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|
1995 Survey of consumer
Finances Here: Introduction Next: |
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| 1.Introduction | |
| 2.Question Text, Variable Names, & Responses | |
| 3.Interview Program | |
| 4.CAPI-database Concordance | |
| 5.Net Worth Program | |
| 6.Public Data Set Variable List |
For a general overview of the 1995 SCF, see Arthur B. Kennickell, Martha Starr-McCluer, and Annika E. Sunden, "Family Finances in the U.S.: Evidence from the Survey of Consumer Finances," Federal Reserve Bulletin, January 1997. (102 KB PDF | 1.2 MB Postscript) Results you may obtain from using this release of the 1995 SCF may differ from those reported in this article for several reasons. First, the Bulletin article is based on an earlier version of the data. Second, the analysis weights used in that article were altered to provide robust estimates of the detailed categories shown: In brief, the data were examined for extreme outliers, and where a given case was overly influential in determining an outcome, the weight was trimmed and other weights were inflated to maintain a constant population. Finally, as noted below, the public version of the data has been systematically altered to minimize the likelihood that unusual individual cases could be identified. Our analysis of the public dataset suggests that these changes should not alter the conclusions of reasonable analyses of the data.
QUESTIONNAIRE
The 1995 SCF was collected using computer-assisted personal
interviewing (CAPI). Thus, there is no questionnaire in the usual
sense. This codebook serves as the authoritative guide to the
definitions of variables included in the survey. At the end of this
file, a copy of the Autoquest (Surveycraft) Interview Program that was used to
collect the data is included. The AQ program serves as the
authoritative reference for questions relating to question ordering
and skip sequences. Because question ordering is important in
understanding the meaning of many questions, users of the data are
encouraged to consult the AQ program. In the survey dataset,
many variables have been moved, recoded, or inferred; almost always
such changes can be identified from the shadow variables associated
with the variables. At the very end of this file, a translation of
most AQ variables into SCF variables is provided, see the section
entitled CAPI-Database Concordance.
However, as noted there, this list is incomplete.
Nevertheless, a diligent user should
be able to deduce the relationship between all the variables.
FILES INCLUDED
The full public dataset consists of two pieces in addition to this
codebook file. The main
dataset,
which contains most of the survey
variables, is a 470 megabyte file (typically stored as a SAS transport
file in zipped form: 8.2 megabytes in this form). A file of of 49.1
megabytes (23.5 megabytes in zipped transport form) contains 999
replicate weights and multiplicity factors intended to be used for
variance estimation.
VARIABLE NAMES
The main data values are stored in the SAS dataset using variable
names prefixed by an "X." We have tried, insofar as it was possible,
to retain the variable numbering system used in earlier SCFs. Where
the content of a variable has changed in a substantive way, we have
assigned a new variable number. A small number of questions were
added, and a small number were deleted. Each of the variables in the
main dataset has a "shadow" variable that describes--in almost all
cases--the original state of the variable (i.e., whether it was
missing for some reason, a range response was given, etc.). An
exception is reported values which have been imputed or otherwise
altered to protect the privacy of respondents (see below); such values
are not flagged in any systematic way. Users who so desire may use
the shadow variables to restore the data to something very close to
their original condition. The shadow variables have the same numbers
as the main variable, but have a prefix of "J." A list of the values
taken by the shadow variables is given in the section below entitled
"DISCUSSION OF RANGE DATA COLLECTION AND J-CODES."
UNIT OF ANALYSIS
Most of the data in the survey are for a subset of the household unit
referred to as the "primary economic unit" (PEU). In brief, the PEU
consists of an economically dominant single individual or couple
(married or living as partners) in a household and all other
individuals in the household who are financially dependent on that
individual or couple. For example, in the case of a household
composed of a married couple who own their home, a minor child, a
dependent adult child, and a financially independent parent of one of
the members of the couple, the PEU would be the couple and the two
children. Summary information is collected at the end of the
interview for all household members who are not included in the PEU.
Throughout the codebook, we refer to the "head" of the household. The
use of this term is euphemistic and merely reflects the systematic way
in which the dataset is organized. The head is taken to be the single
core individual in a PEU without a core couple. In a PEU with a
central couple, the head is taken to be either the male in a mixed-sex
couple or the older individual in the case of a same-sex couple. No
judgment about the internal organization of the households is implied
by this organization of the data. When the original respondent was
someone other than the person determined to be the head in this sense,
all data (including response codes) were systematically swapped with
that person's spouse or partner. The variable X8000 indicates which
cases have been subjected to such rearrangement.
IMPUTATION
The missing data in the survey have been imputed five times by drawing
repeatedly from an estimate of the conditional distribution of the
data. These imputations are stored as five successive replicates
("implicates") of each data record. Thus, the number of observations
in the dataset (21,495) is five times the actual number of respondents
(4299); see below in the weight section of the codebook for a
discussion of the use of these implicates. The imputation procedure
is described in detail in "Imputation of the 1989 Survey of Consumer
Finances: Multiple Imputation and Stochastic Relaxation", by Arthur
Kennickell. For a general discussion of multiple imputation and its
uses, see Multiple Imputation for Nonresponse in Surveys by Donald
B. Rubin, John Wiley and Sons, 1987. The multiple imputations allow
users to estimate the amount of uncertainty in estimates that is due
to imputation. For users who want to estimate only simple statistics
such as means and medians ignoring imputation error, it will probably
be sufficient to divide the weights by 5. Users who want to estimate
regressions should be cautious in their treatment of the
implicates. Many regression packages will treat each of the five
implicates as an independent observation and correspondingly inflate
the reported significance of results. Users who want to calculate
regression estimates, but who have no immediate use for proper
significance tests (perhaps for exploratory work), could either
regress the average of the dependent and independent values across the
implicates, or multiply the standard errors of the regression (on all
observations) by the square root of five. For an easily
understandable discussion of multiple imputation in the SCF from a
user's point of view, see Catherine Montalto and Jaimie Sung,
"Multiple Imputation in the 1992 Survey of Consumer Finances,"
Financial Counseling and Planning, Volume 7, 1996, pages 133-146 (or
on the Internet at http://www.hec.ohio-state.edu/hanna/imput.htm).
"OTHER" CODES
In almost every case where a respondent could supply a response that
did not fit in the codeframe offered to interviewers on their computer
screens, the CAPI program was constructed to allow the entry of a
verbatim response. There were a few open-ended questions that were
set up to accept only a verbatim response. All of these responses were
run through a standard coding process at NORC. Once the data were at
the FRB, strenuous efforts were made to resolve all instances of
responses that remained coded as "other." Because all verbatim
responses were captured by the CAPI program, the resolution
process was simplier than in the past. Such responses that remain
are unusual legitimate responses which do not fit within the
existing codeframe, and because they appear unlikey to reoccur in future
surveys, the codeframe was not augmented. Responses that were not
informative were treated as missing values and were imputed. In the
1992 survey, scanned images of the paper questionniares were stored on
CD ROM, and all "other" responses were looked up. However, because
the collection of verbatim responses was not enforced to the degreee
that is possible with CAPI, a substantial fraction of cases contained
no additional information. Thus, there is a larger fraction of
unresolved "other" responses in 1992 than in 1995. In 1989, it
appears that the SCF coders were more successful than in 1992 in
resolving "other" responses. Because of the different treatment of
verbatim responses over time, analysts should exercise caution in
time series comparisons of "other" responses.
ANALYSIS WEIGHTS
Because the SCF sample is not an equal-probability design, weights
play a critical role in interpreting the survey data. The main
dataset contains the final nonresponse-adjusted sampling weights.
These weights are intended to compensate for unequal probabilities of
selection in the original design and for unit nonresponse (failure to
obtain an interview). The weight (X42001) is a partially design-based
weight constructed at the Federal Reserve using original selection
probabilities and frame information along with aggregate control
totals estimated from the Current Population Survey. The population
defined by the weights for *each implicate* (see above) is 99.0
million households. This weight is a relatively minor revision of the
consistent weight series (X42000) maintained for the SCFs beginning
with 1989 (For a detailed discussion of these weights, see "Consistent
Weight Design for the 1989, 1992, and 1995 SCFs and the Distribution of
Wealth," by Arthur B. Kennickell and R. Louise Woodburn, Review of
Income and Wealth, Series 45, Number 2, June 1999, pp. 193-215 or the
longer version given on the SCF web site at
http://www.federalreserve.gov/pubs/oss/oss2/method.html). The nature
of the revisions to the consistent weights is described in "Revisions
to the SCF Weighting Methodology: Accounting for Race/Ethnicity and
Homeownership," by Arthur Kennickell (see SCF web site). A version of
the revised weight has been computed for all the surveys beginning
with 1989, and this variable has been added to the public versions of
the SCF datasets. Users should be aware that the sum of each of the weights
over all sample cases and imputation replicates is equal to five times
the number of households in the sample universe.
Although the weights should produce reliable results at the level of
broad aggregates (e.g., net worth and income ), it is important to
remember that many of the variables collected in the SCF are highly
skewed in their distribution and that many such variables will apply
to only a relatively small fraction of the sample. In the SCF group
at the Federal Reserve, we routinely review our calculations for the
presence of overly-influential outliers, and robust techniques are
applied when appropriate. We encourage other users to exercise
similar care in analyzing the data. Users who use the SAS procedure
PROC UNIVARIATE are particularly warned to use the FREQ option (as
opposed to the WEIGHT option) to obtain weighted medians.
