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The Journal of Income and Wealth
Year : 2003, Volume : 25, Issue : 1&2
First page : ( 83) Last page : ( 99)
Print ISSN : 0000-0000.

Katyal R.P., Sardana M.G., Satyanarayan J.

Socio-Economic Research Centre, New Delhi

JEL Classification: E01

Introduction

For planning and policy purposes the central and state authorities and research institutions often require data on economic activities, levels of living of the people etc. at the district level. Income of a district is thought to be one of the most important indicator/barometer to measure the economic growth/development of a district vis-à-vis other districts. Preparation of estimates of District Domestic Product (DDP) or District Income has recently gained added importance, as it is one of the three indicators to construct a composite Human Development Index (HDI) for inclusion in the Human Development Report being prepared by some of the states of India. Other two indicators forming part of HDI are life expectancy and educational attainment.

Some of the State Governments started preparing the estimates of district income to measure the income disparity and to plan for the development of backward districts during seventies/early eighties. For example the State of Uttar Pradesh complied the district income estimates for all sectors for 1968–69 but later on restricted the preparation of these estimates to commodity producing sectors only.

The estimation of income at district level is beset with the problems of availability of data, collection and analysis of information etc. The Seventh Conference of Central and State Statistical Organisations held at Hyderabad in December 1985 discussed the issues relating to the preparation of the income at district and rural/urban levels. Keeping in view the demand from the Planning Commission and the state governments for the income estimates at the district and rural/urban levels the Conference recommended constitution of a Technical Group to examine the requirements of data and recommend appropriate methodology for compilation of these estimates. In pursuance of this recommendation the Department of Statistics constituted a Technical Group for Estimation of Income at District and Rural/Urban Levels in January 1987. The Group in its Report submitted in September 1988 recommended that to start with, attempts should be made to compile the district income estimates following the standard methodology, based on the income originating approach, as used for compilation of state income estimates. Due to the free flow of goods and services across the borders of the districts and the non-availability of net factor income earned by the residents from other districts/states/countries, the income accruing approach was not feasible.

Even to compile the estimates by following the income approach a lot of additional data, as detailed in the Report, need to be collected.

For district income estimates, tremendous amount of information would need to be collected and compiled at the district as well as at state levels. The Group felt that the state governments should assess the precise requirements of additional resources for implementing the recommendations of the Group and make necessary provisions in their core schemes.

Since the estimates at the district level would be utilized for the purpose of determining the backwardness/development of a district, and as consequence for allocation of resources, it would be necessary to make necessary adjustments in these estimates in regard to significant flow of income from and to across the territories of typical districts which are rich in minerals and/or forest resources or where flow of daily commuters, migration of labour and cattle are involved. With the present availability of data at the district level it would be sufficient to compile these estimates at an interval of five years.

The Group also detailed the data requirements for compilation of district income estimates and also annexed the essential items for which data need to be maintained at the district level.

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Methodology for estimates of district domestic product

With a view to giving impetus to the compilation of district income estimates by the state governments and to standardize the methodology of district income estimates the National Accounts Division (NAD) of the Central Statistical Organization (CSO) called a meeting of the State Directorates of Economic and Statistics (DES) in 1995. The Meeting entrusted the work of development of the methodology of compilation of District Domestic Product (DDP) jointly to the DES of the states of Karnataka and Uttar Pradesh. The methodology for compiling DDP was developed jointly by the DES of the states Karnataka and Uttar Pradesh in August 1996. The state governments have been broadly following this methodology for preparation of district income estimates.

A number of state governments have already initiated the work on the preparation of DDP. While Andhra Pradesh, Bihar, Haryana, Karnataka, Kerala Madhya Pradesh, Maharashtra, Rajasthan, and Tamilnadu are compiling the estimates for all the sectors of the economy, Arunachal Pradesh, Assam, and Uttar Pradesh have restricted this to the commodity producing sectors.

The methodology for compiling the DDP, given in the following paragraphs, takes into consideration the broad methodology given in the Report of the Technical Group on District Income as also its recommendations and the methodology developed jointly by the DES of the states of Karnataka and Uttar Pradesh in August 1996. The proposed methodology takes into account the available data at the district level for the commodity producing sectors and the results of the surveys, both relating to socio-economic aspects and unorganised sectors of the economy, conducted by the National Sample Survey Organisation (NSSO) and states DES. For many of the sectors of the economy the proposed methodology avoids allocation of state estimates to districts in proportion to the district-wise work force, as this does not take into account the income disparity at the district level.

Broadly the methodology of computation of sectoral estimates is the same as adopted for the estimates of State Domestic Product (SDP). The database for estimation of DDP is still not satisfactory for any of the states. Data for compilation of DDP in respect of commodity producing sectors viz., primary sectors and manufacturing (registered) sector, are mostly available on a regular basis but in respect of remaining sectors, these are very scanty. As such, wherever district-wise basic data are available, these may be utilised to compute the DDP estimates following the methodology adopted at the state level. In case of non-commodity producing sectors, where district-wise basic data are not available, the state level estimates may be allocated to the districts on the basis of suitable district-wise indicators. Further, in some of the commodity producing sectors, though district-wise production data are available, the corresponding prices are not available. In such cases, district-wise production may be evaluated using prices prevailing in the adjoining district/region.

