CHAPTER-VII AGRICULTURE PRODUCTION AND EXPORTS OF GUJARAT
Transcript of CHAPTER-VII AGRICULTURE PRODUCTION AND EXPORTS OF GUJARAT
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CHAPTER-VII
AGRICULTURE PRODUCTION AND EXPORTS OF GUJARAT
7.1 Introduction
The economy of Gujarat is one of the fastest growing economies among all Indian states. It also
has the distinction of achieving higher agricultural growth compared to national average.
Geographical location of Gujarat has endowed it with longest coastal line among all states in
India to international trade, facilitating easier access to international trade. In spite of
industrialization majority of population in Gujarat is dependent on agricultural for its livelihood.
The agriculture production in turn depends on many seasonal factors, resulting in variability of
production. This uncertainty in agricultural production has led to exclusion of rural population
from receiving benefits of economic liberalization and high growth of GDP in India. In such a
scenario it becomes imperative to take steps to increase production improves value added
production in agricultural sector for improving income levels of population dependent on it.
Promoting exports from agriculture sector will lead to improvement in incomes of rural
population, allowing them to share gains and benefits from economic development. The
agriculture production in Gujarat and export performance of selected agriculture commodities
from Gujarat has been studied and presented here.
Export plays a significant role in economic development of a country by enabling it not only to
pay for its import requirement but also lead to multiple expansions in national income through
foreign trade multiplier. The production of most of the agricultural crops in Gujarat has been
increasing over the years; it is the export of these crops that has significantly picked up during
the last decade. Gujarat has an edge in production of castor, cumin, fennel, isabgol, sesamum,
groundnut, mango, garlic, dehydrated onion, fish and seafood and cotton in the international
market (GITCO, 2009).However, agriculture productivity and exports are considerably low in
international market. Substantial improvement of economy needs to be done to take advantage of
opportunities in international market to improve condition of population dependent on
agriculture.
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Since 1991 trade policy reform measures were aimed at integration of industrial, trade and
exchange rate policies to enhance the efficiency in the economy. The object of these measures
has been aimed to eliminate discretionary controls on international trade transactions, reduce the
nominal as also the effective protection available to domestic industry, and to bring domestic
prices closer to world prices. In this context, it is important to distinguish between three
dimensions of trade policy reforms. First - a rapid dismantling of quantitative restrictions on
imports and exports; Second - a substantial reduction of taxes and subsidies on trade and Third -
several adjustments in the exchange rate. The growth in area, production and productivity of
selected agricultural has been studied during pre WTO period of 1980-81 to 1994-95 and post
WTO period 1995-96 to 2008-09 has been under taken to study changes in trend and possible
impact of WTO implementation, The same is also undertaken for selected agro processed
products in Gujarat, subsequent to trend analysis, changes in export of the selected agro products
has been under taken and the same has been presented below here. The agriculture commodities
selected are the ones which have prominent contribution to agriculture exports from Gujarat.
Thus, agriculture commodities selected are Groundnut, Cotton, Castor, Sesamum, Tobacco,
while agro processed products included for study and analysis are castor oil, sesame, Tobacco,
manufactured Pickle &chutney, process fruit juice. For Gujarat, agriculture sector performance
has been analyzed by trend break analysis to show whether major land mark events such as
commencement of economic liberalization in 1991 and implementation of WTO by various
authors. A brief of this has been studied and presented below.
7.2 India’s Agricultural Trade
India's global agricultural trade during pre and post-WTO period has been fluctuating. On an
average per annum, India's global agricultural exports were rupees Crores 9740.5 during pre-
WTO period (1990-95), which increased to rupees72245.30 Crores during post-WTO period
(1995-2009). The coefficient variation of agro export was 70.07 percent. The growth of
agricultural exports has been lower during the pre-WTO period (11 per cent) as compared to the
post-WTO period (18 per cent). Index of agricultural exports increased by 56.3 per cent. This is
an encouraging trend to India's agricultural exports during the post-WTO period. The coefficient
variation of Total national exports was 521 percent (Ref. Table: 7.1) compared to agro exports it
was 70 percent.
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Table 7.1: Export & Import of Agri-Commodities to the total National export & import
(1990-2009)
year Agricultural Imports
Total National Imports
%age Agriculture Imports to
Total National Imports
Agriculture Exports
Total National Exports
%age Agriculture Imports to
Total National exports
1990-91 1205.86 43170.82 2.79 6012.76 32527.28 18.49 1991-92 1478.27 47850.84 3.09 7838.04 44041.81 17.8 1992-93 2876.25 63374.52 4.54 9040.3 53688.26 16.84 1993-94 2327.33 73101.01 3.18 12586.55 69748.85 18.05 1994-95 5937.21 89970.7 6,60 13222.76 82673.4 15.99 1995-96 5890.1 122678.14 4.8 20397.74 106353.35 19.18 1996-97 6612.6 138919.88 476 24161.29 118817.32 20.33 1997-98 8784.19 154176.29 5.7 24832.45 130100.64 19.09 1998-99 14566.48 178331.69 8.17 25510.64 139751.77 18.25 1999-00 16066.73 215528.53 7.45 25313.66 159095.2 15.91 2000-01 12086.23 228306.64 5.29 28657.37 201356.45 14.23 2001-02 16256.61 245199.72 6.63 29728.61 209017.97 14.22 2002-03 17608.83 297205.87 5.92 34653.94 25513728 13.58 2003-04 21972.68 359107.66 6.12 37266.52 293366.75 12.7 2004-05 22811.84 501064.54 4.55 41602.65 375339.53 11.08 2005-06 21499.22 660408.9 3.26 49216.96 456417.86 10.78 2006-07 29637.86 840506.31 3.53 62411.42 571779.28 10.92 2007-08 29906.24 1012311.7 2.95 79039.72 655863.52 12.05 2008-09 36736.52 1340587.78 2.74 85961.82 839977.96 10.23
Source: Govt. of India (2009)
Similarly, India's global agricultural imports also increased from rupees 2764.984 Crores during
pre-WTO period (1990-95) to rupees18602.58 Crores during post-WTO period (1995-2009) on
an average per annum. The coefficient of variation of Agro imports was 73.5 percentage. (Ref.
Table: 7. 1B) However, the increase in global agriculture imports was more than exports
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during post-WTO period. During pre WTO period growth rate of agriculture imports was 43 per
cent during the post-WTO period it was 13.51per cent in case of agro exports as shown in
Table7.1A).
Table 7.1A: Regression Result: Export & Import Values of Agro-Commodities to the total National export & import (1990-2009).
Imports/Exports Year Intercep
t Slope R2
CGR percentag
e
Agri imports
Pre-WTO
1990-1995
6.6 0.36 0.85 43
Total National Imports 10.4 0.18 0.98 20.8
Agri EXports 8.5 0.2 0.96 22.7
Total National Exports 10.1 0.23 0.99 26.1
Agri imports
Post-WTO
1996-2009
8.1 0.12 0.91 13.5
Total National Imports 10.4 0.18 0.96 20.04
Agro Exports 9.18 0.1 0.92 11.1
Total National Exports 10.6 0.17 0.25 18.5
Agro imports
Overall Periods
1990-2009
7.4 0.17 0.9 19.2
Total National Imports 10.4 0.18 0.98 19.8
Agro Exports 8.85 0.12 0.95 13.8
Total National Exports 8.85 0.12 0.95 13.8
Calculation from secondary data
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Table 7.1B: Export & Import Values of Agro-Commodities to the total National exports & import (1990-2009) Average, Co-efficient of variation
Calculation from secondary data
It is clear from the above analysis that liberalization under WTO has rather increased India's
global agricultural imports more than its exports. Indian agriculture sector has been adversely
affected during post-WTO regime. Compound growth of agro imports pre WTO time was 43
percent compared to post WTO growth rate of 13.5 percent, but overall period agro imports
growth was reached to 19.2 percent.
7.2.1 Agriculture in Gujarat:
Geographically Gujarat is endowed with longest coastal line among all states in India, facilitating
easier access to international trade. In spite of industrialization majority of population in Gujarat
is dependent on agriculture for its livelihood. The production of most of the agriculture crops in
Gujarat has been increasing over the years; however it is the export of these crops that has
significantly picked up during the last decade. Since 1991 trade policy reform measures were
aimed at integration of industrial, trade and exchange rate policies to enhance the efficiency in
the economy.
Average annual Growth Rate in Gujarat (GSDP) during the year 1980-81was 6.3 percent, it has
reached to 10.2 percent in the year 2009-10. The total GSDP in the state always registered a
positive annual growth throughout the 30 year period of study, agricultural GSDP did not show
statistically significant trend rate of growth during the first three decades. Before, 1990-91 the
terms of trade were rising for the non-agriculture sector and after 1990-91; the same was
declining.
Average 14434.79 347989.6 32497.64 790893
Mean 759.7259 18315.24 1710.402 41625.95
SD 10613.83 365322.4 22772.44 4123983
CV 73.52948 104.9808 70.07413 521.4338
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The agriculture commodities selected for the study on the basis of substantial contribution of
Gujarat to all India production are groundnut, sesamum, cotton, tobacco (unmanufactured),
cumin, fennel. Similarly, based on same reason agro process commodities selected for study of
export are Tobacco (manufactured), Process fruit juice, Pickle and chutney, Mango pulp and
Castor-oil.
The Gujarat government has set up Gujarat agro industries corporation limited (GAICL) for
providing assistance to food processing units. The government of India has initiated National
Mission of Food Processing (NMFP), realizing the need for processing of food items show that
farmers and primary sectors can improve its income.
7.2.2 Growth Statistics of Gujarat - Agriculture v/s Total GSDP
The structural breaks in the agricultural GSDP and total GSDP series in Gujarat state are
calculated The Quandt method using OLS (ordinary least squares) technique :
In Y = β0 + β1t + β2 (t - ti*) D1 + β3 (t - tj*) D2 + e
Where D1=l for t>t1*
D2 = 1 for t > t2* are two dummy variables and t, * and t2* are break dates.
It can be seen from Table 7.1 the trend rates for agricultural real incomes in the first three
decades in Gujarat turn out to be statistically insignificant and hence the null hypothesis about
the trend rate = 0 cannot be rejected. None of the trend rates during the first three decades is high
and actually, for the 1980s it turns out to be negative and insignificant.
The table shows average annual growth rate (Agriculture + Animal Husbandry) during the year
1980-81 was 12.4 percent, it has reduced to 9.5 percent in the year 2009-10. In case of Average
annual Growth Rate (GSDP) during the year 1980-81was 6.3 percent, it has reached to 10.2
percent in the year 2009-10.
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Table 7.2 Growth Statistics for Gujarat - Agriculture v/s Total GSDP
Periods Average annual growth
rate
Standard
Deviation
Cofficient of
Variation
Trend
Rate (β)
Average. Annual
Trend Rate
Agriculture+ Animal Husbandry
1980-81 to 1989-90 12.4 61.51 4.96 -0.01 1.2
1990-91to 1999-2000 4.9 31.50 6.41 0.05 4.7*
2000-01 to 2008-2009 11.0 21.48 1.96 0.09 9.6*
2000-01 to 2009-2010 (A) 9.5 20.56 2.16 0.08 8.0*
Total GSDP
1980-81to 1989-90 6.3 15.01 2.39 0.05 4.6*
1990-91to 1999-2000 7.4 11.16 1.50 0.08 8.1*
2000-01to 2008-09 10.3 2.83 0.27 0.10 10.7*
2000-01to 2009-2010 (A) 10.2 2.65 0.26 0.10 10.6*
* Statistically significant at 5% level
Source: Shah et al. (2010) & Has Agriculture in Gujarat shifted to high growth path by Ravindra H .
Dholakia page no 5
During 1990s Gujarat shows for the first time a statistically significant trend growth rate of
4.7percent pa. With considerably low extent of fluctuations compared to previous decades. The
last decade (2000-01 to 2009-10) shows both in trend growth rate as well as the lower degree of
fluctuations raising the statistical significance level of the estimate. Log-linear trend rate of
growth estimated on the basis of all observations in the series still gives a highly significant
growth rate of 8 percent pa in real terms during the last decade. Gujarat agriculture in recent
decades almost keeps intact even after two consecutive droughts in the state.
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7.2.3 Structural Breaks in Gujarat Agriculture and Total GSDP
The structural breaks have been identified by empirical studies in India using two distinct
methods: Quandt method (1980) by using regression models. The Bai-Perron method was used
for Indian GDP series. While both the methods statistically find the break dates from the series
itself without the structural break dates, the Bai-Perron method allows simultaneous
consideration of the possibility of multiple breaks that Quandt method does not fully satisfies,
these methods are used to identify the structural breaks in the Agricultural GSDP and total GSDP
series in Gujarat state.
In Y = β0 + β1t + β2 (t - ti*) D1 + β3 (t - tj*) D2 + e
Where D1=l for t>t1*
D2 = 1 for t > t2* are two dummy variables and t, * and t2* are break dates.
After the necessary iterations and trials, the final results for the Quandt method for the total real
GSDP and real agricultural GSDP for Gujarat state considering the 30 year data from 1980-2010
are as follows
The Bai-Perron method with BIC criteria as suggested by Wang (2006) identifies three structural
breaks in real GSDP series but in the Quandt method two structural breaks have been studied.
7.2.4 Real GSDP (at constant 1999-00 prices)
In Y = 2.6817 + 0.4009(t) + 0.0328(t-7) D1+0.0226(t-23) D2
(0.0017) (0.0010) (0.0040)
R2 = 0.989.
For 1980-81, t=l and for2009-10(A),t = 30
Figures in brackets represents Standard Errors of parameters, and all estimated values are significant at 1 percent level of significance.
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7.2.5 Real Agricultural GSDP (at constant 1999-00 prices)
lnY = 3.8027 + 0.0244(t) + 0.0337(t - 22)D 1
(0.0025) (0.0192)
R2 = 0.792.
For 1980-81, t = 1, and for 2009-10(A), t = 30.
Figures in brackets represent Standard Errors of parameters. The basic trend rate is significant at
1 percent level of significance, but the shift parameter (accelerator) is significant only at 10
percent level of significance.
The maximum number of regimes is given by the number of data points (= 30 in our case)
divided by 8 (= 4 in our case). Therefore, up to 4 break dates are considered simultaneously. The
procedure considers the break points in a sequence - 0, 1, 2, 3, 4 in the series and for each run,
generates statistics called Bayesian Information Criterion (BIC) and the familiar residual Sum of
Squares (RSS). Then, the run for which these two criteria are minimized is picked up as the
optimal run and the corresponding number of structural break points is identified as the
endogenously determined point. This method is applied to both total real GSDP and real
agricultural GSDP series in Gujarat over the 30 year period.
7.2.6 Terms of Trade in Gujarat Agriculture
The inter-sectorial terms of trade in a state economy is best measured with the help of GSDP
data by sectors at current and constant prices. GSDP deflators by agricultural and non-
agricultural sectors in Gujarat, and terms of trade defined as the ratio of the two series, i.e.
PNA/PA- trends in terms of trade in Gujarat over the 30 years.
It can be seen that the series fluctuates considerably over time, and shows some broad
decreasing, increasing and again decreasing trends over the three decades. The long-term trends
in the terms of trade in Gujarat, there would be three distinct phases, viz.
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1. 1980-81, when the PNA/PA was declining;
2. 1990-1991, when the PNA/PA was rising; and
3. 2000 -2010, when the PNA/PA was again declining. The sectoral terms of trade in the
domestic economy is related with price incentives to producers, savings and investments
in the economy.
The total GSDP in the state always registered a positive significant annual growth throughout the
30 year period, agricultural GSDP did not show statistically significant trend rate of growth
during the first three decades .The trend rate of total GSDP also was considerably low during the
first two decades in Gujarat. In the last two decades also Gujarat's total GSDP showed
substantial acceleration.
The structural break in PNA/PA series found around 1990-91 exactly coincided with the turn of
agriculture in the state. Before, 1990-91, the terms of trade were rising for the non-agricultural
sector and after 1990-91; the same was declining over time. Thus, agriculture was relatively
losing before 1990-91 and was gaining after 1990-91 in Gujarat. This seems to have spurred
positive and significant growth of agriculture in the state after 1990-91. By changing cropping
pattern in favor of high value crops, bringing more area under plough, increasing cropping
intensity, increasing investments in modern inputs and machinery, increasing irrigation, and
steps for better technology, marketing, storage, etc. This suggests lagged relationship between
prices and agriculture output supply. With increased agricultural supply, total GSDP is also
expected to increase.
The following equations show:
ln (Agri. + AH) = a + b ln (PNA/PA)-1, + u; and
ln(GSDP) = c + d ln (PNA/PA) -1 + v
Where u and v are random errors, and a & c are intercepts, and b & d are elasticity
parameters. The estimates of these equations through OLS regressions are:
ln (Agri.+AH) = 9.63 - 0.667 ln (PNA/PA) -1 + e
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P - values: (3.2E-57) (0.190): R Square = 0.036
And
ln (GSDP) = 11.11-1.775 ln (PNA / PA)-1 + e
P - Values: (2.1E-49) (0.042): R Square = 0.085
These equations are estimated with the 30 years data on Gujarat. It is seen that the first of these
equations on agricultural GSDP is statistically not a good fit at all and the R2 is not significant
even at 10 percent level. However, the second one on the total GSDP is statistically significant at
5percent level with expected negative sign. The estimate for elasticity of supply with one year
lag turns out to ‘be (-) 1.8, implying that one percent increase in relative agricultural prices
would lead to 1.8 percent increase in the total real GSDP in the state on an average in the long
run. The equation for agriculture GSDP does not fit the data for all the years well, perhaps
because there might be substantial changes in the relationship during different phases.
