The migration rate within India between 2020 and 2021 was almost 29 percent. This means, between July 2020 and June 2021, about 26.5 percent of the population in the rural areas of the country were migrants, while this was about 35 percent for the population in urban areas. During the same time period, there was a much higher share of migrants among females than males in the country.

As of 2021, over 24 percent of migrants in rural India came from within the state and only 2 percent migrated from another state. Across India, 73 percent of locals lived in their usual place.

This dataset is about books. It has 10 rows and is filtered where the book subjects is Rural-urban migration-India. It features 9 columns including author, publication date, language, and book publisher.

The dataset contains survey data from a total of 226 low-income migrant workers (100 in Jalandhar and 126 in Guwahati) in India. It contains data on 60 variables, focussing on socio-economic background, migratory experience, ill-treatment and access to justice and access to basic services. Abstract of the study: Indian cities attract a considerable number of low-income migrants from marginal rural households experiencing difficult economic, political and social conditions at home who migrate in search of livelihoods and security. These migrants come from around the country as well as across the border from Nepal, Bangladesh and Myanmar to work in low-income manual occupations in a range of small-scale petty trade, service sector work, transport and construction work. Low-income migrants live and work in precarious conditions and are often denied basic amenities and fundamental rights. Poorly-paid intermittent and insecure jobs make them vulnerable to abuse, extortion or bribery. Many such migrants, both internal and international, lack documentation and proof of identity, whether for basic services such as health care and schooling or electoral voting. Their marginal position entails poorer access to health care provisions and other determinants of health than general (non-migrant) populations, thereby enhancing their vulnerability to ill-health, abuse and ill treatment whilst simultaneously compromising their ability to access protection, legal support or redress, and forms of accountability. Language, appearance and cultural differences exposes many low-income migrants from interior parts of the country or across the border to harassment and political exclusion. Moreover, despite their ubiquitous presence, their precarious livelihoods, informality and invisibility keep them unnoticed in urban planning, in the work of civil society organisations and in social science research. In this context, this collaborative project was designed to generate evidence to advance the rights and protection mechanisms that must be planned and provided for low-income urban migrants. We examined what India's urban transformation means for low-income migrants, their inclusion and social justice by exploring: 1. Low-income migrants' views on transformations in Indian cities, and the opportunities and challenges that confront them; 2. Low-income migrants perceptions of their entitlements, claim-making processes and attempts to protect their own health in a context of poor living and working conditions; 3. The prevalence of violence and extent of exclusion experienced by low-income migrants and how they protect themselves from various forms of violence; 4. The legal, developmental, humanitarian and human rights responses to low-income migrants in Indian cities. Fieldwork based in Guwahati (Assam) and Jalandhar (Punjab), two of India's fastest growing cities, aimed to enrich our understanding of access to health care, the social determinants of health, and experiences of violence, inclusion/exclusion and accessing justice, from the vantage point of diverse low-income migrant workers, from within India as well as cross-border. The project focussed on migrants' perceptions and lived experiences and will generate evidence to advance the rights and protection mechanisms that must be planned and provided for low-income urban migrants. Low-income migrants are mobile, dispersed and invisible, so they present methodological challenges, especially for creating a sampling frame or mapping in a particular locality. A distinctive strength of the project is its innovative methods for accessing these 'hard-to-reach' groups. The proposed research adopted a mixed methods approach. In order to unravel the nuances and complexities of low-income migrants' experiences and situate these within the broader processes of urban transformation in Jalandhar and Guwahati, we combined ethnographic fieldwork with in-depth interviews, a brief survey, and participatory methods such as photovoice.

Abstract

An all-India survey on the situation of employment and uemployment and migration particulars in India was carried out during NSS 64th round (July, 2007 to June, 2008). In this survey, a nation-wide enquiry was conducted in a moderately large sample of households to provide estimates on various characteristics pertaining to employment and unemployment and migration particulars in India and some characteristics associated with them at the national and state levels. Information on various facets of employment and unemployment and migration in India were collected through a schedule of enquiry (Schedule 10.2).

Geographic coverage

The survey covered the whole of the Indian Union except (i) Leh (Ladakh) and Kargil districts of Jammu & Kashmir (for central sample), (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

Analysis unit

Household

Universe

All households of the Indian Union except (i) Leh (Ladakh) and Kargil districts of Jammu & Kashmir (for central sample), (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified multi-stage design was adopted for the 64th round survey. The first stage units (FSU) were the 2001 census villages (Panchayat wards in case of Kerala) in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. However, for the newly declared towns and out growths (OGs) in Census 2001 for which UFS were not done, each individual town/ OG were considered as an FSU. The ultimate stage units (USU) were the households in both the sectors. In case of large FSUs, i.e. villages/ towns/ blocks requiring hamlet-group (hg)/ sub-block (sb) formation, one intermediate stage was the selection of two hgs/ sbs from each FSU. Details of the sample design and estimation procedure is given as a document in external resource .

Sampling deviation

There was no deviation from the original sample deviation.

Mode of data collection

Face-to-face [f2f]

Research instrument

Summary description of the schedule : The schedule 10 on employment-unemployment for NSS60th round consisted of 10 blocks as given below.