For the commodity producing sectors the estimates of DDP may be prepared using the production approach i.e., gross value added = value of output minus the value of inputs, whereas for the services sectors income approach i.e., gross domestic income = compensation of employees plus the gross operating surplus may be used.

For compiling DDP the economy may be divided into following 14 broad sectors (8 commodity producing and 6 non-commodity producing sectors) as done in the case of SDP.

Commodity Producing Sectors

  1. Agriculture

  2. Forestry and Logging

  3. Fishing

  4. Mining and Quarrying

  5. Manufacturing - Registered

  6. Manufacturing - Unregistered

  7. Construction Electricity, Gas and Water Supply

Non-Commodity Producing Sectors

  1. Trade, Hotels and Restaurant

  2. Transport, Storage and Communication

  3. Banking and Insurance

  4. Real Estate, Ownership of Dwellings and Business services

  5. Public Administration and Defence

  6. Other services

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Detailed methodology: Commodity producing sectors

Agriculture including Animal Husbandry

As in the case of SDP, the estimates of value of output of agriculture and animal husbandry may be prepared separately. Because of feeding the animals together and the farmers not keeping separate account of inputs for agricultural crops and animal products, the estimates of inputs cannot be prepared separately. As such the value added estimates may be prepared for the overall activity of agriculture.

Value of Output of Crop Husbandry

As in the case of SDP, the estimates at district level can also be worked out by ‘production approach’. But district level data on production and prices are generally not available uniformly for all the crops. Hence, for estimation purpose, crops may be classified in the following categories:

Crops for which district-wise data on production and prices (primary market or farm harvest prices) are available

In such cases district-wise value of output for each crop may be worked out by using district-wise production and prices. Crops for which though district-wise production is available but corresponding district-wise prices are not available. For this category of crops, district-wise value of output may be computed by using production data of the district and available price data from a neighboring district. In case neighboring district prices are also not available, regional prices may be used. If these are also not available, the only alternative is to use state prices. Efforts should be made to collect prices in respect of all such crops for which area and yield estimates are available. Crops for which district-wise data, both on production and prices, are not available but crop area figures are available. In such cases, district-wise value of output of these crops may be worked out by allocating the state level value of output on the basis of district-wise crop area. Miscellaneous and unspecified crops for which production and price data are not available even at the state level but districtwise crop area is available: In these cases, the value of output may be worked out by multiplying the district-wise crop area with state level value per hectare of respective crops.

For by-products or miscellaneous type of products, wherever possible, cost of cultivation studies (CCS) data on yield rates, inputs, etc. may be used. In the absence of data of CCS for the district, attempts may be made to undertake type studies to fill this gap. Till such time the results of type studies or data from other sources at the district level become available, state level ratios, whether in relation to output or in relation to crop area as used in current series of estimates of SDP, may be adopted uniformly for all the districts.

For the quantity of food grains procured on Government account, the prices are different from the prevailing market prices. As such the quantity procured by the Government may be evaluated at procurement prices and the rest of the produce at the primary market/farm harvest prices.

Value of Output of Animal Husbandry

Procedure similar to the one adopted for compiling SDP may be followed to estimate the value of output from animal husbandry for the district. District-wise estimates of number of different categories of animals and poultry may be worked out using the results of latest two/three livestock censuses, assuming linear/compound growth rates. These may be used along with relevant yield rates to obtain the estimates of production of various livestock products and byproducts and poultry meat.

In general the results of Integrated Sample Survey (ISS) conducted by State Animal Husbandry Department provide state/district level data on production of milk, meat, wool and egg. The survey also provides estimates of category wise number of slaughtered animals. Wherever, ISS results are available only for the state, the estimates for district may be obtained by allocating the state estimate to the districts on the basis of relevant livestock population. To estimate district-wise production of all other items (i.e. other than milk, meat, egg and wool), state level yield rates and ratios may be utilised along with district estimates of number of relevant animals/poultry.

District-wise value of output may then be worked out by evaluating the production obtained as above, by the corresponding district prices, wherever available. In the absence of region or district level prices, the state prices may be utilised for evaluating the district production. Total value of output thus worked out may then be adjusted to the state level estimates.

ItemPrice to be used

(i)MilkRural price/cooperative's collection price
(ii)Meat(buffalo)Slaughter house price
(iii)Goat, sheep and pig meatSlaughter house price
(iv)Hides (cow and buffalo)Slaughter house price
(v)Skins (goat and sheep)Urban wholesale price of goat skin
(vi)Bones (of various animals)Urban wholesale price of bone
(vii)DungRural prices of dung cake
(viii)Egg (hen and duck)National Egg Coordination Committee prices

In regard to the items for which price data are not available, wholesale/retail prices of allied items should be utilised. The price data can be used in various cases as indicated below.

