Supporting Statement (1220-0050) CE Part B Final 12-18-2014

Supporting Statement (1220-0050) CE Part B Final 12-18-2014.docx

Consumer Expenditure Surveys: Quarterly Interview and Diary

OMB: 1220-0050

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Supporting Statement



B. Collection of Information Employing Statistical Methods


  1. Sampling Method

    Consumer Units

    There are approximately 124 million consumer units (CUs) in the Consumer Expenditure (CE) Survey’s universe.1 A CU is the unit from which CE seeks expenditure reports. It consists of all household members in a particular housing unit or other type of living quarters who are related by blood, marriage, adoption, or some other legal arrangement. For unrelated persons it is based on financial dependence in three expenditure categories: shelter, food, and all other expenses. Unrelated persons are considered to be separate CUs if they are responsible for paying their own expenses for at least two of these categories, and they are considered to be part of the same CU if they share expenses for at least two of these categories. Approximately 97 percent of all occupied living quarters are occupied by a single CU.


For an overview of the CE sample design and the CU selection process, please refer to the Memorandum from Jay Ryan on PSUs for the Consumer Expenditure Survey’s 2010 Census-Based Sample Design (Attachment T).


The following table shows estimated numbers of CUs in all 91 strata from which PSUs were selected.2 Please see the section 2 below entitled “Primary Sampling Units (PSUs)” for more information.


Estimated Number of CUs in CE’s 91 Strata


Stratum Code

Estimated Number of CUs in the Stratum

S11A

1,828,360

S12A

7,858,766

S12B

2,395,832

S23A

3,799,819

S23B

1,725,482

S24A

1,344,986

S24B

1,119,611

S35A

2,263,653

S35B

2,234,898

S35C

2,123,283

S35D

1,117,821

S35E

1,088,601

S37A

2,580,930

S37B

2,377,788

S48A

1,683,969

S48B

1,021,527

S49A

5,152,385

S49B

1,741,202

S49C

1,696,807

S49D

1,381,514

S49E

1,243,156

S49F

546,331

S49G

210,112

N11B

2,010,453

N11C

1,700,452

N12C

1,632,959

N12D

1,398,931

N12E

1,576,507

N12F

1,430,722

N23C

1,363,860

N23D

1,308,476

N23E

1,509,512

N23F

1,307,890

N23G

1,576,106

N23H

1,570,832

N23I

1,504,137

N23J

1,376,516

N24C

1,194,440

N24D

1,141,728

N24E

1,320,671

N24F

1,183,952

N35F

1,218,992

N35G

1,061,472

N35H

1,216,063

N35I

1,023,813

N35J

1,242,837

N35K

1,059,119

N35L

1,241,485

N35M

1,031,672

N35N

1,169,991

N35O

1,098,976

N35P

1,245,281

N35Q

1,029,405

N36A

1,015,961

N36B

997,479

N36C

1,052,497

N36D

1,125,113

N36E

1,024,308

N36F

962,821

N37C

978,397

N37D

1,129,751

N37E

1,021,578

N37F

981,908

N37G

1,036,610

N37H

1,106,926

N37I

1,052,659

N37J

1,145,412

N48C

1,296,430

N48D

1,495,761

N48E

1,542,522

N48F

1,287,915

N49H

2,091,811

N49I

2,073,860

N49J

1,856,850

N49K

1,752,562

R11D

262,158

R12G

331,690

R23K

644,884

R23L

542,780

R24G

738,217

R24H

621,636

R35R

619,716

R35S

744,494

R36G

629,641

R36H

565,076

R37K

528,297

R37L

637,760

R48G

193,447

R48H

160,385

R48I

179,683

R49L

286,919

Total

124,000,000






Response Rates


The following table shows expected annual sample sizes for the Quarterly Interview Survey (CEQ) and the Diary Survey (CED) for 2015 and after. A new sample design is starting for both surveys in 2015. The CEQ has two columns, “2015” and “After 2015.” The first column is for the transition period from the old sample design to the new sample design, and the second column is for the new sample design alone. The CED has only one column and it is for the new sample design alone. Unlike the CEQ, the CED does not require a transition period.


