Growth Trends and Determinants of Crop Area Responsiveness in Haryana

Abstract

The study has been done on the determinants of accountability of 6 major crops of the State of Haryana from the year 1980-2018. These major crops have been selected as they cover about 85% of the gross cropped area of the state. It has been observed that the two crops, wheat and paddy, have been growing in rotation as the main crop during this period. The study has validated the results of Narlovion model of area responsiveness. It has been identified that the lagged area, lagged price, and the volatility in price and yield shows the main determinants of area allocation. Furthermore, the study shows the growth trends of area, production and yield of wheat and paddy crop has been positive due to stability in yield, price and insured marketing. The promotion of a more diversified cropping pattern has a prequest condition for the state to achieve sustainable growth. But farmers will not move towards diversification unless they are encouraged by economically attractive alternatives.
Keywords: Agriculture, growth trend, acreage response, price risk, yield risk, area effect, yield effect

Full text

How to cite this article: Singh, J., Singh, J., Singh, N. and Kapoor, S.
(2021). Growth Trends and Determinants of Crop Area Responsiveness
in Haryana. Agro Economist - An International Journal, 08(01): 15-21.
Source of Support: None; Conflict of Interest: None
Agro Economist - An International Journal
Citation: AE: 8(01): 15-21, June 2021
DOI: 10.30954/2394-8159.01.2021.3
Growth Trends and Determinants of Crop Area
Responsiveness in Haryana
Jaspal Singh1*, Jagdeep Singh2, Nirmal Singh3 and Shilpi Kapoor4
1Consultant, NITI Aayog, New Delhi, India
2Assistant Professor, Guru Nanak College, Budhlada, Punjab, India
3Barkatullah University, Bhopal, Madhya Pradesh, India
4Lovely Professional University, Phagwara, Punjab, India
*Corresponding author: jaspal.singh82@nic.in
Received: 24-03-2021 Revised: 29-05-2021 Accepted: 14-06-2021
ABSTRACT
The study has been done on the determinants of accountability of 6 major crops of the State of Haryana from the
year 1980-2018. These major crops have been selected as they cover about 85% of the gross cropped area of the
state. It has been observed that the two crops, wheat and paddy, have been growing in rotation as the main crop
during this period. The study has validated the results of Narlovion model of area responsiveness. It has been
identied that the lagged area, lagged price, and the volatility in price and yield shows the main determinants of
area allocation. Furthermore, the study shows the growth trends of area, production and yield of wheat and paddy
crop has been positive due to stability in yield, price and insured marketing. The promotion of a more diversied
cropping pattern has a prequest condition for the state to achieve sustainable growth. But farmers will not move
towards diversication unless they are encouraged by economically attractive alternatives.
Keywords: Agriculture, growth trend, acreage response, price risk, yield risk, area effect, yield effect
Agriculture sector is dominant sector in Indian
economy which has contribution of 44.14 per of the
workforce employed (PLFS, 2019) and this sector
contributes 17.2 per cent to the country’s gross value
added (NAS, 2019). At the time of independence,
the country was not able to produce enough food
for the population. With the number of steps taken
by the government, the country adopted the Green
Revolution in 1965-66 which resulted in the dramatic
increase in agricultural production and productivity
(Singh et al. 2013). But the growth rate of agricultural
production and productivity is not same in all the
states (Dreze et al. 2006; Singh and Kaur, 2018; Singh
et al. 2018). This has been due to the impact of the
Green Revolution which was limited in those states
where availability of land levelling was smooth &
non-sloppy, existence of high fertility, chances of
availability of articial irrigation facilities, and the
tendency of farmers to the adoption of new farming
techniques. The impact of Green Revolution on
agricultural production has been conned in Punjab,
Haryana, and some parts of Uttar Pradesh.
Another aspect of this inter-regional disparity in
growth performance is seen among crops. Because
the existing mode of production was born from food
shortage, the priority of government, policymakers,
researchers and agricultural scientist was to fulll

