 139 308 170 10 529

December 2018

3,974 1,340 990 22 258 16 209 365 129 9 636

December 2019

4,301 1,572 1,119 12 265 5 128 370 207 0 622

December 2020

5,587 1,186 1,902 86 257 8 119 375 108 0 1,544

4. Household survey: What is the misclassification issue?

Other than those who were themselves ill, under quarantine, or self-isolating due to health concerns, most people who did not work during the survey reference week due to efforts to contain the spread of the coronavirus should have been, and were, classified as “unemployed on temporary layoff.” As happened in earlier months, some people who were not at work during the entire reference week for reasons related to the pandemic were not included in this category but were instead misclassified as employed but not at work for “other reasons.” However, the degree of misclassification in recent months was considerably lower than in the initial months of the pandemic. (Learn more about the misclassification issue.)

The obvious indication of misclassification is the number of people not at work for “other reasons.” This measure has been smaller in recent months than in the initial months of the pandemic, both in the number of people and as a percentage of the total not at work. For example, the number of people not at work for “other reasons” fell from 8.1 million in April to 1.2 million in October. Late in the year, the number of people not at work for “other reasons” increased, reaching 1.5 million in December 2020, higher than the average of 592,000 for December 2016–2019.

The difference between the current number and the average for the same month in prior years has been used to estimate the potential size of the misclassification. (See item 5.) The exact extent of the misclassification is unknown; however, this represents the upper bound of our estimate of misclassification. (Not everyone included in the “other reasons” category is necessarily misclassified. Learn more about the limitations of this estimate of misclassification.)

According to usual practice, the data from the household survey are accepted as recorded. To maintain data integrity, no ad hoc actions are taken to reassign survey responses.

5. Household survey: What would the unemployment rate be if the misclassified workers were included among the unemployed?

If the misclassified workers who were recorded as employed but not at work for the entire survey reference week had been classified as “unemployed on temporary layoff,” the overall unemployment rate would have been higher than reported. This kind of exercise requires some assumptions. For example, first one needs to determine how many workers might be misclassified.

Because the exact extent of the misclassification is unknown, we had to make assumptions to construct these estimates. Specifically, we assumed that all of the increase in the number of employed people who were not at work for “other reasons” compared with the average for recent years was due solely to misclassification. We also assumed that all of these people expected to be recalled and were available to return to work.

Following this approach, there were 1.5 million workers with a job but not at work who were included in the “other reasons” category in December 2020, 952,000 higher than the average for December 2016–2019. If we assume that this 952,000 increase was entirely due to misclassification and that all of these misclassified workers expected to be recalled and were available for work, the number of unemployed people in December (on a not seasonally adjusted basis) would increase from 10.4 million to 11.4 million. The number of people in the labor force would remain at 160.0 million (not seasonally adjusted) as people move from employed to unemployed but stay in the labor force. The resulting unemployment rate would be 7.1 percent (not seasonally adjusted), compared with the official estimate of 6.5 percent (not seasonally adjusted). Estimates of people with a job but not at work are not available on a seasonally adjusted basis, so seasonally adjusted data, such as the unemployment rate mentioned in The Employment Situation news release, are not used in this exercise. (Repeating this exercise, but combining the not seasonally adjusted data on additional people with a job but not at work in the “other reasons” category with the seasonally adjusted estimates reported in The Employment Situation news release yields an unemployment rate of 7.3 percent, compared with the official seasonally adjusted rate of 6.7 percent.) Comparable calculations were previously published for each month since March 2020.

These broad assumptions represent the upper bound of our estimate of misclassification—the largest estimate of unemployment and correspondingly the highest unemployment rate. However, these assumptions probably overstate the size of the misclassification error. (Learn more about the limitations of this exercise and why BLS does not adjust the unemployment rate to account for the misclassification.)

Regardless of the assumptions made as to the degree of misclassification, the trend in the unemployment rate over the period in question is the same—that is, the rate increased in March and April, began declining in May, and showed little change in the last 2 months of the year.

BLS is continuing to evaluate the misclassification issue and will publish a detailed description of the findings in a forthcoming article.

See additional questions related to the effects of the pandemic on the household and establishment survey data, including:

Where can I learn more about methodological changes to the establishment survey birth-death model?

Where can I find information about job gains and losses by earnings?

Were household survey interviewers provided with any special guidance?

How does the pandemic affect the major labor market measures from the household survey?

What’s the difference between a furlough and a layoff in the household survey?

How are people who were absent from their jobs counted in the household survey?

Why doesn’t BLS adjust the unemployment rate to account for the misclassification?

What do we know about why people were at work part time?

Where can I find employment and unemployment by occupation?

How many people were unable to work because their employer closed or lost business due to the pandemic?

How many people want a job, but are not classified as unemployed?

How many people were not looking for work because of the pandemic?

How many people teleworked because of the pandemic?

How are these data different from the unemployment insurance (UI) claims data?

How can unemployment insurance (UI) claims be larger than the number of unemployed people?

How are workers under the Paycheck Protection Program (PPP) treated in these data?