In case of other animal products, for which neither the yield rates nor the prices are available at the district level, the state level value may be allocated to the districts in proportion to the number of animals of each category separately.

District-wise increment in stock for each category of animal/poultry may be worked out as at the state level and these may be evaluated by corresponding district prices.

The value of silkworm cocoons compiled for the SDP, after adjusting the cost of rearing silkworm cocoons, may be allocated to districts in proportion to the area under mulberry in each district.

Keeping in view the data gaps it is suggested that the coverage of ISS may be enlarged by the respective state governments so as to generate the estimates of production of each of the animal product at the district level. Further, prices of agricultural and animal products at the district level need to be collected and compiled from representative centers so that for each of the product the price data are available and utilized for district income estimates.

Value of Inputs for Crops and Animal Husbandry

To arrive at the district-wise gross value added (GVA) from agriculture including Animal Husbandry sector, value of various input items are to be first deducted from the gross value of output of these sectors and then the gross product from operation of Government Irrigation System is added to that. The deductible inputs are same as used in compilation of SDP viz., (i) seed, (ii) organic manure (cattle and buffalo dung), (iii) chemical fertilizers (iv) feed of livestock, (v) pesticides & insecticides, (vi) diesel oil consumption (vii) electricity, (viii) irrigation charges, (ix) market charge, (x) repairs and maintenance of fixed assets and other operational costs and (xi) financial intermediary services indirectly measured (FISIM). To work out the value of these input items at the district level, the state level estimates arrived at independently under the current series of state income estimates may be distributed to the districts on the basis of the procedure indicated below:

Seed

Seed rates and area sown for each of the important crop at the district level are generally available with the district agricultural departments. These data should be collected and quantity of seed for each of the crop may be worked out as a product of seed rate and area under each crop. This may be multiplied by the respective prices at the district level to arrive at the value of seed input. For other crops for which seed rates are not available at the district level, the input of seed for each of the crop may be worked by allocating the value at state level in proportion to the area under each crop at the district level.

Organic manure

State level value of output may be allocated to the district in proportion to the district-wise estimates of value of output of dung manure as worked out in the Animal Husbandry sector.

Chemical fertilizers

State level value may be distributed to districts in proportion to total quantity of chemical fertilizers distributed as obtained from the Agriculture Department.

Feed of livestock

District-wise value of roughage may be estimated by adopting the same methodology as followed for estimating the roughage in case of SDP. For estimating the quantity of concentrates consumed, the returns of CCS may be collected from the agricultural universities that are engaged in such studies in the State and analyzed. In the absence of such study results, the rates of concentrates as adopted for state level estimates for different types of animals and poultry may be used for working out district level estimates also.

Pesticides and insecticides

State level value may be allocated to the districts in proportion to area treated by chemical pesticides in different districts. Efforts may be made to obtain the results of CCS in a state at the district level and the value of pesticides and insecticides districtwise may be worked.

Diesel oil consumption

State level value of consumption of diesel oil by tractors and oil engines may be distributed to districts in proportion to the district weighted totals of number of tractors and oil engines/oil engine pumps used for irrigation as per latest livestock census. Weights being the per unit consumption of diesel oil based on the data collected from the schedules of CCS. If district level consumption of diesel per unit is not available then state level norms may be adopted.

Electricity

State level value may be distributed on the basis of district-wise number of private and government electric tube-wells and energized pump-sets.

Irrigation charges

District-wise irrigation charges, as collected from the district administration may be used for this purpose. In the absence of such data, the state level value may be distributed to the districts in proportion to the area irrigated by government canals.

Market charges

State level norms in respect of crop husbandry and animal husbandry sectors may be used for district income estimates also.

Repair and maintenance of fixed assets and operational costs

District-wise data on fixed assets as available from latest AIDIS/Livestock Census may be used to allocate the state total to the districts. Alternatively the district-wise value of output may be multiplied with the state level ratios of repairs and maintenance etc. to the value of output.

FISIM

State level value of FISIM may be distributed on the basis of total value of output of the district.

Operation Of Government Irrigation System

Data on salaries and wages are likely to be available with the district agriculture departments. The same should be collected and used for allocation of the state level value of contribution by Government Irrigation System to the districts in proportion to the district-wise salaries and wages/area irrigated by government canals.

Forestry and Logging

Major Forest Products

The forest circles/divisions/sub-divisions are generally not coterminous with district boundaries. The records of the forest/revenue departments at the division/sub-division/forest range/forest coupe levels will have to be looked into so as to demarcate forest areas within a district. For example, in case of Madhya Pradesh the boundaries are now coterminous with one or more forest divisions.

District-wise value of output of timber may be worked out using the district-wise production and prices for different varieties.

