Dr. Sarita Rana Associate Professor (Commerce), University ...
Transcript of Dr. Sarita Rana Associate Professor (Commerce), University ...
International Journal of Research in Economics and Social Sciences(IJRESS) Available online at: http://euroasiapub.org Vol. 8 Issue 2, February- 2018 ISSN(o): 2249-7382 | Impact Factor: 6.939 |
International Journal of Research in Economics & Social Sciences Email:- [email protected], http://www.euroasiapub.org
(An open access scholarly, peer-reviewed, interdisciplinary, monthly, and fully refereed journal.)
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India’s Floricultural Exports during the WTO Regime
Dr. Sarita Rana Associate Professor (Commerce),
University College, Kurukshetra University,
Kurukshetra.
Indian floriculture, ipso facto, has gained momentum at the turn of the century. Such a phenomenon may be noticed by leaps and bounds in the areas under floriculture and the quantum of the production and exports of floricultural products. Keeping in view the progress and the achievements in floriculture during the first decade of the 21st century along with the international changing scenario in floriculture, there is a dire need of self introspection of India’s strengths and weaknesses in floriculture. India, being a country of continental proportions having a variety of geographical and agro-climatic conditions, cheap labour, potentials for skilled labour, availability of natural resources and centrally located for South East Asian and Middle East Asian markets; all are the strengths of Indian floriculture. On the other hand, there are certain weaknesses like lack of skilled labour, widespread illiteracy among farmers, geographical distance from the U.S. and the European markets and of course technological backwardness of Indian floriculture also. It is also very crucial to mention here that the Government of India launched the Mission for Integrated Development of Horticulture (MIDH) from the year 2014-15 during the 12th FYP for the all round development of horticulture sector covering fruits, vegetables, flowers, aromatic plants, spices, mushrooms, coconut, cashew, cocoa and bamboo. The MIDH subsumed the National Horticulture Mission (NHM), the Horticulture Mission for North East and Himalayan States (HMNEH), the National Bamboo Mission (NBM), the National Horticulture Board (NHB), the Coconut Development Board (CDB) and the Central Institute for Horticulture (CIH), Nagaland.
Current Global Floricultural Scenario –
During the globalization era, floriculture has become paramount commercial activity in the agriculture sector. It is the right time to examine the dynamics of global trade in the area of floriculture particularly when it is being viewed as being high growth industry. There are more than 140 countries involved in commercial floriculture. Netherlands is the leading flowers producing country whereas Germany is the biggest importer of floricultural products. At the same time, the U.S. flower market is considered the most lucrative import market. The U.S. Floriculture market showed the signs of the recovery in 2014 after a span of seven years when the market started going down due to the global financial crisis of 2007-08. It was the time housing bubble bursted. There are some other countries like Colombia, Ecuador, Kenya and Ethiopia those have gained speed in cut flowers trade by acquiring the share of 44 per cent approximately collectively and crossed the share of the Netherlands. These countries have some advantages of their location geographically. There are a few signs of the dynamics of global floral trade, i.e., it is fast changing and gaining momentum towards new trends.
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(An open access scholarly, peer-reviewed, interdisciplinary, monthly, and fully refereed journal.)
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Review of Studies –
Sindhu, S. S. and Saha, Tarak Nath (2010) conducted a study and expected a better scope in future as there has been a shift in tends towards tropical flowers and that can be gainfully exploited by India with high diversity in indigenous flora. They stressed to improve the biotechnological tools for desired results in the direction. Such efforts have been made at IARI for chrysanthemum and evolved its two varieties, viz. Pusa Anmol and Pusa Stabdi. They also gave importance to another area for value addition like extraction of pigments, essential oils, pharmaceutical and nutraceutical compounds. They also explained the challenges ahead, e.g., trained HRD, quality planting material and limited choice of varieties available in India.
