NSSO

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NSSO

An econometric analysis of Unit level Data from NSS 68th round Employment-Unemployment Survey- A Sample Case

For the below econometric analysis, the data extraction to analysis was done in STATA software.

Background:

National Sample Surveys (NSS) 68th round (2011-12) indicate that around 61.6 per cent of rural working-age women (15-59 yrs) were principally engaged in housework or domestic duties. While this has increased by about 6 percentage points between 1999-2000 and 2011-12, in the same period, the work participation rate among rural working-age women has declined by about 11 percentage points. This has become an intense area of debate among economists, on the reasons behind such a phenomenon, given the spectacular growth in the economy in the same period.

It has also been argued that this was due to the steep decline in availability of work for women in rural areas, due to rising landlessness and declining labour absorption in agriculture on one hand and their inability to access urban non-agricultural employment, given the lack of basic work amenities and problems of security.

In this context, it is pertinent to note that a large proportion of women engaged in domestic duties do not report themselves to be unemployed, even if they have some free time and they may be willing to seek job/attend work, as they may not be willing to go outside the household premises for that purpose. Nonetheless, they may be willing to accept certain types of work, if the work is made available to them at their household premises.

As per NSS definition, the women engaged in domestic duties are generally not considered part of the labour force i.e. neither working nor available for work, excepting those who have additional subsidiary employment. As per the estimates of NSS 68th round Employment & Unemployment Survey (2011-12), there are around 15.75 Crores women (age more than 15 years), who are engaged in domestic duties in rural sector and 17 per cent of these women have only subsidiary employment (14 per cent as self-employed in agriculture & 3 per cent as casual worker in agriculture), thus 83 per cent are purely non-workers. Thus, by this definition, we have an estimated 13.07 Crores women engaged in domestic duties alone, who are non-workers.

Further, the restrictive definition of unemployed, as persons, who during the reference period actively sought work and did not find any, may have excluded a significant portion of the aforesaid women engaged purely in domestic duties in rural sector. These women from their past experience and observation of the shrinking labour market may not have sought work as they might have known that remunerative employment was not possible. Thus, not making an attempt to seek work does not reflect lack of interest or inability to work. With no means of obtaining remunerative employment, they may have resigned themselves to un-remunerative and minimally productive forms of labour like collecting food, fuel and fodder and mending clothes for the use of their household. If they are considered as part of the workforce, it is estimated that the estimated unemployment rate among rural women in the working age group (15-59 years) would go up very sharply from 1.7 per cent to 50.7 per cent.

Preferred choice for additional work by rural women engaged in domestic duties, particularly dairying at the macro level

At the outset, it would be of interest to get an idea of the demographic changes in the decade between 1999-00 and 2011-12 for rural women, who were engaged in domestic duties. As can be seen from the Table-1 below, not much changes are observed in the age group 15-29 years but for all other age groups, we find sharp increases ranging from 7 to 11 per cent. These also underlines the fact that the engagement of women in the middle age groups have increased significantly in domestic duties, reasons for which, we have discussed earlier.

Table: Per cent of rural women above 15 yrs and engaged in domestic duties (usual principal status code 92 & 93) with their preference for additional work

Prefered Work => Tailoring Dairy Other AH Poultry Spinning & Weaving Others Total
NSS Survey Year => 1999-00 2011-12 1999-00 2011-12 1999-00 2011-12 1999-00 2011-12 1999-00 2011-12 1999-00 2011-12 1999-00 2011-12
Age Group (yrs)  
15-19 19 26 8 4 2 2 4 3 4 4 6 5 43 48
20-24 16 21 9 5 3 3 4 3 4 5 7 6 43 47
25-29 14 17 11 7 3 4 5 3 4 5 6 6 43 46
30-59 6 8 10 7 3 4 3 4 2 2 4 4 29 30
60 & above 0 1 3 2 1 1 1 1 0 0 1 1 6 5
All 10 12 9 6 3 3 3 3 3 3 5 4 33 34

Table: State-wise disaggregated analysis of rural women engaged in domestic duties and their preference for dairying

