Redesign Options for the Consumer 

Expenditure Survey 

 

November 10, 2011 

Prepared for:

The National Academy of Sciences

500 Fifth Street NW

Washington, DC 20001

Prepared by:

Westat

1600 Research Boulevard

Rockville, Maryland 20850-3129

(301) 251-1500
Redesign Options for the Consumer Expenditure Survey iii 

Authors 

 

The principal authors of this report are David Cantor, Sid Schneider, and Brad Edwards. Bob Fay 

and David Judkins performed the analysis of the impact of the proposed Quarterly Interview survey 

on sampling variances. Lou Rizzo assisted in the computation of statistical power of the field tests. 

Pat Cunningham and Pat Ward assisted with developing the cost estimates. 

Redesign Options for the Consumer Expenditure Survey v 

Table of Contents 

Chapter Page

Executive Summary ........................................................................................... xi 

1 Introduction ........................................................................................................ 1 

2 Objectives of the Redesign................................................................................ 3 

Sources of Measurement Error ........................................................................ 3 

Increasing Flexibility .......................................................................................... 7 

3 Potential Approaches to the Redesign of the CE Program ......................... 9 

Alternative Data Sources................................................................................... 9 

Administrative Data Linked to Respondents ................................................. 13

Administrative Data Supplied by the Respondent ......................................... 16 

Records of Expenditures ................................................................................... 21

Respondent Incentives ....................................................................................... 30

4 Recommended Design: Diary Survey.............................................................. 33

Overview.............................................................................................................. 33

Diary Survey Procedures................................................................................... 35

Diary Survey Costs and Implications for Sample Size.................................. 46

5 Recommended Design: Quarterly Interview Survey..................................... 53 

Costs of Proposed Design ................................................................................. 60

Sample Size and Precision................................................................................. 65

Discussion............................................................................................................ 74

6 Development and Evaluation of the Proposed Design ................................ 81

Common Elements............................................................................................ 81

Development and Testing of the Diary Survey .............................................. 86

Development and Testing of the Quarterly Interview Survey..................... 92

References............................................................................................................ 97
Contents (continued) 

Redesign Options for the Consumer Expenditure Survey vi 

Appendixes Page

A Survey Source of Data for Consumer 

Expenditure Survey Integrated Tables, 2009.................................................. A-1 

B Methods for Projecting Variances for New Design...................................... B-1 

C Total Variance Reductions for the Quarterly Interview Survey in 

Each of the Three Reference Periods.............................................................. C-1 

Executive Summary Tables

A Schedule for the redesign of Diary survey ...................................................... xv

B Quarterly Interview survey schedule and procedures for sample 

CUs....................................................................................................................... xvii

C Comparison of design features of current and redesigned surveys ............. xix

D Data requirements for CE analysts and redesigned CE program ............... xx

E Experimental design for field test for the Diary survey................................ xxi 

F Design for field test for interview survey that includes reference 

period as experimental factor............................................................................ xxi 

Tables

1 Use of payment instruments in a typical month, by type of 

instrument (from Foster, Meijer, Schuh, and Zabek, 2011)......................... 18

2 Use of payment instruments in a typical month, by type of 

transaction (from Foster, Meijer, Schuh, and Zabek, 2011)......................... 19

3 Percentage of households using selected electronic banking 

technologies: 1995 to 2007 (from Census Bureau, 2011)............................. 21

4 Smartphone ownership and Internet use summary (from Smith, 

2011)..................................................................................................................... 27

5 The demographics of smartphone ownership (from Smith, 2011) ............. 28

6 Comparison of design features of current and redesigned surveys ............. 35

7 Schedule for the redesigned Diary survey....................................................... 36
Contents (continued) 

Redesign Options for the Consumer Expenditure Survey vii 

Tables (continued) Page

8 Information that appears on various kinds of records of 

expenditures......................................................................................................... 40

9 Summary comparison of current and proposed CE designs ....................... 48

10 Summary of CE diary costs............................................................................... 49

11 Administrative records cost for diary .............................................................. 50

12 Quarterly Interview survey schedule and procedures for sampled 

CUs....................................................................................................................... 56

13 Summary of Quarterly Interview cost per year.............................................. 61

14 Quarterly Interview costs by mode (assume one respondent per 

CE unit) ................................................................................................................ 62

15 Administrative records cost for Quarterly Interview.................................... 64

16 Expenditure types used to simulate proposed design for the 

Quarterly Interview survey by lowest level publication group..................... 67

17 Simulation of effects on within PSU variation of the redesigned 

Quarterly Interview survey for 1-, 3-, and 12-month reference 

periods by expense categories........................................................................... 68

18 Data requirements for CE analysts and redesigned CE program ............... 77

19 Additional costs of proposed design relative to current design (in 

millions)................................................................................................................ 78

20 Experimental design for field test for the Diary survey................................ 89

21 Power for difference in response rates by sample size, level of 

response rate and size of difference................................................................. 91

22 Power for difference in match rates by number of completes, 

level of match rate and size of difference* ..................................................... 91
Contents (continued) 

Redesign Options for the Consumer Expenditure Survey viii 

Tables (continued) Page

23 Power for difference of means for selected expenditures, number 

of consumer units completing a diary and effect size* ................................. 91

24 Design for field test for interview survey that includes reference 

period as experimental factor............................................................................ 94

25 Power for difference of means for selected expenditures, 

completed interviews and effect size* ............................................................. 95

Appendix Tables

A-1 Survey source of data for Consumer Expenditure Survey 

integrated tables, 2009........................................................................................ A-1 

B-1 Definitions of new expenditure categories..................................................... B-7 

B-2 Estimates and standard errors under current design ..................................... B-24

C-1 Simulation of effects on total variance of the redesigned 

Quarterly Interview survey for a 1-month reference period and 

cuts in sample size .............................................................................................. C-1 

C-2 Simulation of effects on total variance of the redesigned 

Quarterly Interview survey for a 3-month reference period and 

cuts in sample size .............................................................................................. C-3 

C-3 Simulation of effects on total variance of the redesigned 

Quarterly Interview survey for a 12-month reference period and 

cuts in sample size .............................................................................................. C-5 

Executive Summary Figure

A Transactions per consumer per month ........................................................... xiv

Figures

1 Transactions per consumer per month ........................................................... 20

2 Weighted percent of medical expenditures for which the 

respondents used each recall method (from Schneider, 

Gustavson, Li, Göksel, DiGaetano, and Edwards, 2009)............................. 23
Contents (continued) 

Redesign Options for the Consumer Expenditure Survey ix 

Figures (continued) Page

3 Rotation schedule for proposed design for the Quarterly 

Interview survey.................................................................................................. 54

4 Percent reduction in sampling variance for a 3-month reference 

period .................................................................................................................... 72

5 Percent reduction in sampling variance for a 12-month reference 

period .................................................................................................................... 72

6 Percent reduction in sampling variance for 1-month reference 

period .................................................................................................................... 73

Redesign Options for the Consumer Expenditure Survey xi 

Executive Summary 

 Introduction 

The Consumer Expenditure Survey (CE) program, consisting of the Diary survey and the Quarterly 

Interview survey, is an ongoing source of data about consumer purchasing in the United States. The 

program also provides data crucial to the calculation of the Consumer Price Index. 

Estimates of consumer expenditures derived from CE data have tended to be lower than estimates 

derived from other sources. This discrepancy has grown larger in recent years. In addition, the 

response rate to the survey has declined significantly over the previous 10 years. These issues 

potentially increase the error in the estimates, as well as reduce the efficiency of the survey. 

Therefore, the Bureau of Labor Statistics (BLS) recently contracted with the National Academy of 

Sciences (NAS) to recommend approaches to the redesign of the CE program. NAS contracted with 

Westat to make recommendations for this redesign, with the goals of reducing measurement error; 

aligning the program with developments in the retail industry; and offering the respondents more 

flexibility in the way that they gather and report their data. In this paper, we propose several 

approaches to redesigning the CE program that address each of these goals. 

 General Approach of Redesign 

The recommended redesign addresses the NAS objectives through three interrelated changes. The 

first recommended change is to reduce respondent burden. The burden on CE respondents is 

considerable, which may reduce the quality of the information collected, and make some 

respondents unwilling to cooperate. For example, the Quarterly Interview survey averages 

approximately one hour, is repeated five times over a 12-month period, involves asking respondents 

to recall very detailed information for extended periods of time, and requires a single respondent to 

proxy for all other household members. All of these requirements lead to significant time and 

cognitive burden. 

A second recommended change to the design is to incorporate administrative and personal record 

information into the data collection, with the goals of improving data quality and reducing 

respondent burden. The third recommended change is to improve the methods used to collect the 

self-report information. Since the CE was designed in the early mid-1960s, there has been significant 
Executive Summary 

Redesign Options for the Consumer Expenditure Survey xii 

progress in designing surveys. This includes reducing the amount of proxy reporting, using various 

types of incentives and improving the design of the recall interview. Also, many new technologies 

for collecting data have emerged in recent years. 

This report is divided into three parts. The first part reviews literature on the potential role of 

alternative data sources. The second part provides the specific recommendations for a redesigned 

CE program. The third part sets forth potential evaluation studies to assess the impact of the 

proposed redesigned CE program. 

 Alternative Sources of Data 

The proposed redesign of the CE program calls for less reliance on the respondents’ memories of 

their expenditures and greater reliance on records. Records of the respondents’ expenditures are 

potentially available from several sources. 

Other data collection activities. First, data aggregators such as Neilsen and NPD obtain price and 

sales data from a large number of retailers. Neilsen claims to collect data from “virtually every major 

retail chain.” However, data aggregators collect little data from small retailers. Moreover, data 

aggregators provide little information about the statistical properties of the data. Data aggregators 

may therefore not be a suitable source of data for the CE program. 

Instead, the CE program might collect sales and price data directly from a sample of retailers and 

estimate expenditures for the purposes of the CPI. The retailers would have to provide microdata 

tailored to the needs of the CE program. Retailers might seriously consider providing such data if 

they were asked by the BLS. 

The National Consumer Panel is a joint venture of Nielsen and SymphonyIRI involving over 52,500 

households. Respondents in the households scan the bar codes of the products that they purchase. 

Although the National Consumer Panel is intended to collect comprehensive data about consumer 

expenditures, its methods are in many ways incompatible with the CE program. For example, 

documentation is absent on sampling, self-selection, nonresponse, and attrition. No studies have 

been conducted to measure the effect of any bias. The Department of Agriculture rejected the 

National Consumer Panel as a source of data about food purchases. It is probably also not suitable 

for the CE program. 
Executive Summary 

Redesign Options for the Consumer Expenditure Survey xiii 

The Department of Agriculture elected instead to recruit its own panel, which will provide data 

about food obtained for consumption at home or away from home. The methods of this program, 

known as the Food Acquisition and Purchase Survey (FoodAPS), appear to be compatible with the 

goals of the CE program in many ways. In some ways, however, the methods are not well suited to 

the CE program; for example, the data collection period and the sample size are not a good fit. 

Discussions between BLS and the Department of Agriculture seem to be warranted to determine 

whether the methods of FoodAPS could be adjusted to serve the purposes of both agencies. 

Data mining firms such as Teradata and Catalina Marketing work with loyalty card data for great 

numbers of consumers. Catalina Marketing, for example, claims to work with data from 300 million 

retail transactions per week. These data mining firms do not analyze the spending of individual 

households. The potential utility of the data that data mining firms could provide to the CE program 

is unclear. However, BLS might be able to collect data about respondents’ households directly from 

retailers that have loyalty card programs. 

Administrative Data. Data obtained directly from retailers are likely to be more accurate than 

respondent-provided data are likely to be. Other federal surveys, such as the National Immunization 

Survey and the Residential Energy Consumption Survey, have employed administrative data to 

supplement and improve the quality of data reported by respondents. 

Conceivably, CE respondents could provide their loyalty card numbers to interviewers, who would 

then ask the retailers to provide the purchasing histories for those loyalty cards. This method would 

not be perfect; a consumer may sometimes forget to give a loyalty card to the cashier or may lend 

the card to friends. Moreover, retailers do not routinely release purchasing histories. The BLS might 

explore the feasibility of obtaining purchasing history data by contacting large retailers with loyalty 

card programs. Expenditure data is also potentially available from utility companies, rental agents, 

and lenders. 

Respondent-supplied administrative data. CE respondents would need to expend little effort to 

access electronic records for their purchases made by check, electronic fund transfer, credit card, 

debit card, and online payment service. They could download the files directly from the web sites of 

financial institutions, or use financial software packages such as Mint. Alternatively, respondents 

could use software that was developed specifically for the CE program. These data files would 

contain a portion of the data required by the CE program, such as the total amount and the 

approximate date of purchases. 
Executive Summary 

Redesign Options for the Consumer Expenditure Survey xiv 

Data files would usually not exist for purchases made by cash or by money order. However, the 

results of a survey by the Federal Reserve Bank of Boston revealed that only 29.3 percent of 

purchases are by cash or money order. The remaining purchases—over 70 percent—are transacted 

by credit card, check, debit card, or other method that creates an electronic record. 

Figure A. Transactions per consumer per month

Respondents therefore can download files that potentially document over two-thirds of their 

purchases. The data would not be complete, however. The respondents would have to provide 

receipts or other documentation, or rely on their memories, to fill in the data required for the CE 

program. 

Records of expenditures. Research from the Medical Expenditure Panel Survey, the National 

Immunization Survey, and other federal data collection efforts suggest that the quality of survey data 

is enhanced when respondents provide administrative data. In the case of the CE program, 

respondents could provide receipts that list the description and price of each individual product or 

service purchased, and the date of the purchase. Respondents who had no receipt for a purchase 

could create documentation by completing a short form. Alternatively, they could create 

documentation using a smart phone, by completing an on-screen form, photographing the purchase, 

or recording a voice memorandum at the time of the purchase. 

Cash; 18.4; 29%

Money order; 0.5; 

1%

Check; 8.2; 13%

Debit card; 19; 29%

Credit card; 11.2; 

17%

Prepaid card; 0.8; 

1%

Online bill pay; 

3.3; 5%

Bank account 

payment; 3; 5%
Executive Summary 

Redesign Options for the Consumer Expenditure Survey xv 

 Recommended Redesign: Diary Survey 

We recommend that the CE program continue to collect data in separate Diary and Quarterly 

Interview surveys. Data collection in our proposed redesign of the Diary survey would follow this 

schedule: 

Table A. Schedule for the redesign of Diary survey

Initial interviewer visit to the household – In person

 Respondent signs consent form to obtain information electronically

 The method that respondent will use to provide data is chosen (paper or electronic)

 Interviewer provides a scanner to respondents who will report electronically

 Interviewer provides an envelope or box for respondents to store receipts

 Interviewer provides diary forms to respondents who will neither mail nor scan receipts

2-3 days after initial visit – Telephone

 Interviewer calls respondent, helps respondent overcome any barriers to providing data

 Interviewer continues to monitor respondent’s data reporting activity

7 days after initial visit – Telephone/In person

 If the respondent appears to be sending data electronically or on paper diligently, interviewer 

telephones; otherwise interviewer visits in person

 If interviewers visit in person, administer a recall interview

 Interviewer continues to monitor respondent’s data reporting activity

10 days after the initial visit – Telephone

 Interviewer calls respondent, helps respondent overcome any barriers to providing data

 Interviewer continues to monitor respondent’s data reporting activity

14 days after the initial visit – Telephone/In person

 If the respondent appears to be sending data electronically or on paper diligently, interviewer 

telephones; otherwise interviewer visits in-person

 Interviewers who call close out the data collection

 Interviewers who visit in person administer a recall interview and close out the data collection

The interviewer first visits the respondent, explains the survey, and helps the respondent choose a 

data collection technique. Every adult in the household is asked to provide expenditure data. The 

respondent provides the household’s loyalty card numbers and signs a consent form for the 

interviewer to collect purchasing history data from the retailers. The interviewer supplies a box or 

envelope for the respondents to store receipts and other purchase documentation. 

There are two alternative methods that respondents could use to report their data. They could report 

their expenditure data electronically or on paper. If they provide data electronically, they are given a 

small scanner. They then scan their receipts and send the scan files to a central repository. They also 

download data files for their checking, credit and debit cards, and other accounts from their financial 
Executive Summary 

Redesign Options for the Consumer Expenditure Survey xvi 

institutions’ web sites, and send these data files to the central repository. The repository system 

would extract purchase data from the receipts using optical character reading technology and 

software specially designed to extract data about individual purchases. The repository system would 

then generate a web survey that would ask the respondents to provide the remaining information 

that the CE program needs. 

For example, if a respondent purchased 10 items at Macy’s and paid with a credit card, the 

respondent would send a scan of that receipt and the credit card data file to the central repository. 

The repository system would match the entry for the purchase in the credit card data file with the 

receipt. The web survey would include questions such as “On July 5, 2011, you purchased shoes for 

$55.25 and paid by credit card. Was this purchase for a male or a female?” 

Respondents who do not provide data electronically would mail the envelopes containing their 

receipts to the central repository. They could also mail photocopies of monthly statements for their 

credit card, checking, and other accounts. Staff at the repository would scan the receipts and enter 

data from the statements. The system would generate a telephone survey for the interviewers to 

collect the remaining data needed by the CE program. 

The interviewers also collect purchasing histories from retail chains, using the loyalty card numbers 

for the respondents’ households. Of course, retail chains would have to be willing to provide these 

data. 

The interviewers monitor the activity of each household. The interviewers telephone the households 

and encourage them to provide data, whether electronically or by U.S. mail. They determine whether 

any respondents are having difficulty providing data and attempt to resolve any problems. These 

calls occur about 2 days after the initial visit, and again 7 days after the initial visit. 

If a household was not providing data adequately, an interviewer would visit the household in 

person 7 days after the initial interview. The interviewer would conduct a recall interview, in which 

the respondent would report the household expenditures during the 1-week reporting period. The 

interviewer would use an Event History Calendar technique to facilitate the respondent’s recall. 

Ten days after the initial interview, the interviewers again telephone the respondents. The 

interviewers again try to resolve any difficulties that the respondents might be experiencing and 

encourage the respondents to provide their data. 
Executive Summary 

Redesign Options for the Consumer Expenditure Survey xvii 

Fourteen days after the initial interview, the interviewers close out the data collection. If a household 

appears to have provided adequate data, electronically or by U.S. mail, this final contact is by 

telephone. Otherwise, the interviewer visits the household and conducts a recall interview. Again, 

the interviewer uses an Event History Calendar technique. 

Using data on the cost of the current Diary survey, we estimate the recommended design will cost 

approximately 60 percent more than the current design ($8 million versus $5 million). Most of this 

increase is attributable to the use of multiple respondents in each household. A smaller portion is 

from the administrative record component. 

 Recommended Design: Quarterly Interview Survey 

Data collection for our proposed redesigned Quarterly Interview survey would follow this schedule: 

Table B. Quarterly interview survey schedule and procedures for sample CUs

Initial interview - In-person interview 

 Obtain consents

 Determine data collection methods, electronic or paper

 Provide data collection instructions

 Conduct bounding interview

2 weeks, Month 1 and Month 2 after initial interview – Telephone c ontact 

 Review respondent’s provision of data, electronic or paper

 Encourage respondent to provide data

3 months after initial interview – In-person contact 

 Review records collected

 Conduct recall Interview

12 months after initial interview – Telephone/In-person 

 Mail instruction packet beforehand

 Followup telephone call to orient respondent and conduct bounding interview

 If household has changed, use initial contact protocol

12 months plus 2 weeks, 13 months, 14 months after initial interview – Telephone contact 

 Review respondent’s provision of data, electronic or paper

 Encourage respondent to provide data

15 months after initial interview – In-person interview 

 Review records collected

 Conduct recall Interview
Executive Summary 

Redesign Options for the Consumer Expenditure Survey xviii 

We recommend only two waves of data collection, instead of the current four. Each wave would last

3 months. Data about food and alchohol expenditures would be collected in summary form. The 

Diary survey would be used to estimate these expenditures for the CPI. 

As in the Diary survey, respondents would be asked to furnish their loyalty card numbers so that 

administrative data could be collected from retailers. In addition, utility and mortgage companies 

would be asked to provide expenditure data on items such as electricity, water, gas and housing. 

Unlike the Diary survey, only one respondent would provide data per household. 

As in the Diary survey, respondents could provide their data electronically. They could scan their 

receipts and send the receipt files to a central repository. They could also send the data files that they 

download for their credit card, checking, and other accounts, or they could send their receipts and 

photocopies of their monthly account statements by U.S. mail. The repository system would 

automatically extract the purchase data and generate a web survey or a telephone survey script. 

The interviewer would telephone the respondents 2 weeks, 1 month, and 2 months after the initial 

interview to encourage the respondents to send in their data, and to resolve any difficulties that the 

respondents may have encountered. 

Three months after the initial interview, the interviewer would conduct an in-person interview. This 

contact would include a recall interview if the respondent had not provided adequate data. Again, 

the recall interview would employ an Event History Calendar technique. The reference period need 

not be uniformly 3 months. We recommend that the reference period be 1 month, 3 months, or 12 

months, depending on the category of the expenditures. We recommend that the BLS continue to 

conduct research to identify the optimum recall periods. 

One year after the initial contact, the process is repeated for the second wave. The initial contact for 

the second wave is by telephone, unless the household had changed. In that case, the contact is in 

person. 

Our recommended redesign for the Quarterly Interview survey would cost nearly twice as much as 

the existing methods. The increase is attributable to the additional effort in contacting more 

households. Reducing the number of panel waves from four to two requires twice as many 

households to collect the same amount of information. However, ththis design also results in a 

significant reduction in sample variation, due to eliminating the within-household correlation across 

panel waves. For example, maintaining the current 3-month recall period for all expenditures results 
Executive Summary 

Redesign Options for the Consumer Expenditure Survey xix 

in a median reduction in sample variation of 35 percent over the current design. This variation can 

be further diminished by selectively increasing the reference period to 12 months for appropriate 

items. 

The other major cost increase is attributable to the administrative survey of retailers and utility 

companies. This accounts for approximately half of the increase. It is possible to significantly reduce 

the cost of this survey by restricting the survey to utility companies. If only utility companies are 

involved, the cost would be about 30 percent of the cost of including retailers as well. 

In summary, our recommended redesigned Diary and Quarterly Interview surveys compare to the 

existing methods as follows: 

Table. C. Comparison of design features of current and redesigned surveys

Design feature Current collection Redesigned survey 

Diary Survey 

# of Recall Interviews/CU 0-2 (depends on use of diary) 0–2 (depends on record use)

Reference period 1 week 1 week

Sample design Cross-sectional Cross-sectional

Mode Paper Web and paper

In-person/telephone interviews 3 1 to 3, depending on use of records

Telephone reminders Yes, unknown how many 1–4 depending on use of records

Number of respondents 1 person All persons 14+

Incentives None Monetary and nonmonetary

Personal electronic records None All respondents willing to use it

Use of receipts Yes, not strong emphasis Yes, very strong emphasis

Administrative Record Survey No From retailers used by respondents

Interview Survey 

# of Recall Interviews/CU 4 2

Reference period 3 months 1, 3, 12 months depending on item

Sample design Panel – 4 waves (3 months apart) Panel, 2 waves (12 months apart)

Mode CAPI Web, CAPI

In-person/telephone interviews 5 3

Telephone reminders Not known 6–7, depending on use of records

Number of respondents Main CU respondent Main CU respondent

Incentives None Monetary and Nonmonetary

Personal electronic records None All respondents willing to use it

Use of receipts Yes, not strong emphasis Yes, very strong emphasis

Administrative Record Survey No From retailers and utility companies

Our recommended redesign would meet the needs of CE analysts, as described below. 
Executive Summary 

Redesign Options for the Consumer Expenditure Survey xx 

Table D. Data requirements for CE analysts and redesigned CE program

Requirement Addressed by redesign? 

Complete picture of spending Yes. If modules are used on interview, imputation 

might be required

Level of expenditure detail Yes

Population Yes

Sample size and geographic detail May need to increase cost to meet current 

requirements

Time period and periodicity Yes

Panel component Annual estimates of change. 

It will not be possible to estimate at a CU level: (1) 

expenditures for an entire year; (2) change for 

intervals of less than 1 year. 

Integrated microdata Yes

Income Yes, but not directly addressed in recommendations

Socioeconomic information Yes

Assets and liabilities Yes, but not directly addressed in recommendations

We recognize that BLS is not likely to be in a position to spend twice as much on the survey in the 

near future. In light of this, we suggest priorities for the components of our proposed redesign. The 

highest priority should be given to the personal record component, which offers the greatest 

promise to improve measurement and reduce respondent burden. It is also the least expensive 

component associated with our recommendations. We also recommend that the use of both the 

multiple diary keepers and the incentives be tested. If they are found to reduce total survey error, 

they should be adopted. Both have the potential to improve measurement and reduce burden. We 

recommend the next highest priority should be to conduct some type of administrative survey, 

giving a survey of utility companies the highest priority. This should be the least expensive to 

administer and offers a direct substitute for a substantial portion of the current CE interview. A 

design that reduced the number of panel waves is seen as very desirable from the point of view of 

reducing respondent burden. This may be affordable if future research shows that it is possible to 

incorporate a 12-month reference period for selected items that are now collected with a 3-month 

period. This would result in a significant reduction in sampling variance and make our proposed 

design more economical. 
Executive Summary 

Redesign Options for the Consumer Expenditure Survey xxi 

 Development and Evaluation of the Proposed Redesign 

We propose methods for developing the software and other materials needed for our proposed 

redesigned CE program. We propose a series of small field tests to evaluate the software, such as the 

software to scan the receipts and send the scan files to the central repository, and to extract the 

purchase data and generate the followup surveys. The field tests would also evaluate printed 

materials, such as instructions and forms for recording purchases that have no receipts. Field tests 

could also evaluate methods for assigning data collection techniques to individual respondents, and 

for collecting administrative data from retail chains, utilities, rental agents, and others. 

A field test of the proposed redesigned Diary survey could use this design: 

Table E. Experimental design for field test for the Diary survey

 New design – respondent selection Current design

Response method Single respondent Multiple respondent 

9 $50 $70 $50/$10 $80/$20

Method 1 1 2 3 4

Method 2 5 6 7 8

Households would be assigned to have one or multiple respondents; to have a low or high value 

incentive; and to either have a data collection method assigned or to allow the respondents to 

choose a data collection method. These conditions would be compared with the current design. 

Outcome variables would include the mean level of expenditures, the proportion of expenditures 

that match retailer administrative data, the proportion of expenditures that respondents report using 

records rather than memory, nonresponse, cost, time required for data collection, and proportion of 

expenditures reported during the recall interview. 

