1. DRAFT
National Survey on
Household Income and Expenditure
Data – Documentation
Study sponsored by:
National Council of Applied Economic Research (NCAER)
Reference Year
2004-2005
3. CONTENTS
About the study.......................................................................................................... 1
1. Background .....................................................................................................................1
2. Lesson Learned from International Experiences ...........................................................3
3. Survey ..............................................................................................................................4
3.1 Approach .....................................................................................................................4
3.2 Coverage .....................................................................................................................5
3.3 Sample Design.............................................................................................................5
3.3.1 Selection of Rural Sample.................................................................................6
3.3.2 Selection of Urban Sample................................................................................8
4. Primary Data Collection .................................................................................................11
4.1 Data Processing ...........................................................................................................13
4.2 Data Analysis..............................................................................................................14
Appendix I: Concept and Definitions ....................................................................... 16
Variable list for the data ............................................................................................. 28
4. National Household Survey of Income and Expenditure (2004-05)
National Household Survey of Income and Expenditure (2004-05)
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5. National Household Survey of Income and Expenditure (2004-05)
National Household Survey of Income and Expenditure (2004-05)
A Note about Data
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National Household Survey of Income and Expenditure (2004-05)
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1. Background
Economic analysts and policy makers identify three main purposes for compiling information on
income distribution. The first is driven by a desire to understand how the pattern of income
distribution can be related to patterns of economic activity and the returns to labour, capital and land,
and to the way in which societies are organised – i.e. to theoretical and institutional considerations.
The second reflects the concern of policy makers to determine the need for both universal and socially
targeted actions on different socio-economic groups and to assess their impact. The third is an interest
in how different patterns of income distribution influence household well being and people’s ability to
acquire the goods and services they require to satisfy their needs.
Unfortunately, there is great dearth of reliable longitudinal data on household income in India. The
NSSO has made efforts in the past for collecting information on household income along with the
consumer expenditure following interview method of data collection in its 9th round (May 1955-
September 1955) and 14th round (July 1958-June 1959). Later, it undertook collection of data on
receipts and disbursements as a part of the Integrated Household Survey (IHS) in its 19th round (July
1964-June 1965), and 24th round (July 1969-June 1970) with the aim of obtaining a complete picture
of transactions of the household income.
In 1983-84, the NSSO attempted once again a pilot enquiry on household income by following two
approaches viz. collection of household income directly from sources of earnings from one set of
household and the collection of data on household consumption and saving from second set of sample
households and data on income, consumption and saving from the third set of households. The
objective was to explore the possibility of evolving an operationally feasible and sound technical
methodology for collection of data on household income by interview method by examining the
effectiveness of direct income survey against the alternative approach of consumption and saving
enquiry.
Experience showed that there were difficulties in collection of reliable income data in the field due to
ambiguities in choice of unit of sampling, sampling frame, reference period of data collection, and
even items of information. Seasonality effect, lack of availability of accounts from employer
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8. National Household Survey of Income and Expenditure (2004-05)
households, significant amount of purchases through credit, hidden income generated through wages
paid in kind, etc. are other factors coming in the way of proper data collection. For these reasons, the
National Sample Survey Organisation has perhaps reframed from collection of data on household
income. Greater emphasis was, therefore, placed on household expenditure surveys.
However, since the mid 1980s there is another large scale survey, the Market Information Survey of
Households (MISH) of NCAER, which is less well known than the NSS. The MISH survey was
initiated in 1985-86 to estimate market size, penetration for a variety of consumer goods and most
importantly to provide a profile of consuming households in terms of income, occupation and location.
These surveys are one of the few consistent sources providing comparable household income data on a
regular basis. The main concept of income that has been used in the MISH is the concept of
“perceived monetary income”, which includes all income received by the household as a whole, and by
each of its members, during the reference year. However, as a corollary, the MISH surveys have
generated valuable demographic data, particularly on income. It has been suggested that these data
could throw light on broader social trends in the economy.
One major concern about MISH surveys was the adequacy of a single income question ‘What is your
annual household income from all sources? In the most recent publication ‘The Great Indian Poverty
Debate’ it has been emphasized that there is need for better survey data, improvements in the data and
broadening the indicators by which relevant policy issues may be objectively addressed. Also, National
Statistical Commission recommended to examine the feasibility of reintroducing the receipts and
disbursement block with last 365 days as a reference period as was the case with the 19th to 25th
Rounds of NSS adopting integrated household schedule. But still it has not happened.
In light of the above, the Council undertook the current study “National Survey of Household Income
and Expenditure” to generate more robust and reliable estimate of household income by following
international practices.
This survey is also important in view of the fact that NSS 61st round (2004-05) data on household
consumer expenditure will be available shortly which provides an opportunity to attempt a meaningful
comparative analysis through these two data sets. It is hoped that the resultant data sets will be useful
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to different sets of users such as core researchers, policy makers and corporates without diluting its
strength i.e., time series continuity.
2. Lesson Learned from International Experiences
NCAER research team studied the experience of several developing countries in organising household
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income and expenditure surveys , as was reviewed in-depth and presented in the Report of the
Canberra City Group of UN Statistical Commission, called 'Expert Group on Household Income
Statistics'. Over 70 participants from 26 national organisations and 7 international organisations were
involved in the work of the Canberra Group with objective to enhance national household income
statistics by developing standards on conceptual and practical issues related to the production of
income distribution statistics. It carried out a meta-survey (survey about surveys) of 106 income
components that are actually collected in 30 household income surveys in 25 countries from all
continents.
Based on experiences gained through reviewing these studies, desirable survey procedures such as
approach, concepts and definitions, sample design and sample size, content of questionnaire,
estimation were adopted in the current study to fill the data gap on household income. For instance,
§ The accounting period used for income distribution analysis is one year as per recommendation,
and similarly, household has been adopted as the basic statistical unit.
§ A hierarchy of components of income is built up which provides definitions of total disposable
household income.
1 The major sources reviewed includes Situation Assessment Survey of Farmers (NSS); Integrated Household Survey
(NSS); Employment and Unemployment Survey (NSS); All India Rural Household: Survey on Saving, Income and
Investment (NCAER 1962); Survey on Urban Income and Saving (NCAER 1962); Market Information Survey of
Households (NCAER); Micro-Impact of Macro and Adjustment Policies (MIMAP); Rural Economic and Demographic
Survey (NCAER); Expert Group on Household Income Statistics, Household Income and Expenditure Statistics (ILO);
Chinese Household Income Project (1995) and Household Income and Expenditure Survey (Sri Lanka).
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§ The recommended practical definition of income has been adopted for use in making international
comparisons of income and major components covered are as given (for details refer Appendixes I
and II).
- Cash wages and salaries
- Bonuses
- Profit/loss from self-employment
- Rental income
- Interest and dividends received
- Employer based pensions
- Government social benefits
- Other regular payments from outside the household
3. Survey Description and Methodology
3.1 Approach
This survey was primarily aimed to generate more robust and reliable estimate of household income
besides other sets of information such as demographic profile of households (religion, caste, education,
occupation, etc), estimates of market size and penetration of manufactured consumer goods
(consumables and durables) and ownership patterns. The target population of the survey was the total
population in the country, with states and urban/rural categories as sub-populations or target groups,
for whom representative estimates were also sought.
The survey methodology and sampling design adopted is similar to that used by the National Sample
Survey Organisation (NSSO) in its Household Budget Surveys (HBS). This is a household survey and
a list of households (sampling frame) is a prerequisite to selecting the representative sample from
which to collect the desired information. The sampling frame needs to be up-to-date and free from
errors of omission and duplication (which is particularly problematic). In developing countries like
India, such a sampling frame is neither readily available nor can it be easily prepared since developing
new frames is an expensive proposition. A three-stage stratified sample design was adopted in which a
ready-made frame was used at least for the first two stages, and a sampling frame i.e., list of
households, was developed in the last stage.