SAMPLING ERROR
Because we are unable to give users any sample information about cases
in the dataset, they will be unable on their own to compute
reasonable estimates of the sampling variances of their estimates. To
facilitate such estimation, we have included two files of replicate
weights and multiplicity factors--one corresponding to X42000 and one
to X42001. Using detailed information about the original sample
design, we selected 999 sample replicates from the final set of
completed cases in a way intended to capture the important dimensions
of sample variation (Arthur Kennickell, Douglas McManus and Louise
Woodburn, "Weighting design for the 1992 Survey of Consumer Finances"
(HTML | 2.6 MB Postscript) for details).
For each survey case and each replicate, the file
contains a weight (WT1B1-WT1B999) and the number of times the case was
selected in the replicate (MM1-MM999). We computed weights for each
replicate using exactly the same procedures we used for the main
weights. Replicate weights were computed only for the first implicate
of each case. For most purposes, users will probably want to multiply
the weight times the multiplicity: in all cases the sum of each of the
weights times the corresponding multiplicities of the cases equals the
total number of households. To estimate the sampling variance of the
mean of family income, for example, a user would estimate the mean 999
times using the replicate weights and compute the standard error of
that estimate. An estimate of the total standard error is given by
SQRT((6/5)*imputation variance + sampling variance).
A simple SAS program to compute the standard error due to sampling and
imputation for the mean and median of a given variable is provided
below. This program may be adapted easily for other types of
calculations. To conserve on necessary memory, the program computes
sampling error using blocks of 100 replicate weights rather than the
full set at once. Users with large amounts of RAM may wish to
increase the size of these blocks, and those with smaller amounts may
wish to decrease the size.
SUMMARY VARIABLES
DISCLOSURE REVIEW
It is important to note that aside from the cell collapsing, there is
no key in this codebook or in the dataset that would allow users to
identify directly either which data items have been smoothed or
otherwise altered, or which cases were selected for imputation of
critical values (that is, the shadow variables in this dataset may not
always reflect the true original status of every variable). Although
this blurring of the data will have some effect on analysis, that
effect should be negligible in most cases. For further details
on the procedures taken to protect the identity of respondents, see
"Disclosure Review and Its Implications for the 1992 Survey
of Consumer Finances" by Gerhard Fries, Barry Johnson, and R. Louise
Woodburn (1997 working paper, SCF group, Federal Reserve Board).
Users who feel that the restrictions imposed on the public dataset are
too constricting are encouraged to submit written proposals for
expanded data release, and those requests will be given serious
consideration in the release of data from future surveys.
Dollar variables have been rounded according to the following scheme:
CASE ID NUMBERS
DATA REVIEW
CONTACT INFORMATION
* MACRO MEANIT;
* AK: May 1, 1997 version;
* DSN specifies the name of the dataset to be used (the dataset
should contain the following: the main weight renamed as WGT0, a
set of variables WGT1-WGT999 equal to the replicate weights
multiplied by the corresponding multiplicity factors, a variable
for which one wishes to compute the standard error due to
imputation and sampling for the mean and median, and a variable
IMPLIC equal to the implicate number of each case)
VAR contains the name of the variable for which one desires
standard errors
PFLAG: blank prints interim statistics/any character string
(e.g., NO) surpresses printing;
%MACRO MEANIT(DSN=,VAR=,PFLAG=);
* compute global mean/median;
PROC UNIVARIATE DATA=&DSN;
FREQ WGT0;
VAR &VAR;
RUN;
* rank order the data for the median calculation;
PROC SORT DATA=&DSN;
BY &VAR;
RUN;
PROC IML WORKSPACE=10000000 SYMSIZE=5000;
RESET LOG LINESIZE=78;
* first imputation variance;
EDIT &DSN;
TEMP={IMPLIC &VAR WGT0};
READ ALL VAR TEMP INTO MDATA;
* total population;
POP=SUM(MDATA[,3])/5;
* create matrix to hold values of means/medians by implicates;
IM=SHAPE(0,1,5);
ID=SHAPE(0,1,5);
* compute mean/median;
DO I=1 TO 5;
IMP=MDATA[LOC(MDATA[,1]=I),2:3];
* compute mean;
MM=IMP[,1]#IMP[,2];
IM[1,I]=MM[+,]/POP;
* compute median;
DD=IMP[RANK(IMP[,1]),];
DD[,2]=CUSUM(DD[,2])/POP;
ID[1,I]=DD[MIN(LOC(DD[,2]>=.5)),1];
FREE IMP MM DD;
END;
FREE MDATA;
%IF (&PFLAG EQ ) %THEN %DO;
PRINT IM ID;
%END;
* next sampling variance;
* create matrix to hold values of means/medians by replicates;
RM=SHAPE(0,1,999);
RD=SHAPE(0,1,999);
%DO I=1 %TO 10;
%PUT CLUMP NUMBER &I;
%IF (&I EQ 1) %THEN %DO;
%LET TOP=99;
%LET BOT=1;
%LET LEN=100;
%END;
%ELSE %DO;
%LET BOT=%EVAL(&TOP+1);
%LET TOP=%EVAL(&TOP+100);
%LET LEN=101;
%END;
%LET WSTR=%STR();
%DO J=&BOT %TO ⊤
%LET WSTR=&WSTR WGT&J;
%END;
EDIT &DSN;
TEMP={&VAR &WSTR};
READ ALL VAR TEMP WHERE (IMPLIC=1) INTO MDATA;
* compute means;
MEAN=MDATA[,2:&LEN]#MDATA[,1];
RM[,&BOT:&TOP]=MEAN[+,]/POP;
* compute medians;
DO I=2 TO &LEN;
MDATA[,I]=CUSUM(MDATA[,I])/POP;
RD[&BOT+I-2]=MDATA[MIN(LOC(MDATA[,I]>=.5)),1];
END;
FREE MDATA;
%END;
%IF (&PFLAG EQ ) %THEN %DO;
PRINT RM RD;
%END;
* finally, compute standard error wrt imputation/sampling;
* (X-X-bar)**2/(n-1);
IVM=(IM-IM[,+]/5)##2;
IVM=IVM[,+]/4;
IVD=(ID-ID[,+]/5)##2;
IVD=IVD[,+]/4;
RVM=(RM-RM[,+]/999)##2;
RVM=RVM[,+]/998;
RVD=(RD-RD[,+]/999)##2;
RVD=RVD[,+]/998;
* SQRT(((ni+1/(ni))*SIGMAI**2) + SIGMAR**2));
TVM=SQRT((6/5)*IVM+RVM);
TVD=SQRT((6/5)*IVD+RVD);
IVM=SQRT(IVM);
IVD=SQRT(IVD);
RVM=SQRT(RVM);
RVD=SQRT(RVD);
PRINT "STD DEV IMPUTATION: MEAN: " IVM " MEDIAN: " IVD;
PRINT "STD DEV SAMPLING: MEAN: " RVM " MEDIAN: " RVD;
PRINT "COMBINED STD DEV: MEAN: " TVM " MEDIAN: " TVD;
QUIT;
%MEND MEANIT;
* create dataset from main dataset and replicate weight file;
DATA DAT(KEEP=NW IMPLIC WGT0-WGT999);
MERGE xxx.main_ds(KEEP=Y1 X42001 ...)
xxx.rep_wgts(KEEP=Y1 MM1-MM999 WT1B1-WT1B999);
BY Y1;
* multiply replicate weights by the multiplicity;
ARRAY MULT {*} MM1-MM999;
ARRAY RWGT {*} WT1B1-WT1B999;
ARRAY WGTS {*} WGT1-WGT999;
DO I=1 TO DIM(MULT);
* take max of multiplicity/weight: where cases not selected for
a replicate, there are missing values in these variables;
WGTS{I}=MAX(0,MULT{I})*MAX(0,RWGT{I});
END;
WGT0=X42001;
* define implicate number of case;
IMPLIC=Y1-10*YY1;
* define net worth (for example);
NW=.......;
RUN;
* run the macro;
%MEANIT(DSN=DAT,VAR=NW);
We have not made an effort to include summary variables (e.g., net
worth) in the dataset. Although it is complicated to construct such
variables, it is our belief that a substantial amount of judgment is
involved in selecting which variables to include, and that other
analysts should make their own decisions. However, as a guide to
users, we have included at the end some SAS
code to compute net worth
according to our routine definitions.
To protect the privacy of individual respondents, the data in this
release have been systematically altered by several means to
minimize the possibility of identifying any survey respondent. For
some discrete variables, small or unusual cells were collapsed as
noted in the variable descriptions in the next section of the codebook.
Continuous variables were
rounded. Data were also blurred by other unspecified means. In
addition, a number of other cases were identified for more extensive
treatment. Some of these cases were selected on the basis of extreme
or unusual data values. Other cases were selected at random. For
each of these cases, a selection of critical variables was set to
missing and statistically imputed subject to constraints designed to
ensure that any distortions induced in key population statistics would
be minimal. The geographic identifiers here have been systematically
altered for a subset of respondents by swapping their locations with
those of otherwise similar respondents. Where relevant, the codebook
provides more detailed information on cell collapsing and other
techniques.
DO I = 1 TO DIM($VARs);
IF (0 < $_VAR < 5) THEN $_VAR=1;
ELSE IF (5 <= $_VAR < 1000) THEN $_VAR=MAX(1,ROUND($_VAR,10));
ELSE IF (1000 <= $_VAR < 10000) THEN $_VAR=ROUND($_VAR,100);
ELSE IF (10000 <= $_VAR < 1000000) THEN $_VAR=ROUND($_VAR,1000);
ELSE IF (1000000 <= $_VAR) THEN $_VAR=ROUND($_VAR,10000);
ELSE IF (-1000 <= $_VAR < - 5) THEN $_VAR=ROUND($_VAR,10);
ELSE IF (-10000 <= $_VAR < -1000) THEN $_VAR=ROUND($_VAR,100);
ELSE IF (-1000000 < $_VAR < -10000) THEN $_VAR=ROUND($_VAR,1000);
ELSE IF .Z < $_VAR <= -1000000 THEN $_VAR=-1000000;
END;
An important exception to this rounding rule is amounts that were
reported in an hourly frequency (e.g., X4112). If the hourly amount
is greater than $25, then the above rounding rule applies. Otherwise,
the amount is rounded to the nearest $.10.
