Getting Started Guide

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Getting started with Consumer Expenditure Survey (CE)
Public-Use Microdata (PUMD)∗
Division of Consumer Expenditure Survey, Bureau of Labor Statistics†
September 9, 2014
∗Version 3.0
†For questions or comments, please contact the CE by phone, (202) 691-6900, or email, CEXINFO@bls.gov.
Contents
1 Introduction 1
1.1 Purpose ........................................... 1
1.2 What is CE PUMD? .................................... 1
1.3 Do I really need CE PUMD for my project? ....................... 1
2 PUMD file structure 2
2.1 Interview survey data ................................... 2
2.1.1 Quarterly files ................................... 2
2.1.2 “Annual” or “5 quarter” files ............................ 3
2.1.3 Paradata ...................................... 3
2.2 Diary Survey Data ..................................... 3
2.2.1 Quarterly files ................................... 3
2.3 File naming conventions .................................. 4
2.3.1 File names and directories ............................. 4
2.3.2 What’s the “X” about? ............................... 5
3 PUMD file content overview 5
3.1 Interview quarterly files .................................. 5
3.1.1 FMLI-CU characteristics, income, and summary expenditure variables .... 5
3.1.2 MEMI-CU member characteristics and income ................. 6
3.1.3 MTBI-Monthly expenditure file classified by UCC ............... 6
3.1.4 ITBI-Consumer Unit monthly income classified by UCC ............ 7
3.1.5 ITII-Consumer Unit monthly imputed income file classified by UCC. ..... 7
3.1.6 NTAXI-Federal and state tax information classified by tax unit ........ 8
3.2 Interview annual files–EXPN ............................... 8
3.2.1 CLA-Clothing and sewing materials ....................... 9
3.2.2 IHB-Hospitalization and health insurance detailed questions .......... 9
3.2.3 VEQ-Vehicle maintenance and repair ....................... 10
3.3 Diary files .......................................... 11
3.3.1 FMLD-CU characteristics, income, weights, and summary level expenditures 11
3.3.2 MEMD-CU member characteristics and income ................. 11
3.3.3 EXPD-Detailed weekly expenditure file categorized by UCC .......... 12
3.3.4 DTBD-Detailed annual income file categorized by UCC ............ 12
3.3.5 DTID-Consumer Unit imputed income file categorized by UCC. ....... 12
4 Documentation 13
1 Introduction
1.1 Purpose
The Getting Started Guide is intended for the novice user of CE Public-Use Microdata (CE PUMD).
The guide introduces the structure and content of the CE PUMD files and lists the available
documentation.
1.2 What is CE PUMD?
The CE PUMD are a series of data files that contain a wealth of detailed variables concerning each
individual response from the two CE surveys within a collection year. This level of detail is useful
for a broad spectrum of research, but to analyze the data requires researchers to have an advanced
knowledge of a statistical software package, such as SAS.
1.3 Do I really need CE PUMD for my project?
Many research projects do not require that much detail. For these projects, CE provides tabulated
data with pre-calculated population means, aggregates, and standard errors as well as selected
demographic characteristics.
The online CE tabular data, available at http://www.bls.gov/cex/tables.htm, are broken
out by the following characteristics:
Age of reference person
Composition of consumer unit
Highest education level of any member of the consumer unit
Higher income before taxes (>$70,000)
Hispanic or Latino origin of reference person
Housing tenure and type of area (Urban/Rural)
Income before taxes (<$70,000)
Number of earners in consumer unit
Population size of area of residence
Quintiles of income before taxes
Race of reference person
Region of residence
Size of consumer unit
Selected age of reference person
1
The tabular data are constructed from internal CE microdata, and are widely used by re-
searchers, journalists, businessmen, policy makers, academics, non-profits, students, and local,
state, federal, and foreign governments.