Region State Willing to accept any work Willing to accept Dairy Willing to accept Dairy (as a % of Total) Willing to accept Dairy as Regular full time Occupation (as a % of willing to accept Dairy) Willing to accept Dairy as Regular part time Occupation (as a % of willing to accept Dairy) Have requisite skill to perform Dairy (as a % of willing to accept Dairy) Easy Initial Finance require for Dairy Working Finance require for Dairy
East Assam 24,01,621 1,36,282 5.67 22.59 76.76 49.21 48.18 41.98
East Bihar 64,02,415 12,74,524 19.91 13.65 84.09 67.40 65.56 22.59
East Chattisgarh 6,62,651 60,694 9.16 3.34 96.01 70.16 54.75 16.24
East Jharkhand 14,18,249 2,17,763 15.35 38.89 61.11 39.05 76.54 13.71
East Orissa 32,69,934 7,61,234 23.28 11.96 87.41 59.22 75.37 23.17
East West Bengal 64,75,343 7,40,035 11.43 24.84 73.72 77.12 50.10 39.04
East Total 206,30,213 31,90,532 15.47 17.75 80.82 65.05 64.11 26.64
North Haryana 6,39,994 82,286 12.86 38.20 61.19 80.15 25.88 32.39
North Himachal Pradesh 1,87,339 9,776 5.22 64.10 35.91 83.73 73.05 22.65
North Jammu & Kashmir 6,99,598 74,832 10.70 7.19 90.48 87.24 58.87 29.39
North Punjab 14,96,611 3,75,669 25.10 16.96 82.97 91.47 77.47 14.85
North Rajasthan 25,81,924 4,35,578 16.87 49.18 43.57 60.45 73.74 20.11
North Uttar Pradesh 116,54,086 26,24,729 22.52 17.50 79.16 83.20 69.60 23.87
North Uttaranchal 4,03,963 78,525 19.44 23.52 73.81 83.57 60.83 32.43
North Total 176,63,515 36,81,395 20.84 21.69 74.94 81.37 69.52 22.99
South Andhra Pradesh 12,01,372 2,33,193 19.41 21.78 74.91 89.64 77.73 14.25
South Karnataka 16,03,172 4,46,839 27.87 36.29 60.63 74.95 53.95 32.87
South Kerala 14,83,222 2,67,273 18.02 32.76 64.24 72.21 78.72 12.36
South Tamil Nadu 13,67,035 2,62,407 19.20 25.66 65.96 67.35 75.10 15.53
South Total 56,54,801 12,09,712 21.39 30.41 65.34 75.53 68.59 20.99
West Goa 27,564 120 0.44 100.00 100.00 55.00
West Gujarat 12,86,199 3,40,690 26.49 18.55 81.32 77.33 46.96 44.99
West Madhya Pradesh 34,31,666 3,79,681 11.06 24.49 65.15 71.72 84.38 4.04
West Maharashtra 35,03,515 3,97,713 11.35 17.71 78.89 58.96 57.83 32.39
West Total 82,48,944 11,18,204 13.56 20.27 74.96 68.89 63.53 26.60
All India Total 529,48,087 92,59,739 17.49 21.52 75.47 73.49 66.79 24.39


Educational Levels wise preference

Also, the following charts can be prepared as below indicating the preference of women doing domestic duties to take up the additional work.

Emp unemp1

Preference based on age group and education level, social group, Occupation type & Zone

Emp unemp2

NSSO

Widening of Horizons-NSSO Surveys

The 75th round NSSO survey would also include information on communicable diseases, Swachh Bharat and education being attained by specially-abled persons for the first time in the country during one year from July 2017 till June 2018.

With one more feature in the pocket of NSSO, the household social consumption for education survey include students from three years, that is, pre-primary level school-goers up to thirty-five years. Whereas, in the previous round of 2011-12, the upper age limit of students was bracketed at 29 years.

Vocational and technical education would form a special module and also mothers and their newborns aged below 1 years of age will be considered a part of the household in which the baby was born which is also one more notable shift from previous survey parameters.

The newly introduced module on Swachh Bharat would have focus on the existence of toilets per household and garbage disposal facilities.

The national sample size for the 75th round is 30,792.

Data collection would be followed by data collation and validation prior to publication as per the set procedures before release of official estimates for the year 2017.

NSSO

Social consumption Survey: Key Indicators on Education

The below analysis was done by extracting and analysing NSSO unit level data of 71st Round in STATA.