Under the original numbering system (XX1), the sample design is
apparent from the identification numbers. Thus, each case included in
the public version of the dataset has been given an identification
number (YY1), which is intended to mask the knowledge of which cases
were drawn from the SCF list sample. It is not possible to know
with certainty from the information provided in the public version of
this dataset which cases derive from the list sample. Because we
routinely use the original numbers internally, users who direct
questions to us about specific cases might want to be sure to
emphasize that they are using the external ID number to avoid
confusion.
We have spent many hours searching for errors in the data. Many
seeming inconsistencies are actually in the raw data and appear to have
no obvious reconciliation. Other types of inconsistencies may have
been induced as a byproduct of imputation, even though elaborate
checks are built into the imputation routines. We ask our colleagues
who use this dataset to help us find the remaining resolvable
inconsistencies. Our presumption is always that the respondent
understood each question and reported accurately, and that the process
of transcription and coding did not distort that information. In the
relatively small number of cases where other information led us beyond
a reasonable doubt of the validity of the data, we have changed data,
either by altering values directly or by setting them to missing and
imputing them; in all such cases, the shadow variables indicate that
we have overridden reported data.
It is likely that some users will have trouble understanding the
organization of the data at first. IF AFTER HAVING FRAMED A FOCUSED
QUESTION AND EXHAUSTED ALL OF YOUR LOCAL RESOURCES, YOUR PROBLEM
PERSISTS, you may call Gerhard Fries at ((202) 452-2578 or e-mail
[email protected]) or me at ((202)-452-2247 or e-mail
[email protected])).
****We prefer correspondence via e-mail.****
While we would like to be helpful to you, please realize that we are
not set up to provide extensive services to users. We hope that by
persistence, you will almost always be able to figure out what you
need by consulting the questionnaire and the codebook below. We
should be your last resort.
DISCUSSION OF RANGE DATA COLLECTION AND J-CODES
Dollar values in the 1995 SCF were collected in a way that
takes advantage of the power of CAPI (for a detailed description and
analysis see "Using Range Techniques with CAPI in the 1995 Survey of
Consumer Finances" (HTML |
133 KB PDF | 240 KB Postscript) by Arthur B.
Kennickell (1996 working paper, SCF
group, Federal Reserve Board). In the past, we had evidence that some
respondents volunteered figures in ranges. Good interviewers have
always tried to get respondents to settle on a single "best" figure,
but sometimes it may be that there may be no firm figure (e.g., the
value of a privately-held business may be known only at the point it
is actually sold) and probing too far could cause the respondent to
answer "don't know". The 1995 survey allowed for responses to be
reported in ranges volunteered by respondents. There is another class
of respondent that may not volunteer a range, who do not know (or will
not give) an exact figure, but who will give some information about
the value. To obtain information from this second group of people, we
have included in the CAPI program two options. First, a respondent who
is uncomfortable actually saying an amount may report a letter from a
card that specifies a number of ranges. The range card has been used
very successfully in earlier waves of the SCF, but CAPI allows the
option to be presented consistently. Second, a respondent who
declines the use of the range card is asked a series of questions in a
"decision tree" that are designed to specify a range. In earlier
SCFs, the decision tree was used for people who did not know or
refused to report a figure for their total income, and in the current
Health and Retirement Survey such a procedure is used for many dollar
figures. The evidence from both sources is very encouraging. In the
1995 SCF, the decision tree breaks vary by question (so that, for
example, monthly rent is not subject to the same ranges as the value
of corporate stock). The computer sequences used for range followup
for all dollar values in the 1995 survey (known as "DKDOL") are
outlined schematically in a section below. It should be noted that
interviewers were strongly instructed that a single dollar value is
the best answer to each of these questions. Although there is the
distinct possibility that respondents may become "trained" in the use
of the range questions during the course of the interview (the effect
of this training is unclear at present: respondents may tend to report
"too many" ranges because they know that they are allowed;
alternatively, respondents may learn that it is much quicker to give a
single dollar figure), interviewers should be using all of the
standard techniques to get respondents to give a single figure where
possible.
![[SCF
logo]](../bitmaps/lorenz.gif)
Qnn. How much is your [******]?
level 1: $________ $___RANGE $______DK $__Refuse
|________________|
level 2: Confirm Range card Range card?
or dollar range?
RC DR YES NO/DK Refuse
level 3: OUT Letter Upper bound Letter Decision
Lower bound tree
level 4: OUT Confirm OUT Confirm OUT
level 5: OUT OUT
(OUT=proceed to next question)
At the first level, the respondent has the option of providing a
dollar amount (as in the past, interviewers were strongly urged to
obtain a single dollar value where possible), volunteering a range,
answering "don't know," or refusing to answer. Each of these
responses implies a different sequence of questions. In the case of a
single dollar figure, the CAPI program displays in words the number
the interviewer has typed into the computer and proceeds to the next
question. If the respondent volunteers a range, there is an option to
report either a range in dollars (and in some cases the upper or lower
bound of a range may be missing--e.g., as in the case where a
respondent answers "greater than a million dollars") or to give a
letter from a range card (the ranges are given below). If the
respondent answers "don't know" or refuses to answer, the program will
present a request to use the range card. If the respondent is unable
to use the range card (answers "no" or "don't know"), the program
presents a series of questions known as a "decision tree," which is
specified in greater detail below. If the respondent refuses when
asked to use the range card, the program proceeds to the next
question. The exact question text for this sequence is given below.
Because of software limitations, negative ranges presented a special
problem. It was not feasible to build in negative ranges directly.
As a compromise, interviewers were instructed to collect the ranges in
absolute values and record in a comment box available in the program
the fact that the range was negative.
Text presented to interviewer at level 2 if R volunteers a range:
CHOOSE:
ENTER LETTER FROM RANGE CARD
ENTER LOW END AND HIGH END OF RANGE
Text presented to interviewer at level 3 if R volunteers a range and
chooses the range card at level 2:
ENTER LETTER FROM RANGE CARD:
Possible card responses shown on range card:
A ...... $1 - $100
B ...... $101 - $500
C ...... $501 - $750
D ...... $751 - $1,000
E ...... $1,001 - $2,500
F ...... $2,501 - $5,000
G ...... $5,001 - $7,500
H ...... $7,501 - $10,000
I ...... $10,001 - $25,000
J ...... $25,001 - $50,000
K ...... $50,001 - $75,000
L ...... $75,001 - $100,000
M ...... $100,001 - $250,000
N ...... $250,001 - $1 million
O ...... $1 million - $5 million
P ...... $5 million - $10 million
Q ...... $10 million - $25 million
R ...... $25 million - $50 million
S ...... $50 million - $100 million
T ...... More than $100 million
Text presented to interviewer at level 3 if R volunteers a range and
gives a dollar range at level 2:
ENTER LOW END OF RANGE : $___,___,___.00
ENTER HIGH END OF RANGE : $___,___,___.00
Text presented to interviewer at level 2 if R answers DK/Ref at level 1:
Can you give me a range from this card? HAND R RANGE CARD.
YES
NO
Text presented to interviewer at level 3 if R answers DK/Ref at
level 1 and answers YES at level 2:
ENTER LETTER FROM RANGE CARD:
Possible card responses shown on range card:
See above
Decision tree sequence presented to interviewer at level 3 if R
answers DK/Ref at level 1 and NO/DK at level 2:
CONSIDER THE FOLLOWING 7 NUMBERS WHICH ARE STRICKLY INCREASING IN
VALUE: V1, V2, V3, V4, V5, V6, AND V7. RESPONDENTS ARE ASKED A
SEQUENCE OF QUESTIONS TO FIND THE INTERVALS DEFINED BY THESE NUMBER A
GIVEN VARIABLE FALLS.
Q1. Was it V4 dollars or more?
YES --> GO TO Q2
NO, DK --> GO TO Q5
Ref --> EXIT
Q2. Was it V5 dollars or more?
YES --> GO TO Q3
NO, DK, Ref --> EXIT
Q3. Was it V6 dollars or more?
YES --> GO TO Q4
NO, DK, Ref --> EXIT
Q4. Was it V7 dollars or more?
YES, NO, DK, Ref --> EXIT
Q5. Was it V1 dollars or more?
YES --> GO TO Q6
NO, DK, Ref --> EXIT
Q6. Was it V2 dollars or more?
YES --> GO TO Q7
NO, DK, Ref --> EXIT
Q7. Was it V3 dollars or more?
YES, NO, DK, Ref --> EXIT
To allow for appropriate ranges for all dollar questions, there are
eight different versions of the V1 to V7 variables given below.
