System of Collection of Agricultural Statistics in India Including Land Use and Area Statistics
System of Collection of Agricultural Statistics in India Including Land Use and Area Statistics
System of Collection of Agricultural Statistics in India Including Land Use and Area Statistics
INTRODUCTION
India predominantly is an agrarian economy both from the point of view of employment as
well as contribution to the national income. Availability of reliable and timely crop estimates
is hence of paramount importance to the planners, administrators, policy makers and research
scholars. The Government depends on these data in taking a number of policy decisions
regarding pricing, processing, procurement, storage, transport, marketing, export/import,
public distribution and many other issues like investment planning. The system of generating
annual estimates of area, yield and production of crops in India is more than a century old. A
constant evaluation of the mechanism for generation of timely and reliable agricultural
production statistics, therefore, assumes vital importance and significance. The Directorate of
Economics and Statistics (DES) releases estimates of area, production and yield in respect of
51 principal crops of food grains, oilseeds, sugarcane, fibers and important commercial and
horticulture crops. These crops together accounts for nearly 87% of agriculture output.
The organization of this lecture note is as follows. Section 1 presents the system of release of
Advance and Final Estimates of area, production and yield by the DES on the basis of reports
received from State Agricultural Statistics Authorities (SASAs) Section 2 gives a bird eyeview of area statistics. Section 3 deals with various aspects of yield estimates namely extent
of coverage, sampling design and degree of precision of estimates. Under Section 4, some of
important limitations of CES (Crop Estimation Surveys) are discussed. Section 5 gives an
account of the schemes launched to fine tune crop statistics. Finally, section 6 presents the
conclusion.
1.1
The period of an agricultural crop year is from July to June, during which various farm
operations from preparation of seed bed, nursery, sowing, transplanting various inter-culture
operations, harvesting, threshing etc. are carried out. Different crops are grown during the
agricultural seasons in the crop year. Final estimates of production based on complete
enumeration of area and yield through crop cutting experiments become available much after
the crops are actually harvested. However, the Government requires advance estimates of
production for taking various policy decisions relating to pricing, marketing, export/import,
distribution, etc. Considering the genuine requirement of crop estimates much before the
crops are harvested for various policy purposes, a time schedule of releasing the advance
estimates has been evolved. These estimates of crops are prepared and released at four points
of time during a year as enumerated below:
1.2
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The second advance estimate is made in the month of January every year when the advance
estimates of kharif crops prepared during the National Conference of Agriculture for Rabi
Campaign may undergo a revision in the light of flow of more precise information from the
State Governments. Around this time, the first advance estimates of rabi crops are also
prepared. The Second Advance Estimates then cover the second assessment in respect of
Kharif Crops and the first assessment in respect of Rabi Crops.
1.4
The third advance estimates are prepared towards the end of March/ beginning of April every
year, when the National Conference on Agriculture for Kharif campaign is convened and the
State Governments come up with their assessments for both kharif and rabi crops. The earlier
advance estimates of both kharif and rabi seasons are firmed up/ validated with the
information available with State Agricultural Statistics Authorities (SASAs), remote sensing
data, available with Space Application Centre, Ahmedabad as well as the proceedings of
CWWG.
1.5
The fourth advance estimates are prepared in the month of June/July every year, when the
National Workshop on Improvement of Agricultural Statistics is held. Since most of the rabi
crops get harvested by the end of May, SASAs are in a position to supply the estimates of
both kharif and rabi seasons as well as likely assessment of summer crops during the National
Workshop. Like the third advance estimates, the fourth advance estimates are duly validated
with the information available from other sources.
1.6
Final Estimates
Under the existing system of crop estimation, the fourth advance estimate is followed by final
estimates in December / January of the following agricultural year. The main factors
contributing to the relatively large number of crop estimates are the large variations in crop
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AREA STATISTICS
From the point of view of collection of area statistics, the States in the country are divided
into three broad categories:(i)
States and U.Ts which has been cadastrally surveyed and where area and land use
statistics are built up as part of the land records maintained by the revenue agencies
(referred to as Land Record States or temporarily settled states). The system of
land record is being followed in 13 major states and 4 UTs of Chandigarh, Delhi,
Dadar & Nagar Haveli and Pondicherry. These states/UTs account for about 86% of
reporting area.
(ii)
The states where area statistics are collected on the basis of sample surveys (normally
known as non-land record states or Permanently Settled States which are three in
number viz. Kerala, Orissa and West Bengal). A scheme for Establishment of
Agency for Reporting of Agricultural Statistics (EARAS) has been introduced in
these three states which envisages, inter-alia, either the estimation of areas by
complete enumeration or through sample surveys in a sufficiently large sample of
20% villages/ investigators zones. These states accounts for about 9% of reporting
area.
(iii)
In hilly districts of Assam, the rest of the states in North-Eastern Region, Sikkim,
Goa, UTs of Andaman & Nicobar Islands, Daman & Diu and Lakshadweep where no
reporting agency had been functioning, the work of collection of Agricultural
Statistics is entrusted with the village headmen (5%).