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NCAER's experience with socio-economic surveys in India has been that, more than the total sample
size, it is the geographical spread over the country that is more important from the point of view of
statistical efficiency of estimates. This applies perhaps even more so to income and expenditure, whose
distribution across the population is likely to show a large degree of heterogeneity. Consequently, a
notable feature of the survey design is that the sample of households was selected from a wide cross-
section of households in the country, covering both rural and urban areas, with the objective of
enhancing the precision of the estimates. The rural sample for the survey was selected from a rep-
resentative number of districts across the country, while the urban sample covered a range from big
cities to small towns with populations below 5,000.
While the first two stages of stratification in the survey used pre-existing sampling frames, the survey
developed a sampling frame of households at the third and last stage. In the absence of a definitive list
of households, households in the selected villages and urban blocks were randomly selected by
adopting systematic random sampling. In the case of large villages/urban blocks, a fraction of
households were listed in view of time and cost constraints. These households were randomly chosen.
3.2 Coverage
Primary survey of households was undertaken in 24 major States/Union Territories of India covering
both rural and urban areas of Andhra Pradesh, Assam, Bihar, Chandigarh, Chhattisgarh, Delhi, Goa,
Gujarat, Haryana, Himachal Pradesh, Jharkand, Karnataka, Kerala, Madhya Pradesh, Maharashtra,
Meghalaya, Orissa, Pondicherry, Punjab, Rajasthan, Tamil Nadu, Uttaranchal, Uttar Pradesh, and
West Bengal. Territories excluding Jammu & Kashmir, Sikkim, Arunachal Pradesh, Nagaland,
Manipur, Mizoram, Tripura, Andaman & Nicobar Islands, Daman & Diu, Dadra & Nagar Haveli
and Lakshadweep. Remaining states were left out due to operational difficulty and accounts for only 3
to 4 per cent of the country's total population.
3.3 Sample Design
A three-stage stratified sample design has been adopted for the survey to generate representative
samples. Sample districts, villages and households formed the first, second and third stage sample
units respectively for selection of the rural sample, while cities/towns, urban wards and households
were the three stages of selection for the urban sample. Sampling was done independently within each
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state/UT and estimates were generated at state/UT level. Estimate for all-India was basically the
aggregation of estimates for all states/uts. The sample sizes at first, second and third stages in rural and
urban areas were determined on the basis of available resources and the derived level of precision for
key estimates from the survey, taking into account the experience of NCAER in conducting the earlier
surveys such as MISH, etc.
Within a state there are variations in respect of social and economic characteristics. The bigger a state,
the larger is the variation. In the National Sample Survey (NSS), within a state, regions are formed
considering the homogeneity of crop pattern, vegetation, climate, physical features, rainfall pattern,
etc. An NSS region is a group of districts within a state similar to each other in respect of agro-
climatic features. In the present survey within a state, NSS regions formed the strata for both rural
and urban sampling.
3.3.1 Selection of Rural Sample
In the rural sample design, a sample size of 250 districts was allocated to the 64 NSS regions within
the 24 covered States/UTs in proportion to the total number of districts in an NSS region. From each
of the NSS regions, the allocated number of districts were selected, as the first-stage sample units,
with probability proportional to size and replacement, where rural population of each district as per
2001 Population Census was used as size measure.
Villages formed the second stage of selection procedure. District-wise lists of villages are available
from census records (Census 2001) along with population. A total sample of 1976 villages (second-
stage sampling units) was allocated to the selected 250 districts approximately in proportion to rural
population of each selected district. The allocated number of sample villages in a selected district were
chosen with equal probability sampling approach.
In each of the selected villages, approximately 100 households were selected following equal
probability sampling approach for listing purpose and preliminary survey. During this preliminary
survey, information on land possessed and principal source of income of the listed household was
collected for use in stratifying the listed households into 8 strata as follows:
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• Stratum 1: Principal source of income was self-employment in agriculture and land possessed was
0-2 acres;
• Stratum 2: Principal source of income was self-employment in agriculture and land possessed was
2-10 acres;
• Stratum 3: Principal source of income was self-employment in agriculture and land possessed was
above 10 acres;
• Stratum 4: Principal source of income was labour (agricultural/other casual);
• Stratum 5: Principal source of income was self-employment in non-agriculture and land possessed
was 0-2 acres;
• Stratum 6: Principal source of income was self-employment in non-agriculture and land possessed
was above 2 acres;
• Stratum 7: Principal source of income was regular salary/wages and other sources and land
possessed was 0-2 acres; and
• Stratum 8: Principal source of income was regular salary/wages and other sources and land
possessed was above 2 acres.
From each of the above 8 strata, 2 households were selected by following equal probability sampling
approach. In case, any of the strata was found to be missing (no household), then households from
previous stratum, where additional households were available, were selected so as to get 16 sample
households in a selected village.
Following the above sampling design in rural areas, the realised sample of 31,446 households out of
preliminary listed sample of 211,979 households was spread over 1976 villages in 250 districts and 64
NSS regions covering the 24 States/UTs.
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Table 1: Profile of Rural Sample
State Number of Stage I Stage II Stage III
NSS Total Sample Total Sample Listed Sample
Regions districts districts villages villages households households
Himachal Pradesh 1 12 6 17,495 32 2,736 512
Punjab 2 17 8 12,278 48 4,983 768
Chandigarh 1 1 1 23 5 500 78
Uttaranchal 1 13 6 15,761 30 3,044 480
Haryana 2 19 9 6,764 47 4,862 752
Delhi 1 9 1 158 6 668 88
Rajasthan 4 32 16 39,753 118 12,036 1,888
Uttar Pradesh 4 70 29 97,942 274 30,356 4,384
Bihar 2 37 18 39,018 196 21,721 3,136
Meghalaya 1 7 5 - 10 991 160
Assam 3 23 11 25,124 67 6,419 1,072
West Bengal 4 17 9 37,955 123 12,438 1,968
Jharkhand 1 18 9 29,354 59 5,930 944
Orissa 3 30 14 47,529 86 9,958 1,376
Chhattisgarh 1 15 7 19,744 49 4,924 784
Madhya Pradesh 6 45 22 52,117 132 14,092 2,112
Gujarat 5 25 12 18,066 90 10,659 1,440
Maharashtra 6 33 16 41,095 157 18,057 2,512
Andhra Pradesh 4 22 12 26,614 160 16,619 2,560
Karnataka 4 27 14 27,481 103 11,969 1,648
Goa 1 2 2 347 10 1,166 160
Kerala 2 14 7 1,364 63 6,368 848
Tamil Nadu 4 30 14 15,400 101 10,443 1,616
Pondicherry 1 4 2 92 10 1,040 160
ALL INDIA 64 522 250 571,474 1,976 211,979 31,446
3.3.2 Selection of Urban Sample
According to the 2001 census, there are about 4,850 cities/towns in the states/UTs (excluding Jammu
& Kashmir). The population of cities/towns in India varies from less than 5,000 to over a crore. In the
urban sample design, within the 24 covered States/UTs, the 64 NSS regions were again treated as
strata. In each NSS region, towns were categorised into five groups based on their population, namely
big towns and small towns. There are 170 cities with a population exceeding 2 lakh. All the cities
were selected with a probability of one. The remaining cities/towns were grouped into four strata on
the basis of their population size and from each stratum a sample of towns was selected independently.
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A progressively increasing sampling fraction with increasing town population class was used for de-
termining the number of towns to be selected from each stratum. From each NSS region, the allocated
number of small towns were selected by following an equal probability sampling procedure. The
sampling fraction was used at the state level. (Table 1).