Background

In rural areas, literacy rate was seen as 71% compared to 86% in urban areas. Also among persons of age 7 years and above male literacy rate being substantially higher (83%) than female literacy rate (67%). Similarly it was found in the rural areas, nearly 4.5% of males and 2.2% of females completed education level of ‘graduation and above’ while in the urban areas 17% of males and 13% of females completed this level of education.

Similar survey was conducted by NSSO during July 2007 – June 2008 as a part of its 64th Round.

The main objective of survey on ‘Social Consumption: Education’ was to assess the (a) participation of persons aged 5-29 years in pursuit of education, (b) extent of use of educational infrastructure, facilities and incentives provided by Government, (c) private expenditure incurred by households on education, (d) the extent of educational wastage in terms of dropping-out and discontinuance and its causes, and (e) IT literacy of persons aged 14 years and above.

Sample Size

The survey covered entire country with samples taken from 36,479 households in rural areas and 29,447 households in urban areas from 4,577 villages and 3,720 urban blocks.

Key Indicators

Some key indicators on various aspects of social consumption on education are calculated using the unit level survey data are as follows:

I. Literacy rates rates

Literacy rate among persons of age 7 years and above in India was 75%. In rural areas, literacy rate was 71% compared to 86% in urban areas.

Differences in literacy rate among persons of age 7 years and above was observed with male literacy rate being substantially higher (83%) than female literacy rate (67%).

Adult literacy (age 15 years and above) rate in India was around 71%. For adults also, literacy rate in rural areas was lower than that in urban areas. In rural areas, adult literacy rate was 64% as compared to 84% in urban areas.

II. Accessibility of nearest primary, upper primary and secondary school

No significant difference between rural and urban India existed in terms of distance for physical access to primary schooling. In both rural and urban areas, nearly 99% households reported availability of primary school within 2 kms from the house.

For accessing educational institutions providing higher level of learning, say upper primary or secondary, a lower proportion of households in rural areas compared to the households in urban areas reported existence of such facilities within 2 kms.

Nearly 86% of rural households and 96% of urban households reported upper primary schools within a distance of 2 kms from the house while nearly 60% of rural households and 91% of urban households reported secondary schools at such a distance.

III. Completed level of education among persons of age 5 years and above

The proportion of persons having completed higher level of education, say, graduation and above, was more in the urban areas than in the rural areas.

In the rural areas, nearly 4.5% of males and 2.2% of females completed education level of ‘graduation and above’ while in the urban areas 17% of males and 13% of females completed this level of education.

IV. Attendance and enrolment

In both rural and urban areas, a very small proportion of persons (nearly 1 per cent) in the age group 5-29 years, were currently enrolled but not attending educational institutions.

In rural areas 58.7% of males and 53% of females in the 5-29 age-group were currently attending educational institution. In urban areas, the percentages being 57% for males and 54.6% for females.

V. Attendance ratios

Gross Attendance Ratio for level ‘primary’ was nearly 100% for both males and females in rural and urban areas.

Gross Attendance Ratio at level ‘primary to higher secondary’ was 91% and 88% for rural males and females respectively, marginally lower as compared to 93% for both males and females in urban sector.

Net Attendance Ratio in India at primary level was 84% for male and 83% for female children in the age-group 6-10 years, the official age-group for Classes I-V.

There was no major rural-urban or male-female disparity at all-India level till elementary level (primary and upper primary) in the Net Attendance Ratio.

NSSO

NSSO Overview

The National Sample Survey (NSS) is one of the oldest continuing household sample surveys in the developing world. The survey is conducted on a regular basis by the National Sample Survey Organisation (NSSO), Indias premier data collection agency. Since 1972, the NSSO has fallen under the Ministry of Statistics and Program Implementation of the Government of India (GOI).

The role of the NSS must be seen in the broader context of Indian economic development. At independence and through much of its early development, the country was faced with a subsistence production structure (mainly in agriculture) characterized by mass poverty and hunger.

Systematic data on the extent, magnitude, and patterns of poverty, as well as on household consumption patterns and trends, were not readily available for informed policy interventions. To remedy this, the GOI launched the NSS to gather nationally representative information on household structure, consumption, and production.

History

The first NSSO round was conducted in19501951and included information on land utilization, prices of essential commodities, and daily wages of skilled and unskilled laborers at the village level. At the household level, data was obtained on demographic characteristics as well as land ownership, cultivation, and utilization. In addition, detailed data was gathered on monthly and weekly consumption, as well as on entrepreneurial activities, from a subset of the sampled households. The first round was based on a random of only 1,833 villages out of a total of 560,000.