Block 0: Descriptive identification of sample household Block 1: Identification of sample household Block 2: Particulars of field operations Block 3 - Household Characteristics. Block 3.1 :particulars of out-migrants who migrated out any time in the past Block 4: demographic and usual activity particulars of household members Block 5: Time disposition of members during the week ended on ........... Block 6: Migration particulars of household members Block 7: Household consumer expenditure Block 8: Remarks by investigator Block 9: Comments by superintendent / senior superintendent Block 10: Comments by other supervisory officer(s)

Response rate

At the all-India level, 12,688 FSUs (7,984 villages and 4,704 urban blocks) was allocated for survey. Out of these 12,688 FSUs allotted for survey, 12,589 FSUs could be surveyed – 7,921 in rural and 4,668 in urban. A sample of 10 households was planned for survey from each selected village and urban block.The survey covered a sample of 1,25,578 households (79,091 in rural areas and 46,487 in urban areas) and a sample of 5,72,254 persons (3,74,294 in rural areas and 1,97,960 in urban areas).

Abstract

The national sample survey (NSS), set-up by the government of India in 1950 to collect socio-economic data employing scientific sampling methods, completed its forty-ninth round as a six months survey during the period January to June,1993. Housing condition of the people is one of the very important indicators of the socio-economic development of the country. Statistical data on housing condition in qualitative and quantitative terms are needed periodically for an assessment of housing stock and formulation of housing policies and programmes. NSS 49th round was devoted mainly to the survey on housing condition and migration with special emphasis on slum dwellers. An integrated schedule was designed for collecting data on 'housing condition' as well as ' migration '. Also,households living in the slums were adequately represented in the sample of households where the integrated schedule was canvassed.The present study was different from the earlier study in the sense that the coverage in the present round was much wider. Detailed information on migration have been made with a view to throw data on different facets of migration. For this reason we find separate migration data for males & females, migrant households, return migrants, the structure of the residence of the migrants' households before & after migration, status of the migrants before and after migration and other details on migration. It is to be noted that comprehensive data on out-migrants & return-migrants were collected for the first time in the 49th round.

Geographic coverage

The survey covered the whole of Indian union excepting ( i) Ladakh and kargil districts of Jammu & kashmir ( ii ) 768 interior villages of Nagaland ( out of a total of 1119 villages ) located beyond 5 kms. of a bus route and ( iii ) 172 villages in Andaman & Nicobar islands ( out of a total of 520 villages ) which are inaccessible throughout the year.

Analysis unit

• Households
• Individuals

Universe

The survey used the interview method of data collection from a sample of randomly selected households and members of the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

A two-stage stratified design was adopted for the 49th round survey. The first-stage units(fsu) were census villages in the rural sector and U.F.S. (Urban Frame Survey) blocks in the urban sector (However, for some of the newly declared towns of 1991 census for which UFS frames were not available, census EBs were first-stage units). The second-stage units were households in both the sectors. In the central sample altogether 5072 sample villages and 2928 urban sample blocks at all-India level were selected. Sixteen households were selected per sample village/block in each of which the schedule of enquiry was canvassed. The number of sample households actually surveyed for the enquiry was 119403.

Sample frame for fsus : Mostly the 1981 census lists of villages constituted the sampling frame for rural sector. For Nagaland, the villages located within 5 kms. of a bus route constituted the sampling frame. For Andaman and Nicobar Islands, the list of accessible villages was used as the sampling frame. For the Urban sector, the lists of NSS Urban Frame Survey (UFS) blocks have been considered as the sampling frame in most cases. However, 1991 house listing EBs (Enumeration blocks) were considered as the sampling frame for some of the new towns of 1991 census, for which UFS frames were not available.

Stratification for rural sector : States have been divided into NSS regions by grouping contiguous districts similar in respect of population density and crop pattern. In Gujarat, however, some districts have been split for the purpose of region formation, considering the location of dry areas and distribution of tribal population in the state. In the rural sector, each district with 1981 / 1991 census rural population less than, 1.8 million/2 million formed a separate stratum. Districts with larger population were divided into two or more strata, by grouping contiguous tehsils.

Stratification for urban sector : In the urban sector, strata were formed, within the NSS region, according to census population size classes of towns. Each city with population 10 lakhs or more formed a separate stratum. Further, within each region, the different towns were grouped to form three different strata on the basis of their respective census population as follows : all towns with population less than 50,000 as stratum 1, those with population 50,000 to 1,99,999 as stratum-2 and those with population 2,00,000 to 9,99,999 as stratum-3.

Sample size for fsu's : The central sample comprised of 5072 villages and 2928 blocks. Selection of first stage units : The sample villages have been selected with probability proportional to population with replacement and the sample blocks by simple random sampling without replacement. Selection was done in both the sectors in the form of two independent sub-samples.