It can be seen from the above price-wise regression results that during 1980-90, the elasticity was
positive and not significant, but during the latter period of 1990-2010, the elasticity was negative
and significant. It is because of such a sharp contrast in the two phases that the overall regression
for the whole 30-year period turned out to be statistically insignificant.
7.2.7 Cropping pattern in Gujarat
The changes in cropping pattern in Gujarat have been presented in table 7.3. It reveals that the
area under total food grains has declined from 49 percent from the triennium 1980-83 to 38
percent during triennium 2005-08. During the same period area under total cereals declined from
44.52 percent to 30.42 percent. While the area under rice has more or less remained around 5 to
6 percent, the area under wheat has significantly increased from 4.95 percent in 1980-83 to 9.67
percent in 2005-08. The area under bajra has declined sharply from 18.67 percent to 8.43
percent. Among cereals, the sharpest decline in area has been observed for jowar from 10.18
percent in 1980-83 to 1.22 percent in 2005-08. The percent area under oilseeds has slightly
improved from 24.59 per cent in 1980-83 to 26.17 percent in 2005-08. While the percentage area
under groundnut, a major cash crop of Gujarat, has declined from 19.76 to 17 percent, other
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oilseeds crops like castor, sesamum and rapeseed and mustard have made substantial gains. Area
under total pulses has marginally increased from 7.86 percent to 7.35 percent.
Table: 7.3 Cropping Pattern of Gujarat – (1980-83 to 2005-08)
(Area as Percent to Gross Cropped Area)
S.NO Crops Triennium Average
1980-83 1990-93 2000-03 2005-08
1 Rice 5.43 6.15 6.32 6.40 2 Wheat 5.90 5.45 4.01 9.67 3 Jowar 10.18 5.90 2.11 1.22 4 Bajra 13.78 13.39 10.80 8.43 5 Maize 2.94 3.53 4.56 4.01 6 Ragi 0.47 0.30 0.25 0.19 7 Kodra 0.66 0.14 0.04 0.00 8 Barley 0.12 0.12 0.12 0.00 9 Other Cereals 0.74 0.40 0.27 0.49 10 Total Cereals 40.21 35.39 28.44 30.42 11 Gram 0.96 0.98 0.41 1.62 12 Tur 2.85 3.99 3.24 2.37 13 Other Pulses 4.05 3.74 3.47 3.36 14 Total Pulses 7.86 8.71 7.11 7.35 15 Total Food Grains 48.08 44.10 35.55 37.77 16 Groundnut 19.76 17.71 17.77 17.06 17 Castor 1.78 3.31 3.72 3.10 18 Sesamum 1.22 2.34 3.25 3.00 19 Rape & Mustard 1.77 3.24 2.05 3.02 20 Total Oil Seeds 24.59 26.81 27.01 26.17 21 Cotton 14.04 10.70 15.93 20.54 22 Tobacco 1.09 1.30 1.10 : 0.51 23 Sugarcane 1.02 1.62 2.43 1.93 24 Gross Cropped Area
in '00 Hact. 100.00
(108992) 100.00
(106952) 100.00
(106395) 100.00
(110446)*
*Estimated average Note: Figures in bracket denote GCA in 00' Hact.
Source: Directorate of Agriculture, Krishi Bhavan, GoG, Gandhinagar, 2009
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The average area under cotton, a major cash crop of Gujarat, has fluctuated over the decades.
However, the introduction of Bt. Cotton has resulted in rise in its area from 14.04 percent in
1980-83 to 20.54 percent in 2005-08.
Cropping pattern in Gujarat indicates that it is quite distinct from what has prevailed at the all
India level. Some structural rigidity has been observed in area allocation at the national level. At
the all India level, food grain crops continued to claim around 75 percent of the gross cropped
area for almost the first three decades of planning (1951-80). Thereafter, even though it had
gradually declined, it was as high as 64 percent in 2003-04. In contrast, Gujarat had only 47
percent of its GCA under food crops during 1980-83, which has gradually declined to 38 percent
only by 2005-08. (Ref. Table 7.3).
The scope for increasing net area sown may be limited; the gross cultivated area can increase
with increasing irrigation creating opportunities for double cropping. It has been observed in
recent years that recharging of wells and construction of check dams, farm ponds and deepening
of village tanks have helped in increasing rabi cultivated area in Saurashtra, Kutch and North
Gujarat by 6 to 8 lakh hectares or about 5 to 7 percent of cultivated area.
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Table: 7.4 Average Yield Rates of Crops in Gujarat
(Yield in Kg./Hact)
Sr. No.
Crops 1980-81 to 1984-85
1985-86 to 1989-90
1990-91 to 1994-95
1995-96 to 1999-06
2000-01 to 2004-05
2005-06 to 2008-09
1 Rice 1343 1157 1443 1636 1476 1814 2 Wheat 2123 1957 2234 2228 2372 2686 3 Jowar 570 408 508 776 927 1161 4 Bajra 970 758 851 1066 1 162 1267 5 Maize 1244 1016 1157 1461 1425 1207 6 Ragi 897 682 869 991 925 984 9 Other Cereals 580 502 467 601 669 1099 10 Total Cereals 1108 901 1152 1402 1467 1828 11 Gram 868 577 659 721 747 983 12 Tur 751 591 767 827 645 997 13 Other Pulses 584 388 426 460 456 526 14 Total Pulses 683 497 606 652 564 781 15 Total Food Grain 1037 828 1046 1252 1287 1623 16 Groundnut 791 730 706 984 11 17 1477 17 Castor 1280 1 188 1660 1884 1544 1926 18 Sesamum 331 278 322 441 440 385 19 Rape & Mustard 1315 1205 1173 1190 1288 1433 20 Total Oil Seeds 846 796 839 1080 1098 1413 21 Cotton 213 206 260 317 287 558 22 Tobacco 1731 1610 1741 1740 1710 1607 23 Sugarcane 7220 7056 8269 7289 6991 7549
Source: Directorate of Agriculture, Government of Gujarat, Gandhinagar, 2009 Average Yield Rates
The table: 7.4 shows average yield rates of crops in Gujarat. As production performance is
influenced by both changes in area as well as productivity, a better indicator of progress will be
changes in yield rates of crops over the period. Data on changes in five yearly average yield rates
during 1980-85 to 2005-09 are provided in table 7.4. The data show that Gujarat farmers have
been scaling higher peaks of productivity over time. Among cereals, the highest peaks in average
productivity have been achieved for rice, wheat, jowar and bajra during 2005-09. Only maize
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crop had achieved higher average productivity level during 1995-2000. Among pulses, gram, tur
and all pulses have achieved highest peak in average productivity during 2005-09.
Among oilseeds, groundnut, castor and rapeseed and mustard and all oilseeds had achieved
higher average yield rates during 2005-09. Only in the case of sesame, the peak average
productivity level was found during 1995-2000. During the 20 year period (1980-2000) cotton
had achieved peak average productivity during 1995-2000. The increase in average productivity
level achieved for cotton was remarkably high during 2005-09 due to the introduction of Bt.
cotton. Thus, it can be concluded that considerable improvement in productivity has been
achieved in Gujarat continuously during the period of study.
7.2.8 Influence of Trade Openness of Agricultural Exports
The value of co-efficient of determination (R2) exceeds 89 percent. Affecting the agricultural
exports as constant, the 89 percent variation in agricultural exports is explained by trade
openness. The estimated parameter (p) reveals that one unit change in Trade Openness, the
agricultural exports increases by 0.944 units. This variable emerges statistically significant. The
regression estimates of the model are presented in Annexure 7.5. It may be seen from the table
that the computed value of F is greater than the table value at 1 percent level. As far as an Indian
agricultural export is concerned, the above results proved that, trade openness exert a positive
impact on agricultural exports.
7.2.9 Influence of Trade Openness on Manufactured Goods Export
Export performance of manufactured goods so many factors. In this back drop, the study attempt
to estimate the impact of globalization. In addition to trade openness, which is an indicator of
globalization, the Real Effective Exchange Rate (REER) is also considered as a determinant. It
represents a measure of International competitiveness. The co-efficient of the Trade Openness
(p) is expected to be positive in its character. It shows that a unit increase in trade openness
would tend to increase exports of manufactured goods of India. The regression estimate of the
model is presented in Annexure 7.5. It may be seen from the table that the co-efficient of
multiple determination (R2) of the model is 0.65 i.e., nearly, 65 percent of the variations in
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exports of manufactured goods are explained by the variable i.e. Trade openness. This variable
emerges statistically significant at 1 percent significant level. For one unit change in Trade
openness, the export of manufactured goods increased by 0.803 units. The constant term of the
model is -30354.35. Because calculated F value is greater than the table value, the whole model
is significant at 5 percent as well as 1 percent level.
The agriculture export from Gujarat data and results of analysis were also available from other
sources, which have been briefly presented below.
7.2.10 Agricultural Performance and Exports from Gujarat
In recent past Gujarat has experienced significant increase in production of major crops.
Farmers have changed from commercial crops to cash crops. There has been a significant
increase in area under castor, mustard, and sesamum; groundnut and cotton, being the main cash
crops of Gujarat. The productivity of most crops has risen substantially over the years and this
rise has been most pronounced during 2000-2010. All the cereals except maize, pulses, and gram
achieved the peak of productivity during the period 2005-09. The coefficient of variation in
Gujarat for most of the crops highlights a sharp decline in the risk factor and volatility in the
productivity for farmers. It is interesting to see that the reduction in risk is more pronounced for
commercial and cash crops than for traditional crops.
Apart from food grains (cereals and pulses), oilseeds, and cash crops like cotton and tobacco,
Gujarat has leapfrogged in production of horticulture crops also. The area, production, and yield
of fruits and vegetables have increased substantially. For example, from 1992-93 to 1999-00,
production of fruits and vegetables grew by 5.5 percent p.a.; whereas from 2000-01 to 2007-08,
the same grew at 12.8 percent p.a. Gujarat has an edge in castor, cumin (jeera), fennel (saunf),
psyllium (isabgol), sesamum (til), groundnut, mango, garlic, dehydrated onion, fish and seafood,
and cotton in the international market (GITCO, 2009). Although concrete data on exports at the
state level are not collected and published by any official source so far in the country, there are a
few isolated efforts made to estimate exports originating from Gujarat (GITCO, 2001 and 2009).
Some data are collected from exporters and CMIE, cybex India, New Delhi etc.
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Total agro & allied products export from India was Rs.176.65 Billion compared to Gujarat Rs.
22.57 billion, percentage of changes 12.78 during the 2000-01. Over a period of time during the
year 2004-05 export percent reduced to 10.27, Sesamum and Niger seeds changed from 19.40 to
16.6 percent. Groundnut from 39.56 to 39.86 percentages shows almost no significance change.
Most important value added products exported from Gujarat it has reduced from 89 percent to 87
percent. Process fruit and vegetable percentage of export increases from 155 to 500 percentages.
Table7.5. indicates that all the agro products have experienced a remarkable growth in exports in
the country as well as in the state during the four years 2000-01 to 2004-05. Gujarat has emerged
as a hub of agricultural production like cotton, castor, and psyllium production as well as exports
to international markets. The value of floriculture exports has also increased more than three-
folds over a period of time from Gujarat.
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Table 7.5 Export Values of Major Crops from India and Gujarat
(Rs. Billion)
2000-01 2004-05 Increase
India Gujarat % India Gujarat % India Gujarat
Agriculture& allied products
176.65 22.57 12.78 271.1 27.84 10.27 1,535 1,233
Rice 29.26 1.46 4.99 664.2 30.452 4.585 2',055 -
Spices 16.22 1.97 12.15 179.420 11.15 6.215 1.015 -
Sesame and Niger seeds
5.98 1.16 19.40 72.3 12 16.60 1.209 1,034
Groundnut 3.16 1.25 39.56 50.2 2 0 39.84 1,589 1,600
Oilmcals 20.44 5.03 24.61 310.1 70 22.57 1,517 1,392
Castor oil 9.53 8.56 89. X2 102.8 90 87.55 1,079 1,051
Fresh fruits and Vegetables
8.4 0.4 4.76 162.5 22 13.54 1,935 5,500
Processed food, fruits and vegetables
13.28 2 15.06 154.7 10 6.46 1,165 500 - -
Poultry and dairyproducts
2.13 0.5 23.47 67.1 1 1.5 17.14 3,150 2,300
Floriculture 1.33 0.04 3.01 20,5 6 29.27 1,541 15,000
Source: Compiled from GITCO (2001) as quoted in Dholakia (2003) and GITCO (2009)
It is clear from table that export of agriculture products has declined during this period, while
exports of food items also declined. The table 7.6 shows export of selected items from
Ahmedabad International air-cargo terminal but fruits and vegetables has increased considerably
both in terms of quantity and value of exports from international air cargo terminal at
Ahmedabad. The exports of flowers is also picking up. Thus, fruits and vegetables and flowers
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are increasingly taking the place of food items and agricultural products as an export item from
Ahmedabad air-cargo.
Table 7.6 Exports of Selected Items from Ahmedabad International Air-Cargo Terminal
Source: Compiled from figures provided by GSECL, 2010
Gujarat has 40 seaports at different location, however, in terms of turnover; the ports of Gujarat
are far ahead of the national average. The respective share of 12 large seaports of India is shown
in table 7.6, Gujarat has only one major port, namely Kandla, which has consistently risen in
ranks during the past decade and topped the chart for tonnage handled since 2007-08 displacing
Vishakhapatnam as the highest tonnage handling port. Over this period, tonnage handled at
Kandla port increased at 9.57 percent p.a. The Kandla port has shown a huge jump after 2004-05
and even the recent global economic slowdown has not affected Kandla port's performance
adversely. In fact, several capacity expansion works were taken up during the global slowdown
year of 2008-09 and the current capacity utilization for the Kandla port stands at 93 per cent.
2005-06 2006-07 2007-08 2008-09
Quantity
(Tons)
Rs. Lakh Quantity
(Tons)
Rs. Lakh Quantity
(Tons)
Rs. Lakh Quantity
(Tons)
Rs. Lakh
Agricultural products
34.3 57 43.86 96 136.7 178.4 4.43 16.24
Food item 126.9 447 66.64 282 85.92 122.4 81.52 268.66
Fruits & vegetables
44 25 47.14 17 168.7 109.2 232.7 255.75
Flowers 0.5 3 0 0 0 0 9.84 17.69
Total of Above 205.7 532 157.6 395 391.3 410 328.5 558.34
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Table 7.7 Percentage Share of Tonnage handled by Major Seaports of India
Sea Port 1999- 2000- 2001- 2002- 2003- 2004- 2005- 2006- 2007- 2008-
2000 2001 02 03 04 05 06 07 08 09
Kolkata 11.41 10.67 10.57 11.42 11.97 11.29 12.52 11.87 11.03 10.19
Paradip 5.01 7.08 7.35 7.62 7.34 13.63 7.82 8.30 8.17 8.75
Visakhapa- tnam
14.53 15.90 15.42 14.67 13.84 12.25 13.18 12.16 12.44 12.05
Ennore 0.00 0.00 1.18 2.71 2.69 2.32 2.17 2.31 2.23 2.17
Chennai 13.77 14.66 12.56 10.74 10.65 10.70 11.16 11.52 11.01 10.84
Tuticorin 3.67 4.37 4.53 4.24 3.97 3.86 4.05 3.88 4.14 4.15
Cochin 4.71 4.67 4.19 4.15 3.94 3.44 3.29 3.29 3.05 2.87
New Mangalore
6.47 6.36 6.09 6.83 7.74 8.28 8.14 6.91 6.94 6.92
Mormugao 6.70 6.98 7.97 7.54 8.08 7.49 7.48 7.38 6.77 7.86
Mumbai 11.18 9.63 9.19 8.55 8.70 8.59 10.44 11.29 10.99 9.78
JNPT 5.51 6.61 7.83 8.56 9.05 8.01 8.91 9.66 10.74 10.80
Kandla 17.03 13.07 13.12 12.96 12.04 10.15 10.84 11.42 12.50 13.62
Source: Maps of India (2010)
However, the small and medium ports of Gujarat show the real strength of performance. Over a
decade of time Kandla has highest percentage of share of tonnage i.e. 13.62 percent followed by
Vishakhapatnam ie 12.05 percent. The non-major ports, also known as minor and intermediate
ports, have commanded 70 to 80 per cent of the total tonnage handled by all Indian non-major
ports over the past two decades. The share of non-major ports of Gujarat has been high for long
now, the increase in tonnage has significantly picked up since 1999-2000.
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Table 7.8 Numbers of APMC and Market Yards in Gujarat
2002 2003 2004 2005
Market Committees (APMC)
Main Yards of Market Committees
Sub-Market Yards
199
172
226
201
180
220
202
182
225
201
188
215
Source: India Stat Market (2010)
The state Government had amended the APMC Act to provide competition, allow spot markets,
and contract farming. As shown in Table 7.8. the APMC during the year 2002-2005 not very
significant changes are witnessed. Very limited progress in these areas in the state has been
made but concrete macro level data is yet not available on their functional details. The farmers/
producers would certainly stand to gain. The number of sub market yards has reduced from 226
to 215 during the year 2002-05, indicating that more efforts need to be put in for providing
farmers appropriate price of their products.
7.3 Trend, Variability, and Growth Analysis of area, production and yield of selected
agro commodities:
Keeping in view objectives of the study, data collected from different sources were analyzed.
Compound growth rates in area, production and yield of selected agro commodities were worked
out for the Gujarat state as well as India. The growth rates were worked out for two sub periods;
namely, pre WTO period (1980-81to 1994-95) and post WTO period (1995-96 to 2008-2009)
and for the overall study period of 1980-81 to 2008-09
For estimating the growth of area, production, productivity, and exports, the compound growth
rate was computed using the following function.
Y = a bt
Log Y = Log a + t Log b
Where Y = Area, Production, Productivity, exports.