Since that first round, more than sixty NSS rounds have been conducted. Naturally, both the organization and the surveys have undergone many changes since then.

Organizational View

At the organizational level, the technical wing of the NSSO was divested from the Indian Statistical Institute and placed under the direct control of the GOI. The field operations group was placed under the guidance of a governing council headed by an eminent academic and members drawn both from government and academia since 1970; it now functions as a full-fledged wing of the GOI.

Increased Sample Size

Important changes also occurred in the surveys themselves. With increased demand for more disaggregated information, the sample size of the rounds has expanded significantly, from 1,833 villages in the first round to more than 14,000 rural villages and urban blocks in more recent rounds. With the large increase in sample size, a decision was made (beginning with the197374 round) to split the rounds into two:

quinquennial (or thick) rounds done at approximately five-year intervals on a large sample of households (about 120,000) and thinrounds undertaken during intervening periods on smaller samples (approximately 35 to 40 percent of the thick-round samples).

The expansion of the sample size, especially for the collection of data on consumption expenditure and employment, has allowed NSS estimates to be representative at the below-state (but not district) level. The NSSO is representative at the level of regionscollections of several districts grouped together on the basis of broadly similar agro-climatic conditions. Regions are not administrative units. The NSS has delineated a total of seventy-eight regions in the country.

Coverage

The coverage of the NSSO varies over the different rounds. Each round always obtains information on consumption and employment; however, the rounds also cover other subjects, such as health, schooling, or disability, in the form of additional modules. Thus, for instance, the fifty-eighth round focused on disability, housing conditions, village facilities, and urban slums, while the sixtieth round covered morbidity, health care, and conditions of the elderly. Since its inception, the NSSO has covered some fifty different subjects in its surveys, such as household debt and investment, literacy and culture, health, schooling, and village-level infrastructure.

Availability of NSSO Data

Until 1998 the unit record data from the NSSO was not available to the public.

This restricted considerably the wider use of the surveys by researchers. Indeed, only a few studies were based on the NSS data, including the measurement of poverty and unemployment and the construction of price indices, such as those by Ahluwalia (1978), Bhattacharya et al. (1980), Jain and Tendulkar (1989, 1990), and Minhas et al. (1987, 1988). In 1998 the GOI made the NSS unit record data, retrospectively from the thirty-eighth round of 1983, available in the public domain at a modest fee. Since that time, numerous researchers have used the data to address a number of issues, such as health, nutrition, schooling, disability, small-scale industry, and food subsidies (Borah 2006; Deolalikar 2005; Gupta 2003; Subramanian and Deaton 1996). Poverty and, to a smaller extent, unemployment remain the two top issues that are explored by researchers with the NSS data (e.g., Datt 1999; Deaton and Dreze 2002; Dubey and Gangopadhyay 1998; Sen 2000; Sundaram 2001a, 2001b; Sundaram and Tendulkar 2001).

Constraints

The NSSO has sometimes changed its data collection methodology midstream, and this has affected the comparability of estimates over time.

This was particularly the case in the fifty-fifth round, when the NSSO adopted a different reporting period for certain types of consumption expenditures, rendering consumption and poverty estimates from that survey noncomparable to those from earlier periods.

Another weakness of the data is that, unlike some other national socioeconomic surveys (notably the National Socio-Economic Household Survey), there is no fixed rotation schedule for the special-interest modules that are attached to the core consumption-employment module of the NSSO. As a result, it is difficult to obtain nationally representative data on important topics such as health and education on a regular, ongoing basis. For instance, the NSSO included a health-care module in the fifty-second round conducted in 19951996, but this was not repeated until the sixtieth round in 2004. Likewise, the topic of rural assets and indebtedness was covered in the forty-eighth round in 1992 and only revisited in 2003 in the fifty-ninth round.

NSSO

70th Round of NSSO Debt and Investment Survey

Overview

National Sample Survey Office (NSSO) undertook All-lndia Debt and Investment Survey (AlDlS) in its 26th round (1971-72), 37th round (1982l, 48th round (1992) and 59tn round (2003) and latest survey on the assets and liabilities of the households was collected as in 2012.