Table 2: Sampling fraction for city/town groups
Town Town population Total Sample Sampling
class ('000) towns towns fraction
I > 10000 3 3 1.00
II 5000-10000 3 3 1.00
III 1000-5000 29 29 1.00
IV 500-1000 37 37 1.00
V 200-500 98 98 1.00
VI 100-200 219 56 0.26
VII 50-100 396 44 0.11
VIII 20-50 1,135 28 0.02
IX < 20 2,270 44 0.02
Total 4,190 342 0.08
A total sample size of 2255 urban wards was allocated among the selected small/big towns in
proportion to the number of wards in the respective towns. The allocated number of wards were
selected from each sample town following equal probability sampling approach. Thus, towns and
wards formed the first and second-stage sample units in the urban sample design.
Like in the rural sample design, within a selected ward, a sample of about 100 households was selected
for listing and preliminary survey, following equal probability sampling approach. In the preliminary
survey, at the time of listing of the sample households, information on household size, household
consumption expenditure for last month ((MPCE), and principal source of household income were
collected for use in stratifying the listed households into 7 strata as follows:
• Stratum 1: Principal source of income was regular salary/wage earnings and sources like
remittances, pension, etc. and MPCE of Rs. less than 800;
• Stratum 2: Principal source of income same as in stratum 1 but MPCE Rs. 801-2500;
• Stratum 3: Principal source of income same as stratum 1 but MPCE above Rs. 2500;
• Stratum 4: Principal source of income was self-employment and MPCE less than Rs. 800;
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• Stratum 5: Principal source of income was self-employment and MPCE Rs. 801-2500;
• Stratum 6: Principal source of income was self-employment and MPCE above Rs. 2500;
• Stratum 7: Principal source of income was casual labour (agricultural or non-agricultural).
From each of the above strata, 2 households were selected at random with equal probability of
selection. If there was no household in any of the strata, the shortfall was compensated from the
previous stratum, where additional households were available, so as to get 14 sample households from
each selected ward in urban sector for detailed survey.
Table 3: Profile of Urban Sample
State Number of Stage I Stage II Stage III
NSS Total Sample Total Sample Listed Sample
Regions towns towns blocks blocks households households
Himachal Pradesh 1 56 2 22 5 502 70
Punjab 2 157 12 472 74 7,596 1,036
Chandigarh 1 1 1 21 10 1,000 140
Uttaranchal 1 76 3 129 18 1,881 252
Haryana 2 97 13 596 74 7,543 1,036
Delhi 1 4 1 289 60 7,197 840
Rajasthan 4 216 19 851 114 11,568 1,596
Uttar Pradesh 4 670 51 2,036 316 31,975 4,424
Bihar 2 120 14 444 75 7,973 1,050
Meghalaya 1 10 1 6 6 600 84
Assam 3 110 5 100 20 1,940 280
West Bengal 4 239 18 - 142 14,620 1,988
Jharkhand 1 95 10 860 68 6,896 952
Orissa 3 132 8 322 45 4,501 630
Chhattisgarh 1 84 8 473 44 4,412 616
Madhya Pradesh 6 368 19 799 114 11,516 1,596
Gujarat 5 190 19 572 146 14,615 2,044
Maharashtra 6 347 35 2,220 273 31,553 3,822
Andhra Pradesh 4 173 27 1,172 195 20,426 2,730
Karnataka 4 237 22 905 153 18,819 2,142
Goa 1 38 2 12 4 440 56
Kerala 2 98 13 1,019 79 8,030 1,106
Tamil Nadu 4 68 37 2,272 207 21,937 2,898
Pondicherry 1 4 2 23 13 1,273 182
ALL INDIA 64 4,190 342 15,615 2,255 238,813 31,570
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Following the above sampling design in urban areas, the realised sample of 31,570 households, out of
preliminary listed sample of 238,813 households, was spread over 2,255 urban wards in 342 towns and
64 NSS regions covering the 24 States/UTs.
Table 4: Number of Persons Surveyed by Location
State Rural Urban All India
Himachal Pradesh 2,744 322 3,066
Punjab 4,044 5,285 9,329
Chandigarh 434 661 1,095
Uttaranchal 2,506 1,257 3,763
Haryana 4,612 5,453 10,065
Delhi 475 3,960 4,435
Rajasthan 10,744 8,635 19,379
Uttar Pradesh 28,819 23,462 52,281
Bihar 15,607 5,272 20,879
Meghalaya 866 308 1,174
Assam 4,803 1,107 5,910
West Bengal 10,185 8,885 19,070
Jharkhand 4,999 4,823 9,822
Orissa 7,046 3,040 10,086
Chattisgarh 3,998 2,948 6,946
Madhya Pradesh 11,609 8,090 19,699
Gujarat 6,760 9,700 16,460
Maharashtra 13,091 18,158 31,249
Andhra Pradesh 11,314 11,245 22,559
Karnataka 8,134 9,608 17,742
Goa 772 281 1,053
Kerala 3,635 4,539 8,174
Tamil Nadu 7,033 12,163 19,196
Pondicherry 740 777 1,517
Total 164,970 149,979 314,949
4. Primary Data Collection
Data collection work of this survey was entrusted to 12 state level Net Working Agencies (NWAs).
The criteria adopted to select the NWAs were: (a) they have been registered under the Societies Act,
(b) they have been empanelled in the NCAER and (c) they have necessary infrastructure to carry out
the data collection work in the respective state(s), with experience of such work in a related area and
(d) they have a cost-effective financial plan for undertaking the data collection work. The selected
NWAs worked in close liason with the NCAER. They engaged in all 250 interviewers and 50
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supervisors to complete data collection work in all the 24 states/uts during the period 15 October 2005
- 7 January 2006. The selection of the NWAs was done by 27 September 2005. The interviewers and
supervisors having a minimum educational qualification of graduate degree and having knowledge of
regional language(s) were recruited by the NWAs, keeping in view the duration of the field work and
workload allotted to them for timely completion of the data collection work. The survey core team of
NCAER consisted of 2 Advisors (part-time), 1 Senior Fellow, 2 Associate Fellows, 1 Research
Analyst and 5 Research Associates. Also, 14 professional researchers of NCAER were designated as
states-in-charge for overall supervisors of data collection work.
The ultimate success of a large-scale survey such as the present one depends upon proper training to
the interviewers and supervisors in addition to an efficient sample design and well designed survey
schedules (questionnaires). Training was done in two phases. In the first phase, the training was
imparted to trainers who were the heads of the selected NWAs and NCAER states-in-charge. This
meeting-cum-training was conducted from 20 September to 23 September 2005 at the headquarters
of NCAER, New Delhi. One day was devoted exclusively for pre-testing of the schedules in a nearby
sample village of Haryana state. In the second phase of training, the interviewers and supervisors were
trained before actual start of data collection work. This training was imparted by both the heads of
selected NWAs as well as NCAER staff during the month of October 2005 for a period of 3-6 days
including one day for pre-testing of the schedules. The arrangement for this training programme was
done by the concerned NWA. The topics for the training included a detailed discussion and
explanation of aims and objectives of the present survey, period of data collection work, reference
period, concepts, definitions and classifications such as the ones relevant for principal industry and
occupation, which were used in the schedules; sample design, listing schedule, stratification methods
for rural and urban listed households and detailed structure and contents of the household schedule
and the schedules used for the two other modules, sponsored by Max New York Life Insurance Ltd.
and Maruti Udyog Ltd. The participation and presence of NCAER staff during the course of this
phase of training at each centre was found very useful. In fact, NCAER staff supervised one or two
sample places work completed during their stay and brought the filled-in schedules to NCAER
headquarters for test scrutiny. Each of the NCAER staff who visited the training centres in October
2005 submitted a feedback report along with suggestions for improvement. The
mistakes/inconsistencies found in the scrutiny of the schedules brought by them to NCAER
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19. National Household Survey of Income and Expenditure (2004-05)
headquarters as well as their feedback reports were used to communicate immediately with the
concerned NWA to ensure the rectification of such errors in the further data collection work. Besides
a general feedback, covering common types of mistakes and suggestions for rectification were also
circulated to all the NWAs. This system of issuance of feedback communications based on test-
scrutiny of the schedules at NCAER headquarters in the very beginning of data collection work
helped a lot in reduction of non-sampling errors and improvement of data quality in the survey.