Singh et al.
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the food demand of the nation. Consequently,
research focused on a few geographical areas and
selected crops. Therefore, wheat and paddy crops
became the centre pivot of research. As a result, the
area, production, and productivity of these crops
increased over time. Due to the natural advantage
of resources endowment, the responses of the new
agricultural technology have been very impressive
in Punjab, Haryana and western Uttar Pradesh.
Haryana is the state where the successful impact
of the Green Revolution has been recorded and the
performance of the agriculture sector has shown
impressive improvement. Haryana state achieved
high growth in production and productivity of food
crops during the green revolution era with the grace
of natural resource endowment especially articial
irrigation facilities and plain land.
Haryana has been a predominantly agrarian economy
and this sector contributes 19.2 per cent to the state’s
gross income with 27.41 per cent of employment
(Singh et al. 2020). The state plays its role as a slight
bigger state; slight in terms of an occupied area which
is mere about 1.4 percent of the total geographical
area of the country (DES, 2019); bigger in terms of
contribution of wheat which is about 27 per cent and
rice about 8.2 per cent of the centre pool. In Haryana,
the area under wheat and paddy has increased in
recent times and the area under other crops has
decreased. It is important to understand the growth
trends and different factors of crop responsiveness
in Haryana. The state, like Punjab, has been under
a tendency of cropping pattern following towards
mono-cropping (Singh & Singh, 2018). This paper
explores the growth performance of the agriculture
sector in Haryana and the factors identifying the
responding area allocation.
According to Narlovion model, factors like yield risk
and price risk have a negative effect; on the other
hand lagged area, yield and farm harvest price have
a positive effect on area allocation. The present study
revisits area allocation debate in six major crops
(wheat, paddy, bajra, rapeseed and mustard, cotton
and gram) cultivation in Haryana state. The paper
examines the growth performance of these crops with
respect to area, production and yield in Haryana.
The study, furthermore, decomposes the change
in production in area, yield and interaction effects.
Furthermore, the factors responsible for increasing
area under some crops have been identied.
MATERIALS AND METHODS
The study is based on the secondary data collected
for the period of 1980-81 to 2018-19 of Haryana state.
For this 6 major crops have been studied. Three major
crops (Paddy, Bajra, and Cotton) have been selected
for the Kharif season and similarly for the Rabi season,
three major crops (Wheat, Gram, and Rapeseed &
mustard) have been selected. These major crops
cover 85% of the total cropped area. We compiled
data on area, production and yield of selected
crops. For this, various statistics have been obtained
from published sources like Statistical Abstract of
Haryana, Economics and Statistics Director (DES of
Haryana State); Area, Production and Yield Statistics,
Directorate of economics and statistics India; cost of
cultivation data of Haryana state for estimating farm
harvest prices. The study period has been divided
into two parts viz., period-I 1982-83 to 2002-2003,
period-II 2002-2003 to 2017-18.
Fig. 1: Map of Study area
Area of study has been highlighted in Fig. 1. The
Haryana state is located in the north-west part of
the county. Haryana bifurcated from Punjab state
in 1966, now it occupied about 1.34 per cent (about
4421 thousand hectors) of the total geographical area
of the nation.
Growth Rate Analysis
The compound growth rate of area, production and
yield for selected crops are estimated for selected
periods of time. The crop-wise compound growth
rates are estimated to study the growth with the
following exponential model.

Growth Trends and Determinants of Crop Area Responsiveness in Haryana
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Y = abt
Log Y = log a + t log b (by taking the log of both sides)
CGR = (Antilog b – 1) × 100
Where,
t = time period in year
Y = area/production/productivity
a & b = Regression parameters and
CGR = Compound growth rate.
Instability Analysis
To measure the instability in area, production and
productivity, coefcient of variation (CV) has been
used as a measure of variability. The CV is calculated
by the following formula;
100CV
Mean
σ
=×
where
CV is stated as coefcient of variation and σ stands
for standard deviation (SD)
Decomposition of change in production
The Component Analysis Model has been used
to calculate the relative contribution of area and
productivity in the total output changes for cotton,
bajra, wheat, paddy, rapeseed & mustard and gram
crops as used by other scholars (Minhas, 1964;
Minhas, 1965; Sharma, 1977; Shende et al. 2011;
Kalamkar et al. 2002; Singh, et al. 2018). The method
states that if A0, P0 and Y0 are respectively area,
production and productivity in base year and An,
Pn and Yn are values of the respective variables in
nth year then
∆P = A0 ∆Y + Y0 ∆A + ∆Y∆A
The first, second and third terms of the above
equation represent productivity, area and interaction
effect respectively. Hence is usual difference operator
showing change is
ΔA = An−A0; ΔY = Yn−Y0; and ΔP = Pn − P0
Area Responsiveness Analysis
To examine the area responsiveness, Nerlovian
lagged adjustment model (1958) has been applied in
the study. The area responsiveness means the change
in acreage due to the unit change in the variables
under consideration during the period of study. The
area responsiveness function has been tted for the
state of Haryana. The general specication of the
model is given below:
Areat = α + β1 Areat–1 + β2 Pricet–1 + β3 Yieldt–1 + β4
Pricerisk + β5 Yieldrisk + Trend + μt
where,
Areat = Area under crop at t time
Areat-1 = Area under crop at t-1th time
Yieldt-1 = Lag yield crop at t-1th time
Yieldrisk = Yield volatility in last three year
Pricerisk = Price volatility in last three year
α, β1 to β5 are regression coefcients and μ is random
error term.
RESULTS AND DISCUSSION
Adoption of new agricultural technology during mid-
1960s in India has shown the growth of foodgrain
production which has been very impressive. The
changes are well known as the Green revolution of
India. But the responsiveness of these technological
changes has been recorded only in wheat and paddy
crop. As a result, the area and production of these
crops increased over time. In table 1, the changes
in the cropping patterns are depicted. The biggest
change in per cent area cultivation during 1980-81
to 2017-18 has been estimated in paddy crop which
increased from 8.6 per cent to 21.7 per cent. The area
under cotton, wheat, rapeseed & mustard crops has
increased in the state but the area under bajra, gram
and other crops has decreased.
Bajra, which occupied about 16.1 per cent of the gross
cropped area of that state has been found to be the
main kharif crop during 1980-81 in Haryana. But, the
tendency of the area allocation to this crop has been
decreasing. Area under paddy and wheat has been
35.7 percent during 1980-81 which increased to 59
percent in 2017-2018. The reason behind the increase
in area under these crops is insured marketing,