Sampling deviation

There was no deviation from the original sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire consisted of 13 blocks as given below : Block - 0 : Descriptive Identification of Sample Household Block - 1 : Identification of Sample Household Block - 2 : Particulars of Field Operations Block - 3 : Household Characteristics Block - 4 : Demographic and Migration Particulars of Members of Household Block - 5 : Building and Environment Particulars Block - 6 : Particulars of the Dwelling Block - 7 : Particulars of Living Facilities Block - 8 : Particulars of Building Construction for Residential Purpose Block - 9 : Particulars of Dwelling/Land Owned Elsewhere Block - 10 : Use of Public Distribution System(PDS) Block - 11 : Some General Particulars of Slum Dwellers Block - 12 : Remarks by Investigator Block - 13 : Comments by Supervisory Officer(s)

Despite rapid urbanization across the global south, identity politics within rural-urban migrant communities remains understudied. Past scholarship is divided over whether village-based ethnic divisions will erode or deepen within diverse poor migrant populations. I assess these divergent predictions through ethnography and survey experiments (N=4218) among unique samples of poor migrants in India. Contra conventional expectations, I find intra-class ethnic divisions are neither uniformly transcended nor entrenched across key arenas of migrant life. Instead, I observe variation consistent with situational theories predicting ethnic divisions will be muted only in contexts triggering a common identity among migrants. I pinpoint urban employers and politicians as these triggers. Poor migrants ignore ethnic divisions when facing these elites, who perceive and treat them in class terms. However, migrants remain divided in direct interactions with each other. These bifurcated findings imply poor migrants may be available for both class-based and ethnic mobilization in the city.

In 2023, approximately a third of the total population in India lived in cities. The trend shows an increase of urbanization by more than 4 percent in the last decade, meaning people have moved away from rural areas to find work and make a living in the cities. Leaving the fieldOver the last decade, urbanization in India has increased by almost 4 percent, as more and more people leave the agricultural sector to find work in services. Agriculture plays a significant role in the Indian economy and it employs almost half of India’s workforce today, however, its contribution to India’s GDP has been decreasing while the services sector gained in importance. No rural exodus in sightWhile urbanization is increasing as more jobs in telecommunications and IT are created and the private sector gains in importance, India is not facing a shortage of agricultural workers or a mass exodus to the cities yet. India is a very densely populated country with vast areas of arable land – over 155 million hectares of land was cultivated land in India as of 2015, for example, and textiles, especially cotton, are still one of the major exports. So while a shift of the workforce focus is obviously taking place, India is not struggling to fulfill trade demands yet.

Characteristics of sample households in rural India for the study (unweighted), NSSO 64th round (2007–2008) (in %).

Odds ratios and associated significance levels from the binary logistic regression models assessing the association between explanatory variables and temporary migration across several economic groups in rural India, NSSO 64th round (2007–2008).

Urbanization in the global South is intricately linked with the internal mobility of people and the impacts of climate change. In India, changing precipitation patterns pose pressure on rural livelihoods through the increasing frequency and severity of droughts, contributing to rural-to-urban mobility. At destination, however, insufficient information is available on the complex mobility backgrounds of the new arrivals. We employ a mixed methods approach to investigate mobility patterns to Pune, India, with a special focus on the role of droughts. Combining a household survey with in-depth interviews and monthly precipitation data on district level, we use descriptive statistics and qualitative content analysis to show a significant relationship between drought at origin and mobility to Pune. Particularly affected are recent arrivals, migrants of rural origin and from other states, and those currently living in informal areas. The link between droughts and mobility decisions is usually indirect, hidden behind economic conditions such as the loss of agricultural jobs. Paradoxically, migrants affected by droughts at origin face increased flood risk at destination. This risk, however, is often consciously taken in favor of better livelihood opportunities in the city. With climate scenarios projecting increasingly variable precipitation patterns, understanding the climate-mobility-urbanization nexus gains importance, especially for destination hotspots like the city of Pune.

We provide an explanation for the large spatial wage disparities and low male migration in India based on the trade-off between consumption smoothing, provided by caste-based rural insurance networks, and the income gains from migration. Our theory generates two key empirically verified predictions: (i) males in relatively wealthy households within a caste who benefit less from the redistributive (surplus-maximizing) network will be more likely to migrate, and (ii) males in households facing greater rural income risk (who benefit more from the insurance network) migrate less. Structural estimates show that small improvements in formal insurance decrease the spatial misallocation of labor by substantially increasing migration. (JEL G22, J31, J61, O15, O18, R23, Z13)

Abstract

In pursuance of the recommendations made by the Governing Council (G.C.) of the National Sample Survey Organization (NSSO) in its 44th meeting held on 16 January 1987 to undertake a comprehensive survey on the socio-economic conditions of the tribal people in the 44th round (July 1988 - June 1989) of NSS, various schedules of enquiries on the subject were drawn up and tested in the field through a try-out survey. The schedules were discussed in details in the meetings of the Working Groups (W.G) set up by the G.C., NSSO for the NSS 44th round. In the light of the experiences gained through the try-out survey, the schedules of enquiry were finalized by the W.G. and subsequently approved by the G.C. of the NSSO in its 45th meeting held on 29 December 1987.

With a view to studying the problems of land alienation faced by the tribal population due to in-migration of non-tribals in the tribal areas and also to assess the differences in the socio-economic standard of living between the tribals and the non-tribals, a schedule of enquiry (schedule type 29.3) was designed and collected information from the non-tribal households residing in the tribal areas.

The Survey measures the disparity between the tribal and non-tribal households in respect of certain key characteristics and also the extent of displacement of the tribal population from the tribal belts due in-migration of non-tribals. This schedule relate to in-migration, economic activity, assets and liabilities along with the details about the extent and manner of acquisition and disposal of land by the non-tribals.

Geographic coverage

National, State, Urban, Rural

Analysis unit

Households

Universe

All tribbles households within country

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design is, as usual, stratified two-stage with the census village as the first stage unit in the rural sector and UFS block as the first stage unit in the urban sector. The second stage units were households for all schedules.The sample design in the rural sector was decided with a view to providing good estimates for the tribal enquiry. Except in the north-eastern region, the tribal population was concentrated in some districts within the states having considerable tribal population and even in those districts they were found to be unevenly distributed geographically. Therefore special stratification and selection procedures were adopted not only to net sufficient number of tribal households in the sample but also to improve the design in general for the tribal enquiry.