If you are looking for more detailed expenditures than what are available in the online tables,
then you can request disaggregated tables (“prepubs”) by contacting our office at: http://www.
bls.gov/cex/csxcont.htm. The disaggregated tables will have more granular expenditures such
as “bacon” or “pork chops” instead of “pork.” You can see the level of detail available in the tables
by looking at the underlying items in the glossary of expenditures terms: http://www.bls.gov/
cex/csxgloss.htm#expn.
If your research needs cannot be met with the available tables, then the CE PUMD files may
be for you. With the CE PUMD files, you will be able to calculate means and other statistics by
demographic groups that you define, as well as conduct more complex analysis such as regression
analysis or analysis of variance.
However, the CE PUMD is a large, complex dataset that requires an extensive time commitment
by users to study the documentations to learn how to use the data appropriately. In addition to
the time needed to learn how to use the files, users must also have a good working knowledge of
an advanced statistical software package, such as SAS, SPSS, or STATA, to manipulate the files.
Because of the large file sizes, it may be difficult to use a package such as Microsoft Excel to conduct
analysis.
If you have any questions about whether the CE PUMD is right for you, our staff would be
happy to give you guidance. Contact us at: http://www.bls.gov/cex/csxcont.htm. We also host
an annual CE Microdata Users’ Workshop to help our users learn how to use the CE PUMD files
through hands-on practical training. Look for an announcement on the CE website for our next
workshop.
2 PUMD file structure
2.1 Interview survey data
2.1.1 Quarterly files
“Quarter” refers to the calendar quarter in which the interview occurred. For example, any Con-
sumer Unit (CU) interviewed in April, May, or June would have their data stored in the quarter 2
(Q2) datasets. During an interview, the CU is asked to report expenditures for a reference period of
three months. So, for a CU interviewed in April, their expenditures in the Q2 file are for January,
February, and March. (This is important to remember when calculating calendar year estimates.)
Five quarters of interviews are included in each PUMD release, Q1 of (RELEASE YEAR) through
Q1 of (RELEASE YEAR + 1). There are six types of data files organized by quarter:
1. FMLI - a file with characteristics, income, weights, and summary level expenditures for the
CU.
2. MEMI - a file with characteristics and income for each member in the CU.
3. MTBI - a detailed monthly expenditure file categorized by Universal Classification Code
(UCC).
4. ITBI - a Consumer Unit monthly income file categorized by UCC.
2
5. ITII - a Consumer Unit monthly imputed income file categorized by UCC.1
6. NTAXI - a file with federal and state tax information for each tax unit in the CU.2
2.1.2 “Annual” or “5 quarter” files
The Interview EXPN files contain expenditure and non-expenditure information collected directly
from all major sections of the quarterly Interview survey. For each PUMD release, there are roughly
50 annual EXPN datasets, with each dataset corresponding to a specific section of the Interview
survey (http://www.bls.gov/cex/csxsurveyforms.htm#interview). Because these datasets cor-
respond directly to the Interview survey sections, there are varying reference periods for the expen-
ditures contained within each EXPN dataset, dependent upon the questions within each section.
Each annual EXPN dataset is made up of the five quarters of data within each release.
2.1.3 Paradata
Beginning in 2009, the CE began releasing paradata, which is data about the interview process.
Paradata is available in two datasets:
1. FPAR - a file with data about the survey, including timing for each section and whether the
respondent used records.
2. MCHI - a file with data about the contact history between the field representative and the
respondent, including reasons for interview refusal and time of contact.
Typically, each paradata file has nine quarters of data, starting with Q1 from the (RELEASE YEAR
- 1) to Q1 from the (RELEASE YEAR + 1). Nine quarters are included within each PARADATA
file so users can have paradata records across all interviews for a given CU. (A CU completing their
last interview during Q1 of (RELEASE YEAR) has the potential to have had their first (bounding)
interview during Q1 of (RELEASE YEAR - 1)).3
2.2 Diary Survey Data
2.2.1 Quarterly files
“Quarter” refers to the calendar quarter in which the Diary booklet was placed in the home of the
CU by the Census Field Representative. All Diary files are organized as quarterly files. Those
include:
1. FMLD - a file with characteristics, income, weights, and summary level expenditures for the
CU.