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t = Time variable
a = Constant
b = (1+r) = where r = (compound growth rate) = (Antilog b-1) x 100
Variability has been examined by computing coefficient of variation
CV= Standard Deviation X 100
Mean
Index of Instability = CV X (1- R²)
Coefficient of variation was multiplied by (1- R²) the formula suggested by Cuddy and Della (1978) was used to compute the index of Instability.
The empirical study is based on data analysis using statistically and econometric methods.
Period-wise growth rates and trend-breaks are worked out to find out any possible shifts in the
trend behavior of the trade variables under study. While growth rates are worked out by using
Regression method, for the year’s pre and post WTO trend breaks.
Production of Groundnut in Gujarat and India.
In Gujarat groundnut production is undertaken predominantly in Saurashtra region. The data
related to area, production and productivity is presented in table 7.9
The state of Gujarat is a principal and highest producer of groundnut and contributes to major
share of demand for edible oil of people in the country. The data related to area allocated,
production and yield of groundnut in Gujarat and India are given in table 7.9. The data indicates
that total area allocated for groundnut production in Gujarat and India has declined by10 percent
approximately in 2009-10 compared to 1980-81. In Gujarat area allocated gas declined during
pre WTO era. While the same for India increased from 1980-81 to 1994-95 by about 10 percent
during pre WTO period while it declined by around 18 percent during post WTO period. Thus,
the area under cultivation for groundnut in Gujarat as a percent of area under cultivation for India
has remained stagnant (around 30 percent) between 1980-81 and 2009-10, although during pre
WTO era it had declined by almost 24 percent in 1994-95. It is clear that during post WTO
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period farmers in Gujarat have allocated greater percent of land although total land under
groundnut has remained same.
Overall, there is a large variation in land allocation to groundnuts for India, 8667000ha in 1991-
92, while it declined to 5935000 hectares in 2003-04. This variability has been less, for Gujarat.
The period during post WTO has seen even less variability in land allocation to groundnut in
Gujarat. Thus, farmers in Gujarat have become more consistent in allocation of land to
groundnut cultivation in post WTO era.
The state of Gujarat also contributes to a healthy share of groundnut production in India both
during pre and post WTO periods. However, the share to all India production has varied
considerably during pre WTO period from a low of 8.6 percent in 1993-94 to high of 32.3
percent in 1980-81, as well as post WTO period from a low of 10.7 percent in 2001-02 to high of
55 percent during the year 2004-05. Thus, it is evident that during post WTO period Gujarat is
more consistently contributing to a higher percent to total all India production of groundnut.
The table 7.9, further reveals that yield of groundnut has increased from 741 kg per hectares in
1980-81 to 1393kg per hectare in 2009-10, indicating doubling of yield, the average yield during
post WTO period is much higher than average yield during pre WTO era. However, during post
WTO years the yield has not shown much improvement and has stagnated around 1300-1400 kg
per hectares in Gujarat. Some years during post WTO period have a very low yield, which
corresponds to failure of groundnut crop in Gujarat. The yield of groundnut in Gujarat, however,
is much higher than yield for all India.
The table 7.9A provides regression result for area, production, and productivity of groundnut in
Gujarat and India during pre and post WTO period. It is clearly evident from intercept value that
average production and productivity in Gujarat has improved during post WTO period in
comparison to pre WTO period while the same has not improved much and remained stagnant
for India as a whole. The table further reveals that in Gujarat growth of production and
productivity during post WTO period is higher compared to pre WTO period. This indicates
improvement in efficiency in groundnut production since WTO implementation in Gujarat. In
contrast to Gujarat, growth in production and productivity for India is much less. The ‘T’ value
decline for Gujarat as well as for India during post WTO period compared to the pre WTO
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period, indicating reduced variability in production of groundnut. Compared to India, Gujarat
recorded less variability in production of area and productivity during post WTO period; this
may be owing to improved agriculture practices adopted by farmers relative to their counterparts
in India.
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Source: Ministry of Agriculture, Govt. Of India, 2010
Table 7.9 Area, production, Yield of Groundnut in Gujarat & India (1980-2009) – Pre and Post WTO regime.
Year
Gujarat India '000
Hectares Area sown
Area (%)
'000 tonnes Total
production production
(%) 'Kg./Hect
Yield '000 Hect Area sown
'000 tonnes Total
production Kg./Hect
Yield 1980-81 2179 31.6 1615.5 32.3 741 6904.6 5005 725
1981-82 2177.5 29.3 2175.6 30.1 999 7429 7223 972
1982-83 2105.5 29.2 1285.4 24.3 610 7215 5282 732
1983-84 2149.6 28.5 1810.1 25.5 842 7539 7085 940
1984-85 2061.1 28.8 1572.3 24.4 763 7168 6435.9 898
1985-86 1868.1 26.2 473.2 9.2 253 7124.8 5121.3 719
1986-87 1827.4 26.2 1329.9 22.6 728 6982.1 5875.4 842
1987-88 1050.5 15.3 140 2.4 133 6844 5853.6 855
1988-89 1823.4 21.4 2875 29.8 1577 8529 9658 1122 1989-90 2038.1 23.4 1669.6 20.6 819 8710 8100 930
Pre WTO 1990-91 1701.6 20.5 1052.6 14.0 619 8309 7510 904 1991-92 1941.9 22.4 699.7 9.9 360 8667.9 7090 818 1992-93 1884 23.1 2068.4 24.2 1098 8166.4 8560 1048 1993-94 2053 24.7 676.6 8.6 330 8321.7 7830 941 1994-95 1914 24.4 2305 28.6 1204 7848.6 8061.6 1027
Post WTO 1995-96 1902.9 25.3 1028.3 13.6 540 7524 7579.4 1007 1996-97 1834.9 24.2 2449.1 28.3 1335 7596.4 8642.9 1138 1997-98 1926.2 27.2 2615.9 35.5 1358 7088.2 7372.1 1040 1998-99 1940.8 26.2 2577.8 28.7 1328 7396 8981.5 1214 1999-01 1826.5 26.6 717.5 13.6 393 6867.3 5258.1 766 2001-02 1745.2 26.6 688.6 10.7 395 6558.6 6408.3 977 2002-03 1887.7 30.3 2646.6 37.7 1402 6238.1 7027.5 1126 2003-04 2029.4 34.2 1094.5 26.6 539 5935.5 4121.1 694 2004-05 2003.4 33.5 4477.6 55.1 2235 5987 8126.5 1357 2005-06 2000.4 30.1 1886.6 27.8 943 6640.4 6774.4 1020 2006-07 1954 29.0 3389 42.4 1734 6736 7993.3 1187 2007-08 1773 31.6 1435 29.5 809 5615.1 4863.5 866 2008-09 1860 29.6 3300 35.9 1774 6290 9180 1460 2009-10 1910 31.0 2660 37.1 1393 6160 7170 1164
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Table 7.9A: Regression Results on Area, Production, Productivity of Groundnut in Gujarat and India (1980-81 to 2008-2009)
Calculation from secondary data
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Table 7.9 B: Regression Results and Descriptive statistics of Groundnut Cultivation in Gujarat and India (1980-81 to 2008-2009).
Agri. Commodities
Gujarat
India
'000 Hectares
Area sown
'000 tonnes
Total production
'Kg./Hectare
Yield
'000 Hectares
Area sown
'000 tonnes
Total production
'Kg./Hectare
Yield
Groundnut
Average 1909.28 1817.77 939.79 7185.92 7041.01 982.38 SD 206.59 1008.61 518.41 850.51 1421.57 188.73 CV 10.82 55.49 55.16 11.84 20.19 19.21 Index of instability
10.80 54.59 54.07 64.54 20.16 3.87
Calculation from secondary data
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The growth analysis was carried out with the help of regression coefficients. The regression co-
efficient for Gujarat State and India has shown negative growth with decreasing trend in area
under groundnut. These regression coefficients were also statistically significant at 1 percent
level of probability.
It can be seen from Table 7.9 B that there has been more variation in productivity in groundnut
production (55.16 percent) for Gujarat State than (19.21 percent) for all India. The instability in
productivity was more for Gujarat compared to all India average. This may be due to unfavorable
monsoon and prevalent dry spells during the month of September which has badly affected the
pod formation in crop resulting in reduction in yield per hectare and thereby decreasing the
productivity of groundnut and some unusually goods years. However, area allocation in Gujarat
shows very less instability compared to all India. This indicates that farmers are consistent in
allocating land to groundnut in Gujarat.
During the post-WTO period, the growth rate for area and production was increased. Thus,
variation in growth rate of production between post-WTO periods was due to protocols
developed by board for multiplication of groundnut using the tissue culture route. Advance
technologies have ensured genetic purity and selection of appropriate time for planting as
demanded by the market led to the increase in productivity, as the prices shot up in international
market.
Production of Cotton in Gujarat and India
Cotton is a very important cash crop in India and the country ranks first in cotton area in the
world and second in cotton production. About 15 million farmers in the country spread across 10
states are engaged in cotton production, on an area of about 10 million hectares. India also holds
a prominent position in cotton textile industry in the world, manufacturing products for a large
number of end uses in India and abroad. Despite being one of the top most cotton growing
countries in the world, the cotton yields in India are one of the lowest.
A major reason for this low productivity is the severe insect pest incidence, which causes
extensive crop damage. The major cotton producing states in the country are Maharashtra,
Gujarat, Andhra Pradesh, Punjab and Tamil Nadu, and among them Maharashtra alone accounts
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for over one-third of the cotton area in the country. The state of Gujarat has been one of the
leading cotton producer states in India. In 1980–81, it accounted for 20 percent of area and
almost 25 percent of cotton production of India. However, as revealed by data in table 7.10, area
under cotton cultivation declined, in absolute term as well as percent wise of all India level by
the year 1994-95 prior to implementation of WTO. Since, implementation of WTO, it is evident
from table 7.10 that area allocated to cotton in Gujarat has increased consistently to 25 percent of
all India in the year 2009-10, the cotton production has also increased to almost 32 percent of all
India levels. The increase in share of production was especially visible from 12.20 percent in
2001-02 to 38.80 percent in 2007-08, when it attained highest share in all India production. This
may be attributed to early and widespread adoption of Bt cotton cultivation by farmers in Gujarat
compared to farmers in rest of India.
The comparison of productivity also reveals that Gujarat has higher productivity compared to all
India levels throughout the period of study. For all years with a few years of exceptions the yield
of cotton production in Gujarat is higher on an average by approximately 20 percent during pre
and post WTO period, except for a few exceptional years of bad years for cotton cultivators.
Overall the productivity has increased by more than 2.5 times in Gujarat compared to less than
2.5 time for India. Thus, Gujarat has succeeded in improving productivity more compared to
India as clear from data in table 7.10.
Table 7.10: Area, production, and Yield of Cotton in Gujarat & India (1980-2009) – Pre
and Post WTO Regime
Gujarat India
'000 Hect Area sown
Area (%)
'000 bales Total
production Prodn (%)
Kg./Hect Yield
'000 Hect Area sown
'000 bales Total
production Kg./Hect
Yield Year 1980-81 1566.2 20.0 1738.4 24.8 189 7823 7010 152 1981-82 1513.7 18.8 2039.7 25.9 229 8057 7884 166 1982-83 1512.1 19.2 1628.6 21.6 183 7871 7534 163 1983-84 1399 18.1 1444.4 22.6 176 7721 6387 141 1984-85 1383.4 18.7 2068.9 24.3 254 7382.1 8507 196 1985-86 1450.7 19.3 2122.3 24.3 249 7532.7 8727 197 1986-87 1321.8 19.0 1156.9 16.8 149 6948 6905 169
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1987-88 762.2 11.8 415.3 6.5 93 6459.3 6382 168 1988-89 1090.9 14.9 1470.2 16.8 229 7343 8744 202 1989-90 1187.2 15.4 1755.5 15.4 251 7695 11422 252 1990-91 921 12.4 1324.9 13.5 245 7440 9840 225
Pre WTO 1991-92 1135.2 14.8 1180.6 12.2 177 7661.4 9710 216 1992-93 1151.1 15.3 1988.5 17.4 294 7541.9 11400 257 1993-94 1126 15.4 1622.8 15.1 245 7320.5 10740 249 1994-95 1204.7 15.3 2269.3 19.1 320 7871 11890 257
Post WTO 1995-96 1410.4 15.6 2201.5 17.1 265 9035.3 12860.7 242 1996-97 1484.1 16.3 2657.7 18.7 304 9120.5 14231.3 265 1997-98 1519 17.1 3180 29.3 356 8868.4 10851.4 208 1998-99 1658.5 17.8 3903 31.8 400 9342.4 12287.1 224 1999-01 1539.3 17.7 2085.6 18.1 230 8709.7 11529.6 225 2001-02 1615.3 18.9 1161.4 12.2 122 8534.6 9523.8 190 2002-03 1749.9 19.2 1702.7 17.0 165 9132 9997 186 2003-04 1634.8 21.3 1684.6 19.5 175 7669.7 8623.7 191 2004-05 1641 21.6 4026.9 29.3 417 7597.9 13729 307 2005-06 1906.3 21.7 4724.8 28.8 421 8786.6 16428.6 318 2006-07 1906 22.0 6772 36.6 604 8677.1 18499 362 2007-08 2390 26.1 8787 38.8 625 9144.5 22631.8 421 2008-09 2420 25.7 8280 32.0 582 9410 25880 468 2009-10 2350 25.0 7010 31.5 507 9410 22280 402
Source: Ministry of Agriculture, Govt. Of India, 2010
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Table 7. 10 ARegression Results on Area, Production, Productivity of Cotton in Gujarat and India (1980-81 to 2008-2009) – Pre and Post WTO Regime
Calculation from secondary data
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Table 7.10 B: Regression Results and Descriptive statistics of Cotton Cultivation in Gujarat and India (1980-81 to 2008-2009)
Agri. Commodities
Gujarat
India
'000 Hectares
Area sown
'000 bales
Total production
'Kg./Hectare
Yield
'000 Hectares
Area sown
'000 bales
Total production
'Kg./Hectare
Yield
Cotton
Average 1515.51 2841.50 291.59 8141.57 11808.10 242.03 SD 401.89 2205.49 143.60 820.67 5001.99 82.87 CV 26.52 77.62 49.25 10.08 42.36 34.24 Index instability
63.80 0.19 11.40 2.48 8.87 7.99
Calculation from secondary data
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The area augmented from 15.66 lakh hectares & 78.23 lakh hectares in 1980-81 to 12.04lakh
hectares &78.71 lakh hectares in 1994-1995, thereafter decreased slightly and it was stood at
23.50 lakh hectares & 94.1 lakh hectares in 2009-10 (Table 7.10) with a growth rate of 1.99
percent & .8 percent during the overall period. The production of cotton in Gujarat has shown lot
of fluctuations and it was stood at 17.38 lakh bales&70.10 lakh bales for India 70.10 lakh bales
& 222.80 lakh bales respectively during 1980-81 and 2009-10 with a growth rate of 5.5 & 3.73
percentages for the overall period for Gujarat and India respectively.
The similar situation was observed in the case of yield also, the yield augmented for Gujarat
&India are 189kg/hectares&152kg/hectares in 1980-81 to 320kg/ hectares&257kg/hectares in
1994-1995 thereafter increased and it was stood at 507kg/ hectares&402kg/hectares during the
2009-10 (Ref.Table7.10) with a growth rate of 1.99 percentage & 0.8 percent during the overall
period, and yield growth rate for overall period was (1980-2009) found to be at3.46
percent2.91percent respectively for overall period (Ref.Table7.10 A).
Pre WTO i.e. 1980-81 to 1994-95 compound growth rate of area in Gujarat was negative i.e-3.23
percent Intercept was 7.3 percent and slope was negative that was -0.03 percent compare to India
-0.446 percent negative and non-significant.
Post WTO i.e. 1995-96 to 2008-09 compound growth of Area of cotton in Gujarat & India was
4.2 percentages. Analysis for productivity CGR of India was 2.91 percent compare to Gujarat
3.46 percent. Overall period (1980-81 to 2008-09) compound growth in area of cotton for
Gujarat was 1.99 percentages; CAGR of India was 3.73 percentages (Ref. Table 7.10 A).
The average area, production and yield of cotton in Gujarat has shown lot of fluctuations and it
ranges between 1515.5 hectares, 2841.5 bales and 291.5 kg per hectare respectively and
coefficient variation 26.5 percent, 77.6 percent & 49.2 percent (Ref.Table7.10 B) for India the
average area, production, yield was not very significant, i.e. 8141.5, hectares, 11808 bales,
242.03 kg/hectares respectively. The coefficient of variation for entire period i.e. 1980-2010
for Gujarat has high levels of variation than India.
The R² value of area, production, yield Gujarat & India was 40.3 percent, 46.3 percent, &37.6
percent and India was 45 percent, 70.1 percent &, 62.9 percent respectively. All the cases pre,
post WTO and overall period “T” value were less than 3.05 so CAGR and slope were 1 percent
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levels of significance. The coefficient of adjustment of area is little high indicating that less time
required for area adjustment. The Index instability for area, production and yield of cotton in
Gujarat Was 63.8, .192&11.49 compare to India in area it was 2.48, for production and yield it
was 8.8 and 7.99 respectively. It can be concluded that Gujarat has high levels of instability
compare to India.
Production of Castor in Gujarat and India.
The state of Gujarat is a principal producer of castor, which contributes to major share of
demand for edible oil of people in the country. The data related to area allocated, production and
yield of castor in Gujarat and India are given in table 7.11. The data indicates that total area
allocated for castor production in Gujarat and India has increased by more than 50 percent
approximately in 2009-10 compared to 1980-81. In Gujarat, area allocated to castor increased
from 1980-81 from 181000 hectare to 1994-95 to 382000 hectares during pre WTO while it
increased to 433000 hectares during post WTO period. Thus, the area under cultivation for castor
in Gujarat as a percent of area under cultivation for India has increased between 1980-81 and
2009-10 from 36 percent to 50 percent.