In the case of firewood, consumption of firewood may be estimated at the district level using the pooled results of central and state samples of the latest available quinquennial (55th Round) survey of NSSO relating to household consumer expenditure. The value of firewood at the state level may be allocated to the districts in proportion to the district-wise consumption of firewood.

Till such time the district-wise pooled results of central and state samples of 55th round of NSS are worked out the value of output of firewood at state level may be allocated to the districts in proportion to the forest area of each district.

Minor Forest Products

District-wise value of output may be worked out using the districtwise production and prices of different products wherever available from the Minor Forest Products Corporation etc. For other products in the absence of district-wise data the state level value of other minor forest produce may be allocated to districts in proportion to the forest area in the districts.

Repairs, Maintenance and other Operational Costs

State level ratio may be utilised for working out district-wise estimates of repairs, maintenance and other operational costs.

Fishing

In the case of marine fishing, the district-wise value of output may be worked out by multiplying the district-wise production by the corresponding district prices. Similar procedure may be followed in working out district-wise value of output of inland fish also. The district wise production of marine and inland fish is likely to be available through district fishery officer. In case the district-wise prices are not available, then district-wise value may be worked out using district-wise production and adjoining district/region prices. Data on operational costs including repairs and maintenance even for SDP are not available and the national level norms are used for SDP. Thus there is no other alternative but to use the state level norm/ratios for DDP estimates also.

Mining and Quarrying

For major minerals including petroleum (crude) and natural gas (utilised), the district-wise value of output as available with Indian Bureau of Mines, Nagpur, may be used. District wise value of production of coal can also be obtained from Coal India Ltd. and that of natural gas and crude oil from ONGC. For minor minerals, the district-wise value of output may be collected from the State Mines and Geology Department. If the data are not available, the value of output of minor minerals may be worked out in proportion to the royalty value. For working out input costs, the state level proportions may be adopted.

Manufacturing - Registered

The Annual Survey of Industry (ASI) being conducted by the Field Operation Division of the NSSO provides the requisite data for compiling estimates of GVA for manufacturingregistered sector (units registered under the Factories Act, 1948) of manufacturing both at the national as also the state level. The sampling strategy adopted till ASI 1996–98 aimed at even providing data to generate district level estimates by the DES.

On the recommendation of a Steering Committee constituted by the Department of Statistics and Programme Implementation, Government of India in May 1999, a revised sampling strategy has been put into operation from ASI 1998–99 so as to enable the FOD of the NSSO to manage the field work of about 45000 units with the sanctioned field resources. With the new sampling strategy, ASI would cater to the generation of estimates only at all-India and State levels. Under the new sampling strategy all factories engaging 200 or more workers are being covered on a complete enumeration basis (called census sector) and the remaining factories on a sample basis (called sample sector). However, in case of small states/union territories of Manipur, Meghalaya, Nagaland, Tripura and Andaman and Nicobar Islands, all factories are being covered on a complete enumeration basis.

At present the states of Assam, Orissa, Rajasthan, Uttar Pradesh, and West Bengal cover the residual units belonging to the sample sector of their states with their own resources. For these states by appropriately pooling the results of units covered by the state field staff and the ASI field work (census sector and sample sector) conducted by FOD of the NSSO, districtwise estimates can be computed. Other state governments who are interested in generating district level estimates may take steps to cover additional samples with their own resources. Till such time the states DES are able to mount resources to participate in the ASI programme, the GVA for the sample sector may be allocated to the districts using an appropriate indicator. The value added per worker derived from the results relating to the census sector of the ASI for the district multiplied by an estimate of the work force engaged in the sample sector of ASI for the district may be taken as the indicator for allocating the GVA for the sample sector of the ASI for the state to the districts. The data collected under the Fourth Economic Census 199899 can be utilised to work out an estimate of the work force engaged in the sample sector of factories covered in the ASI in the district.

It is understood that the Chief Inspector of Factories (CIF) in most of the states is maintaining an up-to-date computerized list of factories registered under the Factories Act, 1948. The field staff of FOD of NSSO are using it as a frame for ASI field work. The list available with the CIF contains information relating to number of workers in each registered factory. As an alternative to using the data collected under the Fourth Economic Census, this list can be used for estimating the work force engaged in the sample sector of factories covered in the ASI in any of the districts.

Manufacturing & Unregistered

The methodology for compiling the DDP jointly developed by the DES of the states of Karnataka and Uttar Pradesh in August 1996 for manufacturing-unregistered and many other sectors/sub-sectors suggests the use of workforce for allocation of SDP to districts.

The allocation of state domestic product for a particular sector in proportion to work force has the implicit assumption that the value added per worker is the same for all the districts. Such a procedure makes the rich districts less rich and the poor districts less poor. Thus the disparity in income gets reduced and does not reflect the proper picture. As such its use to the extent possible may be avoided.