Besides information on assets and liabilities, the survey gathered information on the amount of capital expenditure incurred by the households during the Agricultural Year 2O12-13, under different heads, like residential buildings, farm business and non-farm business

Objective

  • To obtain information on the stock of assets, incidence of indebtedness, capital formation and other indicators or rural/urban economy which will be of value in developing the credit structure in particular, and also for obtaining other allied information required in the field of planning and development.

Sample Size

Visits 1 & 2: This survey covers the whole of the Indian Union. Each sample FSU is being visited twice during this round in visit 1 and visit 2. Since the workload of the first visit (i.e. visit 1) is more, the first visit continues till the end of July 2013. Thus, period of the first visit is January – July 2013 and that of the second visit (i.e. visit 2) is August – December 2013.

The number of villages/blocks (FSU) surveyed was 4,529/3,507 and number of sampled households (SSU) surveyed were 110,800 in visit 1 and 108,421 in visit 2.

Important terms

House: Every structure, tent, shelter, etc. was a house irrespective of its use. It might be used for residential or non-residential purpose or both or even might be vacant.

Household: A group of persons normally living together and taking food from a common kitchen constituted a household.

Household size: The number of members of a household was its size.

Household classification: The household classification was based on the source of major income of the household

Categories of rural households

  • Cultivator: All households having operated area of land 0.002 hectare or more during the last 365 days preceding the date of survey are considered ‘cultivator households’.
  • Non-cultivator: All the remaining households

Categories of urban households

  • Self-employed and
  • Others

Average assets holdings (AVAs) per household: Average value of total physical and financial assets per household.

Incidence of indebtedness (IOI): A household was considered to be indebted if the household had any cash loan outstanding on 30.06.12.

Average amount of debt (AOD): Based on the debt of the indebted households, average amount of debt calculated.

Debt-asset ratio (DAR): is defined as the average amount of debt outstanding on a given date for a group of households expressed as a percentage of the average value of assets owned by them on the given date. Thus, this ratio reflects the burden of debt on any particular group of households on a given date.

Information in Debt and Investment Survey

The survey on Land and Livestock Holding contains information on

  • The assets of the household as on 30th June 2012, classified into
    • physical assets and
    • financial assets
  • The liabilities of the household as on 30th June 2012 in visit 1 and as on 30th June 2013 in visit 2
  • The amount of capital expenditure incurred by the household during July 2012 – June 2013 on
    • Residential plots, houses or buildings
    • Farm business, and
    • Non-farm business.

Besides collection of information on Debt and Investment, information was collected on some household characteristics such as

  • Household classification
  • Social group
  • Religion
  • Whether the household operated any land on Jhum cultivation during last 365 days, etc.

Some information on demographic particulars from each of the household members was also collected such as

  • Sex
  • Age
  • General education level etc.

Important Indicators

  • Assets
    • Average value of asset by occupational category of household and by decile class of household assets
    • Share of different components of assets in the total value of assets for each occupational category of households and for decile class of household assets
  • Indebtedness
    • Incidence of Indebtedness (IOI) and Average Amount of Debt (AOD) as on 30.06.2012 by occupational category of household and for decile class of household assets and for different social groups
    • Variation in IOI of households as on 30.06.2012 by nature of credit agency, by terms of interest and rate of interest
    • Variation in distribution of amount of cash debt by nature of credit agency, by terms of interest, rate of interest and by duration of cash dues
    • Distribution of indebted households and outstanding dues as on 30.06.2012 by broad purpose of loan
    • Debt-Asset ratio for decile class of household assets
  • Capital Formation
  1. Percentage of households reporting fixed capital expenditure, expenditure on purchase of land, average values (Rs.) of fixed capital expenditure and average values (Rs.) of expenditure on purchase of land per household for occupation categories/household asset holding classes during 01.07.2012 to 30.06.2013

STATA codes for extraction of data from .txt file

Before reading this section, you have to read “Ready reckoner NSSO Unit level Data Analysis”, “Importing text data into STATA using infix command”.