Overall, there is a large variation land allocation for India, increased by approximately 60
percent from 1980-81 to 2009-10. In Gujarat this increased in much larger, 140 percent
approximately during same period. This variability has been less relatively for Gujarat. The
period during post WTO has seen even less variability in land allocation to castor in Gujarat.
Thus, farmers in Gujarat have become more consistent in allocation of land to castor cultivation
post WTO era.
The state of Gujarat also contributes to a healthy share of castor production in India both during
pre and post WTO periods. However, the share to all India production has varied considerably,
pre WTO period from 204000tonnes in 1980-81to 634000 tons in 1993-94, as well as post WTO
period from a high of 885800tonnes in 2001-02 to low of 799800 tons during the year 2004-05.
Thus, it is evident that during post WTO period Gujarat is more consistently contributing a
higher percent to total all India production of castor.
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The table 7.11, further reveals that yield of castor has increased from 942 kg per hectares in
1980-81 to 1963kg per hectare in 2009-10 indicating doubling of yield, the average yield during
post WTO period is much higher than average yield during pre WTO era. However, during post
WTO years the yield has not shown much improvement compared to pre WTO period (1990-91).
Data reveals that yield has been fluctuating. The yield of castor in Gujarat, however, is much
higher than yield for all India.
The table 7.11A provides regression result for area, production, and productivity of castor in
Gujarat and India during pre and post WTO period. It is clearly evident from intercept value that
average production and productivity in Gujarat has improved during post WTO period in
comparison to pre WTO period while the same has not improved much and remained stagnant
for India as a whole. The table further reveals that in Gujarat growth of production and
productivity during post WTO period is higher compared to pre WTO period. This indicates
improvement in efficiency in castor production since WTO implementation in Gujarat. In
contrast to Gujarat growth in production and productivity for India is much less. The ‘T’ value
increased for Gujarat and decreased for India during post WTO period compared to the pre WTO
period, indicating variability in production of castor. Compared to India, Gujarat recorded more
variability in production of area and productivity during post WTO period; this may be owing to
variability in seasonal factors.
The ‘T’ value of Area has increased for Gujarat from pre WTO to Post WTO period. For India,
the ‘T’ Value for Area decreased to about 1/3rd from Pre WTO to Post WTO period but overall
period it increased to more than 100 percentages.
From Table7.11A it is noticed that in Gujarat during Pre-WTO (1980-81 to 1994-95) period, area
under castor increased by 3.64 percent per annum and production increased by 7.14 percent.
Whereas during post-WTO period the growth rate for area and production was not increased at
the same rate. For India for the same period area under groundnut was increased at 2.12 percent
per annum and the production was increased at 7.38 percent. Whereas, the growth rate for area
and production during post-WTO period decreased in comparison to the pre WTO period.
World's total production of castor seed is around 12.5 lakh tones and it is cultivated in more than
30 countries. Due to its many end uses in various industries, castor oil has a high level of global
demand, which is constantly growing at 3-5 percent per annum. The major consumer regions/
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countries of castor oil (with their annual consumption figures in brackets) are: European Union
(110000 MT); India (100000 MT); China (80000 MT); Brazil (40000 MT); USA (40000 MT);
Japan (20000 MT); and Thailand (15000 MT). Major castor producing countries are: India,
China, Brazil, Paraguay, Ethiopia, Philippines, Russia, and Thailand. India is the world's largest
producer of castor and its derivatives contributing 65 percent of total production followed by
China with 23 percent and Brazil with 7 percent production. India is also the leading producer of
castor seed oil, with annual world production hovering around 5.5 lakh tons. India's yield at 1.09
tons per hectare in 2004-05 was the highest in the world and cultivated area at 800,000 hectares
again (57 percent of world) contributing to 64 percent of the world total production. In castor oil
and derivatives of castor, India had a share of more than 86 percent in 2005-06 (SEAI, 2007a)
world.
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Table 7.11 Area ,production, Yield of Castor in Gujarat & India(1980-2009) – Pre and Post WTO Regime
Gujarat India
'000 Hect Area sown
'000 tonnes Production '000 Hectares
'000 tonnes
'Kg./ Hect
Year Area (%)
Total production Percentage Yield Area
sown Total
production Yield
1980-81 181 36.1 170.5 83.6 942 501.1 204 407 1981-82 195.5 35 229.9 74.2 1176 558 310 556 1982-83 206.7 35.6 294.2 85.5 1423 580 344 593 1983-84 202.2 32.4 281.1 69.4 1390 624 405 649 1984-85 258.2 38.5 333.1 70.9 1290 670.6 469.7 700 1985-86 239.9 37.7 202.3 65.6 843 636.6 308.3 484 1986-87 208.8 36.1 129.3 56.1 619 577.6 230.3 399 1987-88 68.1 14.2 69.8 35.8 1025 479.5 195.2 407 1988-89 191 30.3 289 69.6 1513 631 415 658 1989-90 242.2 34.5 350 67.7 1445 702 517 736
Pre WTO 1990-91 345.1 42.6 551.4 77 1598 810.4 716 884 1991-92 278.1 39.1 425.3 73.7 1529 711.8 577 811 1992-93 306.1 46.4 496.4 78.8 1622 659.7 630 955 1993-94 312.3 45.6 509 80.2 1630 684.5 634.8 927 1994-95 382.6 49.1 686.6 81.2 1795 779.2 845.3 1085
Post WTO 1995-96 388.1 49.2 613.4 78.9 1580 789 777.3 985 1996-97 371.2 50.1 737.1 81.7 1986 740.4 901.7 1218 1997-98 348.2 54.3 686.5 82.8 1972 641.4 829 1292 1998-99 348.3 51 694.5 82.6 1994 682.5 840.3 1231 1999-01 346.3 43.7 622.4 79.6 1797 791.8 782.2 988 2001-02 459 42.2 639 72.1 1392 1087.7 885.8 814 2002-03 304.7 42 465.1 70.7 1526 725.9 657.7 906 2003-04 242.2 41.1 283.1 65.8 1169 589.6 430.3 730 2004-05 290.3 40.5 541.1 67.7 1864 717.2 799.8 1115 2005-06 325.6 43.6 563.3 70.7 1730 747.2 797 1067 2006-07 342 39.3 665 66.9 1944 869.9 993.9 1142 2007-08 288 45.8 533 69.9 1851 628.4 762.3 1213 2008-09 358 45.5 708 67.2 1978 786.9 1053.6 1339 2009-10 433.9 49.9 851.7 72.7 1963 870 1171 1346
Source: Ministry of Agriculture, Govt. Of India, 2010
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7.11A: Regression Results on Area, Production, Productivity of Castor in Gujarat and India (1980-81 to 2008-2009) – Pre and Post WTO Regime
Calculation from secondary data
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It can be seen from Table 7.11 B that there has been less variation in productivity (24.19 percent)
for Gujarat State than (33.03 percent) for all India. But instability in productivity was also less
for Gujarat compared to all India average. However, area allocation in Gujarat shows very less
instability compared to all India. This indicates that farmers are consistent in allocating land to
groundnut in Gujarat.
Table 7.11B: Regression Results and Descriptive statistics of Castor Cultivation in Gujarat and India (1980-81 to 2008-2009)
Agri. Commodities
Gujarat
India
'000 Hect
Area sown
'000 tonnes
Total production
'Kg./Hectare
Yield
'000 Hectares
Area sown
'000 tonnes
Total production
'Kg./Hectare
Yield
Castor
Average 291.85 469.69 1537.45 699.10 637.36 884.03 SD 85.74 208.70 371.86 124.13 266.97 292.03 CV 29.38 44.43 24.19 17.76 41.89 33.03 Index iiinstability
6.84 11.09 0.50 4.16 9.50 7.51
Calculation from secondary data
The state wise castor production in India is given in Annexure 7.2. The major producers of castor
in India are: Gujarat, Andhra Pradesh, Rajasthan, Karnataka, Orissa, Tamil Nadu, and
Maharashtra. In 2005-06, castor production in Gujarat was 5.71 lakh tons accounting for
63percent of the total in India from 37 percent of the total acreage in India. Gujarat also tops in
castor yield per hectare, which was 1715 Kgs compared to the all-India average of 1010 Kgs.
During the year 2000-01 Andhra Pradesh cultivated 3.98-lakh hectares area it has reduced to
1.57 lakh hectares in the year 2008-09. For production in the year 2000 to2008 it reduced to 1.36
lakh tons to 1.29 lakh tons. The area, production and yield of castor have increased in Gujarat
.The districts of Mehsana, Banaskantha, Sabarkantha, Gandhinagar, Patan, Ahmedabad and
Kutch are major production centers of castor in Gujarat.
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During pre WTO i.e. 1980-81 to 1994-95 compound growth rate of area under castor in Gujarat
was 3.64 percent, Intercept was 5.1 and slope was .03 compared to India where CGR was 2.12
percent, intercept and slope was 5.08 and .06 respectively. For production compound growth rate
was 7.14 percent, intercept, slope was 5.08 and 0.06 compared to India 7.38 percent, 5.43 and
0.071. For productivity compound growth rate was 3.37 percent, 6.8 percent and 0.03 percent.
Compare to India compound growth rate of yield 5.1 percent intercept, slope was 6.06 and 0.47
percent respectively. When compared to post WTO data, it clearly indicates the comparative
advantage of Gujarat over India in castor production. It is evident that Gujarat has consolidated
this advantage during post WTO period and it ranges between 291.8 hectares 469.6 tons and
1537.6 kg per hectare respectively and coefficient of variation being 29.3, 44.4 and, 24.1. For
India the average area, production, yield was not very significant, i.e. 699.1 hectares, 637.3
tones, 884 kg per hectares. Overall, for entire period of study, the coefficient of variation for
Gujarat is higher with respect to area shown and the total production compared to India, however
for yield it is less for Gujarat, indicating higher efficiency in production of castor in Gujarat. This
is also indicated by the index of instability as shown in the table 7.11 B.
Production of Sesamum in Gujarat and India
The state of Gujarat contributes to a handsome share of Sesamum production in the country. The
data related to area allocated, production and yield of Sesamum in Gujarat and India are given in
table 7.12. The data indicates that total area allocated for sesamum production in Gujarat has
increased by six percent approximately in 2009-10 compared to 1980-81 while for India it
declined during this period. In Gujarat area allocated increased during pre WTO era. While the
same for India increased from 1980-81 from 2442500 hectares to 1994-95 to 1970500 hectares
during pre WTO while it decreased to 1848000 hectares during post WTO period. Thus, the area
under cultivation for sesamum in Gujarat as a percent of area under cultivation for India has
increased between 1980-81 and 2009-10 from nine percent to thirteen percent.
Overall, there is a large variation in land allocation for India, 2626800ha in 1991-92, while it
declined to 1444400 hectares in 2003-04. This variability has been less for Gujarat. The period
during post WTO has seen even less variability in land allocation to sesamum in Gujarat. Thus,
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farmers in Gujarat have become more consistent in allocation of land to sesamum cultivation
post WTO era compared to India but a large variation in land allocation to sesamum in Gujarat is
experienced.
The data reveals that during post WTO period Gujarat is more consistently contributing to a
higher percent to total all India production of sesamum.
The table 7.12 further reveals that yield of sesamum has increased from 168 kg per hectares in
1980-81 to 356 kg per hectares in 2009-10 indicating doubling of yield, the average yield during
post WTO period which is much higher than average yield during pre WTO era.
The table 7.12 A provides regression result for area, production, and productivity of sesamum in
Gujarat and India during pre and post WTO period. It is clearly evident from intercept value that
average production and productivity in Gujarat has improved during pre WTO period in
comparison to post WTO period, while the same has not improved much and remained stagnant
for India as a whole. The table further reveals that in Gujarat growth of production and
productivity during post WTO period is higher compared to pre WTO period. This indicates
improvement in efficiency in sesamum production since WTO implementation in Gujarat. In
contrast to Gujarat the growth in production and productivity for India is less. The ‘T’ value
increased for Gujarat as well as for India during post WTO period compared to the pre WTO
period, indicating increased variability in production of sesamum during post WTO period.
Compared to India, Gujarat recorded still less variability in production of area and productivity
during post WTO period, this may be owing to improved agriculture practices adopted by
farmers relative to their counterparts in India.
From Table7.12 A it was noticed that in Gujarat during Pre-WTO (1980-81 to 1994-95) period,
the growth rate in area and production of sesamum has increased at the rate of 4.8 percent per
annum. Whereas during post-WTO period the growth rate for area and production has decreased.
For India for the same period area under sesamum growth rate in area and production was
decreased. The ‘T’ value of Area has decreased for Gujarat from pre WTO to Post WTO period.
For India, the ‘T’ Value for area has increased by about fifty percent or 1/2 from Pre WTO to
Post WTO period but overall variability has increased. Overall, however, production CGR is 6.6
percent while yield growth rate is 2.56 percent for Gujarat, the same is much lower 0.6 percent
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and 2.14 percent for India. There has been considerable fluctuation in yield as clear from data
during pre WTO period as well as post WTO period.
Table 7.12 Area, production, and Yield of Sesamum in Gujarat &India (1980-2009) – Pre
and Post WTO Regime
Gujarat India
'000 Hect.
'000 tonnes
'Kg./Hect.
'000 Hect. '000 tonnes 'Kg./Hec
t.
Area sown Area Total
prodn Prodn Yield Area sown
Total production Yield
Year (%) (%)
1980-81 212.3 8.7 35.7 8 168 2442.5 446 183
1981-82 130.7 5 42.6 7.2 326 2593 590 228
1982-83 146.4 6.6 43.2 7.8 295 2217 552 249
1983-84 126.8 5.8 46.1 8.2 364 2204 559 254
1984-85 143.9 6.8 49.9 9.6 347 2117.4 520.7 246
1985-86 144.9 6.5 25.4 5.1 175 2217.4 501 226
1986-87 128.4 5.9 12.4 2.8 97 2163.8 447.7 207
1987-88 100.8 4.7 3.9 0.7 39 2153 583 271
1988-89 154.5 6.3 88.8 13 575 2448 682 279
1989-90 175.1 7.3 67.9 9.1 388 2387 745 312
Pre WTO
1990-91 238.5 9.5 67.9 8.1 285 2515.5 835 332
1991-92 238.2 9.1 45.3 6.4 190 2626.8 706 269
1992-93 298.9 14 160 21.1 535 2128.6 758 356
1993-94 257.8 11.6 35.4 6.3 137 2217.4 563.7 254
1994-95 257 13 95 16.2 370 1970.5 586.6 298
Post WTO
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1995-96 249.7 13.7 92.4 17.4 370 1825.7 531.1 291
1996-97 281.7 14.1 145.2 22.7 515 1991.7 640.5 322
1997-98 295.7 17.8 177 31.2 599 1660 568.1 342
1998-99 300.7 18.7 136.9 26 455 1609 527.3 328
1999-01 300.3 19.2 87.3 18.2 291 1560.2 479.9 308
2001-02 356.9 20.8 98.4 19 276 1720 517.8 301
2002-03 379.6 22.7 226.6 32.5 597 1670.6 697.8 418
2003-04 344.1 23.8 123.2 27.9 358 1444.4 441.3 306
2004-05 402.4 23.7 240.8 30.8 598 1700.3 782.1 460
2005-06 371.9 20.2 117.1 17.4 315 1844 674.1 366
2006-07 364 21.1 143 22.3 393 1723.2 641.1 372
2007-08 355 20.8 71 11.5 200 1703.2 618.4 363
2008-09 300 16.7 141 18.6 470 1799.1 756.9 421
2009-10 238.5 12.9 84.9 13.3 356 1848 640 346 Source: Ministry of Agriculture, Govt. Of India, 2010
Area cultivated of Sesamum in different states in India is shown in Annexure 7.3. During the
year 2000-01, Gujarat has highest 3.56 lakh hectares followed by Rajasthan 2.31lakh hectares,
Andhra Pradesh 1.82 lakh hectares compared to India 17.2 lakh hectares. It has come down to
2.38lakh hectares for Gujarat, for India 18.48 lakh hectares, but in case of Andhra Pradesh it
slightly increases 3.56 lakh hectares during the year 2008-09. The average area of Gujarat for the
year 1980-09 was 2.51 lakh hectares and coefficient of variation was 35.9 percent and Index of
Instability is 7.8 percent (Ref. Table 7.12B), compared to India average 20.17 lakh hectares,
coefficient of variation was 16.6 percent and index instability was 3.95 percent. In case of
production contribution of major states are again Gujarat was highest that is .98 lakh tons
followed by West Bengal .92 lakh tons and whole India it was 5.17 lakh tons during the year
2000-01. Karnataka had also produced 0.40 lakh tons during 2009-10, Gujarat has produced 0.84
lakh tons compare to India 6.4 lakh tons (Ref Annexure 7.3A).
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Table 7.12 B: Regression Results and Descriptive statistics Sesamum Cultivation in Gujarat and India (1980-81 to 2008-2009)
Agri. Commodi
ties
Gujarat
India
'000 Hect.
Area sown
'000 tonnes
Total production
'Kg./Hect.
Yield
'000 Hect.
Area sown
'000 tonnes
Total production
'Kg./Hect.