For the manufacturing unregistered and the unorganised segments of the remaining sectors of the economy i.e. unorganised trade, unorganised hotels and restaurant, unorganised road transport, unrecognised educational institutions, unorganised medical and health services, etc. the estimates of GVA are worked out as a product of work force and GVA per worker. While the GVA per worker is derived from the follow-up surveys of economic censuses carried out by the NSSO, the work force is estimated from the quinquennial surveys of employment and unemployment of the NSSO.

Fifty-sixth round (2000–01) of the NSSO covered the unorganized manufacturing (i.e. not registered under the Factories Act, 1948). Central and state samples may be pooled to generate the district-wise GVA per worker at 2-digit level of National Industrial Classification (NIC) as done for the SDP. GVA per worker may be multiplied by the corresponding estimates of work force (discussed in paras 37 and 38) to arrive at the GVA at 2-digit of NIC. By aggregating, the total GVA for the sector at the district level may be arrived.

Till such time the district-wise value added per worker is derived based on the pooled results of central and state samples of NSS for the benchmark year 2000–01, it is suggested that the estimates of SDP may be prepared separately for rural and urban areas for the benchmark year using NSS results. For other years the SDP may be apportioned to rural and urban areas in proportion to the benchmark estimates. These estimates may then be allocated to the districts using the district-wise workforce. Such a procedure ensures that at least the rural/urban disparity in earnings is taken care of.

The estimates of the work force for 1993–94 at the state level, based on the 50th round (1993–94) Survey of Employment and Unemployment of NSSO, along with the methodological note, at 3-digit level of NIC were supplied by the NAD of the CSO to the states for use in the state income estimates in March 1999. In what follows the estimates of work force will refer to the work force based on the NSS surveys mentioned above.

For any activity (2–3 digit level of NIC), the estimate of work force as provided by the NAD of the CSO, may be estimated by allocating the state total to various districts in proportion to district-wise work force, in that activity, as available from the latest population census.

From the total work force for manufacturing at the district level the corresponding work force of manufacturing - registered based on ASI may be subtracted to arrive at the work force for the manufacturing & unregistered sector at 2-digit level of NIC.

Construction

41. Data on wage rates of the construction workers can be easily collected at the district level. The estimates of state income from this sector may be allocated to the districts on the basis of indicator of work force engaged in construction activity multiplied by the wage rate of construction workers at the district level. In respect of local bodies, direct district-wise data may be collected and utilized.

Electricity, Gas and Water Supply

Electricity

District-wise data on salaries and wages are available with the State Electricity Boards (SEBs). Special efforts may be made to collect/extract data from the administrative records available with SEBs. The state level value added from this sub-sector may be distributed to the districts in proportion to district-wise salaries and wages. The use of work force alone as an indicator will not take into account the disparity in wages and salaries at the district level. Although the pay scales are the same for all districts but the distribution of workers by different pay scales may vary significantly for developed and under developed districts. Thus to capture this disparity, indicator based on salaries and wages will be more meaningful.

Gas

State level value added from bio-gas may be distributed in proportion to the number of bio-gas plants in each districts. For remaining gas sector, the state level estimates may be allocated to the districts on the basis of work force engaged in this activity.

Water supply

State level value added may be allocated to districts in proportion to the districtwise salaries and wages collected from local bodies located in the district.

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Detailed methodology: Non-commodity producing sectors

For the unorganized segments of the non-commodity producing sectors district wise GVA, for a particular activity, may be estimated as a product of work force and the GVA per worker. For the non-commodity producing sectors district-wise total work force at two or three digit of NIC may be based on the NSS surveys of employment and unemployment as discussed under manufacturing-unregistered sector (cf. paras 37 and 38). For public sector undertakings or for the organized segments the work force will be based on the administrative records of the undertakings/enterprises. The work force for the unorganized segments or for the private sector may be derived by subtracting from the total work force of an activity the corresponding work force in the organized segment or in the public sector as the case may be. The value added per worker may be derived from the pooled results of central and state samples of quinquennial surveys of NSSO for the unorganized activities. As in the case of manufacturingunregistered it is suggested that

Till such time the district-wise value added per worker is derived based on the pooled results of central and state samples of NSS for the benchmark years, the estimates of SDP of unorganized segments may be prepared separately for rural and urban areas for the benchmark years using NSS results. For other years the SDP these segments may be apportioned to rural and urban areas in proportion to the benchmark estimates. These estimates may then be allocated to the districts using the district-wise workforce.

Such a procedure ensures that at least the rural/urban disparity in earnings is taken care of.

Trade, Hotels and Restaurants

Trade-Public Sector

SDP relating to public sector may be allocated to districts on the basis of data on salaries and wages available from the administrative records of the relevant public sector undertakings engaged in trading activity.

Trade-Private Sector

The 53rd round NSS covered unregistered trading activities by nondirectory establishments (enterprises engaging not more than five workers including at least one hired worker) and own account enterprises and the states participated in this programme like any other round of NSS. The directory trading establishments (enterprises engaging six or more workers including at least one hired worker) were surveyed by special staff of FOD of NSSO of the same rank as those engaged for conducting the field work of ASI during the same year. The survey is called Directory Trade Establishment (DTE) Survey. The states did not participate in the DTE survey. The estimates at the district level for the benchmark year 1997 may be worked out by pooling the results of central and state samples relating to non-directory enterprises and own account enterprises. For other years SDP relating to the private segment of the economy relating to this sector may be allocated to district in proportion to the gross value of output of commodity producing sectors in each district.

