Draft data-documentation

National Survey onHousehold Income and Expenditure

Data – Documentation

Study sponsored by:

National Council of Applied Economic Research (NCAER)

Reference Year

2004-2005

DRAFT

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

National Household Survey of Income and Expenditure (2004-05)National Household Survey of Income and Expenditure (2004-05)

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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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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

income and expenditure surveys1, 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;


2-10 acres;


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

Stage I Stage II Stage IIIState Number ofNSS

RegionsTotal

districtsSampledistricts

Totalvillages

Samplevillages

Listedhouseholds

Samplehouseholds

Himachal Pradesh 1 12 6 17,495 32 2,736 512Punjab 2 17 8 12,278 48 4,983 768Chandigarh 1 1 1 23 5 500 78Uttaranchal 1 13 6 15,761 30 3,044 480Haryana 2 19 9 6,764 47 4,862 752Delhi 1 9 1 158 6 668 88Rajasthan 4 32 16 39,753 118 12,036 1,888Uttar Pradesh 4 70 29 97,942 274 30,356 4,384Bihar 2 37 18 39,018 196 21,721 3,136Meghalaya 1 7 5 - 10 991 160Assam 3 23 11 25,124 67 6,419 1,072West Bengal 4 17 9 37,955 123 12,438 1,968Jharkhand 1 18 9 29,354 59 5,930 944Orissa 3 30 14 47,529 86 9,958 1,376Chhattisgarh 1 15 7 19,744 49 4,924 784Madhya Pradesh 6 45 22 52,117 132 14,092 2,112Gujarat 5 25 12 18,066 90 10,659 1,440Maharashtra 6 33 16 41,095 157 18,057 2,512Andhra Pradesh 4 22 12 26,614 160 16,619 2,560Karnataka 4 27 14 27,481 103 11,969 1,648Goa 1 2 2 347 10 1,166 160Kerala 2 14 7 1,364 63 6,368 848Tamil Nadu 4 30 14 15,400 101 10,443 1,616Pondicherry 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

Townclass

Town population('000)

Totaltowns

Sampletowns

Samplingfraction

I > 10000 3 3 1.00II 5000-10000 3 3 1.00III 1000-5000 29 29 1.00IV 500-1000 37 37 1.00V 200-500 98 98 1.00VI 100-200 219 56 0.26VII 50-100 396 44 0.11VIII 20-50 1,135 28 0.02IX < 20 2,270 44 0.02Total 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

Stage I Stage II Stage IIIState Number ofNSS

RegionsTotaltowns

Sampletowns

Totalblocks

Sampleblocks

Listedhouseholds

Samplehouseholds

Himachal Pradesh 1 56 2 22 5 502 70Punjab 2 157 12 472 74 7,596 1,036Chandigarh 1 1 1 21 10 1,000 140Uttaranchal 1 76 3 129 18 1,881 252Haryana 2 97 13 596 74 7,543 1,036Delhi 1 4 1 289 60 7,197 840Rajasthan 4 216 19 851 114 11,568 1,596Uttar Pradesh 4 670 51 2,036 316 31,975 4,424Bihar 2 120 14 444 75 7,973 1,050Meghalaya 1 10 1 6 6 600 84Assam 3 110 5 100 20 1,940 280West Bengal 4 239 18 - 142 14,620 1,988Jharkhand 1 95 10 860 68 6,896 952Orissa 3 132 8 322 45 4,501 630Chhattisgarh 1 84 8 473 44 4,412 616Madhya Pradesh 6 368 19 799 114 11,516 1,596Gujarat 5 190 19 572 146 14,615 2,044Maharashtra 6 347 35 2,220 273 31,553 3,822Andhra Pradesh 4 173 27 1,172 195 20,426 2,730Karnataka 4 237 22 905 153 18,819 2,142Goa 1 38 2 12 4 440 56Kerala 2 98 13 1,019 79 8,030 1,106Tamil Nadu 4 68 37 2,272 207 21,937 2,898Pondicherry 1 4 2 23 13 1,273 182ALL 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 3,066Punjab 4,044 5,285 9,329Chandigarh 434 661 1,095Uttaranchal 2,506 1,257 3,763Haryana 4,612 5,453 10,065Delhi 475 3,960 4,435Rajasthan 10,744 8,635 19,379Uttar Pradesh 28,819 23,462 52,281Bihar 15,607 5,272 20,879Meghalaya 866 308 1,174Assam 4,803 1,107 5,910West Bengal 10,185 8,885 19,070Jharkhand 4,999 4,823 9,822Orissa 7,046 3,040 10,086Chattisgarh 3,998 2,948 6,946Madhya Pradesh 11,609 8,090 19,699Gujarat 6,760 9,700 16,460Maharashtra 13,091 18,158 31,249Andhra Pradesh 11,314 11,245 22,559Karnataka 8,134 9,608 17,742Goa 772 281 1,053Kerala 3,635 4,539 8,174Tamil Nadu 7,033 12,163 19,196Pondicherry 740 777 1,517Total 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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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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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.