A field test of the proposed redesigned Quarterly Interview survey could use this design: 

Table F. Design for field test for interview survey that includes reference period as 

experimental factor

 New design – respondent selection Current design

Reference Period 

Group Single respondent Multiple respondent 

$50 $70 $50/$10 $80/$20 9 

Group 1 1 2 3 4

Group 2 5 6 7 8
Executive Summary 

Redesign Options for the Consumer Expenditure Survey xxii 

Households would be assigned to have one or multiple respondents; to have a low or high value 

incentive; and to have fixed reference periods or reference periods that vary depending on the 

expenditure category. These conditions would be compared with the current design. 

 Our report discusses the number of households to include in the field tests and provides a power 

analysis. 
Redesign Options for the Consumer Expenditure Survey 1 

The Consumer Expenditure Survey (CE) program is an ongoing source of data about consumer 

purchasing in the United States. CE data have a crucial role in the calculations for the Consumer 

Price Indices (CPI) and other statistics. The CE program also provides extensive data about the 

characteristics of consumers themselves. Researchers use CE data to monitor consumer behavior 

and to study issues such as the relationship between consumers’ demographic backgrounds and 

spending. 

The design of the CE program must be periodically updated to take advantage of new technologies 

and to ensure that CE methods are aligned with changes in the retail environment and survey 

practice. Recently, the Bureau of Labor Statistics (BLS) contracted with the National Academy of 

Sciences (NAS) to review the redesign options available and to identify the most promising ones. 

The redesign is motivated by several issues. The first and most important issue is measurement 

error. Comparisons with other sources of data suggest that CE respondents tend to underreport 

their household expenditures. This underreporting may be attributable to several causes. For 

example, CE respondents must report for everyone in the household. Respondents may find this 

task to be overly burdensome and may not thoroughly gather or report expenditure data from others 

in the household. Other potential sources of error in the CE program are panel conditioning, 

frequent telephone administration of surveys that were intended to be administered face-to-face, and 

the length of the reporting period. 

The second issue pertains to changes in the survey and retail environments. Consumers are 

increasingly making purchases online or through automatic fund transfers. Also, they often buy 

many different types of merchandise in a single purchase at “big box stores” such as Target. The 

current CE methods may not adequately accommodate these expenditures. Moreover, new 

technologies may offer innovative methods for collecting expenditure data. For example, 

smartphones may provide a way for some respondents to track their purchases; financial software 

packages provide a means for respondents to download their credit card and checking account data. 

The third issue is the need for greater flexibility to reflect the diverse preferences of the respondents. 

Current CE methods do not sufficiently tailor data collection methods to the respondents. A multiIntroduction 1 
Redesign Options for the Consumer Expenditure Survey 2 

method, multi-mode approach might allow respondents to use the data collection method that is 

best suited to their preferences, their daily routines and their abilities. 

This report presents a number of approaches that BLS might pursue to redesign the CE program in 

a way that addresses these issues. The goals of the report are to analyze the challenges that the CE 

program currently faces, and to propose solutions that can improve the ability of the CE program to 

measure expenditures by U.S. consumers. The report also proposes an evaluation study to assess the 

feasibility of the proposed solutions. 

This report is organized into chapters: 

 Chapter 2 discusses the objectives of the redesign of the CE program: to reduce 

measurement error, to take into account changes in the retail industry and the 

development of new electronic tools, and to provide respondents with greater flexibility;

 Chapter 3 presents potential approaches to redesigning the CE program, with an 

emphasis on reducing reliance on the accuracy of the respondents’ recollections about 

their expenditures; 

 Chapters 4 and 5 present the proposed redesign of the Diary survey and the Quarterly 

Interview survey, respectively, including discussions of the implications of our 

recommendations for cost and precision; and 

 Chapter 6 presents several potential approaches to evaluating our redesign 

recommendations. 
Redesign Options for the Consumer Expenditure Survey 3 

Comparisons between CE data and data from the Personal Consumption Expenditures (PCE) of 

the National Income and Product Accounts, produced by the Bureau of Economic Analysis, suggest 

that CE respondents tend to underreport expenditures. Estimates of consumer expenditures from 

the CE program are generally lower than estimates from the PCE. Some of this discrepancy is 

probably due to methodological differences between the two data collection programs, as Garner et 

al. (2006) discussed:

Simply put, the Bureau of Labor Statistics collects CE expenditure data 

through sample surveys and weights the results to obtain population 

estimates. The Bureau of Economic Analysis, in contrast, calculates PCE 

estimates on the basis of industry production data collected in economic 

censuses and through surveys conducted by outside agencies. There are 

clear differences in the types of expenditure data obtained, dictated by the 

data collection methods and data sources used by the two agencies. In 

addition, the populations covered by the CE and the PCE differ. 

Even considering these methodological differences, comparisons between the CE and PCE data 

strongly suggest that CE respondents tend not to report their expenditures completely. The CE-toPCE ratio for comparable expenditures is approximately 80 percent overall. This ratio ranges 

between 60 and 70 percent for durable and non-durable goods, while it is over 90 percent for 

services (Garner, 2009). These ratios have been declining over time. For example, for comparable 

items of durable goods, the CE-to-PCE ratio declined from 88 percent to 69 percent between 1992 

and 2007 (Garner et al., 2009). 

Sources of Measurement Error 

Some of this decline is very likely due to increasing error in the CE. The response rate for the CE 

interview survey has declined steadily from 82 percent in 2000 to 74 percent in 2010 (Safir, 2011). 

This trend tracks closely the general decline in response rates for other general population surveys 

(Brick and Williams, 2009). 

Objectives of the Redesign 2 
Redesign Options for the Consumer Expenditure Survey 4 

In addition, an increasing number of CE interviews are being conducted by telephone, instead of 

face-to-face. Respondents tend to report fewer expenditures when they are interviewed by telephone 

(Safir and Goldenberg, 2008). In a face-to-face interview, the interviewers employ show cards to 

help the respondent recall expenditure items; they cannot use show cards during a telephone 

interview. Past research suggests that telephone respondents are more likely than face-to-face 

respondents to “satisfice,” or issue a response that is not very accurate but which moves the survey 

along (Hollbrook et al., 2003). “Satisficing” is especially likely with challenging interviews that 

require a great deal of recall, like the CE interview.

Respondent burden may be an additional source of measurement error in the CE program (Lessler, 

1987; Cantor, 2010). First, respondents may find the task of recalling their expenditures to be 

inherently burdensome. While in theory the Diary survey respondents are expected to log their 

expenditures as they occur, in practice many respondents recall expenses as best they can 

immediately before the interviewer collects the diary. 

The 3-month reference period in the CE Quarterly Interview survey may also be a source of 

respondent burden and measurement error. A classic study by Neter and Waksberg (1964) found 

that the length of the reporting period had a significant effect on the accuracy of the expenditure 

data that respondents provided. Shorter, bounded, reference periods produced significantly more 

reports of expenditures than longer, unbounded periods. The extent of this effect varied depending 

on the nature of the expenditure. Respondents may not remember small and unremarkable 

expenditures over a 3-month period. Respondents may have particular difficulty recalling the 

required supplementary information, such as the price and the taxes paid. For example, in 2007 the 

CE-to-PCE ratio was 96 percent for automobiles, but only 44 percent for video and audio goods 

(Garner et al., 2009). One possible reason for this difference is that the purchase of an automobile is 

a more salient and memorable event. 

The recall task is made more complex by the requirement that CE respondents report on all 

expenses for all members of the consumer unit (CU). While respondents are encouraged to consult 

other household members during the reference period, household members may not be motivated 

to give the respondent accurate data consistently. The respondents can report only on the 

expenditures that they know about, and their knowledge may be incomplete (Kojetin and Miller, 

1993). Also, the respondent may be reluctant to report on certain expenditures in the consumer unit, 

fearing that reporting the expenditure would be a violation of the privacy of another member of the 

household. 
Redesign Options for the Consumer Expenditure Survey 5 

The sheer number of questions in the Quarterly Interview survey could add to respondent burden. 

The interview is quite long, and likely to fatigue some of the respondents, who may answer less 

carefully as the interview goes on. The published length of the interview survey is one hour. Of 

course, the actual length would be expected to vary according to the number of expenses to be 

reported. Larger and more affluent households may have more expenses, so the respondents may 

need more time to complete the interview. Because each respondent is interviewed five times over 

the course of one year, the real and perceived burden is great. 

The term “panel conditioning” refers to the situation in which a respondent deliberately answers a 

question in a way that avoids additional questions. For example, the respondent might untruthfully 

say that the household had no expenditures of a particular kind, to avoid having to answer questions 

about those expenditures. With long interviews such as the CE Quarterly Interview, panel 

conditioning is a possible contributor to measurement error.

Interviewer burden is an often overlooked phenomenon which could also have a role in the quality 

of CE data. If CE respondents appear to have difficulty providing data, to take shortcuts, and to be 

annoyed, the interviewer may take steps to shorten the interview. CE interviewers conceivably may 

be inclined to accept partial answers or to encourage respondents to work through the interview 

quickly at the expense of data quality.

Any redesign of the CE surveys must take into account the need to reduce respondent burden and 

measurement error. The redesign must balance the need for a great amount of detailed data with the 

need to ensure that the respondents report those data completely and accurately. 

 Electronic Records of Expenditures 

Consumers today commonly make purchases using modes that leave an electronic record. When an 

electronic record exists, respondents potentially could provide the expenditure data by retrieving 

information about the purchase from a database, or by printing out a record of the purchase, rather 

than by trying to remember the details of the purchase or by finding a receipt. 

For example, soon after a consumer makes a purchase using credit card, debit card, check, electronic 

fund transfer, or PayPal, a record of the transaction appears in a file that can be downloaded from 

the web site of a financial institution. When a consumer makes an online purchase, the vendor 
Redesign Options for the Consumer Expenditure Survey 6 

typically sends a confirmation email, or provides a confirmation page, that the consumer can print 

out. 

The CE program does not currently ask respondents to provide these electronic records of 

expenditures. Their potential role in the CE data collection process deserves attention. These 

records cannot provide all of the data required by the CE program, however. They potentially offer 

a way to help respondents remember expenditures without a great deal of effort.

 Changes in the Retail Environment 

Any redesign of the CE program should take into account several recent developments in the retail 

landscape. These changes include the consolidation of the grocery and pharmacy retail industry; the 

expansion of loyalty card programs, especially among supermarket and drug store chains; the 

prominence of “big box stores” like Walmart and Target that offer a very wide range of 

merchandise; and the emergence of firms that employ data mining and data aggregation techniques 

in the retail industry. 

In recent years, the grocery and pharmacy retail industries have greatly consolidated through mergers 

and acquisition. By 2005, the 20 largest U.S. grocery store retailers accounted for 61.6 percent of 

total sales, up from 40.6 percent in 1995 (Kaufman, 2007), while Walgreen's, CVS, and Rite Aid

represented 73.2 percent of drugstore sales, and Costco and Sam's Club accounted for 89.5 percent 

of warehouse club sales (Fox & Sethuraman, 2006). This consolidation in the retail industry means 

that an increasing proportion of consumers make purchases at fewer retailers. As a result, relatively 

few retail chains hold data about the purchases of a large proportion of CE respondents. If those 

retail chains were willing to make those data available, the CE program would have a method of 

verifying or enhancing the data provided by the respondents. 

The expansion of loyalty card programs may be relevant to the redesign of the CE program. 

Retailers that offer loyalty cards potentially could monitor the purchases of individual consumers. If 

CE respondents provided their loyalty card numbers, and retailers were willing to release purchasing 

data, the CE program would have access to objective information about the respondents’ 

expenditures. Of course, this idea has some drawbacks. Consumers sometimes forget to provide 

their loyalty card to the cashier when they make a purchase. Some consumers may lend their loyalty 

cards to friends. Also, most retailers, including Walmart, have no loyalty card programs.
Redesign Options for the Consumer Expenditure Survey 7 

“Big box stores” such as Target and Walmart offer merchandise in a wide range of categories, 

including groceries, clothing, health supplies, electronics, and so on. CE respondents may have 

difficulty remembering expenditures at these outlets. For example, if a CE respondent purchased a 

large amount of food items and one article of clothing and one music CD during a shopping trip, 

the consumer may not recall the clothing item and the CD. The respondent may need to refer to a 

receipt to recall those items. The prominence of “big box stores” increases the need for records 

such as receipts to document CE respondents’ purchases. 

In recent years, retailers have relied increasingly on data aggregators and data mining companies 

such as Nielsen, SymphonyIRI, Teradata, and Catalina Marketing. These firms provide a way for the 

retailers to understand the purchasing behaviors of their customers. Conceivably, these firms have 

data that may be useful to the CE program. 

Increasing Flexibility 

The current design of the CE is not adequately flexible or adapted to the specific needs of the 

individual respondents. The procedures for collecting data in the Diary survey or the Quarterly 

Interview survey do not vary very much among the respondents. If the data collection methods were 

made more flexible, respondents might feel less burdened and more willing and able to report their 

data accurately and completely.

Moreover, the current CE Quarterly Interview survey is difficult to change when changes are 

needed. The survey is administered as a computer-assisted personal interview (CAPI). With this 

system, much time and effort is required to make changes to the interview procedures and 

questions. As purchasing methods and technologies change, the CAPI interview methods should 

have the flexibility to shift rapidly in response. 

The CE data collection methods also could be tailored to the characteristics of the respondents. For

example, some respondents may be quite comfortable with the existing paper-and-pencil Diary 

survey methods while others would strongly prefer to keep their data using a desktop computer or a 

smartphone. Some respondents may agree to download files of their credit card and checking 

account activity, while others may perceive a privacy threat and refuse. Some respondents may have 

no checking account and therefore have no checking account data files to download. In particular, 

lower income households disproportionately have no checking accounts and use cash or money 
Redesign Options for the Consumer Expenditure Survey 8 

orders instead (Blank & Barr, 2009; Kim, 2001; McKernan & Sherraden, 2008). During economic 

downturns, increasing numbers of consumers stop using or terminate their credit cards (Foster, 

Meijer, Schuh, and Zabek, 2011). 

A redesign of the CE program should take into account such individual differences. By offering 

respondents a range of options for reporting their expenditure data, the CE program might collect 

high-quality data while minimizing respondent burden. 
Redesign Options for the Consumer Expenditure Survey 9 

This section presents some potential approaches to redesigning the CE program, and discusses the 

advantages and drawbacks of each approach. The redesign options are intended to address the 

important issues facing the CE program: measurement error, respondent burden, changes to the 

retail landscape, the emergence of new technologies, and the need for greater methodological 

flexibility. 

Alternative Data Sources 

Currently, the respondents are the sole source of data in the CE program. A redesigned program 

could take advantage of other sources of data (Tucker, 2011; Eltinge, 2011). 

Data from Retailers or Data Aggregators. Some larger retailers maintain databases with sales and 

price information. Data aggregators obtain the databases from many of these retailers, with the goal 

of providing summaries that can guide marketing decisions. For example, they use the data to help 

manufacturers decide upon the best pricing and advertising strategies for their products. Their goal 

is not to study the purchasing behavior of individual households. Nonetheless, these data could be 

useful for at least some aspects of the CE program. For example, aggregated retail data may be 

useful for CPI calculations, which do not require household-level information. 

Neilsen is an example of a data aggregator. According to the company’s web site, Nielsen obtains 

sales and price data electronically from “virtually every major retail chain.” Walmart, the nation’s 

largest retailer, was late to join the Nielsen panel of retailers; it did not start to provide data to 

Nielsen until July, 2011 (Wohl, 2011). Nielsen also attempts to collect data about retailers that do 

not participate in this program. For example, before Walmart began to provide its sales and price 

data, Nielsen conducted interviews with Walmart shoppers to obtain those data. 

Several other market research firms obtain price and sales data from retailers. For example, NPD 

(2011) claims to get data from a panel of 900 retailers representing 150,000 stores in and out of the 

United States. The data include sales per store and pricing.

Potential Approaches to the 

Redesign of the CE Program 3 
Redesign Options for the Consumer Expenditure Survey 10 

The data from aggregators such as Nielsen or NPD may potentially allow the CE program to 

generate estimates that could be used for the CPI. The major advantage of this approach is that the 

data are collected without the need for any respondent interviews. However, the approach has 

several drawbacks.

First, these data may be seriously flawed. Perloff and Denbaly (2007) raised questions about the sales 

and price data that Nielsen obtains from major vendors. They said that this dataset generally does 

not contain data from smaller retailers, creating a systematic bias. Perhaps a more important 

criticism is that the methods used to collect these data are not made public. 

In addition, aggregators provide little information about the statistical properties of their data. 

Without this information, the CE program may not adequately identify the best methods for using 

the data in CPI calculations. 

Another major drawback to using data from aggregators is that it creates a dependency between BLS 

and the data aggregator. If the company changes methods, or discontinues its work, the CE data 

collection effort would be in jeopardy.

An alternative to using data from aggregators may be more feasible: The CE program could collect 

sales and price data directly from a sample of retailers and estimate expenditures for purposes of the 

CPI. This method is similar to the methods that the BLS uses to collect data in the Current 

Employment Statistics program or the Job Openings and Labor Turnover Survey (JOLTS). For the 

data to be useful, however, the retailers would have to provide microdata, tailored to the purposes of 

the CE program. The BLS might have to develop special tabulations for these microdata.

To our knowledge, the BLS has not approached individual retailers to obtain their sales and price 

data. Retailers may well be reluctant to provide these data. However, these retailers might seriously 

consider such a request from BLS, especially when they realize that the data will be used for 

important purposes such as calculations for the CPI. Retailers might also be motivated by a clear 

incentive to provide their data. For example, retailers turn their data over Nielson because of the 

useful information they get in return, which they use to guide their marketing decisions. If BLS 

could similarly develop feedback reports that summarized the information in useful ways for the 

retailers, they may be willing to provide their sales and price data. BLS may have to negotiate 

agreements with each retailer on an individual basis. 
Redesign Options for the Consumer Expenditure Survey 11 

National Consumer Panel. In 2009 Nielsen and SymphonyIRI launched a joint venture, called the 

National Consumer Panel, with the goal of studying purchasing habits of American households 

(SymphonyIRI, 2011; Nielsen, 2011). Each household in the National Consumer Panel is given a 

small barcode scanner. Each time someone in the household makes a purchase, a respondent in that 

household uses the barcode scanner. First the respondent scrolls a list of retailers on the scanner 

screen and selects the name of the retailer, if it is on the list. Then the respondent scans the bar 

codes of all the UPC-labeled items that were purchased at that retailer. If the product has no UPC 

barcode, the respondent scans an appropriate barcode from a set of barcodes that they keep on 

hand. SymphonyIRI and Nielsen receive the scanned data daily from each household in the panel. 

According to literature from Nielsen and Symphony IRI, over 52,500 households are currently 

participating in the National Consumer Panel. 

The goal of the program is to obtain highly accurate expenditure data using bar code scanning, 

rather than relying on respondents’ recollections of their purchases. Nonetheless, the quality of 

National Consumer Panel data can be questioned. 

U.S. Department of Agriculture (USDA) researchers considered and rejected the idea of using data 

from SymphonyIRI-Nielsen’s National Consumer Panel for the National Household Food 

Acquisition and Purchase Survey (FoodAPS). Perloff and Denbaly (2007) explained the reasons for 

that decision. They wrote that the properties of the sample drawn for the National Consumer Panel 

have never been made public. They argued that documentation was absent on sampling, data 

collection procedures, self-selection, nonresponse, and attrition. Further, they wrote that “no formal 

statistical studies have been conducted to measure the magnitude of the size of any potential bias.”

They argued that the demographic makeup of the National Consumer Panel appeared to be very 

different from that of the overall U.S. population. They also pointed out that Nielsen and 

SymphonyIRI did not maintain longitudinal data, but discarded data that were more than 3 years 

old, making any study of trends over time all but impossible. They further pointed out that Nielsen 

and SymphonyIRI charged high prices for the data. Sales and price data for just one or two product 

categories cost hundreds of thousands of dollars. Finally, they found that Nielsen and SymphonyIRI 

refused to release certain parts of the dataset, such as data regarding brand market share, and data 

about a household’s participation in programs such as WIC. 

Perloff and Denbaly (2007) concluded that “relying on commercial vendors is unattractive because 

these firms charge very high prices, do not fully disclose the nature of their data, provide data for 

only very short periods, and report only variables that are important for commercial customers and 

not all variables that are important for researchers. One approach to ameliorating data shortages for 
Redesign Options for the Consumer Expenditure Survey 12 

research would be to have government agencies or nonprofit organizations collect the ideal datasets 

or provide incentives to commercial providers.” USDA ultimately decided to collect data itself for 

FoodAPS, using its own sample. 

Einav, Leibtag, and Nevo (2008) also questioned the quality of the data collected using the home 

barcode scanning method. They compared data that respondents provided using a bar code scanner 

with data provided by the retailers themselves. The authors found that “...for approximately 20 

percent of food-shopping trips recorded in the (bar code) data, there was no corresponding 

transaction in the retailer’s data.” Apparently for those data, the respondents entered the incorrect 

supermarket chain, or the wrong date of the purchases. The authors continued, “For the trips that 

did match up, roughly 20 percent of the (purchased) items were not recorded.” Clearly, asking 

respondents to scan the bar codes of their purchases cannot by itself solve the challenges facing the 

CE program.

FoodAPS. The Economic Research Service and the Food and Nutrition Service of USDA will soon 

collect home barcode scanning data from a random sample of American households in FoodAPS. 

The respondents are asked to scan the barcodes of every food item that they buy. If the item carries 

no UPC bar code, the respondents scan an appropriate bar code printed in a booklet. The 

respondents use a very small scanner with no keyboard or screen. The respondents are also asked to 

keep receipts for all of their food purchases, both for food to be eaten at home and food to be eaten 

away from home, and to keep a diary of their food purchases on special forms. Respondents are 

further asked to call an interviewer after they purchase a meal away from home, so that they can 

report the details of the meal in a CATI interview.

The FoodAPS data include quantities, prices, and expenditures for all at-home and away-from-home 

foods and beverages purchased or acquired at no cost from all sources. The data also include 

household characteristics, including income, participation in programs such as the Special 

Supplemental Nutrition Program for Women, Infants and Children (WIC), and general information 

about non-food expenditures (U.S. Department of Agriculture, 2011). 

The FoodAPS data appear to be equivalent in many ways to the data that the CE program collects 

for food expenditures. Conceivably, FoodAPS data could supplement CE data for food 

expenditures. However, the CE program probably should not discontinue collecting data about food 

expenditures and use FoodAPS data instead. The FoodAPS sample size of 5000 is probably too 

small for FoodAPS data to be comparable to CE data. Also, the FoodAPS data collection period, 

March to June, 2012, is not a good fit with CE methods. In addition, FoodAPS collects data about 
Redesign Options for the Consumer Expenditure Survey 13 

food obtained at no cost, such as in programs that give free meals to indigent schoolchildren, while 

the CE program collects data only about purchased food. 

Nonetheless, FoodAPS does seem to have some promise as a data collection mechanism for the CE 

program. With some changes to the FoodAPS data collection methods, FoodAPS data could 

potentially meet the needs of both USDA and BLS. Discussions between the two agencies are 

warranted.

Data Mining Firms. The business focus of two companies, Teradata and Catalina Marketing, is to 

mine retailers’ databases of purchases. Teradata provides data mining software that retailers can use 

to study their customers’ purchasing behaviors. Catalina Marketing provides data mining services to 

retailers. It also markets systems that print coupons for consumers when they complete their 

purchases. These coupons are tailored specifically to the individual consumer, based upon the 

consumer’s purchasing history, as recorded in loyalty card data. For example, a consumer who has a 

history of purchasing breakfast cereals might receive a cents-off coupon for cereal redeemable only 

at that retailer. Catalina Marketing’s web site claims that the company’s systems operate in 25,000 

U.S. stores, logging more than 300 million transactions per week. 

The Baltimore City Paper published an article on Teradata and Catalina Marketing, covering such 

issues as data privacy (Jackson, 2003). The article concluded that “Companies like Catalina and 

Teradata use...data to spot trends and insist they have little use for individual information.” The 

article quoted a Catalina executive as saying, “it would be difficult, though possible, to single out and 

review one person’s buying history, but ...the company has no business interest in doing such.” The 

potential utility of the data that Teradata or Catalina Marketing could provide to the CE program is 

unclear. The optimum path may be for BLS to seek data directly from individual retail chains that 

have loyalty card programs.

Administrative Data Linked to Respondents 

Many federal surveys collect data simultaneously from households and from administrative sources. 

The administrative data are used to verify or to supplement the data provided by the household 

respondents. The CE program currently collects data only from household respondents. The 

program does not attempt to collect any administrative data from retailers, utilities, banks, apartment 
Redesign Options for the Consumer Expenditure Survey 14 

lessors, or other potential sources. However, administrative data potentially could reduce 

measurement error in the CE program. 

The idea of obtaining data from retailers has an obvious appeal: those data are likely to be more 

consistently accurate than respondent-provided data are likely to be. Other federal data collection 

projects have used administrative data to improve the quality of data that respondents had provided 

from memory. The experiences of those researchers suggest that in many cases administrative 

sources can provide data that respondents omitted, correct data that respondents misreported, and 

verify data that respondents correctly provided. 

For example, in the Medicare Current Beneficiary Survey, researchers asked Medicare beneficiaries 

about the nature and the cost of the medical services that they have received. The researchers linked 

the respondents’ self-reported data to Medicare administrative files. By linking the data this way, 39 

percent of missing cost data were corrected, and 22 percent of erroneous reports about whether 

Medicare was a payer were corrected (Eppig and Chulis, 1997). 

In the National Immunization Survey, telephone interviewers call respondents and conduct an 

interview about the immunization history of children in the household. The respondents’ reports are 

later verified; the medical providers who immunized the children are asked to provide the dates of 

the child’s prior immunizations. The data from the medical providers have improved the quality of 

the respondents’ reports. For example, data from the medical providers revealed that 61 percent of 

the children whose parents’ reports suggested that their immunizations were not up-to-date actually 

did have up-to-date immunizations (Battaglia, Shapiro, and Zell, 1996).

The Energy Information Agency of the Department of Energy collects data about energy 

expenditures from a nationally representative sample of housing units in the Residential Energy 

Consumption Survey (RECS). The interviewers ask about household energy characteristics, such as 

the sources of energy used, household demographics, and energy usage patterns. When the 

household respondent in a rented property is unsure of the answers to the interviewer’s questions, 

the interviewer attempts to collect the data from the rental agent. After collecting the household 

data, the Energy Information Agency conducts the Energy Supplier Survey (ESS), to collect 

administrative data. The ESS is a mail survey of energy companies that serviced the households that 

participated in the RECS. The ESS collects data about the amounts of natural gas, electricity, fuel 

oil, and propane that the RECS households used. The ESS data are used to correct and augment the 

RECS data.
Redesign Options for the Consumer Expenditure Survey 15 

Linking respondent reports in the CE surveys with administrative data might also bring about 

improvements in data quality. For example, data from retailers could contain the date of a purchase, 

as well as the price, the sales tax, and a description of the item purchased. The data could 

supplement a respondent’s data, and help ensure that the respondent did not forget to report the 

purchases. The respondent would still have to provide additional information needed for the CE 

surveys, such whether the expenditure was for a person outside the household. 

