1 

CE Data Quality Report (Prototype) 

Laura Erhard and Lucilla Tan 

Bureau of Labor Statistics 

Overview 

The Consumer Expenditure Survey (CE) has 

historically provided some limited metrics

for data users to evaluate the overall quality 

of output provided in its products. 

Published tables provide standard errors, 

the public-use microdata user guide 

provides response rates, and the public-use 

microdata datasets provide all the variables 

and flags necessary for users to create his 

or her own quality measures. There has 

long been a recognition for the need for 

more comprehensive data quality metrics 

that are timely and routinely updated, 

accessible to data users from a single 

source. However, there is also recognition 

of the high cost in terms of resources and 

commitment to identifying appropriate 

metrics and establishing the information 

base necessary to routinely produce reports 

on survey data quality. In order for this 

effort to be sustainable, the benefits from it 

must be relevant and useful to survey 

operations and data users. 

This report is the first in a series of 

iterations towards a single reference source 

on a comprehensive set of CE data quality 

metrics that are timely and routinely 

updated for the Consumer Expenditure 

Quarterly Interview Survey (CEQ) and the 

Consumer Expenditure Diary Survey (CED). 

The initial measures presented in this first 

report were based on already currently 

collected data and producible with limited 

resources. The decision to release the first 

report with only a very limited set of 

measures was based on the recognition of 

the benefits of “learning-by-doing” –

providing CE with insight as to what 

resources might be needed to produce such 

a product routinely. As a better 

understanding of the infrastructure needed 

for creating measures of data quality in the 

CE develops, more metrics will be 

produced. 

How to read this report 

The following section (Data Quality 

Measures) includes a summary table of all 

the metrics annual percentage changes. 

Each subsequent section of this document 

relates to a specific data quality measure or 

group of measures. The first part of each of 

these sections describes the current trends 

for the measure(s) followed by a graph over 

time. General definitions and a guide for 

interpreting the different measures are 

included after the graph(s). Detailed 

definitions and descriptions of the data 

used can be found in the Appendix. 

Data Quality Measures 

The measures reported in this report for the 

years 2009 through 2013 are: 

CE Response and Nonresponse Rates 

Expenditure edit rates

Income imputation rates

The annual rates for these measures appear 

in Table 1, and their annual percentage 

change are shown in the Figure 1. The 

annual rates of these measures and further 

details about the measures are reported in 

the sections that follow. The charts in the 

sections that follow are based on the 
 2 

annual rates in Table 1. All rates presented 

in the report are produced using 

unweighted data. 

 

Figure 1. Annual percentage change from the 

previous year of data quality meaures

-2.1% -1.8%

-3.5%

-10.4%

-1.6%

-3.2%

-2.0%

-4.2%

2010 2011 2012 2013

Response Rate 

 CED CEQ

2.0%

0.2%

2.6%

0.1%

-7.4%

-3.3%

2.9%

5.7%

Overall edit rate for expenditures

-1.0%

0.1% 0.3%

-3.2%

1.9%

-0.5%

-2.4%

-4.6%

Income imputation rate

Table 1. Annual rates of data quality measures

(unweighted) 

Data Quality 

Measure

2009 2010 2011 2012 2013

Percent

Response Rate 

 CEQ 75.0 73.8 71.4 70.0 67.1

 CED 73.0 71.5 70.2 67.8 60.8

Overall edit rate 

for expenditure 

reports

 CEQ 16.2 16.6 16.6 17.0 17.0

 CED 27.6 25.6 24.7 25.5 26.9

Imputation rate 

for expenditure 

reports

 CEQ 6.8 7.1 7.3 7.5 8.1

 CED na na na na na

Allocation rate 

for expenditure 

reports

 CEQ 8.6 8.7 8.5 8.8 8.2

 CED 27.4 25.4 24.5 25.3 26.7

Overall 

imputation rate 

for income 

reports

 CEQ 48.0 47.5 47.5 47.7 46.2

 CED 52.7 53.7 53.4 52.1 49.8
 3 

CE Response and Nonresponse 

CE Interview Survey (CEQ) 