While the area statistics are collected on complete enumeration basis in respect of states in
category (i) above, on ad-hoc methods based on impressionistic approach in case of states in
category (iii) above, a scheme for Establishment of Agency for Reporting of Agricultural
Statistics (EARAS) has been introduced in the three states in category (ii) above. For further
details of EARAS section 6.3 may be referred to.
3. YIELD ESTIMATES
The second most important component of production statistics is yield rates. The yield
estimates of major crops are obtained through analysis of scientifically designed crop cutting
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Coverage
A total of 68 crops comprising 52 food crops and 16 non-food crops were covered under CES
during 2004-05 as per details given in table 1.
Table 1: Crops Covered under CES
Type of Crop
Percentage
487493
71.0
11
7
10
16
2
52
129898
3336
9798
33876
21985
686386
18.9
0.5
1.4
4.9
3.2
84.1
11
103787
79.9
Fibres
Drugs and Narcotics
Sub-Total (B) :
Grand Total (A) + (B)
3
2
16
68
24560
1582
129929
816315
18.9
1.2
15.9
100.0
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Sampling Design
Stratified multi-stage random sampling design is generally adopted for carrying out CES with
tehsils/taluks/revenue inspector circles/CD blocks anchals etc. as strata, revenue villages
within a stratum as first stage units of sampling, survey numbers/ fileds within each selected
villages as sampling units at the second stage and experimental plot of a specified shape and
size as the ultimate unit of sampling. In each selected primary unit generally 2 survey
numbers/fields growing the experimental crop are selected for conducting CCE.
In a bid to improve efficiency of estimates, pre-stratification of design taking into account the
impact of irrigation and type of seeds was adopted during 2004-05 in some states namely
A.P., Bihar, Chhattisgarh, Gujarat, Jharkhand, Karnataka, M.P., Maharashtra, Rajasthan and
Tamil Nadu. The details of such stratification are given in the table 2.
Table 2: Stratification According to Inputs
State
1
Andhra Pradesh
Bihar
Chhattisgarh
Gujarat
Karnataka
Jharkhand
Karnataka
Madhya
Pradesh
Maharashtra
Rajasthan
Tamil Nadu
*
@
**
Lack of availability of required data in the presently available system of area statistics at
different level; and
3.3
Degree of Precision
The magnitude of standard error reflects the precision of the estimates and the degree of
precision reduced with increase in the standard error. It is generally agreed that desirable
level of standard error (SE) for crop yields is 0% to 5% . However, the experience shows that
in good number of cases, S.Es are above the desirable limits in some of states like Andhra
Pradesh, Bihar, Chhattisgarh, Gujarat, Karnataka, Kerala, Madhya Pradesh, Maharashtra,
Orissa, Rajasthan and West Bengal which put a question mark on the reliability of the
estimates. Concerted efforts are required on the part of State Governments by increasing
sample size and supervision to ensure that the SEs do not exceed 5%.
4. LIMITATIONS OF CES
CES have been quite useful in providing desired estimates. However, it has the following
important limitations:
Non response
Errors in CCE
Substitution of experiments
Non response
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Errors in CCE
An analysis of the results of CCE through the sample check under ICS few years before
revealed that about 90% of experiments could be conducted without error at All India level.
However the position is quite different once State-wise analysis is made. Table 3 indicates
the position of different types of errors observed during the conduct of CCE in kharif season.
Table 3: Incidence of Errors in Crop Cutting Experiments
Sl.no.
1
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
States
2
Andhra Pradesh
Assam
Bihar
Gujarat
Haryana
Himachal
Pradesh
Jammu
&Kashmir
Karnataka
Kerala
Madhya Pradesh
Maharashtra
Orissa
Punjab
Rajasthan
Tamil Nadu
U.P.
West Bengal
Delhi
Pondicherry
% of expts.
Where no
error was
noticed
3
85
94
92
92
90
68
E2
E3
E4
E5
E6
E7
E8
4
0
0
0
0
2
3
5
0
0
0
0
1
1
6
1
0
0
0
1
0
7
0
0
0
0
5
4
8
1
0
0
0
0
2
9
7
0
4
9
17
14
10
4
0
0
0
2
3
11
5
6
4
0
3
10
75
15
79
99
90
44
96
92
76
75
53
100
55
100
1
0
0
5
0
0
0
0
2
0
0
0
2
0
0
4
0
0
0
0
1
0
0
0
0
0
0
2
0
1
2
3
1
0
0
0
11
0
0
36
0
0
0
0
13
0
0
0
1
0
1
4
0
0
0
0
2
0
0
0
1
1
2
37
1
4
29
28
15
0
20
0
5
0
4
15
0
0
0
0
10
0
0
0
8
1
2
15
3
5
1
2
16
0
35
0
Note: E1: Error in selection of Survey /Sub survey nos., E2: Error in selection of field
within Survey /Sub-survey No., E3: Error in the measurement of the field, E4: Error in
selection of random nos., location and marking of plots, E5: Error in weighment of
produce, E6: Error in recording ancillary information, E7: Inadequate arrangements for
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Substitution of Experiments
Instructions for conduct of CES prohibit substitution of sampling units once selected. But
instances of substitution of sampling units at village and field level are observed. During
1996-97, incidences relating to substitution was around 5% in Bihar, Karnataka and Madhya
Pradesh. In majority of the cases, the fields were substituted either because the crop was
harvested prior to selection of the field or crop harvested before the date fixed. Substitution of
duly selected sampling units by any other convenient unit may result in distorted results.