However, the idea of obtaining data from retailers poses considerable challenges. Retailers as a rule 

do not release data about the purchases of individual customers. Some retailers do have loyalty card 

programs and could in principle release the purchasing histories of individual customers. However, 

retailers do not generally release any customers’ purchasing histories. The only exception is that 

pharmacies do usually release customers’ purchasing histories for prescription drugs. Moreover, only 

retailers who have loyalty card programs can easily collect data for individual households. Most small 

retailers do not have loyalty card programs. Even Walmart, the nation’s largest retailer, has no loyalty 

card program. 

When a retailer does release loyalty card information about individual customers, it can be a 

newsworthy event. For example, the Denver Post (Raabe, 2010) reported that the Centers for 

Disease Control and Prevention (CDC) obtained information about customers’ purchases from 

Costco to track down the source of a salmonella outbreak. CDC researchers examined the purchases 

of afflicted Costco customers, using loyalty card data. They identified several products that most or 

all of these customers had purchased. Soon the CDC researchers discovered the salami product that 

was to blame for the outbreak. 

The Denver Post article mentioned that Safeway, King Soopers, Krogers, and Costco used loyalty 

card data to facilitate Class I product recalls, the category in which customers could be harmed or 

sickened by a faulty product. For example, Costco used loyalty card data to identify customers who 

purchased a toy that posed a choking hazard for children. Costco contacted these customers and 

warned them to discard or return the toy. Similarly, King Soopers used loyalty card data to identify 

customers who purchased seasonings that had spoiled. They employed an automated telephone 

system to warn these customers.

The needs of the CE program do not have the urgency of a dangerous product recall, or a CDC 

investigation of an epidemic. On the other hand, in the 1990’s, Arbitron was able to persuade some 

retailers, including A&P, to provide point-of-sale data for the households in its consumer panel. The 
Redesign Options for the Consumer Expenditure Survey 16 

retailers were motivated to provide these data because Arbitron gave them valuable market research 

analysis in return. 

Obtaining administrative data for the CE program would not be straightforward. With other 

surveys, such as the Medicare Current Beneficiary Survey, or the National Immunization Survey, or 

the Residential Energy Consumption Survey, only a relatively few sources needed to be consulted 

for each household. CE households, by contrast, make purchases from a very large number of 

retailers and vendors. However, the BLS name has credibility. The CE and CPI programs are 

relatively well known. Furthermore, a comprehensive set of data, linked to respondents, is not 

required. Even partial data can be used for quality assessments. Many respondents may be willing to 

sign consents for the release of their data. The BLS might consider conducting a pilot study to 

investigate the feasibility of obtaining administrative data about CE households from various 

sources such as retailers with loyalty card programs, utility companies, and other sources. With the 

high degree of consolidation in the grocery, pharmacy, and warehouse club industry, data for a large 

number of respondents are potentially available from a relatively few sources.

Administrative Data Supplied by the Respondent 

Some administrative data could be available from the CE respondents themselves. Respondents 

would need to expend relatively little effort to access records about their purchases made by check, 

electronic fund transfer, credit card, debit card, or online payment service such as PayPal. The 

respondents could download these data files directly from the web sites of the relevant financial 

institutions. Respondents who used financial software packages such as Mint could use that software 

to help them download those data files. Alternatively, respondents could enter their account 

numbers and passwords into software developed specifically for the CE program. That software 

could be designed using the Yodlee (2011) Software Development Kit (SDK), which automates 

downloads from the web sites of financial institutions. Mint and many other financial software 

packages were developed using the Yodlee SDK.

The data files from these financial institutions would hold a portion of the data currently required 

for the CE program. The files would show the total dollar amount of the respondents’ purchases. In 

the case of the PayPal, debit card, credit card, and electronic fund transfer purchases, the files would 

also show the date of the purchases and the payee. The checking account files would show only the 
Redesign Options for the Consumer Expenditure Survey 17 

date that the checks cleared, not the date of the purchase, and would only sometimes show the 

payee.

The value of the files would be that they showed, with a high degree of accuracy, the dollar amounts 

of the expenditures. They would also show at least the approximate dates that the expenditures 

occurred. The additional details that are required would have to come from a different source, such 

as receipts or the respondent’s memory.

The data files would generally not cover, however, cash and money order transactions. Those 

transactions do not leave a record in a data file, except in the case of certain money orders, such as 

those purchased with a prepaid Western Union debit card. 

However, most other expenditures would be documented in these data files. That fact raises an 

important question for the CE program: What proportion of consumer expenses currently are 

transacted using a medium other than cash or money order, and therefore leave an electronic 

record?

The answer to that question is suggested by a recent survey conducted by the Federal Reserve Bank 

of Boston. The results of the Survey of Consumer Payment Choice (Foster, Meijer, Schuh, and 

Zabek, 2011) reveal the proportion of consumer purchases that are transacted by cash, check, credit 

card and other methods. Table 1 shows that in 2009, the most recent year for which data are 

available, CUs reported a mean of 64.5 transactions per month. Of those, a mean of 18.4 were by 

cash and 0.5 were by money order. Thus, a total of 18.9 of the 64.5 monthly transactions, or 29.3 

percent, were by cash or money order. These transactions would not be likely to appear in any 

online data file. 

Table 1 reveals that a mean of 8.2 transactions per month are by check, 19.0 are by debit card, 11.2 

are by credit card, 0.8 are by prepaid card, 3.3 are by online bill payment set up to occur 

automatically on a regularly scheduled basis, and 3.0 are by online bill payment that occurs when 

needed, not automatically on a regularly scheduled basis. Thus, a total of 45.5 transactions per 

consumer per month, or 70.5 percent of the 64.5 monthly mean, would be likely to appear in a 

database file that could be downloaded from the web site of a financial institution. 
Redesign Options for the Consumer Expenditure Survey 18 

Table 1. Use of payment instruments in a typical month, by type of instrument

(from Foster, Meijer, Schuh, and Zabek, 2011)

Number and percent of expenditures per consumer per month 

 

Number of expenditures 

Mean Percent of expenditures Percentage 

2008 change r 2009 2008r 2009 

Total payments 67.4 

 

64.5 

 

-4.2 100.0 

 

100.0 

 Paper instruments 24.1 26.7 10.8 35.4 41.8 

Cash 14.5 18.4 26.9 20.8 28.2

Check or money order 10.0 8.7 -13.1 14.6 13.5

 Check 9.6 8.2 -14.0 13.9 12.7

 Money order 0.4 0.5 23.6 0.6 0.8

Travelers check 0.0 0.0 -38.2 0.0 0.0

Payment cards 35.4 30.7 -13.2 52.5 47.8 

Debit 21.2 19.0 -10.0 30.8 29.3

Credit 14.4 11.2 -21.9 21.1 17.3

Prepaid 0.4 0.8 - 0.6 1.2

Prepaid, per adopter† 2.6 2.6 -0.6 — —

Electronic payments 7.4 6.2 -15.1 10.9 9.7 

Online banking bill payment* 3.4 3.3 -3.4 3.1 5.1

Bank account number payment* 4.1 3.0 -26.1 7.9 4.6

Bank account number payment, per adopter† 7.3 5.4 -26.5 — —

Direct deduction from income 0.8 0.6 -31.4 1.1 0.8 

* Adjusted for changes from 2008 to 2009 in the survey definition of transaction categories.

† Estimates for this row are calculated using only adopters of a payment instrument, not all consumers. Per adopter estimate is

included due to changes in the survey design that affected the rates of adoption of payment instruments, making the per consumer 

estimates not comparable across years.

NOTE: Superscript "r" denotes revised. Numbers in italics are not comparable across years due to changes in the survey. Numbers may 

not sum exactly due to rounding or missing values.

Table 2 shows that in 2009, a mean of 18.4 transactions per CU per month were for bill payments, 

and 2.4 of those (13.0 percent) were by cash or money order and therefore would probably not 

appear on any downloadable file. A total of 5.1 transactions per CU per month were for online 

payments. None of those were by cash and 0.1 (2.0 percent) were by money order. A total of 

42.3 transactions were for retail, service, and person-to-person transactions, and 16.8 of those 

(40.7 percent) were by cash or money order. In summary, approximately 70.5% of all transactions 

could potentially lead to some type of electronic record (Figure 1).1

 

1 The survey from which these data are derived is the American Life Panel. . This is a web-based panel that has recruited members from other general 

population surveys, including the Monthly Survey (MS) administered by the University of Michigan and the Face-to-Face Recruited Internet Survey 

Platform, administered by Stanford and ABT-SRBI (Foster, et al, 2011). Individuals who agree to be in the panel are provided access to the 

internet through a Web TV, if they do not have their own access. Coverage and response rates associated with a panel of this type are difficult to 

calculate because of the multiple stages of selection and possible attrition over time.
Redesign Options for the Consumer Expenditure Survey 19 

Table 2. Use of payment instruments in a typical month, by type of transaction 

(from Foster, Meijer, Schuh, and Zabek, 2011)

Number and percent of expenditures per consumer per month 

Number 

of expenditures Bill payments Online payments 

Retail, service and 

person to person 

2008r 2009 2008r 2009 2008r 2009 

Paper instruments 5.1 5.5 1.6 1.4 17.9 20.1 

Cash 1.2 2.1 NA NA 13.6 16.6

Check or money order 4.1 3.4 1.6 1.4 4.5 3.9

 Check 3.9 3.2 NA 1.3 4.3 3.8

 Money order 0.2 0.3 NA 0.1 0.2 0.2

Travelers check NA NA NA NA NA NA 

Payment cards 7.9 7.1 3.7 3.0 23.9 20.8 

Debit 4.6 4.5 2.1 1.8 14.8 13.1

Credit 3.6 2.6 1.6 1.2 9.4 7.6

Prepaid 0.0 0.1 0.1 0.1 0.3 0.5

Electronic payments 6.0 5.2 1.4 0.7 NA 0.4 

Online banking bill payment 2.2 3.1 NA NA NA 0.2

Bank account number 

payment

4.0 2.1 1.4 0.7 NA 0.2

 

Direct deduction from income 0.8 0.6 NA NA NA NA 

 

Paper instruments 7.4 8.3 2.3 2.2 25.7 31.3 

Cash 1.5 3.0 NA NA 19.3 25.2

Check or money order 5.9 5.3 2.3 2.2 6.4 6.1

 Check 5.6 4.9 NA 2.0 NA 5.8

 Money order 0.3 0.4 NA 0.2 0.3 0.3

Travelers check NA NA NA NA NA NA 

Payment cards 11.6 11.0 5.5 4.6 35.4 32.2 

Debit 6.4 6.8 3.0 2.7 21.3 19.8

Credit 5.1 3.9 2.3 1.8 13.6 11.6

Prepaid 0.0 0.2 0.1 0.2 0.5 0.8 

Electronic payments 9.0 8.0 1.9 1.0 NA 0.6 

Online banking bill payment 3.1 4.8 NA NA NA 0.3

Bank account number 5.9 3.3 1.9 1.0 NA 0.3 

Direct deduction from income 1.1 0.8 NA NA NA NA 

NOTE: Superscript "r" denotes revised. Numbers in italics are not comparable across years due to changes in the survey. Numbers may 

not sum exactly due to rounding or missing values. The notation “NA” indicates that the estimate is not available. 
Redesign Options for the Consumer Expenditure Survey 20 

Figure 1. Transactions per consumer per month

In summary, these findings suggest that fully 70.5 percent of consumer purchases are documented in 

electronic format. More specifically, 87.0 percent of bill payments, 98.0 percent of online payments, 

and 59.3 percent of retail, service, and person-to-person transactions are documented in electronic 

purchase confirmations or in files that can be downloaded from the web sites of financial 

institutions. 

The trend to the use of electronic methods of payment is increasing at a very fast pace. In 1995 the 

percentage of individuals who participated in electronic banking was approximately 4 percent, 

compared to 53 percent in 2007. The percentage using pre-authorized electronic fund transfers has 

doubled during this time period from 25 percent to 49 percent and the percentage using debit cards 

has more than tripled from 20 percent to 71 percent (Table 3, which is Table 1184 from the 2011 

Statistical Abstracts [Census Bureau, 2011]). New technological innovations are continually 

emerging, such as smartphone apps for purchasing and e-receipts (Clifford, 2011), in which retailers 

such as Old Navy email receipts to the consumer rather than print out paper receipts. Certainly, 

even more forms of electronic purchase documentation will appear in the future. Any redesign of 

the CE program must take these innovations into account. 

Cash; 18.4; 29%

Money order; 0.5; 

1%

Debit card; 19; 29% Check; 8.2; 13%

Credit card; 11.2; 

17%

Prepaid card; 0.8; 

1%

Online bill 

pay; 3.3; 5%

Bank account 

payment; 3; 5%
Redesign Options for the Consumer Expenditure Survey 21 

Table 3. Percentage of households using selected electronic banking technologies: 1995

to 2007 (from Census Bureau, 2011)

Technology 

Survey of Consumer Finances 

ReutersUniversity of Michigan 

Surveys of Consumers 

1995 1996 2001 2004 2007 1999 2003 2005 

Electronic 

Direct deposit of any type 53 67 71 75 80 65 70 77

ATM Card 35 55 57 65 76 59 65 69

Debit Card* 20 37 50 62 71 NA 54 62

Preauthorized debits 25 40 43 50 49 31 46 57

Automated phone system NA 26 22 20 25 40 44 46

Computer banking 4 7 19 34 53 10 32 51

Smart card** 1 2 3 NA NA NA 6 12

Prepaid card† NA NA NA NA NA NA 73 73

Nonelectronic 

In person 87 81 78 78 85 NA NA NA

Mail 59 55 51 51 59 NA NA NA

Phone (talk in person) NA 43 42 42 57 NA NA NA

Source: Board of Governors of the Federal Reserve System, Federal Reserve Bulletin, July 2009, and unpublished data.

* A debit card is a card that automatically deducts the amount of a purchase from the money in an account.

** A smart card is a type of payment card containing a computer chip which is set to hold a sum of money. As the card is used, 

purchases are subtracted from that sum.

† Prepaid cards are cards that contain a stored value, or a value that has been paid up-front, allowing you to use the card much like 

cash. As you use the card, the prepaid value is drawn down. Examples are phone cards and gift cards. Smart cards are different from 

prepaid cards in that you can add money to the card at special machines designed for smart cards or sometimes at ATMs.

NOTE: Covers only those households that access services (other than by check or credit card) at a bank, thrift institution, or credit union 

based on sample surveys. For details on the Survey of Consumer Finances, see the Federal Reserve Board, 

<www.federalreserve.gov/boarddocs/surveys\>. The Reuters/University of Michigan Surveys of Consumers is based on data from 

approximately 1,000 respondents. For details, see the University of Michigan Survey Research Center, 

<http://www.sca.isr.umich.edu/>.

Records of Expenditures 

One of the most obvious ways to improve the quality of CE data and to reduce the respondents’ 

reliance on memory is to encourage the respondents to keep documentation of their expenditures. 

This documentation could be in the form of receipts, including paper cash register receipts and 

printouts of online purchase confirmations. If no receipt was available, such as for purchases from 

vending machines, the documentation could be in the form of a notation; the respondents could 

create a record of the purchase using a smartphone or simply by writing down information about 

the purchase on a short paper form.
Redesign Options for the Consumer Expenditure Survey 22 

Evidence from several federal surveys suggests that when respondents keep records of some kind, 

they provide better-quality data than they do when they simply try to recall the data. Such records 

could be very simple, such as receipts or notations.

Medical Expenditure Panel Survey. For example, data from the Medical Expenditure Panel 

Survey (MEPS) suggest that respondents who rely on memory alone to report their data are more 

likely to err than are respondents who use a memory aid. All the respondents in MEPS receive a 

calendar to record their medical expenditures. They are asked to record each health-related product 

or service they obtained, how much it cost, and the vendor who provided it. The calendar has a 

pocket for the respondents to keep receipts, explanation of benefits forms, or bills to document 

their medical expenditures. 

MEPS respondents, however, often failed to heed the instructions to keep up the calendar and to 

save receipts or other documentation. For 59.8 percent of the medical expenditures reported in 

2003, the respondents relied solely on memory to report out-of-pocket medical expenses. For only 

20.0 percent of the medical expenditures did the respondents use the calendar and for only 

9.7 percent did the respondents refer to documentation such as receipts to help them report out-ofpocket medical expenditures (Kashihara and Wobus, 2007). 

When respondents did use the calendar or keep documentation, their data tended to be more 

accurate than when they relied on memory alone. The respondents’ reports were compared with 

medical providers’ records, which were assumed to be accurate. Use of the calendar improved the 

accuracy of respondents’ reports for out-of-pocket medical expenditures. In a logistic regression 

analysis, the odds ratio of 1.16 was significant (p<.05), suggesting that use of the calendar was 

associated with accurate reports, as compared with the use of memory alone. Use of documentation 

such as bills and explanation of benefit forms improved the accuracy of respondents’ reports on 

insurance payments. The odds ratio of 1.30 was significant (p<.05), suggesting that the use of bills 

was associated with accurate reports (Kashihara and Wobus, 2007).

More recent MEPS data, for 2004 to 2006, are shown in Figure 2. For only 22.5 percent of the 

medical expenditures did the respondents keep notes on a calendar. For only 13.7 percent of the 

medical expenditures did the respondents refer to documentation such as receipts. Variables which 

may be proxies for low socioeconomic status, including lower family income, less educational 

attainment, Medicaid coverage, and lack of health insurance, were associated with a decreased 

tendency to record medical data on the calendars, or to keep documentation, and an increased 

tendency to rely on memory to report data. In addition, demographic variables such as African-
Redesign Options for the Consumer Expenditure Survey 23 

Figure 2. Weighted percent of medical expenditures for which the respondents used each 

recall method (from Schneider, Gustavson, Li, Göksel, DiGaetano, and Edwards, 

2009)

NOTE: Interviewers could note that respondents could use more than one recall method for any medical expenditure. The recall method 

was classified as “missing” when interviewers did not note any recall method.

American race, Hispanic ethnicity, younger age, male sex, and worse health were associated with 

decreased use of a calendar or documentation, and increased use of memory (Schneider, Gustavson, 

Li, Göksel, DiGaetano, and Edwards, 2009).

The MEPS data suggest that records can improve the quality of the data obtained through 

respondents’ reports, but respondents tend not to be as diligent as researchers might like in keeping 

records.

National Immunization Survey. In the National Immunization Survey, when interviewers 

telephone the sampled households, they ask the respondents if they have a “shot card” showing the 

child’s past immunizations. When the respondents have a shot card, the interviewer asks them to 

refer to it to report the data.

Respondents who referred to shot cards tended to provide more accurate immunization data than 

did respondents who relied solely on memory. A total of 90.5 percent of children who appeared to 

be up-to-date from a shot card were actually up-to-date. Only 78.0 percent of children who appeared 

85.64

1.59

22.46

2.61

13.72

1.18

15.26

0

10

20

30

40

50

60

70

80

90

Memory Checkbook Calendar Prescription label Documentation Other Missing

Weighted percent of medical events

Respondents' recall method
Redesign Options for the Consumer Expenditure Survey 24 

to be up-to-date based on reports from the parent’s memory were actually up-to-date (Brick, Kalton, 

Nixon, Givens, and Ezzati-Rice, 1999; Ezzati-Rice, Zell, Massey, and Nixon, 1996).

However, the shot cards introduced a systematic bias. Very rarely did a shot card show an 

immunization that actually did not occur. When an error appeared on a shot card, it was almost 

always the omission of an immunization. Thus, while errors in reports from memory might include 

both inaccurate reports of immunizations and inaccurate omissions, errors on shot cards included 

almost exclusively inaccurate omissions.

The CE program might similarly benefit if respondents could be motivated to keep records of their 

expenditures. The experience of the Census Bureau in the Survey of Income and Program 

Participation (SIPP) suggests that several techniques may be effective in motivating respondents.

SIPP. Census Bureau researchers attempted to motivate some of the SIPP respondents to use their 

personal records, rather than just their memory, to report their income (Bogen, Moore, and Marquis, 

1994; Marquis, 1995; Moore, Marquis, and Bogen, 1996). 

The SIPP researchers employed these techniques to encourage the respondents to use their records:

 Interviewers told the respondents that personal record use was the norm. They said that 

it was the usual, expected part of the respondent’s task. 

 Interviewers asked respondents who could not produce a record of income to replace it. 

For example, respondents who said that they had discarded their pay stubs were asked 

to get replacement stubs from their employers. The interviewers then called or returned 

to the respondents to collect the income information from the replacement pay stubs. 

 Interviewers trained the respondents in recordkeeping. They showed the respondents 

how to store documents such as pay stubs, and how to make a written record of income 

that came with no documentation, such as public assistance payments.

 Interviewers telephoned respondents between interviews to remind them to keep 

records of all income. 

 Interviewers permitted respondents to retrieve their records during an interview, even 

when this was time consuming. 

With these procedures, the researchers achieved a substantial increase in the use of records. They 

compared respondents who were encouraged to use records to report their income with control 

respondents, who did not receive such encouragement. They found that only 25 percent of the 
Redesign Options for the Consumer Expenditure Survey 25 

control respondents referred to records in the SIPP interviews. However, 87 percent of the 

respondents who received the intervention referred to records. The researchers described that level 

of record usage as “astonishingly high.” 

The use of records was generally associated with improved data quality. The SIPP respondents were 

more accurate (p<.05) in reporting their level of income when they referred to records. However, 

the intervention did not bring about any significant change in the number of income sources 

reported. 

The intervention was associated with two drawbacks. First, it brought about a decrease in the 

response rate. In one wave of data collection, the control group response rate was 94 percent while 

the intervention group response rate was 82 percent. In the second wave, the difference persisted. 

The control group response rate was 98 percent while the intervention group response rate was 90 

percent. This discrepancy may be attributable to the increased respondent burden associated with 

retrieving and reading documentation. 

In addition, the per-case cost of data collection was markedly different between the control and 

intervention groups. While the control group costs were in the $18 to $24 range, the intervention 

group costs were much higher, in the $49 to $50 range. 

In summary, the results of other federal surveys strongly suggest that data quality improves when 

respondents keep records. However, encouraging respondents to keep records poses a considerable 

challenge. The experience of SIPP shows that respondents can be effectively motivated. However, 

the effort to motivate the respondents drives up costs and causes the less cooperative respondents 

to withdraw from the survey. 

The CE program might adopt new procedures to encourage respondents to keep receipts and other 

records diligently. Those procedures would have to be carefully crafted so that they did not add an 

unacceptable burden to the interviewers and thereby drive up costs. The procedures would also need 

to take into account those respondents who are not amenable to keeping records under any 

circumstances. 
Redesign Options for the Consumer Expenditure Survey 26 

 Records Created by the Respondents 

CE respondents sometimes cannot refer to any record of an expenditure because they neglected to 

obtain a receipt, or they misplaced the receipt, or no receipt was provided, such as with a purchase 

from a vending machine. For these kinds of purchases, the respondent could create documentation. 

The purpose of the documentation would be to remind the respondent about the expenditure. That 

is, the documentation could help ensure that the respondent remembered to report the expenditure, 

and also provide at least a few details about the expenditure.

That documentation could be in any of the following formats: 

 A small paper form on which the respondent writes a description of the purchase and 

the amount; 

 A text message containing a description of the purchase and the cost; 

 An email message containing a description of the purchase and the cost; 

 Responses to questions on a smartphone screen about the nature and the amount of the 

purchase; 

 Voice messages left on an Interactive Voice Response (IVR) system; the respondent 

calls the IVR system, which asks the respondent to describe the purchase and state the 

amount paid (similar to theexpensetracker.com); 

 Voice memorandums recorded via a smartphone app; the respondent records a 

description of the purchase and the amount paid; 

 Voice memorandums recorded on a digital recorder; the respondent records a 

description of the purchase and the amount paid; 

 A photograph that the respondent takes with a smartphone; the photograph could be of 

the purchased items, or the store where the purchase occurred; or

 A photograph that the respondent takes of the bar code on a purchased item using a 

smartphone. 

Many of these ideas involve a smartphone. Respondents potentially could use smartphones to fill 

out a short form about a purchase, or record a voice message describing a purchase, or even 

photograph a purchase or a bar code on a purchase. 
Redesign Options for the Consumer Expenditure Survey 27 

 Smartphones 

All CE respondents potentially could be asked to obtain and keep receipts. Many respondents might 

be comfortable using an IVR system or a voice recorder or even a portable bar code scanner. 

However, only respondents who have and are comfortable using smartphones would wish to collect 

data with them. 

The Pew Internet and American Life Project (Smith, 2011) conducted a telephone survey about 

mobile device ownership in April and May, 2011 with a sample of 2,277 U.S. adults. Respondents 

were contacted by both landline and cell telephone. The results indicated that 83 percent of 

American adults own a cell phone of some kind, and for 42 percent of them, that phone is a 

smartphone. Thus, the results suggest that 35 percent of American adults own a smartphone 

(Table 4).

Table 4. Smartphone ownership and Internet use summary (from Smith, 2011) 

% of smartphone owners, cell owners and all adults who... 

 % of smartphone owners 

who... 

% of all cell owners 

who... 

% of all adults 

who... 

Own a smartphone 100% 42% 35%

Use the internet or email on 

Smartphone

87 36 30

Use smartphone to go online on a 

typical day

68 28 23

Go online mostly using Smartphone 25 10 8

Source: The Pew Research Center's Internet & American Life Project, April 26 – May 22, 2011 Spring Tracking Survey. n=2,277 adult 

internet users ages 18 and older, including 755 cell phone interviews. Interviews were conducted in English and Spanish.

Moreover, the Pew data suggest that most smartphone owners tended to make use of the device’s 

Internet capabilities. Table 4 shows that 87 percent of smartphone owners use their device to access 

web sites or for email. 

The Pew data suggest that certain demographic characteristics are associated with smartphone usage. 

Table 5 shows the relationship between smartphone ownership and demographic background. 

