EXPORT PERFORMANCE OF INDIAN MANGOES – AN …€¦ · Mango peel and pulp contain other...

EXPORT PERFORMANCE OF INDIAN MANGOES – AN ECONOMETRIC ANALYSIS

Thesis submitted to the University of Agricultural Sciences, Dharwad

in partial fulfilment of the requirements for the Degree of

MASTER OF BUSINESS ADMINISTRATION

IN

AGRIBUSINESS

BY

POOJA TRIVEDI

DEPARTMENT OF AGRIBUSINESS MANAGEMENT COLLEGE OF AGRICULTURE, DHARWAD

UNIVERSITY OF AGRICULTURAL SCIENCES, DHARWAD - 580 005

JUNE, 2012

ADVISORY COMMITTEE

DHARWAD (A. D. NAIK) JUNE, 2012 MAJOR ADVISOR

Approved by :

Chairman : ____________________________ (A. D. NAIK)

Members : 1. __________________________ (B. K. NAIK)

2. __________________________ (N. M. KERUR)

3. __________________________ (S. G. ANGADI)

4. __________________________ (S. G. ASKI)

C O N T E N T S

Sl. No.

Chapter particulars

CERTIFICATE

ACKNOWLEDGEMENT

LIST OF TABLES

LIST OF FIGURES

1. INTRODUCTION

2. REVIEW OF LITERATURE

2.1 Growth rate and trend analysis

2.2 Nominal protection coefficient

2.3 Markov Chain Analysis

2.4 Co-integration Analysis

2.5 Problems of Mango Export

3. METHODOLOGY

3.1 Description of the study area

3.2 Data Collection

3.3 Analytical tools and techniques employed

4. RESULTS

4.1 Trend in area, production, productivity and export of mangoes

4.2 Behaviour of Indian mango export prices

4.3 Export competitiveness of Indian mangoes

4.4 Direction of trade in Indian mango export

4.5 Market integration in Indian mangoes

4.6 Problems associated with mango export

5. DISCUSSION

5.1 Annual growth and trend in area, production, productivity and export of mangoes

5.2 Behaviour of export prices of mangoes for different countries

5.3 Export competitiveness of Indian mangoes in international market

5.4 Direction of trade of Indian mango exports

5.5 Market integration between domestic market prices and world market prices

5.6 Problems associated with mango export from India

6. SUMMARY AND POLICY IMPLICATIONS

REFERENCES

LIST OF TABLES

Table No.

Title

1.1 Major mango producing countries in the world (2010-11)

1.2 Leading mango producing states in India (2010-11)

3.1 Estimation of Nominal Protection Coefficient (NPC) (Exportable Hypothesis)

4.1 Trend in area of mango cultivation across different states

4.2 Trend in mango production across the states

4.3 Trend in mango productivity across the states

4.4 Trend in mango exports to major countries

4.5 Growth Rate of area under mango in different states

4.6 Growth Rate of mango production in different states

4.7 Growth Rate of mango productivity in different states

4.8 Growth Rate of mango exports to different countries

4.9 Behaviour of export prices of mangoes in different countries

4.10 Nominal Protection Coefficient for mango exports to different countries during 2010-11

4.11 Transitional Probability Matrix of Indian mango exports to different destinations

4.12 Projections of Indian mango exports to major importing countries

4.13 Co-integration between domestic and international market


LIST OF FIGURES

Figure No.

Title

1 Trend in area of mangoes across the states

2 Trend in production of mangoes in India

3 Trend in productivity of mangoes in India from 1990 to 2010

4 Trend in export of mangoes from India during 1991 to 2010

5 Behaviour of prices of Indian mangoes in different destinations during 1991 to 2010

6 Projection of share of Indian mangoes to different destinations up to 2015-16

1. INTRODUCTION India, known as fruit and vegetable basket of the world, is the second largest producer of fruits {71.52 million MT(Metric Tonnes)]} after China, obtained from 6.33 million hectare (Ha) area and contributing about 12 per cent share in global fruit production. The horticulture sector contributes about 30.4 per cent of the agriculture Gross Domestic Product, besides providing employment for 19 per cent of the labour force. The economic importance of horticultural produce has been increasing over the years due to increasing domestic and international demand. Area, production, productivity, availability and exports have increased manifolds. This has provided ample opportunities for utilization of waste/marginal lands, employment generation and effective land use strategies.

The country ranks first in production of mangoes (39%), bananas (28%,) papayas, lemons, limes, pomegranate, sapota and aonla. The quantum of mangoes produced by India constitutes huge share of world’s mango production. But it contributes only 0.37 per cent to the export earnings from the agricultural products.

Trade in fruits has become steadily more important over the last decades. The composition, volume, and direction of this trade have changed as incomes and insistence on quality have grown on the demand side, while technology and trade agreements have influenced the supply side. Lower prices and greater availability of produce year-round, in tandem with increasing incomes; have enhanced the array of fruits in the global consumer’s basket of goods. Other factors, such as concern for a healthy diet and improved handling and transportation, have furthered the globalization of fruit trade. Globalization of markets is likely to continue as the basic factors of supply are combined with innovations in technology and lower trade barriers, enabling suppliers to meet the preferences of a more affluent clientele. Developed countries will continue to dominate global trade in fruits, but new varieties will find their way into the diets of the relatively affluent everywhere.

The total agri exports from India to the world in 2010-11 stood at Rs 43, 62, 688 Lakhs with the share of fresh mangoes to the extent of Rs 16292.13. Though India's share in the global market is still nearly 1% only, there is increasing acceptance of horticulture produce from the country. The research and development programmes in horticulture have greatly contributed to the present scenario. Still there are a few gaps which need to be addressed for consolidation of strengths. Multi-location testing of varieties for adaptation, quality evaluation of clones and production of nucleus planting material of elite clones are necessary for providing fillip to the growth and sustenance of horticulture. Studies need to reorient towards identification of resilient varieties which can adapt to dynamics of weather parameters and thrive to produce satisfactorily under different kinds of biotic and abiotic stresses thus coping with the present problem of climate change. The recent advances in some frontier technologies such as satellite imagery availability, use of GPS and modern mapping techniques using GIS could greatly improve the understanding of the land use planning and these need to be exploited for expanding horticultural crops. Adoption of good horticultural practices and value chain concepts in production and utilization will open up new vistas in the prevailing scenario of demand for food and environmental safety as future markets are going to be highly quality conscious with stringent regulations. Considerable efforts are needed to harmonize and integrate pre-harvest protocols for ensuring efficient postharvest management system including value addition to make the produce export competitive. Supply chain management, storage and cold chain are crucial to reduce losses in the post-harvest stage. Market intelligence, creation of alternate markets and integration of farmers are crucial. Rapid expansion of mobile telephone technology and its affordable access even in rural areas should be exploited gainfully to the stakeholders issues on different aspects of production, utilization, and market access. All the above developments should in direction of making India more export competent.

Mango (Mangifera indica l.) belonging to the Anacardiaceae family, is the most important fruit of India. It is known as “King of fruits” and is the most important commercially grown fruit crop of India.

Mango is rich in a variety of nutrients. The fruit pulp is high in prebiotic dietary fibre, vitamin C, diverse polyphenols and provitamin A carotenoids. Mango contains essential vitamins and dietary minerals too. The antioxidant vitamins A, C and E compose 25 per cent, 76 per cent and 9 per cent of the dietary reference intake (DRI) in a 165gm serving. Vitamin B6 (pyridoxine, 11per cent DRI), vitamin K (9 per cent DRI), other B vitamins and essential nutrients such as potassium, copper and 17 amino acids are also present in mango in good proportion. Mango peel and pulp contain other phytonutrients, such as the pigment antioxidants carotenoids, polyphenols, and Omega-3 and Omega-6 polyunsaturated fatty acids.

World Scenario

Mango covers an area of 4,369 thousand ha (2010-11) where India occupies top position among mango growing countries of the world and produces 42 per cent of the total world mango production. China and Thailand stand second and third among mango producing countries with a share of 11.29 per cent and 6.60 per cent respectively. World mango production currently averages 67.8 million tonnes per year with Asia accounting for 75 per cent of the production followed by South and North America with about 10 per cent share Brazil, Egypt, Pakistan, Mexico and China have higher productivity/ha compared to India (having an average productivity of 6.2 tons/ha). The details are given below in the table 1.1.

Among internationally traded tropical fruits, mango ranks only second to pineapple in quantity and value. The major markets for fresh and dried mangoes are Malaysia, Japan, Singapore, Hong Kong and the Netherlands. Southeast Asian buyers who consume mangoes all year round, source their supplies mainly from India, Pakistan, Indonesia, Thailand, Malaysia, Philippines, Australia and most recently, South Africa. Table 1.1: Major mango producing countries in the world (2010-11)

S No. Country Production (in MT) Share (per cent)

1 India 16337400.00 42.24

2 China 4366300.00 11.29

3 Thailand 2550600.00 6.60

4 Pakistan 1784300.00 4.61

5 Mexico 1632650.00 4.22

6 Indonesia 1313540.00 3.40

7 Brazil 1188910.00 3.07

8 Bangladesh 1047850.00 2.71

9 Philippines 825676.00 2.14

10 Nigeria 790200.00 2.04

Source: Food & Agricultural Organisation (FAO) Note: The production figures include mango, mangosteens and guava production put together

Most international trade in fresh mangoes takes place within short distances. North America imports majority of its mangoes from Mexico, Haiti and Brazil. India and Pakistan are the predominant suppliers to the West Asian market. Southeast Asian countries get most of their supplies from the Philippines and Thailand. European Union buyers source mangoes from South America and Asia. Although Asia accounts for 75 per cent of the world production, its dominance does not translate into international trade.

Asian producers find it easier to expand sales to the European Union. Europe’s acceptance of different varieties is greater, because of a large demand from Asian immigrant groups and because phytosanitary restrictions are comparatively less stringent there. Transportation costs are not as big a factor in exporting mangoes to the European Union as in exporting to the US market. For example, India and Pakistan are able to compete with non-Asian suppliers to the European Union, whereas proximity gives Mexico and Haiti a clear advantage in supplying to the US market. The European Union imports 54 per cent of its mangoes during May-July and November-December periods, with peak imports in June. French imports peak in April and May, whereas the UK imports are concentrated during May to July. German imports are spread more evenly throughout the year. Among the top suppliers, Brazil supplies mainly during November to December period, US during June to October, South Africa during January to April and Venezuela during April to July. Pakistan supplies the majority of its exports to the European Union during June and July, while Indian exports take place mainly during the month of May.

Indian scenario

India has the richest collection of mango cultivars. The fruit is cultivated in the largest area i.e. 2,297 thousand ha with production of 15.2 million tons. Mango is grown almost in all the states of the country. Andhra Pradesh tops the list of mango producing states with 27.1 per cent share, followed by Uttar Pradesh with 23.88 per cent. Other major producers are Maharashtra, Karnataka, Bihar and Gujarat (Table 1.2).

There are 1000 varieties of mango in India but only about 30 varieties are grown commercially. Some of the most important varieties have been listed below:

Major mango varieties

Variety Characteristics

Alphonso This variety is medium in size, ovate oblique in shape and orange yellow in colour. The pulp is yellow to orange in colour. It is soft, firm and fibreless. It is a mid-season variety of South India.

Banganpalli The flesh is firm to meaty, fibreless. Fruit is large in size and obliquely oval in shape. The colour of fruit is golden yellow. Good keeping quality and a mid season variety of South India.

Chausa Fruit is large in size, ovate to oval oblique in shape and light yellow in colour. It is a late variety of North India.

Dashehri Fruit size is medium, shape is oblong to oblong-oblique and fruit colour is yellow. The pulp is firm and fibreless and a mid season variety of North India.

Langra Fruit is of medium size, ovate shape and lettuce green in colour. The lemon-yellow flesh is juicy and flavourful. It is scarcely fibrous, a mid season variety of North India.

Totapuri Fruit size is medium to large, shape is oblong with necked base and colour is golden yellow. Flesh is cadmium yellow and fibreless, a mid season variety of South India

Kesar Fruits are medium sized, flesh is sweet and fibreless. Colour is apricot yellow with red blush, an early season variety of West and Central India.

Table 1.2: Leading mango producing states in India (2010-11)

S. No. State Production (MT) Share (%)

1 Uttar Pradesh 3,623.22 23.86

2 Andhra Pradesh 3,363.40 22.14

3 Karnataka 1,778.75 11.71

4 Bihar 1,334.87 8.79

5 Gujarat 911.3 6.00

6 Tamil Nadu 823.74 5.42

7 Orissa 642.01 4.23

8 West Bengal 620.17 4.08

9 Jharkhand 427.94 2.82

10 Kerala 380.86 2.51

Subtotal 13,906.26 91.56

11 Other states 1,28,174 08.44

Total 1,51,88,000 100.00

Source: National Horticulture Board

Export scenario

India is one of the 15 leading exporters of agricultural products in the world. As per the International trade Statistics 2011, published by the World Trade Organization (WTO), India’s agricultural exports amounted to US $ 23.2 billion with a 1.7 per cent share of world trade in agriculture in 2010 (Source: APEDA).