Yield
Sesamum (Til)
Average 251.54 93.25 347.72 2017.29 606.62 307.17 SD 90.31 60.07 153.79 335.03 107.29 65.69 CV 35.90 64.42 44.23 16.61 17.69 21.38
Index instability
7.80 64.50 4.88 3.95 1.20 5.00
Calculation from secondary data
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Production of Tobacco in Gujarat and India
Major area of tobacco sowing in India is Gujarat with 0.87 lakh hectares, followed by
Karnataka, 70.5h lakh hectares, Andhra Pradesh 0.52 lakh hectares of area sown. Production
of 1.48 lakh tons for Gujarat is also highest followed by Andhra Pradesh 0.88 lakh tons
compared to 3.44 lakh tons of total production in India during the year 2000-01. The yield of
tobacco 1425kg/hectors compare to India 1592kg/hect during the year 2009-10 (Ref.
Table7.13). Average area sown for Gujarat for overall period i.e., (1980-2009) was .95 lakh
hectares compare to India 3.96lakh hectares. The coefficient of variation in area in Gujarat
was 23.1 percent, and index instability was 73.9 percent, for whole India 12.5 percent, 2.04
percent. For production average was 1.56 lakh tons, the coefficient of variation was
28.4percent, Instability was 7.75 percent. Compare India 5.28lakh tons, the coefficient of
variation was 12.9, Instability was 19.006 percent. For productivity 1641.7 kg/hect,
coefficient of variation was 14.9 percent Instability was, 0.23 percent compare to India11.1
percent & 19 percent respectively (Ref Table 7.13B).
The state of Gujarat is a major producer of tobacco. The data related to area allocated,
production and yield of tobacco in Gujarat and India are given in table 7.13. The data
indicates that total area allocated for tobacco production in Gujarat and India has decreased
by 18 percent approximately in 2009-10 compared to 1980-81. In Gujarat area allocated
decreased during post WTO era. While the same for India decreased from 1980-81 to 1994-
95 during pre WTO period, it increased during post WTO period. Overall, there is a large
variation in land allocation for India. This variability is relatively less for Gujarat. The period
during post WTO has seen even less variability in land allocation to tobacco in Gujarat with
less land allocated to Tobacco in Gujarat. Thus, farmers in Gujarat have moved away from
tobacco cultivation, although relative to pre WTO period. It is clear from data that share of
land allocated in Gujarat to total land allocated to tobacco in India declined to 12.6 percent in
2009-10 from 31 percent in 1995-96. As far as productivity is concerned during pre WTO
period Gujarat had considerable higher productivity compared to India during pre WTO
period. However, during post WTO period productivity of tobacco production has become
almost equal in Gujarat and India in post WTO period. The total production in Gujarat during
post WTO period has declined sharply. As a percent of total India production, production in
Gujarat has declined from as high as 50 percent in 1981-82 and 43 percent in 2001-02, it
declined to 11 percent in 2009-10. Thus, a shift away from tobacco cultivation in Gujarat is
observed.
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Thus, it is evident that during post WTO period Gujarat is more consistently contributing a lesser
percent to total all India production of tobacco. The table 7.13A provides regression result for
area, production, and productivity of tobacco in Gujarat and India during pre and post WTO
period. It is clearly evident from intercept value that average production and productivity in
Gujarat has declined during post WTO period in comparison to pre WTO period while the same
has not improved for India as a whole.
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Table: 7.13: Area, production, and Yield of Tobacco in Gujarat & India (1980-2009) – Pre and Post WTO Regime
Gujarat India
'000
Hectares Area (%)
'000 tonnes 'Kg./
Hect. Yield
'000 Hect.
'000 tonnes
'Kg./ Hect.
Year Area sown
Total production
Production (%)
Area sown
Total production Yield
1980-81 130.7 30.5 190.9 39.7 1461 428.2 481 1123 1981-82 119.6 26.9 263.2 50.6 2201 444 520 1171 1982-83 107.4 21.4 188.1 32.3 1751 503 582 1157 1983-84 108.3 24.6 186.9 37.9 1726 440 493 1120 1984-85 108.4 24.8 173.5 35.7 1601 436.6 485.9 1113 1985-86 106.2 26.8 167.8 38 1580 397 441.2 1111 1986-87 110.4 28.4 182.8 39.6 1656 389 462 1188 1987-88 81.5 25.6 121.8 33.2 1494 318 367.4 1155 1988-89 90 23.9 151 30.6 1678 377 493 1308 1989-90 112.6 27.3 182.9 33.1 1624 413 552 1337
Pre WTO 1990-91 109.6 26.7 192.9 34.7 1760 411 556 1353 1991-92 85.3 20 154.3 26.4 1809 427 584.4 1369 1992-93 105.5 25.2 172.1 28.9 1631 418.5 596.5 1425 1993-94 96.7 25.1 179.2 31.8 1853 384.8 562.9 1463 1994-95 113.4 29.7 213.2 37.6 1880 381.7 566.7 1485
Post WTO 1995-96 121.8 30.9 196 36.6 1609 394.6 535.2 1356 1996-97 112.6 26.3 211.5 34.4 1878 428 615.6 1438 1997-98 111 23.9 183.9 28.9 1657 465 636.5 1369 1998-99 110.6 23.5 103.7 17.1 938 470.1 608.2 1294 1999-01 110.6 25.6 103.7 19.8 938 432.5 523.5 1210 2001-02 87.8 33.6 148.6 43.1 1692 261.5 344.7 1318 2002-03 85.5 24.5 145.3 26.6 1699 348.5 545.5 1565 2003-04 66.4 20.3 114.7 22.9 1727 327.2 500.2 1529 2004-05 68.2 18.4 124.9 22.7 1831 369.7 549.9 1487 2005-06 71.3 19.5 113.9 20.7 1598 366.5 549.1 1498 2006-07 71.3 19.1 113.9 20.6 1598 372.8 552.2 1481 2007-08 71.3 19.3 113.9 21.9 1598 368.51 519.37 1409 2008-09 46 13.2 79 16 1717 348.1 493.26 1417 2009-10 49.2 12.6 70.1 11.3 1425 390.15 621.25 1592 Source: Ministry of Agriculture, Govt. Of India, 2010
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Table 7.13 A: Regression Results on Area, Production, Productivity of Tobacco in Gujarat and India (1980-81 to 2008-2009)
Calculation from secondary data
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Table 7.13 B: Regression Results and Descriptive statistics of Tobacco Cultivation in Gujarat and India (1980-81 to 2008-2009).
Agri. Commodity
Gujarat
India
'000 Hectares
Area sown
'000 tonnes
Total production
'Kg./Hectare
Yield
'000 Hectares
Area sown
'000 tonnes
Total production
'Kg./Hectare
Yield
Tobacco
Average 95.49 156.68 1641.72 396.96 528.91 1339.34 SD 22.08 44.56 245.82 50.01 68.44 148.98 CV 23.13 28.44 14.97 12.60 12.94 11.12 Index instability
73.90 7.75 0.23 2.04 19.01 19.00
Calculation from secondary data
Pre WTO i.e. (1980-81 to 1994-95) compound growth rate of tobacco in area for Gujarat has
been negative. For production compound growth rate is also negative and less compared to
India. For productivity compound growth rate was 0.08 percent positive which can be
considered as stagnating.
Analysis for post WTO that is (1995-96 to 2008-09) compound growth of area and
production of Tobacco the compound growth rate percent was negative (-6.1 percent). During
the overall period 1980-81to 2008-09 for tobacco area, production as well as yield in Gujarat
compound growth rate of area was negative i.e. -2.2 percentage. The ‘T’ value decreased for
Gujarat as well as for India during post WTO period compared to the pre WTO period,
indicating less variability in production of tobacco. However, this less variability is with less
production as well. The coefficient of variation of area, production and productivity for
entire period i.e. 1980-2010 for Gujarat has high levels of variation than compared to India.
The index of instability is also less in India than Gujarat as is clear from table (7.13 B). Thus,
it clearly indicates that farmers in Gujarat have moved away from tobacco due to their
preference for other cash crops. However, it continued to contribute significantly to
production of tobacco (12 percent approx.) in India in 2009-10.
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7.4 Export pattern during pre and post WTO period: Gujarat
In order to assess the export performance of commodities under study, compound growth
rates calculated and examined its behavior for the whole period from 1990-91 to 2009-10 and
also separately for the sub-periods from 1990-91 to 1994-95 and from 1995-96 to 2009-10.
Compound growth rates of quantity and value of exports of groundnut Manufactured &Un-
manufacture, castor oil, sesame, Tobacco, Cotton, Pickle &chutney, process fruit juice, for
the country were estimated for the three periods using exponential growth function.
A compound annual growth rate is worked by using the following equation:
Yi = a bi
Taking logarithms of the above equation to base 10 gives
Log Yi = log a +t log bi
I.e. Y = A + Bt+ ut
Where Y is the dependent variable (the export value of i th commodity), t is the trend (time
variable) a & b are the parameters. The compound annual growth rate is derived as (Antilog
B - 1) 100.
Exports of Agriculture commodities and Agro processed product:-
The increased production in agriculture sector has also contributed to export of agriculture
commodities. It is clear from above analysis that production in selected agriculture
commodities has increased substantially more during post WTO period in Gujarat compared
to India. The higher productivity and substantial proportion of production of selected agro
commodities in Gujarat also leads to considerable export of these selected agriculture
commodities from Gujarat. The export data of selected agro products and agro-processed
products has been collected for study. The export data of all India has been considered for
analysis of agro commodities in which Gujarat has a lead and enjoys major share in exports.
The agriculture commodities selected for the study on the basis of substantial contribution of
Gujarat to all India production are ground nut, sesamum, cotton, tobacco (unmanufactured),
cumin, fennel. Similarly, based on same reason in agro process commodities selected for
study of export are tobacco (manufactured), process fruit juice, pickle and chutney, mango
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pulp and castor oil. The all India export data for these selected agriculture commodities and
agro processed products has been presented, analyzed and the results are explained in
following lines.
The case of Groundnut, sesamum, cotton
The data for export of groundnut, sesamum, and cotton are presented in table 7.14 from 1990-
91 to 2008- 09. The data reveals that prior to 1995-96 export was undertaken to a very limited
extent. Out of the three commodities, only cotton contributed substantially during pre WTO
period. During this period groundnut and sesamum contributed less to exports while
groundnut export rose sharply in 1993 -94, sesamum exports were around 100 Crores rupees
from 1990-91 to 1994-95. The five years data till 1994-95 reveals fluctuation in the quantity
as well as value of exports, in case of groundnuts, sesamum as well as cotton. The fluctuation
in prices of these commodities is also evident from the data in table 7.14 during post WTO
period.
There is a clear trend of increasing quantity being exported in case of groundnut; similar
trend is discernable from value of groundnut being exported. It is further revealed that some
years have registered a sharp fall in quantity and value of groundnut exports, for example
2002-03 and 1998-99. Since 2002-03, there is a continuous up trend in quantity as well as
value of exports. Overall during post WTO period quantity of groundnut exports has
increased almost by a little less than three times, while value of exports has increased by
more than six times that of in the year 1995-96 as prices have also increased. Thus, groundnut
exports have a trend of increasing quantity and value of exports during study period.
The exports of sesamum in terms of quantity remained constant during five years before
WTO while the quantity of exports increased more than four times during post WTO
implementation period. The exports both in quantity and value terms have fluctuated, due to
export demand and domestic surplus production. During five years of study the cotton export
in quantity and value terms declined as indicated in table No 7.14. In contrast the export of
cotton during post WTO has increased continuously. The increase in export of cotton has
been steep since 2004-05. Also the value of export of cotton since 2004-05 has leapfrogged,
mainly due to adoption of hybrid variety of BT cotton seeds. Thus, despite yearly fluctuation
value of export of cotton has registered a fifty times increase during post WTO period, which
is quite commendable performance.
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The descriptive statistics for export of groundnut, sesamum and cotton are shown in table
7.14 A. This reveals that considerable variability in exports of selected crops exists. The
variability in value of export is much higher than variability in quantity of exports. This
clearly indicates that fluctuations in international prices tend to increase variability. Further,
groundnut is more consistent as an export commodity, compared to sesamum, while export of
cotton is much higher in value as well as quantity coupled with greater variability in value of
exports.
The results of regression analysis have been presented in table 7.14 B for selected
commodities. In case of groundnut the growth rate of export has declined during post WTO
period while an increase in ‘T’ value indicates larger spread around mean compared to pre
WTO period. For sesamum again, growth rate of export in value as well as quantity has
increased during post WTO period, while ‘T’ value for quantity of export has declined, but
for value of exports has increased indicating larger spread in value due to variability in prices
internationally. For cotton, on the other hand, variability in quantity and value of exports is
very high as is clear from data in table 7.14 A. However, as given in table 7.14 B, for cotton,
‘T’ value has decreased during post WTO period compared to pre WTO period. Also, for
cotton, the annual growth rate in exports has been approaching thirty percent in quantity as
well as in value terms. Thus, post WTO period has seen Bt revolution in cotton, resulting in
high increase in growth of exports, supported by increased production of cotton, particularly
in Gujarat.
Table 7.14: Export of selected Agri commodities (Groundnut, Sesamum, Cotton) from India 1990-2010 – pre and post WTO period.
Commodity/ YEAR
Groundnut Sesamum Cotton
QTY (‘000 tonnes)
Value (Rs. Crore)
QTY (‘000 tonnes)
Value (Rs. Crore)
QTY (‘000 tonnes)
Value (Rs.
Crore)
pre WTO period
1990-91 33.02 58 59.77 91.31 497.14 854.72
1991-92 3.61 7.34 59.59 102.49 160.34 305.94
1992-93 4.34 7.72 67.7 116.22 63.74 181.78
1993-94 254.21 170.63 39.05 73.51 312.56 653.59
1994-95 51.12 101.32 59.57 141.73 70.75 139.76
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post WTO period
1995-96 118.91 230.69 84.14 257.26 33.28 203.54
1996-97 148.78 325.84 103.8 275.28 269.58 1574.51
1997-98 245.4 506.3 129.32 302.58 157.33 821.89
1998-99 58.33 139.66 105.25 323.51 41.96 206.92
1999-00 158.13 371.16 95.11 328.22 15.91 77.07
2000-01 201.37 316.4 182.38 515.27 29.7 221.07
2001-02 112.81 250.94 218.97 562.23 78.23 42.69
2002-03 67.89 178.3 118.31 372.89 11.75 50.28
2003-04 176.93 179.11 189.11 708.9 139.61 942.37
2004-05 177.15 547.02 168.28 708.95 86.64 422.58
2005-06 190.06 513.69 699.81 746.8 614.8 2904.35
2006-07 251.43 798.46 233.34 939.58 1162.22 6107.81
2007-08 269.59 1054.08 317.01 1642.29 1557.59 8865.39
2008-09 297.89 1239.01 196.98 1494.26 457.56 2865.85
2009-10 339.08 1424.55 215.98 1495.38 1360.27 9542.59
Source: Director General of Commercial Intelligence, Kolkata.2010
The table 7.14 B indicates that during pre WTO period of 1990-91 to 1994-95 compound
growth rate of groundnut export quantity was positive i.e. 67 percent. Intercept &slope was
1.6 and 0.51 compared to export value was 53 percent, intercept and slope was 2.2 and 0.42
respectively for export value.
During post WTO period of 1995-96 to 2009-10 compound growth rate of groundnut export
quantity was positive i.e.6.8 percent. Intercept and slope is 4.2 and 0.06 compared to
compound growth rate of 12.5 percent, intercept and slope of 4.4 and 0.11. Overall
compound growth rate i.e. (1990-91 to 2009-10) of ground nut export quantity was 15.8
percent and for value is 21.5 percent, intercept and slope has been 3.08 and 0.14 and for value
3.36 and 0.19 respectively.
The coefficient of variation of export quantity for entire period i.e. 1990-2010 is 63.3
percent and export value of 97.08 percent respectively. (Ref.Table7.14A).
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The R² value of export quantity and value for groundnut was 46 and 65 percent respectively
for overall period as given in table7.14B. All the cases post WTO and for overall period ‘T’
value is less than 3.05 so CAGR and slope were 1 percent levels of significance. But in pre
WTO period ‘T’ value were less at 2.35 so CAGR and slope were 10 percent levels of
significance. This indicates that during pre WTO period variability is lower compared to
overall period of study.
During pre WTO i.e. (1990-91 to 1994-95) compound growth rate of sesamum export
quantity was negative i.e. 4.2 percent. Intercept is 4.15 and slope is -0.042 (negative)
compared to growth of export value by 5.6 percent and significant intercept and slope of 4.4
and 0.05
In contrast the post WTO i.e. (1995-96 to 2009-10) compound growth rate of sesamum
export quantity was positive by 8.8 percent. Intercept is 4.04 and slope is 0.08 compared to
export value compound growth was 14.7 percent significant intercept and slope was 4 .5 and
0.13. Thus it indicates improved export performance during post WTO period.
The coefficient of variation export of sesamum quantity for entire period for quantity of
export and value of export are same. The R² value of export quantity and value was percent,
71 percent 94 percent respectively (Ref.Table7.14B). All the cases pre & post WTO and
overall period ‘T’ value were less than 3.05; CAGR and slope were 1 percent levels of
significance. This indicates that low variability during pre and post WTO period has
continued for exports of sesamum.
The coefficient of variation for export of cotton quantity for entire period has been 131
percent and export value was 157 percent respectively indicating faster value growth of
export of cotton. The R² value of export quantity and value is 13 and 26 percent for pre and
post WTO period respectively. All the cases during pre & post WTO and overall period ‘T’
value is less than 3.05 so CAGR and slope has 1 percent levels of significance, indicate less
variability in export of cotton, which is not affected by WTO implementation.