Maria, Cantor (2010) explained that flower plants suitable for cultivation under the subtropical conditions as of the middle and southern areas of Korea have been developed by breeding organizations such as the National Horticultural Research Institute (NHRI). New floral cultivars were released by the Institute for rose, gladiolus, gerbera, carnations, lilies, chrysanthemum and some native flowers that have good morfo-decorative characteristics. In Korea, researches are going on to adopt genetic engineering technology and development of superior cultivars. Tantri, Malini L. and Deshpande, R.S. (2010) conducted a study on the WTO and Agricultural Policy in Karnataka. The study basically covered the whole agricultural sector of the Karnataka economy but it also encompassed the crops of horticulture, of course including floricultural products. The study examined the WTO clause relating with the agriculture sector and its implications for the primary sector of the Karnataka. The SWOT analysis based on the interviews of the stakeholders put some light on the future policy paradigm and implications of the WTO regime suggesting in-built solutions to the needs of the State’s short and long-terms perspectives. More, T.A. and Jagtap, K.B. (2011), analysed the agriculture economy of India since the inception of the planning era. They have propounded that there is a limit of increasing production in food grains. Now it is the right time to focus on the modern technology and a switch over to the horticultural cops. They stressed the need for research particularly in the field of horticultural crops. They concluded that science and technology led development can be the driving force to face the view challenges in the modern times. Nagabhushana, S. and Govindappa, D. (2013) conducted a study of the WTO negotiations and its impact on the developing economy of India. They have brought the attention towards the arms twisting behaviour of the advanced and strong countries towards the weaker and developing counterparts. Most of the countries of the South have an agricultural economy. Therefore, the researchers have stressed on the dire need on the part of the WTO to protect the agriculture sector of the developing economies. Unfortunately, it did not happen in the true letter and spirit. Roy, T.N., Das, K.K. and Rai, D. (2014) discussed and explored the possibilities of value addition of multi-utilities floricultural products in eastern India in general and West Bengal in particular. It is eco-friendly crop with high potential of income and employment generation for small and marginal farmers. They highlighted that the value chain of loose and cut flowers is highly unorganized. Therefore, efforts are required in the direction along with improving infrastructural facilities and increasing buyers’ awareness.
International Journal of Research in Economics and Social Sciences(IJRESS) Available online at: http://euroasiapub.org Vol. 8 Issue 2, February- 2018 ISSN(o): 2249-7382 | Impact Factor: 6.939 |
International Journal of Research in Economics & Social Sciences Email:- [email protected], http://www.euroasiapub.org
(An open access scholarly, peer-reviewed, interdisciplinary, monthly, and fully refereed journal.)
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Objectives of the Study –
The specific objectives of the present study are the following;
1) To examine the current status of
India in global floricultural trade during the WTO regime.
2) To analyse the measurement of
stability in India’s floricultural exports in the global dynamic market.
3) To suggest policy measures for
the expansion of India’s share in the global floricultural market.
Sources of Data –
The present study is chiefly based on the secondary data available from various Government and multi-lateral institutions published sources. Most of the data have been collected from the following sources:
(i) Foreign Trade Statistics of India,
Directorate General of Commercial Intelligence and Statistics, Ministry of
Commerce, Government of India, Various Issues.
(ii) Export Statistics for Agro and
Food Products, Agricultural and Processed Food Products Export Development
Authority (APEDA), Ministry of Commerce, Government of India, Various Issues.
(iii) Horticultural Statistics at a
Glance, Horticulture Statistics Division, Ministry of Agriculture and Farmers’
Welfare, Government of India, Various Issues.
(iv) Economic Survey, Department of
Economic Affairs, Ministry of Finance, Government of India, Various Issues.
(v) International Trade Statistics,
available at htpp://www.intracen.org.
(vi) Key Statistics (World Trade
Statistical Review), available at htpp://www.wto.org
Research Methodology –
Some mathematical and statistical tools have been used on the data collected from the year 1994-95 to 2013-14. The data is pertaining to India’s floricultural exports year-wise and country-wise both. The year 1994-95 has been taken since the WTO came into existence on 1st January, 1995. In this manner, the whole period of the study belongs to the era of globalization. First of all, exports coefficients have been calculated in both the manner, i.e., year-wise and country-wise.
To measure the market or country concentration of floricultural exports from India to 40 major importing countries of the world, two indices have been used Hirschman- Herfindahl Index (D1) and Entropy Index (D2). In the present research work, both the concentration measures are based on the share (export coefficients) of the individual importing countries of the floricultural products. Let m denote the numbers of importing countries and qit represents the imports from iih partner country at time t. Then the sum of qit from 1 to m will be qt and the
International Journal of Research in Economics and Social Sciences(IJRESS) Available online at: http://euroasiapub.org Vol. 8 Issue 2, February- 2018 ISSN(o): 2249-7382 | Impact Factor: 6.939 |
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(An open access scholarly, peer-reviewed, interdisciplinary, monthly, and fully refereed journal.)
