chapter-6 regional variation and convergence in...
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Regional Variation and Convergence in Agricultural Development in India
Chapter-6
Regional Variation and Convergence in Agricultural Development in India
6.1 Introduction
Agriculture in India, the predominant sector of the economy, is the source of
livelihood of almost two thirds of the workforce in the country. The contribution
of agriculture and allied activities to India's economic growth in recent years has
been no less significant than that of industry and services. Agriculture continues
to be the dominant sector of Indian economy as nearly 60% of workforce is
engaged in agriculture in spite of slowing down of its contribution to GDP from
50.5 in 1950-51 to nearly 18.5 in 2007-08, whereas in the advanced countries like
the UK and United States only 2 to 3%, in France about 7% and in Australia about
6% of the working population is engaged in agriculture. Another feature of
agriculture is the dependence of the growth of other sector on agriculture.
Empirical studies show that a unit increase in agricultural output would have
positive effects on both industrial production and national income. It has also been
argued that agricultural sector has played an important role behind the observed
widespread inequality in per capita income in India (Kalirajan et al 1998,1999,
Birthal et al,20 11). It is well known that there exist wide regional variations in
Indian agriculture in terms of agro climatic conditions, persistence of rainfall,
resource base, irrigation facility and infrastructural development.
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Regional Variation and Convergence in Agricultural Development in India
The history of agriculture in India after independence can be divided into three
specific periods. These arel) pre green revolution period, 2) first phase of green
revolution, 3) second phase of green revolution, 4)post reform period.
Pre green revolution period(l951-52 to 1965-66)
This period covers the time period (1950-51 - 1964-65). After achieving
independence and considering the then prevailing institutional, demographic and
sociopolitical nature of Indian agriculture, the thrust of policies given by Indian
planners was on institutional and agrarian reforms. The policies for irrigation and
land reform development received the topmost priority on the policy agenda. The
first plan also aimed at solving food crisis in India and therefore gave the highest
priority to agriculture, especially in food production by allotting 31% of the total
public sector outlay on agriculture, As a result of favourable weather condition;
the total agricultural production exceeded the target of 62 metric tons and reached
to 67 metric tons. Also a steady increase in area, average yield per hectare resulted
in increased production in agricultural output. During 1950-65, the annual growth
rate of area under crop and yield per hectare was quite impressive. The area
growth was the major source of growth of output during this period. For example,
during 1949-50 to 1964-65, the contribution to area growth to output growth was
50.16%, while that of yield growth was only 38.41% (DES,2008). Moreover,
extension of cultivable area before 1964-65 was expressed by all crops as
cultivation was extended to marginal and fallow lands and in many cases waste
land and forest lands. During this period rice recorded the most impressive growth
rate in yield of 2.1% and the yield growth rate of wheat was 1.3% during this
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Regional Variation and Convergence in Agricultural Development in India
period. Among non-food grain crops cotton and sugarcane recorded modest
growth rates during this period. In the second plan main focus was on
industrialization and securing equal opportunities for all particularly for the
weaker sections. Out of total plan outlay 20% was spend on agriculture. Despite
the reduction in plan outlay on agriculture, the progress on agricultural front was
satisfactory. Foodgrain production recorded nearly 80 metric tons. The production
of cotton, oilseeds and sugarcane was increased but failed to achieve the target.
First phase of green revolution
However, experience in the second plan brought about the thought on the policy
makers that the rate of growth in agricultural production was a major limiting
factor in the development of the Indian economy. Also it was becoming clear by
the mid 60's that there was no alternative to technological change in agriculture
for achieving self sufficiency in food grain. During the third plan the Government
introduced the new agricultural technology known as Intensive Agricultural
District Programme (lADP), which was soon followed by a programme of using
improved seeds, viz, High Yielding Varieties Programme (HYVP). The outcome
of the experiment was miraculous, leading to veritable green revolution (Gulati
and Fan,2008). The total amount of food grains harvested increased from 74 mt in
1966-67 to 105 mt in 1971-72 achieving self-sufficiency in food grain (India,
Ministry of Agriculture, 2003). But those outcomes were supported by public
investment in fertilizers, power, irrigation and credit (Fan et al. 2004). Moreover,
according to Gulati et al (2008) this outstanding result was also supported by
favourable pricing policy and the availability of inputs including canal water,
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Regional Variation and Convergence in Agricultural Development in India
fertilizers, power and credit. However, there were regional variations in the
performance of agriculture. During the period 1972-73 to 1979-80 two
unfortunate incidents were happened 1) Two consecutive droughts in 1972-73 and
2) Oil shock. During this period food grain production decreased by 7.7% and
India slid back into the trap of food grain imports of an average of 4 metric ton a
year from the United States between 1973 and 1976 (FAOATAT,2004).
Second phase of green revolution
The period 1980-83 to 1990-93 can be termed as second phase of green revolution
in the history of Indian agriculture. In 1980s, India gained its status of food self
sufficient country. During 80's India achieved a great success in agricultural front
with annual growth rate of 3.8%. The production of foodgrains in 1983-84 was
152 metric ton. While from 1967-68 Green Revolution arose from the
introduction of new high yielding varieties of Mexican wheat and dwarf rice
varieties, but from 1983-84, Green Revolution is said to occur with the expansion
of supplies of inputs and services to fanners, agricultural extension and better
management. The most significant development in this period was the notable
acceleration of growth rates in eastern India. The perfonnance of West Bengal
during this period was spectacular. The growth rate in agricultural output
increased to an unprecedented level of 5.39% per annum. Similarly, Bihar was
also recorded a significant acceleration in growth rates from -0.41% during 1970-
73 to 1980-83 to 2.08% during 1980-83 to 1992-95. The central and southern
region also recorded acceleration in its growth rate. While in central region
growth rates observed a mixed result, the state of Tamil Nadu in the southern
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Regional Variation and Convergence in Agricultural Development in India
region recorded an unprecedented growth of 4.59% per annum. The state Andhra
Pradesh had also experienced with a notable acceleration in this growth rate
during this period. In case of yield, All India registered a growth of 3.15% per
annum. All the regions during this time period experienced a high growth in yield.
The eastern region specially made a turnaround with a high yield growth of
3.32%. The state of West Bengal achieved a spectacular yield growth rate of
4.39% per annum highest over all periods during this period. It was observed that
the sources of yield growth were different in different region whereas in eastern
states it was mainly from high yield rate of rice, in central region it was changes
in cropping pattern (shift from low value coarse cereal to oilseeds), in southern
region it was from rapid increase in rice as well as oilseeds, in north-western
region it was from rice, wheat, cotton and to some extent sugarcane (Bhalla and
Singh,200 1 ).
Post reform period
After 1991, India adopted a series of macroeconomic and structural reforms in
industry specially relating to the exchange rate and foreign investment. These
policy changes ushered in an era of higher economic growth with GDP recording
a high of6.5% per year growth between 1991-92 and 1996-97 compared to 5.2%
in the 1980's. According to Gulati and Fan (2008), although the reforms were
implemented in off-farm activities, they affected agriculture in two ways.
1) The higher rate of economic growth has led to a consequent rise in PCI
during 1991-93. This has, in fact, led to the diversification of food demand
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Regional Variation and Convergence in Agricultural Development in India
into non-foodgrain crops such as fruits and vegetables, as well as meat
mainly poultry and dairy products.
2) The lowering of industrial protection significantly improved the incentive
framework for the sector through improvement in the domestic TOT
between agriculture and industry.
In spite of the above facts the agricultural GDP in India faced a deceleration
during post reform period covering almost all the major sectors including those
such as horticulture, livestock, fisheries. During 9th and 1oth plan agricultural GDP
was far below the target fixed. In most of the crop acreage expansion has been
observed to follow a declining trend. Only wheat experienced a modest growth in
area of 0.11% during the period 1995-96 to 2004-05. At the all India level, the
output growth decelerated to 1.74% per annum during 1990-93 to 2003-06. At the
regional level, the growth of agricultural output decelerated to 1.58% per annum
in north-western region, to 1.0% per annum in eastern region, to 3.15% pa in
central region, to 0.48% pa in southern region. All states except Gujarat and to
some extent Maharashtra registered a sharp decline in their output growth rates in
the post reform period (Bhalla and Singh, 2009). Given the stagnant NSA and
GCA, there has been a substitution in area expansion from one crop to another.
The availability of land for agriculture got constrained because of the pressure of
demand for land for nonagricultural sector and rapid urbanization in recent years.
Along with area, the growth of productivity of majority crops faced sharp
deceleration. At the ali India level, the productivity growth rate decelerated to
1.52% per annum during this period. The productivity growth of rice and wheat
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Regional Variation and Convergence in Agricultural Development in India
decelerated to 0.82% per annum and 0.56% per annum respectively from 2.4%
per annum and 2.61% per annum respectively in the previous decade. Only cotton
and maize registered productivity growth rate of 2% during 1995-96 to 2004-05.
At the regional level also the productivity growth decelerated for all regions
except the state Gujarat compared with the period 1980-83 -1990-93.
There is a plethora of literature about the growth, instability, cropping pattern and
interstate difference in agriculture in India. Several studies such as Rao (1975),
Dharm Narain (1977), Mehra (1981), Hazell (1982), Rao et al(1988) etc. have
pointed out that the new strategy of agricultural production based on HYV seed
fertilizer technology has contributed to the growth in production and productivity
in India. In an elaborate study, Bhalla and Singh (200 1) showed that a marked
acceleration took place in both the output and yield growth rate in Indian
agriculture during 1980-83 to 1992-95. This result was supported by many authors
like Sa want and Achutah (1995) claiming that the yield rate of both foodgrain and
non-foodgrain crops accelerated significantly along with output growth during
80's. The study by Bhalla and Singh (2001) also evidenced that increase in
regional disparity during the first phase of green revolution was followed by
decline in the same during the second phase of green revolution, the effect of
HYV spreading everywhere the country. According to them during the first phase,
the most gainers were western region and most low producing zone was eastern
region. But in the second phase ( 1981-1991 ), eastern region experienced a notable
acceleration in both output and yield growth especially the state of West Bengal.
Several attempts have also been made to explain the variability in agricultural
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Regional Variation and Convergence in Agricultural Development in India
production in India and its causes. Dev (1987) shows a higher degree of instability
in agricultural production in less irrigated area compared to irrigated area. Using
Panel data framework Mathur et al. (2006), show that the deceleration in both
output and yield growth during 90's was dependent mainly on government
expenditure on agriculture, fertilizer usage, rainfall and population. Janaiah et al.
(2005) explained the long term growth in yield which was noticeable from the
adoption of modem techniques has been slowed down by decreasing impact of
modem technologies. In order to explain the factors behind deceleration in
agricultural output and yield during 90's, Chand et al. (2001) in their study
claimed the slowdown in growth of fertilizer use, irrigation, energy and crop
intensity to be the major reasons behind the downturn of agricultural growth.
About convergence/ divergence of agricultural growth across Indian states, the
study by Kalirajan et al.( 1998) found the long term divergence and cyclical
pattern in agricultural growth. According to them, the investment climate in
agriculture and operation of both the supply and demand factors are responsible
for slowing down of growth rates and the regional divergence in agricultural
production and productivity. Another study by Ghosh (2006) examined the
regional disparities in agricultural development across 15 major states in India
during 1960-61 to 2001-02. He found absolute p and a divergence in land
productivity, labour productivity and per capita agricultural output across states
after the dissemination of new HYV technology and large scale economic
reforms. He also found conditional convergence in agricultural development
taking human capital, physical capital and rural infrastructure as conditional
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Regional Variation and Convergence in Agricultural Development in India
variable. Through the unit root test he proved 6 states out of 15 states are
following different steady state path than that of all India. Under this backdrop,
the main objectives of this study are
1. To analyse the trend in the rate of growth of value of output in agriculture
as well as yield in the states of India from 70's to the current decade
including the phases of green revolution and new economic reform.
2. To look into the trend in the disparity in respect of value of output from
agriculture and yield among the states during 70's,80's and post reform
period.
3. To examine the nature of cropping pattern prevailing in the states. How far
the states are able to diversify their crop production overtime.
4. To test whether the states are converging in terms of per capita value of
output from agriculture. What are the factors responsible behind the
convergence or divergence of Indian states in per capita value of
agricultural output?