infix str round_centre_code 1-3 str FSU_No 4-8 str Round 9-10 str schedule_No 11-13 str samp 14-14 str sector 15-15 str state_region 16-17 str district 19-20 str stratum_No 21-22 str schedule_type 25-25 str sub_round 26-26 str sub_sample 27-27 str FOD_sub_region 28-31 str hamlet_subblock 32-32 str SSS 33-33 str HH_No 34-35 level 36-37 filler 38-42 HH_size 43-44 str NIC_08 45-49 str NCO_04 50-52 HH_type 53-53 religion 54-54 social_group 55-55 own_any_land 56-56 type_land 57-57 land_owned 58-65 land_leasedin 66-73 otherwise_possessed 74-81 land_leasedout 82-89 land_tot 90-97 Cultivated 98-105 Irrigated 106-113 spl_chr 114-115 blank 116-126 NSS 127-129 NSC 130-132 MLT 133-142 using R7001T1L02.TXT

infix code is used for importing .txt data into STATA. In the above code, with the help of data layout file as provided in supporting documents with the data; the name of variable, length of variable and type of variable is defined. For example, the first variable name is round_centre_code with length of 1-3 and type string as str was written before the name of variable, Similarly, there is one variable with name HH_type with length of variable is 53-53 and since the variable is integer type, it is not required to define the type of variable.

After the successful import of data, you can perform the various activities like calculation of Weights,  creating primary key,merging of the data from one level to other levels, Estimation of the required parameters with the help of weights and perform various statistical analysis.

The extracted files of 70th round of Debt and Investment survey are given in below:

Debt Investment survey

 

 

NSSO

70th Round of NSSO Land and Livestock Holdings Survey

Overview

A nation-wide survey on ‘Land and Livestock Holdings’ in 70th round (January 2013-December 2013) was conducted in Rural India. The surveys on Land and Livestock Holdings are conducted decennially from the 8th round of NSSO (1954-55) onwards. The first survey on land holdings was taken up as part of the World Agricultural Census initiated by the Food & Agricultural Organization (FAO) of the United Nations. The current survey on Land and Livestock Holdings is the seventh such survey.

The information collected in the Land and Livestock Holdings survey could be categorized into the three broad aspects of land ownership holdings, operational holdings and ownership of livestock.

Objective

  • To provide information on different aspects of land use and livestock holdings, and develop suitable indictors and critical inputs as may be useful for planning and policy formulation.

Sample Size

Visits 1 & 2: Each sample FSU (villages) was visited twice during this round. Since the workload of the first visit (i.e. visit1) was more, the first visit continued till the end of July 2013. Thus, period of the first visit was January – July 2013 (7 months) and that of the second visit (i.e. visit 2) was August – December 2013 (5 months).

The number of villages (FSU) surveyed was 4,529 and number of sampled households (SSU) surveyed were 35,604 in visit 1 and 35,337 in visit 2.

Important terms

House: Every structure, tent, shelter, etc. was a house irrespective of its use. It might be used for residential or non-residential purpose or both or even might be vacant.
Household: A group of persons normally living together and taking food from a common kitchen constituted a household.
Household size: The number of members of a household was its size.
Household classification: The household classification was based on the source of major income of the household
Homestead land (house-site): Homestead of a household was defined as the dwelling house of the household together with the courtyard, compound, garden, out-house, place of worship, family graveyard, guest house, shop, workshop and offices for running household enterprises, tanks, wells, latrines, drains and boundary walls annexed to the dwelling house. All land coming under homestead was defined as homestead land (house site).
Plot: A distinct patch of land demarcated generally by a strip of raised land, commonly known as ‘ails’ or ‘bunds’ was defined as a plot.
Ownership of land: A plot of land was considered owned by the household

  • 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 or assignment

Land possessed: Land possessed was given by land owned (including land under ‘owner like possession’) + land leased in – land leased out + land held by the household but neither owned nor leased in (e.g., encroached land).
Land irrigated: Irrigation was considered as a device of purposively providing land with water, other than rain water, by artificial means for crop production. Land irrigated was defined as the net irrigated area.
Lease of land: Land given to others on rent or free by owner of the land without surrendering the right of permanent heritable title.
Otherwise possessed land: All public/institutional land possessed by the household without title of ownership or occupancy right.
Jhum land and jhum cultivation: The preparation of jhum land was done by cutting and clearing of forest areas and burning of the dried biomass by setting fire. The jhum land was used for growing crops of agricultural importance such as upland rice, vegetables or fruits.
Cultivation: All activities relating to production of crops and related ancillary activities were considered as cultivation. Growing of trees, plants or crops as plantation or orchards (such as rubber, cashew, coconut, pepper, coffee, tea etc.) were not considered as cultivation activities for the purpose of this survey.
Livestock: Livestock were those animals which were used for food, fibre, labour, etc. Animals kept as pets, snakes, reptiles, frogs, fishes were excluded from the coverage of livestock.
Household Operational Holding: constitutes of all land that was used wholly or partly for agricultural production and was operated (directed/managed) by one household member alone or with assistance of others, without regard to title, size or location. The land might be operated by members belonging to a single household or by members belonging to more than one household operating jointly.