2. MEMD - a file with characteristics and income for each member in the CU.
3. EXPD - a detailed weekly expenditure file categorized by UCC.
1Available beginning in 2004
2Available beginning in 2013Q2
3With the 2009 PUMD release, historical paradata for 2005-2007 were released. The dataset for 2005 contains 3
quarters of data, while the datasets for 2006 and 2007 contains 4 quarters of data each.
3
4. DTBD - a detailed annual income file categorized by UCC.
5. DTID - a Consumer Unit imputed income file categorized by UCC.4
2.3 File naming conventions
The naming conventions used for each PUMD release is common to both Interview and Diary data.
YY stands for the two digit year and Qstands for the calendar quarter of the Interview or calendar
quarter of the placement of the Diary booklet. Below, the example file directories and names are
for SAS datasets. The only difference in the naming convention for other dataset types (i.e., SPSS,
STATA, etc.) is the file extension.
2.3.1 File names and directories
Interview quarterly files
FMLI \INTRVWYY \FMLIYYQ.sas7bdat
MEMI \INTRVWYY \MEMIYYQ.sas7bdat
MTBI \INTRVWYY \MTBIYYQ.sas7bdat
ITBI \INTRVWYY \ITBIYYQ.sas7bdat
ITII \INTRVWYY \ITIIYYQ.sas7bdat
NTAXI \INTRVWYY \NTAXIYYQ.sas7bdat
Interview annual files
Note: Only selected EXPN files are listed here. All other EXPN files follow the same convention.
CLA \EXPNYY \CLAYY.sas7bdat
IHB \EXPNYY \IHBYY.sas7bdat
VEQ \EXPNYY \VEQYY.sas7bdat
Diary quarterly files
FMLD \DIARYYY \FMLDYYQ.sas7bdat
MEMD \DIARYYY \MEMDYYQ.sas7bdat
EXPD \DIARYYY \EXPDYYQ.sas7bdat
DTBD \DIARYYY \DTBDYYQ.sas7bdat
DTID \DIARYYY \DTIDYYQ.sas7bdat
4Available beginning in 2004.
4
2.3.2 What’s the “X” about?
You may have noticed there is an “X” in the name for some of the Interview quarterly files (eg.
FMLIYY 1x.sas7bdat or MEMIYY 1x.sas7bdat). You may have also noticed that this “X” is only
in the name of quarter 1 files for the current calendar year. This is because files for the first quarter
of any calendar year will appear in two CE PUMD releases:
1. As the “fifth” quarter file in the previous calendar year’s release,
2. And as the “first” quarter file in the current calendar year’s release.
The “X” signifies that the first quarter file of the current calendar year release is not identical to
the fifth quarter file of the previous calendar year release. One reason the files are not identical is
because PUMD production processes use the five quarters of data within the release to calculate
certain values, such as the critical and topcode values of income and expenditures. During years in
which there was a sample design change, there is a bigger difference in the “X” files. For example,
the CE changed its sample design in 2005Q1. When this happens, the CE draws an “overlapping
sample” for 2005Q1, i.e., some CUs are for the old design, some CUs are for the new design, and
some are for both designs.5For the 2004 PUMD release, the CUs in the 2005Q1 files are those for
the old design. For the 2005 PUMD release, the CUs in the 2005Q1 files are those for the new
design. CUs that were in both the old and new designs are contained within the 2005Q1 file for
both the 2004 and 2005 PUMD releases.
3 PUMD file content overview
NEWID, the unique identifier for each CU, is included within every record on each data file.
It can be used to link records of a particular CU across files. For example, linking demographic
information in the Interview FMLI file to expenditure information in the MTBI file. Be aware that
the samples from the Interview and Diary surveys are independent, so there is no CU contained
within both the Interview and Diary files.
3.1 Interview quarterly files
3.1.1 FMLI-CU characteristics, income, and summary expenditure variables
There exists one record per CU.
Each CU is uniquely identified by NEWID.