6.2 Data source & Methodology
The period of the study covers 38 years period from 1970-71 to 2007-08. Twenty
major states have been studied for interstate comparisons. The study uses
exclusively the secondary data. The state wise and crop wise value of output for
the period 1970-71 to 2005-06 have been taken from different issues of CSO,
Govt of India publication. The state wise data on inputs and operated area for
different years are taken from different issues of Indian Agriculture in Brief,
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Regional Variation and Convergence in Agricultural Development in India
Directorate of Economics and statistics, Ministry of Agriculture and Centre for
Monitoring Indian Economy, Agriculture. The data for area, yield and production
of some selected crop for India and the states are collected from different issues of
Centre for Monitoring Indian Economy, Agriculture. The time series data of
values of output and yield has been converted to 1999-00 prices. Eight major
crops have been selected for this study. Those are rice, wheat, jute, cotton,
sugarcane, rapeseed and mustard and potato.
The methodologies which have been followed in this chapter can be summarized
under four headings relating to the estimation of growth, changes in cropping
pattern, measuring diversity in agriculture and convergence analysis.
A. Growth estimation:
1. The Exponential Growth rate of agricultural output over the study period has
been measured. To examine the nature of acceleration and deceleration of
trend growth, log quadratic equation is fitted. For the decomposition of
growth rates in several sub-periods the Kinked Exponential Technique has
been used. For details see chapter 3, pg-.36-38
B. Changes in cropping pattern:
Changes in cropping pattern overtime have been measured in terms of relative
change in area under crops to the changes in GCA. Moreover, the cropped area
GCA elasticity measure of cropping pattern has been applied. This technique
enables us to identify the crops which are very sensitive in the changes of
cropping pattern (see chapter 3 for detail methodology pg-57 for details). In
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Regional Variation and Convergence in Agricultural Development in India
addition to this the crop diversity of Indian states has been measures using
Herfindal Index.
C. Composite Index Agricultural Infrastructure CIA/:
For measuring disparity among the states in respect of different agricultural
indicators, one diversity index has been computed. The Composite Index
Agricultural Infrastructure is computed using deprivation method. Eight
indicators relating to agricultural development have been chosen to construct the
index (for details consult chapter 3 on methodology section, pg-53-55)
D. Convergence Analvsis
!.Absolute Convergence:
Following Barro-Salai-Martin's methodology of convergence, Absolute ~
convergence and a convergence have been estimated (explained in
methodology section of chapter 3 pg-46).
2.Conditional Convergence: To test conditional convergence of PCVOA,
Generalized Method of Moments ( GMM) estimation technique has been used
in the dynamic panel data model. The methodology has already been
discussed in the methodology chapter 3, pg-46-49.
3.Unit Root Test:
The econometric method of time senes analysis for testing convergence
examines the long run behavior of per capita output across countries. This
methodology treats this difference as transitory and as the forecast horizon
grows the difference between any pair of countries converges to zero. Within
a neoclassical Solow type model it produces that the long run behavior of the
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Regional Variation and Convergence in Agricultural Development in India
economy will be independent of initial condition. The test for convergence is
translated to a test for stationary of output differential. A test of the null
hypothesis of no convergence (ie non-stationary) against the alternative of
convergence (ie stationary) is undertaken here.
The null hypothesis is expressed as
Ho: Zi,t =[In(Yi,t)- In-(Y *,t)]- l(t) for all i
The alternative hypothesis is
H1: Zi,t= [In(Yi,t) -In-(Y *,t)] '- l(O) for all i
Where Zi,t is the logarithm of per capita income of ith state relative to national
average. ln(Yi,t) and ln(Y *,t) respectively denote the logarithm of the ith
state's and national average per capita income. I(l) and I(O) are respectively
integrated of the order 1 (non-stationary) and zero (stationary) processes.
6.3 Growth performance of Indian states in agriculture
6.3.1 Growth rate of value of output
An attempt has been made in this section to analyse the growth rates in value of
agricultural output in India and the states as well. In order to obtain a detail idea
about the patterns of growth rates, the period has been divided into three sub
periods. The first sub period covers the period (1970-71 to 1980-81) which can be
looked upon as the first phase of green revolution. The second sub period
covering the period (1980-81 to 1990-91) can be termed as the second phase of
green revolution and the third sub period covering the period ( 1991-92 to 2005-
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Regional Variation and Convergence in Agricultural Development in India
06) can be termed as post reform period. The exponential growth 1 rates are
calculated for the value of output from agriculture and for the yield of output as
well. The analysis of the exponential growth rates of value of agricultural output
taking all crops for the whole period reveal that in India value of agricultural
output grew at the rate of 2.6% per annum. The growth rates of the states exhibit
that the states like Haryana, Maharashtra, Rajasthan, West Bengal, Goa, Himachal
Pradesh, Madhya Pradesh, Manipur, and Punjab have grown at a higher rate than
all Indian average. Among them the highest growth rate was achieved by Haryana
(3.46%) followed by Madhya Pradesh (3.38), Rajasthan (3.36%), Goa (3.3%) and
West Bengal (3.24%). But the state which lagged most was Jammu & Kashmir
with negative growth rate of -0.26%. Otherwise all the states registered positive
growth rate during the whole period ( 1970-71 to 2005-06).
The exponential growth rates of value of agricultural output for the state as well as
for the country have been computed for the 1st sub period (1970-71 to 1979-80).
All India growth during this phase was 1.88%.The states like Manipur (6.46%),
Arunachal Pradesh (5.9%), Maharashtra (5.78%), Punjab (5.43%) and Haryana
(3.36%) occupied the five topmost positions during this period. The five states
recording the lowest growth were Madhya Pradesh (-0.94%), Kerala (-0.8%),
Orissa (0.4%), Bihar (0.6%) and Rajasthan (0.8%) in the same period. Except the
top five states, the states- Gujarat, Goa, West Bengal and Kamataka managed to
register a growth rate higher than the national average. Other states like Andhra
Pradesh, Assam, Himachal Pradesh, Jammu &Kashmir, Tamil Nadu, and Delhi
1 lnYr=a + br+ Ur (Semi logarithmic equation is estimated to derive the exponential growth rate)
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Regional Variation and Convergence in Agricultural Development in India
achieved modest growth rate (see table 6.1). It is clear from the growth figures
that high rate of growth of the value of agricultural output remained concentrated
only in few states. The growth rate of majority of the States was centering around
2 per cent per annum during the period (See Table 6.1 ).
The second sub period (1980-81 to 1990-91) has been regarded as the 2nd phase of
green revolution. Most of the studies mention that fruits of green revolution were
spread to almost all regions during 80's. Moreover, in 1991 the new economic
reform was introduced in all over India. Agricultural sector in India was expected
to get a significant break in its level and trend of growth rate. In this respect,
kinked growth rate2 has been computed for the period 1980-81 to 2005-06 with
1991 as kink.
It is observed from the results of the kinked exponential growth rate that the
period (1980-81 to 1990-91) made a remarkable improvement in the growth rate
of agricultural output in India and allover states. At the all India level the growth
rate accelerated at a rate of 3.34%. The highest growth rate was achieved by the
state Tamil Nadu (5.46%). Except Tamil Nadu , the top five states were West
Bengal (5.25%), Rajasthan (5.5%), Punjab(4.9%), Haryana (4.78%) and Madhya
Pradesh (4.62%).The other states viz Andhra Pradesh (3.16%), Uttar Pradesh
(3.14%), Kamataka(3.94%) made a significant improvement compared to the
previous period. Thus it is evident from the results that gradually the good effects
of the new technology spread to different regions without being concentrated to
some selected part. The states of different regions ie West Bengal of eastern
2 lnY1= a +b,D1t+b2D2t+u1 (Boyce,l987)
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Regional Variation and Convergence in Agricultural Development in India
region, Rajasthan of central region, Tamil Nadu of Southern region contributed to
the higher Growth rate in India. Also the states like Bihar, Orissa, Kerala,
Himachal Pradesh and Assam registered higher growth rate compared to previous
period. Further, decline in the growth rate were recorded by the states like
Maharashtra, Gujarat, Goa, Manipur, Arunachal Pradesh and Delhi respectively.
Among the above states, three states (Maharashtra, Manipur, Arunachal Pradesh)
were on the topmost position in the previous period. The important point to be
noted here is that the poorer states have grown quite well during this period. In
this period Gujarat and Delhi registered a negative growth (see Table 6.1 ).
TABLE6.1: TREND GROWTH RATE OF VALUE OF OUTPUT OF AGRICULTURE DURING
197Q-71 to 2005-06 OF INDIAN STATES
Exponential Growth rate Kinked exponential growth rate
Growth rate Whole period 1st subperiod 2nd subperiod 3rd subperiod
(1970-71 to 2005-06) 1970-71 to 1979-80 1980-81 tol990-91 1990-91to2005-06 b1 b2
Andhra Pradesh 2.406 1.93 3.16 1.46
Arunachal Pradesh 1.065 5.9 3.87 2.32
Assam 2.098 1.67 2.63 1.45
Bihar 2.549 0.61 2.26 1.98
Goa 3.3 3.01 1.46 3.12
Gujarat 2.082 2.76 -0.37 3.29
Haryana 3.463 3.36 4.78 2.34
Himachal Pradesh 2.797 1.4 2.63 1.08 Jammu & Kashmir -0.263 1.79 1.75 -0.03
Karnataka 2.251 2.1 3.94 2.07
Kerala 1.189 -0.8 2.76 2.57 Madhya Pradesh 2.76 -0.93 4.61 1.84 Maharashtra 3.38 5.78 2.2 3.94 Manipur 2.8 6.46 0.45 2.16 Orissa 1.57 0.44 1.66 0.17 Punjab 2.88 5.43 4.9 1.47 Rajasthan 3.36 0.83 5.5 2.58 Tamil Nadu 1.896 1.77 5.46 0.15 Uttar Pradesh 1.918 1.09 3.14 1.58 West Bengal 3.24 2.26 5.25 2.09 Delhi 2.054 1.59 -1.9 1.23 India 2.6 1.88 3.34 2
' Source.Author s calculation
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Regional Variation and Convergence in Agricultural Development in India
The result of third sub period (1991-92 to 2005-06) ie post reform period portrays
completely a different scenario. The growth rate in crop output at all India level
declined to 2% from a high rate of 3.34% in the previous period. It is clear from
all India figure that most of the states experienced a severe setback in agricultural
output. It has been observed that almost all the states experienced with a
deceleration trends in agricultural growth during this period. Only the states
Maharashtra, Goa, Gujarat, Manipur and Delhi managed to improve their growth
rate compared to previous period. The top three states in this phase were
Maharashtra (3.9%), Gujarat (3.3%) and Goa (3.1 %) respectively. A negative
growth was achieved by Jammu& Kashmir.
The most important factor for this agricultural downturn may be the result of
slowdown of food grain production in the post reform period in India. Since
foodgrain comprises nearly 60% of the total crop output in India and majority of
the states are dependent on production of foodgrain, the deceleration in foodgrain
production is reflected in the result of growth of value of crop output.
6.3.2 Yield Growth Rates
After independence, growth in output of crop was mainly contributed by the
growth in area. During the period of 50's and 60's the contribution of yield was
meager. But gradually after the technological breakthrough occurring through
green revolution, yield growth took a dominant part in output growth. According
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Regional Variation and Convergence in Agricultural Development in India
to Bhalla and Singh (2009), during 1949-50 to 1964-65, the contribution of area
growth to output growth was 50.16%, while that of yield growth was only
38.41%. During 1962 to 2003-06, the yield growth accounted for 85.2% of growth
of output while the contribution of area growth was only 14.41%.
The yield of agricu1tura1land has grown at the rate of 1.43% per annum over the
period (1970-71 to 2005-06). The top five states in respect of high yield rate are
Madhya Pradesh (2.81 %), Rajasthan (2.5%), Haryana (2.5%), Punjab (2.12%) and
Uttar Pradesh (2.04%).The states like Orissa and Jammu &Kashmir had registered
negative growth whereas the performance of the states like Assam, Himachal
Pradesh, Karnataka, Kerala and West Bengal has been very poor in respect of
yield growth.