Respondents with a household income over $75,000 were more likely than others to report that they 

owned a smartphone. Smartphone ownership was also associated with having a college degree, age 

less than 50 years, African American race, and Hispanic ethnicity. 
Redesign Options for the Consumer Expenditure Survey 28 

Table 5. The demographics of smartphone ownership (from Smith, 2011)

% of U.S. adults within each group who own a smartphone

All adults 35% 

Gender 

Men (n=973) 39

Women (n=1304) 31

Age 

18-29 (n=337) 52

30-49 (n=581) 45

50-64 (n=659) 24

65+ (n=637) 11

Race/Ethnicity 

White, non-Hispanic (n=1637) 30

Black, non-Hispanic (n=261) 44

Hispanic (n=223) 44

Household Income 

Less than $30,000 (n=671) 22

$30,000-$49,999 (n=374) 40

$50,000-$74,999 (n=276) 38

$75,000+ (n=444) 59

Education level 

No high school diploma (n=229) 18

High school grad (n=757) 27

Some college (n=525) 38

College+ (n=746) 48

Geographic location 

Urban (n=618) 38

Suburban (n=1113) 38

Rural (n=465) 21

Source: The Pew Research Center's Internet & American Life Project, April 26 – May 22, 2011 Spring Tracking Survey. n=2,277 adult 

internet users ages 18 and older, including 755 cell phone interviews. Interviews were conducted in English and Spanish. “Smartphone 

ownership” includes those who say their phone is a smartphone, or who describe their phone as running on the Android, Blackberry, 

iPhone, Palm or Windows platforms. 
Redesign Options for the Consumer Expenditure Survey 29 

These results suggest that about one-third of CE respondents might consider using a smartphone to 

collect their expenditure data. CE respondents with certain demographic characteristics would be 

more likely than other respondents to wish to use a smartphone. 

However, the CE program probably cannot feasibly offer smartphones to respondent as incentives. 

Smartphones are costly. Their cost is greatly reduced when purchased along with a 2-year contract, 

but respondents may not wish to commit to paying for service over two years. Also, respondents 

who are unfamiliar with smartphones may require training to use them for the CE surveys. Some 

may discover that they do not like to use them. For that reason, only CE respondents who already 

own smartphones could feasibly use the devices to keep a record of their expenditures.

 Number of Persons Interviewed in the Household 

The current CE surveys collect data from one household respondent. However, that procedure has a 

disadvantage: The respondent has the burden of reporting the expenditures of all members of the 

CU. The respondent may be unaware of, or reluctant to report, the expenditures of other people in 

the household. Asking all members of the household to provide data may overcome this problem. 

There are several surveys in other countries that distribute diaries to multiple household members 

(e.g., Grootaert, 1986; Filippucci & Ferrante, 1997). In the United States, the FoodAPS survey will 

ask all household members to provide data. 

BLS and the Census Bureau have evaluated a method in which multiple CE household members 

kept diaries (Westat, 2005; Edgar et al., 2006). With that method, a principal respondent was 

responsible for key household expenditures like groceries and utilities. All members of the 

household, including this principal respondent, reported on their own individual purchases. The 

results of the evaluations suggested that a significant number of these individual household members 

did report expenditures. 

For example, the larger study conducted by the Census (Edgar et al., 2006) found that a significant 

number of the individual diaries were filled out by young males, a population that is typically not 

well represented in surveys. In 362 of the 591 households in the multiple respondent group, all the 

adults reported expenditure data. A comparison group was formed using a sample from the ongoing 

CE Diary survey. Overall, the distribution of expenditures across four broad categories (food at 

home, food away from home, clothing, other) did not significantly differ between the multiple and 

single respondent procedures. The number and level of expenditures was quite a bit higher for the 
Redesign Options for the Consumer Expenditure Survey 30 

multiple diary survey. For example, the mean number of reported expenditures per CU was 53.8, 

compared to 37.8 for the production survey. Perhaps more suggestive is a comparison of the mean 

level of expenditures. The single diary CUs had a mean of $856 for the first week of collection 

compared to $1137 for the multiple diary procedure. This is a ratio of about .75. A slightly lower 

ratio of .65 was found for the week 2 ($838 versus $1272). The means for the multiple-diary group 

may have been inflated because blank diaries were not consistently included in the computations. 

Therefore, the differences between the mean reported expenditures of the single and multiple diary 

groups may have actually been somewhat smaller. 

Qualitative evidence—feedback from the field interviewers—indicates that the multiple-respondent 

procedure seemed to encourage the principal respondent to communicate more with others in the 

household. The multiple-respondent procedure seemed to impress upon the principal respondent 

the importance of the task of collecting as many of the CU expenditures as possible.

The multiple-respondent procedure did lead to a lower response rate (61% versus 77%). However, it 

is unclear whether this led to significant bias. Perhaps more troubling is that it took almost twice the 

effort to complete a CU for the multiple diary procedure (5.1 visits versus 2.7 visits). It is difficult to 

know exactly how much of an increase in actual costs this implies without more information on the 

amount of additional time field interviewers spent completing interviews. Nonetheless, taken at face 

value, and based on crude interpolation from Westat cost data, this additional interviewer time could 

lead to up to twice the field costs of the current procedures.

The multiple-respondent procedure is worth considering because of its potential to directly address 

measurement error. While the Census study was not designed to draw quantitative conclusions, it 

does suggest that underreporting could be reduced if multiple respondents report data in each 

household. The multiple-respondent procedure has the potential to reduce the overall mean square 

error. In addition, it also may reduce respondent burden by relieving the principal respondent of 

having to proxy for others in the household. 

Respondent Incentives 

A vast literature exists on the effectiveness of incentives in boosting the response rates in various 

kinds of surveys. Researchers have studied incentives such as cash, checks, gift cards, and contests. 
Redesign Options for the Consumer Expenditure Survey 31 

The results suggest that under appropriate conditions, carefully chosen incentives can be a costeffective means to increase response rates.

Both Berlin et al. (1992) and RTI (2002) tested different levels of incentives for an in-person 

household interview. Both found that incentives increase response rates and save enough money to 

pay for themselves. Similarly, significant incentive effects have been found in comparable 

experiments involving SIPP and the Survey of Program Dynamics (Creighton, King, & Martin, 

2007; Martin, Abreu, and Winters, 2001), the American Time Use Survey (Piskurich et al., 2001), and 

many surveys prior to those (Church, 1993; Singer, 2002).

More recently, Hicks, Connor, Ward, et al. (2009) offered respondents cash incentives in the Medical 

Expenditure Panel Survey. They found that incentives of $50 and $70 improved the response rates 

relative to the existing $30 incentive. This effect was apparent in most subgroups of respondents, 

including low-income, Hispanic, and Black respondents. Moreover, the incentives did not greatly 

increase the costs per case.

Perhaps more relevant for the CE, Goldenberg, McGrath, and Tan (2009) gave randomly selected 

households in the Quarterly Interview survey either a $20 or a $40 prefilled debit card prior to the 

first of the five interviews. The results suggest that the incentives boosted the response rates and this 

effect persisted at least through the fourth interview. The results further suggested that “...incentive 

recipients performed better when compared to the control group on most of the indirect data 

quality measures: they answered more expenditure questions, they used records more frequently, 

they provided fewer don’t know and refused answers, and their reported data required fewer 

imputations and allocations. The $40 incentive performed better than the $20 incentive on 7 of 11 

measures, but some of the differences were very small and most were not statistically significant.” 

(Goldenberg, McGrath, and Tan, 2009). 

Redesign Options for the Consumer Expenditure Survey 33 

This section presents our recommendations for redesigning the CE surveys. Our recommended 

redesign maintains separate Diary and Quarterly Interview surveys. The Quarterly Interview survey 

would collect information primarily about larger expenditures, while the Diary survey would collect 

data primarily on smaller, more frequent expenditures. 

Overview 

In our recommended redesign, the Diary survey would continue to require the respondents to 

record all their household expenditures over a 2-week period. The methods that each respondent 

use to keep an expenditure diary would be tailored to the needs and preferences of the respondent. 

Some may use the current method involving a paper diary. Some may save paper receipts and mail 

them to a central data repository. Some may save paper receipts, scan them, and send the scan files 

to the data repository electronically. Some may also download financial data files, such as for credit 

card accounts, and send those files to the data repository electronically. Some may instead mail in 

photocopies of the monthly statements for their credit card, checking, and other accounts. 

Our recommendations for the Quarterly Interview survey call for four contacts with the household 

over a 15-month period. Three contacts would be face-to-face, and one would be by telephone. 

Additional telephone contacts would be made to motivate the respondent to keep track of expenses. 

In the first face-to-face interview, the interviewer would collect information about the household, 

obtain consents to release records, select the methods by which the respondent would gather and 

report data, and conduct a bounding interview. 

Over a 3-month period, the respondent would report household expenditures. The methods that 

each respondent would use would be tailored to the needs and preferences of the individual 

respondent. The respondents in the Quarterly Interview survey could save and mail in their paper 

receipts, or they could save, scan, and send the receipts to the repository electronically. They could 

download the financial data files and send them to the repository electronically, or they could mail in 

photocopies of their checking, credit card, or other monthly statements. 

Recommended Design: Diary Survey 4 
Redesign Options for the Consumer Expenditure Survey 34 

During this 3-month period, the interviewer would call the respondent three times: 2 weeks, 

1 month, and 2 months after the initial interview. The interviewer would ask if the respondent had 

any questions or was experiencing any problems. The interviewer would ensure that the respondent 

understood the data collection procedures, and try to resolve any issues that might be keeping the 

respondent from following those procedures. The purpose of these calls would be to keep the 

respondents motivated to report their data. 

The second face-to-face interview would occur 3 months after the first. The nature of this interview 

would depend on how completely the respondent provided expenditure data over the 3-month 

period. The interviewer would collect information to augment the data that the respondent had 

reported. 

One year after the initial interview, the respondent would again keep and report expenditure data for 

a 3-month period. 

In both the Diary survey and the Quarterly Interview survey, CE field representatives would attempt 

to obtain purchasing history data from certain retailers. Agreements may be in place for retailers to 

provide these data using the loyalty card numbers of the respondents. 

A summary of the differences between the current procedures and the recommended procedures is

shown in Table 6. The current Diary survey and our proposed redesigned Diary survey both employ 

a 2-week data collection period, with two 1-week diaries. However, our recommended redesign 

emphasizes the use of both electronic and paper records, uses multiple respondents in each 

household, and collects data from administrative records. 

Our recommended redesigned Quarterly Interview survey differs in many ways from the current 

design. The current design is a panel survey with four data collection waves spaced 3 months apart, 

using a combination of in-person and telephone interviews. The redesigned survey reduces this to 

two waves, spaced 12 months apart. There are three in-person interviews and one telephone 

interview. This difference reduces burden by requiring only two waves of data collection, with more 

time in between. As with the Diary survey, there is a greater emphasis on the use of electronic and 

paper records. There is also an incentive and an administrative survey to substitute for collecting 

data directly from the respondent. 
Redesign Options for the Consumer Expenditure Survey 35 

Table 6. Comparison of design features of current and redesigned surveys

Design feature Current collection Redesigned survey 

Diary Survey 

# of Recall Interviews/CU 0 -- 2 (depends on use of diary) 0–2 (depends on record use)

Reference period 1 week 1 week

Sample Design Cross sectional Cross sectional

Mode Paper Web and paper

In-person/telephone interviews 3 1–3, depending on use of records

Telephone reminders Yes, unknown how many 1–4 depending on use of records

Number of respondents 1 person All persons 14+

Incentives None Monetary and nonmonetary

Personal electronic records None All respondents willing to use it

Use of receipts Yes, not strong emphasis Yes, very strong emphasis

Administrative Record Survey No From retailers used by respondents

Interview Survey 

# of Recall Interviews/CU 4 2

Reference period 3 months 1, 3, 12 months depending on item

Sample Design Panel – 4 waves (3 months apart) Panel, 2 waves (12 months apart)

Mode CAPI Web, CAPI

In-person/telephone interviews 5 3

Telephone reminders Not known 6–7, depending on use of records

Number of respondents Main CU respondent Main CU respondent

Incentives None Monetary and nonmonetary

Personal electronic records None All respondents willing to use it

Use of receipts Yes, not strong emphasis Yes, very strong emphasis

Administrative Record Survey No From retailers and Utility Companies

This chapter and the succeeding chapter respectively provide the details of the redesigned Diary and 

Quarterly Interview surveys.

Diary Survey Procedures 

Our recommended redesign methods for the Diary survey are tailored to the preferences and the 

technological abilities of the respondents. Some respondents have no interest in using any of 

technology and would prefer to keep paper records, while others will wish to use technology. 

Respondents in the Diary survey would report their expenditure data over a 2-week period. The 

schedule and procedures are shown in Table 7. The procedures would consist of 5 total contacts by 

the interviewer: (1) initial contact, (2) 3-day reminder call, (3) 1 week contact to finalize purchases 

for prior week, (4) 10 day reminder call and (5) final contact to finalize purchases over the previous 

week. Table 7 provides an outline of the mode for each of these contacts and an outline of the 
Redesign Options for the Consumer Expenditure Survey 36 

procedures for each one. Below we describe in more detail how the data would be reported by the 

respondent and the interviewer’s role. 

Table 7. Schedule for the redesigned Diary survey

Initial interviewer visit to the household – In person

 Respondent signs consent form to obtain information electronically

 The method that respondent will use to provide data is chosen (paper or electronic)

 Interviewer provides a scanner to respondents who will report electronically

 Interviewer provides an envelope or box for respondents to store receipts

 Interviewer provides diary forms to respondents who will neither mail nor scan receipts

2-3 days after initial visit – Telephone

 Interviewer calls respondent, helps respondent overcome any barriers to providing data

 Interviewer continues to monitor respondent’s data reporting activity

7 days after initial visit – Telephone/In person

 If the respondent appears to be sending data electronically or on paper diligently, interviewer 

telephones; otherwise interviewer visits in-person

 If interviewers visit in-person administer a recall interview

 Interviewer continues to monitor respondent’s data reporting activity

10 days after the initial visit – Telephone

 Interviewer calls respondent, helps respondent overcome any barriers to providing data

 Interviewer continues to monitor respondent’s data reporting activity

14 days after the initial visit – Telephone/In person

 If the respondent appears to be sending data electronically or on paper diligently, interviewer 

telephones; otherwise interviewer visits in-person

 Interviewers who call close out the data collection

 Interviewers who visit in-person administer a recall interview and close out the data collection

Respondents Who Elect to Submit Their Expenditure Data Electronically. The system that 

Westat proposed in the BLS project Data capture technologies and financial software for collecting consumer 

expenditure data is the model for the proposed Diary survey. The redesign is based on the concept of 

a central repository. The central repository receives, stores, and manages expenditure data from all 

the respondents. Each respondent has his or her own email address in the repository, so that the 

respondent can provide data electronically. 

File Downloads. Respondents periodically download the data files for their credit card, bank, and 

PayPal accounts and email them to the repository. They could do this in either of two ways. First, 

software could be developed for this purpose. This software would download files much like 

existing financial software products like Mint does: Respondents select their financial institution 

from a list, enter their user names and passwords, and the file download occurs automatically. The 

software then would automatically email (or transfer via FTP) the files to the repository. 
Redesign Options for the Consumer Expenditure Survey 37 

Some respondents might wish to have greater control over the process of downloading these files 

and emailing them to the repository. They may fear that the privacy of the files could be 

compromised. For that reason, respondents could choose to download the files directly from the 

web sites of the financial firms and email them to the central repository themselves.

The data in credit card and PayPal files show the date, amount, and vendor for each purchase. The 

data in bank account files show the amount for purchases by check and the date that the check 

cleared. The data in bank account files show the vendor, amount and date for purchases by debit or 

automatic fund transfer. 

Receipts. Respondents would retain all receipts for their purchases. They would be given stickers to 

put on their wallets reminding them to ask for receipts. When a receipt was in the form of an online 

purchase confirmation, they would print it out. 

The respondents would scan their receipts and email the scan files to the repository. Respondents 

could be given small receipt scanners (similar to the NeatDesk digital scanner) and special software 

for this purpose. The software would automate much of the process. It would instruct the 

respondent how to use the scanner, prompt the respondent to start scanning, and automatically 

email (or transfer via FTP) the scans to the repository.

The repository would receive the scans of the receipts and convert them to text using Optical 

Character Reader (OCR) software. From this text, the system would derive information about each 

item purchased. Software could be developed to extract the individual items that comprise the total 

purchase. For example, if a respondent purchased ten items at a supermarket, the software would 

capture the description and the cost of each of the ten items listed on the single receipt. Creating 

software with this capability will be challenging. Receipts often contain a great deal of text other 

than a description of the purchase and the cost (e.g., “1.5 lb @ $2.00/lb”, “Bonus card savings 

10%”). The software would need to ignore that extraneous text and locate the text that describes the 

individual items purchased and the corresponding costs (e.g., Apples $4.22). The software could also 

be designed to identify returns and exchanges listed on a receipt. 

Several software products already exist that extract data from a document. The AnyDoc suite of 

software products and Nuance OmniPage can extract data from documents. However, they lack the 

functionality to extract expenditure data from receipts. New software would need to be created to 

extract data about purchases, returns, and exchanges from the text of scanned receipts.
Redesign Options for the Consumer Expenditure Survey 38 

Having identified the individual items purchased, the system would then attempt to classify each 

purchase according to the CE categorization scheme. For example, the system would recognize that 

“cheese” was a food item and “shirt” was a clothing item. The system could do this by consulting a 

database of expenditure terms created specifically for the CE program.

Data Matching. The system could then match the receipt data with data from the credit card, 

checking, PayPal, and other financial files. For example, a receipt might show a purchase of $5.52 at 

Home Depot on July 4, 2011. A credit card data file might show a purchase of the same amount, at 

the same store, on the same date. The system would categorize these data as a match. In this way, 

the system would recognize that the data from the two sources both correspond to a single 

purchase. 

This expenditure matching procedure is not novel. It is a standard feature in financial software 

packages such as Mint (2011) and Moneydance (2011). 

The data on receipts for purchases by check, credit card and PayPal will match the corresponding 

data in the credit card, checking, and PayPal files. Data on receipts for other kinds of purchases, 

such as cash purchases, will not match any data in those files.

In addition, some of the purchases documented in the bank, credit card, and PayPal files may not 

match any receipt data. For example, if a respondent did not obtain and scan a receipt for a 

purchase, the system will not be able to match the data in the check, credit card, or PayPal file for 

that purchase with any receipt data. Also, an electronic fund transfer from a bank account, such as 

for a loan payment or a utility bill payment, will not have a corresponding receipt. Therefore, those 

expenditures will appear in the data file for a financial account but the system could not match the 

expenditure with any receipt data.

Expenditures with No Receipt and No Electronic Record. The respondents will sometimes 

make purchases that have no receipt and that have no electronic record. For example, expenditures 

transacted with cash or money order typically have no electronic record. Some expenditures such as 

vending machine purchases involve no receipt. Respondents would need to keep a paper-and-pencil 

record of these expenditures. They could be given a rule: If you are not given a receipt, create your 

own. 
Redesign Options for the Consumer Expenditure Survey 39 

This record could be in the form of a short form that the respondents complete. One possibility is 

that the respondents complete one form per purchase. They could then scan the form along with 

the receipts and email the scan to the central repository. 

Web Questionnaire. The data in the financial data files, receipts, and short forms would not be 

sufficient for the CE program. Table 8 shows the kinds of data available from the various sources. 

The table shows that receipts have most but not all of the information required by the CE program. 

In order to collect the necessary information, we recommend that the repository system periodically 

ask each respondent to complete a web questionnaire. The repository system would create the web 

questionnaire automatically and email it to the respondent. Each page of the questionnaire would 

ask about a single item purchased. 

For example, the web questionnaire might pose a question like “On July 4, 2011, you purchased 

three items at Home Depot. One item was a hammer for $8.95. Was this item for someone on your 

household list?” The system would consult the database of terms and categorize “hammer” as 

“other” rather than “food and drinks” or “clothing.” 

The following examples illustrate how the repository could handle various purchases. 

Credit Card Purchase with Receipt. Respondent A buys 20 items at Safeway, including 3 pounds 

of apples for $6.00, on July 6, 2011, paying for the purchase by credit card. Respondent A scans the 

receipt for this purchase. The scan goes to the repository. The system applies OCR to capture the 20 

items on the receipt, including the apples. The system matches the receipt with the corresponding 

charge in the respondent’s credit card file. Later the system sends an email that asks Respondent A 

to complete a web questionnaire. One of the pages in that questionnaire contains this text: “On July 

6, 2011, you purchased apples for $6.00.” The page also shows the relevant lines from the scanned 

Safeway receipt, which might read “Apples......$6.00.” The page then presents questions to elicit 

the information required by the CE surveys. The system could consult the database of expenditure 

terms to recognize that “apples” is categorized as food. The web survey would ask CE questions 

appropriate for a food, for example, whether it is for consumption at home, and when the 

respondent replies “yes,” whether it is for someone outside the household. 
Redesign Options for the Consumer Expenditure Survey 40 

 

Table 8. Information that appears on various kinds of records of expenditures

 

Date of 

transaction Service 

dates 

Total 

price 

Tax 

amount Tax rate 

Shipping 

fees 

Item 

verbatim 

description 

Item 

description Item ID 

number 

Item 

price 

Item 

rebate 

price 

Cash, no receipt

Paper receipt U U U S U U S U U

Electronic 

confirmation

U U U U S U U U U U

Downloaded file: 

EFT

U U

Downloaded file: 

check

U U

Downloaded file: 

debit card

U U

Downloaded file: 

credit card

U U

Money order

Cashier’s check

NOTE: “U” signifies that the information usually appears in the record. “S” signifies that the information sometimes appears in the record. Service dates refers to the dates that the service 

was received, such as the span of time that a utility provided service. “Item verbatim description” refers to text used by the vendor such as “tshrt” while “item description” refers to readily 

understandable text such as “tee shirt.” “Item ID number” refers to a code such a SKU or UPC number. “Item price” refers to the price of individual items included in the “total price.”

“Item rebate price” refers to discounts for individual items.
Redesign Options for the Consumer Expenditure Survey 41 

Check Purchase with No Receipt. Respondent B signs a contract to have an addition built for his 

house. Respondent B gives the builder a $2,000 check but builder does not immediately provide a 

receipt for payment; the only record of the payment is the contract and the check itself. The 

checking account data file that Respondent B sends to the repository shows the date and amount of 

the check. No receipt matches this check. For that reason, the system asks Respondent B about that 

check in the web questionnaire: “On July 9, 2011 you wrote a check for $2,000. What did you 

purchase?” After Respondent B enters “Construction on my house,” the system consults the 

database of terms, but does not find that phrase. The system therefore asks, “Was this check for 

food and drinks away from home, food and drinks for home consumption, clothing, shoes, jewelry 

and accessories, or all other products, services, and expenses?” Respondent B replies that the 

expense is in the “other” category. The web survey then asks the question, “Is this purchased for 

someone outside the household?” and Respondent B replies with “no.” 

Cash Purchase with Receipt. Respondent C buys $20.00 of gasoline and pays with cash. 

Respondent E gets a receipt for this purchase, and later scans the receipt and emails it to the 

repository. The system applies OCR to read the receipt, and tries to match the purchase with any 

check or credit card purchase in the bank and credit card files. Since this was a cash purchase, the 

system finds no match. It therefore asks Respondent C about the receipt in the web questionnaire. 

The software could be able to apply OCR to determine that the receipt is for gasoline, which falls 

into the “other” CE category. The software could also be able to capture the price from the scan of 

the receipt. The web questionnaire displays an image of the receipt and asks “This appears to be a 

receipt for a $20.00 purchase of gasoline. Is that correct?” When Respondent C answers “yes,” the 

web questionnaire asks the question appropriate for the “other” category—whether the item was for 

someone on Respondent E’s household list. 

Electronic Fund Transfer with No Receipt. Respondent D pays her electric bill through 

electronic fund transfer from her checking account. No receipt is issued. The system detects this 

debit in the checking account data file and finds no matching receipt. Accordingly, the web survey 

asks, “On July 12, 2011, your checking account was debited $125.60 to the Southern Electric 

Company. What did you purchase?” It then asks the other questions necessary for the CE program. 

Respondents Who Do Not Elect to Submit Their Data Electronically. Diary survey 

respondents who choose not to submit their data electronically would still be encouraged to keep 

their receipts. They would be given a box or envelope which they would use to store all their 

receipts. Printed on the box or envelope would be a reminder to obtain and keep receipts. The 
Redesign Options for the Consumer Expenditure Survey 42 

envelopes or boxes would be ready for mailing, with a postage-prepaid frank, and pre-addressed to 

the data repository. 

These respondents would also be asked to keep all their credit card, checking account, and other 

relevant statements that they receive in the mail. If they make any online purchases, they will be 

encouraged to print out and retain the purchase confirmations. 

The respondents would be encouraged to create their own record when they make any purchases 

that involve no receipt. They would be provided short forms to record purchases. If they make a 

purchase with no receipt, such as from a vending machine, they would complete the form to create a 

record. 

The respondents would periodically send, via U.S. Mail, their receipts and forms to the central 

repository. They would also mail photocopies of their credit card and checking account statements. 

Repository staff would scan the receipts and forms (much like services like shoeboxed.com do), and 

enter data from the financial statements. 

Respondents Who Wish to Use a Paper Diary. Some respondents will not wish to scan or to 

mail their receipts to the central repository. These respondents will be permitted to record their 

expenditures in a paper diary, using the current Diary survey methods. 

Interviewer’s Role. During the initial visit to the household in the Diary survey, the interviewer 

would determine whether the respondent was willing and able to use technology to report their 

expenditure data. The interviewer would give instructions on how to record information. The nature 

of those instructions would depend upon the respondent’s willingness and ability to use technology. 

Technology users would hear how to scan receipts and download data files. Nonusers of technology 

would hear how to keep and mail paper records. The interviewer would go through several examples 

with the respondent until the interviewer felt certain that the respondent understood. 

The interviewer would set up advance appointments to talk with the respondent by telephone. The 

purpose of these calls would be to monitor and assist the respondent during the 2-week collection 

period. The interviewers would speak with the respondents at least four additional occasions after 

the first contact. The first call would occur 2 or 3 days after the initial contact.

The interviewer would monitor the activity of those respondents. The interviewers would observe if 

respondents were complying with the instruction to submit data to the repository, whether by U.S.
Redesign Options for the Consumer Expenditure Survey 43 

Mail or electronically. During the first call, interviewers who detect no data collection activity would 

ask the respondents whether they are obtaining receipts. If they are, the interviewers will encourage 

them to scan the receipts or send them in by U.S. Mail. If the respondents are neglecting to 

complete the web questionnaire, the interviewers would encourage them to do so. 

The third contact would occur 1 week after the initial interview. The interviewers would have the 

option to make either an in-person visit or a telephone call. An in-person visit would be necessary if 

the respondent was failing to scan receipts or to send or mail the files to the central repository. In 

this case, the interviewer would personally examine the receipts and other documentation and 

conduct a recall interview. An in-person visit would also be necessary for those respondents who are 

reporting their expenditure data by filling out the paper diary. 