Response rates steadily fell from 

75.0 percent in 2009 to 67.1 percent in 

2013 (Figure 2), with the largest annual 

percentage change of -4.2 percent 

occurring in 2013. A portion of the recent 

decline in 2013 is the result of the 

shutdown of the Federal Government which 

occurred in October 2013.1

 

Refusal rates rose from 17.1 percent 

in 2009 to 21.2 percent in 2013, with 

smaller increase in noncontact rates of 4.5 

percent to 5.8 percent, respectively. The 

reclassification rate of interviews to unit 

nonresponse remained consistently 

negligible throughout this period. 

CE Diary Survey (CED) 

 CED response rates mirrored the 

same declining trend as the CEQ, and were 

Consistently lower. The CED response rate 

fell from 67.6 percent in 2009 to 56.2 

percent in 2013 (Figure 2), with the largest 

annual percentage change of -10.4 percent 

occurring in 2013. The CED was also 

affected by the shutdown of the Federal 

Government, which can account for a 

portion of the decline in the response rate. 

CED refusal rates also trended upwards but 

were consistently lower than those for the 

CEQ, rising from 11.1 percent in 2009 to 

12.8 percent in 2013. CED noncontact rates 

ranged from 4.7 percent to 6.0 percent 

within the period. The nonresponse 

reclassification rate is higher in the CED 

than the CEQ but fairly consistent, ranging 

from 4.7 percent to 6 percent. 

Figure 2. Annual final disposition rates (unweighted) 

Explanation and Interpretation 

 

1 Note that September’s rates were affected by the shutdown as well because interviewers were not able to go out 

and collect data or Diaries that were started in September, but ran into October. 

73.0% 71.5% 70.2%

67.8%

60.8%

75.0% 73.8% 71.4% 70.0%

67.1%

2009 2010 2011 2012 2013

Response Rates 

CED CEQ

4.5% 4.5% 4.8% 5.3% 5.8%

17.1% 18.0%

19.6% 20.1%

21.2%

CEQ: Nonresponse Rates

Noncontact

Refusals

Reclassification rate < 0.2%

4.2% 3.6% 3.3% 3.5%

4.7%

11.1% 10.8% 11.4% 12.1% 12.8%

4.7%

6.0% 5.7% 5.5% 5.5%

CE Diary: Nonresponse Rates

Noncontact

Reclassification

Refusals
 4 

Response and nonresponse rates are measures of cooperation levels in a survey. Since 

not all eligible sample units will be available or agree to participate in the survey, there will be 

some nonresponse to the survey request. Characteristics of nonrespondents may differ from 

respondents and they may have different responses to the survey questions, so that their 

omission from the survey may result in bias in the estimates produced from the survey. While 

weighting adjustments may reduce bias, the effectiveness of this approach depends on the 

availability and quality of variables used in the weighting so that concerns about bias persist. So 

in general, higher response rates (and lower nonresponse rates) are preferred. 

The unit of observation for the CE is the Consumer Unit (CU), so response and 

nonresponse rates are computed at the CU level. Among eligible CUs, nonresponse occurs 

when the interviewer is unable to contact an eligible member of the CU, or when the contacted 

CU member refuses. The Census Bureau categorizes eligible CUs who do not respond to the 

survey as Types A nonresponse. Reasons for Type A nonresponse include the following: the 

interviewer finds no one at home despite repeated visits, all eligible members are away during 

the interview period, or eligible members refuse for any reason. 

In addition to the Type A nonresponse described above, there is a minimal expenditure 

edit check performed at BLS (CE) after Census delivers the data that could change an 

interviewer-coded “completed interview” (or respondent) to “nonrespondent”; this type of 

edit is referred to as the nonresponse reclassification. The edit uses a subset of respondent 

characteristics to highlight CUs that were highly suspect to have under-reported expenditures 

for manual review; reclassification to unit nonresponse occurs when there is adequate 

justification of under-reporting in the data that would adversely impact the quality of the final 

survey estimates. Since this edit increases the number of unit nonresponses, a lower 

reclassification rate is preferred. 