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share of each country in the import of floricultural products for year 1, would be expressed:
= and qit where
sit : Share of each importing country at time t
qit : Imports of each importing country at time t qt : Sum of the total of each importing country i = l, m and t=1, …, T The concentration measures below are based on Sit.
(i) Hircshman – Herfindahl
Index:
S2it where Si : Share of ith importing country at time t .
Herfindahl Index (D1) takes the values ranging from 0 to 1 where 0 indicates
perfect diversification and 1 refers to perfect specialization.
(ii) Entropy Index:
D2 Sit log 1/Sit
The higher value of the Entropy Index (D2) signifies greater information about the concentration of importing countries.
Results and Analysis –
Hirschman- Herfindahl Index (HHI) is a measure of the size of a market in relation to the total market. It may be defined as the sum of the squares of the market shares of a country in the total exports where market shares are expressed as export coefficients shown in Table-1. The results in the table show the export coefficients of major 40 importing countries of India’s floricultural products on yearly basis. The export coefficients of the period from 1994-95 to 2013-14 for forty major importing countries of India’s floricultural exports may guide the exporters and policy makers to know the status of a particular country at a particular time. The information is a very strategic in exports issues. Further, when these
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International Journal of Research in Economics & Social Sciences Email:- [email protected], http://www.euroasiapub.org
(An open access scholarly, peer-reviewed, interdisciplinary, monthly, and fully refereed journal.)
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PRESENTABLE TABLE 1
INDIA'S FLORICULTURAL EXPORTS COEFFICIENTS
(1994-95 to 2013-14) (ALTERNATIVE YEARS SHOWN)
Sr. No. MARKET 1995-96 1997-98 1999-00 2001-02 2003-04 2005-06 2007-08 2009-10 2011-12 2013-14
1 Australia 0.0069837 0.02167221 0.01704935 0.01867692 0.02060127 0.01542544 0.01872758 0.02570808 0.0271269 0.0218469
2 Austria 0.00133023 0.00061569 0.00385538 0.00211881 0.00694694 0.01323603 0.01381784 0.00482239 0.00539253 0.00930029
3 Belgium 0.00615231 0.01514592 0.01216587 0.02958487 0.01014094 0.01764803 0.01446463 0.01643687 0.0212964 0.01647291
4 Canada 0.00349185 0.00184706 0.00779644 0.00651338 0.00938236 0.00424614 0.01643441 0.0261156 0.03293003 0.02994078
5 Chile 0.00016628 0.00110824 0.00059973 0.00015695 0.00059887 0.00043125 0.0002646 0.00020376 0.00221723 0.00596622
6 China P RP 0.00049884 0.00381726 0.00496916 0.00141254 0.0027149 0.01522641 0.00326336 0.00427902 0.01798423 0.02088177
7 Ethiopia 0 0 0 0 0 0.01071488 0.05794673 0.05932894 0.02250082 0.00732617
8 France 0.01396741 0.02610516 0.02638794 0.04151299 0.03253883 0.02046774 0.01599341 0.0140936 0.01111354 0.00960737
9 Germany 0.12886598 0.12867873 0.08841672 0.0973868 0.04543458 0.08084259 0.1030458 0.13804931 0.157451 0.13005045
10 Italy 0.03458597 0.04383697 0.03915353 0.04724162 0.04619316 0.03045281 0.02819427 0.02764382 0.03063068 0.02923887
11 Japan 0.10126372 0.1023273 0.09604181 0.10280154 0.10172875 0.1872284 0.09634268 0.05294437 0.04029344 0.03555604
12 Korea RP 0 0 0.00188485 0.00219728 0.00163692 0.00162548 0.00314576 0.00465258 0.00454396 0.00666813
13 Latvia 0 0 0 0 0.00035932 0.00023221 0.00067619 0.00023772 0.00777401 0.00798421
14 Lebanon 0 0 0.00025703 0.00047085 0.00139737 0.00139327 0.00120539 0.00067921 0.00202562 0.00552753