India exports mango to over 50 countries worldwide. Exports to UAE (United Arab Emirates) and Bangladesh alone accounted to 73 per cent (in terms of value) in 2010-11. Other major importing nations for Indian mango are Saudi Arabia, Qatar, Bahrain, UK (United Kingdom), Kuwait, Singapore and Malaysia. Although a lion’s share of Indian mangoes is exported to the Gulf countries, efforts are being made to tap the European, American and Asian markets also. About 13,000 tonnes of Alphonso variety is exported to Middle East, the UK and the Netherlands every year.

Varieties such as Alphonso, Dashehari, Kesar and Banganapalli that are currently in demand in the international markets are produced and exported from India. ‘Mahamango’, a cooperative society in Maharashtra, was established in 1991 with the support of the Maharashtra State Agricultural and Marketing Board (MSAMB), Pune. It was mainly formed to boost the export of Alphonso mangoes as well as for domestic marketing. Facilities like pre-cooling, cold storages, packaging houses, grading packing lines etc have been made available at the facility centre, with financial assistance from APEDA, New Delhi, and MSAMB, Pune. A similar association named ‘Mangrow’ has been formed for the export of Kesar mangoes from Aurangabad district of Maharashtra.

Domestic strengths for exporting mango

Domestic strengths for exporting mango from India are listed below:

� India occupies top position in total production among mango growing countries of the world.

� India cultivates a wide variety of mangoes; some of them are very colourful and attractive with par excellence edible quality.

� Mangoes are cultivated with sizeable production in almost all the states i.e. Andhra Pradesh, Uttar Pradesh, Maharashtra, Gujarat, Tamil Nadu etc.

� Agri Export Zones for facilitating exports have been established in almost all mango growing areas.

� Packhouses on modern lines have been provided in all mango exporting regions i.e. in Ratnagiri and Sindhudurg in Maharashtra and in Navsari and Borsad in Gujarat for Alphonso variety; in Latur and Aurangabad for Kesar mango; in Saharanpur and Malihabad in U.P. for Dashehari and Chausa mangoes.

� Facilities for facilitating mango exports like Post-harvest Management Centre have been established at Malihabad and Saharanpur. Similarly a mango Export Facility Centre has been established at Ratnagiri.

� Mango farmers of Alphonso and Kesar are already being trained in GLOBALGAP requirements.

� Facilities for Vapour Heat Treatment and irradiation for eliminating fruit fly have been set up.

� India is in advantageous position, as it is nearer to Middle East countries compared to Australia, Kenya etc. main suppliers in Middle East.

Even after having innumerable domestic advantages, India ranks thirteenth in mango export with a meagre share of 1.51 per cent (in 2010). Mexico, Thailand and Brazil rank first second and third respectively in mango export.

Therefore, it is imperative to study the market opportunities and to plan for appropriate export marketing strategy and policy so as to strengthen the export trade in mango. Looking into the importance of this crop in the Indian economy and its problems in the export front, the present study was undertaken.

Specific objectives of the study

a. To analyze the growth and trends in area, production, productivity and export of mangoes from India.

b. To study the behavior of export prices of Indian mangoes to different destinations over the years.

c. To study the export competitiveness and direction of trade of mangoes.

d. To study the integration of domestic and export markets for mangoes.

e. To identify the problems associated with export of mangoes.

Hypotheses

1. There is positive growth and trend in area, production, productivity and export of Indian mangoes

2. There is positive trend in behavior of export prices of Indian mangoes to different destinations over the years.

3. Indian mango is export competitive and there is stability in direction of trade for mango.

4. Domestic and export markets for mango are highly integrated with respect to prices.

5. Indian mango is subjected to supply chain constraints, market access issues and technological constraints

Limitations of the study

Information on mango varieties demanded by different destinations has not been made available in the export data base. Absence of availability of variety wise quantity and price data of mangoes in India, makes the study difficult. While working out the area, production and productivity census, specially for perennial crop such as mango, the recently planted orchards which are in juvenile phase, must not be included for calculation of production and productivity. So with these limitations, earnest effort has been taken to conduct the study.

Organization of the thesis

The entire study has been presented in seven chapters. The first chapter deals with the importance and the current status of the present study. The specific objectives of the study have been indicated.

Chapter II deals with the reviews of the relevant research studies connected with the objectives.

Chapter III provides the main features of the study area and the study out lines. The nature and sources from which relevant data have been collected and the various statistical tools and techniques employed in the study for evaluating the objectives have been discussed.

Chapter IV is devoted to results of the analysis of the data through a variety of tables into which relevant details have been compressed and summarized under appropriate heads and presented in the tables.

Chapter V provides the discussion on casual relationship between certain variables and the outcome which they produced.

Chapter VI briefs the summary of the main findings along with the policy implications that emerged from the findings of the study.

Chapter VII, the final chapter list the references cited while undertaking the research..

Scope of the study

Indian mango, which is known all over the world for its high nutritive value comprises of 52 per cent of world production. Even though India is the highest mango producing country, less than 1 percent of its production is exported. The export of fresh fruits particularly mango has remained so meagre on account of various reasons like strict quarantine measures in some countries, nearness of some consuming countries to other producing countries, legal and political hurdles etc. Nearly 15 percent of India’s mango production is wasted due to lack of infrastructural facilities.

So, this study aims at identifying the reasons for poor export performance of mango and suggesting suitable policy implications so as to gain better price realization of mango in the international market.

2. REVIEW OF LITERATURE

A review of concepts and empirical studies related to the present study would be helpful to project the current thinking on the subject matter of study as well as to formulate relevant concepts and design of the study to draw meaningful conclusions. This would help the researcher to have better and precise understanding of the current research problem and would also facilitate to modify and improve the present study.

This chapter briefly reviews the concepts, analytical tools and findings of the past studies, which are relevant for the present study. The reviews of the past studies were classified under the following headings.

2.1 Growth rate and trend analysis

2.2 Nominal protection coefficient



2.5 Problems of Mango Export

2.1 Growth rate analysis

Growth rates are measures of performance of economic variables. They are not developed to predict; but describe the trends in variables over time. Hence, they are commonly used as indicators of trends in the time series data. Price indices, productivity indices and output series are usually discussed in terms of the changing growth rates over a period of time. Policy decisions are often based on such growth rates that depend on nature and structure of the data.

Jeromi and Ramanathan (1993) examined the growth of world pepper market for the period from 1975 to 1990. Among the exporting countries, Sri Lanka recorded the highest annual compound growth rate of 24.59 per cent. This was mainly due to its low base in the initial years. Positive and statistically significant growth rate was recorded in the case of India. In contrast, the growth rate in total exports from the other producing countries was statistically non-significant. The growth rates of pepper imports ranged from a negative level of 2.56 per cent for Argentina to a high and positive level of 11.64 per cent for Saudi Arabia.

Laxminarayana (1993) analysed the growth performance of silk goods export such as sarees, dress materials, readymade garments, carpet and other silk exports apart from total silk exports for the period 1970-71 to 1989-90. The exponential form of the function was employed to estimate the growth rates. He found that there has been a significant increase in the growth rates of export of all silk variety both in terms of quantity and value during the study period. This growth rate was attributed to tremendous increase in the production of silk under the influence of intensive production and efforts such as increasing the area under the mulberry cultivation, improving the productivity and also by improving the technology in silk reeling and weaving.

Singh (1993) analysed the growth rate in total Indian food grain production during the last 40 years. Total food grain production has increased by 236 per cent with an annual growth rate of 2.74 per cent during the period 1950-51 to 1989-90. Average production increased by 72 per cent between the period 1950-51 to 1965-66 (pre-green revolution) and 1966-67 to 1989-90 (post-green revolution period).

Tripathy and Gowda (1993) computed the growth in groundnut production in Orissa during the post green revolution period (1970-71 to 1989-90) using the growth model, 1n Y = 1n a + t 1n b + u. The study showed that area was the dominant source of growth in output during the post green revolution period and per hectare yield was almost stagnant.

Mamatha (1995) estimated the growth rates of production and export of selected spices for the period from 1970-71 to 1991-92. The spices considered were pepper, chillies, turmeric and ginger. She found that positive growth rate in respect of production and export of the selected spices was due to the increased domestic production and demand for these species in the international market. The increased domestic production and exports were

attributed to the several measures taken by the spice board such as improved methods of production, assistance for the export of spices by setting up facilities for upgrading quality and technical advice on scientific post-harvest operation and processing.

Nagaraja (1997) studied the growth in export of mango from India during the year 1970-71 to 1992-93. He reported that the export of fresh mangoes exhibited a compound growth rate of 27.5 per cent per annum while the value registered a compound growth rate (CGR) of 16 per cent per annum. The unit value in rupees registered a growth of 11.5 per cent per annum and while in dollars it was 3.5 per cent per annum.

Ananthi (2000) analysed the growth of area production, productivity and export of Indian Non-basmati and basmati rice. The growth rates were calculated by sub-dividing the study period into 1949-50 to 1969-70 as first period and 1970-71 to 1997-98 as second period. The area, production and productivity showed positive trend. For the export, the study period considered was 1980-81 to 1998-99 for Basmati and non-basmati rice. The growth rate was also positive and significant.

Ashalatha (2000) analysed the growth rate in cashew in two periods; period-I, from 1956-57 to 1970-71 and period-II, from 1971-72 to 1998-99. It was observed that the growth rate of area, production, productivity, kernel export, raw cashew import, cashew nut shell liquid value and cashew nut shell liquid - unit value of export were showing positive trend but the cashew nut shell liquid quantity exported showed non-significant negative growth.

Angles (2001) studied the production and export of turmeric in south India. He found that all the states registered significant growth in area, production and productivity, except in the case of area in Tamil Nadu and Kerala, production in Tamil Nadu and productivity in Karnataka. The analysis of price trend in important markets of south India revealed an increasing trend in all the markets.

Jayesh (2001) studied the production and export performance of pepper and cardamom in south India. He found that all the south Indian states except Karnataka (-0.47 %) and Tamil Nadu (-1.62 %) recorded significant growth in area and production of pepper and in case of cardamom, all the states recorded a negative growth in area, while the productivity and production showed significant growth. A positive growth was found in the export quantity, value and unit value of pepper. But a negative growth was recorded in the export of cardamom.

Mamale Desai (2001) analyzed the export growth of mangoes from India to different countries using the exponential model of the form y= ab

t and observed that the Hong-Kong

depicted negative growth, but it was not significant. The possible reason that could be attributed for this phenomenon is firstly the increased imports from Pakistan and Sri Lanka. The second reason would be the changing over the political scenario i.e., from capitalized to communist governed economy led to the changes in the import policies. But export value growing at positive rate, the possible reason could be the inflation over the years which have resulted in to a positive growth in value terms inspite of negative growth in quantity of mango exports.

Varghese (2004) worked out the trend in area, production and productivity of cardamom in Kerala for a period from 1970-71 to 2002-03 using semi-logarithmic growth equation. The area under cardamom registered a negative percentage annual trend growth rate of -1.216 which is statistically significant. The output grows at an average annual trend growth rate of 4.14 per cent and yield registered an average annual growth rate of 5.51 per cent.

Lathika and Ajith Kumar (2005), analysed the Growth trends in Area, Production and Productivity of coconut in India of all the coconut producing states/union territories for which the period has been divided into two sub-periods as phase I (1951 to 1995) and phase II (1996 to 2002).

Smita and Patil (2006) studied the trends in export of grapes from India. The compound growth rate for quantity of grapes exported was 12.05 per cent per annum. With respect to value obtained from export of grapes, the corresponding compound growth rate indicated an increase of 22 per cent per annum.

Thanuja (2006) analyzed the export performance and competitiveness of ginger from India for the period of 1985-86 to 2003-04. The study period is divided in to Pre-WTO period (1985-86 ) and Post-WTO period (1994-95).The finding indicated that area under ginger was increased to 0.73 per cent per annum and production increased to 2.07 per cent during pre-WTO (1985-86 to 1994-95) period. Whereas during the post-WTO period the growth rate for area and production was increased at the rate of 1.36 per cent and 1.86 per cent respectively.

Jose and Jayasekhar (2008) studied the growth trends in area, production and productivity of arecanut in India during the period from 1971 to 2004 and revealed that the area and the production of arecanut in India increased tremendously at the rate of 2.2 per cent and 3.2 per cent respectively. The rate of increase in both area and production is mainly due to favourable price prevailed during the period.

Sharad and Shekhar (2008) studied the status of silk production in India during the period from 1980-81 to 2004-05. It revealed that the pattern of growth in area under mulberry cultivation has increased with significant rate of 0.25 per cent. The production and productivity of raw silk showed high significant growth of 5.06 per cent and 4.80 per cent respectively. The production of raw silk has increased mainly due to high yielding mulberry varieties and silk worm breed.