In order get a vivid picture about the growth of yield of the foodgrain and non
foodgrain crops across states the exponential growth rates of the yield of
foodgrain and non-foodgrain crops have been computed for the period 1970-71 to
2009-0fr In this study major eight crops have been selected. At the all India level
the land productivity of foodgrain grew at 2.26% in India whereas the same for
non-foodgrain crops grew at 1.48%. The interstate variations in growth rate of
yield in case of foodgrain and non-foodgrain crops are prominent. The highest
growth in yield for foodgrain for the overall period was achieved by Haryana
(3.61 %). The states in the queue after Haryana were Andhra Pradesh (2.98), Uttar
Pradesh (2.6), West Bengal (2.45) and Punjab (2.21). The lowest growth in this
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Regional Variation and Convergence in Agricultural Development in India
field had attained by the state Jammu & Kashmir (0.812). Except this all the states
considered here have grown at the rate of more than 1% during this period. On the
other hand, the picture of productivity growth in non-foodgrain crop is not
satisfactory. The state of Kerala (1.92) topped in the yield growth rate of non
foodgrain crops. The top four states after Kerala were Himachal Pradesh (1.82),
Rajasthan (1.33), West Bengal (1.18) and Uttar Pradesh (1.15). The trend growth
rate is negative for two states-Maharashtra (-0.361) and Orissa (-0.0104). Other
than that the growth rate of yield for the states Andhra Pradesh, Assam, Punjab,
and Karnataka were very poor.
The segregation of the whole period in three sub-periods reveals that the first sub
period did not experience much improvement in yield rate. At the all India level,
yield rate has grown for total crop at the rate of 1.48% during 1970-71 to 1979-80.
During this time period, the maximum improvement in yield rate was made by
Punjab, Maharashtra, Manipur whereas Orissa, Madhya Pradesh, Kamataka and
Bihar registered negative growth. Also the states like Haryana, Andhra Pradesh,
Kamataka and Jammu &Kashmir achieved a modest growth. The states like Uttar
Pradesh, Rajasthan, and Himachal Pradesh recorded very low rate. During this
period, the positive impact of green revolution was observed to remain
concentrated to some selected zones. For this reason regional variation in yield
was also very high (see Table 6.2).
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Regional Variation and Convergence in Agricultural Development in India
TABLE 6.2: TREND GROWTH RATE OF YIELD FROM AGRICULTURE DURING 1970-71 to
2005-06 OF INDIAN STATES
Exponential Kinked exponential Exponential Growth
Growth rate growth rate rate Whole 1st 2nd
States pd subpd subpd 3rd subpd Whole period(1970-08)
1970to 1970-- 1991-92to2008- Foodgrain Non-
2006 80 1980-91 09 Crop foodgra in
Andhra Pradesh 1.87 2.56 2.64 1.56 2.98 0.192
Assam 0.4 -0.37 2.98 0.021 1.37 0.219
-Bihar 1.91 0.0005 3.86 1.24 1.9 0.917
Gujarat 1.35 2.26 -0 .34 2.93 2.05 0 .657
Haryana 2.5 2.5 6.25 0.19 3.61 0.8
Himachal Pradesh 0.27 1.053 4.46 -0.34 1.39 1.82
Jammu & Kash mir -2.79 0.69 2.08 -1.22 0.812 -3.46
Karnataka 0.82 2.5 2.73 2.06 1.49 0.413
Kerala 0.7 -0.62 3.42 1.58 1.31 1.92
Madhya Pradesh 2.81 -1.21 6.1 1.95 1.89 0.754
Maharashtra 1.92 4.54 2.32 3.02 1.89 -0.361
Manipur 1.64 3.23 3.21 -0.41
Orissa -0.64 -0.19 2.22 -0.28 1.55 -0.0104
Punjab 2.12 3.9 6.38 -1.07 2.21 0.378
Rajasthan 2.52 0.56 4.76 1.79 2.32 1.33
Tamil Nadu 1.96 3.15 4.33 1.53 1.55 0.713
Uttar Pradesh 2.04 0.73 4.71 0.19 2.6 1.15
West Bengal 0.78 1.25 5.48 -0.29 2.45 1.18 India 1.43 1.48 3.38 1.16 2.26 1.48
Source: Author's calculation
Note: The latest available data set for the yield of agricultural output was pertaining to the year 2005-06 while the
segregated data for foodgrain and non-foodgrain could arranged till the period 2007-08.
4
YIELD GROWTH OF FOODGRAIN AND NONFOODGRAIN
CROPS DURING THE PERIOD 1970-71 TO 2007-08 OF
INDIAN STATES
3 ----------------- ---
2
1
0 ~'~ ~~~~~roz~I~~ -1 -a:- ~ -~ ~ .=j- >--a: ""' ·o:t: <r 0 - Vl <~: -I~I <(~I~Vl~~~w~ O
-2 ~:--UJOO'---~;;.--<f'--3:1---od'------t<t---'0 = OC z b z 0 z z Z<( ~=>i7l <(W ~ ~<( ~<(=~ro
~ ~~~~ I ~~~~ <( ~ ~ s
-3
-4
Figure 6.1
• FOODGRAIN
• NONFOODGRAIN
Regional Variation and Convergence in Agricultural Development in India
The period (1980-81 to 1991-92) ie the decade of 80's experienced a huge jump
in yield growth in the country. Most of the states experienced an upsurge in the
yield growth during this period. As in this period the effect of new seed fertilizer
technology had spread to all over India, all the regions got the benefit of it. It is
revealed from the results of kinked exponential yield growth rate that almost all
the states registered acceleration in their yield growth during this period. All India
achieved unprecedented growth of 3.38% in yield whereas the states Punjab
(6.38), Haryana (6.29), Madhya Pradesh (6.11) and West Bengal (5.48)
accelerated at a rapid rate. Again the states like Bihar, Himachal Pradesh, Kerala,
Manipur, Rajasthan, Tamil Nadu and Uttar Pradesh registered higher rate. Except
Gujarat remaining all the states had experienced with a higher rate of growth
compared to the previous period.
To examine the effect of New Economic Reform in yield growth, the kinked
exponential growth rate for the period 1991-92 to 2005-06 has been calculated for
India and the states as well. The result of yield growth in the post reform period
reveals a precarious picture. The all India growth rate has been decelerated to
1.16% in this period compared to 3.38% of the previous period. Surprisingly, the
states like Himachal Pradesh, Punjab, West Bengal, Jammu & Kashmir and Orissa
recorded a negative growth in the post reform period. In fact, again except Gujarat
and Maharashtra, all the states had experienced a significant deceleration trends in
yield growth rates during the post refonn period.
164
Regional Variation and Convergence in Agricultural Development in India
6.3.3 Acceleration and Deceleration in growth of value of agricultural
output and yield in India
In order to investigate whether the growth rate of value of agricultural output and
yield accelerated or decelerated over time, the log quadratic equation has been
estimated (see methodology section of chapter 3, pg-38). In fact, log quadratic
equation has been fitted for the sub-periods 1970-71 to 1990-91, 1980-81 to 1990-
91, 1991-92 to 2005-06and also for the whole period 1970-71 to 2005-06,. The
results show a significant positive 'c' for the period 1980-81 to 1990-91 in both
for the value of output and for yield of crop respectively. Whereas, the same
estimation for the period 1991-92 to 2005-06 has shown negative coefficient for
'c' (see Table 6.3).
TABLE 6.3:ACCELERATION/DECELERATOIN IN GROWTH OF VALUE OF OUTPUT AND
YIELD
Value of output Yield
b c b c
1970-06 0.007 3.19e-04 0.006 0.0002 •'
1970-91 -0.0064 7.86e-04 -0.024 0.0022
1980-91 -0.044 0.06 -0.067 0.09
1991-06 0.029 -7.52e-04 0.025 -6.16e-04
Source:Author' s calculation
165
Regional Variation and Convergence in Agricultural Development in India
Thus, the results establish that there was a significant acceleration in growth rate
in both the value of output and yield during the 2nd phase of green revolution but
the period in the post liberalization has marked a sign of depression both in
agricultural output and its yield rate in India.
6.4 Cropping Pattern in India
Cropping pattern is defined by the proportion of area under different crops at a
point of time. It is a mix of agricultural crops that are grown in particular
geographical area (De,2003). Changes in cropping pattern can be seen as a change
in the proportion of area or value of production under different crops to total
agricultural area. The cropping pattern is governed by the law of comparative
advantage in relation to agro climatic conditions, technical and institutional
factors (Vaidyanathan, 1994). The change in cropping pattern is mainly a
switchover from low value crop to high value crop. This is successfully possible
through large scale irrigation, institutional change and introduction of technical
breakthrough.
In India, from 80's the process of change in cropping pattern hastened and the
change was prominent in favour of non-foodgrain crop. It is reflected from the
ratio of area in food grain crop to GCA. During the period 1970-71 to 1980-81 the
proportion of area under foodgrain experienced a small decline from 74.3% in
1970-71 to 72.6% in 1980-81 (see Table 6.4). But from 80 onwards the share of
area under foodgrain to total GCA declined persistently to 66.9% in 1991-92,
64.6% in 2000-01 and 63.4% in 2007-08 respectively. Taking all the selected non-
166
Regional Variation and Convergence in Agricultural Development in India
foodgrain crops together the area allocation reveals an upward trend at the all
India level over the period 1970-71(8.8%) to 2007-08(11.6%).
TABLE 6.4: CHANGE IN PERCENTAGE OF AREA UNDER FOODGRAIN AND
NONFOODGRAIN CROPS OF INDIAN STATES
FOODGRAIN NONFOODGRAIN
States 1970-71 1990-91 2007-08 1970-71 1990-91 2007-08
Andhra Pradesh 71.07 56.33 54.45 3.3 7.15 10.18
Assam 75.44 71.24 65.59 11.6 13.07 10.32
Bihar 89.86 80.24 88.86 4.4 6.46 6.05
Gujarat 50.78 37.10 36.66 16.5 15.81 24.33
Haryana 77.58 64.36 69.31 9.7 25.11 19.21
Himachal Pradesh 90.15 87.42 83.67 2.7 2.56 2.58
Jammu & Kashmir 89.41 83.76 81.01 3.1 5.55 5.01
Karnataka 66.00 58.01 61.05 10.2 7.26 6.00
Kerala 31.58 19.01 8.80 0.5 0.55 0.12
Madhya Pradesh 81.96 66.12 55.29 4.7 6.83 6.52
Maharashtra 66.93 63.83 64.69 15.8 15.78 21.13
Orissa 68.50 73.90 60.88 1.8 2.76 1.11
Punjab 69.16 75.10 80.09 11.4 12.10 10.43
Rajasthan 76.96 62.39 61.27 3.1 16.03 13.00
Tamil Nadu 70.36 57.43 53.27 6.2 7.18 9.61
Uttar Pradesh 84.59 78.71 76.56 16.1 12.58 14.24
West Bengal 86.22 73.80 65.17 8.7 14.40 14.77
India 74.26 66.87 63.35 8.8 10.96 11.57
Source:Author' s calcu1atJOn
Statewise changes in cropping pattern
Statewise pattern of changes in area of crops overtime in India has been widely
dispersed and varied ( see Appendix Table 6AI 1 to 6AI 17). It is mention worthy
167
Regional Variation and Convergence in Agricultural Development in India
that foodgrain occupies the most important place in area composition in almost all
states still now. Only the state of Kerala experienced a significant and notable
decline in foodgrain area allocation. In Kerala, the area under foodgrain to GCA
was 31.6% in 1970-71, it fell to 19% in 1991-92 and further reduced to only 8.8%
in 2007-08. The change is very much prominent in the reform period. It can be
assumed from this result that there was a spectacular triumph made by Kerala in
case of crop diversification. According to Bhalla and Singh (2009), about 90% of
Kerala's area is under high value plantation crops like condiment and spices and
remaining crops. Because of the preponderance of high value crops in the state,
Kerala along with Punjab has the highest level of crop productivity in the country.
India is mostly a foodgrain producing country. In recent years especially in the
post reform period there is observed to be a marginal shift towards in cropping
pattern in favour of non-food crops. However, there are substantial inter-state
variations to this result. In foodgrain crop, the proportion of area declined at a
high rate in the states like Andhra Pradesh, Gujarat, Rajasthan, Tamil Nadu,
Madhya Pradesh and West Bengal. The other states like Haryana, Himachal
Pradesh, Jammu &Kashmir, Uttar Pradesh also experienced deceleration in the
composition of area under foodgrain, but at a moderate rate. In Bihar around 90%
of GCA was under foodgrain crop in 1970-71. In 1980-81 this percentage
decreased to 66.55. Again the same proportion faced a sharp increase from 66.55
to 80.2% in 1991-92, 90.7% in 2000-01 and 88.9% in 2007-08 respectively.