15 Malaysia 0.00365813 0.00221648 0.00248458 0.0030605 0.00363317 0.00335047 0.01014288 0.00441486 0.00520092 0.0118447
16 Netherland 0.21000998 0.218446 0.25496916 0.18323786 0.10823652 0.0911594 0.13271006 0.1432113 0.14817147 0.14509761
17 New Zealand 0.00365813 0.00233961 0.00376971 0.00690575 0.00762566 0.00636922 0.00585053 0.00784487 0.00457133 0.01223953
18 Poland 0 0 0.00522618 0.00627796 0.02706911 0.0129043 0.01234786 0.01429736 0.01190737 0.01276596
19 Qatar 0 0 0.0006854 0.00125559 0.00043917 0.00116105 0.00120539 0.00373565 0.00169714 0.00642685
20 Saudi Arabia 0.01047556 0.00270903 0.00428376 0.00604253 0.0028746 0.00560624 0.00493914 0.00533179 0.00394175 0.00640491
21 Singapore 0.00266046 0.0213028 0.03015764 0.01859845 0.00978161 0.0066346 0.00405715 0.00611288 0.01034709 0.01998245
22 South Africa 0.00182907 0.00061569 0.00119945 0.00313898 0.00151715 0.00769614 0.00808491 0.00580724 0.00572101 0.01118666
23 Spain 0.01097439 0.01920946 0.02938657 0.03084046 0.01329501 0.01585669 0.02381372 0.0133125 0.01374138 0.01000219
24 U.A.E. 0.01180579 0.01366827 0.02878684 0.02110963 0.01413343 0.02119755 0.02013877 0.03637166 0.03082229 0.03731081
25 U.K. 0.08862654 0.08090137 0.0561172 0.08388919 0.11218908 0.10283629 0.11892162 0.12864226 0.1055513 0.12092564
26 U.S. 0.2956435 0.2436892 0.17400617 0.20262105 0.29300914 0.25201526 0.20779679 0.18019425 0.19514398 0.18554508
27 Others 0.04439641 0.03743381 0.07342358 0.04072824 0.09685791 0.04438547 0.0433351 0.04642396 0.04864229 0.04110551
TOTAL 1 1 1 1 1 1 1 1 1 1
Source: Foreign Trade Statistic of India, Directorate General of Commercial Intelligence and Statistics, Ministry of Commerce, Government of India, Various Issues. Calculations are author's own. Note: Due to large two-dimensional table, only alternative years are shown. Moreover, instead of all the 40 countries, only top exporting countries are shown.
PRESENTABLE TABLE 2
HIRSCHMAN-HERFINDAHL INDEX (HHI) (D1)
Sr. No. MARKET 1995-96 1997-98 1999-00 2001-02 2003-04 2005-06 2007-08 2009-10 2011-12 2013-14
1 Australia 4.8772E-05 0.00046968 0.00029068 0.00034883 0.00042441 0.00023794 0.00035072 0.00066091 0.00073587 0.00047729
2 Austria 1.7695E-06 3.7907E-07 1.4864E-05 4.4894E-06 4.826E-05 0.00017519 0.00019093 2.3255E-05 2.9079E-05 8.6495E-05
3 Belgium 3.7851E-05 0.0002294 0.00014801 0.00087526 0.00010284 0.00031145 0.00020923 0.00027017 0.00045354 0.00027136
4 Canada 1.2193E-05 3.4116E-06 6.0784E-05 4.2424E-05 8.8029E-05 1.803E-05 0.00027009 0.00068202 0.00108439 0.00089645
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5 Chile 2.7649E-08 1.2282E-06 3.5967E-07 2.4633E-08 3.5865E-07 1.8598E-07 7.0012E-08 4.1519E-08 4.9161E-06 3.5596E-05
6 China P RP 2.4884E-07 1.4572E-05 2.4693E-05 1.9953E-06 7.3707E-06 0.00023184 1.065E-05 1.831E-05 0.00032343 0.00043605
7 Ethiopia 0 0 0 0 0 0.00011481 0.00335782 0.00351992 0.00050629 5.3673E-05
8 France 0.00019509 0.00068148 0.00069632 0.00172333 0.00105878 0.00041893 0.00025579 0.00019863 0.00012351 9.2302E-05
9 Germany 0.01660644 0.01655822 0.00781752 0.00948419 0.0020643 0.00653553 0.01061844 0.01905761 0.02479082 0.01691312
10 Italy 0.00119619 0.00192168 0.001533 0.00223177 0.00213381 0.00092737 0.00079492 0.00076418 0.00093824 0.00085491
11 Japan 0.01025434 0.01047088 0.00922403 0.01056816 0.01034874 0.03505447 0.00928191 0.00280311 0.00162356 0.00126423
12 Korea RP 0 0 3.5527E-06 4.8281E-06 2.6795E-06 2.6422E-06 9.8958E-06 2.1647E-05 2.0648E-05 4.4464E-05
13 Latvia 0 0 0 0 1.2911E-07 5.3922E-08 4.5724E-07 5.6512E-08 6.0435E-05 6.3748E-05
