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Purpose: Improvement in IIP
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| 1. |
Assessing
the Feasibility of use of Goods and Services Tax (GST) Data in Index of Industrial Production (IIP)
compilation, factory selection, item basket selection for IIP and to enhance the data coverage of
Annual Survey of Industries (ASI), which in turn will help augment the data frame for IIP.
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Purpose: Expanding the coverage of the existing Environment Accounts being compiled by MoSPI
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| 2. |
To estimate the soil erosion prevention
service provided by the Forest Ecosystem
for two States of India.
NSO, MoSPI in collaboration with Soil and
Land Use Survey of India (SLUSI) under Integrated Nutrient Management (INM)
Division of Ministry of Agriculture and
Farmers' Welfare has estimated the soil
erosion prevention services by forests on
a pilot basis for 2 districts of India using
the RUSLE model.
TOR: A study can be conducted to
estimate the soil erosion prevention
service of the Forest Ecosystem at a panIndia level (at a physical level). The study
would explore the following scenarios
which will be carried out for all States of
India.
- Soil Erosion Prevention
Service in different classes
of forests
- Soil Erosion Prevention by
Forests in comparison to
croplands
The specific TORs are as follows:
- To develop a comprehensive
understanding of the soil erosion
prevention services provided by
the forests including the literature
review and its relevance in the
economy
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To estimate the two scenarios- soil
erosion prevention services in
different classes of forests and soil
erosion prevention services
provided by forests in comparison
to the croplands in physical and
monetary terms for a state on a
pilot basis in consultations with the
stakeholders clearly identifying the
data availability.
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To assess the impact of changing
forest patterns on the services
provided by the forest ecosystem.
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To identify the data gaps and
provide recommendations for
improving data collection and
management.
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To compile a report describing the
detailed methodology, data sets,
highlights, limitations and way
forwards.
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| 3. |
Compilation of Ocean Ecosystem
Accounts for a specified region.
Recognizing the significant contribution
of ocean and coastal resources to NSO,
MoSPI initiated the process of
development of Ocean Accounts
Frameworks in alignment to the SEEA. An
Expert Group has also been constituted
for the same. For compilation of the
accounts on the Ocean, it is important to
have relevant data in appropriate
formats.
TOR: The main objective of the study is to
try piloting ocean accounts for a
particular region such as Gulf of Mannar,
Gulf of Kutch etc. The study would
essentially include the condition
parameters for the oceans- ocean
surface temperature. Having knowledge
about the surface temperature of
different ocean ecosystem viz.
mangroves, coral reefs, lagoons etc. the
health about the ocean sub-ecosystem
can be known. The specific TORs for the
study are:
- To develop a comprehensive
understanding of the ocean ecosystems and its subecosystems
- To estimate the ocean surface
temperature of the study area
including the surface
temperatures of the ocean subecosystems in consultations with
the stakeholders clearly identifying
the data availability
- To establish a methodology for
showcasing the impact of
changing ocean dynamics on
ocean surface temperature
- To assess the impact of changing
ocean surface temperature on
various Ecosystems.
- To identify data gaps and provide
recommendations for improving
data collection and management.
- To compile a report describing the
detailed methodology, data sets,
highlights, limitations and way
forwards.
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| 4. |
Carbon Storage in Oceans- To estimate
the carbon stored in different subecosystem of the oceans.
One of the condition parameters for the
oceans is carbon storage in the ocean,
which involves determining how much
carbon is sequestered or stored within
various components of marine
ecosystems. Oceans play a crucial role in
the global carbon cycle by absorbing
significant amounts of carbon dioxide
(CO₂) from the atmosphere. This is
accomplished through biological,
chemical, and physical processes.
TOR: A study can be conducted to
estimate the carbon stored in different
sub-ecosystem of the oceans. The specific
TORs are as follows:
- To develop a comprehensive
understanding of how carbon is
stored in the oceans including the
literature review and its relevance
in the environment and climate
change
- To estimate the carbon retention
in the ocean in both physical and
monetary terms.
- To assess the impact of changing
carbon storage on the health and
services provided by the ocean
ecosystem.
- To identify the data gaps and
provide recommendations for
improving data collection and
management
- To compile a report describing the
detailed methodology, data sets,
highlights, limitations and way
forwards
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| 5. |
Urban ecosystem accounts- Exploring
the compilation of some of the indicators
of urban accounts using satellite
data/geo spatial data.
- Urban ecosystems are cities and
the surrounding, socio-ecological
systems where most people live.
Urbanisation has significant
pressure on natural ecosystems
which has triggered the need for
innovative actions, research and
policies to face existing and emergent societal challenges such
as climate change, biodiversity loss
and environmental pollution.