Version V1 V2 V3 V4 V5 V6 V7
1 10,000 100,000 250,000 500,000 1,000,000 5,000,000 10,000,000
2 50,000 100,000 500,000 1,000,000 5,000,000 10,000,000 25,000,000
3 50,000 100,000 150,000 250,000 500,000 1,000,000 5,000,000
4 5,000 25,000 50,000 100,000 250,000 500,000 1,000,000
5 5,000 10,000 25,000 50,000 100,000 250,000 750,000
6 500 1,000 5,000 10,000 25,000 75,000 250,000
7 100 250 500 1,000 2,000 10,000 50,000
8 50 100 250 500 1,000 5,000 10,000
There are 31 possible unique outcomes of each version of each of the 8
versions of the decision tree:
1. Q1=NO, Q5=NO
2. Q1=NO, Q5=DK
3. Q1=NO, Q5=Ref
4. Q1=NO, Q5=YES, Q6=NO
5. Q1=NO, Q5=YES, Q6=DK
6. Q1=NO, Q5=YES, Q6=Ref
7. Q1=NO, Q5=YES, Q6=YES, Q7=NO
8. Q1=NO, Q5=YES, Q6=YES, Q7=DK
9. Q1=NO, Q5=YES, Q6=YES, Q7=Ref
10. Q1=NO, Q5=YES, Q6=YES, Q7=YES
11. Q1=DK, Q5=NO
12. Q1=DK, Q5=DK ---> NOTE: RESULTS IN NO BOUNDING INFORMATION
13. Q1=DK, Q5=Ref ---> NOTE: RESULTS IN NO BOUNDING INFORMATION
14. Q1=DK, Q5=YES, Q6=NO
15. Q1=DK, Q5=YES, Q6=DK
16. Q1=DK, Q5=YES, Q6=Ref
17. Q1=DK, Q5=YES, Q6=YES, Q7=NO
18. Q1=DK, Q5=YES, Q6=YES, Q7=DK
19. Q1=DK, Q5=YES, Q6=YES, Q7=Ref
20. Q1=DK, Q5=YES, Q6=YES, Q7=YES
21. Q1=Ref ---> NOTE: RESULTS IN NO BOUNDING INFORMATION
22. Q1=YES, Q2=NO
23. Q1=YES, Q2=DK
24. Q1=YES, Q2=Ref
25. Q1=YES, Q2=YES, Q3=NO
26. Q1=YES, Q2=YES, Q3=DK
27. Q1=YES, Q2=YES, Q3=Ref
28. Q1=YES, Q2=YES, Q3=YES, Q4=NO
29. Q1=YES, Q2=YES, Q3=YES, Q4=DK
20. Q1=YES, Q2=YES, Q3=YES, Q4=Ref
31. Q1=YES, Q2=YES, Q3=YES, Q4=YES
-----------------------------------------------------------------------------
-----------------------------------------------------------------------------
Definitions of the "J" Variables (1995 version)
0 = value reported on original tape (possibly altered during NORC
editing).
1 = question is inapplicable for R (e.g., R has no checking account
so value of checking account is coded as zero -- NOTE: there are
no zeros in the dataset other than such values).
2 = data moved from another location (not including re-arranging
columns in a grid); data moved from another location and added to
data already at new location (e.g., wage income from spouse
reported in independent adult part of section Y added to data
reported for R in Section T).
3 = data provided for a question with a branch structure, but not
known which branch data should be in (e.g., AGI given, but filing
status unknown, R has mutual funds but answers NO to all types).
4 = data change (to non-missing value) at FRB based on comments/verbatims.
Also includes editing changes specified by NORC that were not
possible to implement in their data handling system.
5 = indicates a value coded from a verbatim ("other/specify") response.
6 = data moved/changed as result of coded verbatim ("other/specify")
response.
8 = recode of survey variables, no missing values in antecedents.
For sequences of variables, such as the determination of whether
a dollar value or a percent is reported at Xhead-var/X4206/X4207,
one variable determines which type of variable is reported
(dollar/percent) subsequently; in some cases, the CAPI program
skips to the dollar value question and will puruse the DKDOL
sequence if necessary; if a dollar value (or range) is reported
in this way, the J-code of the initial choice variable is set to
the value '8.'
9 = recode of survey variables, insufficient data collected to
compute value, not imputed.
10 = part of reported value reported elsewhere and edited out here
(e.g., wage income of NPEU member also reported at X5701 along
with income of PEU resulting in J5702=10) or entire reported
value reported elsewhere and edited out here (e.g., all of wage
income of NPEU member reported at X5701 resulting in X5701=5,
J5701=10, X5702=0 and J5702=14).
12 = in case of regular installment loans where term is DK, non-missing
typical payment moved to monthly payment section.
13 = coded value overridden by another value after editing completed
14 = inap given hard-code decision (12, 13, 15, or 16)
15 = hard-coded imputation determined during cleaning.
16 = other reassignment resulting from cleaning that overrides
reported data (e.g., the cleaning of the institutions grid in
Section A).
17 = value of originally missing data item implied by other variable(s).
18 = value originally inap as consequence of CAPI logic, new value
inferred from other values.
19 = value changed, but logical content not altered (e.g., institution
reported for an account, but no link to institutions grid.
Account variable changed to pointer to an added institution of
type indicated by original account question).
25 = correction of NORC edit error or to a non-missing/non-inapplicable value.
ALL RESPONSES THAT FOLLOW HAVE AT LEAST SOME MISSING INFORMATION
90 = Bounding information available based on summary information
provided by respondent (typically, if a R does not know
information about items beyond a certain number in a set of
detailed questions about a larger number of such items, the R is
asked one or a number of summary questions about all remaining
instances).
91 = Same as 90, but R gave range data for the summary information.
RANGE RESPONSES:
POSITIVE RANGES
DECISION TREE RESPONSES THAT RESULTED IN A BOUND FOR POSITIVE NUMBERS
(NOTE: for decision tree codes, responses that resulted in no usable
bounding information are collected separately below)
'*' indicates an open-ended interval
NOTE: for J-code outcomes from 101-878, 921-940, and 971-990, .5 is
added to the J-code if the original response was DK
101=Decision tree response, version 1: outcome 1 (*,<=V1)
102=Decision tree response, version 1: outcome 2 (*,<=V4)
103=Decision tree response, version 1: outcome 3 (*,<=V4)
104=Decision tree response, version 1: outcome 4 (>V1,<=V2
105=Decision tree response, version 1: outcome 5 (>V1,<=V4)
106=Decision tree response, version 1: outcome 6 (>V1,<=V4)
107=Decision tree response, version 1: outcome 7 (>V2,<=V3)
108=Decision tree response, version 1: outcome 8 (>V2,<=V4)
109=Decision tree response, version 1: outcome 9 (>V2,<=V4)
110=Decision tree response, version 1: outcome 10 (>V3,<=V4)
111=Decision tree response, version 1: outcome 11 (*,<=V1)
112=Decision tree response, version 1: outcome 14 (V1,V2)
113=Decision tree response, version 1: outcome 15 (>V1,*)
114=Decision tree response, version 1: outcome 16 (>V1,*)
115=Decision tree response, version 1: outcome 17 (>V2,<=V3)
116=Decision tree response, version 1: outcome 18 (>V2,*)
117=Decision tree response, version 1: outcome 19 (>V2,*)
118=Decision tree response, version 1: outcome 20 (>V3,*)
119=Decision tree response, version 1: outcome 22 (>V4,<=V5)
120=Decision tree response, version 1: outcome 23 (>V4,*)
121=Decision tree response, version 1: outcome 24 (>V4,*)
122=Decision tree response, version 1: outcome 25 (>V5,<=V6)
123=Decision tree response, version 1: outcome 26 (>V5,*)
124=Decision tree response, version 1: outcome 27 (>V5,*)
125=Decision tree response, version 1: outcome 28 (>V6,<=V7)
126=Decision tree response, version 1: outcome 29 (>V6,*)
127=Decision tree response, version 1: outcome 30 (>V6,*)
128=Decision tree response, version 1: outcome 31 (>V7,*)
201=Decision tree response, version 2: outcome 1 (*,<=V1)
202=Decision tree response, version 2: outcome 2 (*,<=V4)
203=Decision tree response, version 2: outcome 3 (*,<=V4)
204=Decision tree response, version 2: outcome 4 (>V1,<=V2
205=Decision tree response, version 2: outcome 5 (>V1,<=V4)
206=Decision tree response, version 2: outcome 6 (>V1,<=V4)
207=Decision tree response, version 2: outcome 7 (>V2,<=V3)
208=Decision tree response, version 2: outcome 8 (>V2,<=V4)
209=Decision tree response, version 2: outcome 9 (>V2,<=V4)
210=Decision tree response, version 2: outcome 10 (>V3,<=V4)
211=Decision tree response, version 2: outcome 11 (*,<=V1)
212=Decision tree response, version 2: outcome 14 (V1,V2)
213=Decision tree response, version 2: outcome 15 (>V1,*)
214=Decision tree response, version 2: outcome 16 (>V1,*)
215=Decision tree response, version 2: outcome 17 (>V2,<=V3)
216=Decision tree response, version 2: outcome 18 (>V2,*)
217=Decision tree response, version 2: outcome 19 (>V2,*)
218=Decision tree response, version 2: outcome 20 (>V3,*)
219=Decision tree response, version 2: outcome 22 (>V4,<=V5)
220=Decision tree response, version 2: outcome 23 (>V4,*)
221=Decision tree response, version 2: outcome 24 (>V4,*)
222=Decision tree response, version 2: outcome 25 (>V5,<=V6)
223=Decision tree response, version 2: outcome 26 (>V5,*)
224=Decision tree response, version 2: outcome 27 (>V5,*)
225=Decision tree response, version 2: outcome 28 (>V6,<=V7)
226=Decision tree response, version 2: outcome 29 (>V6,*)
227=Decision tree response, version 2: outcome 30 (>V6,*)
228=Decision tree response, version 2: outcome 31 (>V7,*)
301=Decision tree response, version 3: outcome 1 (*,<=V1)
302=Decision tree response, version 3: outcome 2 (*,<=V4)
303=Decision tree response, version 3: outcome 3 (*,<=V4)
304=Decision tree response, version 3: outcome 4 (>V1,<=V2
305=Decision tree response, version 3: outcome 5 (>V1,<=V4)
306=Decision tree response, version 3: outcome 6 (>V1,<=V4)
307=Decision tree response, version 3: outcome 7 (>V2,<=V3)
308=Decision tree response, version 3: outcome 8 (>V2,<=V4)
309=Decision tree response, version 3: outcome 9 (>V2,<=V4)
310=Decision tree response, version 3: outcome 10 (>V3,<=V4)
311=Decision tree response, version 3: outcome 11 (*,<=V1)
312=Decision tree response, version 3: outcome 14 (V1,V2)
313=Decision tree response, version 3: outcome 15 (>V1,*)