Hotels and Restaurant

Fifty-seventh round (2001–2002) survey of the NSSO covered the unorganized segments of hotels, restaurants, storage & warehousing, post & telecommunication, mechanized road transport, non-mechanised road transport and other unorganized transport, real state and business services, education, health and social services, and other community, social & personal service activities. Unorganised sector enterprises are those whose activities or collection of data are not regulated under any legal provision and/or which do not generally maintain any regular accounts.

Hotels and Restaurant-Public Sector

SDP relating to public sector may be allocated to districts on the basis of data on salaries and wages available from the administrative records of the relevant public sector undertakings engaged in hotels and restaurant activities.

Hotels and Restaurant-Private Sector

The SDP relating to these activities in the private sector may be allocated to districts on the basis of district wise private work force and the value added per worker as obtained from the pooled results of central and state samples of 57th round survey of NSSO for the unorganized sector. District-wise private work force may be estimated by subtracting from the total work force for this activity the corresponding work force in the public sector undertakings.

Transport, Storage and Communication

Railways

State level estimates, as provided by CSO, may be allocated to districts in proportion to the track length located within the district.

Mechanised Road Transport-Public Sector

52. SDP relating to public sector may be allocated to districts on the basis of data on salaries and wages available from the administrative records of the relevant public sector undertakings engaged in this activity.

Mechanised Road Transport-Private Sector

The SDP relating to these activities in the private sector may be allocated to districts on the basis of district wise private work force and the value added per worker as obtained from the pooled results of central and state samples of 57th round survey of NSSO for the unorganized sector. District-wise private work force may be estimated by subtracting from the total work force for this activity the corresponding work force in the public sector undertakings.

Till such time the district-wise value added per worker is derived based on the pooled results of central and state samples of NSS for the benchmark years, it is suggested that the estimates of SDP of this segments may be prepared separately for rural and urban areas for the benchmark year using NSS results. For other years the SDP of this segment may be apportioned to rural and urban areas in proportion to the benchmark estimates. These estimates may then be allocated to the districts using the district-wise rural/urban workforce.

Non-Mechanised road Transport and Other Unorganised Transport

The value added from this activity may be derived at the district level as a product of district wise work force engaged in this activity and the value added per worker for this activity obtained from the pooled results of central and state samples of 57th round survey of the NSSO for the unorganized sector.

Till such time the district-wise value added per worker is derived based on the pooled results of central and state samples of NSS for the benchmark year, the procedure suggested for mechanized transport to prepare district-wise estimates separately for rural and urban may be adopted.

Water Transport

State level estimates may be allocated to the districts using the same procedure as for the non-mechanized road transport.

Air Transport

The SDP from this sub-sector may be allocated to the districts in proportion to the salaries and wages data collected from the local offices of the airlines.

Storage Warehousing (State and Central)

State level estimates may be allocated to the districts using the same procedure as for the mechanized road transport.

Cold Storage

Cold Storage is covered under ASI. The same procedure as used for manufacturing (registered) may be used.

Storage not elsewhere classified

District-wise estimates may be prepared using the same procedure as for the non-mechanized road transport.

Communication-Public Sector

Data on salaries and wages may be collected from the public sector units located within the district to allocate the SDP from this activity. Alternatively SDP may be allocated using indicators of district-wise revenue generated by post and telegraph offices, telephones, etc. data for which may have to be collected from administrative records of the concerned offices.

Communication-Private Sector

District-wise estimates may be prepared using the same procedure as for the mechanized road transport.

Banking and Insurance

62. Data on salaries and wages can be collected from the regional/district offices of banks and insurance companies. The SDP of this sector may be allocated to the districts on the basis of district wise salaries and wages.

Real Estate, Ownership of Dwellings and Business Services

Real Estate and Business services

District-wise estimates may be prepared using the same procedure as for the non-mechanized road transport.

Ownership of Dwellings

State level estimates may be allocated to districts in proportion to number of dwellings (Rural/Urban) in each district based on census data multiplied by districtwise rent per dwelling worked from the 55th round survey of NSSO by pooling the results of central and state samples.