14 Lebanon 0 0 6.6062E-08 2.217E-07 1.9527E-06 1.9412E-06 1.453E-06 4.6133E-07 4.1031E-06 3.0554E-05
15 Malaysia 1.3382E-05 4.9128E-06 6.1731E-06 9.3667E-06 1.32E-05 1.1226E-05 0.00010288 1.9491E-05 2.705E-05 0.0001403
16 Netherland 0.04410419 0.04771866 0.06500927 0.03357611 0.01171514 0.00831004 0.01761196 0.02050948 0.02195478 0.02105332
17 New Zealand 1.3382E-05 5.4738E-06 1.4211E-05 4.7689E-05 5.8151E-05 4.0567E-05 3.4229E-05 6.1542E-05 2.0897E-05 0.00014981
18 Poland 0 0 2.7313E-05 3.9413E-05 0.00073274 0.00016652 0.00015247 0.00020441 0.00014179 0.00016297
19 Qatar 0 0 4.6977E-07 1.5765E-06 1.9287E-07 1.348E-06 1.453E-06 1.3955E-05 2.8803E-06 4.1304E-05
20 Saudi Arabia 0.00010974 7.3388E-06 1.8351E-05 3.6512E-05 8.2633E-06 3.143E-05 2.4395E-05 2.8428E-05 1.5537E-05 4.1023E-05
21 Singapore 7.078E-06 0.00045381 0.00090948 0.0003459 9.568E-05 4.4018E-05 1.646E-05 3.7367E-05 0.00010706 0.0003993
22 South Africa 3.3455E-06 3.7907E-07 1.4387E-06 9.8532E-06 2.3017E-06 5.923E-05 6.5366E-05 3.3724E-05 3.273E-05 0.00012514
23 Spain 0.00012044 0.000369 0.00086357 0.00095113 0.00017676 0.00025143 0.00056709 0.00017722 0.00018883 0.00010004
24 U.A.E. 0.00013938 0.00018682 0.00082868 0.00044562 0.00019975 0.00044934 0.00040557 0.0013229 0.00095001 0.0013921
25 U.K. 0.00785466 0.00654503 0.00314914 0.0070374 0.01258639 0.0105753 0.01414235 0.01654883 0.01114108 0.01462301
26 U.S. 0.08740508 0.05938443 0.03027815 0.04105529 0.08585436 0.06351169 0.04317951 0.03246997 0.03808117 0.03442698
27 Others 0.00197104 0.00140129 0.00539102 0.00165879 0.00938145 0.00197007 0.00187793 0.00215518 0.00236607 0.00168966
HHI (D1) 0.17014252 0.14646634 0.12684326 0.11106163 0.13725176 0.12961787 0.10368705 0.1016911 0.10581326 0.09600618 Source: Ibid, Table 1 Note : Ibid, Table 1
PRESENTABLE TABLE 3
INDIA'S FLORICULTURAL EXPORTS COEFFICIENTS
(1994-95 to 2013-14) (ALTERNATIVE YEARS SHOWN)
SR.NO. MARKET 1995-96 1997-98 1999-00 2001-02 2003-04 2005-06 2007-08 2009-10 2011-12 2013-14
1 Australia 0.00698243 0.02166981 0.01704847 0.01867619 0.02060102 0.01542539 0.01872753 0.02570808 0.0271269 0.0218469
2 Austria 0.00132999 0.00061562 0.00385518 0.00211873 0.00694686 0.01323598 0.0138178 0.00482239 0.00539253 0.00930029
3 Belgium 0.00615119 0.01514424 0.01216524 0.02958371 0.01014081 0.01764798 0.01446459 0.01643687 0.0212964 0.01647291
4 Canada 0.00349121 0.00184686 0.00779604 0.00651312 0.00938225 0.00424613 0.01643436 0.0261156 0.03293003 0.02994078
5 Chile 0.00016625 0.00110812 0.0005997 0.00015694 0.00059887 0.00043125 0.0002646 0.00020376 0.00221723 0.00596622
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6 China P RP 0.00049874 0.00381684 0.0049689 0.00141248 0.00271486 0.01522636 0.00326335 0.00427902 0.01798423 0.02088177
7 Ethiopia 1.6625E-05 1.2312E-05 8.5671E-06 7.8471E-06 3.9924E-06 0.01071484 0.05794656 0.05932894 0.02250082 0.00732617
8 France 0.01396486 0.02610227 0.02638658 0.04151136 0.03253844 0.02046767 0.01599337 0.0140936 0.01111354 0.00960737
9 Germany 0.12884241 0.12866448 0.08841218 0.09738298 0.04543404 0.08084233 0.1030455 0.13804931 0.157451 0.13005045
10 Italy 0.03457964 0.04383211 0.03915152 0.04723977 0.0461926 0.03045271 0.02819419 0.02764382 0.03063068 0.02923887
11 Japan 0.1012452 0.10231596 0.09603687 0.1027975 0.10172753 0.18722777 0.0963424 0.05294437 0.04029344 0.03555604
12 Korea RP 1.6625E-05 1.2312E-05 0.00188476 0.0021972 0.0016369 0.00162547 0.00314575 0.00465258 0.00454396 0.00666813
13 Latvia 1.6625E-05 1.2312E-05 8.5671E-06 7.8471E-06 0.00035932 0.00023221 0.00067619 0.00023772 0.00777401 0.00798421