The fourth contact would be by telephone. The interviewer would monitor the respondents’ data 

collection activity. For respondents who are not sending information to the repository, the 

interviewer would ask about purchases that may have been missed. 

The fifth, and final, contact would close out the data collection. If the respondent has been 

providing data electronically and completing the web questionnaires, then the contact could be by 

telephone, with a final review of purchases over the prior week. If the respondent had been 

providing data in paper form, or had elected to scan or mail in receipts but had not been consistently 

complying, this visit would be in person. The interviewer would conduct a recall interview during 

this visit.

Recall Interview. The recall interview would augment the data that the respondents had provided 

either electronically or on paper. The interview would also help the respondents to report 

expenditures that they had not yet reported. Some respondents will not adequately download 

financial data files or keep receipts. For those respondents, the recall interview will be the primary 

means of collecting data. 

The respondents would provide details about their expenditures in the recall interview. The recall 

interview would be similar to the current Quarterly Interview survey, except that we recommend 

using an Event History Calendar to help the respondents recall their expenditures. An Event History 

Calendar uses salient events during the reporting period to help the respondent remember events 

that may not be as salient—such as expenditures. 
Redesign Options for the Consumer Expenditure Survey 44 

Single or Multiple Respondents per CU. Considering the results of prior research (Westat, 2005; 

Edgar et al., 2006), we recommend a multiple respondent approach for the Diary survey in which all 

adults in the household provide data about their expenditures. The principal respondent would be 

solely responsible for reporting key expenditures such as rent and utilities. For those that report their 

data electronically, all CU members at least 14 years old will have their own account in the central 

repository. They would be asked to download and email their credit card, checking, and other 

relevant financial files. They will be asked to scan and email receipts. They will also be asked to 

respond to a web survey about their purchases. For those CUs that do not report their data 

electronically, all CU members will mail in receipts and financial statements or keep paper-andpencil diaries. Following the procedures of FoodAPS and other surveys using multiple respondents 

(Westat, 2005; Edgar et al., 2006), the interviewer would ask the principal respondent to instruct the 

other household respondents in the data collection procedures. 

Respondent Incentives. We suggest both monetary and non-monetary incentives. Monetary 

incentives have proven very effective on field studies, such as the Diary survey, to increase response 

rates in a cost effective manner. 

Given the level of effort required for the CE Diary survey, we recommend an incentive of at least 

$50 for the principal respondent. This amount is slightly higher than the amount that Goldenberg et 

al. (2009) tested. However, it is consistent with the amounts proposed for the Medical Expenditure 

Panel Survey and several other field surveys such as the National Survey on Drug Use and Health. 

The incentive would be provided in the form of a prepaid debit card. We also propose a smaller 

incentive of $10 for each of the individual respondents within the household. This is consistent with 

several other federal surveys with multiple respondents (e.g., National Health and Nutrition 

Examination Survey, and FoodAPS). A final level of monetary incentives should be determined 

during the development process. FoodAPS will soon experiment with several incentive levels; the 

results could be applicable to the CE Diary survey.

Additional incentives might be useful to encourage respondents to use electronic records and to 

keep receipts. Wine and Riccobono (2011) report the use of incentives to promote early response to 

the web survey for the National Postsecondary Student Aid Study. A similar incentive structure 

could be considered for respondents who email and scan expenditure documentation in a timely 

way.

We also recommend that the household members receive a non-monetary incentive. The CE 

program provides an opportunity to offer unique incentives that are relevant to the survey itself. 
Redesign Options for the Consumer Expenditure Survey 45 

That is, CE respondents might receive an incentive in the form of useful information about their 

spending. This incentive might motivate respondents to provide complete and accurate data because 

those data would actually enhance the value of the incentive.

One potential non-monetary incentive is a report in which the respondent’s spending is compared 

with that of other people. The report would contain both graphs and text. This incentive would 

show respondents how their data compared with others with similar demographic background. For 

example, the incentive could be in the form of reports which contained graphs displaying the 

respondents’ spending patterns beside the spending patterns of people of the same age and sex, of 

people who live in the same geographic area, or who have the same number of people in the 

household. The comparison data for these reports could come from recent CE results. These 

reports could be in hard copy or online form. 

The financial software package Bundle uses a similar approach (www.bundle.com). Developed by 

Microsoft, Morningstar, and Citigroup, Bundle helps users monitor their spending and keep to a 

budget, like other financial software products such as Mint, Moneydance, and Buxfer. Bundle is 

unique, however, in that it creates online charts for the users, showing the characteristics of their 

spending alongside the spending of others with similar demographic backgrounds. 

Smartphones. Some respondents will be interested in using their smartphones to keep some 

expenditure records. These respondents might use their smartphones to photograph purchases that 

have no receipts, such as an item bought from a vending machine. They might use their 

smartphones to fill out a short form, appearing on the screen, to provide data about the purchase. 

They might record an audio memo describing the purchase on the smartphone. 

Respondents potentially could then refer to these reminders later, to complete paper forms about 

the purchases. They would then scan the forms and send them electronically to the repository. 

Conceivably, the photographs, audio memos, or electronic forms could be sent electronically to the 

repository. These reminders could then be incorporated into the web survey. For example, one page 

on the web survey might have a question like this: “On July 20, 2011 at 3:19 pm you recorded this 

audio memo [click here to listen]. What did you purchase?” 

We believe that smartphones potentially can play an important role in the CE program, as we 

described in our earlier report for BLS (Schneider and Reifer, 2011).
Redesign Options for the Consumer Expenditure Survey 46 

Loyalty Card and Other Retailer Information. For both the Diary and Interview surveys in our 

proposed CE redesign, respondents would be asked to sign a consent form to allow the interviewers 

to obtain expenditure information from the stores where the respondents have loyalty cards. Prior 

arrangements would have to be made with the retailer to arrange for release of this information. 

BLS, the Census Bureau, or a contractor acting as a government proxy, could attempt to negotiate 

procedures for obtaining data from grocery chains, chain pharmacies, and other retailers who have 

loyalty card programs. 

The loyalty card data could serve several purposes: 

 The data would reveal expenditures that the respondents neglected to report; 

 The data could be used to check the accuracy of the data that the respondents provided 

from memory; and 

 The data could be used to itemize purchases when the respondents provided only the 

total sum of all items purchased. For example, when respondents provide a credit card 

invoice that shows only the total amount of the purchase, these data could provide a list 

of the purchased items and their individual costs. 

Diary Survey Costs and Implications for Sample Size 

In this section we discuss the estimated costs and variance implications of the proposed procedures. 

Costs. The Census Bureau provided a summary of CE variable costs for 2010 (including a 

breakdown between interview and diary costs). We used that summary as the primary basis for 

estimating the cost of the proposed design. We transformed some of the Census data (e.g., costs per 

interview, costs per noninterview) into more commonly used metrics (e.g., cost per completed 

interview as the expression of the total costs divided by the number of completed interviews). 

Because the current design does not incorporate any administrative data, we drew upon Westat’s 

2009 cost experience collecting data from administrative records of health care providers on the 

Medical Expenditure Panel Survey’s Medical Provider Component (MPC), sponsored by the HHS 

Agency for Healthcare Research and Quality (AHRQ).

Table 9 summarizes the results of the cost estimation exercise. It compares the current design with 

the design we propose here, holding sample size constant, at 7,000 Consumer Expenditure (CE) 

units. This table provides costs for both the proposed Diary and Quarterly Interview survey design. 
Redesign Options for the Consumer Expenditure Survey 47 

In this section we concentrate on the costs of the Diary survey. The Quarterly Interview survey 

costs are discussed in a later section.

Many assumptions are required to extrapolate costs for the proposed design from the Census CE 

data and the Westat MPC data. For collecting the Diary survey data, the assumptions are provided in 

Tables 10 and 11 for the field data collection and administrative record collection, respectively. Each 

table compares the proposed design with the current design. For the field data collection, these costs 

consist of a combination of personal visits and prompting by telephone. For the administrative data, 

these consist of contacting providers and collecting record data. 
Redesign Options for the Consumer Expenditure Survey 48 

 

Table 9. Summary comparison of current and proposed CE designs

 

Current design 

Proposed designs 

One respondent per CE unit 

for Quarterly Interview, 

multiple for diary 

Multiple respondents per CE 

unit for Quarterly Interview, 

multiple for diary 

Quarterly Interview 

Interviews/CE unit/quarter 1 1 2

Quarters 4 4 4

Interview cost $17,048,783 $24,685,164 $43,199,036

Interview cost/complete $476 $342 $375

Administrative records cost NA $10,192,920 $13,250,796

Administrative records cost/complete NA $283 $368

TOTAL QUARTERLY INTERVIEW COST $17,048,783 $34,878,084 $56,449,832

TOTAL QUARTERLY INTERVIEW COST/COMPLETE $118 $171 $150

TOTAL QUARTERLY INTERVIEW COST/CE Unit $588 $969 $1,568

Diary 

CE Units 7,449 7,449 7,449

Diaries/CE unit/week 1 2 2

Weeks 2 2 2

Interview cost $5,111,926 $7,502,577 $7,502,577

Interview cost/complete $343 $252 $252

Administrative records cost NA $805,992 $805,992

Administrative records cost/complete NA 803 $803

TOTAL DIARY COST $5,111,926 $8,308,569 $8,308,569

TOTAL DIARY COST/COMPLETE $343 $279 $279

TOTAL DIARY COST/CE UNIT $686 1,115 $1,115

GRAND TOTAL -- CE COST FOR ONE YEAR, BOTH COMPONENTS $22,160,709 $43,186,652 $64,758,401 
Redesign Options for the Consumer Expenditure Survey 49 

 

Table 10. Summary of CE diary costs

 

A B C D E F G 

 

Total diary 

cost 

Completed 

CE units 

Cost/ 

completed 

CE unit 

Completed 

diaries 

Cost/ 

completed 

diary 

Administrative 

records cost 

Admin. 

records 

cost/ 

CE unit 

Formula 

 

A/B 

 

A/D 

 

F/B 

Current design (Assumes 2PVs, one diary per week, 2 weeks) NA NA

PV $5,111,926 7,449 $686 7,449 $686 NA NA

TOTAL DIARY COST $5,111,926 7,449 $686 7,449 $686 NA NA

Proposed design 

(Assumes 2.3 PVs,

Two diaries per week, 2 weeks)

Initial visit (PV) $4,355,375 7,449 $585 14,898 $585 NA NA

3 Prompts,most by phone $931,125 7,449 $125 14,898 $100 NA NA

Follow-up Interview

- Telephone @ .3 $391,073 2,235 $175 4,469 $215 NA NA

- Personal Visit@.7 $1,825,005 5,214 $350 10,429 $400 NA NA

TOTAL DIARY COST $7,502,577 7,449 $1,007 14,898 $504 NA NA

TOTAL DIARY + ADMIN. RECORDS $8,308,569 7,449 $1,115 29,796 $279 $805,992 $108
Redesign Options for the Consumer Expenditure Survey 50 

 

Table 11. Administrative records cost for diary

 

2009 MEPS MPC 

Diary 

Sum 

Proposed CE design 

Hospitals Office-based 

doctors 

Large 

organizations 

Small 

organizations 

Interviewing $2,339,952 $1,172,293

Abstraction $1,710,737 $631,824

Other $957,298 $510,209

Total $5,007,987 $2,314,326 $552,866 $253,126 $805,992

Completes (providers/vendors) 4,720 8,501 1,042 931 1,973

Cost per unit $1,061 $272 $531 $272 $803

Household reporting units 8,500 8,500 7,444 7,444

Provider or vendor completes/household reporting units 0.56 1.00 0.56 0.25
Redesign Options for the Consumer Expenditure Survey 51 

The cost of the proposed design for the Diary is approximately 60 percent higher than the current 

design. One major addition for the new procedure is the collection of data from multiple 

respondents. The additional personal visits and telephone calls shown on the budget provide the 

additional costs associated with this. This feature contributes approximately $2.4 million of the 

additional $3.2 million of the higher costs of the new procedure. A second addition is the collection 

of administrative data, which is not done under the current design. This accounts for the remainder 

of the additional costs. 

The administrative records aspect of the proposed design poses the greatest cost uncertainty. For 

this exercise, we have assumed that vendors and financial institutions will cooperate in providing 

cost information for their customers, but the feasibility of the proposed approach needs to be 

established with a proof of concept exercise, then tested carefully in the field. The experience base is 

much smaller for collecting administrative data in surveys than for conducting interviews and 

collecting diaries from household populations. We have made some rather arbitrary assumptions 

about the number of large and small vendors that would be asked to provide cost information for 

their customers, leveraging off the MPC data for hospitals and physicians. However, it should be 

noted that the MPC sample was driven by cost considerations. It supplements the MEPS Household 

data, and AHRQ determined from the outset that some provider types were more important than 

others for estimating national healthcare costs. Thus, hospital events reported by the household 

were sampled with certainty, but only a subsample of the office-based physicians was included in the 

MPC. In imputing for missing data, households with complete data for physicians served as donors 

for households with physician visits that were not selected for the MPC. Similar decisions could be 

made about the CE administrative data in the proposed design, so that it could be scaled up or down 

to meet available resources.

Implications for Sample Size. From a sampling and variance perspective, the proposed design 

does not significantly differ from the current design. Both use a 2-week data collection period. 

Therefore, the above cost discussion provides guidance on the sample sizes required to meet current 

program standards. As discussed, the cost of the recommended design, using multiple respondents, 

is approximately 80 percent more expensive than the current design. It is difficult to translate this 

exactly to implications for sample size. One approximation assumes a direct relationship between 

the increase in cost and sample size. Under this assumption, and without increasing the CE budget, 

the recommended design would collect data from approximately 60 percent of the CUs that provide 

data under the current design. Much of the additional collection cost for the new procedure is 

attributable to the collection of diaries from multiple respondents, rather than just one respondent. 
Redesign Options for the Consumer Expenditure Survey 52 

If the current single respondent design were continued, the unit cost of the recommended design

would be closer to the current design, even including the administrative record collection. 
Redesign Options for the Consumer Expenditure Survey 53 

In our recommended redesign, the primary purpose of the Quarterly Interview survey is to collect 

information about larger expenditures, while the primary purpose of the Diary survey is to collect 

data on smaller, more frequent expenditures. For example, expenditures for food would be covered 

by the Diary survey; these usually small, frequent expenditures would either not be covered, or be 

covered in only abbreviated form, by the Quarterly Interview survey. We are asumming that the 

income data that is currently collected on the Quarterly Interview survey would also be collected.

Our recommendations for the Quarterly Interview survey are intended to minimize respondent 

burden in two ways:

 The number of in-person interviews per CU will decrease from the current five to three; 

and 

 Some expenditure data will be collected through records, rather than interviews.

The current design has a total of five in-person interviews per household, creating significant cost 

and respondent burden. Reducing this number to three in-person interviews would substantially 

reduce this burden and may lead to greater cooperation, fewer dropouts, and better data quality. The 

rotation design is illustrated in Figure 3. Each sampled address will be interviewed in two sets of 

interviews, spaced 12 months apart. For example, in Figure 3, the sample in panel 3 month 3 is 

initially interviewed in Year T+1 and then re-interviewed in Year T+2 in month 3. By collecting data 

at two points in time, the CE program can continue to collect longitudinal data to measure annual 

change and take advantage of the economies associated with following up households that have 

already been recruited. 

The second way our recommended redesign reduces respondent burden is by collecting data about 

many of the expenditures through records. Data about most or all of the large expenditures is likely 

to be available on paper or electronic records and receipts. In addition, data about some 

expenditures may be available relatively easily from sources other than the household. For example, 

financial companies may provide data about mortgage and other loan payments. Utility companies 

may provide data about electricity or natural gas payments.

Recommended Design: Quarterly Interview 

Survey 5 
Redesign Options for the Consumer Expenditure Survey 54 

 

Figure 3. Rotation schedule for proposed design for the Quarterly Interview survey

Year T Year T+1 Year T+2 Year T+3

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar

5(1) 5(2) 5(3)

4(1) 4(2) 4(3) 4(4) 4(5) 4(6) 4(7) 4(8) 4(9) 4(10) 4(11) 4(12) 4(1) 4(2) 4(3)

3(1) 3(2) 3(3) 3(4) 3(5) 3(6) 3(7) 3(8) 3(9) 3(10) 3(11) 3(12) 3(1) 3(2) 3(3) 3(4) 3(5) 3(6) 3(7) 3(8) 3(9) 3(10) 3(11) 3(12)

2(10) 2(11) 2(12) 2(1) 2(2) 2(3) 2(4) 2(5) 2(6) 2(7) 2(8) 2(9) 2(10) 2(11) 2(12)

1(10) 1(11) 1(12)

Key:

X(Y) = Panel X interviewed in month Y

Example: 2(10) = Panel 2 is interviewed in October of Year T and in Year T+1

 

 
Redesign Options for the Consumer Expenditure Survey 55 

Data might also be collected for each respondent from retailers who have loyalty card programs. 

However, these expenditure data would not be collected for food expenditures in the Quarterly 

Interview survey; food expenditure data would be collected only in the Diary survey.

By increasing the focus on records, the goal is to reduce the overall difficulty of the data collection 

for the individual respondent. In addition, it is to reduce the length of the interview. The (untested) 

assumption is that with greater use of records, the overall interview would be shorter. 

Contacts and Interviewing. Table 12 summarizes the data collection. In the first year, there would 

be three telephone contacts between two in-person contacts. The first in-person contact initiates the 

procedures. The respondent will be asked for consents to release records, given instructions on the 

procedures for record collection, and participate in a bounding interview. Two weeks, 1 month, and 

2 months after the contact will be telephone calls to check on the respondent’s progress and to 

encourage the respondents to continue providing data. During the 3-month in-person contact, the 

interviewer will review all records and documentation that have been collected and administer a 

recall interview for the 3-month period. 

Twelve months after the initial contact, a packet will be mailed to the CU to re-orient the 

respondent to the data collection tasks. The interviewer will follow this up with a telephone call to 

confirm the procedures and conduct a bounding interview. Two weeks later, 1 month later (month 

13), and 2 months later (month 14), the respondents will receive reminder phone calls. At month 15, 

an in-person contact will occur using the same procedures as the 3-month in-person contact. 

First in-Person Interview. The first interview with the household would be completed as a 

personal visit. During this visit, the interviewer would identify a respondent in the CU who was 

willing to report on all expenditures for everyone in the household. The respondents would tell the 

interviewers whether they were willing and able to download the data files for their checking, credit 

card, or other accounts. 

The respondents would be asked to sign two consent forms. One would allow survey staff to obtain 

expenditure data directly from the respondents’ utility and mortgage companies. These expenditure 

data would not be collected from the respondents who sign this consent. The second consent would 

allow survey staff to use the respondents’ loyalty card numbers to obtain expenditure data from the 

retailers that issued the loyalty cards.
Redesign Options for the Consumer Expenditure Survey 56 

Table 12. Quarterly Interview survey schedule and procedures for sampled CUs

Initial interview - In-person interview 

 Obtain consents

 Determine data collection methods, electronic or paper

 Provide data collection instructions

 Conduct bounding interview

2 weeks, Month 1 and Month 2 after initial interview – Telephone contact 

 Review respondent’s provision of data, electronic or paper

 Encourage respondent to provide data

3 months after initial interview – In-person contact 

 Review records collected

 Conduct recall Interview

12 months after initial interview – Telephone/In person 

 Mail instruction packet beforehand

 Followup Telephone call to orient Respondent and conduct bounding interview

 If household has changed, use initial contact protocol

12 months plus 2 weeks, 13 months, 14 months after initial interview – Telephone contact 

 Review respondent’s provision of data, electronic or paper

 Encourage respondent to provide data

15 months after initial interview – In-person interview 

 Review records collected

 Conduct recall Interview

The interviewer would then administer the Quarterly Interview survey, to collect information on 

recent purchases. The last month might be a suitable reference period. In this way, the first interview 

will serve as a bounding interview for the second interview.

The interviewers would instruct the respondents on the data collection procedures. All respondents 

would be instructed to save receipts for all their expenditures, except food and alcoholic beverages. 

They would also be instructed to write a note for all expenditures for which they had no receipt. 

They would receive short forms to use for those notes. 

Additional instructions would vary, depending upon the individual respondent’s ability and 

willingness to download data files for their checking, credit card, and other relevant accounts. 

Respondents who will download these files would receive instructions similar to the instructions 

given to the Diary survey respondents who will download these files. The procedures for the Diary 

survey are explained above but will be summarized here.
Redesign Options for the Consumer Expenditure Survey 57 

The respondents would be asked to download their credit card, checking, and other account data 

files and email them to the central repository at least once per week. They would also be asked to 

keep their receipts from all purchases except food. They would be given a small receipt scanner and 

software developed specially for the CE program. The respondents would scan their receipts and 

email the scan files to the central repository at least once per week. They would also scan the notes 

that they created for purchases with no receipts, and email the scan files to the central repository. 

They would be given special software to automate all these procedures.

The CE system would derive the individual expenditure items from the receipts. It would use OCR 

software to turn the scanned receipts into text. Software created especially for the CE program 

would extract from this text the description and price of each individual expenditure item. The CE 

system would match the expenditure data in the scanned receipts with expenditure data from the 

downloaded credit card, checking, and other account files. 

The respondents would periodically complete a web questionnaire. The web questionnaire would 

ask about each individual item purchased. The questionnaire would ask details needed by the CE 

program such as whether the expenditure was for someone outside the household. 

Some respondents may be unwilling or unable to download financial files, or to scan receipts, or to 

complete a web survey. These respondents would be given envelopes to store their paper receipts 

and completed forms for purchases with no receipts. The envelopes will carry a postage prepaid 

frank, and be pre-addressed to the central repository. The respondents would be asked to mail an 

envelope on a regular schedule. CE staff would then receive the envelope and scan the receipts. The 

respondents would also be asked to mail in photocopies of their monthly statements for their credit 

card, checking, and other accounts. CE staff would enter those data as well. 

Interim Contacts. Field representatives would monitor the activity of each respondent. They would 

determine whether each respondent was scanning receipts and forms and emailing the scan files to 

the central repository, or mailing envelopes with paper receipts and forms. The field representatives 

will call the respondents two weeks after the first interview to ask if the respondent had any 

questions or concerns. If the respondent has not been sending data to the central repository, or 

appears to be sending too little data, the field representative will determine whether the respondent 

is encountering any problems or is simply remiss. The field representative would try to address any 

issues that the respondent may be encountering. 
Redesign Options for the Consumer Expenditure Survey 58 

The field representatives would telephone each respondent three times: 2 weeks, 1 month, and 2 

months after the first interview. Again the field representatives would attempt to ensure that the 

respondents remained motivated to provide data for their households. They would ask the 

respondents about any potential problems. They would check the repository to determine which 

respondents had stopped providing data, or seemed to provide data only sporadically. The field 

representatives would try to remedy any issues during these telephone calls.

Second in-Person Interview. During the second in-person interview, conducted 3 months after 

the first in-person interview, the field interviewer will review the receipts and forms that the 

respondents sent to the repository, and, if the respondent used the Internet, the data that the 

respondent provided through the web questionnaires. The interviewer would ask the respondent to 

provide information that may have been omitted in the prior web questionnaires for any reason, 

such as the respondent’s failing to know at the time about an expenditure by another member of the 

household, or the respondent’s neglecting to obtain or scan a receipt. If the respondents did not 

complete any web questionnaires or had provided few receipts and data files, the interviewer would 

administer a recall interview.

The interviewer’s questions would take into account the reference period for each kind of 

expenditure. The interviewers would ask about a 1-month, 3-month, or 12-month period, depending 

on the nature of the expenditure. The length of this interview would depend on how much 

information the respondent had sent to the central repository. For example, if the respondent had 

already sent in information for certain types of expenditures, such as regular mortgage payments, 

utility bills, health club memberships, health insurance, the interviewer would not need to ask 

questions about these expenditures. The interviewer would ask about expenditures which the 

respondent may not have exhaustively reported. 

The interviewer would encourage the respondent to use records as a memory aid during this 

interview. For example, some respondents may have receipts on hand that they never sent to the 

central repository. Some respondents who did not download their financial files for their credit card, 

checking or other accounts may have hard-copy statements for those accounts. 

Other memory aids should be developed as the structure of the interview is determined. An event 

history calendar could be used, at least for those respondents who have not provided much 

information to the central repository. All materials should be designed to facilitate the interview. The 

material shown to respondents should be optimized for memory search. For example, research using 

eye-tracking and response latencies (Redline et al., 2009) has found grouping responses within major 
Redesign Options for the Consumer Expenditure Survey 59 

subheadings, such as on the current CE Information Cards, can lead to confusion. The formatting 

for the visual aids should be tested so that it can help respondents provide information to the 

interviewers. Novel types of displays should be tested, such as pictures of items, which might be 

easier to coordinate with interviewer questions.

Contacted at Month 12. This contact would initiate a 3-month period in which the respondent 

would report data. Prior to the interview, a field representative would mail the respondent a package 

that included the instructions and materials for the survey. If this is the same CU as the prior 

contact, a telephone call would be made by the field representative to re-acquaint the respondent 

with the survey procedures. The field interviewer would remind the respondent to provide electronic 

records. The field interviewer would attempt to elicit cooperation from respondents who were not 

providing data diligently. The interviewer would conduct a brief recall interview which would serve 

as a bounding interview. 

An in-person interview would be conducted for households that have changed since the first 

interview. The in-person interview is required in that situation because the interviewer must obtain 

consents, provide instructions and conduct the bounding interview. Otherwise, this interview would 

be conducted by telephone. 

Interim Contacts and Interview at Month 15. The methods for the interim contacts and the recall 

interview at month 15 would repeat the same procedures as conducted 12 months earlier. 

Number of Respondents. We are aware of no studies that examined the feasibility of using 

multiple respondents in each household in the Quarterly Interview survey. Prior research, described 

above, suggests that the Diary survey, with its short time frame, could benefit from a multiplerespondent design. Further research is needed to determine whether a multiple-respondent design is 

cost-effective for the Quarterly Interview survey.

If the decision is made to stay with a single-respondent design, techniques could still be developed 

to improve data quality. Most importantly, respondents could be encouraged to speak with other 

household members daily to learn about their expenditures. Each household member could receive a 

box or an envelope for storing receipts or forms documenting purchases with no receipts. 

Incentive. We recommend that respondent incentives in the Quarterly Interview survey be similar 

to those for the Diary survey. Both a monetary and a non-monetary incentive should be provided. 

