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Methodology - District Gross Domestic Product
Methodology - District Gross Domestic Product
Methodology - District Gross Domestic Product
Methodology - District Gross Domestic Product
Methodology - District Gross Domestic Product
Methodology - District Gross Domestic Product
Methodology - District Gross Domestic Product
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Methodology - District Gross Domestic Product

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Gross Domestic Product is defined as the total value of all final goods produced within a specified geographical area in a given year. The domestic product estimates provide an insight of how the …

Gross Domestic Product is defined as the total value of all final goods produced within a specified geographical area in a given year. The domestic product estimates provide an insight of how the economy of an area is developing.

Such estimates are usually prepared by the Central Statistical Organization at the country level and also at the Sate level. However, estimates of GDP at much finer level such as the district in India are not available. Such estimates wherever available at the district level, have merely been an academic exercise. Both the Central Statistical Organization (CSO) and the various state governments’ statistical and planning departments have only attempted such exercise as pilots. The importance of GDP at the district level in understanding the economy as well as planning for the future is hardly arguable, whether for the government or the industry.




While the methodology has been developed, discussed and debated, estimated have not been attempted. Poor quality of data has been one primary reason for this. However, recent information technology initiatives have brought a host of district level data to the public domain. Time series and quick updates have ensured availability of consistent data at the district level. This prompted us to attempt estimating the district level GDP across sectors for the first time in 2007. The first set of estimates for 2006-07 received considerable appreciation from the industry and the government. Organizations such as the RBI, 13th Finance Commission, and others appreciated the effort and also provided us with critical inputs.


After incorporating the various suggestions, we now provide you with a complete series on the district level gross domestic product. This volume thus provides you with Gross Domestic Product at current prices as well as at 1999-00 prices for all 593 districts (according to Census 2001) in India for the years 2001-02 to 2007-08. These estimates are not only for the overall GDP but also provide sectoral details of GDP. Other indicators such as per worker GDP and per capita GDP have also been provided for each sector.


This database provides the estimates at the district, state and All India levels. The state and All India estimates are from the GDP figures released by the Central Statistical Organisation. For some of the UT's namely Daman and Diu, Dadra and Nagar Haveli and Lakhsadeep the CSO does not provide the data. For these UT's we also do not provide the data. Thus the aggregate of all the districts or of all the states will not sum up to the All India GDP figure.


Further, the district data presented here is rounded off at one decimal point. Thus, the aggregate of district’s total will not match the State Figures. The CSO from time to time revises the GDP estimates as much better information flows in from the various sources. This new series on GDP estimates from the year 2001-02 to 2007-08 has been based on the current release of the GDP figures by the CSO. Also, many suggestions provided by users have been incorporated in the methodology. Thus past district level GDP may not tally with the current estimates. However, the past data has a very high correlation with the current data.


The CSO follows a combination of the income and “value-added” approach in estimating the GDP at the state level. The approach for various sectors is based on the availability of data. In our estimation of the DDP we have restricted ourselves to the value of production estimation. The obvious reason is that the data regarding inputs and stocks is inconsistent. Even estimating the value of production was a challenge.