In addition, the nonresponse reclassification rates may also be viewed as an indicator of 

the potential for nonresponse bias because the minimal expenditure edit (which triggers 

reclassification) converts these ‘respondents’ to nonrespondents. If those reclassified as 

nonrespondents are systematically different from respondents, nonresponse bias will result. 

From this perspective also, a lower reclassification rate is preferred. Ideally, other indicators 

that attempt to measure nonresponse bias should be considered in conjunction with this 

reclassification rate when evaluating nonresponse bias. 

This reclassification is conducted in both the Interview and Diary surveys; however, 

cases in the Interview survey account for less than 0.2 percent for all cases and are excluded in 

for the CEQ in Figure 2. 

Although the CE Interview Survey comprises five waves of data collected from the same 

CU, and two waves for the CE Diary Survey, longitudinal response rates are not currently 

computed for either CE survey. The CE treats each wave of data collected as independent from 

each other in the production of official survey estimates, and consequently, response and 
 5 

nonresponse rates are computed for each wave independently; these rates are depicted in the 

graphs above.2 

Summary: Everything else equal, higher response rates are more desirable for minimizing 

potential nonresponse bias for surveys if respondents are representative of the target 

population. The trend of declining response rates continued in 2013 for both the CEQ and the 

CED, emphasizing the need to better understand if and how differences between respondents 

and nonrespondents affect nonresponse bias of key survey estimates. 

Definitions 

 Eligible Sample (denominator for all rates): the total number of eligible consumer units for 

the period. 

 Response rate (AAPOR definition RR2): the total number of completed and partial 

interviews (interviews that provide data for use in the production tables) for the period, 

divided by the eligible sample. 

 Refusal rate (AAPOR definition REF3): the total number of nonresponse units due to refusals 

(for various reasons such as time, language or health problems) and insufficiently 

completed interviews for the period, divided by the eligible sample. 

 Noncontact rate (1- AAPOR definition CON3): the total number of nonresponse units due to 

inability to contact any sample unit member for the period, divided by the eligible sample. 

 Nonresponse reclassification rate: the total number of consumer units for the period who 

had been classified as interviews at the close of the data collection period but were 

subsequently reclassified as nonresponse based on a review of their total expenditures and 

other information, divided by the eligible sample. 

Details on the exact calculations of the rates can be found in Appendix A. 

 

2

 For the CE Interview Survey, Wave 1 is treated as a bounding interview, and is excluded in the response and 

nonresponse rates presented in the graphs. 
 6 

CE Expenditure Edit Rates (Imputation and Allocation) 

Imputation and allocation are two major types of data edit routines to improve expenditure 

and income estimates derived from the Interview and Diary Surveys. In addition to the overall 

expenditure data edit rate, imputation rate and allocation rate are separately reported for 

income and expenditures. The figure shown in this section is based on Table 1. 

CE Interview Survey (CEQ) 

The increase in the overall proportion of edited expenditure reports between 2009 and 2013 

was small (16.2 percent to 17.0 percent, respectively), with a larger increase in imputation rates 

from 6.8 percent in 2009 to 8.1 percent in 2013 (Figure 3). The trends of imputation rates 

varied dependent on the expenditure category. Expenditure categories with the most apparent 

trends in increasing imputation rates between 2009 and 2013 included vehicle purchases, 

leased vehicles, telephone expenses, and trips and vacations. Only two categories had a clear 

trend of decreasing imputation rates: construction and repairs for jobs not started and disposal 

of owned properties. Allocation rates were largely steady around 8.6 percent, then falling to 

8.2 percent in 2013. 

CE Diary Survey (CED) 

The overall edit rate declined between 2009 and 2011 from 27.6 percent to 24.7 percent, but 

increased to 26.9 percent in 2013 (Figure 3). Allocation is the primary form of edit performed 

on CED expenditures, and the overall edit rate largely reflects allocation rates. 
 7 

Explanation and Interpretation 

At the completion of an interview, data from the interviewer’s laptop are transmitted to the 

Census Master Control System. The Census Bureau’s Demographics Surveys Division preforms 

some preliminary processing and reformatting of the data before transmitting the data to BLS 

on a monthly basis; names and addresses of respondents are not transmitted. At BLS, a series 

of automated and manual edits are applied to data in order to make data consistent, fill in 

missing information, and correct errors in the collected data. (For more description about the 

data collection and processing for the CE surveys, see 

http://www.bls.gov/opub/hom/pdf/homch16.pdf. 