Variables include demographics for the reference person and spouse of reference person, income
at the CU level, sample housing unit information, summary level expenditures, and weighting
variables.
Note: Not all the variables within the FMLI file are shown in the sample below.
5CUs can be in both the old and new designs because the designs are based on areas of the United States called
Primary Sampling Units (PSU). So if a CU was in a PSU that was in both designs, then they are used in both designs.
5
NEWID AGE_REF FAM_SIZE FINCBTXM FDAWAYPQ FDAWAYCQ FINLWT21
1 2545235 82 2 11807.0 0 0 1980.829
2 2545245 69 3 33773.0 370 0 22347.181
3 2545255 22 1 11000.0 180 0 15272.973
4 2545275 57 1 163793.8 680 0 14774.904
5 2545305 45 2 116227.0 770 0 18557.247
6 2545355 37 1 120000.0 2000 0 16921.900
7 2545365 29 4 31400.0 625 0 15776.683
8 2545375 53 2 200.0 1530 0 15271.262
9 2545385 64 1 60000.0 455 0 16723.973
10 2545405 46 2 84608.2 1540 0 16474.727
3.1.2 MEMI-CU member characteristics and income
There exist multiple records per CU.
There exists one record per member.
Unique records are defined by the combination of NEWID and MEMBNO.
Variables include demographics about CU members, member level income, and member re-
lationship status to the reference person.
Note: Not all the variables within the MEMI file are shown in the sample below.
NEWID MEMBNO AGE CU_CODE EARNER EDUCA SEX MEMBRACE SALARYXM
1 2667582 4 1 3 NA NA 1 1 1
2 2667602 1 26 1 1 2 1 1 745
3 2667602 2 23 0 1 5 2 1 3282
4 2667602 3 2 3 NA NA 1 1 1
5 2667612 1 22 1 1 5 1 4 871
6 2667612 2 24 6 1 5 1 4 1605
7 2667612 3 57 7 1 4 1 4 817
8 2667612 4 49 7 2 4 2 4 1
9 2667642 1 29 1 1 4 1 1 312
10 2667652 1 28 1 1 7 1 1 1
3.1.3 MTBI-Monthly expenditure file classified by UCC
There exist multiple records per CU.
There exists one record per expenditure per purchase month/year.
Prior to the 2010 PUMD release, unique records were not identified. From the 2010 re-
lease forward, unique records can be identified using a combination of NEWID, EXPNAME,
SEQNO, and ALCNO.
The monthly expenditure amounts are mapped from corresponding EXPN variables.
6
Note: Not all the variables within the MTBI file are shown below.
NEWID UCC COST COST_ GIFT PUBFLAG REF_MO REF_YR
1 2554935 210110 232 1 2 2 3 2013
2 2554935 210110 232 1 2 2 2 2013
3 2554935 210110 232 1 2 2 1 2013
4 2545765 210110 600 1 2 2 3 2013
5 2545765 210110 600 1 2 2 2 2013
6 2545765 210110 600 1 2 2 1 2013
7 2562785 210110 500 1 2 2 4 2013
8 2562785 210110 500 1 2 2 3 2013
9 2562785 210110 500 1 2 2 2 2013
10 2560385 210110 660 1 2 2 4 2013
3.1.4 ITBI-Consumer Unit monthly income classified by UCC
There exist multiple records per CU.
There exists one record per income item per month/year.
Unique records are defined by NEWID, UCC, REFMO, and REFYR.
The monthly amounts are mapped from the corresponding CU-level imputed income mean
values.
Note: This ITBI sample shows ALL variables that are in the full ITBI file.6
NEWID REFMO REFYR UCC PUBFLAG VALUE VALUE_
1 2545235 1 2013 5100 2 520.8333 NA
2 2545235 2 2013 5100 2 520.8333 NA
3 2545235 3 2013 5100 2 520.8333 NA
4 2545235 1 2013 5110 2 520.8333 NA
5 2545235 2 2013 5110 2 520.8333 NA
6 2545235 3 2013 5110 2 520.8333 NA
7 2545235 1 2013 5200 2 2500.0000 NA
8 2545235 2 2013 5200 2 2500.0000 NA
9 2545235 3 2013 5200 2 2500.0000 NA
10 2545235 1 2013 5210 2 2500.0000 NA
3.1.5 ITII-Consumer Unit monthly imputed income file classified by UCC.
There exist multiple records per CU.