Till such time the district-wise rent per dwelling is derived based on the pooled results of central and state samples of NSS for the benchmark year, it is suggested that the estimates of SDP of this segments may be prepared separately for rural and urban areas for the benchmark year using NSS results. For other years the SDP of this segment may be apportioned to rural and urban areas in proportion to the benchmark estimates. These estimates may then be allocated to the districts using the district-wise number of dwellings

Public Administration

In the case of central government administration, data on central government employees are being collected by the Directorate General of Employment and Training (DGET). Efforts may be made to collect similar data at the district level to allocate the state totals. Alternately till such time these data are collected state total may be allocated in proportion to district-wise work force as most of these employees will be located at the state headquarters. In the case of state government employees data on salaries and wages at the district level may be collected from concerned departments to allocate the state total. For local bodies district wise data may be collected from local bodies and used

Other Services

Education, Research and Scientific Services - Recognised Institutions

Data on salaries and wages of teaching and non-teaching staff are being compiled by the state education departments for recognized institutions, universities etc. in connection with their publication Education in States by aggregating the data at the district level. These data should be collected and may be used to allocate state totals to districts.

Education, Research and Scientific Services - Unrecognised Institutions

For this activity the district wise estimates may be prepared using the procedure used for private mechanised road transport. Instead of public sector the work force for the recognised institutions may be subtracted from the total work force for education to derive the work force for the unrecognised institutions.

Medical and Health Services-Public Sector

Data on salaries and wages may be collected from the concerned units within the district and used to allocate State level estimates to districts.

Medical and Health Services-Private Sector

District-wise estimates may be prepared using the same procedure as for the mechanized road transport.

Legal Services

District-wise estimates may be prepared using the same procedure as for the non-mechanized road transport.

Sanitary Services

District wise data (Rural/Urban) may be collected from local bodies and used

Rest of Other Services

District-wise estimates may be prepared using the same procedure as for the non-mechanized road transport.

Estimates at Constant Prices

The methodology for working out estimates at constant prices will be more or less the same as that for current prices in the sectors of Agriculture and Animal Husbandry, Forestry and Logging, Fishing, Mining and Quarrying, Manufacturing (unregistered), Construction, Real Estate, Ownership of dwellings and Business services and Trade, Hotels and Restaurants.

In the sectors where estimates are worked out by ‘Production approach’ the current year production may be evaluated on the basis of base year prices to obtain the value of output at base year prices. For the remaining sectors, the District Income estimates at constant prices may be worked out using the state level deflator of current to constant prices. In Mining and Quarrying sector, the district-wise price differentials may be introduced by multiplying the district wise gross value added at current prices by the ratio between the wages of nonagricultural and rural labour for the base year and for current year.

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Issues for Discussion

Income Originating vs. Income Accruing Approach

For capturing the disparity in income and development income accruing to the residents need to be captured. Due to free flow of goods and services across the borders of the districts and the non-availability of net factor income earned by the residents from other districts/states/countries, the income accruing approach was not feasible. Thus the income originating approach is used for compilation of estimates of state income/district income.

Since the district level estimates would be utilized for the purpose of determining the backwardness/development of a district, and as consequence for allocation of resources by the planners and policy makers as well as for construction of a composite index HDI in connection with the Human Development Report, it would be necessary to make necessary adjustments in these estimates in regard to significant flow of income from and to across the territories of typical districts rich in minerals and/or forest resources or where flow of daily commuters (particularly the districts having state capitals or concentration of industrial units), migration of labour, cattle and net factor income from abroad are involved.

Frequency of Estimates

Since the main purpose of the estimates is for their use for planning purposes and also in view of the present availability of data for the unorganized sectors at an interval of five years, it would be sufficient to compile these estimates at an interval of 5 years.

Purchasing Power Parity and HDI

Per capita DDP in real term expressed in purchasing power parity dollars (PPP$) is used for construction of HDI. PPP$ are not available for the states/districts. Use of all India PPP$ is resorted to. The purchasing power of the rupee varies from state to state, district to district and within district in rural and urban areas. Work on the estimation of purchasing power of rupee was initiated for the state of Maharashtra and two other states under the plan schemes during eighties but not much progress was made. If the HDI at the district level has to have some meaning then the studies on purchasing power of the rupee need to taken up.

District Domestic Product and State Domestic Product

The estimates of SDP for the commodity producing sectors are generally built up by aggregating the DDP of all districts by the state DES using data on production, inputs and prices at the district level. However, for the non-commodity producing sectors the SDP is compiled using state level data from public sector/private corporate sector and GVA per worker and work force for the unorganized segments of the economy. For proper synchronization it is necessary that the SDP estimates are aggregated from the DDP estimates for all the sectors. This no doubt requires generation of requisite district-wise data for the noncommodity producing sectors at least to begin with on a quinquennial basis. State DES have to evolve a suitable sampling strategy for the state sample so that from the follow up surveys of economic censuses district-wise estimates could be generated with adequate precision.

Prices

Producer prices prevailing in the primary markets/farm gates for agricultural products/collection centres for forestry products and at the landing centres for the fishery products at the district level are being collected through market surveys. However for many of the products these data are not available. For example in case of Karnataka

‘State level prices are used to value the district production for animal husbandry, forestry and fishing.’

The price data for all products, which are important for a particular district, need to be collected and compiled on a regular basis for use in district income estimates. In this regard it would be necessary for the state income estimation units at the state levels to first draw up specific lists of such products for each of the district before initiation of collection of prices.