314=Decision tree response, version 3: outcome 16 (>V1,*)
315=Decision tree response, version 3: outcome 17 (>V2,<=V3)
316=Decision tree response, version 3: outcome 18 (>V2,*)
317=Decision tree response, version 3: outcome 19 (>V2,*)
318=Decision tree response, version 3: outcome 20 (>V3,*)
319=Decision tree response, version 3: outcome 22 (>V4,<=V5)
320=Decision tree response, version 3: outcome 23 (>V4,*)
321=Decision tree response, version 3: outcome 24 (>V4,*)
322=Decision tree response, version 3: outcome 25 (>V5,<=V6)
323=Decision tree response, version 3: outcome 26 (>V5,*)
324=Decision tree response, version 3: outcome 27 (>V5,*)
325=Decision tree response, version 3: outcome 28 (>V6,<=V7)
326=Decision tree response, version 3: outcome 29 (>V6,*)
327=Decision tree response, version 3: outcome 30 (>V6,*)
328=Decision tree response, version 3: outcome 31 (>V7,*)
401=Decision tree response, version 4: outcome 1 (*,<=V1)
402=Decision tree response, version 4: outcome 2 (*,<=V4)
403=Decision tree response, version 4: outcome 3 (*,<=V4)
404=Decision tree response, version 4: outcome 4 (>V1,<=V2
405=Decision tree response, version 4: outcome 5 (>V1,<=V4)
406=Decision tree response, version 4: outcome 6 (>V1,<=V4)
407=Decision tree response, version 4: outcome 7 (>V2,<=V3)
408=Decision tree response, version 4: outcome 8 (>V2,<=V4)
409=Decision tree response, version 4: outcome 9 (>V2,<=V4)
410=Decision tree response, version 4: outcome 10 (>V3,<=V4)
411=Decision tree response, version 4: outcome 11 (*,<=V1)
412=Decision tree response, version 4: outcome 14 (V1,V2)
413=Decision tree response, version 4: outcome 15 (>V1,*)
414=Decision tree response, version 4: outcome 16 (>V1,*)
415=Decision tree response, version 4: outcome 17 (>V2,<=V3)
416=Decision tree response, version 4: outcome 18 (>V2,*)
417=Decision tree response, version 4: outcome 19 (>V2,*)
418=Decision tree response, version 4: outcome 20 (>V3,*)
419=Decision tree response, version 4: outcome 22 (>V4,<=V5)
420=Decision tree response, version 4: outcome 23 (>V4,*)
421=Decision tree response, version 4: outcome 24 (>V4,*)
422=Decision tree response, version 4: outcome 25 (>V5,<=V6)
423=Decision tree response, version 4: outcome 26 (>V5,*)
424=Decision tree response, version 4: outcome 27 (>V5,*)
425=Decision tree response, version 4: outcome 28 (>V6,<=V7)
426=Decision tree response, version 4: outcome 29 (>V6,*)
427=Decision tree response, version 4: outcome 30 (>V6,*)
428=Decision tree response, version 4: outcome 31 (>V7,*)
501=Decision tree response, version 5: outcome 1 (*,<=V1)
502=Decision tree response, version 5: outcome 2 (*,<=V4)
503=Decision tree response, version 5: outcome 3 (*,<=V4)
504=Decision tree response, version 5: outcome 4 (>V1,<=V2
505=Decision tree response, version 5: outcome 5 (>V1,<=V4)
506=Decision tree response, version 5: outcome 6 (>V1,<=V4)
507=Decision tree response, version 5: outcome 7 (>V2,<=V3)
508=Decision tree response, version 5: outcome 8 (>V2,<=V4)
509=Decision tree response, version 5: outcome 9 (>V2,<=V4)
510=Decision tree response, version 5: outcome 10 (>V3,<=V4)
511=Decision tree response, version 5: outcome 11 (*,<=V1)
512=Decision tree response, version 5: outcome 14 (V1,V2)
513=Decision tree response, version 5: outcome 15 (>V1,*)
514=Decision tree response, version 5: outcome 16 (>V1,*)
515=Decision tree response, version 5: outcome 17 (>V2,<=V3)
516=Decision tree response, version 5: outcome 18 (>V2,*)
517=Decision tree response, version 5: outcome 19 (>V2,*)
518=Decision tree response, version 5: outcome 20 (>V3,*)
519=Decision tree response, version 5: outcome 22 (>V4,<=V5)
520=Decision tree response, version 5: outcome 23 (>V4,*)
521=Decision tree response, version 5: outcome 24 (>V4,*)
522=Decision tree response, version 5: outcome 25 (>V5,<=V6)
523=Decision tree response, version 5: outcome 26 (>V5,*)
524=Decision tree response, version 5: outcome 27 (>V5,*)
525=Decision tree response, version 5: outcome 28 (>V6,<=V7)
526=Decision tree response, version 5: outcome 29 (>V6,*)
527=Decision tree response, version 5: outcome 30 (>V6,*)
528=Decision tree response, version 5: outcome 31 (>V7,*)
601=Decision tree response, version 6: outcome 1 (*,<=V1)
602=Decision tree response, version 6: outcome 2 (*,<=V4)
603=Decision tree response, version 6: outcome 3 (*,<=V4)
604=Decision tree response, version 6: outcome 4 (>V1,<=V2
605=Decision tree response, version 6: outcome 5 (>V1,<=V4)
606=Decision tree response, version 6: outcome 6 (>V1,<=V4)
607=Decision tree response, version 6: outcome 7 (>V2,<=V3)
608=Decision tree response, version 6: outcome 8 (>V2,<=V4)
609=Decision tree response, version 6: outcome 9 (>V2,<=V4)
610=Decision tree response, version 6: outcome 10 (>V3,<=V4)
611=Decision tree response, version 6: outcome 11 (*,<=V1)
612=Decision tree response, version 6: outcome 14 (V1,V2)
613=Decision tree response, version 6: outcome 15 (>V1,*)
614=Decision tree response, version 6: outcome 16 (>V1,*)
615=Decision tree response, version 6: outcome 17 (>V2,<=V3)
616=Decision tree response, version 6: outcome 18 (>V2,*)
617=Decision tree response, version 6: outcome 19 (>V2,*)
618=Decision tree response, version 6: outcome 20 (>V3,*)
619=Decision tree response, version 6: outcome 22 (>V4,<=V5)
620=Decision tree response, version 6: outcome 23 (>V4,*)
621=Decision tree response, version 6: outcome 24 (>V4,*)
622=Decision tree response, version 6: outcome 25 (>V5,<=V6)
623=Decision tree response, version 6: outcome 26 (>V5,*)
624=Decision tree response, version 6: outcome 27 (>V5,*)
625=Decision tree response, version 6: outcome 28 (>V6,<=V7)
626=Decision tree response, version 6: outcome 29 (>V6,*)
627=Decision tree response, version 6: outcome 30 (>V6,*)
628=Decision tree response, version 6: outcome 31 (>V7,*)
701=Decision tree response, version 7: outcome 1 (*,<=V1)
702=Decision tree response, version 7: outcome 2 (*,<=V4)
703=Decision tree response, version 7: outcome 3 (*,<=V4)
704=Decision tree response, version 7: outcome 4 (>V1,<=V2
705=Decision tree response, version 7: outcome 5 (>V1,<=V4)
706=Decision tree response, version 7: outcome 6 (>V1,<=V4)
707=Decision tree response, version 7: outcome 7 (>V2,<=V3)
708=Decision tree response, version 7: outcome 8 (>V2,<=V4)
709=Decision tree response, version 7: outcome 9 (>V2,<=V4)
710=Decision tree response, version 7: outcome 10 (>V3,<=V4)
711=Decision tree response, version 7: outcome 11 (*,<=V1)
712=Decision tree response, version 7: outcome 14 (V1,V2)
713=Decision tree response, version 7: outcome 15 (>V1,*)
714=Decision tree response, version 7: outcome 16 (>V1,*)
715=Decision tree response, version 7: outcome 17 (>V2,<=V3)
716=Decision tree response, version 7: outcome 18 (>V2,*)
717=Decision tree response, version 7: outcome 19 (>V2,*)
718=Decision tree response, version 7: outcome 20 (>V3,*)
719=Decision tree response, version 7: outcome 22 (>V4,<=V5)
720=Decision tree response, version 7: outcome 23 (>V4,*)
721=Decision tree response, version 7: outcome 24 (>V4,*)
722=Decision tree response, version 7: outcome 25 (>V5,<=V6)
723=Decision tree response, version 7: outcome 26 (>V5,*)
724=Decision tree response, version 7: outcome 27 (>V5,*)
725=Decision tree response, version 7: outcome 28 (>V6,<=V7)
726=Decision tree response, version 7: outcome 29 (>V6,*)
727=Decision tree response, version 7: outcome 30 (>V6,*)
728=Decision tree response, version 7: outcome 31 (>V7,*)
801=Decision tree response, version 8: outcome 1 (*,<=V1)
802=Decision tree response, version 8: outcome 2 (*,<=V4)
803=Decision tree response, version 8: outcome 3 (*,<=V4)
804=Decision tree response, version 8: outcome 4 (>V1,<=V2
805=Decision tree response, version 8: outcome 5 (>V1,<=V4)
806=Decision tree response, version 8: outcome 6 (>V1,<=V4)
807=Decision tree response, version 8: outcome 7 (>V2,<=V3)
808=Decision tree response, version 8: outcome 8 (>V2,<=V4)
809=Decision tree response, version 8: outcome 9 (>V2,<=V4)
810=Decision tree response, version 8: outcome 10 (>V3,<=V4)
811=Decision tree response, version 8: outcome 11 (*,<=V1)
812=Decision tree response, version 8: outcome 14 (V1,V2)
813=Decision tree response, version 8: outcome 15 (>V1,*)
814=Decision tree response, version 8: outcome 16 (>V1,*)
815=Decision tree response, version 8: outcome 17 (>V2,<=V3)
816=Decision tree response, version 8: outcome 18 (>V2,*)
817=Decision tree response, version 8: outcome 19 (>V2,*)
818=Decision tree response, version 8: outcome 20 (>V3,*)
819=Decision tree response, version 8: outcome 22 (>V4,<=V5)
820=Decision tree response, version 8: outcome 23 (>V4,*)
821=Decision tree response, version 8: outcome 24 (>V4,*)
822=Decision tree response, version 8: outcome 25 (>V5,<=V6)
823=Decision tree response, version 8: outcome 26 (>V5,*)
824=Decision tree response, version 8: outcome 27 (>V5,*)
825=Decision tree response, version 8: outcome 28 (>V6,<=V7)
826=Decision tree response, version 8: outcome 29 (>V6,*)
827=Decision tree response, version 8: outcome 30 (>V6,*)
828=Decision tree response, version 8: outcome 31 (>V7,*)
RANGE CARD RESPONSES FOR POSITIVE NUMBERS
901=Range card response via [F9]: range A. $1 to $100
902=Range card response via [F9]: range B. $101 to $500
903=Range card response via [F9]: range C. $501 to $750
904=Range card response via [F9]: range D. $751 to $1,000
905=Range card response via [F9]: range E. $1,001 to $2,500
906=Range card response via [F9]: range F. $2,501 to $5,000
907=Range card response via [F9]: range G. $5,001 to $7,500