There exists one record per income item per month/year.
Unique records are defined by NEWID, UCC, REFMO, REFYR, and IMPNUM.
6The dataset views in this document were generated using R, which represents missing values as “NA.” Other
statistical software packages may represent missing values as a period, blank space, or in another manner.
7
The monthly amounts are mapped from the corresponding CU-level imputed income im-
putes(5 imputes per income item).
This file is necessary to calculate variances and standard errors for imputed income.
Note: This ITII sample shows ALL variables that are in the full ITII file.
NEWID REFMO REFYR UCC PUBFLAG VALUE VALUE_ IMPNUM
1 2545235 1 2013 900030 2 982.8333 NA 1
2 2545235 1 2013 900030 2 982.8333 NA 2
3 2545235 1 2013 900030 2 982.8333 NA 3
4 2545235 1 2013 900030 2 982.8333 NA 4
5 2545235 1 2013 900030 2 982.8333 NA 5
6 2545235 2 2013 900030 2 982.8333 NA 1
7 2545235 2 2013 900030 2 982.8333 NA 2
8 2545235 2 2013 900030 2 982.8333 NA 3
9 2545235 2 2013 900030 2 982.8333 NA 4
10 2545235 2 2013 900030 2 982.8333 NA 5
3.1.6 NTAXI-Federal and state tax information classified by tax unit
There may exist multiple records per CU.
There exists one record per tax unit.
Unique records are defined by the combination of NEWID and TAX UNIT.
Variables include federal and state tax rates, tax liabilites, and various tax-related character-
istics of the tax unit.
Note: Not all the variables within the NTAXI file are shown in the sample below.
NEWID TAX_UNIT DEPCNT FILESTAT SRATE_CY SRATE_PY
1 2545235 1 2 3 0.0000 0.0000
2 2545245 1 2 3 0.0000 0.0000
3 2545255 1 0 1 0.0000 0.0653
4 2545275 1 0 1 0.0575 0.0575
5 2545305 1 0 2 0.0475 0.0475
6 2545355 1 0 1 0.0758 0.0764
7 2545365 1 2 2 0.0930 0.0930
8 2545375 1 2 3 0.0000 0.0000
9 2545385 1 0 1 0.0610 0.0610
10 2545405 1 1 3 0.0400 0.0400
3.2 Interview annual files–EXPN
Each EXPN file is different, with some having multiple records per CU and others with one
record or no records per CU interviewed each quarter.
8
Unique records are defined differently in each file.
Common variables to all EXPN files: NEWID is the unique CU identifier. QYEAR defines
the year and interview quarter for a given record. SEQNO is assigned sequentially during
the interview as each expenditure record is recorded into the database. ALCNO is assigned
sequentially for each record that has been allocated from one expenditure during the process.
For example, a CU may report spending $50 on a pair of men’s pants and a shirt. The CE
will allocate out that record into separate records, one for men’s pants and shorts($30) and
one for men’s shirts($20). REC ORIG describes the origin of the record, i.e., whether the
expenditure data was collected during the current interview, expenditure data collected for
a current reference period in a previous interview, household inventory data collected during
a previous interview that was pulled forward to the current, or data that was created by the
CE processing edit system.
Variables include those directly collected from the Interview survey questionnaire on expen-
ditures and screener questions. Variables that are recalculated by CE are also included.
Examples:
3.2.1 CLA-Clothing and sewing materials
Unique records in CLA are defined by the combination of NEWID, SEQNO, and ALCNO.
CLOTHYA is an item code variable for the type of clothing expenditure (suits, dresses,
undergarments, etc.)
CLOTHMOA is an indicator variable for the month in which the purchase occurred.