Sampling frame of villages: The list of 1981 census villages constitute the sampling frame for selection of villages in most districts. However in Assam (where '81 census was not done) and a few districts of some other states (where the available lists of villages were not satisfactory), 1971 census village lists were used as frame.

Stratification : In Haryana, Jammu & Kashmir, Punjab, Chandigarh, Delhi, Goa, Daman & Diu and Pondicherry where there were practically no tribal population, the strata used in NSS 43rd round were retained. In Meghalaya, Mizoram, Nagaland, Arunachal Pradesh, Sikkim, Dadra and Nagar Haveli and Lakshadweep also the strata of 43rd round were retained because of the high percentage of ST. population in these States/U.T.'s. (The strata of 43rd round have been retained in the case of Sikkim as the distribution of tribal population is more or less uniform over all the districts).In the remaining states fresh stratification was carried out as described below.

In these states all districts accounting for the bulk of the states's tribal population were selected for formation of strata with concentration of tribal population. Besides these districts, tribal concentration strata were demarcated also in some other districts with relatively small tribal population in order to ensure coverage of as many different ethnic groups as possible.

Within each district so identified for formation of tribal concentration strata, , the tehsils with relatively high concentration of tribal population, together constituted one stratum. These tehsils were selectd in such a way that together they accounted for the bulk (70% or more) of the district tribal population and the proportion of tribal to total population and the proportion of tribal to total population in this stratum was significantly greater than that of the district as a whole. The strata so formed were not always geographically contiguous. These tribal concentration strata are called STRATUM TYPE -1. Further, all the strata of Meghalaya, Mizoram, Nagaland, Arunachal Pradesh, Dadra & Nagar Haveli, Lakshdweep and Sikkim are also considered as stratum type-1. All the remaining strata in the rural sector (in any State/U.T.) were called stratum type -2.

General and special sample villages : There were two types of sample villages in this round. The first type was the general sample in which all enquiries were carried out. The second type was designated as "special sample villages" in which only schedules 3.1, 29.1, 29.2 and 29.3 were canvassed. The special sampleswere intended for augmenting the general sample for the tribal enquiry. These special sample villages were selected only from the tribal concentration strata (stratum type 1 ) of the 16 States and the U.T. OF Andaman & Nicobar Islands 1) of 16 States and the U.T. of Andaman & Nicobar Islands. There were no special sample villages in the remaining States/U.T.'s. The special samples were called sample type-1 and the general samples, sample type-2.

Schedule type 29.3 was canvassed in the general and special sample villages to tribal strata only. Four households were selected from the frame of non-scheduled tribe households in each of the villages of stratum type 1. In large special sample villages, the distribution of sample households was 2 each from area type 1 and area type 2, Schedule 29.3 was not be canvassed in the urban sector.

Detailed procedures of samp[ling may be seen in INSTRUCTIONS TO FIELD STAFF : VOLUME I attached as external resource.

Sampling deviation

There was no deviation from the original sample deviation.

Mode of data collection

Face-to-face [f2f]

Research instrument

Schedule 29.3 consisted of the following blocks :

Block 1 : identification of sample household Block 2 : particulars of field operations Block 3 : remarks by investigator Block 4 : remarks by supervisory officer (s) Block 5 : household characteristics Block 6 : demographic and migration particulars of household members Block 7 : usual and current week activity particulars Block 8 : particulars of land owned and possessed activity on the date of survey Block 9 : particulars of disposal of land during last 5 years Block 10 : inventory of assets owned on the date of survey. Block 11 : particulars of cash dues and grain & other commodity dues payable by the household on the date of survey and transaction of loans during last 365 days.

Questionaire is published in English language.

In 2023, approximately ** percent of the population in Papua New Guinea were living in rural areas. In comparison, approximately ***** percent of the population in Japan were living in rural areas that year. Urbanization and development Despite the desirable outcomes that urbanization entails, these rapid demographic shifts have also brought about unintended changes. For instance, in countries like India, rapid urbanization has led to unsustainable and crowded cities, with **** of the urban population in India estimated to live in slums. In China, population shifts from rural to urban areas have aggravated regional economic disparities. For example, the migration of workers into coastal cities has made possible the creation of urban clusters of immense economic magnitude, with the Yangtze River Delta city cluster accounting for about a ******of the country’s gross domestic product. Megacities and their future Home to roughly 60 percent of the world’s population, the Asia-Pacific region also shelters most of the globe’s largest urban agglomerations. Megacities, a term used for cities or urban areas with a population of over ten million people, are characterized by high cultural diversity and advanced infrastructure. As a result, they create better economic opportunities, and they are often hubs of innovation. For instance, many megacities in the Asia-Pacific region offer high local purchasing power to their residents. Despite challenges like pollution, income inequality, or the rising cost of living, megacities in the Asia-Pacific region have relatively high population growth rates and are expected to expand.