Edits are defined as any changes in the data made during processing that require judgment or 

assumptions (whether model based or manually adjusted by the analyst). Imputation and 

allocation are two major types of data edit routines to improve estimates derived from the 

Interview and Diary Surveys. 

 Data imputation routines currently account for missing or invalid entries and address 

most expenditure and income fields, excluding assets. 

 Allocation routines are applied, when respondents provide insufficient detail to meet 

tabulation requirements. For example, if a respondent provides a non-itemized overall 

expenditure report for the category of fuels and utilities, that overall amount will be 

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

22%

24%

26%

28%

30%

2009 2010 2011 2012 2013

Percent of MTAB expenditure records

Figure 3. Annual edit rates of expenditure reports by method

CEQ overall edit CEQ allocation only

CEQ imputation only CEQ other

CED overall edit (mostly allocation)
 8 

allocated to the target items mentioned by the respondent (such as natural gas and 

electricity). 

In addition to allocation and imputation, data are reviewed and manually edited as needed by 

BLS economists based on the economist’s research and expert judgment. 

Summary: The higher imputation rate of expenditure reports was coupled with a lower 

allocation rate for the CEQ in 2013 (8.6 percentage change, and -6.9 percentage change, 

respectively, between 2013 and 2012; see Table 1) causing the overall edit rate to be stable 

between the two years. Higher imputation rates reflect higher item nonresponse, which is not 

desirable. However, imputation based on sound methodology improves the completeness of 

the data to produce survey estimates. 

In contrast to the CEQ, the allocation rate of CED expenditures rose – it was 5.7 percent higher 

in 2013 relative to 2012. The higher allocation rate of CED expenditures indicate that 

respondents are not providing the required item detail in their diary reports. 

Income imputation rates fell in both the CEQ and CED in 2013 (by -3.2 percent, and -4.6 

percent, respectively). 
 9 

CE Income Imputation Rates 

CE Interview Survey (CEQ). 

The proportion of consumer units’ whose total income before tax included any imputed 

sources of income continued a declining trend from 48 percent to 46.2 percent between 2009 

and 2013 (Figure 4, left panel). However, the imputation rate of zero-reported income to a 

positive value increased from 1.3 percent to 2.1 percent over this period. This edit is referred to 

as “All valid blank” conversion. It occurs when a CU reports that they received no income, but 

the BLS imputes that some income was received. 

CE Diary Survey (CED). 

As in the CEQ, the proportion of imputed income in the CED also declined between 2009 and 

2013, from 52.7 to 49.8 percent (Figure 4, right panel). The imputation rate of zero-reported 

income to a positive value (“All valid blank” conversion) was relatively steady around 3 percent 

across this span of 5 years. 

NOTE: Drop off in income imputation rates for both surveys. In 2013, substantial revisions were 

made to the income section: some questions were merged together or split into new questions. 

The change in questionnaire is the likely cause of the larger change in income imputation rates 

for both CEQ and CED surveys in 2013. 

Figure 4. Annual income imputation rates

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

45.0

50.0

55.0

2009 2010 2011 2012 2013

ALL VALID BLANK RATE

IMPUTED INCOME RATE

CEQ 

Income All valid blank

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

45.0

50.0

55.0

2009 2010 2011 2012 2013

ALL VALID BLANK RATE

IMPUTED INCOME RATE

CED 

Income All valid blank
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Appendix A. Detailed Metric Definitions 

In appendix A, we present the details of all proposed metrics for the data quality measures 

used in the report. These include the response rates, refusal rates, noncontact rates, 

reclassification rates, and editing rates for expenditures and income). 