The “Type B/C rate” is the percent of sample addresses that are not occupied housing units – they are nonexistent, nonresidential, vacant, demolished, etc.  The rest are occupied housing units, and the “Type A rate” is the percent of those occupied housing units that did not prticipate in the survey.


The response rates shown below are the CEQ’s and CED’s actual response rates over the past five years (2008-2012) minus 5 percentage points. Response rates have been decreasing over time, so the 5-year historical response rates are reduced by 5 percentage points to account for this downward trend.


Starting in 2015 the CEQ and CED will draw their samples of addresses from a new sampling frame called the Master Address File (MAF), which is a list of addresses from the 2010 census plus biannual updates from the U.S. Postal Service’s Delivery Sequence File. The CEQ and CED do not have any experience with the MAF, but the ACS does have some experience with the MAF, and the Type B/C rate of 13% comes from ACS’s experience. The Type B/C rate of 16% for the CEQ’s 2015 transition period is a weighted average of the Type B/C rates from the new and old sampling frames (13% and 20%).


The sample sizes shown below are the annual number of quarterly interviews for CEQ, and the annual number of bi-weekly diaries for CED.



Quarterly Interview

Diary

Category

2015

After 2015

2015

and After

Total Sample Size

50,400

48,000

12,000





Type B and C Noninterviews (vacant, demolished, etc.)




Number

8,064

6,240

1,560

Percent of Total Sample

16.0

13.0

13.0





Eligible Units




Number

42,336

41,760

10,440

Percent of Total Sample

84.0

87.0

87.0





Type A Noninterviews




Number

14,394

14,198

3,550

Percent of Eligible Units

34.0

34.0

34.0





Completed Interviews




Number

27,942

27,562

6,890

Percent of Eligible Units (Response Rate)

66.0

66.0

66.0




The sample size for 2012 and 2013 for Interview were approximately 61,280 annually and for Diary, the sample size in 2012 and 2013 were approximately 12,700.


For more information on the calculation of response rates, see the 2008 CE Anthology article “Response Rates in the Consumer Expenditure Survey,” by Sylvia Johnson-Herring and Sharon Krieger (Attachment Q).


In 2008 CE staff conducted a nonresponse bias study to determine whether the missing data from nonrespondents generated any bias in the Interview survey’s published estimates.  Their study was undertaken in response to an OMB directive. Results from four individual studies were synthesized, and they concluded that no bias was generated in spite of that fact that CE’s data are not “missing completely at random.”  As they said, “the results from these four studies provide a counterexample to the commonly held belief that if a survey’s data are not missing completely at random (MCAR) then its estimates are subject to nonresponse bias.”  For more information, see “Assessing Nonresponse Bias in the Consumer Expenditure Interview Survey” (Attachment R).



2. Collection Methods

Under contract with BLS, field representatives from the U.S. Census Bureau personally visit the households in the Diary and Interview surveys’ samples to collect the data. Prior to a household visit, respondents in both the Diary and Interview surveys’ are sent an advanced letter. Each household in the Diary survey is asked to record all of the expenditures it makes during a 2-week period. Field representatives visit each household in the sample three times. On the first visit, the field representatives introduce themselves, explains the survey, and leaves a diary in which the household members are asked to record all their expenditures for a 1-week period. On the second visit, the field representatives pick up the first week’s diary, ask whether there are any questions, and leave another diary for the second week. On the third visit, the field representatives pick up the second week’s diary and thank the household for participating in the survey. After participating in the survey for 2 weeks, the household is dropped from the survey, and it is replaced by another household. Each household in the Interview survey is interviewed every 3 months for 4 consecutive quarters. Trained field representatives ask household members about their expenditures over the previous 3 months. Responses are entered into a laptop computer. The households in the Interview survey are on a rotating schedule, with approximately one-fourth of the households in the sample being new to the survey each quarter. Households in both the Interview and Diary survey are sent a Thank You letter, as well as a certificate of appreciation, after completion of the Interview or second week of the Diary.