908=Range card response via [F9]: range H. $7,501 to $10,000
909=Range card response via [F9]: range I. $10,001 to $25,000
910=Range card response via [F9]: range J. $25,001 to $50,000
911=Range card response via [F9]: range K. $50,001 to $75,000
912=Range card response via [F9]: range L. $75,001 to $100,000
913=Range card response via [F9]: range M. $100,001 to $250,000
914=Range card response via [F9]: range N. $250,001 to $1,000,000
915=Range card response via [F9]: range O. $1,000,001 to $5,000,000
916=Range card response via [F9]: range P. $5,000,001 to $10,000,000
917=Range card response via [F9]: range Q. $10,000,001 to $25,000,000
918=Range card response via [F9]: range R. $25,000,001 to $50,000,000
919=Range card response via [F9]: range S. $50,000,001 to $100,000,000
920=Range card response via [F9]: range T. More than $100,000,000
921=Range card response via DKDOL: range A. $1 to $100
922=Range card response via DKDOL: range B. $101 to $500
923=Range card response via DKDOL: range C. $501 to $750
924=Range card response via DKDOL: range D. $751 to $1,000
925=Range card response via DKDOL: range E. $1,001 to $2,500
926=Range card response via DKDOL: range F. $2,501 to $5,000
927=Range card response via DKDOL: range G. $5,001 to $7,500
928=Range card response via DKDOL: range H. $7,501 to $10,000
929=Range card response via DKDOL: range I. $10,001 to $25,000
930=Range card response via DKDOL: range J. $25,001 to $50,000
931=Range card response via DKDOL: range K. $50,001 to $75,000
932=Range card response via DKDOL: range L. $75,001 to $100,000
933=Range card response via DKDOL: range M. $100,001 to $250,000
934=Range card response via DKDOL: range N. $250,001 to $1,000,000
935=Range card response via DKDOL: range O. $1,000,001 to $5,000,000
936=Range card response via DKDOL: range P. $5,000,001 to $10,000,000
937=Range card response via DKDOL: range Q. $10,000,001 to $25,000,000
938=Range card response via DKDOL: range R. $25,000,001 to $50,000,000
939=Range card response via DKDOL: range S. $50,000,001 to $100,000,000
940=Range card response via DKDOL: range T. More than $100,000,000
RESPONDENT-PROVIDED DOLLAR RANGE FOR POSITIVE NUMBERS
941=Upper and lower bounds given
942=Upper bound given, lower bound missing
943=Lower bound given, upper bound missing
INTERVIEW COMMENT INDICATES THAT RANGES ARE NEGATIVE
DECISION TREE RESPONSES THAT RESULTED IN A BOUND FOR NEGATIVE NUMBERS
(NOTE: for decision tree codes, responses that resulted in no usable
bounding information are collected separately below)
151=Decision tree response, version 1: outcome 1 (negative value)
152=Decision tree response, version 1: outcome 2 (negative value)
153=Decision tree response, version 1: outcome 3 (negative value)
154=Decision tree response, version 1: outcome 4 (negative value)
155=Decision tree response, version 1: outcome 5 (negative value)
156=Decision tree response, version 1: outcome 6 (negative value)
157=Decision tree response, version 1: outcome 7 (negative value)
158=Decision tree response, version 1: outcome 8 (negative value)
159=Decision tree response, version 1: outcome 9 (negative value)
160=Decision tree response, version 1: outcome 10 (negative value)
161=Decision tree response, version 1: outcome 11 (negative value)
162=Decision tree response, version 1: outcome 14 (negative value)
163=Decision tree response, version 1: outcome 15 (negative value)
164=Decision tree response, version 1: outcome 16 (negative value)
165=Decision tree response, version 1: outcome 17 (negative value)
166=Decision tree response, version 1: outcome 18 (negative value)
167=Decision tree response, version 1: outcome 19 (negative value)
168=Decision tree response, version 1: outcome 20 (negative value)
169=Decision tree response, version 1: outcome 22 (negative value)
170=Decision tree response, version 1: outcome 23 (negative value)
171=Decision tree response, version 1: outcome 24 (negative value)
172=Decision tree response, version 1: outcome 25 (negative value)
173=Decision tree response, version 1: outcome 26 (negative value)
174=Decision tree response, version 1: outcome 27 (negative value)
175=Decision tree response, version 1: outcome 28 (negative value)
176=Decision tree response, version 1: outcome 29 (negative value)
177=Decision tree response, version 1: outcome 30 (negative value)
178=Decision tree response, version 1: outcome 31 (negative value)
251=Decision tree response, version 2: outcome 1 (negative value)
252=Decision tree response, version 2: outcome 2 (negative value)
253=Decision tree response, version 2: outcome 3 (negative value)
254=Decision tree response, version 2: outcome 4 (negative value)
255=Decision tree response, version 2: outcome 5 (negative value)
256=Decision tree response, version 2: outcome 6 (negative value)
257=Decision tree response, version 2: outcome 7 (negative value)
258=Decision tree response, version 2: outcome 8 (negative value)
259=Decision tree response, version 2: outcome 9 (negative value)
260=Decision tree response, version 2: outcome 10 (negative value)
261=Decision tree response, version 2: outcome 11 (negative value)
262=Decision tree response, version 2: outcome 14 (negative value)
263=Decision tree response, version 2: outcome 15 (negative value)
264=Decision tree response, version 2: outcome 16 (negative value)
265=Decision tree response, version 2: outcome 17 (negative value)
266=Decision tree response, version 2: outcome 18 (negative value)
267=Decision tree response, version 2: outcome 19 (negative value)
268=Decision tree response, version 2: outcome 20 (negative value)
269=Decision tree response, version 2: outcome 22 (negative value)
270=Decision tree response, version 2: outcome 23 (negative value)
271=Decision tree response, version 2: outcome 24 (negative value)
272=Decision tree response, version 2: outcome 25 (negative value)
273=Decision tree response, version 2: outcome 26 (negative value)
274=Decision tree response, version 2: outcome 27 (negative value)
275=Decision tree response, version 2: outcome 28 (negative value)
276=Decision tree response, version 2: outcome 29 (negative value)
277=Decision tree response, version 2: outcome 30 (negative value)
278=Decision tree response, version 2: outcome 31 (negative value)
351=Decision tree response, version 3: outcome 1 (negative value)
352=Decision tree response, version 3: outcome 2 (negative value)
353=Decision tree response, version 3: outcome 3 (negative value)
354=Decision tree response, version 3: outcome 4 (negative value)
355=Decision tree response, version 3: outcome 5 (negative value)
356=Decision tree response, version 3: outcome 6 (negative value)
357=Decision tree response, version 3: outcome 7 (negative value)
358=Decision tree response, version 3: outcome 8 (negative value)
359=Decision tree response, version 3: outcome 9 (negative value)
360=Decision tree response, version 3: outcome 10 (negative value)
361=Decision tree response, version 3: outcome 11 (negative value)
362=Decision tree response, version 3: outcome 14 (negative value)
363=Decision tree response, version 3: outcome 15 (negative value)
364=Decision tree response, version 3: outcome 16 (negative value)
365=Decision tree response, version 3: outcome 17 (negative value)
366=Decision tree response, version 3: outcome 18 (negative value)
367=Decision tree response, version 3: outcome 19 (negative value)
368=Decision tree response, version 3: outcome 20 (negative value)
369=Decision tree response, version 3: outcome 22 (negative value)
360=Decision tree response, version 3: outcome 23 (negative value)
371=Decision tree response, version 3: outcome 24 (negative value)
372=Decision tree response, version 3: outcome 25 (negative value)
373=Decision tree response, version 3: outcome 26 (negative value)
374=Decision tree response, version 3: outcome 27 (negative value)
375=Decision tree response, version 3: outcome 28 (negative value)
376=Decision tree response, version 3: outcome 29 (negative value)
377=Decision tree response, version 3: outcome 30 (negative value)
378=Decision tree response, version 3: outcome 31 (negative value)
451=Decision tree response, version 4: outcome 1 (negative value)
452=Decision tree response, version 4: outcome 2 (negative value)
453=Decision tree response, version 4: outcome 3 (negative value)
454=Decision tree response, version 4: outcome 4 (negative value)
455=Decision tree response, version 4: outcome 5 (negative value)
456=Decision tree response, version 4: outcome 6 (negative value)
457=Decision tree response, version 4: outcome 7 (negative value)
458=Decision tree response, version 4: outcome 8 (negative value)
459=Decision tree response, version 4: outcome 9 (negative value)
460=Decision tree response, version 4: outcome 10 (negative value)
461=Decision tree response, version 4: outcome 11 (negative value)
462=Decision tree response, version 4: outcome 14 (negative value)
463=Decision tree response, version 4: outcome 15 (negative value)
464=Decision tree response, version 4: outcome 16 (negative value)
465=Decision tree response, version 4: outcome 17 (negative value)
466=Decision tree response, version 4: outcome 18 (negative value)
467=Decision tree response, version 4: outcome 19 (negative value)
468=Decision tree response, version 4: outcome 20 (negative value)
469=Decision tree response, version 4: outcome 22 (negative value)
470=Decision tree response, version 4: outcome 23 (negative value)
471=Decision tree response, version 4: outcome 24 (negative value)
472=Decision tree response, version 4: outcome 25 (negative value)