14 Lebanon 1.6625E-05 1.2312E-05 0.00025701 0.00047083 0.00139736 0.00139326 0.00120538 0.00067921 0.00202562 0.00552753
15 Malaysia 0.00365746 0.00221623 0.00248445 0.00306038 0.00363313 0.00335046 0.01014285 0.00441486 0.00520092 0.0118447
16 Netherland 0.20997157 0.2184218 0.25495605 0.18323067 0.10823522 0.09115909 0.13270967 0.1432113 0.14817147 0.14509761
17 New Zealand 0.00365746 0.00233935 0.00376951 0.00690548 0.00762557 0.00636919 0.00585051 0.00784487 0.00457133 0.01223953
18 Poland 1.6625E-05 1.2312E-05 0.00522591 0.00627771 0.02706879 0.01290425 0.01234782 0.01429736 0.01190737 0.01276596
19 Qatar 1.6625E-05 1.2312E-05 0.00068537 0.00125554 0.00043917 0.00116105 0.00120538 0.00373565 0.00169714 0.00642685
20 Saudi Arabia 0.01047364 0.00270873 0.00428354 0.0060423 0.00287456 0.00560622 0.00493913 0.00533179 0.00394175 0.00640491
21 Singapore 0.00265997 0.02130043 0.03015609 0.01859772 0.00978149 0.00663458 0.00405714 0.00611288 0.01034709 0.01998245
22 South Africa 0.00182873 0.00061562 0.00119939 0.00313886 0.00151713 0.00769611 0.00808488 0.00580724 0.00572101 0.01118666
23 Spain 0.01097239 0.01920733 0.02938506 0.03083925 0.01329485 0.01585664 0.02381365 0.0133125 0.01374138 0.01000219
24 U.A.E. 0.01180363 0.01366675 0.02878536 0.0211088 0.01413326 0.02119747 0.02013871 0.03637166 0.03082229 0.03731081
25 U.K. 0.08861033 0.0808924 0.05611432 0.0838859 0.11218774 0.10283595 0.11892127 0.12864226 0.1055513 0.12092564
26 U.S. 0.29558943 0.2436622 0.17399722 0.2026131 0.29300563 0.25201442 0.20779618 0.18019425 0.19514398 0.18554508
27 Others 0.04438829 0.03742967 0.0734198 0.04072664 0.09685675 0.04438532 0.04333497 0.04642396 0.04864229 0.04110551
SUM 1 1 1 1 1 1 1 1 1 1
Source: Ibid, Table 1 Note: Ibid, Table 1
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PRESENTABLE TABLE 4
ENTROPY INDEX ( D2 )
SR.NO. MARKET 1995-96 1997-98 1999-00 2001-02 2003-04 2005-06 2007-08 2009-10 2011-12 2013-14
1 Australia 0.01505407 0.0360617 0.03014706 0.03228575 0.03473562 0.02794717 0.03235217 0.04087405 0.042497 0.03627918
2 Austria 0.00382524 0.00197656 0.00930624 0.00566532 0.01499279 0.0248604 0.02569504 0.01117221 0.01223138 0.01889356
3 Belgium 0.01360053 0.02755877 0.02329497 0.04523193 0.02022004 0.03094229 0.02661042 0.02932635 0.03560106 0.02937498
4 Canada 0.00857799 0.00504851 0.01643503 0.01423906 0.01902432 0.01007185 0.02932296 0.04134361 0.04881574 0.04562187
5 Chile 0.00062829 0.00327494 0.00193226 0.00059705 0.00192995 0.00145127 0.00094657 0.00075206 0.00588496 0.01327067
6 China P RP 0.00164692 0.00923025 0.01144706 0.0040256 0.00696702 0.02767244 0.00811379 0.01013552 0.03138443 0.03508624
7 Ethiopia 7.9454E-05 6.045E-05 4.3411E-05 4.0062E-05 2.1554E-05 0.02110839 0.07167829 0.07278079 0.03707689 0.01564227
8 France 0.0259043 0.04132829 0.0416543 0.05736177 0.04840429 0.0345685 0.02872505 0.02608694 0.0217175 0.01938186
9 Germany 0.11466217 0.11458104 0.09314116 0.09850453 0.06100059 0.08830902 0.10170292 0.11871768 0.12641026 0.11521015
10 Italy 0.05052706 0.0595331 0.05509603 0.0626254 0.06168688 0.0461777 0.04369649 0.04308019 0.04637005 0.04485358
11 Japan 0.10070106 0.10129859 0.09772347 0.10156573 0.10097083 0.13623249 0.09790146 0.06756656 0.05619991 0.05152378
12 Korea RP 7.9454E-05 6.045E-05 0.00513548 0.00584044 0.00456037 0.00453347 0.00787154 0.01085125 0.01064453 0.01450982
13 Latvia 7.9454E-05 6.045E-05 4.3411E-05 4.0062E-05 0.00123768 0.00084388 0.00214348 0.00086149 0.01639814 0.01674902
14 Lebanon 7.9454E-05 6.045E-05 0.00092269 0.00156651 0.00398902 0.00397911 0.00351836 0.00215173 0.00545589 0.01247822