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Table 7.14A: Descriptive statistics of selected agricultural Commodity (Groundnuts, sesamum, Cotton) from India (1990-2010)
Calculation from secondary data
Agricultural Commodities & value added product
Descriptive statistics
India
Quantity (in matric tones)
Value(in crores)
Groundnuts Average 158 421.01 SD 100.07 408.72 CV 63.33 97.08
Sesamum (Til) Average 167.17 559.93 SD 145.44 490.20 CV 87.00 87.54
Cotton Average 356.04 1849.23 SD 469.79 2909.91 CV 131.94 157.35
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Table 7.14 B: Regression Results selected agricultural- Commodity (Groundnuts, sesamum, Cotton) from India (1990-2010)
Calculation from secondary data
para meters
Pre WTO (1990-91 to 1994-95) Post WTO (1995-96 to 2009-10) Overall Period (1990-91 to 2009-10)
Inter cept slope R2 CGR
(%) ‘T’
Value Inter cept slope R2 CGR
(%) ‘T’
Value Inter cept slope R2 CGR
(%)
‘T’
Value Groud Nut
Qty 1.61 0.51 0.21 67.01 0.83 4.27 0.06 0.34 6.85 12.1 3.08 0.14 0.46 15.89 6.9 Rs. 2.29 0.42 0.21 53.14 1.45 4.5 0.11 0.52 12.56 10.43 3.37 0.19 0.65 21.56 8.35
Sesamum Qty 4.16 -0.04 0.1 -4.2 17.2 4.05 0.08 0.49 8.87 12.2 3.84 0.09 0.71 10.36 21.66 Rs. 4.47 0.05 0.12 5.62 15.9 4.58 0.13 0.92 14.75 29.58 4.29 0.15 0.94 16.99 39.18
Cotton Qty 6.06 -0.32 0.32 -27.62 6.74 1.83 0.24 0.44 27.3 1.78 4.05 0.08 0.13 9.38 6.28 Rs. 6.68 -0.28 0.33 -24.89 8.58 3.22 0.25 0.39 28.97 2.64 4.85 0.14 0.26 15.35 7.21
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Table 7.15: Export of selected Agro commodities (Fennel, cumin) from India 1990-2010.
Commodity/
YEAR
Fennel
Cumin
QTY (‘000 tonnes)
Value (Rs. Crore)
QTY (‘000 tonnes)
Value (Rs. Crore)
pre WTO period
1990-91 17.68 70.69 2137 7.18
1991-92 15.41 62.92 1654 6.37
1992-93 17.65 118.47 2620 14.34
1993-94 14.18 92.95 3225 16.3
1994-95 10.82 70.62 5618 24.49
post WTO period
1995-96 9.43 68.13 3895 17.34
1996-97 10.27 96.29 6375 34.37
1997-98 10.63 152.76 16281 81.35
1998-99 13.93 189.5 10595 59.8
1999-00 12.79 196.88 6145 34.28
2000-01 1.01 205.95 17134 178.35
2001-02 13.46 225.66 15643 148.18
2002-03 - 289.37 8790.6 72.69
2003-04 - 295.06 5597 41.06
2004-05 - 315.04 1247 101.9
2005-06 - 309.34 12879 98.19
2006-07 - 433.89 26000 201.5
2007-08 - 499.09 28000 291.5
2008-09 - 294.78 52550 544
2009-10 - 724.17 49750 548.24
Source: Director General of Commercial Intelligence,Kolkata,2010
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The case of Fennel and Cumin
The exports of Fennel in terms of quantity remain constant before WTO while the quantity of
exports decreased with increased fluctuations during post WTO implementation period. The
exports both in quantity and value term have fluctuated, due to export demand and domestic
surplus production. During five years of study the Fennel export in quantity value terms
declined as indicated in Table No 7.15. The export of fennel during post WTO has increased
continuously. Also the value of export of Fennel reached maximum in 2007-08.
The growth of Fennel export in terms of quantity and value are given in table 7.15B. The
growth rate were calculated for both pre and post-WTO periods. During pre WTO period the
quantity decreased at the rate of 2.65 per cent per annum and value increased 2.65 per cent
per annum respectively. This was observed because India was unstable exporter of fennel to
the international market. During the post-WTO period, the export quantities and value
increased at a moderate rate of 4.14 per cent and 9.45 percent per annum respectively.
The coefficient of variation of export of Fennel in quantity for entire period has been 67
percent while in terms of export value it is 74 percent.
The R² value of export quantity and value of Fennel is 27 and 68 percent respectively. During
pre & post WTO and overall period ‘T’ value reduced further compared to pre WTO period
indicating greater stability in export performance.
The exports of cumin in terms of quantity has increased since pre WTO period, however,
quantity of exports increased faster during post WTO implementation period. The exports
both in quantity and value term have fluctuated, due to export demand and domestic surplus
production. Also the value of export of cumin post WTO was minimum in 2003-04, while
reached a maximum during 2008-09 which is almost 13 times the value of exports in 2003-
04.
The descriptive statistics for export of Fennel and cumin are shown in table 7.15A. This
reveals that considerable variability in exports existing for both the variability in value of
export is much higher than variability in quantity of exports. This clearly indicates that
fluctuations in international prices.
The growth of cumin export in terms of quantity and value are given in table 7.15B. The
quantity of exports increased at the rate of 29.7 per cent per annum and value increases 40.4
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per cent per annum, respectively during pre WTO period. During the post-WTO period, the
export quantities and value were increased at the rate of 12.4 per cent and 20.73 percent per
annum respectively, indicating sustained increase in export during post WTO period.
The coefficient of variation export of Cumin quantity for entire period is 108 and for export
value 128 percent, respectively. This is much higher than in case of Fennel (Ref.Table7.15A).
The R² value of export of quantity and value of Cumin was 54 and 85 percent respectively
(Ref.Table7.15B). The ‘T’ value has shown a decrease during post WTO period compared to
pre WTO period, indicating a less variability in export of Cumin. Thus during post WTO
period exports of Fennel and Cumin has been increasing with less variability and greater
degree of consistency.
Table 7.15 A: Descriptive statistics of selected agricultural Commodity (Fennel, Cumin)
from India (1990-2010)
Calculation from secondary data
Agricultural Commodities & value added product
Descriptive statistics
India
Quantity (in matric tones)
Value (in crores)
Fennel Average 4321.80 18.85 SD 2900.86 14.08 CV 67.12 74.69
Cumin Average 13806.78 126.07 SD 14912.64 162.05 CV 108.00 128.54
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Table 7.15 B: Regression Results Agricultural Commodity (Fennel and Cumin from India (1990-2010)
Calculation from secondary data
Para meters
Period-I (1990-91 to 1994-95) Period-II (1995-96 to 2009-10) Overall Period (1990-91 to 2009-10)
Intercept
Slope R2
CGR (%)
‘T’ Valu
e
Intercept
Slope R2 CGR
(%) ‘T’
Value Intercept
Slope R2 CGR
(%)
‘T’
Value
Fennel Qty 7.42 -0.02 0 -2.65 6.65 7.83 0.04 0.07 4.14 14.23 7.33 0.07 0.27 7.7 21.18
Rs. 1.71 0.03 0.08 2.55 10.4 1.8 0.09 0.42 9.45 4.46 1.57 0.1 0.68 11.1 7.76
Cumin Qty 7.15 0.26 0.79 29.7 27.6 7.85 0.11 0.28 12.4 10.98 7.6 0.13 0.54 14.35 21.56 Rs. 1.48 0.34 0.89 40.4 6.36 2.18 0.19 0.69 20.73 4.52 1.95 0.2 0.85 22.7 8
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Table 7.16: Export of selected Agricultural Value Added Commodities (Tobacco Manu and Tobacco Unmanu) from India 1990-2010.
Commodity/
YEAR Tobacco (unmanu) Tobacco (manu)
QTY (‘000 tonnes)
Value (Rs.Crore)
QTY (‘000 tonnes)
Value (Rs. Crore)
pre WTO period
1990-91 67.49 192.66 17.68 70.69
1991-92 68.78 314.11 15.41 62.92
1992-93 70.61 355.57 17.65 118.47
1993-94 90.49 368.76 14.18 92.95
1994-95 42.91 184.13 10.82 70.62
post WTO period
1995-96 77.66 378.69 9.43 68.13
1996-97 106.64 660.48 10.27 96.29
1997-98 134.07 917.48 10.63 152.76
1998-99 75.04 572.29 13.93 189.5
1999-00 118.84 812.04 12.79 196.88
2000-01 97.34 661.26 1.01 205.95
2001-02 84.48 582.05 13.46 225.66
2002-03 100.47 733.52 - 289.37
2003-04 120.64 801.41 - 295.06
2004-05 135.74 940.07 - 315.04
2005-06 142.7 1021.32 - 309.34
2006-07 158.25 1251.36 - 433.89
2007-08 173.34 1432.8 - 499.09
2008-09 208.31 2766.27 - 294.78
2009-10 230.88 3621.24 - 724.17
Source: Director General of Commercial Intelligence, Kolkata,2010
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The case of Tobacco
The table 7.16 shows data on exports of Tobacco unmanufactured and Tobacco
manufactured. The export of Tobacco unmanufactured in terms of quantity and value has
remained stagnant during pre WTO study period in value terms. Quantity of export on the
other hand has shown a decline in both case during pre WTO period. The quantity of
unmanufactured tobacco has increased by more than 3 times during post WTO period while,
export in terms of value has increased by 18 times during 1995-96 to 2009-10.
The descriptive statistics for export of Tobacco unmanufactured and Tobacco manufactured
are shown in table 7.16A. This reveals that considerable variability in exports of both exists.
The variability in value of export is much higher than variability in quantity of exports. This
clearly indicates that fluctuations in international prices are on the higher side.
The growth of Tobacco export in terms of quantity and value are given in table 7.16 B. The
growth rate was calculated for both pre and post-WTO periods. The data clearly shows that
the quantity has decreased at the rate of 6.12 per cent per annum and value increased at the
rate of 0.7 per cent per annum respectively during pre WTO period. During the post-WTO
period, the export quantities and value were increased at the rate of 6.44 and 11.89 percent
per annum respectively, for exports of tobacco unmanufactured.
Tobacco unmanufactured earn 23.29 US Million dollar for UK, In the year 2007-08 Belgium
had reached to 60.8 US Million dollar. The coefficient of variation of export of Tobacco
(unmanufactured), quantity is 87 percent and for export value was 87.5 percent respectively.
The R² value of export quantity and value Tobacco (unmanufactured) has been 73 and 82
percent respectively (Ref.Table7.15B). The ‘T’ value has increased during post WTO period,
compared to pre WTO period indicating higher variability in exports both for quantity and
value of exports. Thus, it can be concluded that higher exports since WTO implementation is
also associated with increased variability. The variability is much higher for value exports
due to fluctuations in prices of tobacco internationally. This indicates greater uncertainty and
risk for exporters.
240 | P a g e
7.5 Value added selected agro products Export:
A, better export performance was evident in case of Groundnut, Cotton, and Tobacco,
sesamum and castor in the period of economic liberalization and during WTO regime. The
export performance of value added processed products of selected agro products have been
studied for pre and post WTO periods.
In any country or economy, the value addition capabilities increase with its development.
Greater value addition to resources leads to increase in domestic income. Increased value
addition in agriculture sector needs to be encouraged and required to increase income of
farmers and processors. The value addition in agricultural produce is important as it increase
shelf life of produce, increases export potential of agro processed produce, allow farmers to
get better price of surplus production and leads to increase in income of rural population
engaged in primary sector. The government of India as well as in Gujarat is promoting agro
processing industry so that benefits of growth spread to primary sector and rural areas as well
as to ensure inclusive growth.
The Gujarat government has set up Gujarat agro industries corporation limited (GAICL) for
providing assistance to food processing units. The government of India has initiated National
Mission of Food Processing (NMFP), realizing the need for processing of food items and
ensuring that farmers and primary sector can improve its income. Also, this enables to reduce
wastage of surplus production and increase value addition in agriculture sector. In Gujarat,
GAIC is the nodal agency for administering schemes under NMFP. The principal schemes to
be covered from 2012 are scheme for technology up gradation, setting up modernization,
expansion of food processing industries, secondly, scheme for supporting cold chain facilities
for Non- horticultural products and refer vehicles, thirdly, scheme for human resource
development and fourthly, scheme for promotional activities. The state of Gujarat is being
promoted by state government as the agro business destination. The efforts of government in
promotioning agro processing and agro business are further likely to increase exports of agro
processed products and increase value additions and income levels of those engaged in
agriculture sector. The export performance data of agro processed products in India, where
Gujarat has substantial contribution is presented and discussed in following lines. The agro
processed products selected are manufactured tobacco, process fruit juice, mango pulp, pickle
and chutney and castor oil and their exports from India have been analyzed below.
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The case of Manufactured Tobacco
The data related to quantity and value of exports of manufactured tobacco is given in table
7.16. Based on the DGCI&S data on manufactured Tobacco exports, the entire period post
WTO recorded a continuous growth from 1995-96 to 2001-02 experienced a growth of 30
percent in quantity terms, during same period value of exports increased by 350 percent. The
value of exports of manufactured tobacco since 2001-02 further increased by 300 percent.
Hence, export value has continuously shown increase during post WTO period when exports
increased from 70.69 Crores to 724.17 Crores of rupees. The coefficient of variation of
export of manufactured tobacco, quantity is observed to be 36 percent and for export value to
be 72 percent respectively, indicating smaller variability in comparison to unmanufactured
tobacco. Thus, it shows that manufacturing process has reduced variability in exports quantity
and export value. The table 7.16B provides descriptive statistics of manufactured tobacco
exports. It indicates that intercept has reduced during post WTO period while ‘T’ value has
only marginally increased, showing very less increase in variability of export of
manufactured tobacco during post WTO period.
Table 7.16 A: Regression Results and Descriptive statistics on Export (Quantity, value) of selected agricultural - Commodity & Value Added products from India (1990-2010)
Calculation from secondary data
Agricultural Commodities & value added product
Descriptive statistics
India
Quantity (in matric tones)
Value(in crores)
Tobacco(unmanu) Average 115.23 928.37 SD 49.03 854.41 CV 42.55 92.03
Tobacco(manu) Average 12.27 235.578 SD 4.47 169.57 CV 36.42 71.98
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Table 7.16B: Regression Results on Export (Quantity, value) of selected Agricultural
Commodity & Value Added Products from India (1990-2010)
Calculation from secondary data
para
meters
Period-I (1990-91 to 1994-95) Period-II (1995-96 to 2009-10) Overall Period (1990-91 to 2009-10) Inter cept slope R2 CGR
(%) ‘T’
Value Intercept slope R2 CGR (%)
‘T’ Value Intercept slope R2 CGR
(%) ‘T’
Value Tobbaco (unmanu)
Qty 4.38 -0.06 0.14 -6.12 14.4 4.01 0.06 0.68 6.44 24.57 4.03 0.06 0.73 6.26 38.26 Rs. 5.58 0.01 0 0.7 13.7 5.39 0.11 0.72 11.89 20.25 5.3 0.11 0.82 12.5 34.42
Tobbaco (manu)
Qty 3.02 -0.1 0.69 -10.1 22.2 - - - - - - - - - - Rs. 4.28 0.04 0.06 3.96 14.1 3.88 0.12 0.86 13.3 19.86 4.01 0.11 0.89 12.25 35.22
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The table 7.17 provides data related to export of processed fruit juice and pickle and chutney from India during 1990 to 2010.
Table 7.17: Export of selected Agricultural Value added Products (Process fruit juice, Pickle & chutney) from India 1990-2010.
Quantity : ‘000 tonnes) (Value : Rs. Crore)
Source: Director General of commercial Intelligence, Kolkata, 2010
The case of processed fruit juice and pickle and chutney
Commodity/YEAR Process Fruit Juice
Pickle & Chutney
QTY Value QTY Value pre WTO period
1990-91 - 61.98 - 41.2 1991-92 - 88.34 - 31.5 1992-93 - 119.76 - 42.9 1993-94 - 155.6 13106.16 36.13 1994-95 - 169.44 17719.44 49.74
post WTO period 1995-96 - 204.56 15597.66 52.55 1996-97 - 209.44 18390.31 56.43 1997-98 - 272.87 24372.27 76.71 1998-99 - 290.87 21138.06 75.96 1999-00 - 373.21 26737.6 89.98 2000-01 - 556.84 40703.54 136.46 2001-02 - 512.55 38758.97 120.34 2002-03 - 574.13 56384.37 154.16 2003-04 - 343.66 63052.73 119.75 2004-05 - 369.16 67193.29 120.58 2005-06 - 599.91 - 118 2006-07 - 711.4 - 116.11 2007-08 - 773.4 - 138.91 2008-09 - 1099.15 - 135.27 2009-10 1155.95 - 163.05
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It can be discerned from data that value of both these items was very less in 1990-91. This
marked the start of economic liberalization, since then exports share increased continuously.
The data shows that value of exports of pickle and chutney during post WTO period
increased by more than three times while that of processed fruit juice increased by 5.5 times.
The growth in export of pickle and chutney is in principal demanded by Indian immigrants
abroad, while processed fruit juice has much broader and large market. The descriptive
statistics for export of Process fruit juice and pickle and chutney are shown in Table 7.17A.
This reveals that there is considerable variability in exports.
The table shows that the value of Process fruit juice exports recorded an overall growth rate
of 14.03 percent for the period (1990-91 to 2009-10.) The pre WTO period registered a
higher growth rate of 29.4 percent and for post WTO period a lower growth rate of 11.7
percent is recorded.
During pre WTO i.e. (1990-91 to 1994-95) compound growth rate of Process fruit juice
export value was positive i.e. 29.4 percent. Intercept was3.9 and slope was 0.25 compared to
export value of post WTO that is (1995-96 to 2009-10) compound growth rate of Process
fruit juice export was 11.7 percent while significant intercept and slope are 4.7 and 0.11. It is
clear from table 7.17 B that ‘T’ value has declined during post WTO period indicating less
variability in exports that is despite slowing average annual growth of exports compared to
pre WTO period.