Further, the state of Punjab experienced an increase in the proportion of area
168
Regional Variation and Convergence in Agricultural Development in India
under foodgrain from 69.2% in 1970-71 to 80.1% in 2007-08. Except Punjab and
Bihar, all most all the states show a diversification of cropping pattern in favour
of non-food crops.
The states like Andhra Pradesh, Gujarat, Haryana, Jammu & Kashmir, Madhya
Pradesh, Maharashtra, Rajasthan, Tamil Nadu and West Bengal experienced with
an increase in area allocation under major non-food crops over the study period.
However, the pace of diversification got accelerated in the post reform period for
a majority of states. Among the 17 states considered here, more than 9 states faced
a deceleration in share of non-foodgrain crops after the year 1991-92. Among the
remaining states Andhra Pradesh, Maharashtra and Tamil Nadu managed to
maintain a steady upward trend in terms of area allocation towards selected non
foodgrain crops. The states like Gujarat, Madhya Pradesh, Punjab and Rajasthan
experienced with an increase in area allocation under non-food crops especially in
the post reform period. Crop as well as state-wise analysis is given in appendix
table 6AI I-6A 16
6.5 Measuring the shift of cropping pattern: Crop area-Gross Cropped
Area Elasticity
In most of the states including in India, area effect is found to be negative for food
grain crops, which implies that the area under foodgrain has declined over the
period. On the other hand, the area under non-food grain crops increased
substantially over the period 1970-71 to 2007-08 (see table 6.5 and 6.6). A simple
169
Regional Variation and Convergence in Agricultural Development in India
measure to examine the shift in cropping pattern or the acreage change of each
crop due to intercrop substitution of areas and expansion of GCA is the 'crop area-
GCA elasticity' 3 measure. The result of elasticity measure for foodgrain and non-
foodgrain crops are provided in the table 6.5 and 6.6. It is evident that elasticity
value is greater than unity for non-foodgrain crops and less than zero for
foodgrain crops in India. This implies that there is a shift in cropping pattern
towards non-food grain crops from foodgrain crops during the period in the
country.
The elasticity analysis of different states in India provides a comprehensive
picture about the cropping pattern and the crop diversification during the period
1970-71 to 2007-08. From the table it appears that the states Andhra Pradesh,
Gujarat, Himachal Pradesh, Karnataka, Kerala, Maharashtra, and Uttar Pradesh
faced a negative elasticity value for foodgrain crops indicating diversion of area
against foodgrain crops whereas the states Bihar, Madhya Pradesh, Punjab and
Tamil Nadu, achieved a value greater than one implying a skewed cropping
pattern towards food grain. Again for non-food grain crops the elasticity value is
greater than one for the states Andhra Pradesh, Gujarat, Haryana, Jammu
&Kashmir, Maharashtra, Rajasthan and West Bengal. On the other hand the value
lies between 0 and 1 for the states Assam, Bihar, Himachal Pradesh, Karnataka,
Orissa and Punjab. For these states, the increase in area allocation under non-
foodgrain crops is found to be less than the increase in GCA. Moreover, the states
3 E-= :c;:.=:1ge- :::: t:.s. s~o:·;:~: of S:'"E-3 '-.:!:::.~:~ c~·::,~
::·~ cl:s::g~: :~ c~:A
170
Regional Variation and Convergence in Agricultural Development in India
Kerala, Madhya Pradesh, Uttar Pradesh and Tamil Nadu attained a negative
elasticity value implying a diversion of area from selected non-foodgrain crops.
The result of elasticity measure for individual crop is presented in the tables in
appendix table 6AII 1 to 6AII 17.
TABLE6.5:AREA EFFECT, YIELD EFFECT AND CROP AREA-GCA ELASTICITY OF
FOODGRAIN CROPS OF INDIAN STATES DURING 1970-71 TO 200U-08
FOODGRAIN
States Area Effect Yield Effect total change increase in Area E'
in Production under Crop
Andhra Pradesh -6268.11 19336.41 13068.30 -2017.40 E<O
Assam 334.41 1034.19 1368.60 406.50 O<E<1
Bihar 173.63 2128.34 2301.97 -3148.50 E>1
Gujarat -947.31 2382.81 1435.50 -1317.40 E<O
Haryana 501.84 7842.56 8344.40 519.57 O<E<l
Himachal Pradesh -23.50 514.36 490.87 -15.67 E<O
Jammu & Kashmir 185.40 412.46 597.87 128.37 O<E<1
Karnataka 649.37 5146.63 5796.00 452.67 E<O
Kerala -1101.63 386.90 -714.73 -657.63 E<O
Madhya Pradesh -142.28 2168.62 2082.57 -5270.70 E>1
Maharashtra -1603.65 4922.08 5608.00 -1464.00 E<O
Orissa 3124.85 5312.25 2511.90 -331.20 O<E<1
Punjab -178.86 12204.65 18464.80 2380.40 E>1
Rajasthan -3058.32 3435.06 5066.17 44.00 O<E<1
Tamil Nadu 36.32 255.92 16.73 -2001.60 E>1
Uttar Pradesh 1106.13 17712.56 21464.73 -74.67 E<O
West Bengal 517.59 8288.21 8805.80 417.90 O<E<1
India -5478.91 131726.91 126248.00 -1201.03 E<O
Source:Author' s calculatiOn
171
Regional Variation and Convergence in Agricultural Development in India
TABLE6.6: AREA EFFECT, YIELD EFFECT AND CROP AREA-GCA ELASTICITY OF SELECTED
NONFOODGRAIN CROPS OF INDIAN STATES DURING 1970-71 TO 200J-Oi
NONFOODGRAIN States Area Effect Yield Effect total change increase in Area E'
in Production under Crop
Andhra Pradesh 9070.94 507.76 9578.70 945.20 E>1
Assam -19.87 -8.53 -28.40 73.50 O<E<1 Bihar 905.64 2107.79 3013.43 -11.10 O<E<1 Gujarat 11869.01 8494.49 20363.50 1315.80 E>1 Haryana 1129.71 306.36 1436.07 759.80 E>1 Himachal Pradesh 19.58 73.16 92.73 0.10 O<E<1 Jammu & Kashmir 5.35 -16.11 -10.77 29.80 E>1 Karnataka 30429.67 -14681.61 15748.07 -332.90 O<E<1 Kerala -741.57 616.37 -125.20 -12.00 E<O Madhya Pradesh 357.70 182.23 539.93 356.30 E<O Maharashtra 60167.52 -19745.89 40421.63 1266.50 E>1 Orissa 2816.94 9.93 2826.87 -49.80 O<E<1 Punjab -651.09 3432.52 2781.43 176.00 O<E<1 Rajasthan 2531.47 623.49 3154.97 2369.60 E>1 Tamil Nadu 4764.62 16901.38 21666.00 101.00 E<O Uttar Pradesh 32774.20 30395.43 63169.63 -186.10 E<O West Bengal 10612.08 4930.02 15542.10 825.50 E>1 India 92366.59 109537.31 201903.90 7887.60 E>1 Source:Author' s calculation
A close examination of the results of elasticity measure provides some striking
phenomena. In case of Bihar, for foodgrain crops, E> 1 indicates the bias in
cropping pattern towards foodgrain production. Among foodgrain crops, for rice,
E> I and for wheat, E<O. This implies among foodgrain crops, there is a strong
bias towards the cultivation of rice. It is observed that in the state of Madhya
Pradesh, for foodgrain crops E> 1 , for rice is E> 1 and for wheat E<O . Except
cotton, in all other cash crops ie Rapeseed &Mustard, potato and sugarcane the
figure for elasticity is negative. This implies that except cotton, Madhya Pradesh
is broadly a foodgrain producing state. In contrast, though the States like Punjab,
172
Regional Variation and Convergence in Agricultural Development in India
Tamil Nadu are broadly foodgrain dominated, there is observed to be a marginal
shift in cropping pattern towards the cultivation of non-food crops.
6.6 Measuring Diversity in cropping pattern Herfindal Index
The change in cropping pattern can further be analysed by using the indices of
crop diversification. There are different indices to measure the extent of crop
diversification like Herfindal Index, Simpson Index, Ogive Index and Entropy
Index etc. Among them Herfindal Index, Simpson Index and Entropy Index are
used widely. These indices are calculated on the basis of proportion of GCA under
different crop cultivated in a particular geographical area. Crop diversification
index is actually a measure to show the direction of change of cropping pattern of
a particular state or region at a point of time. The more the state is diversified in
cropping the more the change in cropping pattern is expected towards high value
crop.
In this study we have used the Herfindal Index to measure the pace of crop
diversification across states in India during the period 1970-71 to 2009-G&. The
computation of index enable us to make an interstate comparison about the extent
to which the states are able to diversify overtime and the question that whether the
agriculturally advanced states with better provision of irrigation, fertilizer and
assured supply of variety of input usage are able to diversify more than their
poorer counterpart. That means, is the rich-poor gap plays any role in crop
diversification?
173
Regional Variation and Convergence in Agricultural Development in India
Basically the nature of crop diversification is amenable to agro climatic
environment, weather condition, soil quality, temperature etc. Some crops are
better produced in the tropical zone whereas some are better produced in arid zone
and coastal area. So production of a crop is essentially dependent on the weather
condition of the particular region. Despite this, provision of assured irrigation, use
of HYV seeds, use of fertilizers may change the cropping pattern a lot.
Therefore, spatial variation in respect of supply of assured irrigation and others
plays a major role in crop diversification.
TABLE6.7: HERFINDAL INDEX OF CROP DIVERSIFICATION OF INDIAN STATES
1970-71 1980-81 1991-92 2000-o1 2007-o8
Andhra Pradesh 0.494 0.490 0.679 0.673 0.696
Assam 0.415 0.446 0.476 0.490 0.559
Bihar 0.192 0.557 0.355 0.176 0.210
Gujarat 0.717 0.749 0.849 0.885 0.827
Haryana 0.997 0.993 0.975 0.987 0.985
Himachal Pradesh 0.187 0.143 0.235 0.221 0.300
Jammu & Kashmir 0.200 0.261 0.295 0.334 0.341
Karnataka 0.556 0.605 0.661 0.595 0.626
Kerala 0.900 0.913 0.964 0.985 0.992
Madhya Pradesh 0.327 0.655 0.561 0.695 0.692
Maharashtra 0.531 0.528 0.574 0.596 0.638
Orissa 0.531 0.376 0.454 0.557 0.629
Punjab 0.516 0.478 0.428 0.371 0.352
Rajasthan 0.407 0.493 0.593 0.644 0.612
Tamil Nadu 0.503 0.567 0.668 0.608 0.711
Uttar Pradesh 0.272 0.447 0.373 0.354 0.405
West Bengal 0.253 0.352 0.448 0.531 0.568
Source:Author' s calculation
174
Regional Variation and Convergence in Agricultural Development in India
In this section the Herfmdal Index is computed for each state for the years 1970-
71, 1980-81, 1990-91, 2000-01 and 2007-08 respectively. The result of the
calculated HH Index is presented in the table 6.7. HHI is basically a concentration
index and thus the higher value is an indicator of specialization of crop activities.
So, to obtain the index of diversification it is subtracted from 1. The index value
above 0.5 mentions that the crop diversification is high while the value below 0.5
means the reverse that is the rate of crop diversification is slow. In other words it
means concentration or specialization in some crops.
From the result it is obvious that the states like Kerala, Gujarat, Kamataka,
Maharashtra, Madhya Pradesh and Tamil Nadu were able to diversify their crop
from the beginning of the period. Crop diversification is higher in these states.
Further, the states Andhra Pradesh and Rajasthan hastened the process of crop
diversification from the reform period. The same is true for the state West Bengal
from the year 2000-01. The state of Assam began this process recently as the
index value surpassed 0.5 for this state in 2007-08. Moreover, the state of Orissa
initially being diversified slowed down in later years. But since 2000-01 the
process of diversification has started again. On the other hand, the rate of crop
diversification has been slow in the states like Bihar, Himachal Pradesh, Jammu
&Kashmir, Punjab, and Uttar Pradesh. Otherwise it can be said that the above
states are concentrated in the production of some selected crops. Crop
concentration is high for these states. In fact, these states are mainly foodgrain
based.