Geographic coverage

The survey covered the whole of the Indian Union except (i) Leh (Ladakh) and Kargil districts of Jammu & Kashmir (for central sample), (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

Analysis unit

Household, Individual

Universe

The following rules regarding the population to be covered were applied in listing of households and persons:

1. Under-trial prisoners in jails and indoor patients of hospitals, nursing homes etc., are to be excluded, but residential staff therein will be listed while listing is done in such institutions. The persons of the first category will be considered as normal members of their parent households and will be counted there. Convicted prisoners undergoing sentence will be outside the coverage of the survey.

2. Floating population, i.e., persons without any normal residence will not be listed. But households residing in open space, roadside shelter, under a bridge, etc., more or less regularly in the same place, will be listed.

3. Foreign nationals will not be listed, nor their domestic servants, if by definition the latter belong to the foreign national's household. If, however, a foreign national becomes an Indian citizen for all practical purposes, he or she will be covered.

4. Persons residing in barracks of military and paramilitary forces (like police, BSF, etc.) will be kept outside the survey coverage due to difficulty in conduct of survey therein. However, civilian population residing in their neighbourhood, including the family quarters of service personnel, are to be covered. Permission for this may have to be obtained from appropriate authorities.

5. Orphanages, rescue homes, ashrams and vagrant houses are outside the survey coverage. However, persons staying in old age homes, students staying in ashrams/ hostels and the residential staff (other than monks/ nuns) of these ashrams may be listed. For orphanages, although orphans are not to be listed, the persons looking after them and staying there may be considered for listing.

DEFINITION OF A HOUSEHOLD:

A group of persons normally living together and taking food from a common kitchen will constitute a household. It will include temporary stay-aways (those whose total period of absence from the household is expected to be less than 6 months) but exclude temporary visitors and guests (expected total period of stay less than 6 months). Even though the determination of the actual composition of a household will be left to the judgment of the head of the household, the following procedures will be adopted as guidelines.

(i) Each inmate (including residential staff) of a hostel, mess, hotel, boarding and lodging house, etc., will constitute a single-member household. If, however, a group of persons among them normally pool their income for spending, they will together be treated as forming a single household. For example, a family living in a hotel will be treated as a single household.

(ii) 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 will be treated as a member of the household with whom he or she resides.

(iii) A resident employee, or domestic servant, or a paying guest (but not just a tenant in the household) will be 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.

(iv) 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.

(v) If a member of a family (say, a son or a daughter of the head of the family) stays elsewhere (say, in hostel for studies or for any other reason), he/ she will not be considered as a member of his/ her parent's household. However, he/ she will be listed as a single member household if the hostel is listed.

Kind of data

Sample survey data [ssd]

Sampling procedure

Outline of sample design: A stratified multi-stage design has been adopted for the 64th round survey. The first stage units (FSU) was the 2001 census villages (Panchayat wards in case of Kerala) in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. However, for the newly declared towns and out growths (OGs) in census 2001 for which UFS had not yet been done, each individual town/ OG was considered as an FSU. The ultimate stage units (USU) was be households in both the sectors. In case of large FSUs i.e. villages/ towns/ blocks requiring hamlet-group (hg)/ sub-block (sb) formation, one intermediate stage was the selection of two hgs/ sbs from each FSU.

Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages (Panchayat wards for Kerala) constitute the sampling frame. For the urban sector, the list of latest available Urban Frame Survey (UFS) blocks and for non-UFS towns list of such towns/ OGs was considered as the sampling frame.

Stratification: Within each district of a State/ UT, generally speaking, two basic strata were formed: i) rural stratum comprising of all rural areas of the district and (ii) urban stratum comprising of all the urban areas of the district. However, within the urban areas of a district, if there were one or more towns with population 10 lakhs or more as per population census 2001 in a district, each of them formed a separate basic stratum and the remaining urban areas of the district was considered as another basic stratum. For a few districts, particularly in case of Tamil Nadu, if total number of towns in the district for which UFS was not yet done exceeds certain number, all such towns taken together formed another basic stratum. Otherwise, they were merged with the UFS towns for stratification.

Sub-stratification in the Rural sector: If "r" be the sample size allocated for a rural stratum, the number of sub-strata formed is "r/4?. The villages within a district as per frame were first arranged in ascending order of population. Then sub-strata 1 to "r/4" were demarcated in such a way that each sub-stratum comprised a group of villages of the arranged frame and have more or less equal population.

Sub-stratification in the Urban sector: If "u" be the sample size for a urban stratum, "u/4" number of sub-strata were formed. The towns within a district, except those with population 10 lakhs or more and also the non-UFS towns, were first arranged in ascending order of population. Next, UFS blocks of each town were arranged by IV unit no. × block no. in ascending order. From this arranged frame of UFS blocks of all the towns, "u/4? number of sub-strata were formed in such a way that each sub-stratum had more or less equal number of FSUs. For towns with population 10 lakhs or more, the urban blocks were first arranged by IV unit no. × block no. in ascending order. Then "u/4? number of sub-strata were formed in such a way that each sub-stratum had more or less equal number of blocks. All non-UFS towns taken together within the district formed one sub-stratum.

Total sample size (FSUs): 12688 FSUs for central sample and 13624 FSUs for state sample have been allocated at all-India level.

Allocation of total sample to States and UTs: The total number of sample FSUs is allocated to the States and UTs in proportion to population as per census 2001 subject to a minimum sample allocation to each State/ UT. While doing so, the resource availability in terms of number of field investigators had been kept in view.