The case of Pickle and chutney
The export of Pickle and Chutney in terms of value showed a growth rate of8.72 percent for
the entire period. The pre WTO period recorded a negative growth rate of 5.27 percent in
quantity compared to second period growth rate of 6.79 percent.
The pre WTO compound growth rate of Pickle and chutney export value was positive i.e. 5. 2
percent, compared to export value for post WTO period compound growth rate of pickle &
chutney of 6.7 percent.
Overall compound growth rate i.e. (1990-91 to 2009-10) of pickle and chutney export value
was 8.7 percent. It can be seen from table 7.17 A that coefficient of variation of value of
exports is much lower than quantity of exports, in case of, pickle and chutney. The table 7.17
B reveals that the growth in value exports is marginally higher during post WTO period. T
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value is also higher by small value during post WTO period. It can be concluded that growth
rate and variability has shown only marginal change during post WTO period.
Table 7.17 A: Descriptive statistics on Export of selected agricultural Value Added products (Process Fruit Juice, Pickle & Chutney) from India (1990-2010)
Calculation from secondary data
Agricultural Commodities & value added product
Descriptive statistics
India
Quantity (in matric tones)
Value(in crores)
Process Fruit Juice Average …. 432.11 SD …. 315.71 CV …. 73.06
Pickle & Chutney Average 33596.2 93.78 SD 19323.38 43.17 CV 57.51 46.03
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Table 7.17B: Regression Results on Export (Quantity, value) of selected Agricultural Commodity & Value Added Products from India (1990-2010)
para meters
Period-I (1990-91 to 1994-95) Period-II (1995-96 to 2009-10) Overall Period (1990-91 to 2009-10)
Inter cept
slope R2 CGR (%)
‘T’ Value
Inter cept
slope R2 CGR (%)
‘T’ Value
Intercept slope R2 CGR (%)
‘T’
Value
Process Fruit Juice
Qty - - - - - - - - - - - - - - - Rs. 3.94 0.25 0.96 29.4 40.4 4.7 0.11 0.8 11.73 24.38 4.41 0.13 0.91 14.04 38.79
Pickle & Chutney
Qty - - - - - - - - - - - - - - - Rs. 3.53 0.05 0.22 5.27 19 3.81 0.06 0.7 6.79 23.43 3.54 0.08 0.86 8.72 36.53
Calculation from secondary data
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Table 7.18: Export of selected Agriculture Processed Value- added products (Mango pulp,
castor oil) from India 1990-2010.
Quantity : ‘000 tonnes & Value : Rs. Crore
Commodity/YEAR Mango Pulp Castor Oil
QTY Value QTY Value
pre WTO period
1990-91 - 66.48 36.21 57.51
1991-92 - 63.66 90.85 139.7
1992-93 - 69.3 68.23 117.39
1993-94 26219.6 57.98 138.91 289.3
1994-95 34460 80.71 184.6 441.28
post WTO period
1995-96 36023.3 84.61 291.82 742.52
1996-97 40302.2 106.01 241.47 672.24
1997-98 45874.5 125.31 204.42 576.13
1998-99 38133.7 138.56 203.91 672.11
1999-00 72384.2 196.53 269.11 1067.4
2000-01 57303.5 263.85 259.64 952.76
2001-02 76735.2 241.34 213.68 625.94
2002-03 96107.3 297.01 177.69 609.81
2003-04 89514.8 241.99 152.36 656.06
2004-05 90988.6 300.86 271.69 1077.98
2005-06 - 352.85 254.72 939.72
2006-07 - 404.84 294.87 1090.11
2007-08 166752 509.68 282.18 1275.72
2008-09 173013 752.98 357.26 2128.72
2009-10 186197 744.6 397.7 2177.57
Source: Director General of commercial Intelligence,Kolkata,2010
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The case of Mango pulp and Castor Oil
The exports of Mango pulp in terms of quantity and value of exports before WTO increased by
20 percent in years’ time, while during post WTO implementation period the exports value has
increased rapidly by around 900 percent during 15 years of WTO implementation. In contrast to
mango pulp the castor oil exports picked up immediately since economic liberalization and
increased by 5 times in quantity terms and 8 times in value terms during pre WTO period. The
castor oil shows robust growth in value exports since 1995-96 during post WTO period as clear
from the table. The castor oil exports increased to rupees 2178 Crores by the year 2009-10
The descriptive statistics for export of Mango pulp and Castor Oil are shown in table 7.18A.
This reveals that considerable variability in exports is experienced. The variability in value of
export is much higher than variability in quantity of exports.
Based on the DGCI&S data on Mango pulp exports overall recorded a growth rate of 14.7
percent. The pre WTO period shows annual export growth rate of 3.95 percent and post WTO
period recorded a lower growth rate of 15.48 percent in terms of quantity of exports the annual
compound growth rate.
The table 7.18 A shows a marginally higher variability for mango pulp and castor oil during post
WTO period compared to pre WTO period. Pre WTO period i.e. (1990-91 to 1994-95)
compound growth rate of Mango pulp export value was positive i.e. 2.98 percent for post WTO
that is (1995-96 to 2009-10) compound growth rate of Mango pulp was 15.4 percent. Overall
compound growth rate i.e. (1990-91 to 2009-10) of Mango pulp export value was 14.7 percent
(Ref. Table7.18B). The table shows same ‘T’ value for export of mango pulp which indicates
low variability. The variability on the other hand for exports of castor oil have doubled during,
post WTO period, although overall variability remained low indicating stability in export supply
from country.
During pre WTO period compound growth rate of castor oil export value was positive i.e. 44.5
percent compared to export value of post WTO period compound growth rate of castor oil was
2.6 percent. Overall compound growth rate i.e. (1990-91 to 2009-10) of castor oil export value
was 7.7 percent which can be considered healthy growth in export of castor oil and mango pulp.
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Table 7.18A: Descriptive statistics of selected agricultural Value Added products (Mango
Pulp, Castor Oil) from India (1990-2010)
Calculation from secondary data
Agricultural
Commodities &
value added product
Descriptive
statistics India
Quantity
(in matric tones)
Value(in crores)
Mango Pulp Average 82000.60 254.95
SD 53347.26 211.47
CV 65.05 82.94
Castor Oil Average 219.56 815.49
SD 92.22 570.15
CV 42.00 69.91
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Table 7.18 B: Regression Results of selected Agricultural Value Added Products (Mango Pulp, Castor Oil) from India (1990-2010)
Calculation from secondary data
para meters
Period-I (1990-91 to 1994-95) Period-II (1995-96 to 2009-10) Overall Period (1990-91 to 2009-10) Inter cept slope R2 CGR
(%) ‘T’
Value Inter cept slope R2 CGR
(%) ‘T’
Value Intercept slope R2 CGR (%)
‘T’ Value
Mango Pulp
Qty - - - - - - - - - - - - - - - Rs. 4.12 0.02 0.15 2.99 30.2 3.69 0.14 0.95 15.48 29.73 3.78 0.13 0.96 14.73 49.86
Castor Oil
Qty 3.39 0.37 0.84 44.52 11.1 5.19 0.02 0.21 2.6 27.17 4.49 0.07 0.57 7.72 24.5 Rs. 3.66 0.48 0.91 61.66 12.6 5.89 0.07 0.58 7.51 25.24 4.98 0.14 0.75 14.48 22.42
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The destination wise results of regression analysis have been presented in table 7.19 for export of selected agro products.
Table 7.19: Regression Results of Selected Agricultural commodity & Value added products direction of export percentage share Export from India (1995-2008).
Country
Groundnut (1995-2008)
Intercept Intercept slope T R²
Indonesia 1.3 0.56 1.7 0.78
UK 0.74 0.05 0.33 0.64 Ukrain 1.8 0.13 1.23 0.11
Malayasia 0.3 0.64 1.55 0.04
Philippines 0.3 0.08 0.49 0.05
Process fruit juice(1995-2008)
Intercept slope T R²
Saudiarabia 2.2 0.07 13.6 0.44
UK 2.3 0.002 28.09 0.002
Neitherlands 1.8 0.06 9.59 0.32
USA 2.7 -0.079 15.5 0.44 UAE 2.09 0 18 0.24
Sesame (1995-2008)
Intercept slope T R² USA 3.2 -0.08 18.8 0.47 Egypt -0.19 0.32 -0.07 0.19
Neitherlands 1.33 0.22 1.03 0.098
Taiwan 0.81 0.35 3.19 0.87 Turkey 0.18 0.36 0.44 0.74
Tobacco Manu (1995-2002)
Intercept slope T R²
SaudiArabia 4.6 -2.10E-47 2.51E+01 1
UAE 3.39 0.004 10.7 0.0067 USA 2.34 0.15 10.1 0.62 Malayisa 0.15 0.36 0.46 0.82 Sigapore -2.33 0.7 -5.07 0.89
Tobacco(U/Manu)(1995-2008)
Intercept slope T R² World 4.6 -2.10E-
47 2.51E+31 1
Belgium 2.95 0.03 9.2 0.04 Russia 2.97 -0.03 4.7 0.011 Germay 1.6 0.02 3.35 0.007
Singapore 2.85 -0.21 6.54 0.48
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UK 0.976 0.14 3.25 0.46
Cotton(1995-2001)
Intercept slope T R² World 4.6 -2.10E-
47 2.51E 1
USA 2.56 0.0009 32.4 0.0005 UK 2.38 0.004 27.1 0.012
Malayesia 2.6 -0.081 25.9 0.71
Bangladesh 0.616 0.17 1.56 0.42
Korea 2.04 -0.04 30.4 0.67 Calculation from secondary data
Thus, overall the value added process agro products are showing a steady and healthy growth
in exports. However, further efforts need to be improved to give a substantial fillip to export
of processed agro products from India and Gujarat.
7.6 Markov Chain Analysis
The export promotion policy of a country must be in tune with fast changing and dynamic
international markets for commodities. Markov chain analysis provides a probability
approach in broadly unraveling the changes. Estimation of transitional probability matrix is
central to Markov chain analysis. It helps to find probable direction of exports in future of a
commodity. It indicates the direction of the changes which help to decide, whether changes
are in desirable directions or if changes are needed to boost exports to a particular market.
The transitional probabilities presented herein provide an indication of change in direction of
trade of groundnut during pre and WTO periods from India.
Table 7.20 Transition probability matrix of groundnut exports during pre-liberalization pre WTO period (1985-1991)
USSR Singapore Czechoslovakia Netherlands German F Rp
Yugoslavia Others
USSR 0.8293 0.000 0.000 0.000 0.000 0.000 0.1707 Singapore 0.6774 0.1396 0.0000 0.0000 0.0000 0.1831 0.0000 Czechoslovakia 0.7039 0.0000 0.0556 0.0000 0.2406 0.0000 0.0000 Netherlands 0.5146 0.0000 0.0000 0.0000 0.0000 0.0000 0.4854 German F Rp 0.0000 0.0000 0.0000 0.0000 0.2341 0.0000 0.7659 Yugoslavia 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 1.0000 Others 0.0000 0.3241 0.3423 0.1452 0.0891 0.0993 0.0000 Source: Calculated from secondary data
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It is evident from Tables 7.20 that the then USSR was a highly loyal market for the export of
Indian groundnut during pre-liberalization period as indicated by high retention probability of
82.93 per cent while it lost 17 percent to other nations.. India could not retain its previous
export shares to Netherlands, Yugoslavia and others as clear from table. Germany, Singapore
and Czechoslovakia were likely to be not so loyal markets for Indian groundnut during the
pre-liberalization period. During this period India lost confidence of traditional Indian
groundnut buyers like Netherlands, Germany etc. Germany could retain 23.41 percent of
groundnut exports, while lost 76 percent to other nations because of changing export policy
as a result of frequent embargoes on export and the change in exporting agency. Moreover,
the production of groundnut had itself become unstable owing to persistent drought in
principal growing areas. During the period 1981-82 to 1986-87, production had oscillated
between 5.0 and 7.3 million tons.
The table 7.12 provide transition probability matrix during post economic liberalization but
pre WTO period. It is evident that Russia and Indonesia exhibited high degree of loyalty
towards Indian groundnut exports. Russia retained 100 per cent of its previous export shares
and Indonesia retained 68.75 per cent of its previous export shares. Indonesia loses 31 percent
Indian exports to Russia. While the per cent retention of previous export shares to Singapore,
UK, Germany and others was very low, India could not retain its previous share to
Netherlands. During this period UK would lose to Indonesia 46 percent and to other nation by
around 29 percent while it is likely to retain 25 percent groundnut exports in future from
India. Singapore is likely to retain 30 percent exports only, while losing 32 percent to UK and
around 20 percent each to Indonesia and Netherlands. Germany is likely to retain only 11
percent, while it will lose 15 percent to Indonesia and 73 percent to others. On the other hand
Netherland is not likely to retain any share in export and will lose 52 percent to Germany and
remaining 48 percent to others. Hence the transition matrix indicates that share of others will
shift to Singapore mainly while others will retain 13 percent of exports of groundnut. Thus,
during pre WTO and post liberalization period, Russia and Indonesia have been the most
loyal destination of export of ground nut for India. It is further revealed that Germany,
Singapore, Netherlands and UK are not so reliable, as the retention of exports is very less.
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Table 7.21 Transition probability matrix of groundnut exports during post
liberalization pre WTO period (1992-1995)
Singapore Indonesia UK Russia Netherlands German F Rp
Others
Singapore 0.2984 0.1940 0.3210 0.0000 0.1866 0.0000 0.0000 Indonesia 0.0000 0.6875 0.0000 0.3125 0.0000 0.0000 UK 0.0000 0.4619 0.2516 0.0000 0.0000 0.0000 0.2865 Russia 0.0000 0.0000 0.0000 1.0000 0.0000 0.0000 Netherlands 0.0000 0.0000 0.0000 0.0000 0.0000 0.5165 0.4835 German F Rp
0.0000 0.0000 0.0000 0.0000 0.0000 0.1141 0.7387
Others 0.7588 0.1089 0.0000 0.0000 0.0000 0.0018 0.1305 Source: Calculated from secondary data
It can be seen that groundnut exports from India have shown a shift towards a few south east
Asian countries away mainly form selected European countries due to economic
liberalization and also mainly due to WTO requirements. In order to capture complete impact
of WTO requirements and changed regulations, in particular, in European countries a
separate Markov transition matrix is constructed to capture shift and direction in groundnut
export from India for the period of 2001-2008. The same has been presented in table 7.21 the
table indicates that Indonesia has a very high tendency of export retention in future i.e. 97
percent. Also Malaysia and Singapore are likely to retain export share of groundnut to an
extent of 66 percent and 68 percent respectively. In contrast to probable gains by these two
countries Philippines is likely to lose its entire exports to Malaysia, UK is also likely to lose
its share in Indian groundnut exports by 91 percent to Malaysia., while Srilanka will retain a
substantial share of 43 percent and lose 56 percent to Malaysia. It is clear from data that
Nepal will retain only mini scale exports, loosing bulk of it to 62 percent to Indonesia and 30
percent to Singapore.
Thus it can be concluded that Indonesian dominance since 2001 as groundnut export
destination from India is emerging very strongly, this is followed by Malaysia and Singapore
as loyal destinations for groundnut export from India. This is quite in contrast to the
groundnut export destinations in Europe prior to WTO and economic liberalization.
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Table 7.22 Transition probability matrix of groundnut in exports during post WTO period (2001-2008)
Nepal Srilanka UK Singapore Philippines Malaysia Indonesia Others
Nepal 0.0730 0.0000 0.0000 0.3035 0.0000 0.0000 0.6235 0.0000
Srilanka 0.0000 0.4305 0.0115 0.0000 0.0000 0.5580 0.0000 0.0000
UK 0.0000 0.0000 0.0867 0.0000 0.0000 0.9133 0.0000 0.0000
Singapore 0.0000 0.0000 0.0000 0.6777 0.3223 0.0000 0.0000 0.0000
Philippines 0.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000 0.0000
Malaysia 0.0351 0.0000 0.0179 0.0094 0.0041 0.6594 0.0000 0.2741
Indonesia 0.0000 0.0067 0.0000 0.0132 0.0000 0.0081 0.9720 0.0000
Others 0.0000 0.0000 0.0000 0.0397 0.3851 0.0000 0.5752 0.0000
Source: Calculated from secondary data
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CHAPTER-VIII
CONSTRAINTS IN PROCESSING AND EXPORTING
AGRICULTURAL COMMODITIES AND AGRO
PROCESSED PRODUCTS FROM GUJARAT
8.1 Introduction
The volumes of exports from a country are significant as they allow domestic producers to
access foreign markets. It is clear from discussion in previous chapters that considerable
export of agriculture commodities and agro processed products from Gujarat is under taken
and there is an uptrend in these as well. The exports from primary sector are important for
improving rural income. Export of value added products from agriculture sector thus presents
good opportunity to boost standard of living of rural population. The constraints in export of
agricultural commodities and agro based products from Gujarat are studied in this chapter.
The agri exporters face constraints due to factors emerging from within the country as well
from factors emerging from changes in international market.
The exporter entrepreneurs require a level playing field to remain competitive in the
international market (Asian Development Bank, 1990). The Government of India formulated
EXIM policies regularly and launched many a programmes to boost exports. Gujarat
government has taken many initiatives to increase agriculture exports. The multilateral
negotiations under the auspices of the GATT and then WTO were aimed to reduce trade
barriers existing in the form of tariffs and non tariffs barriers. But eventually there emerged
new international standards for products and production methods, which are perceived to be
further obstacles to cross border trade by the exporters of developing countries like India.
There is a general concern shared among trade analysts in these countries that certain WTO
provisions like agreement on SPS, Agreement on TBT, and agreement on agriculture and
TRIPs agreement have trade restrictive clauses (Sen, 2000). The institution of the WTO is
viewed as a mechanism to safeguard interests of the trade lobbies in developed countries,
imposing new regulations on developing economies, though many of these apprehensions are
not corroborated by facts.