1. Response and nonresponse rates 

In order to calculate the response and non-response rates, we use data sets that are not fully 

processed by BLS. These data sets are used because the fully processed data excludes nonresponse cases. The datasets used include good interviews and type A non-interviews. 

Following the model of the production tables, each wave of data is treated independently for 

the CE quarterly interview survey (CEQ) and each weekly diary will be treated independently for 

the CE Diary survey (CED). 

Eligible Sample (denominator for all rates): 

The total number of good interviews and interviews due to non-response, non-contact, or other 

eligible households. This excludes any address that was sampled and ineligible (for example, an 

abolished household at a sampled address or a commercial business at a sampled address). 

CEQ: 

Count of all unique CUs in data file. Includes the following interview OUTCOME codes3. 

201 Completed interview

203 Transmit, no more follow-up possible (Through Section 20 complete)

215 Insufficient partial (TYPE A NONINTERVIEW)

216 No one home, unable to contact (TYPE A NONINTERVIEW)

217 Temporarily absent (TYPE A NONINTERVIEW)

219 Other (TYPE A NONINTERVIEW)

321 Refused, Hostile respondent (TYPE A NONINTERVIEW)

322 Refused, Time related excuses (TYPE A NONINTERVIEW)

323 Refused, Language problems (TYPE A NONINTERVIEW)

324 Refused, Other (TYPE A NONINTERVIEW)

CED: 

Count of all unique CUs in data file. Includes the following diary PICKCODE (pick up) codes. 

201 Interview

216 Type A - No home(unable to contact)

 

3

 Codes for the OUTCOME variable are also available the public use microdata paradata file, FPAR. The OUTCOME 

codes have the same values and definitions as shown in Appendix A. The file FPAR has been available since the 

2009 data release. 
 11

217 Interview - Temporarily Absent(counted as Type B noninterview for Census, in scope for 

BLS)

219 Type A - Other - Specify

321 Type A - Refused, Hostile respondent

322 Type A - Refused, Time-related excuses

323 Type A - Refused, Language problems

324 Type A - Refused, Other - Specify

325 Type A - Diary Placed Too Late

326 Type A - Blank Diary, majority of items recalled without receipts(counted as Type B 

noninterview for Census)

A.1.a: Response Rate (AAPOR definition RR2) 

Defined as total number of good and partial interviews (interviews that provide data for use in 

the production tables), divided by the eligible sample. 

CEQ: 

OUTCOME = 

201 Completed interview

203 Transmit, no more follow-up possible (Through Section 20 complete)

CED: 

PICKCODE = 

201 Interview

217 Interview - Temporarily Absent(counted as Type B noninterview for Census, in scope for 

BLS)4

A.1.b: Refusal Rate (AAPOR definition REF3) 

Defined as total number of type A non-interviews that were refused or started, but not 

completed, divided by the eligible sample. Refused interviews includes refusals due to time, 

language problems, and other types of refusals. 

CEQ: 

OUTCOME = 

215 Insufficient partial (TYPE A NONINTERVIEW)

321 Refused, Hostile respondent (TYPE A NONINTERVIEW)

322 Refused, Time related excuses (TYPE A NONINTERVIEW)

 

4

 Expenditures made while on trips are out of scope for CED, so temporarily absent cases are counted as having 

had no in-scope expenditures (zero expenditures) during the diary week for the CE published tables. For collection 

purposes, these cases are treated as Type B Noninterviews in the CED. For OMB reporting purposes these cases 

are treated as Type A Noninterviews. 
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323 Refused, Language problems (TYPE A NONINTERVIEW)

324 Refused, Other (TYPE A NONINTERVIEW)

CED:

PICKCODE = 

321 Type A - Refused, Hostile respondent

322 Type A - Refused, Time-related excuses

323 Type A - Refused, Language problems

324 Type A - Refused, Other - Specify

A.1.c: Noncontact Rate 

Defined as total number of type A non-interviews that were due to non-contact, divided by the 

eligible sample. 