175
Regional Variation and Convergence in Agricultural Development in India
6.7 Regional Disparity in Agricultural Infrastructure In India: An
Interstate Analysis
India is characterized by wide regional variation m agro-climatic condition.
Output in different region is varied due to varied agro-climatic factors, physical
resource endowment and also varying level of investment in rural infrastructure
and technological innovation. After the advent of new seed fertilizer technology
the improvement in growth in output and yield per hectare in India became
dependent more on irrigation condition, use of inputs i.e. use of fertilizers,
tractors, pumpsets, rural electrification etc. The use of HYV seeds is very much
amenable to the fertilizers and irrigation. The states with better irrigation status
got better results in yield growth than the states with poorer irrigation condition.
The correlation coefficient between yield growth and the quantum and intensity of
inputs used is found to be strong.
This study attempts to examine the disparities prevailing in the use of various
agricultural inputs across states and to investigate the regional variation in
agricultural development. A composite index of agricultural infrastructure has
been constructed by 'Deprivation Method' to explore the disparity in agricultural
infrastructure across the states of India. The detailed methodology of constructing
the index is explained in the chapter 3 {pg-53-55).
For constructing this index eight agricultural development indicators are selected.
They are following
);>Cropping intensity (CI)
);>Percentage irrigated area to GCA(IAGC)
176
Regional Variation and Convergence in Agricultural Development in India
~Fertilizer consumption per hectare of GCA ( fcgc)
~Credit to agriculture (CCA)
~Number of tractors and pumpsets used per 1 000 hectares (TAP)
~Average yield of agricultural land (A Y)
~Road length per 100 sq km (RL)
~Percentage share to total consumption of electricity in agriculture (CELA)
The regional variation in the use of agricultural inputs in India is quite high. A
close examination of the statistics of few selected indicators reveals this striking
phenomenon. Use of fertilizer per hectare varies from 44.41 to 215.73 Kg/beet in
the year 2007-08. The percentage of area irrigated to GCA varies from 2.4
hectare in Assam to 97.7 hectare in Punjab in the same year. In per capita credit to
agriculture the state of Jammu& Kashmir lagged far behind the other states in
India during the period 1981 to 2008. There is a substantial difference in the
percentage use of electricity for agriculture purpose across states. It varies from
0.53% in HP to 40.17% in Haryana . Further, there remains a huge gap across
states in road length in km per hundred square Km.
In order to make an account of whether regional variation across states has
widened overtime in terms of the selected development indicators, two measures
of inequality are employed. They are Coefficient of variation (COV)4 and Gini
concentration coefficient (GINIC) 5.
4 (SD/Mean) * I 00 5
GiniC= 2Cov(y,r)IN y (see Pyatt eta!., 1980)
177
Regional Variation and Convergence in Agricultural Development in India
TABLE6.8: INEQUALITY MEASURES OF AGRICULTURAL INFRASTRUCTURE INDICATORS
DURING THE PERIOD 1981,1991,2001 AND 2007
Coefficient of Variation GINIC
1981 1991 2001 2007 1981 1991 2001 2007
Cl 0.137 0.151 0.163 0.302 -0.075 -0.082 -0.088 -0.139
IAGC 0.668 0.635 0.620 0.617 -0.336 -0.319 -0.334 -0.337
FCGC 0.832 0.603 0.535 0.496 -0.403 -0.330 -0.293 -0.273
CCA 0.733 0.652 0.713 0.677 -0.400 -0.358 -0.395 -0.375
TAP 1.161 1.064 0.862 0.858 -0.540 -0.505 -0.419 -0.030
AY 0.400 0.496 0.434 0.405 -0.213 -0.265 -0.232 -0.224
RL 0.903 0.923 0.855 0.962 -0.378 -0.391 -0.381 -0.100
CELA 0.891 0.701 0.762 0.749 -0.478 -0.388 -0.419 0.211
Source:Author' s calculation
The results of the computed coefficient of variation and GINIC measures are
presented in the table 6.8. The COV and GINIC measures have provided more or
less identical results in exhibiting the inequality trend across states in terms of the
selected development indicators. For cropping intensity and road length in km per
100 sq km a sharp rising trend is observed in both COV and GINIC for the whole
period (1980-81 to 2007-08). Fortunately, in the factors like percentage irrigated
area to GCA,. fertilizer consumption per hectare of GCA, credit to agriculture,
number of tractors and pumpsets used per 1 000 hectares, percentage share to total
consumption of electricity in agriculture, the inequality measures have shown a
downward trend for overall period. Only the factor average yield shows a
fluctuating trend during the time period.
178
Regional Variation and Convergence in Agricultural Development in India
Though it has been revealed by the inequality measures that disparity in terms of
the above mentioned development indicators are diminishing across states
overtime but the formation of index would reveal actually whether it is possible
for any agriculturally poor state to catch up or going ahead of a agriculturally
developed states over the chosen period of time. The computed index of all the
states and the subsequent rank of each state according to the value of the index are
presented in the table 6.9 for the year 1980-81, 1990-91, 2000-01 and 2007-08
respectively. From the ranking of the index appearing in the table it is apparently
clear that the states which was in topmost position in 1980-81 are still remaining
in the same position in the year 2007-08 ie the states occupying the top five
position in 1980-81 are successful to maintain the similar position in the year
2007-08 whereas Assam and Orissa remained as two least developed states
throughout the whole period. Other than these seven states, it has been observed
for few states to change their position in the course of time. For example the state
of Madhya Pradesh being in the lowest position in 1980-81 staged up to lth
position in 2007-08. Again the state Kamataka and Himachal Pradesh being in the
same position in 1980-81 went to different destinations in 2007-08, while
Kamataka triggered to achieve a position of 9th in 2007-08, Himachal Pradesh
trailed behind by getting a position of 15th among the 17 states in the same year.
Moreover, the performance of Jammu& Kashmir has been remained poor
throughout the period. Its position deteriorated from 9th in 1980-81 to 14th in the
terminal year. Also it is noticeable that West Bengal being in the position 11 in
1980-81 improved its performance to reach a position ofih in 2007-08.
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Regional Variation and Convergence in Agricultural Development in India
TABLE6.9: COMPOSITE INDEX OF AGRICULTURE INFRASTRUCTURE OF INDIAN
STATES DURING 1980-81 TO 2007-08 (CIAI)
INDEX RANK 1980- 1990- 2000- 2007- 1980- 2000- 2007-81 91 01 08 81 1990-91 01 08
AndhraPradesh 0.33 0.52 0.57 0.58 5 4 4.5 4
Assam 0.10 0.10 0.10 0.08 16.5 17 17 16 Bihar 0.21 0.29 0.39 0.39 11 8.5 8 8 Gujarat 0.28 0.31 0.32 0.45 7 7 10 6 Haryana 0.60 0.72 0.73 0.76 2 2 2 2 Himachal Pradesh 0.17 0.17 0.16 0.16 13.5 15 15 15 Jammu&Kashmir 0.22 0.22 0.20 0.23 9 12.5 14 14 Karnataka 0.17 0.33 0.41 0.37 13.5 6 7 9 Kerala 0.31 0.28 0.33 0.27 6 10 9 13 Madhya Pradesh 0.10 0.21 0.22 0.31 16.5 14 13 12 Maharashtra 0.21 0.26 0.28 0.32 11 11 11 11 Orissa 0.12 0.13 0.12 0.07 15 16 16 17 Punjab 0.90 0.94 0.85 0.85 1 1 1 1 Rajasthan 0.24 0.22 0.27 0.34 8 12.5 12 10 TamiiNadu 0.51 0.50 0.57 0.54 4 5 4.5 5 UttarPradesh 0.53 0.61 0.61 0.63 3 3 3 3 WestBengal 0.21 0.29 0.42 0.41 11 8.5 6 7
Source:Author' s calculation
Thus the fact: is that contrary to agriculturally poor states, some agriculturally
advanced states have been successful in creating agricultural infrastructures and
thus they are enjoying the benefits of modem agricultural development. This
resulted in the prevalence of disparities across states
6.8 Agricultural Growth in India: A Convergence Analysis
This section deals with the convergence analysis of per capita value of agricultural
output during the period 1970-71 to 2008-09. Following Barro and Salai- Martin's
notions of convergence, sigma convergence and ~ convergence of PCVOA have
been measured. Again in order to measure the factors that are responsible for
creating divergence across states, conditional convergence tests are performed.
180
Regional Variation and Convergence in Agricultural Development in India
Using dynamic panel data model, the regression analysis for testing conditional
convergence has been done using the Generalized Method of Moments technique.
Moreover, to specify the states that are responsible for overall divergence or the
states that are not converging to national average, unit root test has been
performed.
The analysis of growth rate of total value of agricultural output and yield for
Indian states during the period reveals the fact that on an average value of output
for the country grew at the rate of 2.6% whereas the yield grew at a rate of 1.43%
for the whole period. The segregation of the whole period into three phases reveal
that during the post green revolution period both output and yield growth
accelerated but in the post reform period growth rate decelerated for the country
as well as for majority of the states. Moreover, the growth rate achieved at the
national level is not uniform across the states. After the initiation of Green
Revolution disparity among states has, in fact, increased at a high rate. Some
Western and Eastern states got the benefit of better irrigation, sufficient rainfall,
good soil quality etc initially. But after sometime good effects of Green
Revolution spread to all over India and disparity somewhat diminished. After the
introduction of New Economic Reform, in the neoliberal regime, inequality again
started increasing. The estimation of coefficient of variation of value of
agricultural output for the states show that coefficient of variation increased from
0. 79 in 1970-71 to 0.95 in 2002-03 and again marginally dropped to 0.89 in 2005-
06, still it is much higher than the level in 1970-71.
181
c: 0 ·.;::;
"' ·;:
"' > -0 .... c: <II ·;::; :;:: -<II 0 u
Regional Variation and Convergence in Agricultural Development in India
Coefficient of variation of total and per capita value of output
100 90 80 70 60 50 40 30 20 10
0
AT1/ , ._.,...,~ - .
.-t <:t l' o rY'l lDC'lNU'lOO .-t <:tl' ~~r:--ooD?~~q'~c;'9 9 9 OrY'l<Dcf.,NLI'lOO.-t<:ti' O rY'llD r--r--r--,..._oooooommmooo 0'\0'\ C'lC'IC'lC'lO'\C'lC'lmOO O ~MM MMMMMHMr-.JNN
Figure 6.2
- per ca pita va lue of output
- total va lue of output
6.8.1 Sigma Convergence of PCVOA across states of India
Next, an attempt has been made to examine the nature of divergence/convergence
of per capita value of agricultural output in Indian states. In this regard, first of all
we have tested the sigma convergence for PCVOA across states overtime. The
result is displayed in figure 6.3. The figure plots standard deviation of logarithm
of PCVOA of states for the period 1970-71 to 2008-09. The standard deviation
increased from 0.4 in 1970-71 to 0.53 in 2008-09 indicating a trend of divergence.
In the figure it is observed that during 1975-76 disparity increased considerably
but it slowed down during 80's ie in the second phase of green revolution but
from the year 1991-92 it again picked up and continued to rise till 2008-09. In
other words, the test of sigma convergence confirms the divergence of per capita
value of agricultural output across Indian states over time.
Regional Variation and Convergence in Agricultural Development in India
0.6
SIGMA COEFFICIENT OF PER CAPITA VALUE OF AGRICULTURAL PRODUCT
~ o.s~-~ ·;:; 0 .4 y :;:: -~ 0.3 u ro E 0.2 -+-Series l till
·u; 0.1
0
Figure 6.3
6.8.2 Absolute ~ divergence of PCVOA in India and states
In the second step, to reaffirm the divergence in PCVOA, absolute ~ convergence
is tested. For this purpose, four regressions have been fitted-one for whole period,
other two for pre and post reform period and the last one for the last decade i.e.
for the period 2000-01 to 2008-09. The growth rate ofPCVOA in terminal year is
regressed on the value of PCVOA at the initial period. The result for absolute ~
convergence is depicted in the table 6.1 0.
TABLE6.10: REGRESSION RESULT OF ABSOLUTE p CONVERGENCE OF PCVOA
t Period p coefficient value significance R2
1970-71 to 2008-09 9.23E-03 1.146 0.266 0.065
Pre Reform Period
1970-71 to 1990-91 1.40E-02 1.14 0.268 0.064
post reform Period
1991-92 to 2008-09 5.68E-03 2.535 0.02 0.254
2000-01 to 2008-09 6.27E-03 0.776 0.447 0.031
Source: Author's calculation
Regional Variation and Convergence in Agricultural Development in India
The results indicate absolute divergence for all the four periods. Absence of
absolute convergence in PCVOA calls for examination of conditional
convergence.