The monetary incentive would be $50 for each of the two recall interviews with the CU respondent. 
Redesign Options for the Consumer Expenditure Survey 60 

A smaller incentive, perhaps $5, would be given to other household members to provide receipts 

and other documentation of purchases. The non-monetary incentive would be a financial report on 

the expenses of the household as described above in the section on the Diary survey. 

Monitoring Interviewers. The success of the Quarterly Interview survey depends in large measure 

on the care with which the interviewers collect the data. In particular, the interviewers need to probe 

for detailed information when necessary. Some respondents may tend to prematurely decide that 

they have no more data to report (Biderman et al., 1986). Appropriate interviewing methods, such as 

the use of extensive cueing can combat this tendency. Interviewers must have the skill to balance the 

need to probe for details and the need to avoid burdening the respondents. 

Past research suggests that when supervisors monitor interviewers’ activities, the interviewers are 

less likely to take shortcuts and more likely to attempt to elicit survey data thoroughly. Two field 

experiments involving the National Crime Victimization Survey (NCVS) suggested that centralized 

telephone interviewing can produce a higher number of crime victimization reports than 

decentralized field interviews can produce (Hubble and Wilder, 1988; Biderman et al., 1986). The 

reason for this effect may be that the telephone interviewers’ data collection activities were 

monitored. 

An important component of the CE redesign should be to institute methods to train, monitor and 

provide feedback to interviewers on an ongoing basis. Dijkstra et. al. (2008) discussed the 

importance of these aspects of the design when administering the SIPP Event History Calendar. The 

monitoring can be done through use of paradata from the computerized interview (e.g., section 

timings) and the use of Computer Audio Recorded Interviews (CARI). The Census Bureau is now 

instituting CARI within many of their household surveys. With CARI, entire interviews or just 

samples of interviews can be recorded. Supervisors later review these recordings to check 

interviewer practices and provide feedback on performance. 

Costs of Proposed Design 

For the Quarterly Interview component, Table 9 provides two variants, the “one respondent per CE 

unit” model like the current design, and an alternative that collects data directly from multiple 

people in the unit. Tables 13 and 14 provide the assumptions behind the field data collection. 

Table 15 provides the costs of collecting administrative records.
Redesign Options for the Consumer Expenditure Survey 61 

 

Table 13. Summary of Quarterly Interview cost per year

 

A B C D E F G H I 

Total 

interview cost 

Quarters 

of 

completed 

CE units 

Cost/ 

completed 

CE unit 

Number of 

completed 

interviews 

Cost/ 

completed 

interview 

Administrative 

records cost 

Admin. 

records 

cost/ 

CE unit 

Interview plus 

records cost 

Interview 

plus 

records 

cost/ 

CE unit 

 A/B A/D F/B A+F H/B 

Current design 

One respondent per 

CE unit

$17,048,783 29,000 $588 35,843 $476 NA NA $17,048,783 $588

Proposed design 

If one respondent 

per CE Unit

$24,685,164 36,000 $686 72,074 $342 $10,192,920 $283 $34,878,084 $969

If multiple 

responders per

CE unit*

$43,199,036 36,000 $1,200 115,148 $375 $13,250,796 $368 $56,449,832 $1,568

*Assume interview costs are twice the cost of one respondent per CE unit, admin. records costs are 1.3 times the cost of one respondent per CE unit.
Redesign Options for the Consumer Expenditure Survey 62 

 

Table 14. Quarterly Interview costs by mode (assume one respondent per CE unit)

 

Current 

design 

 

Panel 1 

Proposed Quarterly Interview design 

Proposed Quarterly Interview design 

Full implementation, all panels 

Steady state (Data for 7,000 CE Units/Quarter) 

 

$/Interview 

 

 

Cost, all 

quarters 

Cost per 

quarter N PV only T only 

Cost, all 

quarters 

Cost per 

quarter N 

$/Int 

G/H 

Cost, all 

quarters 

Cost per 

quarter N 

$/Int 

K/L 

$17,048,783 $12,009,859 $24,685,164

Quarter 1 $3,892,024 7,316 $532 $7,850,794 7,316 $1,073 $6,171,291 7,316 $844

Detail: Bounding Interview at 

0 weeks (PV)

$3,892,024 7,316 $532 $3,892,024 7,316 $532 $2,479,030 7,316 $339

Prompt 1 at 2 wks (T) $177,673 7,316 $24 $88,836 3,658 $24

Prompt 2 at 4 wks (T) $177,673 7,316 $ 24 $88,836 3,658 $24

Prompt 3 at 8 wks (T) $177,673 7,316 $24 $88,836 3,658 $24

Recall at 13 weeks

(PV/T currently, PV proposed)

$3,417,737 7,092 $298 $146 $3,425,751 7,092 $483 $3,425,751 7,092 $418

Quarter 2 at 26 weeks (PV/T) $3,276,573 7,101 $298 $146 $6,171,291 7,316 $844

$2,479,030 7,316 $339

$88,836 3,658 $24

$88,836 3,658 $24

$88,836 3,658 $24

$3,425,751 7,092 $418

Quarter 3 at 39 weeks (PV/T) $3,231,239 7,221 $298 $146 NA NA NA $6,171,291 7,316 $844

$2,479,030 7,316 $339

$ 88,836 3,658 $24

$88,836 3,658 $24

$88,836 3,658 $24

$3,425,751 7,092 $418
Redesign Options for the Consumer Expenditure Survey 63 

 

Table 14. Quarterly Interview costs by mode (assume one respondent per CE unit) (continued)

 

Current 

design 

 

Panel 1 

Proposed Quarterly Interview design 

Proposed Quarterly Interview design 

Full implementation, all panels 

Steady state (Data for 7,000 CE Units/Quarter) 

 

$/Interview 

 

 

Cost, all 

quarters 

Cost per 

quarter N PV only T only 

Cost, all 

quarters 

Cost per 

quarter N 

$/Int 

G/H 

Cost, all 

quarters 

Cost per 

quarter N 

$/Int 

K/L 

Quarter 4 $3,231,239 7,221 $298 $146 $4,159,065 7,221 $576 $6,171,291 7,316 $844

Recall Interview at 52 weeks 

(PV/T currently) @

$3,231,239 7,221 $298 $146 $2,479,030 7,316 $339

Bounding Interview at 39 

weeks (T proposed)

$— $841,755 5,777 $146 $88,836 3,658 $24

Bounding at 39 wks

(PV proposed, new CE units) 

$— $768,297 1,444 $532 $88,836 3,658 $24

Recall Interview at 52 weeks 

(PV proposed) @

$2,549,013 7,221 $353 $88,836 3,658 $24

$3,425,751 7,092 $418
Redesign Options for the Consumer Expenditure Survey 64 

 

Table 15. Administrative records cost for Quarterly Interview

 

2009 MEPS MPC Proposed CE design for Quarterly Interview 

 

 

Hospitals Office-based doctors Large organizations Small organizations Sum 

Interviewing $2,339,952 $1,172,293

Abstraction $1,710,737 $631,824

Other $957,298 $510,209

Total $5,007,987 $2,314,326 $8,615,320 $1,577,600 $10,192,920

Completes (providers or vendors) 4,720 8,501 16,240 5,800

Cost per provider or vendor $1,061 $272 $531 $272

HH Reporting Units 8,500 8,500 29,000 29,000

Provider or Vendor 

Completes/Household

Reporting Unit 0.56 1.00 0.56 0.20
Redesign Options for the Consumer Expenditure Survey 65 

The total cost of the proposed design is approximately two times as expensive as the current design 

($17 million vs. $34 million). Approximately $7 million of the increase is associated with the 

additional effort to collect the quarterly data from respondents. The proposed design requires three 

in-person contacts and a telephone contact to collect two quarters of data. To collect four quarters 

of data, the design then needs six personal visits and two telephone interviews. The current design 

uses 5 personal visits to collect the same number of collection quarters. In addition, two of the six 

in-person contacts for the proposed design are initial visits to the household, which are more 

expensive than follow-up visits. Only one of the five interviews for the current design is an initial 

visit. Finally, for the current design, there are interim contacts made by telephone during each 

collection quarter, which are not done for the current design. 

The remaining additional cost of $10 million is from the administrative record collection. These 

costs could be cut considerably if the collection was restricted to utilities (e.g., gas, water, electricity).

This is discussed further in the last section of this chapter when considering variations in the 

proposed designs. 

In addition to the caveats described for the Diary costs, several others should be mentioned for the 

Quarterly Interview survey. The current design for the Quarterly Interview is multi-mode. Almost all 

of the Quarter 1 interviews are conducted by means of a personal visit or a visit in combination with 

some telephone interviewing. But in subsequent quarters many cases are completed through 

telephone interviews only, or through a combination of phone and personal visit. Therefore, it is 

very difficult to determine current design costs by mode. In the proposed design, we attempt to 

avoid this problem by assuming that all CE units provide data either entirely in person

(as in Quarter 1) or entirely by telephone or by mail (as in the proposed Quarter 4 data collection). 

Census cost data for interviews conducted only in personal visits and for interviews conducted only 

by telephone are used to estimate costs for the proposed design. 

Sample Size and Precision 

Assessing the implications of the above costs for the sample sizes of the Quarterly Interview survey 

is not as straightforward as for the Diary survey. Whereas the sample design for the Diary is very 

similar between the proposed and current surveys, the equivalent Interview surveys are not. 

Consequently, to evaluate the implications of the above recommendations an analysis was conducted 

that simulated the proposed Quarterly Interview survey design. It was assumed that the survey 
Redesign Options for the Consumer Expenditure Survey 66 

would produce annual estimates for the categories published by BLS (see http://www.bls.gov/cex

/2009/stnderror/age.pdf). The expenditures used in the simulation were selected based on current 

practice. The decision on whether to use the Interview or Diary survey for estimates is based on the 

proportion of CUs that report the expenditure and the reported dollar amounts of the expenditure. 

The expenditure item has to be reported frequently enough on the survey to yield a reliable estimate. 

If the item is not purchased very often, then the Diary is not likely to be very reliable given the short 

reference period. If respondents tend to forget the expenditure, the Quarterly Interview survey may 

not be reliable. When differences in reliability are not as much of an issue, the decision on which 

survey to use is based on the assumption that the source yielding the higher expenditure amount is 

preferred. 

For example, virtually all of the food and alcohol expenditure estimates are based on data from the 

Diary survey (see Appendix A for assignments in 2009). All estimates for housing expenditures are 

based on data from the Quarterly Interview survey. However, for a number of domains, the 

estimates for some expenditures use data from the Quarterly Interview survey and the estimates for 

others use data from the Diary survey. For example, estimates for housewares expenditures are 

based on data from both the Quarterly Interview (e.g., plastic dinnerware, flatware) and the Diary 

survey (e.g., china and glassware).

The expenditures used to simulate precision are shown in Table 16. These are the lowest level 

published categories that are exclusively or primarily taken from the current Quarterly Interview 

survey. The analysis used a public use version of the CES 2009 data set, which included interview 

data during the four quarters of 2009 and the first quarter of 2010. The analysis compared the 

estimated variance under the current design, 2ˆσ tot , to estimates of variance for the alternative design, 

simulated using the same data set (see Appendix B Table 2 for the coding of the expenditure 

categories). 

The first step was to identify the contribution of between-PSU variance to the overall variance. The 

scope of the research concerns the effect of redesigning the sample within the sampled PSUs, while 

holding the random selection of PSUs fixed.2 Because the CES is essentially an unclustered sample, 

the specification to for variance estimation was changed using software (SUDAAN) to treat each 

consumer unit as a cluster, but to assume a simple random sample of consumer units had been 

selected. The calculation recognized that consumer units could contribute up to the annual results 

up to four times. Because the calculation involved the many thousands of observed consumer units 

 

2 See Appendix B for more details on the methods used for the simulation.
Redesign Options for the Consumer Expenditure Survey 67 

rather than the 44 replicates, the calculation of within variance is much less subject to random error. 

Because the same data and weights were used, the estimates of expenditures were identical to the 

first calculation but reduced estimates of the standard errors, 2ˆσ wc , for all but 2 of the 53 estimates. 

The between variance, 2ˆσ b , was estimated from the familiar decomposition for two-stage samples,

2 22 σ σσ tot b wc = +

and substituted the estimated values for 2ˆσ tot and 2ˆσ wc into this equation, setting 2ˆσ b = 0 in the two 

exceptional cases.

Table 16. Expenditure types used to simulate proposed design for the Quarterly Interview 

survey by lowest level publication group

Expenditure type Expenditure type 

Mortgage interest and charges Cars and trucks, used

Property taxes Other vehicles

Maintenance, repairs, insurance, other expenses Gasoline and motor oil

Rented dwellings Vehicle finance charges

Other lodging Vehicle, Maintenance and repairs

Natural gas Vehicle insurance

Electricity Vehicle rental, leases, licenses, and other charges

Fuel oil and other fuels Airline fares

Telephone services Public transportation except airfares

Water and other public services Health insurance

Personal services Medical services

Other household expenses Prescription drugs

Household textiles Medical supplies

Furniture Fees and admissions

Floor coverings Audio and visual equipment and services

Major appliances Pets, toys, hobbies, and playground equipment

Small appliances, miscellaneous housewares Recreational vehicle purchases

Miscellaneous household equipment Other entertainment supplies, equipment, and services

Apparel and services, Men, 16 and over Personal care products and services

Apparel and services, Boys, 2 to 15 Reading

Apparel and services, Women, 16 and over Tuition

Apparel and services, Girls, 2 to 15 Other education

Apparel and services, Children under 2 Tobacco products and smoking supplies

Footwear Miscellaneous

Other apparel products and services Cash contributions

Cars and trucks, new Life and other personal insurance

Pensions and Social Security

The first three columns of Table 17 provides the expenditure estimates, the estimated standard 

errors for the current design, 2 1/2 ( ) ˆσ tot and the percent of the total variance due to between-PSU 

variance for expenditures using a 3-month recall period. For most expenditures (e.g., vehicle 

insurance, footwear), this percentage is under 50 percent indicating that the within-PSU variance 
Redesign Options for the Consumer Expenditure Survey 68 

contributes most of the variance, so that any changes in the survey design within PSUs can have 

significant effects on the total variance. There are a few items with significant between PSU 

variance, including electricity, natural gas, fuel oil and water. For these items, the proposed changes 

will have limited effects on the total variance.

Table 17. Simulation of effects on within PSU variation of the redesigned Quarterly Interview 

survey for 1-, 3-, and 12-month reference periods by expense categories

Expense category 

2009 

estimate 

Standard 

error 

% 

between 

PSU 

variation 

% reduction in 

within PSU variance 

1 

month 

recall 

3 

month 

recall 

12 

month 

recall 

Mortgage interest and charges 3593.71 75.0 28 54 58 56

Property taxes 1809.44 31.1 45 57 60 56

Maintenance, repairs, insurance, other 

expenses

1138.71 43.1 33 -67 19 56

Rented dwellings 2854.51 50.7 10 52 57 56

Other lodging 669.01 30.2 27 9 49 56

Natural gas 483.4 16.8 85 37 52 56

Electricity 1376.65 29.2 89 44 53 56

Fuel oil and other fuels 141.46 9.2 68 -28 43 56

Telephone services 1161.76 12.1 56 48 54 56

Water and other public services 480.79 10.5 76 0 51 56

Personal services 389.44 20.2 0 53 45 56

Other household expenses 616.34 14.1 41 10 44 56

Household textiles 84.55 3.2 31 -141 14 56

Furniture 341.22 14.5 12 -191 14 56

Floor coverings 30.31 3.3 25 -241 1 56

Major appliances 188.77 8.8 29 -180 4 56

Small appliances, miscellaneous 

housewares

58.42 2.7 24 -427 10 56

Miscellaneous household equipment 461.1 14.8 40 -99 16 56

Apparel and services, Men, 16 and over 199.7 8.7 40 4 16 56

Apparel and services, Boys, 2 to 15 61.11 2.1 17 -100 34 56

Apparel and services, Women, 16 and 

over

336.41 8.8 47 -86 37 56

Apparel and services, Girls, 2 to 15 77.86 2.8 23 -114 37 56

Apparel and services, Children under 2 70.86 2.8 36 -25 44 56

Footwear 147.32 4.3 59 -116 23 56

Other apparel products and services 229.01 11.6 5 -249 29 56

Cars and trucks, new 1297.15 83.8 19 -275 0 56

Cars and trucks, used 1304.35 70.6 23 -131 6 56

Other vehicles 55.45 11.7 11 -221 3 56

Gasoline and motor oil 1986.4 20.6 40 44 50 56

Vehicle finance charges 281.01 8.2 35 59 62 56

Vehicle, maintenance and repairs 682.29 15.6 41 -135 20 56

Vehicle insurance 883.86 20.8 76 -138 38 56

Vehicle rental, leases, licenses, and 

other charges

446.12 16.0 42 18 53 56

Airline fares 300.92 11.2 18 -130 21 56
Redesign Options for the Consumer Expenditure Survey 69 

Table 17. Simulation of effects on within PSU variation of the redesigned Quarterly Interview 

survey for 1-, 3-, and 12-month reference periods by expense categories (continued)

Expense category 

2009 

estimate 

Standard 

error 

% 

between 

PSU 

variation 

% reduction in 

within PSU variance 

1 

month 

recall 

3 

month 

recall 

12 

month 

recall 

Public transportation except airfares 169.14 7.7 34 -80 22 56

Health insurance 1784.3 26.9 35 41 53 56

Medical services 739.89 25.7 49 -71 26 56

Prescription drugs 361.72 10.6 45 29 44 56

Medical supplies 86.9 4.8 19 -317 5 56

Fees and admissions 602.05 18.5 47 6 42 56

Audio and visual equipment and 

services

955.3 14.7 41 -35 20 56

Pets, toys, hobbies, and playground 

equipment

442.18 13.4 31 -72 45 56

Recreational vehicle purchases 160.1 30.2 10 -357 1 56

Other entertainment supplies, 

equipment, and services

209.53 9.6 33 -78 9 56

Personal care products and services 300.71 6.2 55 44 50 56

Reading 108.99 2.9 51 38 44 56

Tuition 886.87 40.0 0 -101 23 56

Other education 131.85 5.5 21 -72 24 56

Tobacco products and smoking supplies 377.64 10.6 23 47 48 56

Miscellaneous 747.07 31.4 2 -48 29 56

Cash contributions 1723.08 84.4 55 9 25 56

Life and other personal insurance 309.03 12.8 40 -139 37 56

Pensions and Social Security 5163.74 81.0 37 55 59 56

* Negative number indicates an increase in variance.

For all expenditure categories, the analysis simulated the effect of interviewing households for 1-, 3- 

and 12-month reference periods (see last three columns in Table 17). Examining the estimates for a 

3 month reference period indicates the effects of eliminating the four-interview panel design, with 

no change in the reference period. To simulate the effect of interviewing households for one 

3-month period, we changed the specification for the variance software to treat each observation in 

the 2009 data set as independent. This specification can be said to be unclustered. Again, the same 

estimates of expenditures for each group were obtained, but an estimated standard error, 2ˆσ wu , 

smaller than 2ˆσ wc . (In one case, the estimated percent reduction rounds to 0.) This represents the 

estimated reductions in variance from switching to the new design but using the current 3-month 

recall for all expenditures. We estimated the proportional reduction in within variance using 

22 2

1

ˆ ( )/ ˆˆ ˆ R = − σσ σ wc wu wc
Redesign Options for the Consumer Expenditure Survey 70 

These results are shown in the fifth column of Table 17. The within-PSU variance is significantly 

reduced in all cases. The median change across all expenditure categories is 37 percent. 

We next considered the effect of changing the reference periods. This is provided in the fourth and 

sixth columns of Table 17. For a 12-month recall period it is possible to derive a theoretical 

expectation for the reduction in the within variance through a relatively simple argument. For any 

category in which 12-month recall is implemented, a single interview would provide the same 

information as available currently under four cumulative interviews. With respect to within variance, 

this change would multiply the effective sample size by a factor of 4. This simple argument implies a 

75 percent reduction in the within variance.

The argument must be refined, however, because the assumed data for a given year would not be 

complete until the end of the fourth quarter of the following year. For example, with a 12-month 

reference period, respondents in 2011 can contribute to 2010 as late as November of year 2011. To 

prevent a change in schedule, the estimation must depend only on the first quarter of the following 

year. For the January of the current year, there will be reports from all 12 possible interview months 

up through January of the next year. Similarly, all 12 months are available for February and March, 

but April is reduced to 11, May to 10, up to only 3 for December. Thus the average of

(1/12, 1/12, 1/12, 1/11, ..., 1/4, 1/3), .14749, should be compared to 1/12, .08333. Thus, the 

variance, instead of .25 times the current variance, should be (.14749/.08333)*.25 = .4424, or a 

56 percent reduction in variance instead of 75 percent. 

In some cases, the estimated values for the reduction in the 3-month period exceed the theoretical 

value reported for 12-month recall groups, but never by a large amount. The estimates are affected 

by sampling error, but the large number of degrees of freedom used in the calculation provides a 

greater measure of stability than is frequently seen when analyzing components of sampling error.

Within the 12-month group there are distinct patterns according to the type of expense. Those 

expenditures that are done on a regular basis, such as utilities, health insurance, vehicle finance 

charges, there is practically no difference between the 3- and 12-month recall periods. This indicates 

that for these items, eliminating repeated interviewing during the calendar year provides most of the 

gains in precision. There is very little gain from extending the reference period to 12 months. As 

noted above, the design would target these types of expenditures for collection directly from utility 

companies, which makes the reference period less relevant as well. This pattern does not hold for 

items that are not purchased at high frequency (e.g., floor coverings; major appliances; vehicles) or 
Redesign Options for the Consumer Expenditure Survey 71 

on a less regular basis (tuition; airline fares). In these cases, the 12-month period has a significant 

impact on the within-PSU variance.

The effect of a 1-month recall period was estimated using expenditures reported for the month 

preceding the interview. In this case, the estimated expenditures changed as well as the estimated 

standard errors. We again computed the unclustered variance for this design and estimated the 

(signed) reduction in variance by 

22 2

2 1 ˆ ( )/ ˆˆ ˆ R = − σσ σ wc wu wc

Unlike the other estimates, there are significant increases in the variance, as indicated by the negative 

signs in the figure. Some of these items could have reference periods for much longer periods of 

time (e.g., auto sales).3

 There a number of items, however, that are negative and could not easily be 

moved to a 1-month or a 12-month period without significant loss in precision. On the other hand, 

there are items that have positive values, some of which are greater than 20 percent, some greater 

than 40 percent. These items should be considered when changing to a 1-month reference period. 

We next translated the within-PSU reductions to reductions in total variance. These are shown in 

Figures 4–6, respectively, for each of the three different reference periods (see Appendix C for 

detailed data). Total variance reductions were calculated using the values of 2 Rˆ and the values of the 

between variance. For example, even though the theoretical value for 2 Rˆ of 56 percent is reported 

for 12-month recall groups, the effect on total variance is lessened when between-PSU variance is 

taken into account. For purposes of cost comparisons, we also calculated the effect of reducing the 

within-PSU sample sizes by 20 percent or 40 percent, not to propose these specific reductions, but 

to offer a wide range for consideration. 

For a 3-month reference period, there are significant reductions in total variance across most 

expenditures. The median is 35 percent. Reducing the sample size by 20 percent brings variances 

close to the current design (median = 9%). Cutting as much as 40 results in about half of the 

expenditures increasing in variance and half still maintaining a reduction in variance (median = -4%). 

 

3 See Appendix C, Table C3, for the results for specific types of expenditures.
Redesign Options for the Consumer Expenditure Survey 72 

Figure 4. Percent reduction in sampling variance for a 3-month reference period

Figure 5. Percent reduction in sampling variance for a 12-month reference period
Redesign Options for the Consumer Expenditure Survey 73 

Figure 6. Percent reduction in sampling variance for 1-month reference period

As would be expected, switching to a 12-month period shows significant gains in precision, with a 

median of 36 percent with current sample sizes. Even with a 40 percent sample cut, most expense 

categories show positive reductions (median =18). The pattern is the opposite for a 1-month period. 

This results in significant losses in precision. 

These results raise a question of whether a 12-month period provides net advantages, at least for the 

precision of the estimates. Switching to a 12-month period does not have a significant effect on 

variance for the regular expenditures examined in the present analysis (e.g., utilities). For these, 

almost all of the benefit of the proposed design is from altering the panel component of the current 

design. However, this does suggest that collection of these data only needs to occur for half of the 

interviews, if a 12-month period is to be used. For less frequent purchases, it does significantly 

increase precision. If the combination of the use of records and an enhanced recall interview yields 

accurate reports, a 12-month period could be a benefit. However, using a 3-month period would still 

have significant savings in terms of variance. 

The above analysis could not simulate how the measurement would change when shifting to 1- or 

12-month reference periods. For the 1-month simulation, the most recent month was used from a 3-

month recall period. This reflects both possible omissions of expenditures, as well as telescoping. 
Redesign Options for the Consumer Expenditure Survey 74 

Presumably asking for reports over a 1-month period would reduce both of these types of errors. 

Similarly, asking for recall over a 12-month period would likely increase measurement error, all other 

things being equal. Enhanced use of records and recall procedures would seek to improve this 

measurement. 

Discussion 

The goals of the proposed redesign of the Diary and Quarterly Interview surveys, as discussed in 

Chapter 1, are as follows: (1) reducing measurement error, (2) reducing burden and (3) increasing 

flexibility. The data requirements have to do with addressing the needs of the CPI (Casey, 2010) and 

the larger CE user community (Henderson et al., 2011).

Goals of the Redesign. The recommended procedures for the Diary and the Quarterly Interview 

survey address the goals of the redesign in multiple ways. For example, the proposed use of 

electronic and paper records could help address the interrelated goals of reducing measurement 

error and respondent burden. When the data are collected from records, respondents are relieved of 

the task of trying to remember their expenditures. Moreover, the records are likely to be more 

accurate than the respondents’ recollections. The use of incentives may significantly boost the 

respondents’ willingness to keep the appropriate records. The regular reminders by the interviewer 

should also improve respondent compliance. 

We propose using multiple respondents in the Diary survey as a way to reduce respondent burden 

and reduce measurement error. Using multiple respondents, however, has a significant price tag. We 

recommend that BLS conduct a field experiment to evaluate the use of multiple respondents. 

However, even if the idea of multiple respondents is too expensive to implement, we still 

recommend that BLS develop procedures to elicit greater participation in the household. In the end, 

analysis will have to weigh the cost of this design against the decreases in measurement error. Total 

survey error models should be developed to assist in understanding the tradeoffs between reduction 

in error against reductions in the sample size that would be implemented to pay for the procedure. 

We recommend reducing respondent burden in the Quarterly Interview survey by cutting the 

number of waves a CU is in sample from four to two, as well as increasing the time between waves. 