473=Decision tree response, version 4: outcome 26 (negative value)
474=Decision tree response, version 4: outcome 27 (negative value)
475=Decision tree response, version 4: outcome 28 (negative value)
476=Decision tree response, version 4: outcome 29 (negative value)
477=Decision tree response, version 4: outcome 30 (negative value)
478=Decision tree response, version 4: outcome 31 (negative value)
551=Decision tree response, version 5: outcome 1 (negative value)
552=Decision tree response, version 5: outcome 2 (negative value)
553=Decision tree response, version 5: outcome 3 (negative value)
554=Decision tree response, version 5: outcome 4 (negative value)
555=Decision tree response, version 5: outcome 5 (negative value)
556=Decision tree response, version 5: outcome 6 (negative value)
557=Decision tree response, version 5: outcome 7 (negative value)
558=Decision tree response, version 5: outcome 8 (negative value)
559=Decision tree response, version 5: outcome 9 (negative value)
560=Decision tree response, version 5: outcome 10 (negative value)
561=Decision tree response, version 5: outcome 11 (negative value)
562=Decision tree response, version 5: outcome 14 (negative value)
563=Decision tree response, version 5: outcome 15 (negative value)
564=Decision tree response, version 5: outcome 16 (negative value)
565=Decision tree response, version 5: outcome 17 (negative value)
566=Decision tree response, version 5: outcome 18 (negative value)
567=Decision tree response, version 5: outcome 19 (negative value)
568=Decision tree response, version 5: outcome 20 (negative value)
569=Decision tree response, version 5: outcome 22 (negative value)
570=Decision tree response, version 5: outcome 23 (negative value)
571=Decision tree response, version 5: outcome 24 (negative value)
572=Decision tree response, version 5: outcome 25 (negative value)
573=Decision tree response, version 5: outcome 26 (negative value)
574=Decision tree response, version 5: outcome 27 (negative value)
575=Decision tree response, version 5: outcome 28 (negative value)
576=Decision tree response, version 5: outcome 29 (negative value)
577=Decision tree response, version 5: outcome 30 (negative value)
578=Decision tree response, version 5: outcome 31 (negative value)
651=Decision tree response, version 6: outcome 1 (negative value)
652=Decision tree response, version 6: outcome 2 (negative value)
653=Decision tree response, version 6: outcome 3 (negative value)
654=Decision tree response, version 6: outcome 4 (negative value)
655=Decision tree response, version 6: outcome 5 (negative value)
656=Decision tree response, version 6: outcome 6 (negative value)
657=Decision tree response, version 6: outcome 7 (negative value)
658=Decision tree response, version 6: outcome 8 (negative value)
659=Decision tree response, version 6: outcome 9 (negative value)
660=Decision tree response, version 6: outcome 10 (negative value)
661=Decision tree response, version 6: outcome 11 (negative value)
662=Decision tree response, version 6: outcome 14 (negative value)
663=Decision tree response, version 6: outcome 15 (negative value)
664=Decision tree response, version 6: outcome 16 (negative value)
665=Decision tree response, version 6: outcome 17 (negative value)
666=Decision tree response, version 6: outcome 18 (negative value)
667=Decision tree response, version 6: outcome 19 (negative value)
668=Decision tree response, version 6: outcome 20 (negative value)
669=Decision tree response, version 6: outcome 22 (negative value)
660=Decision tree response, version 6: outcome 23 (negative value)
661=Decision tree response, version 6: outcome 24 (negative value)
662=Decision tree response, version 6: outcome 25 (negative value)
663=Decision tree response, version 6: outcome 26 (negative value)
664=Decision tree response, version 6: outcome 27 (negative value)
665=Decision tree response, version 6: outcome 28 (negative value)
666=Decision tree response, version 6: outcome 29 (negative value)
667=Decision tree response, version 6: outcome 30 (negative value)
668=Decision tree response, version 6: outcome 31 (negative value)
751=Decision tree response, version 7: outcome 1 (negative value)
752=Decision tree response, version 7: outcome 2 (negative value)
753=Decision tree response, version 7: outcome 3 (negative value)
754=Decision tree response, version 7: outcome 4 (negative value)
755=Decision tree response, version 7: outcome 5 (negative value)
756=Decision tree response, version 7: outcome 6 (negative value)
757=Decision tree response, version 7: outcome 7 (negative value)
758=Decision tree response, version 7: outcome 8 (negative value)
759=Decision tree response, version 7: outcome 9 (negative value)
760=Decision tree response, version 7: outcome 10 (negative value)
761=Decision tree response, version 7: outcome 11 (negative value)
762=Decision tree response, version 7: outcome 14 (negative value)
763=Decision tree response, version 7: outcome 15 (negative value)
764=Decision tree response, version 7: outcome 16 (negative value)
765=Decision tree response, version 7: outcome 17 (negative value)
766=Decision tree response, version 7: outcome 18 (negative value)
767=Decision tree response, version 7: outcome 19 (negative value)
768=Decision tree response, version 7: outcome 20 (negative value)
769=Decision tree response, version 7: outcome 22 (negative value)
770=Decision tree response, version 7: outcome 23 (negative value)
771=Decision tree response, version 7: outcome 24 (negative value)
772=Decision tree response, version 7: outcome 25 (negative value)
773=Decision tree response, version 7: outcome 26 (negative value)
774=Decision tree response, version 7: outcome 27 (negative value)
775=Decision tree response, version 7: outcome 28 (negative value)
776=Decision tree response, version 7: outcome 29 (negative value)
777=Decision tree response, version 7: outcome 30 (negative value)
778=Decision tree response, version 7: outcome 31 (negative value)
851=Decision tree response, version 7: outcome 1 (negative value)
852=Decision tree response, version 7: outcome 2 (negative value)
853=Decision tree response, version 7: outcome 3 (negative value)
854=Decision tree response, version 7: outcome 4 (negative value)
855=Decision tree response, version 7: outcome 5 (negative value)
856=Decision tree response, version 7: outcome 6 (negative value)
857=Decision tree response, version 7: outcome 7 (negative value)
858=Decision tree response, version 7: outcome 8 (negative value)
859=Decision tree response, version 7: outcome 9 (negative value)
860=Decision tree response, version 7: outcome 10 (negative value)
861=Decision tree response, version 7: outcome 11 (negative value)
862=Decision tree response, version 7: outcome 14 (negative value)
863=Decision tree response, version 7: outcome 15 (negative value)
864=Decision tree response, version 7: outcome 16 (negative value)
865=Decision tree response, version 7: outcome 17 (negative value)
866=Decision tree response, version 7: outcome 18 (negative value)
867=Decision tree response, version 7: outcome 19 (negative value)
868=Decision tree response, version 7: outcome 20 (negative value)
869=Decision tree response, version 7: outcome 22 (negative value)
870=Decision tree response, version 7: outcome 23 (negative value)
871=Decision tree response, version 7: outcome 24 (negative value)
872=Decision tree response, version 7: outcome 25 (negative value)
873=Decision tree response, version 7: outcome 26 (negative value)
874=Decision tree response, version 7: outcome 27 (negative value)
875=Decision tree response, version 7: outcome 28 (negative value)
876=Decision tree response, version 7: outcome 29 (negative value)
877=Decision tree response, version 7: outcome 30 (negative value)
878=Decision tree response, version 7: outcome 31 (negative value)
RANGE CARD RESPONSES FOR NEGATIVE NUMBERS
951=Range card response via [F9]: range A. -$1 to -$100
952=Range card response via [F9]: range B. -$101 to -$500
953=Range card response via [F9]: range C. -$501 to -$750
954=Range card response via [F9]: range D. -$751 to -$1,000
955=Range card response via [F9]: range E. -$1,001 to -$2,500
956=Range card response via [F9]: range F. -$2,501 to -$5,000
957=Range card response via [F9]: range G. -$5,001 to -$7,500
958=Range card response via [F9]: range H. -$7,501 to -$10,000
959=Range card response via [F9]: range I. -$10,001 to -$25,000
960=Range card response via [F9]: range J. -$25,001 to -$50,000
961=Range card response via [F9]: range K. -$50,001 to -$75,000
962=Range card response via [F9]: range L. -$75,001 to -$100,000
963=Range card response via [F9]: range M. -$100,001 to -$250,000
964=Range card response via [F9]: range N. -$250,001 to -$1,000,000
965=Range card response via [F9]: range O. -$1,000,001 to -$5,000,000
966=Range card response via [F9]: range P. -$5,000,001 to -$10,000,000
967=Range card response via [F9]: range Q. -$10,000,001 to -$25,000,000
968=Range card response via [F9]: range R. -$25,000,001 to -$50,000,000
969=Range card response via [F9]: range S. -$50,000,001 to -$100,000,000
970=Range card response via [F9]: range T. Less than -$100,000,000
971=Range card response via DKDOL: range A. -$1 to -$100
972=Range card response via DKDOL: range B. -$101 to -$500
973=Range card response via DKDOL: range C. -$501 to -$750
974=Range card response via DKDOL: range D. -$751 to -$1,000
975=Range card response via DKDOL: range E. -$1,001 to -$2,500
976=Range card response via DKDOL: range F. -$2,501 to -$5,000