Geetalakshmi (2011) conducted a study on Mangoes : New varieties to step exports. The study revealed that the major destination of Indian mangoes are Bangladesh (33.20 per cent), Saudi Arabia (22.61 per cent) and UAE (19.61 per cent) in terms of quantity. The actual export of mangoes to Bangladesh recorded an increase in share from 6 per cent to 33 per cent of total exports during the period 1980-82 to 2005-07. Exports to Japan have shown very high compounded annual growth rate both in terms of quantity (33.87 per cent) and quality (33.25 per cent). India’s fresh mango exports could be improved by focusing on producing varieties that are demanded by foreign consumers. It is important for mango producing countries to concentrate on products that offer them comparative advantages—in most cases labour-intensive products.

Biswas and Kumar (2011) reported in the article Revolution of Mango production that during the year 2008-09 India had an area of 2.1 million hectare under mango with a production of 12.7 million tonnes and productivity of 5.5 tonnes/ha. India ranked first in mango production in the world. But due to certain limitations, mango productivity is declining in the country. In the traditional low density cultivation, per ha plant population in mango orchard ranges from 75 –100. In such situation, mango trees become very big, which make it difficult to perform the needed cultural operations, like training, pruning, disease pests control etc. As a result, irregular bearing of fruits becomes the rule rather than an exception. Low yield or no yield is also common due to alternate bearing. Poor nutrient and water management are also very important factors to improve the needed productivity. High-tech horticulture known as high density planting (HDP), has come into vogue, which is capable of removing the limitations of mango productivity in India.

2.2 Nominal Protection Coefficient (NPC)

Rao (1995) analyzed the export competitiveness of Indian onions in major markets using constant market share model over a period, 1979-82 to 1989-92. The importing countries for analysis were Malaysia, Singapore, Srilanka, UAE and the rest of the importing countries grouped as other onion exports to Malaysia were fairly competitive where in 26 per cent of total change in exports was due to competitiveness of our exports in that market. The UAE was the only country where India’s onions were not at all competitive. Regarding onion exports to the world as a whole, only one per cent of the total change in exports was found to be due to competitive effect.

Reddy et al. (1998) analyzed export competitiveness of groundnut with particular reference to Karnataka using normal protection coefficient techniques under importable and exportable hypothesis. Results of the study showed that groundnut had been receiving significant protection by then existing policies as indicated by coefficients greater than unity.Thus groundnut is neither an efficient import substitute nor an exportable commodity, which showed be occur for concern as it is widely grown in dry land areas, where alternative profitable crops are few.

Ravi and Reddy (1998) examined the export competitiveness of selected agricultural commodities with particular reference to Karnataka using normal protection coefficient techniques. Among the six commodities studied, Karnataka lacked comparative advantages in most of the crops except cotton. The exports potential of jawar, maize and groundnut and sunflower were significantly low. Even though, Karnataka was the leading coffee exporting state, in recent times, domestic market found to be more favourable compared to the export market unlike cereals and oilseeds, Karnataka had an absolute advantage in case of cotton export.

Ashalatha (2000) examined the global competitiveness of Indian cashew for the year 1990-99 by estimating the NPC under both importable and exportable hypothesis. She found that the NPC computed for cashew kernel were low and below unity in all the years both under importable and exportable and hypothesis. The average NPC under importable and exportable hypothesis were 0.83 and 0.91 respectively. From this she concluded that Indian cashew export is globally competitive.

Mahesh (2000) examined the global competitiveness of Indian tea by estimating the nominal protection coefficient (NPC) and domestic resource cost (DRC) under both importable and exportable hypothesis. He found that NPC and DRC were 0.98 and 0.93 respectively under exportable hypothesis and they were 0.71 and 0.66 respectively under importable hypothesis. From this he concluded that Indian tea is globally competitive.

Desai (2001) examined the export potentialities of mango from India by using nominal protection coefficients for the period 1990-1998, which is the ratio of domestic price to the border price. The findings of the study indicated that on an average, the nominal protection coefficients value in fresh mango (0.89), and mango slices (0.45) were lower than one indicating their competitiveness in international market.

Raghavendra (2004) assessed the competitiveness of Karnataka’s important crops in pre and post liberalization. A policy analysis matrix approach found that the NPC value for important crops of Karnataka was less than one in post liberalization period except groundnut EPC and DRC values also less than one in post liberalization period. From this he concluded that all important crops except groundnut are competitive in Karnataka.

Sadavatti (2007) analyzed export competitiveness of Basmati rice with the help of Nominal Protection Coefficient (NPC) for the period 1980-81 to 1989-99. Although Basmati rice trend is positive, it is not smooth and steady. Around 60 to 70 per cent of the entire basmati rice exports are going to Saudi Arabia, Kuwait and UAE. The study reveals that there is ample scope for USA, one of the important importers of Basmati rice. The estimated NPC of the basmati rice with respect to USA with an average of 0.82 reveals that basmati rice export is competitive and enjoys advantages in exports. Basmati rice is a good exportable product. There is ample scope to export basmati rice to USA. But there is stiff competition from Pakistan.

Yeladhalli and Vilas (2009) studied on direction of trade and export competitiveness of onion. The study showed that NPC for onion was 0.947 during 2000-2001 under exportable hypothesis while under the importable hypothesis it was 0.311. This implied that domestic prices received by farmers were below the international prices in India. The DRC ratio worked out to be less than unity (0.23) indicating high export competitiveness of onion. The policy implications in the form of subsidies, simplified export licensing procedures may be directed in view of potential exports for onion from India.

Kumar (2010) assessed the export competitiveness of different lives and analyzed the factors affecting the growth of livestock in India after liberalization. The liberalization policy initiated in 1991 appeared to have improved the performance of livestock exports. The study revealed that India was competitive in export of meat products, except poultry. The export of buffalo meat has been increasing consistently poor domestic demand has further fuelled its export of mutton did not seem to have much prospects in the short-run, as even the domestic demand was not met by domestic production.

Siddaya and Atteri (2010) examined the export competitiveness under the cost compliance horticultural commodities. The NPC, Effective Protection Coefficient (EPC), DRC and Effective Subsidy Co-efficient (ESC) were computed under cost compliance as well as without cost compliance. Except for grapes, NPC, ESC and ORCs were found to be less than unity for fresh and processed fruits and vegetables, implying that the Indian horticultural sector has a comparative advantage in the selected fruits and vegetables. The EPC was more than unity for various fresh and processed fruits and vegetables because the relation between domestic and international input and output prices were not uniform.


Ananthi (2000) analysed the direction of trade of Basmati and non-basmati rice in India using Markov chain analysis. The study period was 1987 -88 to 1998-99. The results indicated that in the countries such as Saudi Arabia, UAE and UK showed the probability of getting more share of import at the cost of countries such as Bahrain, Kuwait and USA. In the case of non-basmati rice all the major countries which import Indian rice will lose their share and the probability of the minor countries importing at present may be dominant over the other countries.

Balappa Shivaraya (2000) studied the changes in trade directions of export of selected vegetables using Markov chain analysis. The results revealed that UAE and Malaysia were the loyal markets for Indian onion. In case of potato, Sri Lanka and Nepal were found to be the most loyal markets, whereas Bangladesh and Nepal were the most stable importers of Indian fresh tomatoes.

Hugar (2002) studied the changes in the share of exports of onion from India to different countries using the Markov model with first order finite Markov chain property to analyze the export shares by countries and forecast the export of onion, which follows stochastic process. The share of export of onion to a particular country at time t was considered as a random variable. Minimum absolute deviations estimation procedure was used to estimate the transition probabilities Pij i.e. probability of share of export to j

lh country

from ilh country. Using this one step transition probability, shares of major importers of onion

from India were compared with observed export shares. One step and five step transition probabilities were also found to predict the export shares of countries for one year and five years after the base year. His results indicated that Malaysia and UAE were loyal markets of onion export from India.

Rajesh et al. (2002) studied the direction of trade of major spices from India during pre liberalization period (1981-82 to 1990-91) and post liberalization period (1991-92 to 2000-01). The results showed that USA had a high retention power (i.e. 0.8083) in pre liberalization period for pepper compared to post liberalization period (0.3188). Japan and Saudi Arabia had high transition probability values of 0.5500 and 0.4921 respectively in retaining cardamom export from India during pre liberalization period. Pakistan, Bangladesh and Saudi Arabia had a retention power in ginger trade during post liberalization period with transition probability values of 0.6387, 0.5032 and 0.548'8, respectively.

Nisha (2004) studied the export potential and direction of exports of Indian groundnut. The results of Markov chain indicated that exports are likely to be concentrated in Indonesia and Malaysia. She also studied the size, composition and direction of exports in addition to sanitary and phytosanitary measures stipulated by different countries.

Mahadevaiah et al. (2005) studied the changing pattern of raw cotton exports from India during pre reforms period (1981-82 to 1990-91) and post reforms period (1991-92 to 1998~99) using Markov Chain model. The transition probability matrix estimated for both the periods showed that China was the only stable importer of Indian Cotton with retention probability values of 0.0832 and 0.3155 during pre and post reforms periods, respectively .The other traditional importing countries such as Bangladesh, Germany, Indonesia, UK, Japan and Korea.

Bhattacharyya and Banerjee (2006) examined the direction of trade of Indian imports and exports Using the gravity model considering panel data of 1950 - 2000. They observed that the number of export destinations more than doubled between 1950 and 2000. The top 5 countries continued to account for around fifty per cent of

exports throughout the period. By the end of the century about 86 per cent of countries were smalltime export partners absorbing less than 1 per cent of total exports. USA was a very important trading partner of India during that period both in exports and imports while the importance of UK, which was very important in the first two decades since 1950, waned over the years. USSR Was important during the I970s and the 1980s

Sadavati (2006) studied the export behaviour of basmati rice using annual time series data covering the period from 1980-81 to 2000-01. The direction of trade and the changes in exports were analysed using Markov Chain Model. She reported that the five major countries importing Indian basmati rice and that the exports would be concentrated in Saudi Arabia and Kuwait in future. Saudi Arabia was one of the stable importers as it reflected high probability of retention at 0.9044.

Pramod et al. (2007) analyzed the changing direction of Indian mango exports using Markov chain. It revealed that the USA, UAE and Bangladesh were stable markets for Indian mango while, UK and Saudi Arabia were unstable markets. The increasing share of other countries showed the need to explore and exploit the market potential of other countries.

Yeladhalli and Vilas (2009) studied on Direction of trade and export competitiveness of onion. Markov chain analysis has been employed to ascertain the direction of trade through transitional probability matrix. The study revealed that Malaysia has shown the increasing trend while UAE has shown a declining trend. UAE and Sri Lanka have been very loyal markets for Indian onion market.

Srivastava et al. (2010) examined the dynamics of change in pulses production vis-a.-vis other crops using the stationary form of the first order Markov Chain model. They found that pulses could retain only 24.38 per cent of their area and 70.73 per cent of their area was substituted by oilseeds while 4.89 per cent was lost to other crops.


Ghosh (2000) investigated intra state spatial integration of rice markets in India. This study used. ML method of co-integration. Intra state regional integration of rice markets was evaluated by testing the long seen linear relationship between the prices of the state specific variety of rice quoted in spatially separated locations in four selected states. The cointegration results for Uttar Pradesh indicated that the regional markets are integrated to such an extent that the low of one price (LOP) holds for III/IV ARWA variety of the LOP for the common variety of rice marketed in Bihar, Orissa and West Belgal, even through the regional rice markets were found to be integrated. The results pertaining to inter-state regional integration of rice markets represented by four market centres chosen from the four selected states revealed that even though the markets are integrated the LOP does not hold.

In the research papers of Yogisha et. al. (2007), market integration for major agricultural commodities was studied by employing distributed lag model, which was superior over correlation analysis. Distributed lag model of potato prices revealed that, Chickballpur market took less than a day to transfer the prices signals from Bangalore followed by Srinivaspur (3.48 days), Chintamani (13.03 days) and Kolar (16.18 days). In case of onion, Chickballpur took 1.38 days followed by Chintamani (4.38 days), Kolar (7.45 days) and Srinivaspur (7.93 days) to reflect Bangalore onion prices. Kolar took 8.34 days to reflect Bangalore ragi prices. In case of groundnut prices, Kolar took less than 6 days and it was highest (16.01 days) for Srinivaspur market.

Chebbi and Lachaal (2007) in their study on agriculture sector and economic growth in Tunisia using time series co-integration techniques indicated that in the long-run all econometric sectors tend to move together (co-integration). But, in the short-run, the agricultural sector seems to have a limited role as a driving force for the growth of the other sectors of the economy. In addition, growth of the agricultural output may not be conducive directly to non-agricultural economic sector in the short-run.

Pushpa (2007) studied the Indain export performance of Basmati rice revealed that, although the trend was positive, it was not smooth and steady. Therefore, there was a need to diversify the geographical concentration. In this context, it was emerged from the study that there was ample scope for export to USA, which is one of the important importer of Indian basmati rice. The estimated NPC with respect to USA indicated that basmati rice export competitive and enjoys advantages in exports. The study also revealed that domestic and export market (USA) prices for basmati rice were well integrated.