While this will increase data collection costs, it also significantly increases the precision on the 

annual estimates. As noted in the Quarterly Interview precision section, the reductions are 
Redesign Options for the Consumer Expenditure Survey 75 

substantial. Further refinement of both the cost and simulation model discussed above is needed. 

The cost models were based on aggregate data for the current design, which hampered our ability to 

refine costs. In addition, further information is needed how the costs and reductions in sample size 

relate to one another. 

For the Quarterly Interview survey, we propose collecting administrative data from utility 

companies, apartment lessors, and other sources. These data would substitute for respondent 

reports, reducing measurement error and respondent burden. Of course, collecting administrative 

data also has a significant cost associated with it. Unlike the elimination of two-panel waves, there is 

no clear cost offset to this component. An important evaluation question is how effective this 

component to the survey is to reduce measurement error with respect to total survey error. By 

investing resources in the administrative record followup, is the survey reducing measurement error 

more than it is increasing variability due to sampling? It is difficult to know without more research. 

When viewed as a single survey program, the redesigned procedures address flexibility in several 

ways. The redesign allows respondents to use a number of different data collection methods that can 

be tailored to the respondent’s daily routines. The challenge will be to develop a procedure that takes 

advantage of this flexibility without making the task overly complicated or to give respondents a way 

to avoid completing the task. The electronic record component is largely a passive method which 

only requires respondents to download files that have some basic information about their 

transactions. If a respondent agrees only to this, there is potential that significant gains can be made 

with respect to reducing measurement error and burden. As noted in Chapter 3, the electronic 

records cover a very large proportion of all expenditures—potentially over 70 percent. In our 

proposed redesign, the respondents are asked to download financial data files. They are also asked to 

save paper receipts. If they do not adequately download the files or keep the receipts, the interviewer 

conducts a recall interview to capture the needed data.

Our proposed redesign also offers the respondents flexibility. At some point, there may not be a 

need for two surveys. The two may merge into a single collection that primarily relies on relatively

passive methods that can address the data requirements of the CE program. A merged survey was 

considered when developing the redesign options. This was rejected because it was not deemed 

feasible for the 4 to 5 year time frame that the redesign is targeting. But it would not be difficult to 

merge the two collections into a single survey if that was warranted.

Addressing CE Data Requirements. The CE must generate information in a way that is usable 

for the CPI. The expenditure data and demographics must be at the appropriate level of detail, 
Redesign Options for the Consumer Expenditure Survey 76 

geographical distribution, and periodicity (Casey, 2010). These data have to be produced in a timely 

way and with sufficient sample size to generate precise estimates. The suggested redesign procedures 

were structured to maintain the current expenditure categories generated around the same timeliness 

as the current CE. We have assumed the same sample design as in the current survey. Consequently 

the level of geographic detail needed keeps the status quo. Similarly, the discussion above has 

provided information on how the designs might affect precision of the estimates. The redesigned 

surveys are more expensive, which affects costs and, in turn, could affect sample sizes. For purposes 

of meeting the requirements of the CPI there would need to be adjustments to either the budgets or 

cutting costs to meet these.

We have also kept constant the level of expenditure detail provided for the CPI. It was difficult for 

the redesign team to consider how to reduce this detail in a logical and meaningful way. If the use of 

records is increased dramatically, reducing detail may not be as critical. However, some 

consideration should be given to cutting this detail to both reduce error and burden. 

The requirements of other CE users are discussed by Henderson et al (2011). These requirements

range from the annual estimates to household expenditure patterns. These requirements are shown 

in Table 18, along with the impact of the recommended redesign. One requirement is that a 

complete picture of spending be provided for a particular CU. This is met in both the Diary and 

Quarterly Interview components by covering all expenditures. The Interview survey will not request 

respondents keep their receipts for food and alcoholic beverages, in an effort to keep this task 

manageable. But the recall interview will cover these expenditures in summary form, as the current 

survey does now. We have discussed the idea of creating rotating modules. These modules would 

collect data at a summary level for a certain class of expenditures, With the exception of food and 

alcoholic beverage expenditures, which come from the Diary survey, these modules would lead to 

some reduction in the precision of the estimates. Whether or not a module is used, a complete 

picture of spending is possible with the redesigned method. 

This design does not provide this complete picture for an entire annual period. By restricting the 

panel to two waves, spaced 12 months apart, it would not be possible to see how annual 

expenditures occur for individual households. One could look at how expenditures change within 

any particular 12-month period by comparing households that are interviewed during different parts 

of the year. 
Redesign Options for the Consumer Expenditure Survey 77 

Table 18. Data requirements for CE analysts and redesigned CE program

Requirement Addressed by redesign? 

Complete picture of spending Yes. If modules are used on Interview, imputation 

might be required

Level of expenditure detail Yes

Population Yes

Sample size and geographic detail May need to increase cost to meet current 

requirements

Time period and periodicity Yes

Panel component Annual estimates of change. Not possible to 

estimate at a CU level: (1) expenditures for an entire 

year; (2) change for intervals of less than 1 year

Integrated microdata Yes

Income Yes, But not directly addressed in recommendations

Socioecomic information Yes

Assets and liabilities Yes, but not directly addressed in recommendations

The one requirement that is not met at the same level as the current survey is the panel component. 

The current survey provides estimates of change on a quarterly basis, while the redesigned method 

does so on an annual basis. The design also reduces the precision of estimating quarterly change in 

the aggregate, since none of the CU’s will overlap within any particular quarter. As noted above, this 

change also seems to lead to more costs, although it isn’t clear how much, if any, given the 

reductions in variance under the redesigned survey. If the advantages of going to a 12-month panel 

are not viewed as important as measuring quarterly change, the design could use a quarterly panel, 

perhaps only using two, rather than four waves. This should reduce costs relative to the 12-month 

panel, but it will increase variances of annual estimates as well relative to the recommended design. 

Another alternative would be to adopt a hybrid approach that ran two different types of panels, one 

with a 12 month and another with a quarterly design. Of course this complicates the design even 

more than is currently the case with two surveys.

Priorities of the Proposed Redesign. While the proposed design has many advantages, the cost of 

the full design, as shown in Table 19, is significantly higher than the current design. Table 19 

provides a summary of the additional costs, relative to the current design, associated with the 

primary redesign components.4

 We recommend the highest priority be given to the use of personal 

records in the collection of the information. This has the greatest long-term potential to address 

both the measurement error and burden placed on respondents. It is also a cost-neutral feature of 

the new design. 

 

4 For purposes of discussion, we do not separate the cost of the incentives from other costs associated with the proposed interview design (e.g., using 

two, rather than four, waves of data collection). We believe this is a conservative assumption given the evidence that the incentives proposed are cost 

neutral and may even save the survey money.
Redesign Options for the Consumer Expenditure Survey 78 

Table 19. Additional costs of proposed design relative to current design (in millions) 

Method to reduce burden and measurement 

error Diary Interview Total 

Use of personal records n N n

Administrative Records .8 10.2 11.0

Reduction in CE Interviews na 7.6* 7.6

Multiple Diary Keepers 2.4 2.4

Enhanced Recall Interview n N n

Total 3.2 17.8 21.0

n= not a significant cost factor

There are two major components of additional costs associated with the proposed design. One is 

the proposed interview structure of two, rather than four, panel waves. This accounts for 

approximately $7 million of the $21 million in additional costs. This is a 40 percent increase in the 

cost of conducting interviews relative to the current Quarterly Interview survey. This does not 

account for the significant cost savings one could achieve by cutting sample size. For example, we 

have shown that cutting sample size on the proposed design by 20 percent would achieve similar 

levels of precision in the annual estimates as the current design if a 3-month reference period was

used for all expenditure items. One could cut as much as 40 percent and still achieve similar 

precision for many of the items if some were shifted to a 12-month reference period. Research into 

whether this is possible should be part of the development process when developing and evaluating 

the recall interview.

The primary motivator to reduce the number of panel waves is to cut respondent burden. As noted 

above, this should be a high priority for the redesign. However, the proposed design has the analytic 

disadvantage of not providing annual estimates of expenditures for individual CUs for all 

expenditures. One could theoretically achieve a similar reduction in burden, while maintaining the 

current four-wave panel design in other ways. For example, one could significantly reduce the 

number of expenditures for which extensive detail is collected. Such a design would develop three or 

four broad classes of expenditures covered in the recall interview in either summary or detailed 

form. These classes might include expenditures on apparel, health care, and entertainment. The level 

of detail collected for each module would be rotated either across households or across panel waves. 

For example, some households may not be asked detailed questions about apparel, while other 

households would not be asked detailed questions about health care. To achieve similar reductions 

in burden as the proposed design, approximately half, or slightly more than half, of the current 

Quarterly Interview survey would be administered in detailed form at any particular point in time.5

 

 

5 The current Quarterly Interview design conducts four 3-month interviews and one bounding interview for an individual CU. The proposed design 

conducts two 3-month recall interviews and two bounding interviews for an individual CU.
Redesign Options for the Consumer Expenditure Survey 79 

The use of modules has disadvantages associated with it. One is that it complicates analysis of total 

household expenditures. A second issue is that it will reduce the precision of the annual estimates. If 

a module collects the detail needed for annual estimates on 60 percent of the interviews, the 

precision of the annual estimate would be reduced by approximately 40 percent, all other things 

being equal. Because of time and resource constraints, we did not fully examine the possibilities of 

this type of design. But it should be considered as part of the redesign efforts. 

A second major component of additional costs of the proposed design is the administrative record 

survey. The survey proposed for the Quarterly Interview survey accounts for $10 million of the 

additional $21 million. The cost represents a fairly extensive administrative survey which would 

collect data on many different types of retail purchases. The costs are based on the provider survey 

conducted for the Medical Expenditure Panel survey. In this case, respondents may go to multiple 

providers, depending on the type of health care expense. It would be possible to significantly reduce 

the cost of the proposed administrative survey by concentrating on utilities, such as electricity, gas 

and water. There will be many fewer companies that would need to be contacted when compared to 

contacting retailers. Based on our recent experience with the Residential Energy Consumption 

Survey (RECS), this could reduce the cost of $10 million to as low as $3 million. This cost might be 

further reduced by restricting the collection of these data for a portion of the sample. If 12 months 

of data are collected at the same time, it would be possible to reduce the number of households for 

which the survey is conducted. For example, under the proposed design, shifting the utility items to 

a 12 month reference period reduced the variance by 56 percent. This implies that significant 

reductions in sample might be possible once shifting to this type of administrative source. 

Variations on the Proposed Redesign. The variations around the proposed design should retain 

the personal record components. This potentially addresses both measurement error and burden 

without a significant increase in costs. It is also recommended that the use of multiple diary keepers 

be retrained, at least for serious consideration in a field experiment. The added expense of this 

procedure of $2.4 million is significant for the diary. However, the evidence on this change indicates 

it could lead to significant reductions in total survey error. It also reduces burden on the main diary 

keeper. Similarly we recommend all designs include an incentive for the Diary and the Quarterly 

Interview Surveys. The evidence suggests this will result in an increase in response rates and a 

reduction in field costs.

One lower cost variation on the proposed design would be to narrow the scope of the 

administrative survey to the collection of utility information. As noted above, this cuts the cost of 

the administrative survey by approximately 70 percent. This variation would maintain the 
Redesign Options for the Consumer Expenditure Survey 80 

recommendation of cutting the number of panel waves from four to two. By lengthening the 

reference periods for key items, it might be possible to cut the sample of the survey, as discussed in 

the section on precision for the Quarterly Interview survey. If it is assumed that sample could be cut 

by 20 percent, then the increase in the cost of interviewing on the Quarterly Interview Survey would 

be approximately $3.8 million. This assumes a proportionate reduction in cost relative to reductions 

in sample size. Combined with the reductions in the scope of the administrative survey, this 

variation on the proposed design increases costs by approximately $9.4 million6 compared to the $21 

million.

A second variation would cut costs further by maintaining the current four-wave panel for the 

Quarterly Interview Survey. As with all of the recommended designs, this second variation would 

include multiple diary keepers ($2.4 million). It would also include the collection of utility data using 

an administrative survey ($3 million). The advantage of this design is that it provides annual 

expenditure information for individual CUs, which is not something the proposed design can do. 

The disadvantage of this approach is that the only measures that directly reduce burden are the use 

of personal records and collection of administrative data on utilities. CUs are retained in panel and 

are asked to complete 4 waves of recall interviews.

 

6$3 million for the administrative record survey, $2.4 million for multiple diary keepers, and $3.8 million for the revised interviewing structure.
Redesign Options for the Consumer Expenditure Survey 81 

This section presents a series of research and development (R&D) activities to identify the most 

promising approaches to redesigning the CE program. The section first presents R&D activities that 

apply to both the Diary survey and the Quarterly Interview survey. It then presents R&D activities

that pertain to each component. 

Common Elements 

Some of our proposed data collection procedures are common to the Diary survey and the 

Quarterly Interview survey. For example, we propose that both surveys obtain expenditure data 

from retailers with loyalty card programs. We propose that in both surveys, respondents be asked to 

save and scan receipts, or to mail in their receipts.

Software Development. Our recommended redesign would require that new software be 

developed. R&D activities would then address these issues: 

 Financial software like Mint can download data files for checking, credit card, and other 

accounts from the web sites of banks and financial companies. Users choose financial 

institutions from a list, and enter their account numbers and passwords. The software 

then automatically downloads the files. Can similar software be developed for the CE 

program, perhaps using the Yodlee SDK? Could the software then automatically 

transfer the files electronically to the central repository? Will CE respondents be willing 

to use this software, or will many find it burdensome, or perceive a risk to their privacy?

Will some respondents prefer to download and email these files themselves, without 

using any special software?

 In our proposed CE redesign, respondents would be asked to save their receipts and to 

complete a short form describing purchases that had no receipts. They would then scan 

their receipts. The scan files would be sent electronically to a central repository. OCR 

software would then turn the scans into text. The system would then extract the 

individual purchases from the text. All of this would occur automatically; the 

respondents would need only to start the software and scan the receipts and forms. 

Existing software such as Neat Receipts has some of this functionality, although it 

cannot extract the individual items purchased. Can all this software be developed so that 

CE respondents can use it without problem? Will the software successfully extract data 

about individual purchases? 

Development and Evaluation of 

the Proposed Design 6 
Redesign Options for the Consumer Expenditure Survey 82 

 The system would match the purchases identified from the receipts with the purchases 

identified from the downloaded data files for the respondents’ credit card, debit card, 

checking, PayPal, and other accounts. Existing software products like Mint and 

Moneydance can accomplish this matching. The matching is needed so that the web 

survey would ask about these expenditures only once. Can software be developed with 

this functionality for the CE program? 

 Once the system identified the individual expenditures, it would generate a web survey 

to ask the respondents the details about each one. Can software be developed to 

generate a usable survey? Will respondents be willing to complete the survey? 

 Potentially, smartphone apps could be created that enable respondents to enter notes 

about purchases, or to photograph purchases or bar codes. The web survey would 

prompt the respondents to enter more data about the purchases. Could such a system 

be developed, including the smartphone apps? Would many respondents use it 

successfully?

The R&D activities for the software needed in our proposed redesign would have several steps:

 Prototyping; 

 Testing for function and usability; 

 Revisions and pilot testing; 

 Further testing and revisions; and 

 Field testing.

Development of Procedures and Materials. Our proposed redesign would require a number of 

hard-copy materials, including the consent forms, the short forms that respondents complete to 

record purchases that had no receipt, and envelopes and boxes for respondents to store receipts, 

and printed instructions. The development of these hardcopy materials should include cognitive 

interviews and usability tests, to address issues such as the following: 

 Are the printed instructions easy for respondents to read, understand and use? 

 Do the respondents tend to have any specific difficulties following the instructions? 
Redesign Options for the Consumer Expenditure Survey 83 

 Are members of the household other than the respondent generally willing to read the 

instructions, and take the time to fully understand them? 

 Can respondents easily use the hardcopy forms to record purchases which have no 

receipt? What is the most usable format for these forms? Should they be designed so 

that respondents record one purchase per form, or should one form cover a single day, 

or is some other formatting best?

The initial testing for these hardcopy materials could be a set of interviews in which respondents are 

asked to use and react to prototypes. In later rounds of testing, respondents could use the materials 

at home, perhaps in concert with other household members. The testing would assess the 

respondents’ ability to understand and use the materials. 

Small Field Pilots. Once initial versions of the hardcopy materials and the software were 

developed, small pilot tests could be run to address issues such as these: 

 Can respondents follow instructions on the use of the different methods to collect 

expense information (such as downloading files, and scanning receipts)? 

 If CUs were to have multiple respondents, can the principal CU respondent successfully 

explain the CE survey procedures to other CU respondents? 

 Do other CU respondents follow the instructions? What issues arise when they are 

asked to follow these instructions? 

 Do respondents prefer to be given a choice in data collection methods, or do they 

prefer to be prescribed a method? Why? 

 What types of technical problems do respondents have when using the software? 

Respondents would be recruited for these field tests with the understanding that the tests would 

involve two contacts. During the first contact interviewers would provide verbal and printed 

instructions. A second in-person visit would be conducted two weeks later to end the data collection 

period. An interviewer would call every 3 or 4 days over the 2-week period to assess the 

respondents’ ability to download financial data files, save receipts, and follow the other procedures. 

During the second visit, the interviewer would debrief the respondent and other members of the 

household to learn the problems they encountered and their views of the procedures. 

Procedures to Assign Methods of Reporting. The procedures afford respondents a number of 

choices for reporting their data. They could download financial data files, scan receipts, complete 

and scan paper forms, or mail in paper receipts and forms. Respondents could possibly also provide 
Redesign Options for the Consumer Expenditure Survey 84 

some expenditure data using smartphones, by completing on-screen forms or recording voice 

memorandums about individual purchases, or photographing their purchases. 

By giving the respondents a range of options, our proposed redesign might tailor the survey 

procedures to the needs and preferences of the respondents. However, we cannot argue that 

maximum flexibility will necessarily result in a higher response rate or better quality data. Giving 

respondents choices for how they can respond can actually result in a diminished response rate 

(Messner et al., 2009; Dillman et al., 2007). CE respondents should be encouraged to provide data 

using electronic methods, which may be more efficient and less burdensome than methods that rely 

on paper. Recent research on mode choice (Christian et al., 2011) suggests that respondents should 

be offered choices in a sequential manner. If that is true, then respondents should be asked to 

download financial files and scan their receipts and forms, and not offered any alternatives, such as 

mailing in paper receipts, unless they objected to the electronic methods. 

On the other hand, the CE program is unique in many ways; prior research on mode choice may not 

completely apply to the CE program. Perhaps respondents should be presented with the electronic 

and paper alternatives and allowed to choose. Perhaps interviewers could ask respondents about 

their use of technology, and their habits regarding saving receipts, and their use of smartphones. The 

data collection method could then be tailored to assign a methodology that would maximize the use 

of electronic and paper records.. We recommend a field test to determine the best way to build 

flexibility into the data collection methods. 

Collection of Administrative Data. Several issues are unresolved about the use of administrative 

data in the CE program. Some of the issues that must be investigated to determine the role of 

administrative data include the following: 

 Will retail, utility and mortgage companies agree to provide a respondent’s information 

if they receive a signed consent?

 What are the major barriers to obtaining the information from these companies? 

 What is the most efficient method for gaining the companies’ cooperation? Is it 

contacting the companies’ central business offices?

 Are there ways that BLS can help motivate the companies to provide data, such as 

through publicity, or a payment? 
Redesign Options for the Consumer Expenditure Survey 85 

 Can information obtained from retail, utility, and mortgage companies be easily 

compared with a respondent’s expenditure reports? 

 How much personnel cost is involved with obtaining information from these 

companies? 

A field test could investigate whether many respondents are willing to sign consent forms to allow 

the interviewers to obtain these data, the conditions under which retail, utility, and mortgage 

companies would provide data, and the extent to which these data can reduce measurement error. 

These data potentially could serve as a substitute for respondent reports. The data potentially could 

be used for adjustments to the respondents’ data, or to fill in data about expenditures that are 

missing from the respondents’ reports. 

Comparison to Current Production Survey. Once the designs of the surveys have been finalized, 

there should be a test that compares the redesigned methods for the CE surveys with the methods 

of the current production CE surveys. The field experiments described below can help compare the 

redesigned methods with the current methods. However, these studies would not use a nationally 

representative sample. Nor would they use a full data collection cycle. A comparison using 

representative samples and a full data collection cycle would provide a more rigorous test of the 

new, redesigned data collection methods. 

Several other redesigns of large federal surveys have involved comparisons between the new and old 

methodologies. For example, the redesign of the Current Population Survey (CPS) included a test to 

compare the redesigned methods with the current methods. This test provided data to help refine 

the new survey methods. However, the new procedures evolved over the life of the data collection 

period, making comparisons with the current methods difficult to interpret. 

The test of the redesigned National Crime Victimization Survey (NCVS) in the early 1990s also 

included parallel surveys. The results allowed statisticians to calculate estimates while the survey data 

collection methods evolved to the new, redesigned ones (Kindermann, Lynch, & Cantor, 1997). 

The field experiment for the CE Interview survey should involve a national sample, or at least a 

sample that could provide results that could be generalized to a specific geographical area, so that 

the results using the redesigned data collection methods could be compared with the results using 

the current methods, and so that the results could be benchmarked to estimates from the American 

Community Survey, the PCE, or other national surveys. In the field experiment, the redesigned 
Redesign Options for the Consumer Expenditure Survey 86 

survey should be administered over at least one full collection cycle, which would be one calendar 

year.

Development and Testing of the Diary Survey 

R&D activities for the Diary survey would have several components: (1) development of the recall 

interview, (2) pilot test to evaluate the data collection procedures, and (3) a field experiment.

Developing the Recall Interview. In our proposed redesign of the CE Diary survey, respondents 

will be asked to complete an in-person recall interview at the end of the 2-week data collection 

period. This interview would employ visual aids such as Event History Calendars, and receipts. 

R&D activities should include assessing the value of various cuing strategies for helping respondents 

remember expenditures during the recall interview. These studies could start with a card sorting task 

that asked respondents to categorize different types of expenditures into different piles. (Westat will 

soon conduct such a card sorting research study under contract with BLS.) The card sorting task will 

reveal how respondents themselves group their expenditures. The results of this research will 

suggest how the recall interview can best be structured.

A second study could evaluate an approach to data collection using an Event History Calendar, a 

method that has been used successfully in other surveys (e.g., Belli, Shay, & Stafford, 2001). An 

interviewer organizes an Event History Calendar around events during the prior week that were 

significant for the respondent. The interviewer then uses these significant events to help cue the 

respondent to recall expenditures. 

Respondents in the evaluation study might save their receipts for a 1-week period. The respondents, 

without referring to these receipts, would be asked to report their expenditures. The receipts could 

be used to assess the accuracy of the data that the respondents provide in the recall interview.
Redesign Options for the Consumer Expenditure Survey 87 

Pilot Study. A pilot study could address the following questions about the Diary survey: 

 Is it feasible to obtain records from retail, utility, and mortgage companies to compare 

against respondent reports? Will respondents be willing to sign consents and will these 

companies be willing to provide the data? 

 What proportion of respondents is willing to download financial data files, scan receipts 

and forms, and email these data? What proportion is willing to mail in hardcopy receipts 

and forms? 

 Are any respondents unwilling to provide data either electronically or on paper, but still 

willing to participate in a recall interview after 1 week? After 2 weeks?

 Are respondents generally willing to provide consent to allow the interviewers to access 

loyalty card information? 

 How should interviewers tailor the data collection method to the respondent? Should 

the interviewer allow the respondent to choose a method, or should the interviewer 

prescribe a method? 

 How effective is the recall interview in obtaining accurate and complete data?

 What types of problems do respondent have with using the software, scanner, 

smartphone apps, and software for downloading financial files? 

 What is the participation rate from CU members who are not the principal respondent, 

when CUs have multiple respondents? 

 What is the reaction of respondents to the various incentives? 

 What is the perceived burden of the procedures? 

 Are interviewers able to effectively monitor the expenditure data that the respondents 

mail or email to the central repository? 

 Is the system able to effectively reconcile expenditures from the receipts and the 

financial data files?

In the pilot study, approximately 200 households would be assigned to each of four groups which 

differ by the number of people interviewed in the household (one respondent vs. all adults, with a 

principal respondent) and the approach taken to determine the response method (interviewer 

assignment vs. respondent choice). This design will provide an initial assessment of how the data 

collection procedures affect data quality and cost.

The respondents’ expenditure reports would be verified by comparing them to retailers’ 

administrative records. The feasibility of this method, of course, is dependent upon the 
Redesign Options for the Consumer Expenditure Survey 88 

establishment of a relationship between BLS and retailers. Ideally, several different types of stores 

such as grocery chains and “big box stores” can be recruited to provide purchase histories for 

specific loyalty card numbers. Respondents might be recruited from customers listed in the loyalty 

card database. 

There are alternative, less direct methods to sample store customers. For example, BLS could 

actively recruit customers through advertisements in newspapers or web sites like CraigsList asking 

for persons who have loyalty cards from particular retail chains. Respondents could be recruited 

using intercept methods, such as when they exited the store. 

Field Experiment. The next step will be to conduct a field experiment that addressed all the 

questions from the pilot study, plus these: 

 What is the most effective combination of incentives to maximize the response rate and 

the respondents’ use of electronic data collection methods (downloading financial data 

files, saving and scanning receipts and forms)?

 Which is most effective: asking a single respondent to provide data or asking every adult 

in the CU? 

 What is the level of burden associated with the redesigned procedure? 

 What is the response rate and associated nonresponse bias of the redesigned 

procedures? 

 Can respondents effectively use the different software and hardware applications? What 

are the problems they encounter? 

 How do the new procedures compare to the current design, with regard to data quality 

and costs? 

The design is illustrated in Table 20. The test would include a total of nine experimental conditions: 

two response methods (respondent choice vs. methods based on respondent habits) would be 

crossed with two conditions for respondent selection (single respondent vs. multiple respondents 

with one principal respondent). Two incentive conditions would be nested within each respondent 

selection method. The current data collection method would be included as an additional condition. 
Redesign Options for the Consumer Expenditure Survey 89 

Table 20. Experimental design for field test for the Diary survey

 New design – respondent selection Current design

Response method Single respondent Multiple respondent 

9 $50 $70 $50/$10 $80/$20

Method 1 1 2 3 4

Method 2 5 6 7 8

The respondents included in the test would be ones whose reports could be compared with data 

from retailers. By including the current collection methods as a treatment, the field experiment 

would allow for comparisons with the experimental procedures. 