6.8.3 Conditional p convergence in PCVOA in India
We have estimated the dynamic panel data model by GMM methods. In
explaining divergence in agriculture across states, we have chosen explanatory
variables as the rainfall of different states, composite index of agricultural
infrastructure and literacy rate. It is to be noted that <b~.oS~index is an weighted
index computed from an array of infrastructural variable in agriculture across
states. These are - Cropping intensity (CI), percentage irrigated area to GCA
(IAGC), fertilizer consumption per hectare of GCA (Fertc) credit to agriculture
(CCA), number of tractors and pumpsets used per 1000 hectares (TAP), average
yield of agricultural land (A Y), road length per 100 sq km (RL ), percentage share
to total consumption of electricity in agriculture (CELA). It is mentioned in
previous sections that the weights are determined by applying PCA for the
variables. The use of CIAI facilitates us from avoiding the problem of
multicollinearity. In the present section we use the panel of four years for the
entire period (1980-81 to 2007-08). There are 7 panels. The total number of
observation for 16 states becomes 112 and the GMM estimation method is used.
The regression equation that has been fitted here is
184
Regional Variation and Convergence in Agricultural Development in India
In the GMM estimation analysis (see table 6.11), the coefficient of 1+~ becomes
0.104 ie the estimated coefficient of~ is -0.896 which is significant at 10% level.
This implies conditional ~ convergence. It is revealed from the result that the
coefficient of CIAI is positive and highly significant. This implies clearly that the
factors determining the condition of agricultural infrastructure which are the main
backbone of agricultural development are significantly responsible for widespread
divergence in agriculture across states of India. It has been also observed from the
result that the coefficient on rainfall is positive and significant. It is an expected
result as rainfall has a significant role to play in agriculture. Variations in rainfall
create divergence among states. Moreover, the coefficient of literacy rate is also
significant but at 14% level. The speed of convergence is 0.224 which is also
high. Thus the result of conditional convergence in case ofPCVOA among Indian
states implies that states are converging to their own steady states. Actually the
states are converging to divergent steady states. It can be said that the index of
agricultural infrastructure acts as a package of agricultural infrastructure across
states and thus play a significant role in explaining divergence in PCVOA.
TABLE6.11: RESULT OF GMM ANALYSIS WITH DETERMINANT CIAI, RAIN AND LITERACY RATE
DURING THE PERIOD 198o-81 TO 2007-08
Variable Coefficient t-Statistic Prob.
PCVOA(-1) 0.104089 1.346821 0.182
CIA I 1.356878 3.277818 0.0016
RAIN 0.000136 7.519695 0
LIT 0.002709 1.476619 0.1439
Source :Author' scalculation
Note: On the availability of comparable figures for the chosen variables, 16 states have been
identified and compiled data over a period of 28 years 1980-81 to 2007-08
185
Regional Variation and Convergence in Agricultural Development in India
However, the composite index of agricultural infrastructure (CIAI) encompasses
several indicators of agricultural development. As observed in India, the
variability in agricultural production is mainly responsible to the variations in
agricultural inputs like rainfall, use of fertilizers and irrigation intensity.
Accordingly a renewed attempt has been taken to examine the role of these
individual indicators on the convergence or divergence of agricultural output over
the period 1970-71 to 2007-08 in Indian agriculture.
Using the same equation of regression, we again consider in this case the panel of
four years with 17 states for the period 1970-71 to 2007-08, there are 9 panels and
therefore total number observation becomes 153.
TABLE 6.12: RESULT OF GMM ANALYSIS WITH DETERMINANT RAIN,FERTC,IA AND LIT
DURING THE PERIOD 1970-71 TO 2007-08
Variable Coefficient t-Statistic Pro b. PCVOA(-1) 0.563143 6.701233 0 RAIN 0.268853 6.450424 0 FERTC 0.297185 3.168496 0.002 lA -0.133 -1.5255 0.1299 LIT -0.51982 -3.11569 0.0023
Source:Author' scalculation
Note: On the availability of comparable figures for the chosen variables, 17 states have been identified
and compiled data over a period of 3 8 years 1970-71 to 2007-08
The result (see table 6.12) of the estimation analysis reveals that the estimated
coefficients for ~ is negative ie (-0.437), (1+~=0.563) confirming further
conditional convergence. The coefficient of rain and fertilizer are found to be
positive and significant. Only the coefficient of the factors IA and literacy bears a
negative sign. This may be is attributable to the problem of multicollenearity. This
186
Regional Variation and Convergence in Agricultural Development in India
result implies that supply of input is also a major factor of explaining divergence
in per capita value of agricultural output.
Thus, overall it can be asserted that absolute divergence in PCVOA across states
of India can be rectified and convergence of states can be possible if proper
infrastructure in agriculture can be set up in agriculturally backward states and
thereby the gap can be reduced. In this connection it is also the fact that the
uneven distribution of input is creating a major barrier in bringing a converging
outcome in agricultural production across states.
6.8.4 Unit root test of Divergence: An Interstate Analysis
Historically, the conventional cross sectional regressiOn for determining
convergence has come under criticisms (Quah, 1993, Friedman, 1992). Quah
showed that this bias is similar to Galton's Fallacy whereas Friedman comments
that convergence is indicated by a diminution of the variance among countries
overtime. Several studies now relied on time series information for determining
the existence or lack there of of convergence rather on cross
section.(BenDevid,1993,1994, Bernard and Duarlof,l995,1996), Li and
Papell,1999, Cheung and Pascual,2004). Long run forecast of difference between
any pair of countries PCGDP converges to zero as the forecast horizon grows
according to this new methodology. Within a neoclassical set up the test for
convergence of per capita income is translated to a test for the stationarity of
output differential (see chapter3 for methodology, pg-49-50).
187
Regional Variation and Convergence in Agricultural Development in India
In this context we examine in this section the behavior of each state's per capita
agricultural output differential with the national average overtime and to ascertain
whether there is any noticeable evidence of convergence over time.
The statistical tests of long run convergence hinges on the time series properties
of [In(Yi,t)-In(-Y •t)] where In(Yi,t) and In(-Y •t) are respectively the logarithm of
per capita value of output of ith state and the national average. In this section the
behavior of [In(Y i,t)-In(-Y •t)] has been tested for the period 1980-81 to 2008-09
for 18 states.
TABLE 6.13: PHILIPS-PERRON UNIT ROOT TEST FOR CONVERGENCE OF PCVOA OF
INDIAN STATES
State PP Test Statistics P-value Andhra Pradesh -4.6* 0
Arunachal Pradesh -2.84 0.19
Assam -5.27* 0
Bihar -3** 0.14
Goa -5.78* 0
Gujarat -4.68* 0
Haryana -4.15 0.01
Himachal Pradesh -4.28* 0
Jammu & Kashmir -2.79 0.2
Karnataka -3.7** 0.03
Kerala -2.42 0.36
Madhya Pradesh -1.82 0.36
Maharashtra -4.18** 0.01
Manipur -3.77** 0.03
Orissa -4.89* 0.002
Punjab -4.16 0.01
Rajasthan -6.37* 0
Tamil Nadu -3.48** 0.01
Uttar Pradesh -4.19** 0.01
West Bengal -2.56 0.29
Notes:* and** denote significance at 1 and 5 percent level respectively
Source:Author' s calculation
188
Regional Variation and Convergence in Agriculturel Development in India
The result of the unit root test for convergence shows a diverging pattern across
states in case of agricultural output. The result is depicted in the table 6.13. The
null hypothesis of unit root for Phillips Pheron test is rejected for the states
Andhrapradesh,Assam, Goa,HimachalPradesh,Kamataka,Maharashtra,Manipur, Or
issa,TamilNadu,UttarPradesh whereas the existence of unit root is accepted for the
states Arunachal Pradesh, Bihar, Jammu& Kashmir, Kerala, Madhya Pradesh,
Punjab, Haryana and West Bengal. Therefore, while 10 states are converging
towards national average in PCVOA overtime, the 8 states are following a
different steady state from national average. Interestingly, out of eight states three
states like Punjab, Haryana and West Bengal belong to the category of
agriculturally advanced states while the remaining five states Arunachal Pradesh,
Bihar, Jammu& Kashmir, Kerala and Madhya Pradesh belong to the category of
backward states. Thus our results establish the argument that the wide variety in
agricultural infrastructure among these eight states is responsible for wide
variability in agricultural production and thus making the growth path divergent.
6.9 Analysis of possible reasons for divergence in PCVOA in India
In the preceding analysis it has been observed that the crucial detenninants of
difference in agricultural growth across states of India are agricultural
infrastructure, rainfall as well as individually irrigated area, consumption of
fertilizer, rainfall. The index of agricultural infrastructure has been constructed
taking into account an array of relevant infrastructural variables. It can be said that
the development of agricultural infrastructure is one of the basic responsibility of
the state government. A substantial amount of public investment is required for
the development of agricultural infrastructure. In order to infer about the
189
Regional Variation and Convergence in Agricultural Development in India
distribution of public investment in agriculture across states, the proxy for public
investment ie PCCE has been regressed on CIAI in the fixed effect framework.
The result (see table 6.14) shows a statistically significant positive relationship
between the two.
TABLE 6.14: RELATION BETWEEN GOVERNMENT EXPENDITURE AND AGRICULTURE
INFRASTRUCTURE ACROSS STATES IN INDIA
Variable Coefficient t-Statistic Pro b.
c 2.197639 3.868587 0.0002
CIAI 9.194107 6.002615 0
Source:Author' s calculation
This implies that the distribution of public investment has been made in favour of
agriculturally developed states. Again to know about the distribution of private
investment in agriculture PCLS has been regressed on CIAI. The positive and
significant relation ensures that private investment 1s also biased towards
agriculturally developed states (see table 6.15). It 1s obvious that private
investment is also generally flows to the states where returns would be high. So
making investment in already developed states would be profitable. Therefore the
skewed distribution of public investment along with difference in weather is the
possible reasons for agricultural divergence in Indian states.
TABLE 6.15: RELATION BETWEEN PRIVATE EXPENDITURE AND AGRICULTURE
INFRASTRUCTURE ACROSS STATES IN INDIA
Variable Coefficient t-Statistic Pro b.
c 4.185833 7.27191 0
CIA I 4.005533 2.580844 0.0113
Source:Author' scalculation
190
Regional Variation and Convergence in Agricultural Development in India
Some recent studies by Yang and Zhu (2004) and Tiffm and Irz (2006) find
agriculture as an important cause for economic growth and conclude that
economic growth cannot be sustained without improving agricultural productivity.
To enquire about whether the regional difference in agricultural infrastructure has
any role to play in explaining divergence in PCNSDP, PCNSDP is regressed on
CIAI (see table 6.16).
TABLE 6.16: RELATION BETWEEN PCNSDP AND AGRICULTURE INFRASTRUCTURE
ACROSS STATES IN INDIA
Variable Coefficient t-Statistic Pro b.
c 4.657447 1.907901 0.0651
CIAI 11.85005 1.901838 0.066
Source:Author' scalculation
It is established from regression result that PCNSDP is high where CIAI is high.
This implies a better developed agricultural infrastructure would enhance
PCNSDP of a state. Thus a broad based developed agriculture can contribute to
higher economic growth of a region. It is stated in a study (Johston & Mellor
1961) that linkages of agriculture within the agriculture sector and with the
nonagricultural sectors are crucial to economic growth.
6.10 Summery and Conclusion
In this study an attempt has been made to examine the performance of major
Indian states in respect of agricultural output and thereby disparity prevailing
across the states. The growth rates of agricultural output clearly reveal the fact
that Indian agriculture has passed a phase of outstanding growth during 80's, but
191
Regional Variation and Convergence in Agricultural Development in India
after New Economic Reform the growth momentum has taken a downturn. For
the overall period the states like Haryana, Maharashtra, Rajasthan, West Bengal,
Goa, Himachal Pradesh, Madhya Pradesh, Manipur and Punjab performed well in
terms of growth of value of agricultural output. The kinked growth rate in the
second phase of green revolution reveals that all the states made a remarkable
progress during this period. The best performed states during this period were
Tamil Nadu, West Bengal, Rajasthan, Punjab and Haryana. The states like Bihar,
Orissa, Kerala, Himachal Pradesh and Assam also registered significant
improvement during this period. But the growth performance during the post
reform period experienced a severe slowdown in respect of growth of agricultural
output. The country as well as the states decelerated during the post reform
period. The similar trend was followed in case of yield growth also.
