The product has been designed to facilitate industrial analysis and research at the micro level. It provides current estimates on crucial industry related information to facilitate better decision making and business planning. This will help in understanding the vast industrial market and the wide differences across districts, states and regions overcoming any sort of constraints imposed by lack of reliable primary data. The series includes measures that will be useful to business planners, policy makers, credit facilitating agencies, banks and financial institutions, traders as well as knowledge seekers and researchers. It enables the investors to prioritize locations at micro level as well as marketers to explore greater opportunities with the help of reliable industry related data across geographic spaces. This product brings out information on production, workforce, number of operational units , value of input and the amount of industrial consumption of various products at all India, state and district levels. It captures both organized and unorganized sector manufacturing activities and provides the aggregate data covering the entire manufacturing activities. The development of this product involves rigorous use of several authentic and reliable data sources in India. These sources include Annual Survey of Industries (ASI), National Sample Survey Organization (NSSO), Economic Census, etc.

1. Indicus Analytics, An Economics Research Firm
Industrial Skyline of India, 2008-09
Methodology
The product has been designed to facilitate industrial analysis and research at the micro
level. It provides current estimates on crucial industry related information to facilitate
better decision making and business planning. This will help in understanding the vast
industrial market and the wide differences across districts, states and regions overcoming
any sort of constraints imposed by lack of reliable primary data.
The series includes measures that will be useful to business planners, policy makers, credit
facilitating agencies, banks and financial institutions, traders as well as knowledge seekers
and researchers. It enables the investors to prioritize locations at micro level as well as
marketers to explore greater opportunities with the help of reliable industry related data
across geographic spaces.
This product brings out information on production, workforce, number of operational
units , value of input and the amount of industrial consumption of various products at all
India, state and district levels. It captures both organized and unorganized sector
manufacturing activities and provides the aggregate data covering the entire
manufacturing activities. The development of this product involves rigorous use of
several authentic and reliable data sources in India. These sources include Annual Survey
of Industries (ASI), National Sample Survey Organization (NSSO), Economic Census,
etc.
Production: The production figures include total ex-factory value of products and by-
products manufactured putting together both organized and unorganized manufacturing
sector. Since our objective is to provide information directly related to industrial activities,
we have chosen ‘production’ instead of ‘total output’.
Workforce: We have considered ‘total persons engaged’ as the representative of workforce
engaged in manufacturing activities. This includes employees and all working proprietors
and others who are actively engaged in manufacturing activities. The estimations of
workforce include both organized and unorganized manufacturing activities.
Manufacturing units: To capture the current industrial production scenario, we have
considered number of operational units instead of total units.
Value of Input: This includes total delivered value of raw materials, components,
chemicals, packing materials, stores and construction consumed by an industry
Industrial consumption of products: This data provides information to marketers
regarding consumption of their products for intermediate usage by the same as well as
other industries.
Our estimates have also taken care of the under-reporting over-reporting as well as any
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2. Indicus Analytics, An Economics Research Firm
mis-reporting regarding crucial variables in the core databases used. To overcome this
problem, we have used adjustment factors obtained using different relevant data sources as
well as the calibration method.
We have used the National Industrial Classification (NIC) 2004 three digit level definitions
of the industrial products to maintain parity across several data sources. We have clubbed
two NIC categories (NIC 151 and NIC 154) while reporting the data due to the change in
the definition of the same overtime. Additionally, due to data constraints, we are not
reporting the NIC 233 (Processing of nuclear fuel).
There are many gaps in published and available data, especially when we are attempting to
work at the district level. For smaller districts with lower populations such as those in the
northeastern parts of India or areas such as The Dangs in Gujarat, or the more interior
parts of Jammu and Kashmir, etc. the estimates maybe suggestive. Finally, in order to
maintain the robustness of the estimates, the data has been rounded off and therefore, the
totals will not match the reported numbers.
Industrial Skyline – Estimation Methodology
Annual Survey of Calibrations
Industries Calibrated with data
Organized Sector published by Reserve Bank
6 years time series of India & Central Statistical
Census of 15k- 38k large Organization
industrial units and
sample survey of 26k-
76k small and medium
industrial units organized
sector
Final Estimates
Estimation State level estimates for
NSSO 3 points in time
Model
Organized and District level estimates
unorganized Sector for 2008-09
Two rounds spanning 5
years time series
sample survey 150,000
& 87,00 units from the
unorganized sector
GDP Manufacturing
District Level estimates
from Indicus GDP
Economic Census
estimates over 7 years
Latest Economic census
used.
Census of 8.4 million
manufacturing units
spanning across the
organized & unorganized
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3. Indicus Analytics, An Economics Research Firm
Methodology
The manufacturing sector in India comprises of the large scale manufacturing units, the
registered small scale manufacturing units and the un-registered manufacturing units. These
units are generally classified by the National Industrial Classification System (NIC). We have
followed the NIC 2004 Classification which is based on the international classification ISEC
Rev 3.1
Most of the public data available provide information on only subsets of the manufacturing
sector. While the data published by the ASI only provide information on the registered units,
the NSSO provides information for the un-registered units. These extremely useful and
robust data sources cover the manufacturing sector. However, these are for different points in
time and present their findings in a manner that it is not easy for users to get a comprehensive
picture of the manufacturing sector. Industrial Skyline is an attempt to not only combine
information from these data sources but to update it and also to provide estimates at the
district level.