- Urban ecosystem accounting has
been identified as one of the
priority areas in the "Strategy for
Environmental Economic Accounts
in India 2022-2026”. Urban
ecosystem accounts are
frameworks used to quantify and
track the flow of resources and the
state of urban ecosystems, In line
with strategy document SSD is
initiating the work of development
of urban ecosystem accounts.
- For compilation of accounts
related to urban, Satellite
data/geo spatial data plays a
crucial role in urban ecosystem
accounts by providing a
comprehensive, accurate, and
scalable way to monitor and
assess various environmental and
socio-economic aspects of urban
area.
TOR: A study may be conducted for
exploring the compilation of some of the
indicators of urban accounts using
satellite data/geo spatial data. This may
include checking of data availability,
suggesting other indicators as per the
spatial data availability, alternate data
source related to following indicative
components:
- Disaggregation the entire urban
area and categorizes larger
patches with common characteristics. For example, a
classification of urban sub- types
could break down the variety of
built-up and semi-natural types
within the city into contiguous
areas with common shared
characteristics (e.g., compact
high-rise, compact low-rise,
open low-rise, sparsely built,
paved, semi-natural area,
natural area).
- Identification & Data collection
on individual asset types of
urban area at as fine a scale as
possible (e.g., lines of street
trees, playgrounds, allotment
gardens, green roofs, drainage
and storage systems, etc.) based
on available very high resolution
(10 m or less) satellite imagery or
other spatial data sets
- Following the disaggregation of
urban area, Identification and
collection of information on
condition characteristics of
urban area (e.g., percentage of
impervious/pervious surfaces,
air quality, water quality, soil
contaminant concentrations) as
measures of landscape-level
characteristics of these subclasses.
- Quantifying ecosystem service in
terms of volume and money
value: Identification of urban
ecosystem services and checking
of availability of data for these
ecosystem services, such as air
purification, water regulation,carbon sequestration
temperature moderation, and
recreation, provided by urban
ecosystems.
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| 6. |
Strengthening of National Indicator
Framework (NIF) for SDGs by
- Identification of the SDG national
indicators for the unaddressed
targets
- Adaptation of SDG global
indicators in Indian Context
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| 7. |
Use of Mobile data for Tourism statistics
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| 8. |
Use of Remote Sensing for estimation of
cattle population
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| 9. |
Use of night light data for estimating
economic development/ infrastructure
development/ impact on job creation.
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| 10. |
The measurement of depletion of
natural sources and hence adjustment of
Gross Domestic Product (GDP) to arrive
at Net domestic Product (NDP).
As per the recommendation of United
Nations Statistical Commission (UNSC),
emphasis will be given on usage of NDP
to measure the economic growth
alongside the GDP. The gross domestic
product will be adjusted for both
consumption of fixed capital and
depletion of natural sources.
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| 11. |
Preparation of distribution accounts in
terms of distribution of households over
income and wealth using the existing
survey results of NSSO and National
Accounts Statistics.
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| 12. |
Exploring feasibility of use of data base
created by researchers for evidencebased decision making in government.
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| 13. |
Time series analysis of the Data on
National Income estimates since 1950-
51.
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| 14. |
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| 15. |
Cross-referencing the CPI estimates with
Wholesales market Price
It may also be explored that to what
extent do wholesale market price
changes explain variations in the CPI
when controlling for external factors
such as supply chain disruptions, taxes,
and commodity price volatility.
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| 16. |
Land Inflation - A methodology for
compilation of land index, collection of
data, design of survey and its possibility
in Indian context may be developed.
The CPI is meant to reflect the cost of
maintaining a certain standard of living
for consumers. Since land price increases
significantly affect housing affordability
and, by extension, the overall cost of
living, including land inflation in the CPI
could provide a more accurate measure
of how rising costs impact households
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Purpose: Price collection from e-commerce platforms for International Comparison
Programme
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| 17. |
Use of Scanner data for CPI and HCES
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Purpose: Surveys
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| 18. |
Exploring alternative criteria for
stratification used in sampling designs of
the surveys of NSSO
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| 19. |
Study on the divergence in population
estimates arising from the Census and
NSS Survey.
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| 20. |
Simplification of extraction of unit level
data of different surveys of MoSPI.
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Purpose: Alternative Data Sources
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| 21. |
Identification of Avenues for Harnessing
Administrative Data.
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| 22. |
Triangulation of Various New Data
Sources viz. GST, E-commerce Sales Data,
etc., with Conventional Data Sources.
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| 23. |
To access the value of official statistics in
terms of the financial savings they
generate.
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| 24. |
Bifurcation of B2C transactions in
- Transaction with Consumer
households; and
- Transactions with non-registered
suppliers from GST data
and further devising a method to further
bifurcate this transaction item-wise (as
required for PFCE compilation)
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