Henrick et al. (2008) studied the existence of spatial integration between and within paddy markets in the north and south of Vietnam. The empirical model used estimates of transfer costs to generalize Ravallion’s model of spatial market integration to allow for threshold effects. A sequential testing strategy was used for market segmentation, the number of threshold, long-run integration, informational efficiency and law of one price within an error-correction framework. Whenever price spreads exceed their threshold, at least 60 per cent of price changes were transmitted between regional markets within a month. The results suggested that national level policies cannot be relied upon to stabilize or support paddy prices in Vietnam. Instead policies need to be designed with the specific production, consumption and marketing characteristics of northern and southern Vietnam in mind.

Saran and Gangwar (2008) analysed the spatial cointegration amongst major wholesale egg markets in India through measurement of oneness in the egg markets for which, the Engle-Granger cointegration test procedure was applied to egg price series for major wholesale egg markets in the country. The study indicated that, the major markets studied were cointegrated apparently due to performance of market intelligence functions by National Egg Coordination Committee (NECC), which helped in transmitting price signals across length and breadth of the country through print media on day-to-day basis. The high degree of cointegration amongst various markets indicated that the markets were competitive and efficient at the wholesale levels.

Vasishi et al. (2008) studied the price behaviour in fruits and vegetable markets using Co-integration and Error Correction Analysis techniques. The empirical results on the price behaviour provided evidence of high volatility in the prices of fruits and vegetables in major markets. There was a presence of long-run relationship across some of the state level markets for less perishable commodities like apple. The findings clearly indicated that the horticulture sector in India can thrive for greater benefit of both producers and consumers only if better infrastructural facilities like storage, modern marketing infrastructure, as well as timely availability of market information and better market intelligence are developed fast across all states.

Yadav (2008) in his study on “Co-integration, Causality, Money and Income in India” using annual data over 1950-51 to 2006-07 established that money supply and national income (both real and nominal) were found to be co-integrated, which suggested the existence of long-run relationship.

Anand et al (2009) in his study on co-integration causality, money and income in india using annual data over aperiod of 1950-51 to 2006-07 established that money supply and national income (both real aand nominal) were found to be co-integrated which suggested the existence of long-run relationship.

Manasa (2010) analysed the Spatial movement of prices and arrivals of Pigeonpea in major five markets in Karnataka by using Co-integration technique. Where results clearly showed, prices in Bidar market were influenced by the price in Gulbarga market to a very high degree. Bidar market price influenced prices in Raichur and Bellary markets almost to the same degree. And Low degree of association was found between Bellary and Sedam markets. The zero order correlation between average monthly prices of pigeonpea in all the selected markets revealed a strong integration among all the markets.

Nikhil (2010) in his study on “Spatial market focus” in Burundi used co-integration analysis to test the degree on integration among the cassava markets. In the results they showed that markets are seemingly integrated for cassava, Bujumbura is an exception with a cassava price that appear quite independent from prices in the rest of the country, between Ngozi and Muyinga markets they found high level of integration. This corroborates anecdotal observations that cassava is moved from Rwanda to Burundi through Ngazi before being distributed elsewhere.

2.5 Problems of Export

Srivastava et al. (1996) reported that, although India was a major producer of a number of delicious varieties of mangoes, it exported only one or two varieties, mainly Alphanso from Maharastra on a large scale. They observed that the incidence of spongy tissue in Alphanso and fruit fly and stone weevil in Amrapali and Dashehari varieties acted as constraints in the export of fresh mangoes. Lack of uniform size and colour among mango fruits also impeded their export. Indian mangoes could not be exported to USA and Japan, as the required vapor treatment of the fruits and air freight were costly.

Gopal Rao (1998) studied the export of horticultural crops from Andra Pradesh and observed that, mangoes and onions were exported in large quantities to foreign countries. The major constraint in the way of increasing export of fruits and vegetables to the International markets were poor quality, premature harvesting of the fruits leading to reduced shelf life and low sugar content, lack of adequate knowledge of the quality standards in International market by both farmers as well as the merchants, poor storage and transport facilities, carelessness in handlings of fruits and vegetables at various stages of picking, packing and transportation. Thus, the author opinioned that the promotion of export of fruits and vegetables in the State needs dissemination of knowledge on International standards of quality, export policies, duties, subsidies and taxes, freight, etc., to all stake-holders form growers to exporters as well as strict supervision and control on quality for export.

Praduman Kumar and Subarthi (1998) stated that, despite nurturing a wide variety of fruits, which enjoyed comparative advantages in their production and export, India had not been able to do well on the horticulture export front. The main reasons which hampered the field from growing according to the author were high cost of raw materials, in adequate and expensive refrigeration facilities during storage, transportation and distribution, poor availability and high cost of quality packaging and related machinery and inefficient existing technologies and high residual effects. To strengthen these activities, the study suggested to diversify and expand the export basket giving due emphasis to the development of domestic market simultaneously and infrastructure facilities.

Hymajyoti et. al (2003) conducted a study on export performance of onion and potato from India. The study was conducted with the objective of assessing the constraints associated with exports. The study revealed that most of the exporters expressed phyto-sanitory problem, lack of demand from importing countries, lack of export promotion measures and lack of infrastructure facility as a major obstacles which impede export of vegetables.

Velavan (2004) observed the major production constraints were poor yield of cashew nuts, because of the age old plantation, necessity of financial support. Lack of irrigation facilities and farmers were not able to adopt proper pest control measures due to the high cost of pesticides. Further, he reported that cashew nut in India face severe competition from other surrogate nuts like almonds, pistachios, hazelnuts, Brazil nuts and macadamia etc. In addition to this, India was facing severe competition from the exporting countries like Brazil and Vietnam in exports of cashew nuts, because of devaluation of their currencies, nonavailability of value added kernels in consumer packets for exports, non-availability of the packing materials in the international standards, inconsistency and the non-uniformity in the quality of kernels for individual brands and the markets. Value added products from the cashew were not available in the exports from India.

Khunt et al (2008) studied on Export potential and Barrier in export of onion from Gujarat. The study showed that the non-tariff barrier faced by exporters were irregular and inadequate onion supply of required quality, infrastructure bottlenecks like debts, lack of quick and cheap transport facility, lack of quality testing labs and phytosanitory problems, lack of export promotion as well as tariff barriers like debt subsidy in transportation and protection tariff imposed by EU against export of India.

Pant et al., (2008) conducted a study on Learning Networks Matter: Challenges to developing learning based competence in Mango production and Post-Harvest in Andhra Pradesh, India. The study explores different aspects of innovation systems ideas in the analysis of mango production and export by smallscale farmers in the South Indian state of Andhra Pradesh. The paper shows how despite favourable agro-ecological conditions and

being the largest international mango producer, India still struggles to build momentum in rapidly emerging export markets. An analysis of the sector’s recent history combined with an empirical account of inter-sectoral and intra-sectoral linkage patterns among stakeholder groups appears to provide the basis for remedial policy suggestions. Most of these relate to aspects of integrated technology development and innovation management.

Suresh kumar and singh (2008) studied on WTO and export competitiveness of apple in Himachal Pradesh. The study revealed that the Himachal Pradesh apple was not competitive with China consequently import from China was increasing rapidly. Although the apple of Himachal Pradesh was competitive with USA apple during pre and post WTO but USA apple export was increasing despite competitive advantage to Himachal Pradesh.

3. METHODOLOGY The source and nature of data for the study and the analytical tools employed in the

study were presented in this chapter.

3.1 Description of the study area

3.2 Data Collection

3.3 Analytical tools and techniques employed

3.1. Description of the study area Peninsular India has a land mass of 32,00483 sq km with 15,200 km land frontier.

India lies to the north of equator between 8°5’ to 37°6’ north latitude and 68.7 to 97.25 east longitudes. India has a varied temperature ranging between 15.7°C and 35.5°C. It receives rainfall ranging from 20 to 80 inches. India gets rainfall from both southwest and northeast monsoon. India’s huge agricultural potential is embodied in its size and in its abundance and diverse nature resources, unlike most part of the World which have a cold and hostile winter and a relatively a small proportion of arable land, India is blessed with bounteous nature across vast fertile river plains, Indian cereal and agriculture crops provide another demonstration of her abundance, diversity and opportunity. The area under consideration for analyzing of mango export, whole India was taken into consideration at aggregate level so as to facilitate data compilation and prices in the international market.

3.2 Data Collection

3.2.1 Nature and source of data

The study was based on both primary and secondary data. The secondary data on area, production, productivity was compiled from National Horticulture Board (NHB) and www.indiastats.com for a period of 20 years (1990-91 to 2010-11). Price and volume of trade of export data for a period of twenty years from 1991 to 2010 was compiled from Agricultural and Processed Food Products Export Development Authority (APEDA). For studying the problems involved in export of mangoes, primary data was collected. A sample of thirty mango exporters was selected using simple random technique. Twenty six farmers were from Nashik as it has maximum number of exporters, two from Delhi, one from Kolkata and one from Mumbai. Thus total sample constitutes thirty exporters. The information was collected from the respondents through mailed questionnaire method.

3.3 Analytical tools and techniques employed To fulfil the specific objective of the study based on the nature and extent of

availability of data, the following analytical tools and techniques will be adopted.

3.3.1. Growth Rate and Trend Analysis

3.3.2. Markov Chain Analysis

3.3.3. Nominal Protection Coefficient

3.3.4. Co-integration Analysis

3.3.1 Growth Rate and Trend Analysis

Growth rate on area, production, yield and exports of Mango was computed for a period of 20 years from 1990-91 to 2010-11.

The linear, log-linear, exponential and power functions are some of the important functional forms employed to study the growth rates. Different functional forms were tried in the past for working out of growth rates in area, yield and production. Some of the important forms tried were the linear growth model (Y = a+ bt), exponential function (Y = ab

t) and

quadratic function (Y = a+bt+ct2). However, it was found that the exponential form of the

function Yt = abt is the better and most frequently used one. In the present study, compound

growth rates for area, production and productivity of Mango of Andhra Pradesh, Uttar Pradesh , Maharashtra, Gujarat, Tamil Nadu, West Bengal, Bihar, Orissa, Karnataka, Kerala, Others and country as a whole were estimated by using the exponential growth function (Angles, 2001) of the form,

Yt = a bt Ut ……………………. (1)

Where,

Yt = Dependent variable for which growth rate was estimated (area, production, yield, quantity and unit value of Mango exported in year’t’).

a = Intercept

b = Regression coefficient

t = Year which takes values from 1, 2 … n.

Ut = Disturbance term in year‘t’.

The equation (1) was transformed into log-linear and written as

log Yt = log a + t log b + log Ut ……………… (2)

Equation (2) was estimated by using Ordinary Least Square (OLS) technique.

The per cent compound growth rate (g) was derived using the relationship (3)

g = (antilog b -1) x 100 ……………. (3)

Where,

g = Estimated compound growth rate per annum in percentage.

b = Antilog of log b

Similarly, the growth rates of export for quantity and value of mango to United Arab Emirates, Bangladesh, United Kingdom, Saudi Arabia, Kuwait, Bahrain, Nepal, Singapore, Qatar and Malaysia including total exports was estimated using the above functional equation(1). The standard error of the growth rate was estimated and tested for its significance with student’s‘t’ statistic.

For estimating the long-run trend of area, production, productivity, export and behaviour of prices of mango in different states, the method of ordinary least squares estimate was employed. This method of ascertaining the trend in a series of data involves estimating the coefficient of intercept (a) and slope (b) in the linear functional form. The equation adopted for this purpose was specified as follows,

Yt = a + bX + e

Yt = Trend values at time t

X = Period in years

a = intercept parameter

b = slope parameter

e = Error

Trends of prices and arrivals for the selected markets were computed and compared. The goodness of fit of trend line to the data was tested by computing the coefficient of multiple determinations which is denoted by R

2.

3.3.2. Markov Chain analyses

The major Indian Mango importing countries considered were Bangladesh, United Arab Emirates, Nepal, United Kingdom, Saudi Arabia and others.

The trade directions of Indian mango exports were analyzed using the first order Markov chain approach. Central to Markov chain analysis is the estimation of the transitional probability matrix ‘P’ whose elements, Pij indicate the probability of exports switching from country ‘i’ to country ’j’ over time. The diagonal element Pij where i=j, measures the probability of a country retaining its market share or in other words, the loyalty of an importing country to a particular country’s exports.

Annual export data for period 1995-96 to 2010-11 was used to analyze the direction of trade and changing pattern of Indian mango export. In this context, five major importing countries of mango i.e. Bangladesh, United Arab Emirates, Nepal, United Kingdom and Saudi Arabia along with others were considered. The average exports to a particular country was considered to be a random variable which depends only on the past exports to that country, which can be denoted algebraically as

Ejt = [ ]jtij

n

i

tePEi +∑

=

−

1

1

Where,

Ejt = exports from India to the jth country in the year t

Eit-1 = exports of ith

country during the year t-1

Pi j = the probability that exports will shift from ith country to j

th country

ejt = the error term which is statistically independent of Eit-1

n = the number of importing countries

The transitional probabilities Pij, which can be arranged in a (c x n) matrix, have the following properties.