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insured prices (through implementation of MSP) and
stable yield of the crop. But in areas where irrigation
facilities are lacking, like that of cotton crop has
increased. This is because the cotton crop needs lesser
irrigation. Secondly, the crop has been available to
the farmers at a fairly reasonable price. The reason
for the decline in area under Bajra and Gram crops
has been price uncertainty and market uncertainty.
The growth rate in area, production and yield of
selected crops is presented in Table 2. During kharif
season, area increased by 3.06 per cent, 1.41 per
cent, and -1.39 per cent of paddy, cotton and bajra
respectively between 1980-81 and 2017-18. The
highest growth rate of area under production of
paddy has been estimated to be 5.76 per cent and
4.33 per cent per annum during 1990-91 to 2000-01.
Area under cotton crop had increased by 3.85 per
cent during 1980-81 to 1990-91. The production of
cotton grows by 5.47 per cent during this period,
while the area under cultivation declined in the next
Table 1: Changing cropping pattern in Haryana over the time
Crop Percentage change in Area Under Different Crops
1980-81 1990-91 2000-01 2010-11 2017-18
Paddy 8.6 11.2 17.2 19.1 21.7
Cotton 5.8 8.3 9.1 7.6 10.2
Bajra 16.1 10.3 9.9 10.2 6.9
Wheat 27.1 31.3 38.5 38.7 37.3
Gram 13.6 11.0 2.0 1.7 0.5
R & M 5.5 8.0 6.6 7.7 8.4
Other crops 23.3 20.0 16.6 15.0 15.1
Gross cropped area (000 ha) 5462 5919 6115 6505 6549
Source: Authors’ estimation using Agricultural Statistics at a glance, DES (Various issues).
Table 2: Growth rates of area, production and yield of selected crops in Haryana
Crop Particular 1980-81 to 1990-91 1990-91 to 2000-01 2000-01 to 2010-11 2010-11 to 2017-18 1980-81 to 2017-18
Kharif
Paddy Area 2.71 5.76 2.26 2.26 3.06
Production 3.04 4.33 3.61 3.42 3.78
Yield 0.31 -1.36 1.32 1.13 0.70
Cotton Area 3.85 1.44 -1.97 2.06 1.41
Production 5.47 -0.51 6.86 -5.31 3.14
Yield 1.56 -1.92 9.01 -7.23 1.71
Bajra Area -3.77 0.23 0.94 -4.65 -1.39
Production -1.60 4.42 6.17 -6.06 2.63
Yield 2.25 4.18 5.17 -1.47 4.08
Rabi
Wheat Area 1.81 2.41 0.95 -0.01 1.41
Production 5.93 4.02 2.00 -1.28 3.10
Yield 4.05 1.58 1.03 -1.27 1.67
Gram Area -4.49 -11.43 -0.48 -14.48 -8.01
Production 0.14 -12.29 0.98 -14.34 -6.69
Yield 4.85 -0.96 1.46 0.17 1.44
R & M Area 8.26 -2.42 -0.13 -0.04 2.10
Production 15.96 -1.92 2.46 1.87 4.50
Yield 7.11 0.52 2.60 1.91 2.36
Source: Authors’ estimation using Agricultural Statistics at a glance, DES (Various issues).

