Since the beginning of the 21st century, the BRICS countries have been considered the five foremost developing economies in the world. Originally, the term BRIC was used by economists when talking about the emerging economies of Brazil, Russia, India, and China, however these countries have held annual summits since 2009, and the group has expanded to include South Africa since 2010. China has the largest GDP of the BRICS country, at 16.86 trillion U.S. dollars in 2021, while the others are all below three trillion. Combined, the BRICS bloc has a GDP over 25.85 trillion U.S. dollars in 2022, which is slightly more than the United States. BRICS economic development China has consistently been the largest economy of this bloc, and its rapid growth has seen it become the second largest economy in the world, behind the U.S.. China's growth has also been much faster than the other BRICS countries; for example, when compared with the second largest BRICS economy, its GDP was less than double the size of Brazil's in 2000, but is almost six times larger than India's in 2021. Since 2000, the country with the second largest GDP has fluctuated between Brazil, Russia, and India, due to a variety of factors, although India has held this position since 2015 (when the other two experienced recession), and it's growth rate is on track to surpass China's in the coming decade. South Africa has consistently had the smallest economy of the BRICS bloc, and it has just the third largest economy in Africa; its inclusion in this group is due to the fact that it is the most advanced and stable major economy in Africa, and it holds strategic importance due to the financial potential of the continent in the coming decades. Future developments It is predicted that China's GDP will overtake that of the U.S. by the end of the 2020s, to become the largest economy in the world, while some also estimate that India will also overtake the U.S. around the middle of the century. Additionally, the BRICS group is more than just an economic or trading bloc, and its New Development Bank was established in 2014 to invest in sustainable infrastructure and renewable energy across the globe. While relations between its members were often strained or of less significance in the 20th century, their current initiatives have given them a much greater international influence. The traditional great powers represented in the Group of Seven (G7) have seen their international power wane in recent decades, while BRICS countries have seen theirs grow, especially on a regional level. Today, the original BRIC countries combine with the Group of Seven (G7), to make up 11 of the world's 12 largest economies, but it is predicted that they will move further up on this list in the coming decades.

Abstract copyright UK Data Service and data collection copyright owner.

Gross Value Added (GVA) measures the contribution to the economy of each individual producer, industry or sector. It is the value of the amount of goods and services that have been produced, less the cost of all inputs and raw materials that are directly attributable to that production.

GVA estimates have been produced as part of the Office for National Statistics' flexible geography project, which aims to produce economic statistics for small geographic areas. These estimates can then be aggregated in a flexible way, allowing users to create their own geographies.

The dataset is made by apportioning total GVA at Local Authority level to lower-level geographies [Lower Layer Super Output Areas (LSOAs) in England and Wales, Data Zones in Scotland and Super Output Areas in Northern Ireland] for the period 1998 to 2019. The lower-level geographies data form the small building blocks that can be aggregated flexibly to larger areas including Middle Layer Super Output Areas, Parliamentary Constituencies, Travel-to-Work areas, Health Boards, and towns. The building blocks enable users to build bespoke areas for analysis. The breaking down of GVA to lower-level geographies is the first time such granularity has been achieved and represents a significant improvement which allows the construction of much more detailed geographic areas.

This dataset includes the following variables:

• LSOA codes and names
• Local Authority District codes and names
• International Territorial Level 1 codes and names
• GVA for the years 1998 to 2019
  

Abstract

An all-India survey on unorganized manufacturing enterprises was carried out by the National Sample Survey Organization (NSSO) as a part of the 62nd round of National Sample Survey (NSS) during July 2005 - June 2006. Other subjects of inquiry were household consumer expenditure, employment and unemployment. Past surveys provided information on various operational characteristics of enterprises like location of enterprise, nature of operation, maintenance of accounts etc. in detail, as well as detailed estimates of employment, assets & borrowings. The 62nd survey round provides information on input, output & value added of unorganized manufacturing enterprises at all India level for different industry groups and at the level of States / UTs for all the industry groups taken together.

The manufacturing sector is one of the important sectors of industry in the Indian economy. As per the latest available National Accounts Statistics, during 2006-07, the manufacturing sector had a share of about 16% in the GDP at factor cost. For the purpose of data collection, the manufacturing sector has been broadly sub-divided into two categories i.e. organized and unorganized. While data for organized manufacturing sector are collected through Annual Survey of Industries (ASI), the same for unorganized manufacturing sector are collected periodically through sample surveys as follow-up surveys of Economic Censuses (EC). The unorganized manufacturing sector has roughly about one-third share in the total contribution by the manufacturing sector in the GDP.

Recognizing the importance of the unorganized manufacturing sector in terms of its share in GDP as well as in total employment, NSS has taken up this subject in many of its rounds. That way collection of data on unorganized manufacture has a long history in the NSS. In fact, the very first round of NSS had small-scale manufacturing and handicrafts as one of its subjects of enquiry. Thereafter, data on small-scale manufacture were collected also in the NSS rounds 3-10, 14, 23 and 29. These surveys used the list of villages from Population Census and list of census enumeration blocks, or lists of Urban Frame Survey (UFS) blocks of NSSO subject to their availability, as the sampling frame for selection of villages / urban blocks.

A review of the surveys conducted by NSSO in the initial rounds mentioned above indicated that a better sampling frame was necessary to generate more accurate statistics of the unorganized sector. The need for auxiliary information on areas of concentration of enterprises for stratification purpose was strongly felt for developing more efficient sampling designs. This demand ultimately culminated in the conduct of periodic Economic Censuses (EC), which provided the frame for the follow-up surveys on non-agricultural enterprises including those engaged in unorganized manufacturing.