The sample lists both for rural and urban areas were supplied to each NWA in respect of the states/uts
allotted to them during the course of the training at NCAER headquarters in September 2005. A
letter was issued by NCAER addressed to the Chief Secretary of the concerned state/ut government
enclosing therewith the names of the districts/towns selected for the survey and also the name of
NWA appointed by NCAER for primary survey data collection and requesting them to inform the
concerned officer(s) in the state/ut about NCAER effort for conducting the survey and issue necessary
instructions to extend cooperation. This letter helped the field staff of NWA in canvassing the
schedules in the selected places in rural and urban areas.
Supervisors of the fieldwork played a very important role in reducing non-sampling errors. The
supervisors engaged by the NWAs did the supervisors work as well as the scrutiny of the schedules
filled-in by the interviewers on cent percent basis in accordance with the scrutiny programme supplied
to them. Though there were detailed instructions for the interviewers to conduct the data collection
work, it was necessary to provide a scrutiny programme with a list of checkpoints for scrutinising the
consistency and accuracy of the responses recorded by the interviewers. Accordingly, field scrutiny
programme was prepared by the NCAER covering detailed points of scrutiny in general and schedule
wise and it was circulated to each NWA, which helped their supervisors in scrutinising the schedules
to make them error free, as far as possible. NCAER staff also undertook field visits in the second
phase in problematic areas to ensure quality of data.
4.1 Data Processing
The NWAs sent in filled-in schedules in two lots through courier services. Although completed
schedules were edited once at the field level, these were again later subjected to manual editing and
coding at NCAER headquarters by a team of editors under the supervisors of the NCAER senior
staff. Then only a completed schedule was considered as ready for data entry. Detailed steps involved
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in the editing process at headquarters were listed out schedule wise and block-wise within a schedule
and these were strictly adhered to in the editing process.
The data entry procedure used was the 'centralised data entry workshop'. The objective of the
operation was to convert the raw data on the paper schedules into an intermediate product (machine-
readable files) that needed to be further refined by means of editing programmes and clerical processes
in order to obtain 'clean' data base as a final product. For this survey, data entry was done at NCAER
headquarters by a group of data entry operators working under supervisors. A special software was
prepared and used to segregate the information contained in the schedule into different parts known as
'decks' containing information on specific blocks of the schedules.
For data validation, data consistency checking software was prepared and used to ferret out both data
entry errors and apparent enumeration mistakes or inconsistencies. Five kinds of checks, namely range
checks, checks against reference data, skip checks, logical checks and typographic checks were used.
Data were saved at different stages before making any further changes and named as stage 0, stage 1,
stage 2 and so on files. Stage 0 consisted of original data and the data after cleaning at any step of
consistency check was saved as latter versions and the final version was stage 5 consisting of the
corrected data of all the states/uts after the final data cleaning.
4.2 Data Analysis
Estimates for various parameters were produced directly from the cleaned data files by weighting each
sample observation with the inverse of the probability of selection of the sample household taking into
account the sampling design.
Cross-validation of estimates for some key parameters such as household size, sex ratio, distribution of
households according to SC, ST, & others, religion, type of dwelling, etc., was done using the results
from external sources such as Census 2001 and National Sample Survey of 2003. Sampling errors for
key estimates from the survey were also produced.
Data analysis for the two additional modules, namely the 'survey on automobile owners' and the
'protection index study' was undertaken first, as these were sponsors studies and preliminary results
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21. National Household Survey of Income and Expenditure (2004-05)
were presented to the sponsor's for discussion and feedback of there comments. Analysis of the survey
data on household income and expenditure has been in progress. Key results from this survey are
expected to be released in October 2006. In due course of time, there are plans to prepare the micro
data file with data at household level (after suppression of identification particulars) for release under
certain conditions for public use.
15
22. National Household Survey of Income and Expenditure (2004-05)
Appendix I: Concept and Definitions
Household: A group of persons normally living together and taking food from a common kitchen
constitute a household. The members of a household may or may not be related by blood or marriage
to one another. Servants, permanent labourers and unrelated members are treated as members of the
household in case they take their meals regularly from the same kitchen. If a person is out for more
than six months during the reference period (2004-05), he/she was not treated as a member of the
household.
Household size: The number of normally resident members of a household is its size. It includes
temporary stay-away but exclude temporary visitors and guests. Even though the determination of the
actual composition of a household is left to the judgment of the head of the household, the following
procedures was adopted as guidelines:
• In deciding the composition of a household, more emphasis is to be placed on 'normally living
together' than on 'ordinarily taking food from a common kitchen'. In case the place of residence of
a person is different from the place of boarding, he or she was treated as a member of the
household with whom he or she resides.
• A resident employee, or domestic servant, or a paying guest (but not just a tenant in the
household) was considered as a member of the household with whom he or she resides even
though he or she is not a member of the same family.
• When a person sleeps in one place (say, in a shop or in a room in another house because of space
shortage) but usually takes food with his or her family, he or she should be treated not as a single
member household but as a member of the household in which other members of his or her family
stay.
• If a member of a household (say, a son or a daughter of the head of the household) stays elsewhere
(say, in hostel for studies or for any other reason), he/she was not considered as a member of
his/her parent's household. However, he/she was listed as a single member household if the hostel
is listed.
Head of the household: The head is the main decision-maker in the family and the person best
informed about the family’s finances. Usually he is chief earner or the oldest member in the household.
The household members are expected to tell the interviewer whom they regard as Head.
16
23. National Household Survey of Income and Expenditure (2004-05)
Rural and Urban Areas: The rural and urban areas of the country are taken as adopted in Census 2001
for which the required information is available with the Survey Design and Research Division of the
NSSO. The lists of Census villages as published in the Primary Census Abstracts (PCA) constitute
the rural areas, and the lists of cities, towns, cantonments, non-municipal urban areas and notified
areas constitute urban areas.
The definition of urban areas adopted for this study is the same as used in the 2001 Census.
Accordingly, urban areas include:
• All places with a municipality/corporation, cantonment board or a notified town area committee;
• All other places satisfying the following criteria:
- minimum population of 5,000
- at least 75 per cent of the male workforce is engaged in non-agricultural pursuits
- a population density of over 400 per sq km (1,000 per sq mile).
NSS Region: An NSS region is a group of districts within a state similar to each other in respect to
agro-climate features. The regions are formed considering the homogeneity of crop pattern,
vegetation, climate, physical features, rainfall pattern etc. There are 78 NSS regions over the
geographical territories of India.
Block: A census block is a specific area, which is clearly demarcated with an eye on the ultimate norm
of workload i.e. the population and/or households to be covered. For the House listing operations
2001, a norm of 120-140 household and a population of 600-700 was fixed for rural blocks. Urban
enumeration block consists a population of about 600-700 or 120-140 houses. Formation of Census
Enumeration Blocks (CEBs) is done once in ten years.