Sample. The sample would be drawn from selected geographical areas that spanned urban and rural 

populations. As with the pilot test described above, the sample should ideally be drawn from 

retailers’ loyalty card databases, so that the participants’ reported expenditure data can be compared 

with the database for validity.

Evaluation Measures. Multiple outcome measures are needed to address the research questions. 

The outcome measures would include the following: 

 Mean level of expenditures; 

 Proportion of reported expenditures that match retailer information in the loyalty card 

database; 

 Proportion of expenditures that the respondents provide using records, rather than 

memory; 

 Cost of data collection per CU; 

 Non-response and bias attributable to non-response; 

 Respondents’ perceived level of burden; 

 Time required to complete interviews; 

 Proportion of respondents requiring the recall interview because they failed to provide 

adequate data via mail or email; 

 Proportion of expenditures reported during recall interview; and 

 Level of respondent satisfaction with the procedures overall, and specifically with the 

software and scanning hardware. 
Redesign Options for the Consumer Expenditure Survey 90 

The direct measure of quality will be a match between the survey and retailer records of selected 

purchases. Other, less direct, measures of quality would be the mean expenditure levels, the 

percentage of respondents using records and the percentage of expenditures that are based on 

records. A debriefing interview will ask respondents about the process such as satisfaction with 

different aspects of the process and any problems they had with the process. 

Sample Sizes and Statistical Power. There are three experimental factors proposed for the above 

field test, in addition to testing the current design. Table 21 provides the power for different sample 

sizes to test hypotheses related to differences in the response rate. The sizes shown represent the 

number in each of the comparison groups. For example, for a sample size of 800 in each group, 

there would be 80 percent power to detect a 7 percentage point different when one of the 

percentages was around 50 percent. If one wanted to be able to conduct this test for comparable 

cells in the experimental design, this would put the total sample size to around 7,200 (9 cells x 800). 

One could also design the study assuming no interactions between some of the experimental factors, 

which would reduce the sample size. 

A second line of research would be to examine the match rates between expenditures in the 

administrative records and the survey reports. For example, a question such as “What percent of 

respondents reported the expenditures listed in the administrative record?” The power listed in 

Table 22 assumes a design effect of 2, considering the geographic clustering of the sample. The rows 

correspond to a 60 percent response rate for the sample sizes listed in Table 21. For example, a 

sample of 800 corresponds to approximately 500 completes (800 x .6). With 500 completes and a 

percentage of 70 percent, there would be 70 percent power to detect a difference of 10 percentage 

points. With 1,000 per group the power goes up considerably. 

The third set of questions to be asked would compare the mean expenditures across the different 

experimental treatments. Since it is suspected that many different types of expenditures are underreported, one point of interest would test if the mean of the experimental treatments were higher. 

Power calculations were made based on the published standard errors for the Diary survey for 

selected expenditures. Table 23 provides the power for different sample sizes. The effect sizes 

represent a 10 percent or 20 percent increase in the mean, using the published estimate for that 

category. With the large variation in expenditures, considerable sample size is needed to precisely 

test for differences. For example, 1,000 completed interviews is needed to have respectable power 

(80%) for a most of the expenditures listed, except alcoholic beverages and eggs, both of which have 

high standard deviations. 
Redesign Options for the Consumer Expenditure Survey 91 

Table 21. Power for difference in response rates by sample size, level of response rate and 

size of difference

Sample size 

p=50% p=70% p=80% 

2+ 7 2 7 2 5 

800 12% 80% 14% 87% 16% 72%

1600 20% 98% 23% 99% 29% 95%

3300 37% 100% 43% 100% 53% 100%

+ Assumed Percentage Point Difference in Response Rates.

Table 22. Power for difference in match rates by number of completes, level of match rate 

and size of difference*

Completes 

p=50% p=70% p=80% 

4+ 10 4 10 4 8 

500 14% 61% 16% 70% 19% 62%

1,000 24% 89% 28% 94% 35% 91%

2,000 43% 99% 50% 100% 61% 100%

+Assumed percentage point difference in match rate.

*Assumes a design effect of 2.

Table 23. Power for difference of means for selected expenditures, number of consumer units 

completing a diary and effect size*

Expenditure type 

n=500 n=1,000 n=2,000 

10%+ 20% 10% 20% 10% 20% 

Food at home 24% 72% 43% 95% 72% 100%

Cereals and Cereal Products 17% 51% 29% 80% 51% 98%

Eggs 13% 39% 22% 67% 39% 92%

Other Food at Home 19% 58% 34% 87% 58% 99%

Food Away From Home 22% 65% 38% 91% 65% 100%

Alcoholic Beverages 7% 15% 10% 26% 15% 46%

*Power calculated for a two sided significance test at p<.95.

+ Effect size = percent difference between the two estimates of expenditures.

It should be noted that these estimates of power assume no change in the design relative to the 

national survey. In a field test it would be possible to gain efficiencies through stratification and 

blocking the sample (e.g., assign different treatments to households on the same block). It also may 

not be necessary to extensively weight the data. This should lead to a more precise test of the 

hypotheses of interest. Similarly, one could adjust the significance levels from 95 percent to 

90 percent, which also increases power. Nonetheless, these calculations indicate that significant 

resources will be needed to test design elements for the CE. It is important to note that when the 
Redesign Options for the Consumer Expenditure Survey 92 

CE was first being designed, Neter and Waksberg (1964) conducted an experiment of approximately 

5700 households, each interviewed 4 times over 18-month field period. 

Development and Testing of the Quarterly Interview Survey 

The Quarterly Interview survey will involve an initial in-person contact with the household in which 

the interviewer would provide instructions, obtain consents and conduct a bounding interview. The 

interviewer would then monitor the extent to which the respondent provided data by mail or email. 

The interviewer would call during that time, and after 1 and 2 months, to encourage the respondents 

to continue to send in expenditure data. The interviewer would conduct the second in-person visit 

after 3 months. This interview would involve conducting a recall interview. A second round of 

contacts would occur 12 months after the initial contact. The purpose of these contacts would be to 

re-orient the CU with the data collection task and to conduct a bounding interview by telephone. 

The interviewer would make interim prompting calls over the first two weeks, and after 1 and 

2 months. The final contact at 3 months would be in person to conclude the data collection and 

conduct a recall interview.

The Recall Interview. The recall interview for the Interview Survey can be developed based on the 

results of the field test of the Diary survey. In particular, the results of the card sorting task study 

could guide the structure of the interview. These results will suggest how respondents tend to 

categorize expenditures, and can point to the optimum cuing strategies. An EHC procedure should 

be developed as well.

The optimum reference periods for the Quarterly Interview survey must be determined. Research 

needs to settle the issue of which expenditures are best handled with a 1, 3, or 12-month reference 

period. 

That research could use a design in which different groups of CUs were asked to provide data about 

various expenditures using various reference periods. For example, one group of CUs could be 

asked to report on expenditures in the domain “personal services” for a 1-month period. That same 

group could then be asked to report for 3 months and then for 12 months. Another group of 

respondents could be asked to report on “personal services” expenditures in the reverse order: first 

12 months, then 3 months and then 1 month. The results of this research would suggest he types of 
Redesign Options for the Consumer Expenditure Survey 93 

errors respondents tend to commit for various types of expenditures using the three reference 

periods. 

Pilot Study. We recommend a pilot test of the proposed redesigned procedures. The interviewers 

would have four contacts with the CUs. In the first two, the interviewers would collect expenditure 

data for a 3-month period. In the second two, the interviewers would collect expenditure data for a 

second 3-month period that started 12 months after the first contact. 

The questions that this pilot study would address are the same questions that the pilot study for the 

Diary survey addressed. Moreover, this pilot study would address two questions unique to the 

Interview survey:

 How effective is the recall interview for various expenditure categories when different 

reference periods are used?

 Is there a difference in response rate and data quality between the first and second year 

of the Quarterly Interview survey?

Again, the sample of CUs should ideally be recruited from retailers’ loyalty card database records so 

that the respondents’ expenditure reports can be compared with data from the database. 

Samples of approximately 200 CUs for each of eight groups would be recruited. These groups 

would vary by: (1) number of people interviewed in the household (one respondent versus all 

adults), (2) the approach taken to determine the response method (the interviewer assigns the 

response method versus the respondent chooses), and (3) the reference period assigned to specific 

expenditure categories (all 3-months versus 1, 3, and 12 months). Decisions on the allocation of 

different expenditure/reference period combinations would be made based on the results of the 

development work described above. 

The methods of the pilot study for the Quarterly Interview survey would be identical to those 

described above for the pilot study for the Diary survey. 

Field Experiment. A field experiment would reveal how redesigned procedures compare to the 

current ones. The complexity of the design of the field experiment would depend on whether or not 

the results of the pilot test strongly suggested that specific data collection procedures were desirable, 

and did not require further evaluation. One design would be identical to that tested for the Diary 
Redesign Options for the Consumer Expenditure Survey 94 

survey (see Table 19). If it is desirable to experiment with different reference periods, the selection 

method could be dropped from the design and replaced with a reference period factor (Table 24).

Table 24. Design for field test for interview survey that includes reference period as 

experimental factor

 New design – respondent selection Current design

Reference Period 

Group Single respondent Multiple respondent 

$50 $70 $50/$10 $80/$20 9 

Group 1 1 2 3 4

Group 2 5 6 7 8

Sample Design and Evaluation Measures. The sample design and evaluation measures would be 

identical to those of the Diary field experiment, described above.

Sample Size and Power Calculations. There are three experimental factors proposed for the 

above field test, in addition to testing the current design. Many of the analytical questions to be 

addressed for the Quarterly Interview survey are similar to those discussed for the Diary. Tables 20

and 21 provide the power for examining hypotheses related to differences in response rates and the 

rate of matches between administrative records and survey reports.

The third set of questions to be asked will compare the mean expenditures across the different 

experimental treatments. To compute the power for these estimates, variances and standard 

deviations were calculated using the 2009 data available on the public use data-set. A single 

collection quarter was used to simulate what would be collected during the field test. The means for 

the interview survey have higher variability (per CU) than the Diary. Therefore the power is not as 

good for comparable sample sizes. Table 25 provides power for the test of whether the means differ 

by 10 percent, 20 percent or 30 percent. Except for electricity expenditures, none of the tests 

achieve the 80 percent level when testing for effect sizes of 10 percent or 20 percent. Even with 

2,000 completed interviews, not all of the comparisons are at this standard for 30 percent effect 

sizes.
Redesign Options for the Consumer Expenditure Survey 95 

Table 25. Power for difference of means for selected expenditures, completed interviews and 

effect size*

Expenditure Type 

N = 500 N=1,000 N=2,000 

10%+ 20% 30% 10% 20% 30% 10% 20% 30% 

Electricity 46% 96% 100% 74% 100% 100% 96% 100% 100%

Apparel and services, 

Men, 16 and over

7% 13% 22% 9% 20% 40% 13% 36% 67%

Apparel and services, 

Women, 16 and over

9% 21% 42% 13% 38% 70% 21% 65% 94%

Vehicle Maintenance 

and repairs

9% 20% 39% 12% 35% 66% 20% 61% 92%

Medical supplies 5% 7% 9% 6% 9% 13% 7% 12% 22%

*Power calculated for a two sided significance test at p<.95.

+ Effect size = percent difference between the two estimates of expenditures.

Redesign Options for the Consumer Expenditure Survey 97 

References 

 Battaglia, M.P., Shapiro, G., and Zell, E.T. (1996). Substantial bias may remain when records are used in a 

telephone survey. Presented to the American Statistical Association. Available at: 

http://www.cdc.gov/nchs/data/nis/data_collection/battaglia1996.pdf. 

Belli, R.F., Shay, W.L., and Stafford, F.P. (2001). Event history calendars and question list surveys: A 

direct comparison of interviewing methods. Public Opinion Quarterly, 65, 45-74.

Belli, R.F., Stafford, F., and Alwin, D. (2008). Calendar and time diary methods in life course research. Los 

Angeles, CA: Sage.

Berlin, M., Mohadjer, L., Waksberg, J., Kolstad, A., Kirsch, I., Rock, D., and Yamamoto, K. (1992). 

An experiment in monetary incentives. Proceedings of the Survey Research Methods Section, American 

Statistical Association. Available at: http://www.amstat.org/sections/srms/Proceedings/. 

Biderman, A.D., Cantor, D., Lynch, J.P., and Martin, E. (1986). Final report of research and development 

for the redesign of the National Crime Survey (Prepared for the Bureau of Justice Statistics). 

Washington, DC: Bureau of Social Science Research, Inc.

Blank, R.M., and Barr, M.S. (Eds.). (2009). Insufficient funds: Savings, assets, credit, and banking among lowincome households. New York, NY: Russell Sage Foundation. 

Bogen, K., Moore, J.C., and Marquis, K.H. (1994). Can we get respondents to use their personal 

income records? Proceedings of the Survey Research Methods Section, American Statistical Association.

Available at: http://www.amstat.org/sections/srms/proceedings/papers/1994_220.pdf. 

Bradburn, N. (2010). Recall period in Consumer Expenditure Surveys Program. Paper presented at the 

Consumer Expenditure Survey Methods Workshop. Available at: 

http://www.bls.gov/cex/methwrkshp_pap_bradburn.pdf. 

Brick, J.M., Kalton, G., Nixon, M., Givens, J., and Ezzati-Rice, T. (1999). Statistical issues in a record 

check study of childhood immunization. Presented to the Federal Committee on Statistical 

Methodology. Available at: http://www.fcsm.gov/99papers/murphy.pdf. 

Brick, J.M., and Williams, D. (2009). Reasons for increasing non-response in US households. Presented at the 

Workshop of the Committee on National Statistics, Washington, DC. 

Cantor, D. (2010). Discussion of plans for designing the recall period for the Consumer Expenditure Interview 

Survey. Presented at the Consumer Expenditure Survey Methods Workshop. Available at: 

http://www.bls.gov/cex/methwrkshp_pap_cantor.pdf. 

Casey, W. (2010). CPI requirements of CE. Available at: 

http://www.bls.gov/cex/ovrvwcpirequirement.pdf. 

Church, A.H. (1993). Estimating the effect of incentives on mail survey response rates: A metaanalysis. Public Opinion Quarterly, 57, 62-79.
Redesign Options for the Consumer Expenditure Survey 98 

Clifford, S. (2011, August 7). Shopper receipts join paperless age. New York Times, p. B1.

Creighton, K.P., King, K.E., and Martin, E.A. (2007). The use of monetary incentives in Census Bureau 

longitudinal surveys (Research Report Series, Survey Methodology). Washington, DC: U.S. 

Census Bureau. 

Dijkstra, W., Smit, J.H., and Ongena, Y.P. (2008). An evaluation study of the event history calendar. 

In R.F. Belli, F. Stafford, and D. Alwin (Eds.), Calendar and time diary methods in life course research 

(pp. 257-275). Los Angeles, CA: Sage.

Dubreuil, G., Tremblay, J., Lynch, J., and Lemire, M. (2011). Redesign of the Canadian Survey of 

Household Expenditures. Presented at the Household Survey Producers Workshop, Bureau of 

Labor Statistics. Available at: http://www.bls.gov/cex/hhsrvywrkshp_dubreuil.pdf. 

Duly, A., Garner, T., Keil, E., Reyes-Morales, S., and Wirth, C. (2003). The Consumer Expenditure 

Survey and AC Nielsen Survey: A data comparison study (unpublished internal document). 

Washington, DC: Bureau of Labor Statistics, U.S. Department of Labor. Cited by Garner, 

McClelland, & Passero (2009).

Edgar, J., Davis, J., Spell, S., Verlander, R., and Wetzel, G. (2006). Individual diary feasibility report

(Census Bureau report). Washington, DC: U.S. Census Bureau. 

Einav, L., Leibtag, E., and Nevo, A. (2008). On the accuracy of Nielsen Homescan data. Washington, DC: 

Economic Research Service, U.S. Department of Agriculture.

Eltinge, J. (2011). Potential topics for study in evaluating uses of external administrative data for the Consumer 

Expenditure Surveys. Discussion presented at the first Panel on Redesigning the BLS Consumer 

Expenditure Survey. Available at: http://www.bls.gov/cex/redpanl1_eltinge.pdf. 

Eppig, F.J., and Chulis, G.S. (1997). Matching Medicare Current Beneficiary Survey and Medicare 

data: The best of both worlds. Health Care Financing Review, 18, 211-229.

Ezzati-Rice, T.M., Zell, E.R., Massey, J.T., and Nixon, M.G. (1996). Improving the assessment of 

vaccination coverage rates with the use of both household and medical provider data. 

Proceedings of the Survey Research Methods Section, American Statistical Association. Available at: 

http://www.amstat.org/sections/srms/proceedings/papers/1996_054.pdf. 

Filippucci, C., and Ferrante, M.R. (1997). Individual diaries and expense documents in the Italian 

Consumer Expenditure Survey. Journal of Official Statistics, 13(2), 113-121.

Foster, K., Meijer, E., Schuh, S., and Zabek, M.A. (2011). The 2009 Survey of Consumer Payment Choice.

Boston, MA: Federal Reserve Bank of Boston. Available at: 

http://www.bos.frb.org/economic/ppdp/2011/ppdp1101.pdf. 

Fox, E.J., and Sethuraman, R. (2006). Retailing in the 21st century. New York, NY: Springer.

Garner, T.I., Janini, G., Passero, L., and Vendemia, M. (2006). The CE and the PCE: A comparison. 

Monthly Labor Review, pp. 20-46. Available at: 

http://www.bls.gov/opub/mlr/2006/09/art3full.pdf. 
Redesign Options for the Consumer Expenditure Survey 99 

Garner, T.I., McClelland, R., and Passero, W. (2009). Strengths and weaknesses of the Consumer 

Expenditure Survey from a BLS perspective. Presented at the Summer Institute, National Bureau of 

Economic Research, Cambridge, MA.

Grootaert, C. (1986). The use of multiple diaries in a household expenditure survey in Hong Kong. 

Journal of the American Statistical Association, 81(396), 938-944.

Henderson, S., Passero, B., Rogers, J., Ryan, J., and Safir, A. (2011). Consumer Expenditure Survey (CE) 

data requirements. Available at: http://www.bls.gov/cex/cedatarequirements.pdf. 

Hicks, W., Connor, S., Ward, P., et al. (2011). An experiment evaluating different amounts of respondent 

monetary gifts. Presented to the Annual Meeting of the American Association for Public 

Opinion Research, Phoenix, AZ.

Holbrook, A., Green, M., and Krosnick, J. (2003). Telephone versus face-to-face interviewing of 

national probability samples with long questionnaires: Comparisons of respondent satisficing 

and social desirability response bias. Public Opinion Quarterly, 67, 79-125.

Hubble, D., and Wilder, B.E. (1988). Preliminary results from the National Crime Survey CATI 

experiment. Proceedings of the Survey Research Methods Section, American Statistical Association.

Jackson, J. (2003, October 1). Card games: Should buyers beware of how supermarkets use “loyalty 

cards” to collect personal data? Baltimore City Paper. Available at: 

http://www.joabj.com/CityPaper/031001ShoppingCards.html. 

Kashihara, D., and Wobus, D. (2007). The effect of reporting aid use on the accuracy of householdreported medical expenditure data. Proceedings of the Survey Research Methods Section, American 

Statistical Association. Available at: http://www.amstat.org/sections/srms/Proceedings/. 

Kaufman, P. (2007). Strong competition in food retailing despite consolidation. Amber Waves 

(Economic Research Service, U.S. Department of Agriculture), 5(1), 4. Available at: 

http://www.ers.usda.gov/AmberWaves/February07/Findings/Strong.htm. 

Kim, A. (2001). Taking the poor into account: What banks can do to better serve low-income markets. 

Washington, DC: Progressive Policy Institute. Available at: 

http://www.ppionline.org/documents/Banks_080601.pdf. 

Kindermann, C., Lynch, J., and Cantor, D. (1997). Bureau of Justice Statistics, National Crime 

Victimization Survey: Effects of the redesign on victimization estimates (NCJ-164381). Washington, DC: 

Office of Justice Programs, U.S. Department of Justice. Available at: 

http://bjs.ojp.usdoj.gov/content/pub/pdf/ERVE.PDF. 

Kojetin, B., and Miller, L. (1993). Estimating the accuracy of proxy responses at the dyadic level. 

Proceedings of the Survey Research Methods Section, American Statistical Association. Available at: 

http://www.amstat.org/sections/srms/Proceedings/. 

Lessler, J. (1987). Comments and ideas for the BLS research agenda for the Consumer Expenditure Survey and 

Current Population Survey (Report to the Bureau of Labor Statistics). Available at: 

http://www.bls.gov/cex/cesrvymethslessler1.pdf. 
Redesign Options for the Consumer Expenditure Survey 100 

Marquis, K.H. (1995). The SIPP measurement quality experiment and beyond: Basic results and implementation.

Presented at the Census Bureau Annual Research Conference, Arlington, VA. 

Martin, E., Abreu, D., and Winters, F. (2001). Money and motive: Effects of incentives on panel 

attrition in the Survey of Income and Program Participation. Journal of Official Statistics, 17,

267-284.

McKernan, S.M., and Sherraden, M. (Eds.). (2008). Asset building and low-income families. Washington, 

DC: Urban Institute.

Menon, G. (1993). The effects of accessibility of information in memory on judgments of behavioral 

frequencies. Journal of Consumer Research, 20, 431-440.

Mint.com. (2011). How to: Track cash spending and checks. Available at: 

http://www.mint.com/blog/how-to/track-cash-spending-and-checks/. 

Moneydance. (2011). Balancing accounts using the Reconcile tool. Available at: 

http://moneydance.com/userguide-contents/balancing%20accounts%20using%20the% 

20reconcile%20tool.html. 

Moore, J.C., Marquis, K.H., and Bogen, K. (1996). The SIPP Cognitive Research Evaluation Experiment: 

Basic results and documentation. Available at: 

http://www.census.gov/sipp/workpapr/wp9601.pdf. 

Neter, J., and Waksberg, J. (1964). A study of response errors in expenditures data from household 

interviews. Journal of the American Statistical Association, 59, 18-55.

The Nielsen Company. (2011). Consumer panel and retail measurement. Available at: 

http://www.nielsen.com/us/en/measurement/retail-measurement.html. 

NPD Group. (2011). Products and services: Retail tracking. Available at: 

http://www.npd.com/corpServlet?nextpage=retail-tracking_s.html. 

Perloff, J.M., and Denbaly, M. (2007). Data needs for consumer and retail firm studies. American 

Journal of Agricultural Economics, 89, 1282-1287.

Piskurich, K., Nelson, D., and Herz, D. (2001). Maximizing respondent contact in the American Time Use 

Survey. Presented at the Annual Meeting of the American Association for Public Opinion 

Research, Montreal, Quebec, Canada.

Raabe, S. (2010, June 10). Shopper-card data traced for other uses. Denver Post. Available at: 

http://www.denverpost.com/business/ci_15264783. 

Redline, C., Tourangeau, R., Couper, M., Conrad, F., and Ye, C. (2009). The effects of grouping response 

options in factual questions with many options. Presented at the Annual Conference of the Federal 

Committee on Statistical Methodology. Available at: 

http://www.fcsm.gov/09papers/Redline_IX-B.pdf. 
Redesign Options for the Consumer Expenditure Survey 101 

RTI. (2002). 2001 National Household Survey on Drug Abuse incentive experiment. Available at: 

http://www.drugabusestatistics.samhsa.gov/nhsda/methods/incentive.pdf. 

Safir, A. (2011). Survey design and data collection. Briefing presented to the Consumer Expenditure 

CNSTAT Panel. Available at: http://www.bls.gov/cex/redpanl1_safir.pdf. 

Safir, A., and Goldenberg, K. (2008). Mode effects in a survey of consumer expenditures. Proceedings 

of the Survey Research Methods Section, American Statistical Association. Available at: 

http://www.amstat.org/sections/srms/Proceedings/. 

Schneider, S.J., Gustavson, B., Li, T., Göksel, H., DiGaetano, R., and Edwards, W.S. (2009). Personal 

health information management and the design of consumer health information technology: Secondary analysis 

of data from the Medical Expenditure Panel Survey (AHRQ Publication No. 09-0090EF). Rockville, 

MD: Agency for Healthcare Research and Quality. 

Schneider, S.J., and Reifer, A. (2011). Data capture technologies and financial software for collecting consumer 

expenditure data. (Report submitted to the Bureau of Labor Statistics). Rockville, MD: Westat. 

Singer, E., Gebler, N., Raghunathan, T., Van Hoewyk, J., and McGonagle, K. (1999). The effect of 

incentives in interviewer-mediated surveys. Journal of Official Statistics, 15, 217-230.

Smith, A. (2011). 35% of American adults own a smartphone. Washington, DC: Pew Internet and 

American Life Project. Available at: 

http://www.pewinternet.org/~/media//Files/Reports/2011/PIP_Smartphones.pdf. 

SymphonyIRI Group. (2011). Consumer Network. Available at: 

http://www.symphonyiri.com/ProductsSolutions/AllProducts/AllProductsDetail/tabid/ 

159/productid/56/Default.aspx. 

Tucker, C. (2011). Using multiple data sources and methods to improve estimates in surveys. Discussion 

presented at the Household Survey Users Workshop. Available at: 

http://www.bls.gov/cex/hhsrvywrkshp_tucker.pdf. 

U.S. Census Bureau. (2011). Section 25. Banking, finance, and insurance. 2011 Statistical Abstract.

Available at: http://www.census.gov/prod/2011pubs/11statab/banking.pdf. 

U.S. Department of Agriculture. (2011). Food assistance and nutrition programs: The National Household

Food Acquisition and Purchase Survey (FoodAPS). Available at: 

http://www.ers.usda.gov/Briefing/FoodNutritionAssistance/food_aps.htm. 

U.S. Department of Energy. (2011). How does EIA estimate energy consumption and end uses in U.S. homes? 

Available at: http://www.eia.gov/consumption/residential/methodology/2009/brief.cfm. 

Westat. (2005). A field test of a multiple diary procedure for the Consumer Expenditure Survey (Report to the 

Bureau of Labor Statistics). Rockville, MD: Westat.

Wine, J., and Riccobono, J. (2011). National Postsecondary Student Aid Study. Presented at the 

Household Survey Producers Workshop, Bureau of Labor Statistics. Available at: 

http://www.bls.gov/cex/hhsrvywrkshp_wine.pdf. 
Redesign Options for the Consumer Expenditure Survey 102 

Wohl, J. (2011). Walmart to give its U.S. store data to Nielsen. Available at: 

http://www.reuters.com/article/2011/07/21/us-walmart-nielsenidUSTRE76K3K420110721. 

Yodlee, Inc. (2011). Yodlee aggregation SDK. Available at: http://www.yodlee.com/solutionsdeveloper-api-yodlee-aggregation.html.