Yield Rates

Yield rates for some of the agricultural products are neither available at the state/district levels in the publications on agricultural production. The agricultural departments at the district/state levels are expected to have these yield rates based on eye estimates in their records. These data need to be collected from their records.

Forest Boundaries

The forest circles/divisions/sub-divisions are generally not coterminous with district boundaries. The records of the forest/revenue departments at the division/sub-division/forest range/forest coupe levels will have to be looked into so as to demarcate forest areas within a district. For example in case of Madhya Pradesh the district boundaries are now coterminous with one or more forest divisions

Inputs in Forestry and Fishing

8. Data on inputs for forestry and logging and fishing even at the national/state level are not available. Ratios developed in the past are being used. Suitable studies in this regard need to be initiated.

Manufacturing - Registered

The sampling strategy in operation from ASI 1998–99 provides servicable estimate at the all-India and state levels. The states Assam, Orissa, Rajasthan, Uttar Pradesh and West Bengal, who are participating in the programme of ASI should take steps to augment the size of the sample for the sample (non-census) sector so that by pooling the data from the two samples district-wise estimates are generated. For this purpose, the Industrial Statistics Wing of the CSO and the FOD of the NSSO should extend full cooperation to these states in the selection of the sample, collection of field data and processing of data of pooled samples. Other states, who are not presently participating in the ASI programme and are interested in generating district-wise estimates for the registered manufacturing sector to meet the needs of state HDR, may take steps to create resources for augmenting the size of the central sample for the sample sector of ASI.

Unorganized Segments of Economic Activity

Pooling of central and state samples is a must if the states have to produce district-wise estimates of value added for the unorganized segments different sectors of non-agricultural economy. The state DES and the Data processing Division (DDP) of NSSO need to develop and maintain excellent working relationship. This would help the and state DES to devise efficient identical data processing procedures for the central and state samples so that pooling of the two samples can be undertaken on scientific basis.

Work Force

In case of Karnataka district-wise work force (as per suggested in the joint methodology developed for DDP by DES Karnataka and DES Uttar Pradesh) district-wise work force has been used to allocate state totals to district in respect of firewood, unregistered manufacturing, construction, road transport, real estate ands business services and other services except education, medical and health and sanitation. Thus the DDP of Karnataka and the HDI for the districts constructed on the basis of the same ignore the disparity at the district level and do not reflect the extent of development/under-development of the districts of Karnataka.

The allocation of state domestic product for a particular sector in proportion to work force has the implicit assumption that the value added per worker is the same for all the districts. Such a procedure makes the rich districts less rich and the poor districts less poor. Thus the disparity in income gets reduced and does not reflect the proper picture. As such its use to the extent possible may be avoided.

Rural/Urban Estimates

Till such time the district-wise value added per worker is derived based on the pooled results of central and state samples of NSS for the benchmark years, it is suggested that the estimates of SDP of the unorganised segments may be prepared separately for rural and urban areas for the benchmark years using NSS results. For other years the SDP of these segments may be apportioned to rural and urban areas in proportion to the benchmark estimates. These estimates may then be allocated to the districts using the district-wise workforce. Such a procedure ensures that at least the rural/urban disparity in earnings is taken care of.

Value Added per Worker

As in the case of SDP, for compilation of DDP for a particular year, the district level value added per worker, derived from the pooled results of central and state samples of the bench mark surveys of NSSO for manufacturing - unregistered (56th round), unregistered trade (53rd round) and unorganised segments of various sectors (57th round), will have to be carried forward or backward using appropriate district level price indices.

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References

Central Statistical Organisation (1974). First Report of the Committee on Regional Accounts, New Delhi.

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Central Statistical Organisation (1976). Final Report of the Committee on Regional Accounts, New Delhi.

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Central Statistical Organisation (1988). Report of the Technical Group for Recommending Methodology for Estimation of Income at the District and Rural/Urban Levels, September.

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Central Statistical Organisation. (1996). Methodology for Preparation of Estimates of District Domestic Product, prepared jointly by Directorate of Economics & Statistics, Karnataka and Uttar Pradesh, August.

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Centre for Research and Development (1999). Estimation of Regional Income-Estimate of NDP of Greater Mumbai, published in The Journal of Income and Wealth, Vol. 21, No. 1, January.

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Dr.ViswanathanRenuka (2001). Preparation of Human Development Report for Kanatak, Seminar on Human Development Through National Surveys, NSS Golden Jubilee Celebration, 6–7 April, Pune.

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PrabhuK. Seeta, KumarSuraj (2001). Data Base for Human Development Assessment: Some Key Issues, Seminar on Human Development Through National Surveys, NSS Golden Jubilee Celebration, 6–7, April, Pune.

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KatyalR.P., SadanaM.G., SatyanarayanJ. (2001). Estimates of District Domestic Product, National Workshop on State HDRs and Estimation of District Income and Poverty organized by the Planning Commission and UNDP at Bangalore.

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