UFS Block: All the urban areas are divided into UFS blocks with a population content ranging from
600 to 800 or 120 to 160 households. UFS is being conducted by NSSO on a regular basis in all the
urban areas with a provision to update the blocks once in every five years.
Ward: Ward is the smallest administrative division of a town or a city. An election to municipal
council is done ward wise. Wards are non-overlapping and mutually exclusive; that is, if a particular
area has been included in one ward it cannot form a part of another ward. Wards are easily
identifiable and there is no room for ambiguity. The population content of the wards could vary. In
small towns, a ward may be of 500 population and in bigger towns a ward may be of 50,000
17
24. National Household Survey of Income and Expenditure (2004-05)
population. There is no provision for higher or lower limit in the Municipal Act. Even within the
same town population contents of different wards differs markedly. For instance, in Patiala Town,
one ward has a population of 3000 and another ward has a population of 10,000. Wards boundaries
are well defined. The population content at a particular point of time is known: The census operations
while forming CEBs base their operations on wards.
National Industrial Classification: Industry is the sector of economic activity in which a person works.
The National Industrial Classification - 1998 is being used for classifying the industry of a person or
enterprise or household. NIC-1998 groups' together economic activities, which are akin in terms of
process type, raw materials, used and finished goods produced. The classification does not make any
distinction according to type ownership, type of legal organisation, type of technology and scale/mode
of operation or type of economic organisation and except in some cases the classification does not
distinguish between large scale and small scale. Total number of sections in NIC-1998 are 17 but in
the present survey section 'Fishing' has been merged with Agriculture and section 'other community
social and personal service activities', merged with 'others'. Hence the total number of sections for the
present survey is 15.
Principal Industry: When a person is pursuing only one type of economic activity, the sector of such
economic activity will be his/her principal industry. When two or more economic activities are pursued
by a person, the economic activity in which more labour time is spent will be his/her principal activity
and the related industry will be his/her principal industry.
National Classification of Occupation: The nature of work performed by a person is called his/her
occupation. For classification of occupation of a person the 'National Classification of Occupation
(NCO - 1968) is used. In an occupation classification, the groups of occupation have to be based on
the fundamental criterion of 'type of work performed'. All the workers engaged in same type of work
are grouped together irrespective of the Industrial Classification of establishments where they are
engaged. For example, all clerical workers have been classified in one occupational group whether they
are engaged in a factory, mine, government office or a shop. Factors like materials handled, tools or
machines used, standard of performance required, level of responsibility involved, physical and social
environments, industrial affiliations, etc. have not affected the classification of occupations. But
factors like types of operations involved in the performance of a job, type of qualifications, vocational
and professional training, status (e.g. own account worker, employer), levels of skill, etc., are
18
25. National Household Survey of Income and Expenditure (2004-05)
considered in classifying a person as belonging to particular occupation. Job definitions or descriptions
represent only the average national picture of the various occupations.
Principal Occupation: The nature of economic activity performed i.e., the type of function performed
by a person is his/her primary occupation, if he/she is engaged in one and only one type of economic
activity. If he/she is pursuing two or more economic activities, principal occupation will be of the
economic activity in which he or she spends more labour time. For classifying the occupation of a
person the National Classification of Occupation (NCO 1968) is used.
Activity Status: Any activity resulting in production of goods and services that adds value to national
product is considered as economic activity. Such activities include (I) production of all goods and
services for market i.e. production for pay or profit and (ii) the production of primary commodities for
own consumption and (iii) own account production of fixed assets, among the non-market activities.
• Employers: The self-employed persons who work on their own account and by and large run their
own enterprise by hiring labour are called employer.
• Own account worker: Self-employed persons who operate their own farm or non-farm enterprises
without hiring any labour are called own account workers.
• Self-employed in agriculture: Persons/households who are engaged in their own farm are defined
as self-employed in agriculture.
• Self-employed in non-agriculture: Persons/households who are engaged in their own non-farm
enterprises are defined as self-employed in non-agriculture.
• Agricultural labour: A person is treated as agricultural labour if he/she follows one or more of the
following agricultural operations in the capacity of labourer or hire or in exchange, whether paid
wholly in cash or kind or partly in cash and partly in kind:
- Farming including cultivation and tillage of the soil, etc.
- Dairy farming,
- Production, cultivation, growing and harvesting of any horticultural commodity,
- Raising of livestock, bee keeping or poultry farming etc.
It may be noted that manual work in fisheries is excluded from the coverage of agricultural labour.
• Casual wage labour: A person casually engaged in other’s non-farm enterprises (both household
and non-household) and getting in return wages according to the terms of daily or periodic work
contract is treated as casual wage labour.
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26. National Household Survey of Income and Expenditure (2004-05)
• Other Casual Labour: A person casually engaged in other’s non-farm enterprises (both household
and non-household) and getting in return wages according to the terms of daily or periodic work
contract is treated as other (casual) labour.
Household Income: In broad terms, income refers to regular receipts such as wages and salaries,
income from self-employment; interest and dividends from invested funds, pensions or other benefits
from social insurance and other current transfers receivable. Income presents a partial view of
economic well being and represents the regular or recurring receipts side of household economic
accounts. It provides a measure of resources available to the household for consumption and saving.
• Regular salaries and wages: The regular salaries and wages are the earnings, which a person
working in other’s farm or non-farm enterprises (both household and non-household) gets in
return on a regular basis (and not on the basis of daily or periodic renewal of work contract). The
following components of salary and wages for all earning members were collected.
- Average salary received per month (Rs.)
- Employer’s contribution to provident fund per month (Rs.)
- Own contribution to provident fund per month (Rs.)
- Bonus and allowances received during April 2004-March 2005
- Other receipt from employer during April 2004-March 2005
- Income tax paid for accounting year April 2004-March 2005
• Bonus: Bonus includes profit sharing bonus, festival bonus, year-end and other bonus and ex-
gratia payments paid at less frequent intervals (i.e. other than bonus paid more or less regularly for
each pay period).
• Self-employed in non-agriculture: Persons/households who are engaged in their own non-farm
enterprises are defined as self-employed in non-agriculture (Craft/Business /Professionals, etc).
The following components of self-employed in non-agriculture were collected.
- Receipts
§ Value (sale) of products & services
§ Value of products retained for own consumption
- Operating expenses (Rs.)
§ Raw material purchased
§ Labour charges
§ Rent
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27. National Household Survey of Income and Expenditure (2004-05)
§ Other expenses (Fuels, transport and marketing, hire charges for equipment, storage,
etc.)
§ Tax on business income
• Agricultural labour: A person is treated as agricultural labour if he/she follows one or more of the
following agricultural operations in the capacity of labourer or hire or in exchange, whether paid
wholly in cash or kind or partly in cash and partly in kind:
- Farming including cultivation and tillage of the soil, etc.
- Dairy farming,
- Production, cultivation, growing and harvesting of any horticultural commodity,
- Raising of livestock, bee keeping or poultry farming etc.
It may be noted that manual work in fisheries is excluded from the coverage of agricultural labour.
The following components of agricultural labour for each wage labourer were collected.
- Periodicity of payment (1=Annual, 2=Monthly, 3=Weekly, 4=Daily)
- Period of employment during April 2004-March 2005 (Months)
- Mode of payment (1=Cash, 2=Kind, 3= Cash & kind)
- Average payment received per month (Rs.)
- Other receipts from employer during April 2004-March 2005
• Casual wage labour: A person casually engaged in other’s non-farm enterprises (both household
and non-household) and getting in return wages according to the terms of daily or periodic work
contract is treated as casual wage labour. The following components of casual wage labour for each
wage earner were collected.
- Periodicity of payment (1=Annual, 2=Monthly, 3=Weekly, 4=Daily)
- Period of employment during April 2004-March 2005 (Months)
- Mode of payment (1=Cash, 2=Kind, 3= Cash & kind)
- Average payment received per month (Rs.)