15 Malaysia 0.00891258 0.00588273 0.00647142 0.00769449 0.00886381 0.00829204 0.02022322 0.01039736 0.01187848 0.02281853
16 Netherland 0.14232703 0.14431216 0.15132526 0.13504134 0.10451533 0.09482369 0.11639931 0.12087359 0.12286903 0.12164109
17 New Zealand 0.00891258 0.00615462 0.00913622 0.01492141 0.01614888 0.01398621 0.01306306 0.0165167 0.01069673 0.02340486
18 Poland 7.9454E-05 6.045E-05 0.01192469 0.01382477 0.04243117 0.02437958 0.0235647 0.02637497 0.02291197 0.02417804
19 Qatar 7.9454E-05 6.045E-05 0.00216855 0.00364254 0.00147445 0.00340786 0.00351836 0.00906879 0.00470156 0.01408766
20 Saudi Arabia 0.02073679 0.00695394 0.01014426 0.01340663 0.00730549 0.01262145 0.01139136 0.01211984 0.00947719 0.01404909
21 Singapore 0.00684976 0.03560605 0.04585611 0.0321841 0.01965684 0.01445135 0.00970379 0.01353242 0.02054086 0.0339572
22 South Africa 0.00500679 0.00197656 0.00350347 0.00785727 0.00427675 0.01626749 0.01691621 0.01298516 0.01282952 0.02182853
23 Spain 0.02150257 0.03297001 0.04501419 0.04659491 0.02494534 0.0285386 0.0386537 0.0249708 0.02558603 0.02000343
24 U.A.E. 0.02275721 0.0254794 0.0443533 0.03536856 0.02614311 0.03547855 0.03415461 0.05234744 0.04657665 0.05328601
25 U.K. 0.09326376 0.08834197 0.07019488 0.09028732 0.10658448 0.10158701 0.10997131 0.1145709 0.10307469 0.11094705
26 U.S. 0.15645877 0.14941655 0.13214353 0.14047824 0.15620834 0.15084943 0.14179231 0.13411121 0.13848292 0.13573561
27 Others 0.06004544 0.05340405 0.08327177 0.05661498 0.09820016 0.06004272 0.05907256 0.06189511 0.06386664 0.05697634
ENTROPY INDEX (D2) 0.93305519 0.98389365 1.07760124 1.11378809 1.06803061 1.09421786 1.15910598 1.16064354 1.17168783 1.22868679 Source: Ibid, Table 1 Note: Ibid, Table 1
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exports coefficients are weighted by the market share, these are HHI shown in the Table-2. The value of HHI ranges from 0 to 1 where 0 shows that there is perfect competition in the market and 1 shows that it’s the monopoly. Therefore, an increase in HHI indicates a decrease in competition and an increase of market power. The Hirschman-Herfindahl Index shows that there is a decreasing trend of the indices in general that starts from 0.163606018 in 1994-95 and 0.170143 in 1995-96 to 0.099525 in 2012-13 and 0.096006 in 2013-14. It is important to mention here that the two dimensional tables in the paper become so heavy that it was not possible to present these in a few pages. Keeping in views the limitations of the presentations of the tables, these are shown in a peculiar manner. On the first dimension of the tables, the number of years reduced and figures of alternative years are shown only. On the second dimension of the tables, the number of countries is reduced from all the forty countries of the study to top few exporting countries of India’s floricultural products. However, the calculations and applications of Hirschman-Herfindahl Index and Entropy Index have been made for all the forty countries and for the whole of the period, i.e., 1994-95 to 2013-14. It has been done so that since the tables in this manner are fitted into the pages in the paper on the one hand and conveys the same meaning to the academicians on the other. In case, the exporters or policy makers are interested in the results of the study then they will have to consult the full quantum of the calculations and results of the study for all the countries and all the years both.