Growth Trends and Determinants of Crop Area Responsiveness in Haryana
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decade which necessitated a decline in production.
However, between 2000-01 and 2010-11, the area of
cotton decreased by 1.97 per cent whereas production
increased by 6.86 per cent per annum which has
been due to high growth rate observed in yield (9.01
per cent) during the same period. Growth rate of
area under Bajra (which was the highest occupied
area share during 1980-81, table 1) was found to be
negative during 1980-81 to 1990-91 and again 2010-11
to 2017-18, and a marginal increase during 1990-91
to 2000-01 and 2000-01 to 2010-11.
The wheat crop has been observed as the main rabi
crop in Haryana due to the staple-food crop of the
state. It occupied about 27 per cent (during 1980s) and
about 37 per cent (during 2020s) of the gross cropped
area. The growth rate of the area, production, and
yield of wheat and rapeseed, and mustard has been
positive in the overall time period (between 1980-
81 and 2017-18). As a result, the area under gram
cultivation has been found to be decreasing during
the study period although the growth rate of yield
is estimated to be positive.
The effect of both area and yield on changes in
production of major crops is presented in Table 3. The
highest change in production in period one has been
in paddy crop in kharif season with 1193 thousand
tonnes and in rabi season wheat production was
changed by 4840.99 thousand tonnes. Paddy crop
production changed 91.14 per cent by area effect.
While the impact of technology has been less, on the
contrary, the effect of acreage on wheat production
estimated as 28.42 and the effect of yield shows 54.37.
Technology for the wheat crop improved during
this time. As a result, production increased. Similar
results can be observed during the second period.
The overall production of paddy had increased by
3248’000 tonnes. The impact of the area effect to
increase this production is 74.89 while the impact
of technology is 8.14. Wheat production increased
by 6418.28 thousand tonnes Technology has been
affected by 50.64 per cent more than the area effect
(28.24) to increase this production. The increase in
production in cotton crop (133.79 thousand tonnes)
is due to increase in area. There is not much impact
of technology in the present case. The reason for the
increase in production in millet crop is due to changes
in technology, because the effect of acreage on the
Table 3: Estimation of area, yield, and interaction effect on production of different crops
Crop Particular Change in production
(in thousand ton)
In percent
Area effect Yield effect Interaction effect
Kharif
Paddy TE 1982-83 to TE 2002-03 1193.00 91.14 4.78 4.08
TE 2002-03 to TE 2017-18 2055.38 68.39 20.14 11.47
TE 1982-83 to TE 2017-18 3248.38 74.89 8.64 16.48
Cotton TE 1982-83 to TE 2002-03 33.66 129.30 -22.46 -6.84
TE 2002-03 to TE 2017-18 100.12 50.01 38.94 11.05
TE 1982-83 to TE 2017-18 133.79 72.06 16.68 11.26
Bajra TE 1982-83 to TE 2002-03 -48.00 360.37 -395.62 135.25
TE 2002-03 to TE 2017-18 262.90 -21.69 139.00 -17.31
TE 1982-83 to TE 2017-18 214.90 -99.79 346.75 -146.96
Rabi
Wheat TE 1982-83 to TE 2002-03 4840.99 28.42 54.37 17.21
TE 2002-03 to TE 2017-18 1577.29 44.45 51.61 3.94
TE 1982-83 to TE 2017-18 6418.28 28.24 50.64 21.12
Gram TE 1982-83 to TE 2002-03 -241.00 104.34 -40.12 35.78
TE 2002-03 to TE 2017-18 -5.00 342.92 -417.53 174.60
TE 1982-83 to TE 2017-18 -246.00 107.41 -117.68 110.27
R & M TE 1982-83 to TE 2002-03 586.00 50.74 13.39 35.87
TE 2002-03 to TE 2017-18 410.88 -16.21 128.49 -12.28
TE 1982-83 to TE 2017-18 996.88 25.91 22.27 51.82
Source: Authors’ estimation using Agricultural Statistics at a glance, DES (Various issues).