- Other receipts from employer during April 2004-March 2005
• Self-employed in agriculture: Persons/households who are engaged in their own farm are defined
as self-employed in agriculture. The following components of self-employed in agriculture were
collected.
- Value of output and its disposal
§ Value produced
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28. National Household Survey of Income and Expenditure (2004-05)
§ Value of output sold
o Cash
o Exchange
o Total
§ Value of output for domestic use
- Operating expenses (Rs.)
§ Seed (Home produced and purchased)
§ Manures, fertilizers and chemicals
§ Irrigation charges
§ Labour charges
§ Other expenses (land rent, hire charges for equipment, storage, etc.)
• Income from other sources:
- Rent from lending land
- Rent from providing accommodation and capital for production
- Net Interest received (Income from bonds, deposits and savings)
- Dividend (Income received from stock holdings and mutual fund shares)
- Employer based private pension (Payments received from companies/government after
retirement)
- Government social insurance and social assistance benefits (Pay supplements to dependent
family members of military, unemployment, cash income from subsidies in any form, etc.)
- Others (Specify___________)
Dividend: Dividend represents the return to someone who has invested in an enterprise but
does not work in it themselves. For incorporated enterprises, they are simply called dividends.
Social insurance benefits: Social insurance benefits are paid in return for contributions paid by,
or on behalf of, the recipient or their beneficiaries. With unfunded employment related benefit
schemes, the contributions may be notional but the main criterion is that there is an obligation
to pay an employment related benefit.
It includes:
22
29. National Household Survey of Income and Expenditure (2004-05)
- Employment related pensions and other insurance benefits paid from private employers’
schemes and government schemes run entirely for benefit of government employees
- Pensions and other benefits from overseas governments
- Military pensions
- Unemployment, sickness, disability, medical, etc. benefits paid from private insurance
schemes that qualify as social insurance
- Payments for education of employees’ families that are part of the remuneration package.
It excludes:
- Lump sum retirement payouts, Benefits from private insurance schemes where
contributions to the scheme are not mandated by government or by an employer, that is,
participation in the scheme is entirely at the discretion of the contributor Payments from
government schemes run entirely for benefit of government employees.
- Some social insurance schemes allow (or force) a participant to take some retirement
benefits in the form of a lump sum payment, often at the date of retirement. In such cases,
subsequent regular payments are lower than they are otherwise would have been if no lump
sum had been paid. The SNA prescribes that all retirement benefits be treated as social
insurance benefits. This avoids the need to obtain information on the amount of lump sum
and regular payments separately, and keeps all contributions and benefits in the same
account.
Social assistance benefits in cash from government
It includes:
- Age, widows, unemployment, sickness, disability, etc pensions and allowances that are not
employment related or dependent on direct contributions to an insurance scheme by the
beneficiary
- Maternity, family and child benefits
- Scholarships and other educational assistance from government
- Reduction in interest on student loans where not means-tested
It excludes:
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30. National Household Survey of Income and Expenditure (2004-05)
- Rental allowances (housing subsidies), Medical expenses reimbursed other social benefits in
kind.
Consumption Expenditure: Household consumption included the value of all goods and services
provided in kind from employers or as a result of home production (including the value of imputed
rent for owner-occupied dwellings), which were already included in total income.
Consumption Expenditure is classified into 8 groups given below:
• Food: While recording consumption, care should be taken to include consumption on
ceremonials, parties, etc. The household made any transfer payment in terms of commodities
like cereals, beverages, fruits, vegetables pulses, etc., the quantity of commodity so paid should
not be shown under domestic consumption of the payer household. The portion out of that
receipt consumed by the recipient household during the reference period was shown against
the consumption of the recipient household.
• Housing: Information was collected on the expenditure for purchase of
rent/taxes/maintenance/ other household services/ water bills etc. items during the reference
period. The actual expenditure incurred towards purchase of these items, used for non-
productive purposes, was considered as the consumer expenditure of the household.
Expenditure both in cash and kind was taken into account. The consumption was recorded in
terms of average per month.
• Health Expenses (fee to medical facilities/medical labs/medicines): These items include
expenditure on medicines of different types and on medical goods; also, payments made to
doctor, nurse, etc., on account of professional fees and those made to hospital, nursing home,
etc. for medical treatment. Medical expenses included IUD (intra-uterine device), oral pills
condoms, diaphragm, spermicide (jelly, cream, foam tablet), etc. Expenditure incurred for
clinical tests, X-ray, etc. were also accounted. For Central government employees receiving
medicines and medical services from CGHS dispensaries, only the monthly contribution made
was considered. If, however, some medicine or service was purchased from outside during the
reference period, the expenditure, even if reimbursed, was to be included. The distinction
between institutional and non-institutional medical expenses lies in whether the expenses were
incurred on medical treatment as in-patient of a medical institution or otherwise.
24
31. National Household Survey of Income and Expenditure (2004-05)
• Transport (road/air/fuel/repair/insurance/license): Expenditure incurred on account of
journeys undertaken and/or transportation of goods made by airways, railways, bus, tram,
steamer, motor car (or taxi), motor-cycle, auto-rickshaw, bicycle, rickshaw (hand-drawn and
cycle) horse-cab, bullock cart, hand-cart, porter or any other means of conveyance was
recorded against this item. The expenditure was taken as the actual fare paid. The
expenditure incurred on journeys undertaken under LTC, etc., even if reimbursed, was to be
included. In case of owned conveyance, the cost of fuel (petrol, mobile oil, diesel, etc.) for
power driven transport and animal feed for animal-drawn carriage were also accounted. For
railway fare, season tickets valid for more than a month were treated differently from other
railway fare expenditure. Value of season tickets valid for more than a month held during the
reference period by a household member was divided by the number of months covered by the
ticket to get the amount to be recorded. For all other railway fare expenditure, the amount
actually paid during the reference period was recorded.
The expenditure incurred on any conveyance used during the reference period partly for
household enterprise and partly for domestic purposes was apportioned on the basis of the
number of kilometers it travelled for each type of use. In case the information on distance
travelled was not available, the apportionment was done on the basis of duration of use, say,
number of hours or days used for enterprise and domestic purpose.
It included bicycle, motorcycle, scooter, motorcar, jeep, tyres and tubes, other transport
equipment etc. Tyre and tubes referred to all those tyres and tubes, which were purchased for
replacement in vehicles. Livestock animals like horses, bullocks, etc., and conveyance such as
horse cab, bullock cart, etc., when used exclusively for non-productive domestic purposes, were
included in other transport equipment.
• Education: This was meant for recording expenses incurred in connection with education like
purchase of books/stationeries/school fee/boarding/school transportation etc. It included
expenditure on goods purchased for the purpose of education, viz., books and journals,
newspapers, paper, pen, pencil, etc. It also included fees paid to educational institutions (e.g.
schools, colleges, universities, etc.) on account of tuition (inclusive of minor items like game
fees, library fees, fan fees, etc.) and payment to private tutor. Occasional payments to the
school fund made on account of charities provided for indigent students and 'donations'
25
32. National Household Survey of Income and Expenditure (2004-05)
generally were not included here as these were regarded as transfer payments. It was noted
that all kinds of books, magazines, journals, etc. including novels and other fiction were
covered under this item.
• Clothing and footwear: Information on value of consumption of all items of clothing and
footwear were collected in whole number of rupees.
• Consumer durable goods: Information on expenditure incurred for purchase and cost of raw
materials and services for construction and repairs of durable goods for domestic use were
collected against this item. Expenditure included both cash and kind. Expenditure incurred on
purchase of durable goods for giving gifts was also included. Expenditure on any durable in this
item was recorded in whole number of rupees. The following points were kept in mind while
filling this item.