Primary Sampling Units (PSUs)

The primary sampling units (PSUs) used in the CEQ and CED are small clusters of counties. The average number of counties in the PSUs selected for the sample is approximately five. The set of sample PSUs used in the two CE surveys consist of 91 PSUs, 75 of which are also used in the Consumer Price Index (CPI). The 91 PSUs fall into three categories:


PSU

size class”

Number

of PSUs

Description

S

23

Large Metropolitan Core Based Statistical Areas (self-representing PSUs)

N

52

Small Metropolitan Core Based Statistical Areas and Micropolitan Core Based Statistical Areas (non-self-representing PSUs)

R

16

Non- Core Based Statistical Areas Areas (non-self-representing PSUs)


The BLS selected these PSUs from a stratified sample design in which one PSU was selected from each stratum. Stratification of the non-self-representing PSUs (the N and R PSUs) used a 4-variable model whose independent variables were latitude, longitude, median household income, and median household property value.


Sampling Within PSUs


Two non-overlapping sampling frames are used to select CUs for the CEQ and CED. They are the Unit and Group Quarters frames. The Unit frame is the Census Bureau’s new “Master Address File” (MAF), and it covers more than 99% of the sample. It is a list of every residential address identified in the 2010 decennial census plus biannual updates from the U.S. Postal Service’s Delivery Sequence File. The Group Quarters frame covers less than 1% of the sample and it consists of boarding houses, hotel rooms, and institutions that were found in the decennial census but are not counted as housing units. It also consists of new group quarters found via the MAF’s biannual updates, field operations, and the new college housing survey.


A “systematic sample” of households is selected from the two frames in each PSU. The first step in the selection process is sorting the households by variables that are correlated with their expenditures. The purpose of this is to ensure that households of every wealth level are well-represented in the sample. The first household in the systematic sample is selected from the sorted list using a random number generator. Then after the initial household is selected every k-th household down the list is selected where “k” is the PSU’s sampling interval.


The two frames have different sort variables. For the Unit frame, each address is assigned to a category based on whether the address is rental or owned property. Both the rental and owned categories are subdivided into quartiles of rental and property values, which are defined uniquely for each county. These eight categories are further subdivided by whether the housing unit is vacant or occupied by 1, 2, 3, or more than 4 people, and each cell is assigned a stratification code value (see table 1).


Table 1. CE Unit Frame Stratification Code Values


Renter/Owner Quartile

Number of Occupants


Vacant

1 person

2 persons

3 persons

4+ persons

Renters 1st Quartile

12

10

11

13

14

Renters 2nd Quartile

23

25

24

22

21

Renters 3rd Quartile

32

30

31

33

34

Renters 4th Quartile

43

45

44

42

41

Owners 1st Quartile

52

50

51

53

54

Owners 2nd Quartile

63

65

64

62

61

Owners 3rd Quartile

72

70

71

73

74

Owners 4th Quartile

83

85

84

82

81

Other

99






All addresses in the Unit frame fall into one of these cells. When the addresses are sorted by this stratification code, renters whose rent is in the lowest quartile are at one end of the list, and owners whose property values are in the highest quartile are at the other end of the list. The stratification code is a surrogate for sorting by expenditures.


To draw a systematic sample, the Unit frame addresses are sorted by PSU, FIPS State code, FIPS County code, the stratification variable described above, Census Tract code, Census Block code, U.S. Postal Service Zip code, Basic Street Address, and MAFID code.


The Group Quarters frame does not have a stratification code, but it has a within-PSU sort. The sort variables in this frame are: PSU, FIPS State code, FIPS County code, Census Tract code, Census Block code, and Census “half-measure” code. (This “half-measure” code identifies two of every four units in a cluster.)


CE interviews consumers who live in non-institutional group quarters, and does not interview consumers who live in institutional group quarters.


Institutional group quarters are primarily correctional facilities or nursing homes, whose residents are formally classified as “inmates or patients.” Typically, these people stay involuntarily and cannot come and go without permission and are generally under the supervision of trained staff.


Non-institutional GQs house people who stay voluntarily and are allowed to come and go without receiving permission. Many non-institutional GQs are college housing; dormitories; and fraternity and sorority housing, both on and off campus. In addition, non-institutional GQs include: hotels and motels that are used entirely or partially for persons without a usual home; shelters for the homeless with sleeping facilities.