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Like the HHI in the Tables 1 and 2, the Entropy index calculations are given in the Tables 3 and 4. The Index is derived from Information Theory. It shows the greater information about the concentration of importing countries of India’s floricultural products. Table-3 shows the export coefficients country-wise and year-wise both for the period from 1994-95 to 2013-14 that may help the exporters and policy-makers for devising an export strategy for a particular country. Table-4 shows the Entropy Index in toto at the end of the table, i.e., last row of the table. In case the detailed information for Entropy Index is required then it may be found in the Table-4 country-wise and year-wise both. Entropy Index shows that there is an increasing trend of the indices in general that starts from 0.947869493 in 1994-95 and 0.933055 in 1995-96 to 1.195627 in 2012-13 and 1.228687 in 2013-14. The higher value of the Entropy Index reveals the greater information about the concentration of importing countries of India’s floricultural products. Keeping in views the limitations of the presentations of the tables, the results are shown in a peculiar manner as described in detail in the preceding paragraph. The indices D1 and D2 in Figure-1 demonstrate the country’s concentration of the exports of floricultural products among the forty major importing countries during the period from 1994-95 to 2013-14. The indices and line graph D1 and D2 are representing Hirschman-Herfindahl Index (HHI) and the Entropy Index respectively. The line graphs are merely graphical presentation of the indices of these two Indices given in the Table-2 and Table-4.
Conclusion and Policy Implications –
The present study has examined the dynamic behaviour of the exports of floricultural products to major forty countries for the period 1994-95 to 2013-14. The whole period may be described as the post-WTO period, i.e., the era of globalization. The Hirschman–Herfindahl Index (HHI) has shown that broadly the indices are going downward that reveals that there is no market power into a few hands and the market has been heading towards perfect competition during the period.
Likewise the Entropy Index also puts more light on the problem. The D2 Index signifies that the higher values of the Entropy Index exhibits high concentration of Indian exports of floricultural products in the various importing countries for the period. The results of the present study provide an adequate information regarding the production and export marketing of floricultural production in India. In the light, a strategic marketing approach having backward and forward linkages coupled with horizontal and vertical integration may go a long way in the direction. India needs a three dimensional approach. First is the achieving the advantages of geographical location and size of the nation. The location is in the proximity of the countries of Middle East Asian, European and some countries of East Asia or South East Asia. The U.S. is the most lucrative, therefore, a segregate policy may be required. The size of the nation provides ample opportunity keeping in view the diversity of natural resources and agro-climatic conditions. Second emphasis must be on the quality of the raw materials, seeds, bulbs, tubers, etc. and the corresponding production of international standards. Lastly the third thrust area is preparing a comprehensive country-wise strategy, dynamic in nature, that too quite updated as per changes in the global market and technological advancement. Above all the political will and the Government support to tackle the bottlenecks in the production and marketing in the global market; may go a long way.
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