Better liaison between the primary workers and the cultivators would go a long way to
control such high incidence of substitution.
4.4 Delegation to Junior Officials
The field work of crop estimation surveys is entrusted with the officials who are normally
one rank higher than the primary worker for area enumeration. Delegation of crop cutting
work particularity to the junior rank has been observed in several states. For example, the
delegation of work was of the order of 10% in case of U.P. during summer 1996-97.
Adequate arrangements are needed for ensuring proper training to the field workers entrusted
with CES to avoid improper conduct of crop cutting experiments.
4.5
While an untrained worker cannot conduct the experiment properly, supply of essential
equipments and its proper use is required for accuracy in measurements. The position is far
from satisfactory particularly in the case of Bihar, Haryana, Himachal Pradesh, J&K,
Karnataka, Maharastra, Punjab, Rajasthan and UP. Even the supplied equipments were
reported to have not been carried to the field for the conduct of CCE in many cases in
Karnataka, M.P., Maharastra, Rajasthan and U.P. This calls for strong administrative
measures for effecting further improvement. Table 4 gives the percentage of experiments
conducted without use/ improper use of crop cutting equipments during 5 years preceding
1997-98 as observed through ICS.
Table 4: Supply and Use of Equipments for CCE During the Last Five Years
Year
1
1997-98
1996-97
1995-96
1994-95
1993-94
TRS
ICS
EARAS
FASAL
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Studying the State system of crop estimation in its normal operative conditions.
136
Checking the accuracy of the area statistics transmitted from the village level through
crop abstract in the very same 10,000 villages.
Providing technical guidance and supervision at the harvest stage in the conduct of about
30,000 CCE distributed across principal crops in various states.
The above checks specifically relate to crop area enumeration, page totaling of khasra register
and supervision of harvest stage of CCE. The sample checks are undertaken by the
supervisory staff of the National Sample Survey Organization and the staff of the State
agencies on a matching basis over a non-overlapping sample. The samples for this purpose
are drawn following the stratified multistage random sampling design.
The analytical findings of the ICS scheme bring to focus the precise lines along which the
improvement in the system of crop statistics system could be effected in context of the
conditions prevailing in each State. The survey operations for generating crop area and yield
estimates are expanded vastly over the space and involve multiple agencies at various levels.
Though these surveys provide the estimates of comparable nature, the management of the
survey and control of survey operations differ significantly from sate to state. The surveys of
such magnitude face a potential threat to the quality of their output from numerous sources of
non-sampling errors. The scheme of ICS serves the purpose of an objective assessment of
non-sampling errors in these surveys and identifies their sources as well as the possible
impact on the quality of data.
5.3 Establishment of an Agency for Reporting Agricultural Statistics
In three permanently settled states namely Kerala, Orissa and West Bengal, there is no land
record system and there is no regular agency for collection of agricultural statistics. In order
to bridge data gap, a scheme namely Establishment of an Agency for Reporting Agricultural
Statistics (EARAS) is being implemented in States which do not have permanent land record
system. In the north-eastern States (except Assam) where no reporting agency functions, the
land use statistics are generated through ad-hoc methods. EARAS scheme has been extended
to NE States of Arunachal Pradesh, Nagaland and Tripura besides Sikkim during 1994-95
but data generation is yet to commence. In these states, the land use statistics are still
generated through ad-hoc methods. However, the scheme of EARAS has been of immense
significance in generating crop estimates for the permanently settled states.
Under the scheme, estimates of area and yield are built on the basis of complete enumeration
of 20% sample of villages every year. The enumeration is supervised by trained staff of
NSSO. This scheme also has some weaknesses as primary workers either do not complete
work in time or do not discharge duties with required sincerity which results in under
estimation of area and production of various crops.
5.4 Crop Estimation Surveys for Fruits and Vegetables
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Experience and recent studies outside India for RS-based crop assessment/ forecasting,
Use of other information such as weather based and field surveys for crop forecasting.
The concept of FASAL thus seeks to strengthen the current capabilities of early and in-season
crop estimation capabilities from econometric and weather based techniques with RS
applications. Mid-season assessments can be supplemented with multi-temporal coarse
resolution data based analysis. In the latter half of crop growth period, direct contribution of
RS in the form of acreage estimates and yield forecasts would be available. However, in this
case also, the addition of more extensive field information and weather inputs would increase
the forecast accuracy.
6. CONCLUSION
Given the diversities prevailing in the domain and dimension of agrarian economy of India,
timely collection of agricultural statistics has been of immense use in estimating agriculture
production in the country. Some of limitations of crop estimation surveys lead to lack of
precision which in turn results in distortion of estimates. The Ministry of Agriculture, in any
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