Allocation of State/ UT level sample to rural and urban sectors: State/ UT level sample was allocated between two sectors in proportion to population as per census 2001 with 1.5 weightage to urban sector subject to the restriction that urban sample size for bigger states like Maharashtra, Tamil Nadu etc. should not exceed the rural sample size. A minimum of 8 FSUs was allocated to each state/ UT separately for rural and urban areas. Further the State level allocation for both rural and urban have been adjusted marginally in a few cases to ensure that each stratum gets a minimum allocation of 4 FSUs.

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More information on the sampling methodology is available in the document " Instructions to Field Staff - Volume-I"

Mode of data collection

Face-to-face [f2f]

Research instrument

In the 64th round survey, a separate schedule on employment and unemployment (Schedule 10.2), with provision for collecting information on migration particulars, will be canvassed.

The broad structure of the employment and unemployment part of Schedule 10.2 will be the same as that of the schedule canvassed during the NSS 60th round with the following modifications: a) Information on vocational training will not be collected. b) Particulars of persons unemployed on all the 7 days will not be collected in the present round.

The scope for collecting information on migration particulars has been enlarged with the provision for collecting information on: a) Migration particulars of the households which migrated to the place of enumeration during the last 365 days, such as location of last usual residence, pattern of migration and reason for migration. b) Particulars of out-migrants who migrated out to other village/ town, from the household, any time in the past, such as present place of residence, reason for migration, period

Abstract

The Employment and Unemployment surveys of National sample Survey (NSS) are primary sources of data on various indicators of labour force at National and State levels. These are used for planning, policy formulation, decision support and as input for further statistical exercises by various Government organizations, academicians, researchers and scholars. NSS surveys on employment and un-employment with large sample size of households have been conducted quinquennially from 27th. round(October'1972 - September'1973) onwards. Cotinuing in this series the fifth such all-india survey on the situation of employment and unemployment in India was carried out during the period july 1993 - june 1994 . In this survey, a nation-wide enquiry was conducted to provide estimates on various characteristics pertaining to employment and unemployment in India and some characteristics associated with them at the national and state levels. Information on various facets of employment and unemployment in India was collected through a schedule of enquiry (schedule 10). Apart from the information usually collected in the quinquennial rounds, information on some new items were also collected.

With the experience gained from the past four quinquennial surveys behind, keeping in view the need for further refinements in the concepts and procedures and wider coverage in the light of international practices, certain modifications/ changes were made in this survey the 50th round, without affecting its comparability with the past surveys. These are briefly cited below:

(i) In the past surveys, the current weekly status (CWS) of a person was first assigned on the basis of the response to the questions relating to his participation in gainful activities (non-gainful activities) and thereafter the daily time disposition data was collected only for those in the labour force as per the CWS. In this round,the daily time disposition for all the persons surveyed were collected and the CWS was determined based on the time disposition data so collected, without probing any further on this point.

(ii) Certain probing questions were introduced to all persons who were unemployed on all the days of the days of the reference week. These include educational background of unemployed, spell of unemployment, industry-occupation of the last employment, reason for leaving the employment, etc.

(iii) A set of probing questions were framed to get the profile of the children (5-14 years) particularly their economic activities.

(iv) As information on migration were collected extensively in the 49th round, items relating to migration were not collected in this 50th round.

(v) The probing questions meant for the employed persons according to usual status were modified to obtain a better view of the underemployment situation.

(vi) Hitherto, in NSS, work was identified with the performing of 'gainful activity'. As the international standards use the term 'economic activity' rather than 'gainful activity', the concept of economic activity was introduced in the fiftieth round. However, the coverage of activities under the new term was kept the same as in the earlier surveys, except, for the inclusion of 'own account production of fixed assets' as a work related activity.

(vii) In the NSS quinquennial surveys the identification of usual status involved a trichotomous classification of persons into 'employed', 'unemployed' and 'out of labour force' based on the major time criterion. In this round, the procedure prescribed was a two stage dichotomous procedure which involves a classification into 'labour force' and 'out of labour force' in the first stage and the labour force into 'employed' and 'unemployed' in the second stage.

Work Programme: The survey period of one year was divided into four sub-rounds of three months duration each as below.

sub-round period of survey

1 July-September, 1993 2 October- December, 1993 3 January-March, 1994 4 April-June, 1994

Period of Survey for the Four Sub-Rounds Equal number of sample villages and blocks was allotted for survey in each of these sub--rounds. However in Andaman and Nicobar Islands , Lakshadweep, and rural areas of Arunachal Pradesh and Nagaland, the re-striction of surveying the allotted households during the sub-round period was not strictly enforced.The survey used the interview method of data collection from a sample of randomly selected households.

Geographic coverage

The fifth quinquennial survey was conducted during the 50th round survey operations from July 1993 to June, 1994. Generally the NSSO surveys cover the entire country with the exception of certain interior areas of Nagala nd and the Andaman & Nicobar Islands. However in this round besides the above, in the state of Jammu & Kashmir out of the 12 Districts, only three Districts could be surveyed. These Districts viz. Jammu, Kathua and Udhampur are however included in the all India estimates..

Analysis unit

Randomly selected households based on sampling procedure and members of the household

Universe

The survey used the interview method of data collection from a sample of randomly selected households and members of the household

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design adopted for this round of survey was similar to that followed in the past surveys in its general aspects. The ge neral scheme was a two stage stratified design with the first stage units being villages in the rural areas and urban frame survey blocks(UFS) in the urban areas. The second stage units were the households.