CLOTHXA is the amount of the clothing expense.
Note: Not all the variables within the CLA file are shown below.
QYEAR NEWID SEQNO ALCNO CLOTHYA CLOTHMOA CLOTHXA
1 20131 2511505 15 0 140 12 204
2 20131 2511555 13 0 270 11 1
3 20131 2511555 13 1 200 11 203
4 20131 2511555 13 2 210 11 4
5 20131 2511555 13 3 190 11 725
6 20131 2511565 15 0 275 12 1
7 20131 2511565 15 1 190 12 572
8 20131 2511565 15 2 150 12 78
9 20131 2511565 16 0 140 12 658
10 20131 2511565 17 0 200 12 759
3.2.2 IHB-Hospitalization and health insurance detailed questions
Unique records in IHB defined by NEWID, SEQNO, ALCNO, and HHIPDLIB.
9
HHIPDLIB is the policy number for the health insurance plan. This number is derived by
the order in which the respondent lists their health insurance plans.
HHICOVQ is the number of people covered by health insurance plan.
QHI3MCX is the amount paid in health insurance premiums during the reference period
(derived by CE).
HHICODE is an indicator variable for the type of insurance plan (HMO, FFS, Medicare
supplement, or other special purpose plan).
Note: Not all the variables within the IHB file are shown below.
QYEAR NEWID SEQNO ALCNO HHIPDLIB HHICOVQ QHI3MCX HHICODE
1 20131 2511505 24 0 1 3 2 2
2 20131 2511505 25 0 2 2 2 2
3 20131 2511555 30 0 1 1 1075 1
4 20131 2511555 31 0 2 1 1297 1
5 20131 2511555 32 0 3 1 1297 1
6 20131 2511565 27 0 1 1 1 1
7 20131 2511565 29 0 3 1 1 4
8 20131 2511575 33 0 1 4 1 1
9 20131 2511585 35 0 1 2 1 2
10 20131 2511595 37 0 2 2 329 1
3.2.3 VEQ-Vehicle maintenance and repair
Unique records in VEQ defined by NEWID, SEQNO, and ALCNO.
VOPSERVY is an indicator variable that decribes the type of maintenance or repair untaken.
VOPMOA is an indicator variable for the month in which the expense occurred.
VOPEXPX is the total cost of the maintenance or repair expense.
Note: Not all the variables within the VEQ file are shown below.
QYEAR NEWID SEQNO ALCNO VOPSERVY VOPMOA VOPEXPX
1 20131 2511505 63 0 100 12 275
2 20131 2511575 61 0 100 11 103
3 20131 2511595 76 0 370 12 201
4 20131 2511625 39 0 115 11 819
5 20131 2511625 39 1 100 11 1
6 20131 2511625 39 2 110 11 1
7 20131 2511675 54 0 100 11 715
8 20131 2511695 126 0 100 12 808
9 20131 2511695 127 0 365 10 417
10 20131 2511695 128 0 365 11 382
10
3.3 Diary files
Most Diary files are analogous to Interview files.
There are slightly different variable names in the Diary files.
The summary level expenditures in the Diary FMLD file are not as extensive as those in the
Interview FMLI file.
3.3.1 FMLD-CU characteristics, income, weights, and summary level expenditures
Analogous to FMLI file in Interview.
Note: Not all the variables within the FMLD file are shown below.
NEWID STRTMNTH WEEKI CUTENURE AGE_REF AGE2 FOODHOME FINLWT21
1 1451201 4 1 1 70 50 52.43 34683.44
2 1451202 5 2 1 70 50 14.00 34683.44
3 1451211 4 1 4 33 1 0.00 31140.85
4 1451212 4 2 4 33 1 28.03 31140.85
5 1451221 4 1 3 88 65 0.00 40310.51
6 1451222 4 2 3 88 65 0.00 40310.51
7 1451241 5 1 1 43 19 152.65 35929.24
8 1451242 5 2 1 43 19 124.05 35929.24
9 1451261 4 1 2 31 1 108.78 33222.60
10 1451262 5 2 2 31 1 61.03 33222.60
3.3.2 MEMD-CU member characteristics and income
Analogous to MEMI file in Interview.