Data sources:
Annual Survey of Industries (ASI) is as the name suggests a yearly survey cum census of
manufacturing units in India which are registered under Section 2m(i) and 2m (ii) of the
Factories Act 1948 and the Bidi and Cigar Workers (Conditions of Employment) Act, 1966. It
captures a host of characteristics of manufacturing units from inputs, workers to gross value
added. For this exercise we have used data from 2000-01 to 2005-06, with census of
15,000-38,000 large scale industrial units and a sample survey of 26,000-76,000 organized
units.
Survey of unorganized manufacturing (National Sample Survey Organization (NSSO)) is a
survey of the unorganized manufacturing units in India. This survey is conducted once in five
years. For this exercise we have used the data for NSS 56th (1999-2000) and 62nd (2005-06)
rounds with sample size 1.5 lakh and 83,000 enterprises, respectively.
Economic Census 2005: A census of all establishments undertaking economic activities is
conducted by the Ministry of Statistics and Programme Implementation in collaboration with
the various state governments. For this exercise we have used the economic census conducted
in 2005.
Reserve Bank of India: Data of schedule commercial bank credit and deposits to the
manufacturing sector from the RBI has been used. For this exercise we have used the data
from 1999-00 to 2007-08.
Central Statistical Organization: The Central Statistical Organization (CSO) provides annual
estimates of the GDP - Manufacturing Sector for All India as well as State level. For this
exercise we have used the GDP for the period 1999-00 to 2007-08. Additionally, we have also
used the latest I-O (Input-Output) matrix for 2003-04 published by the CSO.
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4. Indicus Analytics, An Economics Research Firm
Methodology
The basic methodology was to combine the estimates from the organized and unorganized
sectors. The following function denotes the theoretical concept.
(P)NIC = (Po) NIC + (Pu) NIC
(P)NIC = Total Production for the given industry as per NIC
(Po) NIC = Organized sector Production for the given industry as per NIC
(Pu) NIC = Unorganized sector Production for the given industry as per NIC
However, the data was not available for all the years for both the sectors. Also the latest data
was available for on 2005-06. Thus two steps were required. First to estimate the data for all
the years at the state level for various NIC and second to estimate it for the recent year. A
function of the following form was estimated for the organized and unorganized sector
separately.
(Pij)NIC = fn (GDP, (Lij) NIC , (Xij) NIC, KNIC , (Aij) NIC )
(P)NIC = Ʃij(Yij)NIC
(Pij)NIC = Production of the industry as per NIC
GDP = Manufacturing Sector GDP
(Lij) NIC = Labour employed by the industry as per NIC
(Xij) NIC = Income earned by the labour employed in the industry as per NIC
K = Capital employed
ANIC = A factor for technical efficiency of the industry as per NIC
i = category based on workforce employed
j = category based on production
The relationship established between GDP and production has been used to estimate the
production for various years at the state level and updating of the total production.
Once the production was estimated, the other parameters viz the employment, the number of
units and the input consumed and industrial consumption were determined using a the
following function
(Charij)NIC = fn ((Pij)NIC, (Lij)NIC , (Aij)NIC)
(Char)NIC = Ʃij(Charij)NIC
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5. Indicus Analytics, An Economics Research Firm
Char = Characteristics of the industry (units, input, etc.)
(Pij)NIC = Production of the industry as per NIC
(Lij) NIC = Labour employed by the industry as per NIC
ANIC = A factor for technical efficiency of the industry as per NIC
i = category based on workforce employed
j = category based on production
A similar function was used to determine the production at the district level.
For estimating inter-industrial consumption for various sectors, the latest Input-Output (IO)
matrix published by CSO was used. The actual estimation involved the IO coefficients for
each industry at NIC3 level under the technology assumption.
The inter-industrial consumption estimates in the data involve a basic assumption regarding
the state of technology of the economy. Research studies show that the impact of technology
on the output is very small especially in the manufacturing sector (Sumon Kumar Bhaumik, S.K,
and Kumbhakar S.C, Impact of Reforms on Plant-level Productivity and Technical Efficiency: Evidence from the
Indian Manufacturing Sector).
In order to maintain the robustness of the estimates at such micro level, we have rounded off
the figures to the hundredth place. Therefore, the numbers will not add up to the reported
totals. Also, on the basis of employment, certain industries have been identified to have a
trivial contribution in the total industrial output of the state or district. In such cases, we have
considered the values of production, inputs and units to be relatively insignificant because
these industries will not contribute extensively to the total industrial output in a state or
district. It is an apparent fact that all the industries will not be present in all states & districts.
Consequently, for industries that do not have a presence in certain areas, we have quoted
“NA”.
24th April 2009