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  • 1. District Gross Domestic Product Series 2001-2007 Methodology Gross Domestic Product is defined as the total value of all final goods produced within a specified geographical area in a given year. The domestic product estimates provide an insight of how the economy of an area is developing. Such estimates are usually prepared by the Central Statistical Organization at the country level and also at the Sate level. However, estimates of GDP at much finer level such as the district in India are not available. Such estimates wherever available at the district level, have merely been an academic exercise. Both the Central Statistical Organization (CSO) and the various state governments’ statistical and planning departments have only attempted such exercise as pilots. The importance of GDP at the district level in understanding the economy as well as planning for the future is hardly arguable, whether for the government or the industry. While the methodology has been developed, discussed and debated, estimated have not been attempted. Poor quality of data has been one primary reason for this. However, recent information technology initiatives have brought a host of district level data to the public domain. Time series and quick updates have ensured availability of consistent data at the district level. This prompted us to attempt estimating the district level GDP across sectors for the first time in 2007. The first set of estimates for 2006-07 received considerable appreciation from the industry and the government. Organizations such as the RBI, 13th Finance Commission, and others appreciated the effort and also provided us with critical inputs After incorporating the various suggestions, we now provide you with a complete series on the district level gross domestic product. This volume thus provides you with Gross Domestic Product at current prices as well as at 1999-00 prices for all 593 districts (according to Census 2001) in India for the years 2001-02 to 2007-08. These estimates are not only for the overall GDP but also provide sectoral details of GDP. Other indicators such as per worker GDP and per capita GDP have also been provided for each sector. Indicus Analytics Pvt. Ltd, Methodology District GDP
  • 2. This database provides the estimates at the district, state and All India levels. The state and All India estimates are from the GDP figures released by the Central Statistical Organisation. For some of the UT's namely Daman and Diu, Dadra and Nagar Haveli and Lakhsadeep the CSO does not provide the data. For these UT's we also do not provide the data. Thus the aggregate of all the districts or of all the states will not sum up to the All India GDP figure. Further, the district data presented here is rounded off at one decimal point. Thus, the aggregate of district’s total will not match the State Figures. The CSO from time to time revises the GDP estimates as much better information flows in from the various sources. This new series on GDP estimates from the year 2001-02 to 2007-08 has been based on the current release of the GDP figures by the CSO. Also, many suggestions provided by users have been incorporated in the methodology. Thus past district level GDP may not tally with the current estimates. However, the past data has a very high correlation with the current data. The CSO follows a combination of the income and “value-added” approach in estimating the GDP at the state level. The approach for various sectors is based on the availability of data. In our estimation of the DDP we have restricted ourselves to the value of production estimation. The obvious reason is that the data regarding inputs and stocks is inconsistent. Even estimating the value of production was a challenge. The basic function used in estimating the production index at the district level for the various sectors is given below: For a given district 'd' the production 'Y' for a sector 's' is Y ds i = f (li, ki, ti) Where i=year, l=Labour cost, k= Capital cost, t= Technical Efficiency, s=sector For agriculture sector however, information on production of various crops and their prices at the district level were available. Thus we have estimated the value of production (vop) for each crops produced in the district. The basic function used in estimating the vop is given below: For a district “d” and a crop “i” the vop is ∑VOP = ∑ pi*qi n i i =1 VOP— value of output for each district pi— production for crop i qi—price for crop i i – no. of crops; from 1 to n; n varies from district to district Indicus Analytics Pvt. Ltd, Methodology District GDP
  • 3. The detailed process of estimating the GDP at the district level for the various sectors is presented below: Agriculture: Gross Domestic Product of Agricultural sector is estimated from the aggregate value of production for all the crops produced within a district in a given year. The value of total production of crop is defined as the product of the median price and total output (crop production). The data sources and methodology for computing both production and prices of crops at the district level are presented below. Estimation of Production at the District Level: District level production data is available from 1999-00 to 2005-06. The two main sources of data are Ministry of Agriculture (MoA) and Fertiliser Association of India (FAI). The process of collating the data had two major issues. First the creation of new districts and changing of district boundaries. Number of districts has been varying over the years with new districts being created, some districts being merged together and many being renamed. For the purpose of uniformity of data we have adhered to the Census 2001 list of 593 districts for India. All the data has then been mapped to this list of 593 districts. Data has been combined in cases where complete districts have been combined together. For broken up districts or districts where portions have been combined, we have distributed the production proportionally. The proportional distribution for the latest available production data has been used to allocate the production in previous years. Second, missing data. The production data obtained from the above mentioned sources was found to be missing at various levels. Accordingly, these values have been estimated. Broadly there were three sets of missing values. First, district data was found to be missing for a set of districts in a state while the state aggregates were available. Second, neither the state nor the district data were available. Third, some district data was available, the rest including the state aggregates were missing. Adequate care has been taken in the estimation of the missing values for each of the above sets. Each case being treated separately. A combination of growth rates based on available data at the state and the district have been used in estimating the missing values for the three sets. To validate our process we have compared the trend in agricultural production with the average annual rainfall and other climatic condition for a district in a given year. Data on the number of districts with scantly rainfall in a particular year helped us identify the reasons for poor production. Besides, some state governments come out with the socio- economic review of a state for a particular year. For instance, Socio- Economic Review of Gujarat, 2002-03 confirms the low level production obtained for 2002-03 in many districts of Gujarat. Estimation of Prices at the District Level: Prices of each crop have been taken from Agmarknet and “Agricultural Prices in India” published by Ministry of agriculture. This has provided us with detailed Indicus Analytics Pvt. Ltd, Methodology District GDP