1

1

=∑=

n

i

IjP And 0 ≤ P I j ≤ 1

Thus, the expected export share of each country during period‘t’ is obtained by multiplying the exports to these countries in the previous period (t-1) with the transitional probability matrix. The probability matrix was estimated for the period 1994-95 to 2010-11.

Thus transitional probability matrix (T) is estimated using linear programming (LP) framework by a method referred to as minimization of Mean Absolute Deviation (MAD).

Min, OP* + I e

Subject to

X P* + V = Y

GP* = 1

P* ≥ 0

Where

P* is a vector of the probabilities P I j

O is the vector of zeros

I is an appropriately dimensional vectors of areas

e is the vector of absolute errors

Y is the proportion of exports to each country.

X is a block diagonal matrix of lagged values of Y

V is the vector of errors

G is a grouping matrix to add the row elements of P arranged in P* to unity.

Using the estimated transitional probabilities, the exports of mango to various destinations was predicted by multiplying the same with the respective shares of base year. The export shares of Indian mango to different countries was predicted for the years 2012 to 2015 by using 2 step, 3 step, 4 step and 5 step transitional probabilities.

3.3.4. Nominal Protection Coefficient (NPC)

Nominal Protection Coefficient is a direct measure of competitiveness of a country towards a commodity in the context of free trade. The nominal protection coefficient (NPC) is defined as the ratio of the domestic price to the world reference price of the commodity under consideration.

Symbolically,

NPC = Pd/ Pr

Where,

NPC = Nominal Protection Coefficient

Pd = Domestic Price of the Commodity in question

Pr = World Reference Price of the Commodity in question i.e., what the farmer would have received in case of free trade.

A decision criterion is if NPC is less than one, then the commodity is competitive (under importable hypothesis it is considered a good import substitute and under exportable hypothesis, it is worth exporting). If NPC is greater than one, the commodity is not competitive (not a good import substitute or not worth exporting). The domestic price is normally the wholesale market price of commodity in the selected market. The reference price is the international price adjusted for transfer cost, marketing and trading margins including the processing charges necessary to make the commodity equivalent to the internationally traded commodity.

These coefficients are estimated under two scenario viz., import scenario and export scenario.

Under importable scenario, the competition is deemed to take place at the domestic port and therefore international and domestic transportation cost accord a natural protection to the domestic commodity.

Exportable scenario, the competition is assumed to take place at foreign port and therefore domestic commodity has to be extra efficient to the tune of international transportation costs at least. These two hypotheses therefore yield different estimates of protection.

The interpretation of the coefficient is as follows:

Under importable hypothesis,

NPC < 1 an efficient import substitute

Under exportable hypothesis,

NPC < 1 an efficient export substitute

In the present study Nominal Protection Coefficient (NPC) was estimated under the exportable hypothesis for the year 2010-11. Nominal Protection Coefficient and International Reference Prices in the case of exportable hypothesis are calculated as shown in the Table 3.1.

3.3.5 Market integration technique

Co-integration is an analytic technique for testing for common trends in multivariate time series and modelling long-run and short-run dynamics. Two or more predictive variables in a time-series model are co-integrated when they share a common stochastic drift. Variables are considered co-integrated if a linear combination of them produces a stationary time series.

This analysis was carried out to ascertain the response of price change in one market that is transmitted to other markets. The co-integration analysis was carried out for this purpose to know the inter market price relationship between the domestic market and international markets. Table 3.1: Estimation of Nominal Protection Coefficient (NPC) (Exportable Hypothesis)

Sl. No.

Particulars Place Unit Value

1. Wholesale Price Domestic Market `/ Qtls.

2. Marketing Margin (5%) `/ Qtls.

3. Port Clearing & Handling Charges `/ Qtls.

4. Fob Price (1+2+3+4) Domestic Market `./ Qtls.

5. Freight Charge International Market `/ Qtls.

6. Insurance @ 2% of Price `/ Qtls.

7. Landed Cost ( 5+6+7) International market `/ Qtls

8. Exchange Rate 1$ = `

9. CIF Price (Row 8 / Row 9) US $ / Qtl

10. Reference Price International market US $ / Qtl

11. NPC (Row 10/Row 11)

Price relations are widely used to indicate the overall market performances, the usual definition is that integrated markets are those whose prices are determined interdependently i.e the changes in one market will be fully transmitted to the other markets.

In the present study co-integration method has been adapted with the use of Eviews 7 software to study the market integration for modal prices of the selected markets. To carry out the analysis data has been made stationary mean that the process of generating the data is in equilibrium around a constant value and that the variance around the mean remains constant over a time. If mean changes over time and variance is not reasonably constant, then the series is non-stationary. To decide the stationarity or non stationarity of the data, for each the market ADF test (Augmented Dickey –Fuller Unit root test) has been conducted.

If calculated probability value of respective market in ADF test is less than 0.09 then that market’s price data is already stationary. But if the ADF values are greater than 0.09, data is subjected to 1

st order differencing or 2

nd order differencing until it becomes stationery.

Finally Vector Autoregression Estimates are calculated for all the markets. The VER estimates will provide the short term co-integration with in the markets and between the markets which will be expressed in percentage. The T-statistics are calculated to know the significance of the markets within them and also between markets, which will be decided on the basis of T-statistics values. If the T-statistics values are greater than 1.7 then the integration values are considered as significant otherwise they are Non-significant and will not be considered for drawing the inferences.

4. RESULTSKeeping in view of the Objectives, the data pertinent to the present study was

collected and elicited from various sources and analysed using appropriate techniques. Theresults of the present study are presented as below keeping in view the objectives of thestudy.

4.1 Trend in area, production, productivity and export of mangoes

4.2 Behaviour of Indian mango export prices

4.3 Export competitiveness of Indian mangoes




4.1 Trend in area, production, productivity and export of mangoesThe time series data of area, production, productivity and export was subjected to

trend analysis fitting linear trend equation. The outcomes of analysis are presented herebelow.

4.1.1 Trend in area of mangoes across the statesThe linear trend was computed in order to ascertain the long-run movement in area of

mango in different states over the years and the results are presented in the Table 4.1. Fromthe table, it could be seen that, in the long-run, there is an increase in the area undermangoes in all the states over the years except Bihar and Kerala. In Maharashtra, the annualincrease in area over the years was found to be maximum (28040 ha per year) during thestudy period. The trend analysis indicates that 86 per cent of change in area was due to theinfluence of independent variable, time, as indicated by R2 value of 0.86. The area undermango in Andhra Pradesh, Karnataka, Gujarat, Tamil Nadu, West Bengal and Orissa is seento increase in long run by 16954, 650.3, 3105, 5041, 4639, 1912, and 6549, ha per yearrespectively with R2 values of 0.95, 0.785, 0.952, 0.935, 0.896 and 0.943 respectively.

Area under Uttar Pradesh has also increased over the years but low R2 value of0.13 indicates that time i.e. the independent variable time under study is not explaining thevariations efficiently. Area under the crop under Bihar and Kerala is decreasing by 466.7 and167 ha per year respectively in long run. But the insignificant value of coefficient ofdetermination for both the states was 0.24 and 0.02 respectively over the study period.

Overall, at all India level area under mango cultivation is increasing over the period oftime. The increase in area was at the rate of 71735 ha and it was explained efficiently by ahigh R2 value of 0.96.

4.1.2 Trend in mango production across the statesIn order to ascertain the long-run movements of mangoes production in the mango

growing states, the data relating to production of mango was subjected to linear trendanalysis. Table 4.2 reveals that, there was an increasing trend in the production of mango inIndia over the study period and it was found to be sufficiently explained by independentvariable time (R2 value of .79)

Among the individual states, the annual increase in production of mangoes was foundto be highest in Uttar Pradesh state (91197 MT) whereas lowest was noticed in the state ofWest Bengal (6720 MT) and other states (2370 MT). However in Bihar state, the annualincrease in production was negative (-29784 MT). The annual variations were explained tothe extent of 52 per cent, 9 per cent, 1 per cent and 29 per cent respectively by the timevariable. Rest all the states showed increasing trend in production of mango leading to therising trend in mango production in country as a whole.

Table 4.1: Trend in area of mango cultivation across different states

(ha)

States Intercept Slope R 2

Andhra Pradesh 17195 16954.00 0.95

Uttar Pradesh 25109 650.30 0.13

Karnataka 86403 3105.00 0.79

Bihar 15079 -466.70 0.24

Maharashtra -52910 28040.00 0.86

Gujarat 19841 5041.00 0.95

Tamil Nadu 57244 4639.00 0.94

West Bengal 46480 1912.00 0.90

Orissa 41480 6549.00 0.94

Kerala 80575 -167.4.00 0.02

Others 10506 3244.00 0.31

India 92208 71735.00 0.96

Figure 1. Trend in area of mangoes across the states







Figure 1. (Contd…) Trend in area of mangoes across the states

Table 4.2: Trend in mango production across the states

(MT)


Andhra Pradesh 3000000 52530 0.27

Uttar Pradesh 2000000 91197 0.52

Karnataka 74481 37974 0.69

Bihar 2000000 -29784 0.29

Maharashtra 21601 22574 0.52

Gujarat 20833 25582 0.49

Tamil Nadu 36575 18305 0.40

West Bengal 35457 6720 0.09

Orissa 30499 8931 0.32

Kerala 20794 9457 0.58

Others 90605 2370 0.01

India 8000000 28572 0.79

Figure 2. Trend in production of mangoes in India



Figures 2. Trend in production of mangoes in India




Figure 2. (Contd….) Trend in production of mangoes in India

4.1.3 Trend in mango productivity across the statesLinear trend was fitted to compute the long run movement of productivity of mangoes

across the states, over the years. The results of trend analysis in mango productivity indifferent states and India as a whole are presented in table 4.3.

Plant population of mangoes in orchards under square system and hexagonal systemof planting is 100 and 115 trees per hectare respectively. Productivity of mangoes showed anincreasing trend only in Karnataka, Uttar Pradesh and Kerala with the productivity rising at therate of 0.67, 0.32 and 0.14 MT per ha every year respectively. In rest all the statesproductivity was seen to be deceasing during the period of study. It is evident from the tablethat time is not sufficiently explaining the variations in productivity in case of Bihar,Maharashtra, Gujarat, Tamil Nadu, West Bengal and other states. However in Orissa,Andhra Pradesh and Maharashtra the influence of time factor on productivity of mangoes wasremarkable with the R2 value of 0.81, 066 and 0.64 respectively. Due to decreasing annualproductivity in most of the states, productivity of mango in India as a whole also has comedown during the study period at the rate of 0.135 MT per ha per year. These variations inproductivity of mangoes were explained by time factor up to 68 per cent.

4.1.4 Trend in mango exports to different countriesLinear trend was fitted in order to ascertain the long-run movement of mangoes to

different countries by India over the study period and the results are presented in the Table4.4.

Annual increase in exports was found to be maximum in case of Bangladesh rising atthe rate of 1974 MT every year with time explaining this increase is to an extent of 75 per cent(R2 value075). Next to Bangladesh is UAE where the exports are rising at 850.1 MT per yearwith R2 value of 0.62, followed by Nepal with annual increase in export of 310 MT (R2 value of0.55). UK, Malaysia and Singapore are the countries where exports of mangoes are showingincreasing trend over the study period with an annual increment of 80.26 14.83 and 9.40respectively. The corresponding R2 values were 0.50, 0.58 and 0.31 respectively. Countriesshowing negative trend are Saudi Arabia, Kuwait, Qatar and Bahrain declining at the rate230.4, 59.15, 30.21 and 27.24 MT per year with time explaining the variations in quantityexported up to 39, 32, 22 and 16 per cent respectively.

Total exports from India are growing positively in long run with annual increase of2943 MT which is being explained by fairly high R2 value, showing the contribution of time tothis rise in export quantity up to 81 per cent.

4.1.5 Growth Rate of area under mango cultivationThe Compound Annual Growth Rates of area under mango in different states across

the study period are presented in table 4.5. Except Bihar, in all the states, a significant andpositive annual growth rate was observed over the study period. The annual growth in areawas maximum in Maharashtra (14.92%), which was just 49873 ha in 1991-92, rose to 467000ha by 2010-11. The state which has achieved better annual growth in mango area afterMaharashtra was Gujarat with a Compound Annual Growth Rate of 7.51 per cent. It achieved130000 ha of acreage under mangoes by 2010-11 from a mere 32000 in 1991-92. Orissa isthe next best state as far as spread of mangoes is concerned with a Compound AnnualGrowth Rate of 6.45 per cent. It could achieve a spread of 192600 ha in 2010-11 from just53149 ha. Similarly, Andhra Pradesh also achieved a significant 5 annual growth rate alongwith Tamil Nadu, Kerala, West Bengal and Karnataka with the CAGR of 5.05, 4.88, 2.94, 2.83and 2.76 per cent respectively.