A household was found to grow vegetables in kitchen garden only, or flowers in the courtyard, it was considered to possess an operational holding. Likewise, a household engaged exclusively in livestock keeping or poultry raising or pisciculture was considered to operate a holding, even if no crop production was undertaken by it during the reference period.

A household carried out any agricultural production during the reference period, plots possessed by the household during the major part of the reference period and put to uses other than agricultural production, such as house-sites, paths, buildings, etc., were also included in the operated area of the household operational holding.

A household did not undertake any agricultural production on any part of the land possessed by it during the reference period, it was not considered to have any operational holding.
Individual and joint operational holding: If the household operational holding was managed by one or more members of a single household, it was taken as individual holding. It was treated as a joint operational holding only when it was managed by members of more than one household.

Category of land holding

Landless*: less than or equal to 0.002 hectares
Marginal: more than 0.002 but less than or equal 1.000 hectares
Small: more than 1.000 but less than or equal to 2.000 hectare
Semi-medium: more than 2.000 but less than or equal to 4.000 hectares
Medium: more than 4.000 but less than or equal to 10.000 hectares
Large: more than 10.000 hectares
* ‘less than or equal to 0.002 hectares’ as classified under ‘landless’ category, also includes plots where area is not reported.

Information in Land and Livestock Holding

The survey on Land and Livestock Holding contains information on

  • Particulars of land (owned, leased-out, leased-in and otherwise possessed) of the household
  • Location of land
  • Area
  • Duration of possession
  • Number of lessor/lessee households
  • Terms of lease
  • Land use during July 2012 to December 2012/January 2013 to June 2013/whole agricultural year (July 2012 to June 2013)
  • Whether irrigated
  • Sources of irrigation etc.

Information on number of livestock, poultry, duckery, etc., owned by the household as on the date of survey was also collected. Besides collection of information on land and livestock, information was collected on some household characteristics such as

  • Household classification
  • Social group
  • Religion
  • Whether the household operated any land on Jhum cultivation during last 365 days, etc.

Some information on demographic particulars from each of the household members was also collected such as

  • Sex
  • Age
  • General education level
  • Whether associated with the household operational holding etc.

STATA codes for extraction of data from .txt file

Before reading this section, you have to read “Ready reckoner NSSO Unit level Data Analysis”, “Importing text data into STATA using infix command”.

infix str round_centre_code 1-3 str FSU_No 4-8 str Round 9-10 str schedule_No 11-13 str samp 14-14 str sector 15-15 str state_region 16-17 str district 19-20 str stratum_No 21-22 str schedule_type 25-25 str sub_round 26-26 str sub_sample 27-27 str FOD_sub_region 28-31 str hamlet_subblock 32-32 str SSS 33-33 str HH_No 34-35 level 36-37 filler 38-42 HH_size 43-44 str NIC_08 45-49 str NCO_04 50-52 HH_type 53-53 religion 54-54 social_group 55-55 own_any_land 56-56 type_land 57-57 land_owned 58-65 land_leasedin 66-73 otherwise_possessed 74-81 land_leasedout 82-89 land_tot 90-97 Cultivated 98-105 Irrigated 106-113 spl_chr 114-115 blank 116-126 NSS 127-129 NSC 130-132 MLT 133-142 using R7001T1L02.TXT

infix code is used for importing .txt data into STATA. In the above code, with the help of data layout file as provided in supporting documents with the data; the name of variable, length of variable and type of variable is defined. For example, the first variable name is round_centre_code with length of 1-3 and type string as str was written before the name of variable, Similarly, there is one variable with name HH_type with length of variable is 53-53 and since the variable is integer type, it is not required to define the type of variable.

After the successful import of data, you can perform the various activities like calculation of Weights, creating primary key,merging of the data from one level to other levels, Estimation of the required parameters with the help of weights and perform various statistical analysis.

The extracted files of 70th round of Land and Livestock Holdings are given in below:

70th round data

The each .dta file contains the data in the following format:

70th round sample data