CEQ: 

OUTCOME = 

216 No one home, unable to contact (TYPE A NONINTERVIEW)

217 Temporarily absent (TYPE A NONINTERVIEW)

CED:

PICKCODE = 

216 Type A - No home(unable to contact)
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A.1.d: Reclassification of interview to unit nonresponse (Minimal Expenditure Rates) 

Defined as the total number of interviews that were changed from completed to a Type A noninterview based on a review of total expenditures and other information about the CU, divided 

by the eligible sample. 

CEQ 

OUTCOME = 

219 Other (TYPE A NONINTERVIEW)

TYPEASP = “Minexpn”

CED

INTRVIEW = 

5 Diaries with zero items reported in both weeks of the survey OR Diaries with zero items reported and the 

diary from the other diary week is a Type A, B, or C non-interview

6 Diaries with zero items reported and the diary from the other diary week has > 10 items reported in FDB with 

the total cost of these items being <= $50 OR Diaries with zero items reported and the diary from the other 

diary week has <= 10 items reported in FDB with the total cost of these items being <= $50 and the CU does 

not live in a rural area or a college dormitory and no members of the CU were away during the reference 

period

7 Diaries where there is one person in the CU and the total amount spent on food (at home and away from 

home) is <= $5 in the current week and <= $15 in the other diary week, and the number of items reported 

for non-food items in the current week is < 4 or the total cost of items reported for non-food items in the 

current week is < $30

8 Diaries where there are 2 or 3 members in the CU the total amount spent on food (at home and away from 

home) is <= $10 in the current week and <= $20 in the other diary week and the number of items reported of 

non-food items in the current week is < 4 or the total cost of non-food items reported in n the current week is 

< $30

9 Diaries where there are four or more CU members and CU the total amount spent on food (at home and 

away from home) is <= $20 in the current week and <= $30 in the other diary week and the number of items 

reported of non-food items in the current week is < 4 or the total cost of non-food items reported in n the 

current week is < $30

2. Expenditure Edit Rates 

Expenditure edit rates are calculated using processed CE data (data that are used to produce 

the published tables) for each collection period. Following the model of the production tables, 

each wave of data is treated independently for the CE quarterly interview survey (CEQ) and 

each weekly diary will be treated independently for the Diary survey (CED). 

CEQ:

Interview expenditure edits are calculated using the interview monthly tabulation file (MTAB). 

The “cost flag” (COST_) is used to identify if an expenditure was edited and what type of edit 

was done (imputation, allocation, combination, other). In addition, the “allocation number” is 
 14

used to determine whether the resulting estimated has been allocated. The different types of 

edits (or non-edits) will be identified by the following flags. Note: These definitions may be 

further refined as the metrics are developed. 

 

CEQ 

MTAB 

Flag value

Flag Description Edit group Edit Subgroup

0 All of the source fields were flagged either as 0 (No Census 

adjustment) or -300 output from screens selected for 

microfilm review/no change or -400 output from screens; but 

not selected for microfilm review (no change)

Unedited NA

1 One of the source fields was flagged by Census (source flag >0) Unedited NA

2 Manually updated (expenditure flag = -100) Changed in 

superfix (not a valid data adjustment source record field [-

500]) Changed in superfix (is a valid data adjustment source 

record field [-600]) (Note: All of the following flags (3-9 & Q-S) 

indicate the source field was data adjusted by BLS. The two 

digit numbers in the parenthesis are the trailing digits of the 

source field flag, and indicate the method(s) of adjustment 

named after the parenthesis.)

Edited Other

3 (-01 through -10) IMPUTATION Edited Imputed

4 (-12 through -19) ALLOCATION Edited Allocated

5 (-20 through -27) IMPUTATION and ALLOCATION Edited Combination

6 (-30 through -32) COMPUTATION only Unedited NA

7 (-35 through -43) COMPUTATION and IMPUTATION Edited Imputed

8 (-45 through -52) COMPUTATION and ALLOCATION Edited Allocated

9 (-53 through -68) COMPUTATION, IMPUTATION and 

ALLOCATION

Edited Combination

Q (-70 through -74,-75,-76) MANUAL IMPUTATION Edited Imputed

R (-78 through -85,-86,-87,-88) MANUAL ALLOCATION Edited Allocated

S (-90) SECTION 18 SPECIAL PROCESSING Edited Other

Of note, for both surveys, the number of targets selected for an allocation will affect the 

adjustment rates (the total number of items that are allocated will add to both the numerator 

and the denominator. 