Sampling frame for first stage units:

The frame used for selection of first stage units in the rural sector was the 1991 census list of villages for all the four sub-rounds for 8 states/u.t.s viz. Andhra Pradesh, Assam, Kerala, Madhya Pradesh, Orissa, Uttar Pradesh, West Bengal and Chandigarh. However for Agra district of U.P. and the three districts, viz.Durg, Sagar, and Morena of M.P., samples were drawn using 1981 census list of villages. For Jammu & Kashmir samples for all the 4 sub-rounds were drawn using the 1981 census list as the 1991 census was not conducted in the st ate. For the remaining 23 states/u.t.s, the frame was 1991 census list for sub-rounds 2 to 4 and 1981 census list for sub-round 1 as the 1991 census list was not available for use at the time of drawing the samples. As usual, for Nagaland the list of villages within 5 kms. of the bus route and for Andaman and Nicobar Islands the list of accessible villages constituted the frame. In the case of urban sector the frame consisted of the UFS blocks and, for some newly declared towns where these were not available, the 1991 census enumeration blocks were used.

Region formation and stratification: States were divided into regions by grouping contiguous districts similar in respect of population density and cropping pattern. In rural sector each district was treated a separate stratum if the population was below 2 million and where it exceeded 2 million, it was split into two or more strata. This cut off point of population was taken as 1.8 million ( in place of 2 million ) for the purpose of stratification for districts for which the 1981 census frame wa s used. In the urban sector, strata were formed, within each NSS region on the basis of population size class of towns. However for towns with population of 4 lakhs or more the urban blocks were divided into two classes viz. one consisting of blocks inhabited by affluent section of the population and the other consisting of the remaining blocks.

Selection of first stage units :

Selection of sample villages was done circular systematically with probability proportional to population and sample blocks circular system-atically with equal probability. Both the sample villages and the sample blocks were selected in the form of two or more independent sub-samples. In Arunachal Pradesh the procedure of cluster sampling has been followed. Further large villages/blocks having present population of 1200 or more were divided into a suitable number of hamlet- groups/ sub-blocks having equal population content. Two hamlet- groups were selected from the larger villages while one sub-block was selected in urban sector for larger blocks.

Selection of households :

While listing the households in the selected villages, certain relatively affluent households were identified and considered as second stage stratum 1 and the rest as second stage stratum 2. A total of 10 households were surveyed from the selected village/hamlet-groups, 2 from the fi rst category and remaining from the second. Further in the second stage stratum-2, the households were arranged according to the means of livelihood. The means of livelihood were identified on the basis of the major source of income as i) self-employed in non-agricultu re, ii) rural labour and iii) others. The land possessed by the households was also ascertained and the frame for selection was arranged on the basis of this information. The households were selected circular systematically from both the second stage strata.

In the urban blocks a different method was used for arranging the households for selection. This involved the identification means of livelihood of households as any one of a) self-employed, b)regular salaried/wage earnings, c) casual labour, d) others. Further the average household monthly per capita consumer expenditure (mpce) was also ascertained. All households with MPCE of (i) Rs. 1200/- or more (in towns with population less than 10 lakhs or (ii) Rs. 1500/- or more (in towns with population 10 lakh or more)

In 2025, the degree of urbanization worldwide was at 58 percent. North America, Latin America, and the Caribbean were the regions with the highest level of urbanization, with over four-fifths of the population residing in urban areas. The degree of urbanization defines the share of the population living in areas defined as "cities". On the other hand, less than half of Africa's population lives in urban settlements. Globally, China accounts for over one-quarter of the built-up areas of more than 500,000 inhabitants. The definition of a city differs across various world regions - some countries count settlements with 100 houses or more as urban, while others only include the capital of a country or provincial capitals in their count. Largest agglomerations worldwideThough North America is the most urbanized continent, no U.S. city was among the top ten urban agglomerations worldwide in 2023. Tokyo-Yokohama in Japan was the largest urban area in the world that year, with 37.7 million inhabitants. New York ranked 13th, with 21.4 million inhabitants. Eight of the 10 most populous cities are located in Asia. ConnectivityIt may be hard to imagine how the reality will look in 2050, with 70 percent of the global population living in cities, but some statistics illustrate the ways urban living differs from suburban and rural living. American urbanites may lead more “connected” (i.e., internet-connected) lives than their rural and/or suburban counterparts. As of 2021, around 89 percent of people living in urban areas owned a smartphone. Internet usage was also higher in cities than in rural areas. On the other hand, rural areas always have, and always will, attract those who want to escape the rush of the city.

In 2024, approximately 67 percent of the total population in China lived in cities. The urbanization rate has increased steadily in China over the last decades. Degree of urbanization in China Urbanization is generally defined as a process of people migrating from rural to urban areas, during which towns and cities are formed and increase in size. Even though urbanization is not exclusively a modern phenomenon, industrialization and modernization did accelerate its progress. As shown in the statistic at hand, the degree of urbanization of China, the world's second-largest economy, rose from 36 percent in 2000 to around 51 percent in 2011. That year, the urban population surpassed the number of rural residents for the first time in the country's history.The urbanization rate varies greatly in different parts of China. While urbanization is lesser advanced in western or central China, in most coastal regions in eastern China more than two-thirds of the population lives already in cities. Among the ten largest Chinese cities in 2021, six were located in coastal regions in East and South China. Urbanization in international comparison Brazil and Russia, two other BRIC countries, display a much higher degree of urbanization than China. On the other hand, in India, the country with the worlds’ largest population, a mere 36.3 percent of the population lived in urban regions as of 2023. Similar to other parts of the world, the progress of urbanization in China is closely linked to modernization. From 2000 to 2024, the contribution of agriculture to the gross domestic product in China shrank from 14.7 percent to 6.8 percent. Even more evident was the decrease of workforce in agriculture.