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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.


17

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


18

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


19

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.


20

• Other Casual Labour: A person casually engaged in other’s non-farm enterprises (both household


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


21

§ 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


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


22

§ 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:


23

- 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:


24

- 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.


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• 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'


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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


27

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.


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Variable List for the Data


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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.


29

Variable Description/Label Fields/Columns

Width/Length

Decimals Code Sepcification

stat State Codes 1-2 2 0 Code Value2 Himachal Pradesh3 Punjab4 Chandigarh5 Uttaranchal6 Haryana7 Delhi8 Rajasthan9 Uttar Pradesh10 Bihar17 Meghalaya18 Assam19 West Bengal20 Jharkhand21 Orissa22 Chattisgarh23 Madhya Pradesh24 Gujarat27 Maharashtra28 Andhra Pradesh29 Karnataka30 Goa32 Kerala33 Tamil Nadu34 Pondicherry

bloc_vill Block/Village 3-5 3 0

rura_urba Rural/Urban 6-6 1 0 Code Value1 Rural2 Urban


30


Width/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 Value0 No response1 Yes2 No

owne_dwel_unit Ownership of Dwelling Unit 15-15 1 0 Code Value1 Owned2 Hired3 Others

stru_dwel_unit Structure of the Dwelling unit 16-16 1 0 Code Value1 Kutcha2 Semi-pucca3 Pucca

is_rent Is Part of the Dwelling Rented 17-17 1 0 Code Value1 Yes2 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 Value0 No response1 Yes2 No


31


Width/Length


avail_kitc Availability of Seperate Kitchen 28-28 1 0 Code Value0 No response1 Yes2 No

avail_elec Availability of Electricity 29-29 1 0 Code Value0 No response1 Yes2 No

avail_latr Availability of Latrine 30-30 1 0 Code Value0 No response1 Yes2 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 anyAccount in the Financial Institution

46-46 1 0 Code Value1 Yes2 No

outs_loan Loan Outstanding 47-47 1 0 Code Value1 Yes2 No


32


Width/Length


mem1_id Member-1 Identification No. 48-49 2 0

mem1_sex Member-1 Sex 50-50 1 0 Code Value1 Male2 Female

mem1_age Member-1 Age 51-52 2 0

mem1_marit Member-1 Marital Status 53-53 1 0 Code Value1 Married2 Unmarried3 Divorced4 Widowed

mem1_educ Member-1 Educational Qualification 54-54 1 0 Code Value1 Illiterate2 Up to primary3 Middle ( 8th)4 Matric(10 th)5 Higher secondary6 Graduate7 Post graduate8 diploma/ vocational9 Others


33


Width/Length


mem1_actv Member-1 Activity status 55-56 2 0 Code Value1 Own account worker2 Employer3 Unpaid family worker4 Regular salary/wage employer5 Casual employer6 Unemployed7 Pensioner/remittance8 Student9 Housewife10 Unfit for work11 Others12 Not applicable


mem2_sex Member-2 Sex 59-59 1 0 Same as for Member 1


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





34


Width/Length



















35


Width/Length



















36


Width/Length



















37


Width/Length



















38


Width/Length



















39


Width/Length



















40


Width/Length



















41


Width/Length



















42


Width/Length



nic_1998 Principal Industry Code (NIC 98) 264-265 2 0 Code Value1 Agriculture, Livestock, fishing, hunting