- If the sample household incurred some expenditure on purchase of an asset during the
reference period but did not received it, till the date of survey, the expenditure incurred was
accounted in this block.
- A sample household purchased an asset (durable goods) during the reference period and
the asset was under possession but no payment was made during the reference period.
Such purchases were excluded.
- An asset purchased during the reference period for domestic use and the same asset sold
out during the reference period. Such purchase was also accounted for.
It will include electric bulb, tube light, earthenware, glassware, bucket, washing soap, agarbatti,
plant with pot, brushed, utensil cleaners, steel wool, and other petty articles. Hiring charges
for consumer goods like furniture, electric fans, crockery, utensils and charges for decoration on
ceremonial occasions were also accounted here.
Land possessed: The area of land possessed included land ‘owned’, ‘leased in’ and ‘neither owned nor
leased-in’ but excluded land ‘leased-out’ by the household as on the date of survey. Total land area
possessed was ascertained and recorded under this column. A piece of land was considered to be
'owned by the household' if permanent heritable possession, with or without the right to transfer the
title, was vested in a member or members of the household. Land held in owner-like possession under
long-term lease for 30 years or more or assignment was also considered, as land owned. As regards
26
33. National Household Survey of Income and Expenditure (2004-05)
lease, land given to others on rent or free by owner of the land without surrendering the right of
permanent heritable title was defined as leased out. Land leased-in was defined as land taken by a
household on rent or free without any right of permanent or heritable possession. The lease contract
may be written or oral. If the household had possession of land for which it lacked title of ownership
and also does not had any lease agreement for the case of the land transacted either verbally or in
writing, such land was considered as neither owned nor leased-in. (The total area of land possessed by
the household was worked out as owned + leased-in + neither owned nor leased in – leased out).
Period of survey: Three months duration from 1st October 2005 to 31st December 2005.
Reference Period: The information was collected primarily for the year April 2004 – March 2005. For
the questions where the reference period was mentioned as “Last Month” was defined as thirty days
preceding the date of enquiry.
27
36. National Household Survey of Income and Expenditure (2004-05)
Variable List for Data File
Information Provided Household Characteristics
Demographic and Other Particulars of Household Members
Household Income
Household Consumption Expenditure
Miscellaneous Information
Data File NSHIE_All_India-selected_indicators-26July2008
Number or Variables 197
Number of Records 630015
Questionnaire National Survey on Household Income and Expenditure-(Household Schedule)
Notes:
1. Data has been provided in SPSS data format.
2. Data file contains only numeric values.
28
37. National Household Survey of Income and Expenditure (2004-05)
Variable Description/Label Fields/ Width/ Decimals Code Sepcification
Columns Length
stat State Codes 1-2 2 0 Code Value
2 Himachal Pradesh
3 Punjab
4 Chandigarh
5 Uttaranchal
6 Haryana
7 Delhi
8 Rajasthan
9 Uttar Pradesh
10 Bihar
17 Meghalaya
18 Assam
19 West Bengal
20 Jharkhand
21 Orissa
22 Chattisgarh
23 Madhya Pradesh
24 Gujarat
27 Maharashtra
28 Andhra Pradesh
29 Karnataka
30 Goa
32 Kerala
33 Tamil Nadu
34 Pondicherry
bloc_vill Block/Village 3-5 3 0
rura_urba Rural/Urban 6-6 1 0 Code Value
1 Rural
2 Urban
29
38. National Household Survey of Income and Expenditure (2004-05)
Variable Description/Label Fields/ Width/ Decimals Code Sepcification
Columns Length
intr_numb Interview Number 7-11 5 0
hous_size Household Size 12-13 2 0
bpl_card_owne BPL Card Ownership 14-14 1 0 Code Value
0 No response
1 Yes
2 No
owne_dwel_unit Ownership of Dwelling Unit 15-15 1 0 Code Value
1 Owned
2 Hired
3 Others
stru_dwel_unit Structure of the Dwelling unit 16-16 1 0 Code Value
1 Kutcha
2 Semi-pucca
3 Pucca
is_rent Is Part of the Dwelling Rented 17-17 1 0 Code Value
1 Yes
2 No
rent_hous Rent of the Household 18-22 5 0
dura_stay Duration of Stay 22-24 2 0
numb_room Number of Rooms 25-26 2 0
avail_safe_wate Availability of Safe Drinking Water 27-27 1 0 Code Value
0 No response
1 Yes
2 No
30
39. National Household Survey of Income and Expenditure (2004-05)
Variable Description/Label Fields/ Width/ Decimals Code Sepcification
Columns Length
avail_kitc Availability of Seperate Kitchen 28-28 1 0 Code Value
0 No response
1 Yes
2 No
avail_elec Availability of Electricity 29-29 1 0 Code Value
0 No response
1 Yes
2 No
avail_latr Availability of Latrine 30-30 1 0 Code Value
0 No response
1 Yes
2 No
freq_elec Frequency of Electricity 31-31 1 0
dura_elec Duration of Electricity 32-33 2 0
land_owne Land Owned (Acres) 34-39 6 2
land_poss Land Possessed (Acres) 40-45 6 2
bank_acco Do any Member of the Household have any 46-46 1 0 Code Value
Account in the Financial Institution 1 Yes
2 No
outs_loan Loan Outstanding 47-47 1 0 Code Value
1 Yes
2 No
31
40. National Household Survey of Income and Expenditure (2004-05)
Variable Description/Label Fields/ Width/ Decimals Code Sepcification
Columns Length
mem1_id Member-1 Identification No. 48-49 2 0
mem1_sex Member-1 Sex 50-50 1 0 Code Value
1 Male
2 Female
mem1_age Member-1 Age 51-52 2 0
mem1_marit Member-1 Marital Status 53-53 1 0 Code Value
1 Married
2 Unmarried
3 Divorced
4 Widowed
mem1_educ Member-1 Educational Qualification 54-54 1 0 Code Value
1 Illiterate
2 Up to primary
3 Middle ( 8th)
4 Matric(10 th)
5 Higher secondary
6 Graduate
7 Post graduate
8 diploma/ vocational
9 Others
32
41. National Household Survey of Income and Expenditure (2004-05)
Variable Description/Label Fields/ Width/ Decimals Code Sepcification
Columns Length
mem1_actv Member-1 Activity status 55-56 2 0 Code Value
1 Own account worker
2 Employer
3 Unpaid family worker
4 Regular salary/wage employer
5 Casual employer
6 Unemployed
7 Pensioner/remittance
8 Student
9 Housewife
10 Unfit for work
11 Others
12 Not applicable
mem2_id Member-2 Identification No. 57-58 2 0
mem2_sex Member-2 Sex 59-59 1 0 Same as for Member 1
mem2_age Member-2 Age 60-61 2 0
mem2_marit Member-2 Marital Status 62-62 1 0 Same as for Member 1
mem2_educ Member-2 Educational Qualification 63-63 1 0 Same as for Member 1
mem2_actv Member-2 Activity status 64-65 2 0 Same as for Member 1
mem3_id Member-3 Identification No. 66-67 2 0