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production of this crop has been negative. Gram crop
has increased production due to acreage but due to
increase in production of rapeseed mustard crop
(996.88) both acreage and new technology.
The decision of the farmers to area allocation under
six major crops has been determined by different
price and non-price factors per acre accountability
function. The results of the regression model are
presented in Table 4. Table shows that yield and
price risk adversely affect whereas in the previous
year under area, yield areas have had a positive effect
on area allocation. It has been noted that lag area,
price, yield on kharif crops have a positive effect in
determining the area allocation of paddy and cotton
crops, because the corresponding coefcients are
found to be signicant at the level of 1.5, and 10
percent, respectively. In case of paddy, the yield
risk is not signicant as the minimum support price
(MSP) of the paddy crop has been assured. The lag
area under bajra crop has been signicant, but lag
yield and price risks shows negative significant
results. These results show that farmers are price
conscious in their divisional decisions.
CONCLUSION
This paper explores the growth performance of
the agriculture sector in Haryana and the factors
identifying the responding area allocation. The area
under wheat and paddy has increased during the
study period and the area under other crops has
decreased. The state, like Punjab, has a tendency
of cropping pattern towards mono-cropping. The
reason for the increase in area under these crops was
observed in stability of yield and ensured marketing
at minimum support prices. The area under cash crop
cotton has doubled during this period.
The contribution of area effect has been very strong
which increase paddy production to about 91 per
cent, 68 per cent, and 74 per cent during period
rst, second, and overall period respectively. On
Table 4: Determinants of crop area responsiveness in Haryana (Results of regression analysis)
Particulars Paddy Cotton Bajra Wheat R&M Gram
Dependent variable= Area under crop
Log Lag Area 0.55608***
(0.12500)
0.5187***
(0.1152)
0.4634**
(0.1842)
0.5933***
(0.1495)
0.5257***
(0.1106)
0.0481
(0.1645)
Log Lag Price 0.14942***
(0.0509)
0.3524***
(0.0813)
0.0826
(0.1534)
0.1482**
(0.0607)
0.1732
(0.2255)
0.5259
(0.4201)
Log Lag Yield 0.23129*
(0.1310)
0.2201***
(0.0637)
-0.2117**
(0.1030)
0.04705
(0.06716)
0.3629**
(0.1678)
0.2893
(0.228)
Log Price Risk -0.02000
(0.0180)
-0.0197
(0.0244)
-0.0058
(0.0221)
0.0032
(0.0076)
-0.0085
(0.0339)
-0.0030*
(0.0171)
Log Yield Risk -0.0513***
(0.0178)
0.0474**
(0.0213)
-0.0411*
(0.0213)
0.00023
(0.0062)
0.1192**
(0.0607)
-0.0212**
(0.0099)
Trend — -0.0247***
(0.0058)
-0.0048
(0.0132)
-0.0068
(0.0044)
-0.0114
(0.0150)
-0.1253***
(0.0394)
Constant 0.21284
(1.2917)
-0.4688
(0.7767)
4.615***
(1.6168)
1.9564**
(0.9897)
-0.9177
(1.6480)
1.9104
(3.3949)
Adj. R20.9576 0.8564 0.61857 0.9687 0.7537 0.8800
F Statistics 168.33*** 37.788*** 11.00*** 191.87*** 19.8759*** 46.2536***
DW Statistics 2.2411 1.7540 2.0943 1.6075 1.5543 2.0528
Number of
Observation
38 38 38 38 38 38
Source: Authors’ estimation using Agricultural Statistics at a glance, DES (Various issues).
Note: ***, **, * signicant at 1, 5 and 10% levels, respectively.

Growth Trends and Determinants of Crop Area Responsiveness in Haryana
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the other hand, in the case of wheat, the increase in
production mainly contributed due to technological
improvement which has been reported around 54
per cent, 51 per cent and 52 per cent during the same
time period. The area allocation for the cultivation
of paddy and cotton crops have a positive and
significant effect on the lag area, lag price, and
lag yield. While the lag area and lag price found
to have positive and signicant relation with area
allocation in the case of wheat crop. As we know,
the uncertainty in price and yield shows a negative
effect on crop area allocation in most cases. The study
reveals that the area under paddy is increasing in
Haryana as in Punjab state. This may push the state in
such issues as seen in Punjab, such as depletion in the
level of groundwater, excessive use of fertilizer and
pesticides, etc. which may have more adverse effects
in the future. The promotion of a more diversied
cropping pattern has a prequest condition for the
state to achieve sustainable growth. But farmers will
not move towards diversication unless they are
encouraged by economically attractive alternatives.
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