This study also attempts to analyse the cropping pattern of India as well as states
during the period 1970-71 to 2007-08 by looking into the area allocation and crop
area- GCA elasticity. The cropping pattern in India is mainly biased towards
foodgrain crops. But a change in cropping pattern is observed in favour of some
nonfoodgrain crops during the study period. This study reveals that except Punjab
and Bihar the area allocation towards foodgrain crops decreased for all the states
during the study period. In case of non-foodgrain crops the states like Andhra
Pradesh, Gujarat, Haryana, Jammu& Kashmir, Madhya Pradesh, Maharashtra,
Rajasthan, Tamil Nadu and West Bengal experienced an increasing trend of crop
diversification. Moreover, the elasticity measures also imply the similar pattern of
crop diversification for the states as well as for the country. At the country level
192
Regional Variation and Convergence in Agricultural Development in India
elasticity for foodgrain is negative whereas for nonfoodgrain crops it is positive
and greater than one implying a diversion of area allocation towards nonfoodgrain
crops at a higher rate than the change in GCA. In order to explore the actual
extent of crop diversification Herfindal Index has also been computed for the
period 1970-71 to 2008-09. The result confirms that the food grain dominated
states scores low in the crop diversification index and the states like Andhra
Pradesh, Assam, Gujarat, Haryana, Kamataka, Kerala, Madhya Pradesh,
Maharashtra, Orissa, Rajasthan, Tamil Nadu and West Bengal scored high in
Herfindal Index.
In this study attempt has also been made to measure the disparity across states in
terms of agricultural infrastructural factors. The factors like cropping pattern and
road length per 100 sq km indicate an increasing trend in disparity over the period
whereas for the other factors like irrigated area, consumption of fertiliser,
disparity is reducing. In order to analyse the position of states in terms of their
agricultural endowment a composite index has been constructed encompassing
eight agricultural infrastructural indicators .. This index reveals the true picture of
disparity exhibiting that except some exception the states that get proper
agricultural infrastructure during 80's remained at top still in the period of 2007-
08 whereas some weaker states Assam and Orissa lagged behind in getting proper
agricultural infrastructure throughout the period.
An attempt has also been made in this study to analyse convergence or divergence
of per capita value of agricultural output. The conventional cross section ~ and a
coefficient testing confirm that there is absolute divergence and interstate
193
Regional Variation and Convergence in Agricultural Development in India
disparity increased during the period. The analysis in dynamic panel data model
also supports the result of absolute ~ divergence in per capita value of agricultural
output during the period 1970-71 to 2007-08. The result of absolute P divergence
calls for the testing of conditional convergence of per capita value of agricultural
output for the specified period. As mentioned in the study the conditional
convergence testing is performed twice taking into account two different vectors
of independent variables. The conditional convergence is confirmed in both cases.
This result indicates that Indian agriculture is characterized by significant regional
variation in respect of provision of agricultural infrastructure. If this gallant
infrastructural gap in agriculture can be combated then there will certainly be a
convergence across states in agriculture in India. Similarly the significant regional
disparity in respect of assured irrigation, supply of fertilizers as well as literacy
should be reduced to bring into convergence in agriculture in India. However, the
Philips-Perron unit root test reveals that 10 out of 18 states are converging
towards national average whereas the 8 remaining states maintaining a diverging
trend from national average in terms of per capita value of agricultural output.
Thus it can be said in conclusion that performance of states in terms of
agricultural production and yield is lacking the significant acceleration in growth
in recent period which was observed during 80~s. Some economists suggest for
second green revolution for bringing an accelerated performance in agricultural
output and yield in India. But important findings of conditional convergence
reassures that without an inclusive improvement of agricultural infrastructure ,
accelerated development would not have been possible in Indian agriculture. To
194
Regional Variation and Convergence in Agricultural Development in India
mitigate the regional gap in agricultural infrastructure the policy prescription
would be more and more investment in the lagged region, extension of public and
private credit in remote rural areas. Development of research focusing the
development of dry land area, development of technology requiring less water,
less fertilizer and cheap farming and finally implementation of watershed
development approach are necessary for a more balanced and sustainable
agricultural development in the country.
195
Regional Variation and Convergence in Agricultural Development in India
APPENDIX
TABLE6AI: CHANGE IN CROPPING PATTERN OF INDIAN STATES DURING THE
PERIOD 1970-71 TO 2007-08
TABLE6AI1: CHANGE IN CROPPING PATTERN OF INDIAN STATES DURING THE PERIOD 1970-71 TO
2007-08 IN RICE
Table GAll: RICE
States 1970-71 1980-81 1990-91 2000-01 2007-08
ANDHRA PRADESH 26.4 29.4 29.8 31.3 29.4
ASSAM 71.0 66.0 65.5 65.4 60.5
BIHAR 47.8 34.3 45.8 45.9 45.2
GUJARAT 4.9 5.3 5.7 5.6 6.2
HARYANA 5.4 8.9 11.5 17.2 16.6
HIMACHAL PRADESH 10.5 11.6 8.5 8.6 8.1
JAMMU AND KASHMIR 25.6 27.2 25.2 21.9 23.2
KARNATAKA 10.7 10.5 10.2 12.1 11.0
KERALA 29.8 28.0 17.9 11.5 8.3
MADHYA PRADESH 21.3 7.1 8.7 9.4 7.6
MAHARASHTRA 7.0 7.2 7.7 5.6 6.9
ORISSA 53.4 47.9 46.3 56.3 49.4
PUNJAB 6.9 17.5 27.6 32.9 33.2
RAJASTHAN 0.7 1.0 0.8 0.9 0.6
TAMIL NADU 36.4 35.5 30.4 33.3 30.8
UTIAR PRADESH 19.7 20.0 21.4 23.1 22.9
WEST BENGAL 69.9 67.9 66.9 59.6 58.7
INDIA 22.5 22.9 23.4 23.9 22.4
Source:Author' s calculation
196
Regional Variation and Convergence in Agricultural Development in India
TABLE6AI2:CHANGE IN CROPPING PATTERN OF INDIAN STATES DURING THE PERIOD 1970-71 TO
2007-08 IN WHEAT
WHEAT
1970-71 1980-81 1990-91 2000-01 2007-08
Andhra Pradesh 0.1 0.1 0.1 0.1 0.1
Assam 0.7 3.0 2.0 1.7 1.5
Bihar 11.9 15.1 23.9 26.4 27.3
Gujarat 5.7 5.8 3.9 2.7 10.4
Haryana 22.8 27.0 32.5 38.4 38.1
Himachal Pradesh 33.2 37.0 38.5 39.9 37.8
Jammu & Kashmir 21.2 20.3 22.9 24.8 24.5
Karnataka 2.8 2.9 1.6 2.2 2.1
Madhya Pradesh 16.5 15.2 19.8 15.0 18.3
Maharashtra 4.6 5.3 3.1 3.5 5.5
Orissa 0.2 0.8 0.3 0.1 0.1
Punjab 40.5 41.6 43.1 42.9 44.3
Rajasthan 8.8 9.4 9.8 12.0 11.7
Uttar Pradesh 25.5 31.1 34.3 36.2 36.6
West Bengal 5.1 3.7 2.9 4.7 3.6
India 10.9 12.9 12.8 13.5 14.3
Source:Author' s calculation
TABLE6AI3:CHANGE IN CROPPING PATTERN OF INDIAN STATES DURING THE PERIOD 1970-71 TO
2007-0SIN JUTE
JUTE
1970-71 1980-81 1990-91 2000-01 2007-08
Assam 4.7 3.3 2.6 1.7 1.6
Bihar 1.3 1.4 1.9 1.7 1.7
Orissa 0.5 0.5 0.4 0.0 0.1
West Bengal 5.7 8.0 6.7 6.7 6.3
India 10.9 12.9 12.8 13.5 14.3
Source:Author' s calculation
197
Regional Variation and Convergence in Agricultural Development in India
TABLE6AI4:CHANGE IN CROPPING PATIERN OF INDIAN STATES DURING THE PERIOD 197G-71 TO
2007-08 IN COTION
COTTON
States 1970-71 1980-81 1990-91 2000-01 2007-08
Andhra Pradesh 2.4 3.4 5.4 7.5 8.4
Gujarat 15.7 14.6 10.8 15.5 19.3
Haryana 3.9 5.8 10.6 9.1 7.5
Karnataka 9.1 9.5 4.7 4.5 3.1
Kerala 0.3 0.2 0.4 0.1 0.0
Madhya Pradesh 3.4 2.8 3.2 2.6 3.1
Maharashtra 14.6 12.6 13.5 14.2 15.6
Orissa 0.0 0.0 0.1 0.5 0.6
Punjab 7.0 9.6 8.8 6.0 7.7
Rajasthan 1.3 2.1 2.6 2.7 1.7
Tamil Nadu 4.2 3.4 3.7 2.7 3.5
Uttar Pradesh 0.2 0.2 0.1 0.0 0.0
India 4.5 4.5 4.2 4.6 4.8
Source:Author' s calculation
TABLE6AIS:CHANGE IN CROPPING PATIERN OF INDIAN STATES DURING THE PERIOD 1970-71 TO
2007-08 IN SUGARCANE
SUGARCANE States 1970-71 1980-81 1990-91 2000-01 2007-08 Andhra Pradesh 0.9 1.1 1.8 1.8 1.8 Assam 1.2 1.4 1.0 0.7 0.7 Bihar 1.5 0.9 1.8 1.2 1.4 Gujarat 0.4 0.9 1.1 1.7 1.7 Haryana 3.1 2.1 2.9 2.3 2.2 Himachal Pradesh 0.4 0.3 0.2 0.3 0.3 Jammu&Kashmir 0.4 0.3 0.2 0.3 0.3 Karnataka 0.9 1.4 2.3 3.4 2.4 Kerala 0.3 0.3 0.3 0.1 0.1 Madhya Pradesh 0.3 0.3 0.3 0.3 0.4 Maharashtra 1.1 1.3 2.2 2.8 5.4 Orissa 0.4 0.8 0.4 1.3 0.2 Punjab 2.3 0.7 1.4 0.3 0.3 Rajasthan 0.2 0.2 0.2 0.1 0.0 TamiiNadu 1.8 2.8 3.4 5.0 6.1 UttarPradesh 5.8 5.5 7.6 7.7 8.7 WestBengal 0.5 0.2 0.2 0.2 0.2 All India 1.6 1.5 2.1 2.3 2.6
Source:Author' s calculation
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Regional Variation and Convergence in Agricultural Development in India