and forestry2 Mining & quarrying3 Manufacturing4 Electricity, gas and water supply5 Construction6 Hotel and restaurants7 Transport, storage and communication8 Public administration and defence9 Financial intermediation10 Education11 Health and social work12 Real estate, renting and business activities13 Wholesale/ retail trade , repair household

goods14 Private households15 Others

nco_1968 Principal Occupation Code (NCO 68) 266-266 1 0 Code Value1 Professional, technical and related workers2 Administrative, executive and managerial

workers3 Clerical and related workers4 Sales workers5 Service workers6 Farmers, fishermen, hunters, loggers and

related workers7 Production and related workers, transport

equipment8 Workers not classified by occupation


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Width/Length


prim_sour_inco Primary Source of Income 267-268 2 0 Code Value1 Regular salary/wages2 Self employed in non-agriculture3 Agricultural labour4 Casual labour5 Self employed in agriculture6 Rental7 Interest /remittance/dividend/royalty8 Pension/Bonus9 Social insurance/ assistance10 Others

inco_sala Annual Income from Salary 269-279 11 2

inco_non_agri Annual Income from Self-employment inNon-agriculture

280-290 11 2

inco_labo Annual Income from Labour 291-300 10 2

inco_agri Annual Income from Self-employment inAgriculture

301-311 11 2

inco_othe Annual Income from Other Sources 312-322 11 2

inco_tota Total Income 323-333 11 2

expe_food Annual Expenditure on Food 334-342 9 2

expe_hous Annual Expenditure on Housing 343-351 9 2

expe_educ Annual Expenditure on Education 352-360 9 2


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Width/Length


expe_cloth Annual Expenditure on Clothing andFootwear

361-369 9 2

expe_dura Annual Expenditure on Durable Goods 370-378 9 2

expe_health Annual Expenditure on Health 379-387 9 2

expe_tran Annual Expenditure on Transport 373-380 9 2

expe_othe Annual Expenditure on Other Items 388-396 9 2

expe_tota Annual Household Routine Expenditure 397-405 9 2

day_to_day_deci Day to Day Decision 406-406 1 0 Code Value1 Parents2 Chief earner3 Highest qualified member4 Grownup children5 Ladies6 All adults7 Friends/relatives8 Others

deci_high_educ Higher Education 407-407 1 0 Code Value1 Parents2 Chief earner3 Highest qualified member4 Grownup children5 Ladies6 All adults7 Friends/relatives8 Others


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Width/Length


deci_dura_purc Durable Purchase 408-408 1 0 Code Value1 Parents2 Chief earner3 Highest qualified member4 Grownup children5 Ladies6 All adults7 Friends/relatives8 Others

deci_marr_son Marriage of Son 409-409 1 0 Code Value1 Parents2 Chief earner3 Highest qualified member4 Grownup children5 Ladies6 All adults7 Friends/relatives8 Others

deci_purc_prop Purchase/Ownership of Property 410-410 1 0 Code Value1 Parents2 Chief earner3 Highest qualified member4 Grownup children5 Ladies6 All adults7 Friends/relatives8 Others


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Width/Length


majo_sour_wate Major Source of Drinking Water 411-411 1 0 Code Value1 Hand pump2 Well3 Pond4 River5 Pipe water6 Tap7 Others

majo_sour_cook Major Source of Cooking 412-412 1 0 Code Value1 Fire wood2 Dung cake3 Gobar gas4 Kerosesne5 LPG6 Electricity7 Solar energy8 Others

majo_sour_light Major Source of Lighting 413-413 1 0 Code Value1 Fire wood2 Dung cake3 Gobar gas4 Kerosesne5 LPG6 Electricity7 Solar energy8 Others


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Width/Length


majo_sour_fina Major Source of Finance 414-414 1 0 Code Value1 Post office2 Commercial bank3 Regional Rural bank4 Co-operatives5 Money lender6 Others

majo_sour_info Major Source of Information 415-415 1 0 Code Value1 Television2 Radio/transistor3 Newspaper4 Local people5 Others

hous_weig Household Weight 416-424 9 2

popu_weig Population Weight 425-433 9 2

Draft data-documentation

Documents

Transcript of Draft data-documentation