CED:

Diary expenditure edit rate is calculated using the expenditure files from diary. The “cost flag” 

(COST_) is used to identify if an expenditure was edited. In addition, the “allocation number” is 

used to determine whether the resulting estimate had been allocated. An expenditure record 

will be considered unedited if it has one of the following flags: 

CED EES 

Flag 

Value

Description Explanation

‘0’ Default - no change to data No adjustments were made during processing.
 15

‘3’ Reviewed, no update; default adjustment status The value was reviewed during processing, but 

no adjustments were made.

‘11’ Sales Tax, Preliminary edits, or Minimal 

expenditure reclassification edit

Sales tax is a calculation applied to the data and 

will be treated as unedited for these rates. 

‘15’ Phase 1 Confirmed. Operator/Error Resolution

Overrides (confirms value)

This flag is carried from the CAPI instrument 

and is present when a Field Representative

suppresses a prompt to check the value 

(confirming the reported value). No changes 

are made to the data.

‘16’ Phase 1 Changed. Error Resolution Changes value This flag is carried from the CAPI instrument 

and is present when a Field Representative

updates a value after prompted to check the 

value. Though the data is changed, it is 

assumed that it is edited based on the 

respondent’s input and not considered as 

edited during processing. 

All other flags indicate some type of adjustment during processing and are considered edited 

for the rate. An allocation rate is also produced using the allocation number of a given item 

(ALCNO). Any allocation number not equal to ‘000’ is an allocated value. It is important to note 

that the values that are allocated are included in the editing rate; however, these values may 

also have been edited in some other way during the processing. It is not possible to delineate 

other edits from the current data available. 

Income Imputation Rates 

The CE implemented multiple imputations of income data, starting with the publication of 2004 

data. Prior to that, only income data collected from complete income reporters were published. 

However, even complete income reporters may not have provided information on all sources of 

income for which they reported receipt. With the collection of bracketed income data starting 

in 2001, this problem was reduced but not eliminated. One limitation was that bracketed data 

only provided a range in which income falls, rather than a precise value for that income. In 

contrast, imputation allows income values to be estimated when they are not reported. In 

multiple imputations, several estimates are made for the same consumer unit, and the average 

of these estimates is published. 

Income data from the Diary Survey are processed in the same way as in the Interview Survey. 

Imputation rates for income will be calculated based on the processed CE data (data that are 

used to produce the published tables) for each collection period. Following the model of the 

production tables, each wave of data will be treated independently for the CE quarterly 

interview survey (CEQ) and each weekly diary are treated independently for the Diary survey 

(CED). Imputation rates are calculated for final income before taxes. The income is counted as 

imputed if any of its summed components were imputed during processing. This will be 
 16

identified using the imputation indicator flag. Any value of the flag not equal to ‘100’ is 

considered imputed. 

Imputation Flag values 

Flag Value Description

100 No imputation. This would be the case only if NONE of the variables that are summed to get 

the summary variables is imputed.

2nn Imputation due to invalid blanks only. This would be the case if there are no bracketed 

responses, and at least one value is imputed because of invalid blanks.

3nn Imputation due to brackets only. This would be the case if there are no invalid blanks, and 

there is at least 1 bracketed response

4nn Imputation due to invalid blanks AND bracketing

5nn Imputation due to conversion of valid blanks to invalid blanks. (Occurs only when initial values 

for all sources of income for the consumer unit and each member are valid blanks.)

Additionally, an all valid blank conversion rate is calculated indicating the percent of instances 

that were converted from all valid non-responses (i.e., the respondent replied that the CU did 

not receive income from any source) to invalid non-responses that were subsequently imputed 

during processing. This will be based on the indicator flag with a value of ‘500’ or above.