Note: Not all the variables within the MEMD file are shown below.
NEWID MEMBNO AGE EDUCA MARITAL EMPLTYPE WAGEXM
1 1451201 1 70 5 1 NA 1
2 1451201 2 68 5 1 NA 1
3 1451202 1 70 5 1 NA 1
4 1451202 2 68 5 1 NA 1
5 1451211 1 33 5 3 NA 1
6 1451211 2 9 NA 5 NA 1
7 1451211 3 8 NA 5 NA 1
8 1451211 4 8 NA 5 NA 1
9 1451212 1 33 5 3 NA 1
10 1451212 2 9 NA 5 NA 1
11
3.3.3 EXPD-Detailed weekly expenditure file categorized by UCC
Analogous to MTBI files in Interview.
There are multiple records per CU.
There is one record per expenditure per purchase month/year.
Unique records are not defined.
The weekly amounts are recorded directly from listings in the completed Diary.
Note: Not all the variables within the EXPD file are shown below.
NEWID ALLOC COST GIFT PUB_FLAG EXPNSQDY UCC
1 1451201 0 6.63 2 2 7 10210
2 1451201 0 1.40 2 2 1 20210
3 1451201 0 1.60 2 2 1 110210
4 1451201 0 42.80 2 2 1 170310
5 1451201 0 10.00 2 2 6 190111
6 1451201 0 24.00 2 2 5 190112
7 1451201 0 10.00 2 2 4 190211
8 1451201 0 2.00 2 2 5 190321
9 1451201 0 8.00 2 2 1 190322
10 1451201 0 2.00 2 2 3 190322
3.3.4 DTBD-Detailed annual income file categorized by UCC
Analogous to ITBI file in Interview.
Note: This DTBD example shows ALL variables that are in the full DTBD file.
NEWID UCC AMOUNT AMOUNT_ PUB_FLAG
1 1451201 900030 46918 NA 1
2 1451201 980000 46918 1 1
3 1451201 980010 2 NA 1
4 1451201 980020 70 NA 1
5 1451201 980040 2 NA 1
6 1451201 980060 2 NA 1
7 1451201 980070 46918 1 1
8 1451201 980090 100 NA 1
9 1451201 980210 100 NA 1
10 1451201 980230 100 NA 1
3.3.5 DTID-Consumer Unit imputed income file categorized by UCC.
Analogous to the ITII file.
Note: This DTID example shows ALL variables that are in the full DTID file.
12
NEWID UCC PUB_FLAG AMOUNT AMOUNT_ IMPNUM
1 1451201 900030 1 46918 NA 1
2 1451201 900030 1 46918 NA 2
3 1451201 900030 1 46918 NA 3
4 1451201 900030 1 46918 NA 4
5 1451201 900030 1 46918 NA 5
6 1451201 980000 1 46918 1 1
7 1451201 980000 1 46918 1 2
8 1451201 980000 1 46918 1 3
9 1451201 980000 1 46918 1 4
10 1451201 980000 1 46918 1 5
4 Documentation
To aid in using the PUMD, the CE produces annual user guides and data dictionaries. Since the
2007 PUMD release, the user guides and data dictionaries, for both Interview and Diary data, have
been parsed out into separate documents. Prior to 2007, the user guides and data dictionaries were
combined in one document. The user documentations include:
A summary of changes from the previous release of CE PUMD.
More in depth information of the PUMD files.
Information on CE PUMD nondisclosure requirements.
Formulas and procedures for estimating aggregate statistics from the data.
Data reliability statements.
And other information, including information on sampling design and cooperation levels.
The data dictionaries include a listing of all the CE PUMD variables and descriptions. User guides
and data dictionaries dating back to the 1996 release, along with other miscellaneous documenta-
tions, can be accessed online at the CE website, http://www.bls.gov/cex/csxmicrodoc.htm.
13

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