Bihar noticed a negative Compound Annual Growth Rate of 0.32 per cent, which hadand acreage of 146232 ha in 1991-92 and subsequently dropped down to 147000 ha in 2010-11. However, R2 value was found to be very weak i.e. 0.24.

4.1.6 Growth Rate of mango production in different statesTable 4.6 shows the growth rate of production of mango in different states

compounded annually for a period of twenty years. It is evident from the table that mangoproduction in India has been increasing at a growth rate of 2.46 per cent annually which isstatistically significant at one per cent level of significance. The production of mango in Indiahas increased from 8751622 MT in the year 1991-91 to 15188000 MT in 2010-11 showingminor fluctuations in between the period of study.

Table 4.3: Trend in mango productivity across the states (MT/ha)


Andhra Pradesh 12.47 -0.31 0.66

Uttar Pradesh 6.24 0.32 0.49

Karnataka 8.82 0.67 0.26

Bihar 11.77 -0.17 0.24

Maharashtra 5.23 -0.23 0.64

Gujarat 8.77 -0.17 0.24

Tamil Nadu 6.27 -0.08 0.10

West Bengal 7.88 -0.08 0.05

Orissa 5.64 -0.16 0.81

Kerala 2.48 0.14 0.52

Others 7.89 -0.08 0.01

India 8.47 -0.14 0.68

Figure 3. Trend in productivity of mangoes in India from 1990-2010







Figure 3. (Contd…) Trend in productivity of mangoes in India from 1990-2010

Table 4.4: Trend in mango exports to major countries

(MT)

Countries Intercept Slope R 2

UAE 5807.00 850.10 0.62

Bangladesh -4773.00 1974.00 0.75

UK 685.70 80.26 0.50

Saudi Arabia 6450.00 -230.40 0.39

Kuwait 1679.00 -59.15 0.32

Bahrain 1286.00 -27.24 0.16

Nepal -1612.00 310.00 0.55

Singapore 158.30 9.40 0.31

Qatar 834.20 -30.21 0.22

Malaysia 96.99 14.83 0.58

Total 12408.00 2943.00 0.81

Figure 4. Trend in export of mangoes from India during 1991-2010







Figure 4. (Contd…) Trend in export of mangoes from India during 1991-2010

Table 4.5: Growth Rate of area under mango in different states (ha)

Years AndhraPradesh

UttarPradesh Karnataka Bihar Maharashtra Gujarat Tamil

NaduWest

Bengal Orissa Kerala Others India

1991-92 207596 259767 80803 146232 49873 32000 55824 55060 53149 75480 93837 10776211992-93 225127 258484 82177 147059 54574 34000 58003 55160 55068 77000 124016 11366681993-94 241901 256808 88810 150527 96693 36200 67818 55300 58076 75462 125967 12173621994-95 255936 266166 96344 149490 64936 39040 72335 55300 64106 75462 128266 12283411995-96 263681 262974 104588 150512 78221 52796 72335 55600 74121 75462 145536 12830301996-97 271400 256200 116500 151800 65500 52900 96700 55700 89100 75400 113700 13449001997-98 276200 258700 123900 153200 65500 56700 104500 55800 97600 75400 117400 13849001998-99 252100 240500 123800 154800 110000 57600 93200 59300 109800 84600 115900 14016001999-00 297500 243200 124100 156000 147200 63400 107900 60000 96200 87300 104100 14869002000-01 306200 249100 134400 139100 147200 61200 111500 62500 103800 90500 117100 15226002001-02 341200 253000 115400 139300 164400 65300 110800 65400 107300 81483.33 213700 15758002002-03 370300 247600 117400 139500 181200 69900 112000 66400 113100 86300 119900 16234002003-04 402200 250500 116300 140000 425800 69900 114900 67800 115100 85400 118800 19067002004-05 391900 247000 117500 140100 432700 89700 118400 69100 120300 85400 149700 19619002005-06 459700 251500 124500 140200 444500 96000 125100 70100 125300 88000 130033.3 20807002006-07 471400 261400 129100 140800 447700 102000 135100 78200 140100 76700 171400 21539002007-08 483500 265900 134600 142200 455800 109600 136600 80900 148200 76700 167400 22014002008-09 497700 271200 141300 144100 457000 115700 148800 86000 164300 76700 206200 23090002009-10 480400 276400 153800 146000 474500 121500 132700 88100 177600 63800 197430 23123002010-11 503400 282000 154900 147000 467000 130000 144600 89500 192600 63800 122200 2297000

CAGR(%) 5.05** 0.24(NS) 2.76** -0.32* 14.93** 7.51** 4.88** 2.83** 6.45** 2.94** 5.44** 4.42**R 2 0.96 0.12 0.77 0.24 0.90 0.97 0.89 0.92 0.95 0.60 0.38 0.98

* Significant at 5 per cent level** Significant at 1 per cent level

Table 4.6: Growth Rate of mango production in different states(MT)

Years AndhraPradesh


NaduWest


1991-92 2491152 1787757 677712 1462320 280983.00 320000.00 336351.00 440480.00 291800.00 241054.00 1045744 87516221992-93 2701524 1876064 698505 1764708 327380.00 340000.00 349758.00 162300.00 300000.00 246000.00 809047 92232561993-94 2902812 1922356 843695 1806324 378893.00 362000.00 422036.00 450580.00 321000.00 266346.00 1123114 101132841994-95 3071232 2387201 915268 1793152 361829.00 390400.00 570170.00 454700.00 352100.00 266346.00 1565871 109933281995-96 3164172 2074150 993586 1806144 380130.00 293401.00 570170.00 472600.00 372000.00 266346.00 1362491 108109571996-97 3256300 2418700 1106700 910400 196500.00 288900.00 413900.00 211700.00 409400.00 266300.00 502400 99812001997-98 3314400 1659500 1176400 1838900 65500.00 366200.00 135900.00 502300.00 417400.00 266300.00 491400 102342001998-99 2269600 1775100 1176500 1858100 196900.00 382600.00 559200.00 339400.00 490600.00 249700.00 484100 97818001999-00 2379600 1915000 1179900 1871900 500500.00 382200.00 701400.00 560000.00 343500.00 253300.00 416200 105035002000-01 2449500 2250300 1291400 1112500 500500.00 364200.00 736500.00 380300.00 363300.00 257800.00 530700 102370002001-02 2445800 1950000 1130600 1253500 559000.00 457600.00 438700.00 585000.00 402400.00 246900.00 797600 100202002002-03 2962100 4031300 1098200 1255600 615900.00 495100.00 756500.00 228800.00 402900.00 305500.00 581300 127335002003-04 3217200 2100100 1111200 1540100 629800.00 495100.00 615400.00 406000.00 405200.00 384200.00 585700 114900002004-05 2857520 2225792 1093041 1549693 398677.50 388881.90 538170.50 417398.20 389072.70 275367.10 1637787 117714002005-06 2820208 2169523 1035193 1558810 385178.00 380470.20 510296.80 400825.60 356476.60 270818.50 2596400 124842002006-07 3865200 2980500 1368800 1306900 646300.00 834300.00 580800.00 549800.00 431400.00 445400.00 724600 137340002007-08 4157900 3365000 1223260 870400 710900.00 930100.00 753600.00 623300.00 251800.00 445400.00 665340 139970002008-09 2522000 3465900 1284420 1329800 712800.00 299817.00 821410.00 251800.00 449710.00 445400.00 1166943 127500002009-10 4058300 3588000 1694000 995900 597000.00 856743.00 636290.00 445400.00 577480.00 373170.00 1204717 150270002010-11 4139300 3733000 1772400 1334900 616000.00 911000.00 712700.00 620200.00 647900.00 373200.00 327400 15188000

CAGR(%) 1.57* 3.54** 3.46* -2.04* 5.76** 4.67** 3.83* 1.81(NS) 2.01** 2.94** 1.12(NS) 2.46**R2 0.23 0.54 0.70 0.25 0.33 0.49 0.30 0.08 0.28 0.60 0.02 0.80

* Significant at 5 per cent level ** Significant at 1 per cent level

Compound Annual Growth Rate was found to be highest for Maharashtra (5.76 %)which produced 616000 MT in 2010-11 in comparison to 280983 MT in 1991-92. There was adrastic reduction in production in 1997-98, which came down to 65500 MT, but againrebounded to 196900 MT in 1998-99. Gujarat secured second number in growth of mangoproduction rising annually by 4.67 per cent and this growth is highly significant at one percent. Production of mango in Gujarat grew from 320000 MT in 1991-92 to 911000 MT in2010-11.

Gujarat was followed by Tamil Nadu, Uttar Pradesh, Karnataka, Kerala and Orissawhere mango production was growing significantly, with growth rates 3.82 per cent, 3.54 percent, 3.46 per cent, 2.94 per cent and 2.01 per cent respectively during the study period.Mango production in Bihar was seen to come down annually by 2.04 per cent which wassignificant at five per cent level of significance. Production in Bihar showed a rise from1462320 MT in 1991-92 to 1871900 in 1999-00 but then came down to 1112500 MT.Although it again started increasing slowly from next year and became 1334900 MT in 2010-11 but showed fluctuations in production in between the study period.

In West Bengal and other states were also mango production was growing positivelyevery year with 1.81 per cent and 1.12 per cent respectively but this growth in production wasnon significant.

4.1.7 Growth Rate of mango productivity in different statesCompound Annual Growth Rate of mango productivity in different states has been

depicted in table 4.7. It is evident from the table that only UP, Kerala and Karnataka arehaving positive growth rates of 3.29, 3.22 and 0.67 per cent respectively where Uttar Pradeshexperienced the maximum increase, rising from 6.88 MT per ha in 1991-92 to 13.24 MT perha in 2010-11.

Andhra Pradesh, Bihar, Maharashtra, Gujarat and Orissa experienced negativegrowth rates of 0.31, 1.73, 7.98, 2.64 and 4.17 per cent respectively which were statisticallysignificant. Drastic reduction in productivity was observed in the state of Maharashtra whosemango productivity declined from 5.63 to 1.32 MT/ha. This reduction in productivity wasexplained by time variable up to 58 per cent. Tamil Nadu, West Bengal and other states alsohad negative compound annual growth rate of productivity but it was statistically insignificant.

Since most of the states had negative growth rate of productivity, overall annualgrowth of India also became -1.88 per cent. Sliding productivity from 8.12 MT per year to 6.60MT per year over the study period was responsible for negative growth rate in the country.

4.1.8 Growth Rate of mango exports to different countriesTable 4.8 contains Compound Annual Growth Rate of mango exports, from India to

major destinations. Spectacular growth in export of mangoes from India was observed in thecase of Nepal where compound annual growth rate was 55.84 per cent. The quantum ofexports to Nepal rose from a very meagre 4.83 MT in 1991-92 to 1991.26 MT in 2010-11.Bangladesh also showed a very decent growth rate of 23.93 per cent annually with exportsrising from 94.84 MT to 23049.69 MT in between 1991-92 to 2010-11. RemarkableDifferences were observed in exports of both the countries in the years 1998-99 and 2003-04.Growth rate of both, Nepal and Bangladesh were highly significant at 1 per cent level ofprobability.

Other countries having positive growth rates of mango exports are UAE, UK,Singapore and Malaysia. The export to these countries is growing at 5.27, 5.19, 6.17 and10.29 per cent respectively when compounded annually. Some countries are also showingnegative growth rate. Among them Qatar is having maximum negative growth rate of 8.39 percent which is statistically significant at one per cent. Indian mango export to Qatar was 633.2MT in 1991-92 which rose to 1663.20 MT in 1998-99 but then dropped down to 374.97 MT in2010-11. Export growth of Indian mangoes to Saudi Arabia and Kuwait markets also camedown by 6.66 and 6.82 per cent every year which was significant at one per cent andcoefficient of determination were 0.54 and 0.33 respectively. Bahrain had a downward slopinggrowth of 2.63 but it was in significant.

