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? 

4 
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

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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 

21

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