Military quarters, with the exception of military disciplinary barracks [stockades and jails], are also categorized as non-institutional group quarters. However, only the non-institutional civilian population as opposed to military personnel is eligible to participate in the CE survey. Therefore, military non-institutional group quarters can be listed if and only if the GQ includes non-institutional, non-military units.



Estimation


The estimation procedure for both the CED and CEQ follow well-established statistical principles. The final weight for each sample CU is the product of its base weight (which is the inverse of the CU’s probability of selection); a weight adjustment to account for noninterviews; and a calibration adjustment that post-stratifies the weights to account for population undercoverage. A typical base weight for a CU in the CEQ is approximately 10,000, which means it represents 10,000 CUs – itself plus 9,999 other CUs that were not selected for the survey. A typical final weight for a CU in the CEQ is approximately 18,000, which means it represents 18,000 CUs – itself plus 17,999 other CUs that were not selected for the survey and/or did not participate in the survey.


For additional information on the sample design and estimation methodology used in the CE surveys, refer to “Chapter 16, Consumer Expenditures and Income” in the BLS Handbook of Methods (Attachment S); Jay Ryan’s memo to Richard Schwartz, “PSUs for the Consumer Expenditure Survey’s 2010 Census-Based Sample Design,” December 18, 2012 (Attachment T); and Ruth Ann Killion’s memo to Jay Ryan, “Consumer Expenditure Surveys Sample Allocation for the 2010 Census-Based Sample Design,” February 11, 2014 (Attachment U).



3. Methods to Maximize Response Rates


In the CE Surveys, keeping the noninterview rate at a low level requires special efforts, particularly from the Census Bureau Field staff. For each refusal case, the regional office sends a special letter to the address and assigns the case for follow-up by the program supervisor, supervisory field representative, or senior interviewer, taking into account time and cost considerations.


To adjust for those noninterviews that the field staff cannot convert to interviews, the sample design provides for a noninterview adjustment in the estimation procedure. The computer processing employs special techniques in the CEQ to reference data provided in the previous interview, to keep recall problems and interview time to a minimum.



4. Testing Plans

Subject to resource availability, CE plans to conduct the following studies (prior to the expiration of the clearance).  Ideally these studies will utilize non-production sample, but funding may necessitate the use of production sample for some tests.  A Non-Substantive Change Request (NCR) will be submitted for all of the proposed studies should funding and resources become available.


Test

Survey

Description

Proof-of-Concept Main Data Collection

Interview and Diary

The Proof-of-Concept test will examine the approved proposal for the redesign for the Bureau of Labor Statistics (BLS) Consumer Expenditure Survey (CE) on a small sample, by assessing potential operational, logistical, and selected data quality issues.

Outlet Questions Testing

Interview

The testing of outlet questions in production sample will assess the burden and data quality trade-offs of meeting Consumer Price Index (CPI) Telephone Point of Purchase (TPOPS) requirements in the CE survey.

Incentives Field Test

Interview and Diary

The Incentive Field Test will evaluate differential incentive amounts and structure based on other examples from the statistical agency community and previous CE tests. The test will include a non-monetary incentive component comprised of a package of information provided to respondents.

Large Scale Feasibility Pilot Test

Interview and Diary

The Large Scale Feasibility Test will evaluate the updated redesign for the CE on a large sample, by assessing potential operational, logistical, and data quality issues. The pilot test will be undertaken to evaluate the protocol before fielding of main data collection.




5. Statistical Contacts

The Census Bureau will collect the data. Within the Census Bureau, you may consult the following individuals regarding their area of expertise for further information.


Sample Design: Stephen Ash (301) 763-4294

Data Collection: Howard McGowan (301) 763-5342



11 The number of CUs comes from dividing the Census Bureau’s 2012 estimate of the number of people in the civilian non-institutional population (310 million) by the average number of people per CU (2.5).

2 The number of CUs per stratum comes from allocating the nationwide total of 124 million CUs by each stratum’s proportion of the nationwide population in the 2010 Census.

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