Table 4.7: Growth Rate of mango productivity in different states(MT/ha)

Years AndhraPradesh


NaduWest


1991-92 12.00 6.88 8.39 10.00 5.63 10.00 6.03 8.00 5.49 3.19 11.14 8.121992-93 12.00 7.26 8.50 12.00 6.00 10.00 6.03 2.94 5.45 3.20 6.52 8.111993-94 12.00 7.49 9.50 12.00 3.92 10.00 6.22 8.15 5.53 3.53 8.92 8.311994-95 12.00 8.97 9.50 12.00 5.57 10.00 7.88 8.22 5.49 3.53 12.21 8.951995-96 12.00 7.89 9.50 12.00 4.86 5.56 7.88 8.50 5.02 3.53 9.36 8.431996-97 12.00 9.44 9.50 6.00 3.00 5.46 4.28 3.80 4.60 3.53 4.42 7.421997-98 12.00 6.42 9.50 12.00 1.00 6.46 1.30 9.00 4.28 3.53 4.19 7.391998-99 9.00 7.38 9.50 12.00 1.79 6.64 6.00 5.72 4.47 2.95 4.18 6.981999-00 8.00 7.87 9.51 12.00 3.40 6.03 6.50 9.33 3.57 2.90 4.00 7.062000-01 8.00 9.03 9.61 8.00 3.40 5.95 6.61 6.09 3.50 2.85 4.53 6.722001-02 7.17 7.71 9.80 9.00 3.40 7.01 3.96 8.95 3.75 3.03 3.73 6.362002-03 8.00 16.28 9.35 9.00 3.40 7.08 6.75 3.45 3.56 3.54 4.85 7.842003-04 8.00 8.38 9.56 11.00 1.48 7.08 5.36 5.99 3.52 4.50 4.93 6.032004-05 7.29 9.01 9.30 11.06 0.92 4.34 4.55 6.04 3.23 3.22 10.94 6.002005-06 6.14 8.63 8.32 11.12 0.87 3.96 4.08 5.72 2.85 3.08 19.97 6.002006-07 8.20 11.40 10.60 9.28 1.44 8.18 4.30 7.03 3.08 5.81 4.23 6.382007-08 8.60 12.66 9.09 6.12 1.56 8.49 5.52 7.71 1.70 5.81 3.98 6.362008-09 5.07 12.78 9.09 9.23 1.56 2.59 5.52 2.93 2.74 5.81 5.66 5.522009-10 8.45 12.98 11.01 6.82 1.26 7.05 4.80 5.06 3.25 5.85 6.10 6.502010-11 8.22 13.24 11.44 9.08 1.32 7.01 4.93 6.93 3.36 5.85 6.82 6.60

CAGR(%) -0.31** 3.23** 0.68* -1.73* -7.98** -2.64* -1.01(NS) -1.00(NS) -4.17** 3.22** -1.43(NS) -1.88**R 2 0.61 0.54 0.25 0.20 0.58 0.21 0.02 0.03 0.73 0.48 0.03 0.68

* Significant at 5 per cent level** Significant at 1 per cent level

Table 4.8: Growth Rate of mango exports to different countries(MT)

YearsUnitedArab

EmiratesBangladesh United

KingdomSaudiArabia Kuwait Bahrain Nepal Singapore Qatar Malaysia Total

1990-91 9581.61 94.84 792.57 5798.40 1056.16 983.71 4.83 33.81 633.20 15.19 19378.301991-92 12593.54 999.88 571.43 5395.65 587.37 1782.77 5.89 65.21 663.78 24.11 23045.731992-93 12570.36 2805.97 1141.98 4407.63 1711.93 1377.21 4.90 125.51 740.20 142.57 25850.391993-94 10172.53 1667.75 1030.20 4260.80 1691.58 1306.21 6.34 149.25 671.04 147.97 22793.891994-95 10004.40 4906.98 1218.15 4961.11 1053.57 1172.34 15.36 328.12 454.96 166.10 25414.371995-96 10899.07 1442.96 1269.10 4631.12 1426.99 574.19 2.75 349.86 517.46 238.88 22269.181996-97 9348.97 4879.89 1136.89 4626.62 1466.57 653.62 3.70 312.63 631.37 236.09 24773.501997-98 12200.98 7691.84 2060.14 7956.77 2469.98 1615.27 27.42 248.99 1014.47 390.21 42894.931998-99 8902.72 15069.28 1652.56 10267.76 2362.21 1842.10 266.52 260.29 1663.20 189.19 45407.601999-00 10021.00 9623.93 2297.23 5374.76 1420.87 1063.56 21.10 432.32 1036.96 375.56 34631.192000-01 6859.39 21426.83 842.71 2111.69 940.49 443.20 12.80 302.63 304.85 216.60 37109.672001-02 12809.55 21033.74 1372.87 2942.88 984.70 596.90 101.40 321.93 140.86 356.25 44429.322002-03 14033.56 13392.85 1227.57 2085.02 807.41 866.89 426.19 292.56 164.99 372.63 38001.912003-04 21056.16 23797.13 1511.63 3845.72 438.30 635.65 2930.11 238.84 232.23 294.23 60551.342004-05 10338.61 32503.22 1308.56 2300.53 267.96 848.69 3400.94 159.63 160.29 185.00 53480.052005-06 26533.76 32770.90 839.97 1564.15 104.59 620.81 4116.01 242.24 40.45 243.66 69606.592006-07 22045.51 42887.52 1883.19 1323.56 428.04 489.32 8055.73 230.86 90.99 332.22 79060.872007-08 22469.62 17063.60 2575.37 1488.95 460.84 474.23 7550.89 340.32 77.90 411.69 54350.802008-09 24570.91 45104.46 2527.39 2141.27 546.05 1154.59 4765.02 307.06 265.41 311.38 83703.182009-10 25608.15 33549.89 2958.65 3147.13 804.15 1238.50 4058.15 367.58 659.02 415.31 74460.632010-11 25725.00 23049.69 2723.54 1592.17 580.29 980.66 1991.26 387.81 374.97 397.82 59220.77CAGR 5.22** 23.93** 5.20** -6.66** -6.82** -2.63 (NS) 55.84** 6.17** -8.40** 10.30** 7.23**

R 2 0.56 0.74 0.48 0.54 0.33 0.14 0.83 0.36 0.32 0.49 0.86* Significant at 5 per cent level** Significant at 1 per cent level

Overall compound annual growth rate of mango exports from India was 7.23 per cent,which is statistically significant at 1 per cent. Mango exports from India travelled from 19378MT in 1991-92 to 59220 MT in 2010-11 experiencing maximum exports of 83703 MT in the2008-09. This increase in exports of mangoes from India was very well explained by timevariable as depicted by fairly high R2 of 0.86.

4.2 Behaviour of export prices of Indian mangoes in differentcountries

In order to analyse the behaviour of export prices of Indian mangoes, twenty yearsprice data of different countries was subjected to linear trend analysis. The results of theselong run export prices are presented in table 4.9.

Times series analysis of twenty years data reveals that in long run the export pricesof mangoes are having an increasing trend in all the countries except Nepal. Highest rise inmango prices was observed in case of Kuwait which was 3092 Rs per MT per year with theR2 value 0.68. Kuwait was followed by Qatar and UK, where the annual price rise of mangowas to the extent of Rs 2500 and Rs 2250 respectively. These price variations in both thecountries were explained by the time variable to the extent of seventy three per cent and sixtyeight per cent respectively. Apart from these nations, prices of mango export had a positivetrend in Singapore, Saudi Arabia, Bahrain, UAE, Malaysia and Bangladesh also. The annualincrease in prices of mangoes imported from India to the above mentioned countries was1416, 1343, 1178, 1019, 666.9 and 150.7 respectively with corresponding coefficient ofdetermination values of 0.74, 0.80, 0.67, 0.84, 0.42 and 0.29.

During the study period Nepal was the only one among the studied countries that experiencedyearly decrease in export prices. This decrease was to the tune of Rs 325.3 per MT per yearbut the independent variable under study failed to explain this decrease in prices at whichmangoes are exported to Nepal, as R2 value was merely 7 per cent.

4.3 Export competitiveness of Indian mangoesThe values of Nominal Protection Coefficients (NPC) for Indian mango exports to

different destinations are presented in the table 4.10. Country-wise NPC was worked out forthe year 2010-11. UAE and UK were found to be highly competitive markets with NPC 0.62and 0.54 respectively. Rest of the countries under study i.e Bangladesh, Saudi Arabia,Kuwait, Bahrain, Nepal, Singapore, Qatar and Malaysia were also found to be moderatelycompetitive in comparison to domestic market having NPC 0.89, 0.84, 0.93, 0.93, 0.96, 0.93,0.95 and 0.93 respectively for mango export from India in the year 2010-11 during June.

4.4 Direction of trade in Indian mango exportThe direction of trade of Indian mango to different importing countries was studied by

estimating the transitional probability matrix using the Markov chain framework. It indicatesthe loyalty of an importing country to particular country’s exports. To analyse the exports ofmango, five major countries of the globe were considered and others include the other minorcountries importing mango from India. The average exports from India to other countries wereconsidered for the overall analysis.

4.4.1 Change of direction of trade of mangoesTransitional probabilities of mango exports to different destinations from India are

presented in Table 4.6 depicting a broader idea of change of direction of trade over a periodof fifteen years. There were five major countries, which imported Indian mangoes viz.,Bangladesh, UAE, United Kingdom, Nepal and Saudi Arabia. The exports to remainingcountries were pooled under the ‘other’ countries. The diagonal elements in a transitionalprobability matrix provide the information on the probability of retention of the trade, while, therow elements indicate the probability of loss in trade on account of competing countries. Thecolumn elements indicate the probability of gain in trade from other competing countries.

Table 4.9: Behaviour of export prices of mangoes in different countries

(`/MT)

Countries Intercept Slope R 2

UAE 13684.00 1019.00 0.84

Bangladesh 6846.00 150.70 0.29

UK 16475.00 2252.00 0.73

Saudi Arabia 9411.00 1343.00 0.80

Kuwait 6947.00 3092.00 0.68

Bahrain 12412.00 1178.00 0.67

Nepal 17038.00 -325.30 0.07

Singapore 24922.00 1416.00 0.74

Qatar 3047.00 2500.00 0.73

Malaysia 20546.00 666.90 0.42

Figure 5. Behaviour of prices of Indian mangoes in different destinations during 1991-2010





Figure 5. Behaviour of prices of Indian mangoes in different destinations during1991-2010






Figure 5. (Contd…..) Behaviour of prices of Indian mangoes in different destinationsduring 1991-2010

Table 4.10: Nominal Protection Coefficient for mango exports to different countries during 2010-11

S.No Particulars Unit

UnitedArab

EmiratesBangladesh United

KingdomSaudiArabia Kuwait Bahrain Nepal Singapore Qatar Malaysia

1 Wholesale price ofmango (Delhi) `/Qtls. 4000.00 4000.00 4000.00 4000.00 4000.00 4000.00 4000.00 4000.00 4000.00 4000.00

2 Marketing margin `/Qtls. 200.00 200.00 200.00 200.00 200.00 200.00 200.00 200.00 200.00 200.00

3 Port clearing & handlingcharges `/Qtls. 750.00 750.00 750.00 750.00 750.00 750.00 750.00 750.00 750.00 750.00

4 FOB Price `/Qtls. 4950.00 4950.00 4950.00 4950.00 4950.00 4950.00 4950.00 4950.00 4950.00 4950.005 Freight charge `/Qtls. 470.00 250.00 600.00 480.00 200.00 400.00 460.00 450.00 450.00 450.006 Insurance at 2% of price `/Qtls. 80.00 80.00 80.00 80.00 80.00 80.00 80.00 80.00 80.00 80.007 landed cost `/Qtls. 5500.00 5280.00 5630.00 5510.00 5230.00 5430.00 5490.00 5480.00 5480.00 5480.008 Exchange rate 1$ = ` 49.00 49.00 49.00 49.00 49.00 49.00 49.00 49.00 49.00 49.009 CIF price US $/Qtl 112.24 107.76 114.90 112.45 106.73 110.82 112.04 111.84 111.84 111.84

10 Reference price US $/Qtl 181.00 120.62 210.13 133.71 114.00 118.00 116.00 119.63 117.22 119.0011 NPC 0.62 0.89 0.55 0.84 0.94 0.94 0.97 0.93 0.95 0.94

Table 4.11: Transitional Probability Matrix of Indian mango exports to differentdestinations

Losses

Bangladesh UAE Nepal UKSaudiArabia Others

Bangladesh 0.5027 0.3757 0.0309 0.0269 0.0000 0.0638

UAE 0.4147 0.5680 0.0000 0.0173 0.0000 0.0000

Nepal 0.4136 0.0000 0.5864 0.0000 0.0000 0.0000

UK 0.4856 0.1719 0.0000 0.3425 0.0000 0.0000

Saudi Arabia 0.0000 0.0000 0.0000 0.0777 0.4569 0.4654

Others 0.3319 0.0000 0.0000 0.0000 0.2548 0.4133

Gains

It is evident from Table 4.11 that Nepal, UAE and Bangladesh are comparativelystable markets among major importers of Indian mangoes as reflected by the higherprobability of retention at 0.59, 0.57 and 0.50 respectively. That means the probability thatNepal retained its export share over the study period was 59 per cent likewise UAE retainedits exports by 57 per cent and Bangladesh up to 50 per cent.