mem3_sex Member-3 Sex 68-68 1 0 Same as for Member 1
mem3_age Member-3 Age 69-70 2 0
33
42. National Household Survey of Income and Expenditure (2004-05)
Variable Description/Label Fields/ Width/ Decimals Code Sepcification
Columns Length
mem3_marit Member-3 Marital Status 71-71 1 0 Same as for Member 1
mem3_educ Member-3 Educational Qualification 72-72 1 0 Same as for Member 1
mem3_actv Member-3 Activity status 73-74 2 0 Same as for Member 1
mem4_id Member-4 Identification No. 75-76 2 0
mem4_sex Member-4 Sex 77-77 1 0 Same as for Member 1
mem4_age Member-4 Age 78-79 2 0
mem4_marit Member-4 Marital Status 80-80 1 0 Same as for Member 1
mem4_educ Member-4 Educational Qualification 81-81 1 0 Same as for Member 1
mem4_actv Member-4 Activity status 82-83 2 0 Same as for Member 1
mem5_id Member-5 Identification No. 84-85 2 0
mem5_sex Member-5 Sex 86-86 1 0 Same as for Member 1
mem5_age Member-5 Age 87-88 2 0
mem5_marit Member-5 Marital Status 89-89 1 0 Same as for Member 1
mem5_educ Member-5 Educational Qualification 90-90 1 0 Same as for Member 1
mem5_actv Member-5 Activity status 91-92 2 0 Same as for Member 1
mem6_id Member-6 Identification No. 93-94 2 0
34
43. National Household Survey of Income and Expenditure (2004-05)
Variable Description/Label Fields/ Width/ Decimals Code Sepcification
Columns Length
mem6_sex Member-6 Sex 95-95 1 0 Same as for Member 1
mem6_age Member-6 Age 96-97 2 0
mem6_marit Member-6 Marital Status 98-98 1 0 Same as for Member 1
mem6_educ Member-6 Educational Qualification 99-99 1 0 Same as for Member 1
mem6_actv Member-6 Activity status 100-101 2 0 Same as for Member 1
mem7_id Member-7 Identification No. 102-103 2 0
mem7_sex Member-7 Sex 104-104 1 0 Same as for Member 1
mem7_age Member-7 Age 105-106 2 0
mem7_marit Member-7 Marital Status 107-107 1 0 Same as for Member 1
mem7_educ Member-7 Educational Qualification 108-108 1 0 Same as for Member 1
mem7_actv Member-7 Activity status 109-110 2 0 Same as for Member 1
mem8_id Member-8 Identification No. 111-112 2 0
mem8_sex Member-8 Sex 113-113 1 0 Same as for Member 1
mem8_age Member-8 Age 114-115 2 0
mem8_marit Member-8 Marital Status 116-116 1 0 Same as for Member 1
mem8_educ Member-8 Educational Qualification 117-117 1 0 Same as for Member 1
35
44. National Household Survey of Income and Expenditure (2004-05)
Variable Description/Label Fields/ Width/ Decimals Code Sepcification
Columns Length
mem8_actv Member-8 Activity status 118-119 2 0 Same as for Member 1
mem9_id Member-9 Identification No. 120-121 2 0
mem9_sex Member-9 Sex 122-122 1 0 Same as for Member 1
mem9_age Member-9 Age 123-124 2 0
mem9_marit Member-9 Marital Status 125-125 1 0 Same as for Member 1
mem9_educ Member-9 Educational Qualification 126-126 1 0 Same as for Member 1
mem9_actv Member-9 Activity status 127-128 2 0 Same as for Member 1
mem10_id Member-10 Identification No. 129-130 2 0
mem10_sex Member-10 Sex 131-131 1 0 Same as for Member 1
mem10_age Member-10 Age 132-133 2 0
mem10_marit Member-10 Marital Status 134-134 1 0 Same as for Member 1
mem10_educ Member-10 Educational Qualification 135-135 1 0 Same as for Member 1
mem10_actv Member-10 Activity status 136-137 2 0 Same as for Member 1
mem11_id Member-11 Identification No. 138-139 2 0
mem11_sex Member-11 Sex 140-140 1 0 Same as for Member 1
mem11_age Member-11 Age 141-142 2 0
36
45. National Household Survey of Income and Expenditure (2004-05)
Variable Description/Label Fields/ Width/ Decimals Code Sepcification
Columns Length
mem11_marit Member-11 Marital Status 143-143 1 0 Same as for Member 1
mem11_educ Member-11 Educational Qualification 144-144 1 0 Same as for Member 1
mem11_actv Member-11 Activity status 145-146 2 0 Same as for Member 1
mem12_id Member-12 Identification No. 147-148 2 0
mem12_sex Member-12 Sex 149-149 1 0 Same as for Member 1
mem12_age Member-12 Age 150-151 2 0
mem12_marit Member-12 Marital Status 152-152 1 0 Same as for Member 1
mem12_educ Member-12 Educational Qualification 153-153 1 0 Same as for Member 1
mem12_actv Member-12 Activity status 154-155 2 0 Same as for Member 1
mem13_id Member-13 Identification No. 156-157 2 0
mem13_sex Member-13 Sex 158-158 1 0 Same as for Member 1
mem13_age Member-13 Age 159-160 2 0
mem13_marit Member-13 Marital Status 161-161 1 0 Same as for Member 1
mem13_educ Member-13 Educational Qualification 162-162 1 0 Same as for Member 1
mem13_actv Member-13 Activity status 163-164 2 0 Same as for Member 1
mem14_id Member-14 Identification No. 165-166 2 0
37
46. National Household Survey of Income and Expenditure (2004-05)
Variable Description/Label Fields/ Width/ Decimals Code Sepcification
Columns Length
mem14_sex Member-14 Sex 167-167 1 0 Same as for Member 1
mem14_age Member-14 Age 168-169 2 0
mem14_marit Member-14 Marital Status 170-170 1 0 Same as for Member 1
mem14_educ Member-14 Educational Qualification 171-171 1 0 Same as for Member 1
mem14_actv Member-14 Activity status 172-173 2 0 Same as for Member 1
mem15_id Member-15 Identification No. 174-175 2 0
mem15_sex Member-15 Sex 176-176 1 0 Same as for Member 1
mem15_age Member-15 Age 177-178 2 0
mem15_marit Member-15 Marital Status 179-179 1 0 Same as for Member 1
mem15_educ Member-15 Educational Qualification 180-180 1 0 Same as for Member 1
mem15_actv Member-15 Activity status 181-182 2 0 Same as for Member 1
mem16_id Member-16 Identification No. 183-184 2 0
mem16_sex Member-16 Sex 185-185 1 0 Same as for Member 1
mem16_age Member-16 Age 186-187 2 0
mem16_marit Member-16 Marital Status 188-188 1 0 Same as for Member 1
mem16_educ Member-16 Educational Qualification 189-189 1 0 Same as for Member 1
38
47. National Household Survey of Income and Expenditure (2004-05)
Variable Description/Label Fields/ Width/ Decimals Code Sepcification
Columns Length
mem16_actv Member-16 Activity status 190-191 2 0 Same as for Member 1
mem17_id Member-17 Identification No. 192-193 2 0
mem17_sex Member-17 Sex 194-194 1 0 Same as for Member 1
mem17_age Member-17 Age 195-196 2 0
mem17_marit Member-17 Marital Status 197-197 1 0 Same as for Member 1
mem17_educ Member-17 Educational Qualification 198-198 1 0 Same as for Member 1
mem17_actv Member-17 Activity status 199-200 2 0 Same as for Member 1
mem18_id Member-18 Identification No. 201-202 2 0
mem18_sex Member-18 Sex 203-203 1 0 Same as for Member 1
mem18_age Member-18 Age 204-205 2 0
mem18_marit Member-18 Marital Status 206-206 1 0 Same as for Member 1
mem18_educ Member-18 Educational Qualification 207-207 1 0 Same as for Member 1
mem18_actv Member-18 Activity status 208-209 2 0 Same as for Member 1
mem19_id Member-19 Identification No. 210-211 2 0
mem19_sex Member-19 Sex 212-212 1 0 Same as for Member 1
mem19_age Member-19 Age 213-214 2 0
39