by

Geoffrey Paulin, Ph.D.

Senior Economist

Consumer Expenditure (CE) Survey Program

CE Survey Methodology Symposium

July 16, 2013

Washington, DC

Imputing Across Interviews: 

Balancing Time Savings with 

Data Quality
Reducing respondent burden 

is an important goal...

...In 2011, the average quarterly interview was one hour; 10 percent exceeded 100 minutes. 2
However, this must be balanced with 

maintaining high quality of data.

3
In 2015, the Bounding 

Interview will discontinue.

 CONSEQUENCES:

Need to add bounding information to 

current 2nd interview

Current 2nd interview time will increase, 

which was already shown to be a concern

 QUESTION: Can expenditures collected in 

the (current) 2nd interview be successfully 

imputed from (current) 3rd, 4th, & 5th

interviews to minimize response burden?

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To achieve this, the CE program is investigating 

the feasibility of imputing results from later 

interviews to the current second interview.

5

3rd 4th 5th 2nd
This presentations includes:

1. The conceptual framework currently being investigated

2. Problems encountered or anticipated

3. A request for comments 6
At present, there are three basic 

categories of expenditure under 

consideration:

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1. Utilities (Electricity, Natural Gas, 

Fuel Oil/Other Fuel, Telephone, 

and Water)

2. Apparel

3. Those for which Interview 

respondents are asked are about 

“usual” weekly/monthly 

expenditures

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1. Utilities

Reasons for considering:

Section 4 is the most time consuming

Expenditures are expected to occur each 

month, which makes processing easier (no 

need to decide in which month to place an 

expenditure; just allocate across the three)

Expected to be highly correlated with 

explanatory variables already collected 

(housing size, types of appliances, 

region/State/PSU, urban/rural, city size)

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2. Apparel

Reasons for considering:

Burden reduction.

– In 2011, 75 percent of consumer units interviewed 

reported expenditures for apparel and services (Section 

9). In these cases:

• Section 9 accounted on average for 6 percent of total 

interview time (almost 4 minutes), and increased with 

family size for consumer units up to 6 members.

• 25 percent of reporters required more than 41⁄2 minutes to 

complete the section; 10 percent required over 71⁄2 

minutes.

Many items collected in both surveys are selected 

from the Diary for integrated publications.

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3. Respondents asked about “usual” 

weekly/monthly expenditures

 Food at home

 Food away from home (except on trips)

 Alcoholic beverages at home

 Alcoholic beverages away from home 

(except on trips)

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Reasons for considering 

(GLOBALS):

 In 2011, Section 20 is the second most time-consuming 

expenditure section

 All food and alcohol items are published from Diary

 This indicates that quality of collected data is higher in Diary 

Survey than in Interview Survey.

 Imputing data for food at home from Diary was investigated, 

but dropped due to poor quality of imputed results. However, 

matching from other interviews may produce higher quality 

estimates.

 Food expenditures from the Interview Survey are required for 

supplemental poverty measures, and therefore information 

must be collected where possible.

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Procedural Concerns and 

Clarifications:

 “Back Imputation”—that is, using reports from a specific 

consumer unit’s 3rd, 4th, and 5th interviews to impute that 

consumer unit’s 2nd interview is not feasible as it:

 Causes delays in production (process cannot start until subsequent 

interviews have been completed;

 Is still subject to nonresponse. (What happens if the unit 

participates in the 2nd, but no subsequent, interview?)

 For these reasons, regression using data from ALL consumer 

units participating in 3rd, 4th, and 5th interviews will be 

performed. Collection periods will be matched for source 

data. For example: 3rd, 4th, and 5th interviews from January 

of a given year will be used to impute 2nd interview values 

collected in January of that same year.

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The “Yes/No” question will 

still be asked.

 That is, respondents will be asked whether or 

not the consumer unit incurred each 

expenditure, but not how much was spent if 

the answer is yes.

 This eliminates the need for a two-stage 

estimation procedure where the first stage 

predicts whether or not a purchase took place.

 As a result, the estimation process is much 

easier, and less prone to error, since the first 

stage is reported, not estimated.

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As noted, expenditures shall be 

estimated by regression analysis.

 Hot decking has been considered but rejected.

 Currently, hot decking is used when respondents report that an 

expenditure occurred, but not the amount. The team investigated 

the possibility of adopting this approach for the larger project.

 However, the limitations of hot decking are well-documented (e.g., 

ability to use few predictor variables; effects on variance).

 The limitations are less problematic for filling in nonresponse

blanks, especially when item nonresponse rates are low. But in this 

case, all expenditures would be imputed.

 The inability to properly preserve correlations among expenditures 

and independent variables would be detrimental to microdata

users.

 This means regression will be used.

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The first item considered 

is electricity.

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Status:

 Regressions in progress

 Models are:

The most complicated so far. They include:

– Standard demographics (age, family size, income)

– Special variables such as—

• Number/type of appliances in household, where known

• Detailed geographic data as described earlier

• Type of housing (detached, townhome, highrise, dormitory, mobile 

home, etc.)

Currently run separately for homeowners and 

renters, but may require further breakdown (e.g., 

housing tenure by region).

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Next up:

Apparel 18
Apparel status

 So far, models require only standard 

characteristics variables

 However, may need separate models for 

different family types, etc.

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And finally:

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Food and Alcoholic Beverages

+ =
Globals status

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Models have not yet been constructed, but they 

are expected to be similar to apparel.
Looking ahead:

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General questions

 Quality assessment: Will the imputed values fall 

within acceptable ranges when subjected to testing?

 Are there qualitative differences in current 3rd, 4th, 

and 5th interviews (e.g., means or variance) at least 

when compared to current 2nd interviews for which 

the models need to account?

 What are the unintended consequences of replacing 

reported with imputed data?

 Can/will covariate relationships be preserved (e.g., food 

at home with apparel)

 If not, what are the implications for the supplemental 

poverty measures, and other important uses of the data?

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Technical Questions

 Should single or multiple imputation be 

used?

 If multiple imputation is used, what is the 

proper way to use income, which is itself 

multiply imputed?

 Use average imputed income for each consumer unit the same 

way as a non-imputed variable would be used, generating five 

imputations of the Interview expenditure variable

 Obtain a regression estimate using the five imputed income 

values; shock; repeat four times. In this way, 25 regressions 

yield 5 imputed expenditure values per consumer unit.

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Next Steps:

 Continue refining models and assessing 

quality of results

 Receive and incorporate comments and 

suggestions from experts like you(!)

 Prepare an interim report on feasibility 

(October 2013)

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If you have any suggestions, comments, 

or questions of your own...

...The team looks forward to hearing from you.

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Contact Information

Geoffrey Paulin, Ph.D.

Senior Economist

Consumer Expenditure Survey Program

www.bls.gov/cex

202-691-5132

Paulin.Geoffrey@bls.gov