  • 4. information of daily prices for each mandi in the country for the period 1999-00 to 2005-06 and government publication on crop prices. Estimation of Value of Production:- Value of Production (VOP) has been calculated using the production and prices per crop for each district for the years 1999-00 to 2005-06. These district level estimates of VOP have then been calibrated to the State level VOP. The state level estimates is obtained from CSO for all the crops and for the entire period 1999-00 to 2005-06 Even after cleaning the data, there are instances where we do not have any data on a particular crop for a state, e.g. cashew nuts in case of Goa. For many minor crops the reporting is also poor and the data is missing in most districts. We have thus ensured that for most states, the district data considered for the estimation accounts for over 85% of the states VOP. The only exception is Goa, where the reporting of data is poor. Estimation of DDP:- The district proportions based on the VOP have been used to distribute the state GDP of Agriculture amongst the districts. This process of assigning the GDP to districts has been used for the years 1999-00 to 2005-06. In addition, for the years 2006-07 & 2007-08 the data on production was not available. Thus the district proportion has been estimated based on the growth rate in DDP during 1999-00 to 2005-06. Rest of the sectors: For the remaining sectors a district level index has been developed using the production approach. This index is then used to distribute the State GDP across the districts. The index has been developed using the additive function and by assign equal weights to the various factors. The variables included in the creation of the index represent the various factors of productivity viz labour cost, capital and technical efficiency. District level workers by National Industrial Classification (NIC) given in Census have enabled us to identify the total number of workers in each sector. The median expenditure of the households involved in those NICs is computed from NSSO, survey on employment, unemployment and consumer expenditure. Total outstanding credit of scheduled commercial banks for the sector is taken as a proxy to capture capital cost. RBI provides district level data on outstanding credit of scheduled commercial banks according to occupation. As in the other data sets, credit for some districts in certain occupational categories was found to be missing. In such cases credit values have been estimated using past trends. Sectors where credit is not available, sector specific variables are chosen to reflect the capital cost. In the estimation exercise workers, expenditure, and credit used at the district level are from the sources discussed above. However, for each sector, a sector specific variable has been identified that capture the output of the sector as well as the variations at the district level. For each of the sector, the variables considered are discussed below. Indicus Analytics Pvt. Ltd, Methodology District GDP
  • 5. Forestry: This sector comprises minor and major forest products. Time series on total forest cover at district level has been used. Also, district level value of output has also been calculated using firewood consumption data obtained from census. These above specified variables have been incorporated to estimate district proportion in the GSDP forestry. Fishing: Variables used in fishing sector, i.e., fish production and fishing equipments are sourced from Livestock Census by Ministry of Animal Husbandry. Various fish equipments are given weights on the basis of productivity. Mining and Quarrying: The sector specific variables used in mining & quarrying sector is the district level data on value of minerals, i.e., major minerals, petroleum (crude) and natural gas, collected from Indian Bureau of Mines, Nagpur. District-wise value of production for coal is taken from Coal India Ltd. and that of natural gas and crude oil from ONGC. For minor minerals, the district-wise value of output has been collected from the State Mines and Geology Departments. Manufacturing: Total production of manufacturing sector is used to reflect the performance of manufacturing sector within a district. District level estimates of production for 60 industry groups have been estimated in the product “Industrial Skyline of India”. These estimates are based on the data on organized manufacturing sector from ASI and unorganized sector from NSSO. Construction: Construction sector comprises commercial, residential as well as infrastructural construction. Parameters considered for district level value added in residential construction sector is reflected by households owing pucca houses available from Census. However, commercial construction is also included to add weightage with regard to official and commercial construction in the business hub. Infrastructural development has also been incorporated in the district index value for construction sector. Electricity, Gas, Water supply: This sector covers all the three sectors. These sectors are represented by the following parameters: Electricity: Number of households using electricity at district level is proxy variable of revenue generated from electricity sector. Indicus Analytics Pvt. Ltd, Methodology District GDP
  • 6. Gas: District level number of households using LPG is a substitute consideration for this sector’s income. Water Supply: A proxy variable for “water supply” sector i.e. no. of households having tap in the premise taken from Census, is used to create district level index value for this sector. The composite index for this sector is also generated on the basis of the above specified variables along with consumption expenditure by the workers involved in this sector and credit owing to this sector. Transport, Storage and Communication: The economic activities covered in this sector are (i) transport by railways, (ii) transport by other means, namely, road transport (mechanised and non-mechanised), water transport (coastal, ocean and inland), air transport and services incidental to transport, (iii) storage, (iv) communication services rendered by Post & Tele- communication Departments and Overseas Communication Services. Only available district level variable for this sector is households having telephone connection taken from Census, is used to reflect the performance of this sector. Apart from this, district level workers for all these sectors separately engaged in these sectors provide district level estimation of GDP of Transport, Storage and Communication. Trade, Hotel, Restaurant: The activities considered in the sector are (i) both domestic and export of wholesale and retail trade in all commodities and import, (ii) purchase and selling agents, brokers and auctioneers, (iii) services rendered by hotels and other lodging places, restaurants, cafes and other eating and drinking places. Number of hotels and workers engaged in the sector are utilized to generate an index for this sector. Indicus Analytics Pvt. Ltd, Methodology District GDP
  • 7. Public Administration: Census of central government employees conducted by Government of India, Ministry of Labour (Directorate General of Employment and Training) provides employment details on pay ranges of employees. Index for this sector has been built based on information on income and employment in this sector. Other Services: Other services sector includes real estate, ownership of dwellings and business services and other services. GDP for other services has been allocated to districts in proportion to the index value including working force and expenditure potential of households involving workers in this sector. Indicus Analytics Pvt. Ltd, Methodology District GDP

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