977=Range card response via DKDOL: range G. -$5,001 to -$7,500
978=Range card response via DKDOL: range H. -$7,501 to -$10,000
979=Range card response via DKDOL: range I. -$10,001 to -$25,000
980=Range card response via DKDOL: range J. -$25,001 to -$50,000
981=Range card response via DKDOL: range K. -$50,001 to -$75,000
982=Range card response via DKDOL: range L. -$75,001 to -$100,000
983=Range card response via DKDOL: range M. -$100,001 to -$250,000
984=Range card response via DKDOL: range N. -$250,001 to -$1,000,000
985=Range card response via DKDOL: range O. -$1,000,001 to -$5,000,000
986=Range card response via DKDOL: range P. -$5,000,001 to -$10,000,000
987=Range card response via DKDOL: range Q. -$10,000,001 to -$25,000,000
988=Range card response via DKDOL: range R. -$25,000,001 to -$50,000,000
989=Range card response via DKDOL: range S. -$50,000,001 to -$100,000,000
990=Range card response via DKDOL: range T. Less than -$100,000,000
RESPONDENT-PROVIDED DOLLAR RANGE FOR NEGATIVE NUMBERS
991=Upper and lower bounds given (negative amount)
992=Upper bound given, lower bound missing (negative amount)
993=Lower bound given, upper bound missing (negative amount)
OTHER RANGE RESPONSES THAT YIELDED NO NUMERICAL BOUNDING INFORMATION:
ALL VARIABLES WITH J-CODE VALUES BELOW THIS POINT INITIALLY CONTAIN
MISSING VALUE CODES AND ALL VARIABLES WITH J-CODE VALUES ABOVE THIS
POINT INITIALLY CONTAIN A RANGE MID-POINT OR OTHER SUCH VALUE
INTERVIEWER COMMENT INDICATING NEGATIVE NUMBER
994=Decision tree response, any version: outcome 21 (negative amount)
995=Decision tree response, any version: outcome 12 (negative amount)
996=Decision tree response, any version: outcome 13 (negative amount)
997=R reached range card field by agreeing to give a range at a
dollar field, volunteered to give a letter from the range card, and
subsequently responded DK/Refuse letter from the range card
(negative amount)
998=R answered DK/Refused to a dollar question, volunteered to give a
letter from the range card, and subsequently responded DK/Refuse
letter from the range card (negative amount)
999=R reached a field allowing both an upper bound and a lower bound
for a dollar amount by volunteering to give a range, but
subsequently responded DK/Ref to both upper and lower bound
(negative amount)
1000=R answered DK to main $ question, and refused following
question requesting a range from the range card (negative amount)
1001=R answered Ref to main $ question, and refused following
question requesting a range from the range card (negative amount)
NO INDICATION OF NEGATIVE NUMBER
1094=Decision tree response, any version: outcome 21
1095=Decision tree response, any version: outcome 12
1096=Decision tree response, any version: outcome 13
1097=R reached range card field by agreeing to give a range at a
dollar field, volunteered to give a letter from the range card, and
subsequently responded DK/Refuse letter from the range card
1098=R answered DK/Refused to a dollar question, volunteered to give a
letter from the range card, and subsequently responded DK/Refuse
letter from the range card
1099=R reached a field allowing both an upper bound and a lower bound
for a dollar amount by volunteering to give a range, but
subsequently responded DK/Ref to both upper and lower bound
1100=R answered DK to main $ question, and refused following
question requesting a range from the range card
1101=R answered Ref to main $ question, and refused following
question requesting a range from the range card
OTHER CODES FOR MISSING DATA
2050 = original response was DK.
2051 = original response was NA (includes interviewer errors,
and missing data resulting from editing decisions). Does not
include data missing as a result of missing higher-order questions.
2052 = original response missing as a result of missing information for
a higher-order question (typically a YES/NO cut question). In
this case, the higher-order question has been imputed in such
a way as to render the response appropriate. Also includes some
other miscellaneous cases: (1) if a dollar variable was missing
and DKDOL returned a DK/REF, the corresponding frequency is given
a missing value code equal to that of the dollar field; (2)
similarly, for clusters of variables containing a dollar amount
and percent options.
2053 = refused
2054 = some, DK how many (see B6).
2060 = unresolved data problem (none should remain in final dataset).
2079 = data missing because of questionnaire error, or data not collected.
2080 = recode variable, missing because data not collected for
sub-group, data to be imputed.
2081 = recode variable, some, but not all components originally missing.
2082 = recode variable, all components originally missing.
2097 = override of reported information with (at least partially)
imputed data
2098 = override of reported/inap./other information with a missing value.
2099 = used for absent spouse for J104 or J105 when X104 or X105 < 0.
3000 = data missing because R broke off the interview (each of these
cases reviewed to be sure that sufficient information is
reported that the case can count as a "partial accepted as
complete")
3001 = program, reporting or recording error.
3002 = temporary value given to variables containing illegal values.
These will all be resolved in editing and converted to other
existing codes. (includes "range U")
3003 = illegal zeroes
3004 = uninformative/irrelevant verbatim response
3005 = data not available (applies to data from HEF)
General instructions for J variable coding for recoded variables:
When a recoded variable is taken directly from another single
X-variable, it should have the same J-variable code.
When a recoded variable may come from a single variable in the
original X-variables, or as the result of a calculation based on
some number of X-variables, it is important to distinguish the
information content in the J-variables. As noted above, when the
value is taken directly, the J-variable should have exactly the
same value as that for the X-variable's shadow J-variable.
However, when some calculation is involved, this should be
reflected in the J-variable -- codes 8, 2081, and 2082.
When a recode cannot be computed because some part of the underlying
information was not collected for some subset of cases, the
recode's J-variable should be coded 9 or 2080.
Consider first a respondent who gives a non-missing response to the question that asks for the number of items of the type to be queried in the grid. The interviewer would ask the respondent the first set of detailed questions on the item. Then, the interviewer would be confronted with a question (not to be read to the respondent);
INTERVIEWER: CAN R PROVIDE INFORMATION ABOUT ANOTHER xxxx?
The intention of this question was to allow the interviewer to deal with a potentially hostile respondent and immediately branch to the mop-up questions. If the respondent was cooperative, the interviewer entered a YES response and continued through an identical procedure for each iteration until either the number of items reported was exhausted, or the maximum number of detailed questions was asked and the mop-up question was asked to get summary information on all remaining items. If the respondent reported a number of items less than the maximum number about which the detailed questions are asked, the following question was asked at the end of the final iteration:
Do you (or your family living here) have another xxxx?
A YES response here indicates that the respondent recalled an additional instance in the process of answering the detailed questions. A respondent could continue to "add" iterations until the maximum number of iterations is reached and the mop-up questions are asked.
Another possibility is that a respondent may either not know or be unwilling to tell the number of instances of an item. Because it is known that there is at least one such instance, the first set of detailed questions is asked. Then the respondent is asked:
Do you (or your family living here) have another xxxx?
The questioning then proceedes exactly as it would for a respondent who recalled additional instances.
In processing the data, several steps were taken. Sometimes, interviewers sensed an unwillingness to answer additional questions even though only one more instance remained. In such cases, the mop-up data were mapped into the grid. The fact of this movement is not directly recorded in the J-variables for such cases, though the movement can be deduced from the patterns of J-variables of other questions within an iteration that do not have mop-up equivalents. When respondents added instances, the originally reported number was updated and stored in the customary SCF variable number. The originally reported number of instances has been retained in the dataset since such information cannot be recovered in any other way from the data made available. When summary information was given by respondents who broke off their responses in a grid prematurely, that information was used to bound the imputations of the detailed data. Data items that have an associated J-variable with a value of 90 are ones where a complete response was given in the parallel mop-up variable, and those with a J-variable of 91 are ones where a range response was given in the parallel mop-up variable. There are some complicated mixed cases where a respondent did not give a non-missing value for the number of instances, but was willing to provide non-missing mop-up data. Though tedious, it is possible to deduce this information from the data provided.