TABLE6AI6:CHANGE IN CROPPING PATTERN OF INDIAN STATES DURING THE PERIOD 1970-71 TO
2007-0SIN RAPESEED AND MUSTARD
RAPESEED & MUSTARD
States 1970-71 1980-81 1990-91 2000-01 2007-08
Assam 4.9 6.2 7.9 6.7 6.1
Bihar 0.8 0.6 1.1 1.3 1.1
Gujarat 0.3 1.6 3.7 1.8 2.8
Haryana 2.6 5.5 11.5 6.6 9.3
HimachaiPradesh 0.4 0.6 0.9 1.1 0.9
Jammu&Kashmir 2.9 4.1 5.5 5.7 5.0
Karnataka 0.1 0.0 0.0 0.1 0.0
Madhya Pradesh 1.0 0.8 3.2 2.5 2.8
Maharashtra 0.0 0.0 0.0 0.0 0.0
Orissa 0.7 1.9 1.8 0.2 0.2
Punjab 1.8 1.9 1.5 0.7 0.4
Rajasthan 1.5 2.1 13.2 8.0 11.2
UttarPradesh 9.3 1.7 3.5 3.6 3.5
West Bengal 1.5 1.7 4.8 4.8 4.2
All India 2.0 2.3 3.6 2.4 3.0
Source: Author's calculation
TABLE6AI7:CHANGE IN CROPPING PATTERN OF INDIAN STATES DURING THE PERIOD 1970-71 TO
2007-0SIN POTATO
POTATO States 1970-71 1980-81 1990-91 2000-01 2007-08
Assam 0.9 1.1 1.6 2.0 2.0 Bihar 0.9 0.9 1.7 1.9 1.9 Gujarat 0.0 0.1 0.2 0.3 0.6 Haryana 0.1 0.2 0.2 0.3 0.3 Himachal Pradesh 1.9 1.4 1.5 1.4 1.4 Karnataka 0.1 0.1 0.2 0.3 0.5 Madhya Pradesh 0.1 0.1 0.2 0.2 0.2 Maharashtra 0.1 0.1 0.1 0.1 0.1 Orissa 0.2 0.1 0.1 0.1 0.1 Punjab 0.3 0.6 0.4 0.8 1.0 Rajasthan 0.0 0.0 0.0 0.0 0.0 Tamil Nadu 0.2 0.2 0.1 0.1 0.1 UttarPradesh 0.7 1.1 1.5 1.6 2.0 WestBengal 0.9 1.5 2.7 3.3 4.1 All India 0.3 0.4 0.6 0.7 0.8
Source:Author' s calculation
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Regional Variation and Convergence in Agricultural Development in India
TABLE 6AII: AREA EFFECT, YIELD EFFECT AND ELASTICITY OF
INDIAN STATES DURING THE PERIOD 1970-71 TO 2007-08
TABLE 6AIIl: AREA EFFECT, YIELD EFFECT AND ELASTICITY OF INDIAN STATES IN RICE DURING THE
PERIOD 1970-71 TO 2007-08
RICE
States Area Effect Yield Effect total change increase in Area E'
in Production under Crop
Andhra Pradesh -1163.59 10587.19 9423.60 462.80 E>1
Assam 321.02 961.65 1282.67 356.00 0<E<1
Bihar -206.56 708.72 502.17 -1702.10 E>1
Gujarat 281.24 424.16 705.40 270.40 E>l
Haryana 2176.72 661.28 2838.00 806.00 E<O
Himachal Pradesh 3.40 -5.96 -2.57 -16.60 E<O
Jammu & Kashmir 57.28 83.82 141.10 41.20 O<E<1
Karnataka 641.13 939.87 1581.00 256.00 E<O
Kerala -1060.94 383.44 -677.50 -646.20 E<O
Madhya Pradesh 5724.23 -7925.13 -2200.90 -2824.10 E>1
Maharashtra 116.47 504.53 621.00 218.00 E>1
Orissa -48.48 2656.62 2608.13 -59.20 O<E<l
Punjab 7159.23 2286.77 9446.00 2220.00 E>l
Rajasthan -59.93 120.07 60.13 8.80 O<E<l
Tamil Nadu -1893.91 2977.84 1083.93 -896.80 E>1
Uttar Pradesh 1461.86 6184.80 7646.67 1146.00 E>1
West Bengal 1428.11 7469.19 8897.30 759.70 O<E<l
India 10540.06 46414.94 56955.00 6322.40 O<E<1
Source:Author' s calculation
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Regional Variation and Convergence in Agricultural Development in India
TABLE 6AII2: AREA EFFECT, YIELD EFFECT AND ELASTICITY OF INDIAN STATES IN WHEAT DURING
THE PERIOD 1970-71 TO 2007-08
WHEAT
States Area Effect Yield Effect total change increase in Area E'
in Production under Crop
ANDHRA PRADESH -0.47 0.17 -0.30 -7.90 E<O
ASSAM 43.62 18.82 62.43 35.30 E>1
BIHAR 1052.07 1926.33 2978.40 846.90 E<O
GUJARAT 686.10 967.10 1653.20 696.80 E>1
HARYANA 4029.74 4988.26 9018.00 1333.00 E>1
HIMACHAL PRADESH 77.24 180.82 258.07 64.60 E>1
JAMMU AND KASHMIR 117.92 203.28 321.20 94.30 E>1
KARNATAKA 430.60 -328.33 102.27 -29.00 O<E<1
MADHYA PRADESH 749.80 3125.20 3875.00 339.30 E<O
MAHARASHTRA -207.08 1272.08 1065.00 371.00 E>1
ORISSA -11.51 -1.16 -12.67 -7.40 O<E<1
PUNJAB 3433.32 6358.01 9791.33 1189.00 E>1
RAJASTHAN 1470.73 3126.84 4597.57 1113.80 E>1
UTIAR PRADESH 5943.68 11127.65 17071.33 3208.00 E>1
WEST BENGAL 116.44 -219.94 -103.50 -7.40 E<O
INDIA 16671.52 40176.48 56848.00 9797.60 O<E<1
Source:Author' s calculation
TABLE 6AII3: AREA EFFECT, YIELD EFFECT AND ELASTICITY OF INDIAN STATES IN JUTE DURING THE
PERIOD 1970-71 TO 2007-08
JUTE
States Area Effect Yield Effect total change increase in Area E'
in Production under Crop
ASSAM -612.43 273.53 -338.90 -69.00 E<O
BIHAR 25.71 468.69 494.40 -10.80 O<E<1
ORISSA -293.08 12.41 -280.67 -38.20 O<E<1
WEST BENGAL 1801.83 3386.77 5188.60 202.80 E>1
INDIA 546.47 4149.53 4696.00 65.10 O<E<1
Source: Author's calculation
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Regional Variation and Convergence in Agricultural Development in India
TABLE 6AII4: AREA EFFECT, YIELD EFFECT AND ELASTICITY OF INDIAN STATES IN COTTON DURING THE
PERIOD 1970-71 TO 2007-08
COTTON
States Area Effect Yield Effect total change increase in Area E•
in Production under Crop
ANDHRA PRADESH 1769.74 1609.26 3379.00 817.80 E>l
GUJARAT 617.68 4732.42 5350.10 771.80 E>l
HARYANA 1059.61 424.59 1484.20 290.00 E>l
KARNATAKA 1256.01 1560.04 304.03 -592.30 O<E<1
KERALA -6.30 1.10 -5.20 -6.00 E<O
MADHYA PRADESH -50.45 640.25 589.80 -61.60 E>1
MAHARASHTRA 651.87 3590.13 4242.00 383.00 E>l
ORISSA 109.44 15.86 125.30 49.80 E<O
PUNJAB 192.59 1416.41 1609.00 207.00 E>1
RAJASTHAN 454.38 132.46 586.83 144.20 E>1
TAMIL NADU -153.91 48.31 -105.60 -110.30 E>1
UTIAR PRADESH -44.36 4.70 -39.67 -47.70 E<O " INDIA 2872.09 14640.91 17513.00 1808.70 E>1
Source:Author' s calculation
TABLE 6AIIS: AREA EFFECT, YIELD EFFECT AND ELASTICITY OF INDIAN STATES IN SUGARCANE DURING
THE PERIOD 1970-11 TO 2007-08
SUGARCANE States Area Effect Yield Effect total change increase in Area E•
in Production under Crop AP 5067.53 1132.17 6199.70 127.40 E>1 Ass -291.90 -11.10 -303.00 -6.00 E<O Bihar 620.96 -2047.36 -1426.40 -53.30 E>1 Gujarat 11479.53 1863.77 13343.30 173.60 E>1 Hary 136.69 -1453.69 -1317.00 -15.00 E<O HP -3.61 6.31 2.70 -0.70 E<O J&K -14.42 -6.98 -21.40 -1.90 E<O Kar 12710.66 2163.34 14874.00 209.00 E<O Kerala -370.43 250.43 -120.00 -6.00 E<O MP -475.17 -839.83 -1315.00 14.20 E<O Maha 44223.13 -8180.13 36043.00 876.00 E>1 Orissa -907.17 -73.83 -981.00 -10.20 O<E<1 Punjab -208.16 -391.84 -600.00 -18.00 E<O Rajasthan -948.55 147.55 -801.00 -26.60 E<O TN 18619.45 3157.55 21777.00 219.20 E<O UP 34259.89 20116.11 54376.00 834.00 E>l WB -3989.55 3319.55 -670.00 -21.10 E<O All India 69713.26 75172.74 144886.00 2440.20 E>1 Source: Author's calculation
202
Regional Variation and Convergence in Agricultural Development in India
TABLE 6AII6: AREA EFFECT, YIELD EFFECT AND ELASTICITY OF INDIAN STATES IN RAPESEED AND
MUSTARD DURING THE PERIOD 1970-71 TO 2007-08
RAPESEED & MUSTARD
States Area Effect Yield Effect total change increase in Area E'
in Production under Crop
ASSAM 39.62 15.38 55.00 98.00 E>1
BIHAR 10.36 22.97 33.33 1.50 E<O
GUJARAT 204.08 113.92 318.00 302.40 E>1
HARYANA 688.13 154.54 842.67 469.00 E>1
HIMACHAL PRADESH 1.25 0.98 2.23 4.90 E>1
~AMMU AND KASHMIR 68.05 -57.42 10.63 31.70 E>1
KARNATAKA -0.26 -0.01 -0.27 -1.60 O<E<1
MADHYA PRADESH 375.72 256.85 632.57 374.20 E<O
MAHARASHTRA 2.61 0.82 3.43 4.50 E>1
ORISSA -15.38 -7.58 -22.97 -39.10 O<E<1
PUNJAB -29.62 16.95 -12.67 -75.00 E<O
RAJASTHAN 2507.49 773.75 3281.23 2242.20 E>1
UTTAR PRADESH -146.46 -241.24 -387.70 -1302.20 E<O
WEST BENGAL 181.82 97.48 279.30 305.00 E>1
INDIA 2398.75 2826.25 5225.00 2502.50 E>1
Source:Author' s calculation
TABLE 6AII7: AREA EFFECT, YIELD EFFECT AND ELASTICITY OF INDIAN STATES IN POTATO DURING THE
PERIOD 1970-71 TO 2007-08
POTATO
States Area Effect Yield Effect total change increase in Area E'
in Production under Crop
ASSAM 177.87 558.50 50.50 E>1
BIHAR 3713.73 198.37 3912.10 51.50 E<O
GUJARAT 1325.82 26.28 1352.10 68.00 E>1
HARYANA 389.72 36.48 426.20 15.80 E>1
HIMACHAL PRADESH -7.16 94.96 87.80 -4.10 E<O
KARNATAKA 535.12 35.18 570.30 52.00 E<O
MADHYA PRADESH 572.29 114.61 686.90 29.50 E<O
MAHARASHTRA 90.11 43.09 133.20 3.00 E>1
ORISSA -9.12 -38.98 -48.10 -12.10 O<E<1
PUNJAB 1450.53 334.57 1785.10 62.00 E>1
RAJASTHAN 25.27 62.63 87.90 9.80 E>1
TAMIL NADU -19.73 14.33 -5.40 -7.90 E>1
UTTAR PRADESH 5262.57 4061.33 9323.90 343.00 E>1
WEST BENGAL 6917.96 2064.84 8982.80 338.80 E>1
INDIA 18865.10 10718.80 29583.90 1071.10 E>1
Source:Author' s calculation
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Regional Variation and Convergence in Agricultural Development in India
TABLE6AIII: RESULT OF PRINCIPAL COMPONENT ANALYSIS OF CONSTRUCTION OF CIAI
TABLE 6AIII1: TOTAL VARIANCE EXPLAINED OF CIAI
1980-81 1990-91 2000-01 2007-08
Comp1 70.098 74.76 68.41 65.04
Comp2 17.913 16.34 20.16 15.49
Comp3 11.253 10.22 14.52 9.23
Source:Author' s calculation
TABLE 6AIV: COMPONENT MATRIX OF CIAI
1980-81 1990-91 2000-01 2007-08
Variables Comp1 Comp2 Comp1 Comp2 Comp1 Comp2 Comp1 Comp2
Cl 0.435 0.235 0.336 0.818 0.41 0.72 0.515 0.229
IAGC 0.919 -0.189 0.906 0.009 0.89 0.0061 0.851 -0.0069
FCGC 0.935 6.59E-02 0.891 -0.0064 0.899 0.111 0.894 0.0001
CCA 0.42 -5.20E-02 0.493 -0.73 0.495 -0.613 0.496 -0.125
TAP 0.965 0.141 0.933 0.0031 0.896 0.0045 0.896 0.0063
AY 0.468 0.793 0.603 0.698 0.579 0.499 0.4 0.782
RL 0.214 0.857 0.009 0.394 0.194 0.528 0.0023 0.857
CELA 0.771 -0.502 0.751 -0.583 0.482 -0.782 0.663 -0.585
Source: Author's calculation
204