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A survey of exporters of predominantly agricultural products in Gujarat was conducted to
elicit their views to understand impact of trade policies and trade environment on their export
performance, to assess impact of these changes and the strategies adopted by them to
confront new challenges. Export items from Gujarat are the commodity groups like Ground
nut, Castor, Sesamum, Tobacco (Manu& Unmanu), Cotton, Cumin, Fennel. Value added
agro products like, processed fruit juice, Pickle and chutney, Mango pulp, Castor oil
contribute to agriculture exports from Gujarat.. All together 40 processors and exporters
were covered under the survey. The problems faced by the exporters were analyzed based on
their responses. The responses of selected exporters on various issues related to exports have
been presented here.
Table-8.1: Problems experienced in agriculture exports Cited by the Units under the Sample
Export process sector
No. of Units In sample
Raw Material problems (Shortage, Low quality, high price, etc.)
Machinery/Processing Techniques/Testing lab Non-availability, High cost
Labor Shortage, Unrest, High cost etc.
Finance Shortage, High cost
Other infra-structural Problems Power, Transport etc.
1)Ground Nut other oil seeds
15 11 11 6 8 14
2)Value added sector(Tobacco, Pickle& chutney, Mango pulp, Process fruit juice, etc)
15 14 9 14 7 12
3) Spice (Cumin, Fennel)
5 3 10 5 5 5
Problems 35 28 30 25 20 31
Not facing Problems
5 12 10 15 20 9
Total 40 40 40 40 40 40
Source: Survey Data
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The Table 8.1 summarizes problems at the processing level faced by surveyed exporters of
agriculture products and agro process products. All the exporters put together regarded
machinery related problem as the one which is most widespread and faced by them. They
viewed machine processing technique, high cost of machine, etc as the most teething problem
while understanding agriculture exports. Although machinery related difficulties, agriculture
exports other infrastructure problems have also been cited by 75 percent exporters as
affecting agriculture exports adversely third most critical problem cited, relate to raw material
shortage, poor quality and high prices which adversely affect exports. This is followed by
labour related issues and least severely affecting problem is finance related. However, 12
percent exporters reported no problems faces in exporting. The table further reveals that
groundnut exporters regarded other infrastructure problems followed by raw material related
issues almost adversely affecting exporters for agri value added or processes products
exporters, labour issues and raw material posed biggest challenge, while for spice exporters
machinery related issues are biggest hurdle in exporting machinery.
8.2. Impact of EXIM policies
The exporters were questioned on impact of EXIM policies on their exports. Most of the
exporters reported decline in export sales in value terms, due to downfall in export of high
value items like Ground nut, cotton, sesame etc. But the volume of exports has been
maintained with increase in items like cumin, fennel. The exporters who are custom-grinders
i.e. regular suppliers to overseas buyers as per order, registered better export performance
owing to assured demand conditions.
According to majority of exporters, the EXIM policies of the government had a negative
impact at the price level and on the export front especially in the case of items like pickle,
Mango pulp, etc. Due to increased production of groundnut from countries like Indonesia and
UK, there was decline in international prices. There is oversupply of these commodities in the
world market. Though the Indian variety has high quality characteristics, price
competitiveness is a major factor. Improvement in productivity requires urgent attention to
remain competitive in future.
Exporters cited no major infra-structure constraints other than scarcity of power supply.
According to majority of exporters, rupee appreciation has affected profitability. The
processing units involved in high value added items demanded lower cost foreign currency
loans to compensate for loss from rupee appreciation.
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Though exports of cotton, castor, Tobacco are also subjected to SPS regulations, the
magnitude of the problems associated with this is not significant in view of exporters. Certain
overseas buyers required the implementation of HACCP regulations, as this would fetch a
premium price for the products. The liberalization measures, changes in EXIM policies or
implementation of WTO provisions per se did not have much implication on the industry.
The additional cost incurred for HACCP implementation and testing facilities is not reflected
in increased price realization, according to majority of exporters. This has increased annual
maintenance cost.
Most of the units reported an increasing trend in export sales and net profit as a result of
liberalization measures and EXIM policies. But they opined that SPS, and TBT regulations
appeared trade restrictive in nature at least in the short run. But implementation of these
measures facilitated value addition, quality improvement, product diversification, branding
etc, which in turn sustained export sales. Most of the units surveyed had imported machinery
installed as the procedures for duty-free import are simple for the units in the SEZ. Exporters
welcomed the changes in the export performance.
Table: 8. 2 Ownership of Processing Units
Response Category Nos. of Respondents Percentage
Own Processing Units 25 62.5
Processing through outside Units
15 37.5
Total 40 100.00
Source: Survey Data Agricultural products need primary as well as advanced processing before exporting. Variety
of vegetables and fruits are processed and exported to the overseas market. Processing is
needed to enhance quality or preserve the same till the finished product is consumed by the
overseas buyers. Processing man be taken as value addition activity. Table 8.2 provides
responses of respondents regarding ownership of processing units. Two response categories
have been identified. Own processing units and processing through outside units. According
to the above table, 25 respondents have been found owning their processing units which are
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about 62.25 percentages of the total respondents surveyed against this; about 15 exporters
have been found ensuring processing through outside units which is about 37.5 percent of the
total exporters contacted according to response of exporters.
8.3 Selecting overseas market and ownership of processing unit
In export marketing, selection of overseas market is the first stage. It is difficult to succeed in
exporting unless a right market is found out for the right product. It is costly and time-
consuming too. Thus selecting proper market avoids wastage of time and efforts.
A number of factors are taken into account for evaluation when a decision on selecting
overseas market is made by the exporters. These factors have been identified in response
categories. Apart from others, it includes export assistance available, product specification,
market potentials existing, preferential treatment, profitability, political situation and so on.
Table 8:3 Factors for selecting Overseas Market
Response Category Nos. of Respondents Percentage
Export Assistance Available 10 25
Product Specification 11 27.5
Market Potentials Existing 12 30
Preferential Treatment 02 05
Profitability 03 7.5
Others 02 05
Total 40 100.00
Source: Survey Data
The responses gathered on consideration of these factors for the selection of overseas market
are exhibited in Table 8.3. Accordingly, exporters of agro products have been placing much
emphasis on factors like market potentials existing, product specifications export assistance
available and profitability in declining importance to these factors. Thus, profitability in the
beginning is not given much emphasis; it is assumed that market potential will lead to
profitability later on. The information on various modes used for locating oversized buyers
was sought from exporters. The same has been presented in table 8.4 below.
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Table8.4 Sources being used to locate overseas buyers
Response Category Nos. of Respondents Percentage
Export process council 09 22.5
TA 03 7.5
Direct Contact 06 15
Importers' Directories 10 25
Private Sources 06 15
Other Publications 02 05
Other Sources 04 10
Total 40 100.00
Source: Survey Data
For locating overseas buyers, exporters are using variety of sources. An attempt is made to
know which of the popular sources are used by agro - exporters to locate overseas buyers.
The nine respondents preferring EPCs, as a source of locating overseas buyers is about 22.5
percent of those surveyed. As against 6 respondents preferred using private sources, 10
respondents are found to be taking the help of importers directories as shown Table 8.4. In
terms of proportion ,those using private sources over about 15 percent of total survey
population as against that of 25 percent for those using importers' directories. Trade
association has not emerged as much important sources of locating overseas buyers as
only 2 respondents, i.e. 5 percent of survey population is found using this sources. A Sizeable
proportion of agro exporters about 10 percent of those surveyed have been found using other
sources like internet to locate the overseas buyers there are total four respondents. Thus,
overall exporters are found to be using quite developed sources for locating overseas buyers.
The exporters of agro products have ranked for apprising overseas market. The responses are
summarized in Table 8.5 provides ranking scores on these factors. Accordingly as many as 12
respondents from among those surveyed have given first ranking to price followed by 8
respondents giving competition first ranking, this is followed by 8 respondents have given
first ranking to demand - supply position. In terms of proportion, about 30 percent of the total
respondents have ranked price as the first ranking position as against 20 percent giving first
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ranking to competition and 20.00 percent giving first ranking to demand-supply position. In
case of price, 5 respondents have ranked it for second and third place, and 10 respondents and
8 respondents each have ranked it for the fourth and fifth position. Those giving second and
third position to pricing are about 12.5 percent followed by 25 percentage respondents giving
price as fourth ranking, 20 percentage respondents have given price a fifth place in ranking.
Table 8:5 Ranking of Factors for Appraising Overseas Market
Response Category Nos. of Respondents (Ranking)
Nos. of Respondents (Ranking-Percentage)
I II III IV V I II III IV V
Demand -Supply Position 08 13 10 04 05 20 32.5 25 10 12.5 Distribution Methods 03 08 06 13 10 7.5 20 15 32.5 25 Price 12 05 05 10 08 30 12.5 12.5 25 20 Competition 08 10 07 06 09 20 25 17.5 15 22.5 Business Conditions & Trade practices
09 04 12 07 08 22.5 10 30 17.5 20
40 40 40 40 40 100 100 100 100 100 Source: Survey Data
In case of demand-supply position, 13 respondents have given it second ranking as against 10
respondents giving it the third ranking position. This is about 32.5 percent of respondents
giving demand-supply position a second ranking as against 25 percent respondents giving
third ranking position. About 10 percent of the total respondents have given demand-supply
position a forth ranking as against 12.5 percent respondents preferred to give a fifth rank.
A sizeable number of respondents have ranked distribution method for fourth position which
is about 13 respondents of the total surveyed. This is about 32.5 percent of the total exporters
surveyed giving forth rank to distribution methods.
Thus, Price is ranked most importing in appropriate market followed by demand and supply
position for second place. The Business condition and trade practices factor has emerged
securing higher ranking in third place which is about 30 percentages. It was the distribution
method in fourth and fifth ranked by almost 32.5 percent and 25 percent of the exporters
surveyed for the position.
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From survey data exporters from Gujarat maximum groundnut and sesamum i.e. 37.5 and
22.5 percentage and also they are traditional exporters and they preferred European countries
as the are not very knowledge us about which countries are very competitive. Analysis of
Markov chain model will help Gujarat exporters which country will be more preferable so
that they will be getting more prices for their products in turn Gujarat state as well as whole
nation will be benefited. The exporters are getting high margin of profit but still they are
depend upon middle man the are also taking lot of commission, ISO certificate is also one the
problems for overseas market, though agro commodity and value added products in Gujarat is
high quality and demanding in international market.
8.4 Effect of WTO Implication:
The kolmogorov-smirnov two sample test have been used to analyse ompact of WTO
implication and policy changes on agriculture exports.
The Kolmogorov-Smirnov (K-S) two sample tests are useful in testing whether two
independent samples are drawn from the same population or two identical populations.
If there are any significant differences between the populations from which the independent
samples are drawn in terms of their means or dispersion, the (K-S) test can be used as a
sensitive test to pick up these differences.
Let this sufficiently large differences are denoted as K.
Then this computed with the table value of k at a given level of significance and conclusions
can be drawn whether to accept or reject the null hypothesis.
Here, the number of respondent is 40 so, we use Large Sample (Two-tailed test).
When the two samples are large enough, say over 40 each, then they does not have to be
equal in size.
In such a case cumulative relative frequency distributions are constructed and the difference
between these cumulative relative frequencies for each class (D) is calculated and the largest
difference among these (Ds) is selected for test purpose.
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Table 8:6 The WTO implementation has resulted in gains for agricultural exports from India
Source: Survey Data
Calculated D value--0.385 (maximum value of absolute diff column) (As shown Table
8:6)
Dtable value- 0.215034881
Level of significance - 0.05
Here, 0.385 > 0.215 Hence Null Hypothesis is rejected.
Thus the results indicate that WTO implication has not been resulted is gain for agriculture
exports in view of exporters. The table 8.7 shows for impact of policy changes on exports of
agriculture products and process products.
Factors Frequency Observed proportion Cum prop.
Null hypo.
Cum Null hypo.
Absolute diff. Observed & Null Hypothesis
strongly agree 7 0.175 0.25 0.33 0.33 0.155
Agree 4 0.1 0.35 0.33 0.66 0.23
Disagree 29 0.725 1.075 0.34 1 0.385
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Table 8:7 Recent policy reforms have improved exports from Gujarat
Source: Survey Data
Calculated D value = 0.145 (maximum value of absolute diff column) (As shown Table
8:7)
Dtable value = 0.215034881
Level of significance = 0.05
Here, 0.145 < 0.215 Hence Null Hypothesis is accepted..
Hypothesis Rule: calculated value of D > D table value (calculated from formula) then
hypothesis must be rejected.
Thus, it is concluded that recent policy reforms have improved exports from Gujarat.
The respondents were surveyed regarding problems encountered by processing units, the
same has been presented in table 8.8 below.
The χ2 test is used to test whether there is a significant difference between the observed
numbers of responses in each category under the assumptions of null hypothesis.
In other words, the objective is to find out how well the distribution of observed frequencies
(fo) fit the distribution of expected frequencies (fe).
Hence this test is also called goodness of fit test.
Factors Freq Observed proportion
Cum prop.
Null hypo.
Cum Null hypo.
Absolute Diff Observed & Null(Calculated value of D)
Strongly agree 19 0.475 0.475 0.33 0.33 0.145
Agree 13 0.325 0.8 0.33 0.66 0.005
Disagree 8 0.2 1 0.34 1 0.14
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Table 8.8: The important problem parameters for processing Units
Factors Very Important
Important
Not Important
Row Total
Expected Frequency
Chi Square For Each Cell
Marketing of main products
2 1 2 5 1.875
1.375
1.75
0.007813
0.140625
0.03125
Transportation & Power
2 1 2 5 1.875
1.375
1.75
0.007813
0.140625
0.03125
Marketing of by products
2 1 2 5 1.875
1.375
1.75
0.007813
0.140625
0.03125
High cost on levy & Transportation
2 1 2 5 1.875
1.375
1.75
0.007813
0.140625
0.03125
Row Material problem
2 1 2 5 1.875
1.375
1.75
0.007813
0.140625
0.03125
Machinery Problem
2 2 2 6 2.25 1.65 2.1 0.03125
0.06125
0.005
Labor Problems
2 2 1 5 1.875
1.375
1.75
0.007813
0.195313
0.5625
Not facing any Problems
1 2 1 4 1.5 1.1 1.4 0.25 0.405 0.16
column total
15 11 14 40
0.328125
1.364688
0.88375
Source: Survey Data
critical value of chi square- 23.685(As shown Table 8:8)
Calculated value of chi square
2.57656
Null Hypothesis is that:
There is no difference in the factors in problem parameters among the processing unit’s.
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As the calculated chi square is less then critical value of chi square; hence we cannot reject
the null hypothesis that the opinion is independent on problem parameters of processing unit.
As calculated values exceed critical value, null hypothesis is accepted.
The marketing channels of various selected agriculture commodities has been studied to gain
an insight on their flow filed to the market.
8.5 Marketing Channel
The districts of Mehsana, Banaskantha, Sabarkantha, Gandhinagar, Patan, Ahmedabad and
Kutch are major production centres of castor in Gujarat .It exports around three lakh tons of
castor oil that is worth Rs. 700 crore and is the largest castor oil exporting country. India
exports castor oil in two forms namely: Special grade and Castor Oil Commercial. The
countries that import castor oil from India are: European Union, USA, Japan, China, and
Thailand. Though, India is a dominant player in the world market, it is just a price taker due
to its poor infrastructure. Chart 8.1 shows Marketing Channel for castor in Gujarat.
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Chart 8.1 Marketing Channel for Castor in Gujarat
Producer
Commission Agent
(APMC)
Trader (Whole sellers) Oil extracting &Processing unit
Industries
Export Distributor
Agri input retailer Retailer
Farmer Consumer
Supply raw material to Industries
Export Distributor
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Chart 8.2 shows the Marketing Channel for Tobacco in Gujarat, The merchants usually purchases
through dalals, sub-dalals and commission agents. On completion of harvest, when the grower’s
produce is ready for sale the sub-dalal visit the farmers negotiate and purchase.
Chart 8.2 Marketing Channel for Tobacco in Gujarat
Growers
Sub-Dalals
Dalals commission agents
Traders
Big Bidi Manufacturers
Small Bidi Manufacturers
Dalals commission agents cum Traders
Looseselle
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Chart8.3 shows Marketing Channel for Spices in Gujarat, The farmers bring their produce to APMC.
Exporters /Agents purchase directly from APMC and send to markets in main cities. Whole sellers
directly sell to retailers.
Chart 8.3 Marketing Channel for Spices in Gujarat
Producer
Village Traders/ Brokers
Commission Agents at APMC
Wholesellers
Exporters
Retailers
Export Market
Consumers
Chart 8.4 shows Marketing Channel for Cotton in Gujarat. The seed cotton is mainly picked and then
brought to APMC’s, only 20 percent of cotton is physically brought to APMC; farmers sell their
produce in the village itself. The ginnery owners go to villages and negotiate the prices with the
farmers.
Processors
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Chart 8.4 Marketing Channel for Cotton in Gujarat
Farmers
APMC’S
Gin owners
Spinning unit
Handloom/powerloom
Weaving mills
Ready made garments
Consumers
It is thus clear that exports of selected agriculture commodities and processed products are
steadily increasing for majority of selected products for present study. The government has
taken lot of initiatives to increase exports. However, changes in terms of WTO implication
and importing country specifications are posing a continuous challenge for exporters. The
increased competition in international market keeps exports on alert to make efforts for
improving competitiveness. Hence despite facing multifold challenges and constraint export
of agriculture products and agro process products are showing a slow but sustained increase.
Intermediaries
Dying&printing
Whole cloth