Abstract

The National Sample Surveys (NSS) are being conducted by the Government of India since 1950 to collect socio-economic data employing scientific sampling methods. Seventyeighth rounds of NSS will commence from 1st January 2020. NSS 78th round is earmarked for collection of data on ‘Domestic Tourism Expenditure and ‘Multiple Indicators’. Survey on Multiple Indicators is being conducted for the first time in NSS during this round.

The objective of Multiple Indicator Survey (MIS) is to collect information for developing some important indicators of Sustainable Development Goals 2030. In formation on (i) Migration and (ii)Construction of houses since 2014-15 will also be collected through MIS as per the request of M/o HUA. In addition to these, information on access to mass media, availability of birth registration certificate will be collected in MIS.

Geographic coverage

The survey will cover the whole of the Indian Union except the villages in Andaman and Nicobar Islands which are difficult to access.

Analysis unit

Randomly selected households based on sampling procedure and members of the household.

Universe

The survey used the interview method of data collection from a sample of randomly selected households and members of the household.

Sampling procedure

Sample Design

Formation of sub-units (SUs): Rural areas: A rural village will be notionally divided into a number of sub-units (SU) of more or less equal population during the preparation of frame. Census 2011 population of villages will be projected by applying suitable growth rates and the number of SUs to be formed in a village will be determined apriori.

The above procedure of SU formation will be implemented in the villages with population more than or equal to 1000 as per Census 2011. In the remaining villages, no SU will be formed.

The number of SUs to be formed in the villages (with Census 2011 population 1000 or more) of the frame will be decided before selection of the samples following the criteria given below: projected population of the village no. of SUs to be formed less than 1200 1 1200 to 2399 2 2400 to 3599 3 3600 to 4799 4 4800 to 5999 5 .......and so on ....

Special case: For rural areas of (i) Himachal Pradesh, (ii) Sikkim, (iii) Andaman & Nicobar Islands, (iv) Uttarakhand (except four districts Dehradun, Nainital, Hardwar and Udham Singh Nagar), (v) Punch, Rajouri, Udhampur, Reasi, Doda, Kishtwar, Ramban of Jammu and Kashmir (vi) Leh and Kargil districts of Ladakh region and (vii) Idukki district of Kerala, numbers of SUs to be formed in a village will be determined in such a way that each SU contains 600 or less projected population. Further, SUs will not be formed in the villages in the above mentioned districts/States with population less than 500 as per Census 2011. In the remaining villages the number of SUs to be formed for these States/districts will be as follows: projected population of the village no. of SUs to be formed less than 600 1 600 to 1199 2 1200 to 1799 3 1800 to 2399 4 2400 to 2999 5 .......and so on ....

Urban areas: SUs will be formed in urban sector also. The procedure will be similar to that adopted in rural areas except that SUs will be formed on the basis of households in the UFS frame instead of population, since UFS frame does not have population. Each UFS block with number of households more than or equal to 250 will be divided into a number of SUs. In the remaining UFS blocks, no SU will be formed.

The number of SUs to be formed in the UFS blocks of the frame will be decided before selection of the samples following the criteria given below: number of households of the UFS block no. of SUs to be formed less than 250 1 250 to 499 2 500 to 749 3 750 to 999 4 1000 to 1249 5 .......and so on ....

Stratification of FSUs: (a) Each district will be a stratum. Within each district of a State/UT, generally speaking, two basic strata will be formed: (i) rural stratum comprising of all rural areas of the district and (ii) urban stratum comprising of all the urban areas of the district. However, within the urban areas of a district, if there are one or more towns with population one million or more as per Census 2011, each of them will form a separate basic stratum and the remaining urban areas of the district will be considered as another basic stratum. (b) A special stratum, in the rural areas only, will be formed at all-India level before district level strata are formed in each State/UT. This stratum will comprise all the uninhabited villages as per Census 2011 belonging to all States/UTs.

Mode of data collection

Face-to-face

According to a survey conducted in 2015 across India, over ** percent of the surveyed households had an average monthly income up to 10,000 Indian rupees. This percentage varied among the rural and urban areas, where over ** percent of the rural households and ** percent of the urban households earned up to 10,000 Indian rupees monthly. India had a high rate of rural to urban migration, as Indian cities provided better standards of living and employment opportunities.

Multiple income generators

For most of the population, income is earned in form of wages or salary, rent from residential or commercial property, interest from financial investments, and profits from family businesses. Most Indian households have multiple earning members to support consumption expenses on a day to day basis. During the surveyed year, around ** percent of the households had a single earner, mostly the head of the family, followed by about ** percent of households with two earning members.

Employment scenario

There are a lot of uncertainties in the job market in India. Non-availability of jobs matching education and skills was one of the main reasons for unemployment among Indian graduates. Underemployment was also a problem, and it was higher in urban areas than rural ones. Even though a majority of the population was self-employed, most jobs taken by workers had no written job contracts in both the salaried and casual employment sectors.