With the launching of the EC in 1977 (five ECs have been conducted so far), the follow-up surveys of EC on unorganized manufacturing generally used the village and block level information on number of enterprises/workers as per the EC for selection of villages and urban blocks in the follow-up surveys. The approach of data collection from enterprises was also changed from the 'household approach' used earlier (i.e. prior to the launching of EC) to the 'site approach' whenever such sites existed. So far NSS has conducted six follow-up surveys of EC through rounds 33rd (1978-79), 40th (1984-85), 45th (1989-90), 51st (1994-95), 56th (2000-01), and 62nd (2005-06) with unorganized manufacture as the main subject of enquiry. In the 62nd round of NSS, area frame thrown up by the latest EC (1998) was however used only partially because the frame was considered to be old. However, for 27 cities having a population of one million or more (as per Census 2001) which are likely to have a substantial share in the total number of unorganized manufacturing enterprises in the country, a decision was taken to make use of the list of urban blocks giving count of number of enterprises/workers at the block level as per EC 1998 as the sampling frame for stratification and selection of urban blocks. For the remaining towns/cities, latest lists of UFS blocks were used as the sampling frame2. In case of rural areas, list of villages (or panchayat wards in case of Kerala) of Census 2001 served as the sampling frame for selection of villages as the first stage units (FSUs).

Geographic coverage

The survey covered the whole of the Indian Union except (i) Leh and Kargil districts of Jammu & Kashmir, (ii) interior village of Nagaland situated beyond five kilometers of bus route and (iii) villages of Andaman and Nicobar Islands which remain inaccessible throughout the year. All the sample FSUs of the districts Poonch and Rajouri of the state of Jammu and Kashmir became casualty. Thus, the estimates for Jammu and Kashmir as well as for all-India do not include these areas.

Analysis unit

• enterprise

Universe

Unorganized manufacturing enterprises not covered by ASI, under the two-digit codes 15 to 37 (Section 'D') of NIC-2004 and enterprises under cotton ginning, cleaning and baling (NIC-2004, code 01405). All government and public sector undertakings were outside the coverage of the survey. It is to be noted that only those enterprises, which operated for at least 30 days (15 days for seasonal enterprises) during the last 365 days preceding the date of survey, were eligible for survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

One salient feature of the sample design adopted during the 62nd round was the use of list frame, in addition to the usual area frame, which was done to capture sufficient number of relatively 'bigger' enterprises with a view to improving the overall estimate of gross value added per worker, total number of workers, total input, total output, etc. A list of 8,000 big non-ASI manufacturing enterprises2 for the urban sector only was prepared as per the data of the census of manufacturing enterprises conducted by Development Commissioner of Small Scale Industries (DCSSI) in 2003. This list served as the list frame. All these units in the list frame were considered for survey without resorting to any sampling. For the coverage of all other enterprises in the universe, the usual area frame approach was followed for sampling of enterprises in stages. It is important to mention that this dual frame approach was experimented for the first time in the 62nd round. The effectiveness of using the list frame has been discussed under Chapter four.

In the area frame approach, the list of all the villages (panchayat wards in case of Kerala) / urban blocks of the country served as the sampling frame of first stage units (FSUs). Thus, the FSUs were villages (panchayat wards in case of Kerala) in the rural sector and urban blocks in the urban sector. The ultimate stage units were enterprises in both the sectors. However, in case of large FSUs requiring hamlet-group (hg) / sub-block (sb) formation, one intermediate stage in the sampling involved the selection of two hg's / sb's from each FSU out of a minimum of three hg's/sb's formed in the FSU. Of these two selected hg's/sb's, one was selected with probability '1' (termed as segment 1) and another one (termed as segment 2) was selected from among the remaining hg's/sb's of the FSU at random. The hg/sb selected with certainty (i.e. segment 1) was the hg/sb having maximum number of directory manufacturing establishments (DMEs) (or with maximum number of non-directory manufacturing establishments (NDMEs) if there was no DME, or with maximum number of own account manufacturing enterprises (OAMEs) if there was no DME/NDME, or with maximum population if there was no DME/NDME/OAME3 in the entire FSU). Smaller FSUs without any hg/sb formation were identified/categorized as segment 1 for the purpose of survey (segment 2 does not exist for such FSUs). As regards the first stage stratification, two basic strata were formed within each district of a State/UT: rural stratum comprising all rural areas of the district and urban stratum consisting of all urban areas of the district. However, each city with a population of one million or more as per Census 2001 was invariably treated as a separate stratum by itself. For details of stratification, sub-stratification and selection of sample FSUs, reference may be made to Appendix-B of of the final report no.526.

For each of segments 1 and 2 for the selected sample FSUs, a frame of eligible enterprises was prepared by the field investigators by visiting each and every house/household within the selected geographical area. While doing so, if any enterprise of the list frame was encountered, care was taken not to list it again within segment 1 or 2 as a part of the area sample / area frame to guard against duplication of enterprises between the two types of frames. Listing and sampling of enterprises in the area frame was independent for each of segments 1 and 2. In this context, it may be mentioned that for each selected FSU of rural sub-strata 1 and 2 only (see Appendix B for composition of these two sub-strata), segment 9 was also carved out within the FSU, which comprised top 10 big non-ASI registered SSI enterprises (identified by jointly considering the number of workers in the enterprise and gross value of output of the enterprise) located within the boundaries of the entire FSU. The list of such units for selected FSUs was made available to the field investigators in order to facilitate formation of segment 9. Respective frames of segments 1 and 2 in these FSUs excluded the units listed under segment 9. The effectiveness of the formation of segment 9 has been discussed under Chapter