Saudi Arabia and other minor importers are also fairly stable retaining their share tothe extent of 46 per cent and 41 per cent respectively while UK had retained only 34 per centof its previous imports which implies that it is also a stable market but to a lesser extent thanother importers. Bangladesh lost its 38 per cent of import share to UAE, 3 per cent to UK, and6 per cent to other countries but at the same time it gained 409 per cent from UK, 41 per centexport share of Indian mangoes each from UAE and Nepal and 33 per cent from others. UAElost (41.5 per cent) as well as gained (37.6 per cent) its major share from Bangladesh and asmall part was lost (1.73 per cent) and gained (1.71 per cent) from UK thus retaining its 56.8per cent share. Nepal lost 41.4 per cent of Indian mangoes to Bangladesh but at the sametime it gained up to 3.1 per cent from Bangladesh hence managing to retain its share up to58.6 per cent.

UK lost its share of Indian mango to Bangladesh to the tune of 49 per cent and 18 percent to UAE while it snatched 8, 3, 2 per cent of market from Saudi Arabia, Bangladesh andUAE respectively. Saudi Arabia lost its share of Indian mango import (i.e. 47 %) to otherimporting nations. It gained from other nations to the tune of 26 per cent. Other importingnations lost most of their share to Bangladesh (33 %) but gained 47 per cent from SaudiArabia.

As per the Transitional Probability Matrix (table 4.11), Nepal is the most reliable andloyal market for mango export among the markets under study.

4.4.2 Projections of Indian mango exports to major importing countriesThe market share projections of Indian mango to the major importing countries were

computed up to 2015-2016 using the transitional probability matrix (table 4.11). The actualand projected values are also presented graphically for easy understanding. Table 4.12presents the projections based on actual and estimated values from 1995-96 to 2010-11.

As it could be evident from the table, the actual export share to Bangladesh hadincreased from 6.48 per cent to 38.9 per cent of total Indian exports between 1995-96 and2010-11. The quantity exported had increased from 1442.96 MT to 23049.69 MT during thisperiod. Projected export show that exports to Bangladesh would be around 25800 MT by2015-16 would be about 47 per cent of total exports in that year. The proportion of actualmango exports to UAE decreased from 48.94 per cent in 1995-96 to 43.44 per cent in 2010-11. The actual exports were 25725 MT during 2010-11. As per projections exports areexpected to go down and it will be approximately 23300 MT by 2015-16. This wouldconstitute42 per cent of the total mango export from India. Export share to Nepal increasedfrom 0.01 per cent in 1995-96 to 3.36 per cent in 2010-11. The projected share of Indianmango exports would be 3.51 per cent of total mango export to Nepal in 2015-16 which wouldbe approximately 1900 MT in absolute terms.

Although in absolute terms, there is an increase in quantity of mango exports to UKbetween the years 1995-96 to 2010-11 from 1269.10 MT to 2723.54 MT, but in relative terms,it has decreased from 5.7 per cent to 4.6 per cent and the estimated value suggests thatexports to UK will decrease and will be approximately 1900 MT by 2015-16. Export to SaudiArabia has drastically reduced to 1592 MT in 2010-11 from 4631 MT in 1995-96. The shareof exports from India out of total exports also came down to 2.69 per cent from 20.8 per cent.As per projections is expected that quantum of mango export to Saudi Arabia would be 1960MT during 2015-16 which would constitute just 3.57 per cent of total export basket.

4.6 Market integration in Indian mangoesCo-integration is an analytic technique for testing for common trends in multivariate

time series and modelling long-run and short-run dynamics. Two or more predictive variablesin a time-series model are co-integrated when they share a common stochastic drift.Variables are considered co-integrated if a linear combination of them produces a stationarytime series.

Co-integration was studied to analyse the integration between domestic market(Delhi) and international markets using monthly data of five years (2006-07 to 2011-12). Co-integration is a two step process: first any long run equilibrium relationships between marketsare established, and then a dynamic correlation model is estimated.

The first step in co-integration is Augmented Dickey Fuller- Unit Root Test (ADF Test)which is conducted to check the data for stationarity. On conducting ADF Test for presentstudy it was found that Kuwait, Qatar and Bahrain markets had unit root i.e. they were alreadystationary which meant that co-integration could not be studied in these markets. Hence thesethree markets were removed from the data set. Rest of the markets i.e. UAE, Bangladesh,Saudi Arabia, Nepal, Singapore, Malaysia and Delhi were made stationary by taking firstdifference.

As a part of co-integration analysis, Gragner Causality Test is used to know if co-integration exists between two markets or not. The results for Gragner Causality test revealedthat Delhi market Gragner caused Malaysia, Singapore Gragner caused Delhi market andUAE Gragner caused Delhi market. Results obtained from Gragner Causality test were sameas that of Vector Error Correction Test which was done to analyse co-integration betweenDelhi and UAE, Bangladesh, Saudi Arabia, Nepal, Singapore and Malaysia.

In order to know the co-integration between the domestic and export marketsconsidered under study, Vector Error Correction Mechanism was conducted and the results ofthe same are presented in the table 4.13. The co-integration coefficients were tested for thesignificance by comparing the [T] values with the table [T] value (1.7) and the significancewas established. The co-integration coefficients were significant only with Saudi Arabia andUAE with the co-integration coefficient values of 0.14 and 0.10 respectively. For othermarkets i.e. Delhi, Bangladesh, Malaysia, Nepal, and Singapore the co-integrationcoefficients were found to non significant.

Table 4.12: Projections of Indian mango exports to major importing countries

(MT)

Years Bangladesh UAE Nepal UK Saudi Arabia Others

2011-201225775.50

(43.52)

23738.95

(40.09)

1880.83

(3.18)

2120.60

(3.58)

1781.98

(3.01)

3922.91

(6.62)

2012-201325911.80

(47.01)

23531.40

(42.69)

1900.43

(3.45)

1967.69

(3.57)

1813.61

(3.29)

4095.84

(7.43)

2013-201425885.48

(47.04)

23438.44

(42.59)

1916.14

(3.48)

1917.84

(3.49)

1872.13

(3.40)

4190.74

(7.62)

2014-201525847.49

(47.03)

23367.18

(42.51)

1924.54

(3.50)

1903.001

(3.46)

1923.038

(3.5)

4255.52

(7.74)

2015-201625816.61

(47.01)

23309.88

(42.45)

1928.29

(3.51)

1899.62

(3.46)

1962.80

(3.57)

4303.56

(7.84)

*Values in parentheses denote percentages

Figure 6. Projection of share of Indian mangoes to different destinations upto 2015-16



Figure 6. Projection of share of Indian mangoes of different destinations upto 2015-16



Figure 6. (Contd….) Projection of share of Indian mangoes to different destinationsupto 2015-16

Table 4.13: Co-integration between domestic and international market

ErrorCorrection: D(DEL) D(BNG) D(MLY) D(NP) D(SA) D(SNG) D(UAE)

CointEq1 -0.0598 -0.0487 0.060628 0.047117 -0.13501 0.037985 0.098838

[-0.83209] [-1.00917] [ 1.59277] [ 0.83974] [-1.77965]* [ 0.70091] [ 2.46145]*

D(DEL(-1)) 0.145685 -0.12546 -0.18663 -0.07807 -0.07825 -0.048 -0.05647

[ 0.92786] [-1.18993] [-2.24406]* [-0.63684] [-0.47212] [-0.40537] [-0.64366]

D(DEL(-2)) 0.204435 0.069707 0.108811 -0.00841 0.221451 0.292262 -0.18208

[ 1.29087] [ 0.65549] [ 1.29716] [-0.06801] [ 1.32459] [ 2.44722]* [-2.05764]*

D(BNG(-1)) 0.327838 0.017164 0.016419 0.294834 0.307367 0.258385 -0.17625

[ 0.83622] [ 0.06520] [ 0.07907] [ 0.96322] [ 0.74267] [ 0.87398] [-0.80459]

D(BNG(-2)) 0.340227 -0.39127 -0.08549 -0.39549 0.197012 -0.73524 0.308172

[ 0.92828] [-1.58982] [-0.44038] [-1.38207] [ 0.50919] [-2.66017] [ 1.50482]

D(MLY(-1)) 0.352502 0.170183 -0.13058 -0.03388 -0.06431 0.630298 -0.35104

[ 1.23059] [ 0.88477] [-0.86064] [-0.15150] [-0.21265] [ 2.91790] [-2.19323]

D(MLY(-2)) -0.14981 0.159953 -0.256 -0.10913 -0.28268 -1.2575 0.057724

[-0.47446] [ 0.75441] [-1.53066] [-0.44268] [-0.84804] [-5.28119] [ 0.32718]

D(NP(-1)) -0.33515 0.039918 0.108274 -0.24672 -0.35531 -0.02745 0.256223

[-0.95144] [ 0.16876] [ 0.58032] [-0.89709] [-0.95551] [-0.10334] [ 1.30180]

D(NP(-2)) -0.4129 0.283389 0.061991 0.212953 -0.4481 0.670245 -0.28413

[-1.23254] [ 1.25978] [ 0.34936] [ 0.81418] [-1.26706] [ 2.65312] [-1.51791]

D(SA(-1)) 0.366787 0.171938 -0.22111 -0.15413 -0.20996 -0.34413 -0.07745

[ 1.47093] [ 1.02686] [-1.67407] [-0.79169] [-0.79760] [-1.83010] [-0.55590]

D(SA(-2)) 0.200628 0.080334 -0.0326 0.004089 0.129841 -0.13378 0.131416

[ 1.04650] [ 0.62404] [-0.32107] [ 0.02732] [ 0.64156] [-0.92534] [ 1.22682]

D(SNG(-1)) -0.5106 0.012798 0.022178 0.014085 -0.17428 0.014820 0.042903

[-3.32013]* [ 0.12393] [ 0.27226] [ 0.11730] [-1.07350] [ 0.12779] [ 0.49928]

D(SNG(-2)) -0.10373 -0.07632 -0.10406 0.033901 -0.09942 -0.08783 0.208954

[-0.70681] [-0.77446] [-1.33874] [ 0.29588] [-0.64174] [-0.79363] [ 2.54828]

D(UAE(-1)) -0.33683 -0.04648 0.097750 0.059178 -0.34207 -0.0534 -0.52147

[-1.61434] [-0.33173] [ 0.88449] [ 0.36327] [-1.55298] [-0.33939] [-4.47293]

D(UAE(-2)) -0.00591 0.090332 -0.06989 0.097046 -0.28484 -0.32416 -0.28522

[-0.02432] [ 0.55335] [-0.54276] [ 0.51128] [-1.10986] [-1.76816] [-2.09968]

*values are significant at 5 per cent** Figures in square brackets indicate T values** DEL- Delhi ; BNG- Bangladesh ; MLY- Malaysia ; NP- Nepal ; SA- Saudi Arabia ;

SNG- Singapore ;UAE- United Arab Emirates

Table 4.14: Problems associated with mango export

(n=30)

S.No Problems Number ofrespondents Percentage

1. Perishable nature of fruit 30 100.00

2. High cost of transportation 27 90.00

3. Lack of storage facilities 26 86.67

4. Absence of refrigerated trucks 27 90.00

5. Lack of market information 22 73.33

6. Lack of knowledge on export varieties 23 76.67

7. Lack of consistency in quality 26 86.67

8. Lack of consistency in supply 27 90.00

9. Absence of suitable export varieties 25 83.33

10 High packing cost 28 93.33

One month previous prices of Delhi market will have an impact on the present pricesin Malaysia market to an extent of 18.66 per cent in opposite direction. Similarly two monthlagged prices of Delhi market will affect present prices in Singapore market up to 29.2 percent in positive direction and present UAE market prices to an extent of 18.2 per cent inopposite direction. Similarly one month lagged prices in Singapore market will have an impactto an extent of 51 per cent on present prices of mangoes in Delhi market. In all other marketsthough there exists co-integration between the prices but they were insignificant.

4.6 Problems associated with mango exportTable 4.14 indicates problems identified in exports of mangoes from India. Perishable

nature of fruit was found to be the major constraint as expressed by cent per cent of samplerespondents. Next important constraints observed in export of mangoes were high packingcost (93.33 %) followed by high cost of transportation (90 %) and absence of refrigeratedtrucks (90 %). Exporters during the study also expressed that lack of storage facilities (86.67%), lack of consistency in quality (86.67 %), absence of suitable export varieties (83.33 %),lack of knowledge on export varieties (76.67 %) and lack of market information (73.33 %)were the other problems associated with mango exports to different destinations from India.

5. DISCUSSION

The results of the investigation mentioned in the previous chapter are discussed in detail in this chapter under the following heads. It is hoped, it would help in identifying some policy measures, which would be adopted by the government to overcome constraints identified by this study.

5.1 Annual growth and trend in area, production, productivity and export of mangoes in India

5.2 Behaviour of export prices of Indian mangoes for different countries


5.4 Direction of trade of Indian mango exports

5.5 Market integration between domestic market prices and world market


5.1 Annual growth and trend in area, production, productivity and export of mango

The annual time series data collected with respect to area, production, productivity and export of Indian mangoes were subjected to linear trend analysis and the results of analysis are interpreted under the following subheads.

5.1.1 Annual growth and trend in area under mangoes across the states

The linear trend was computed in order to ascertain the long-run movement of area of mangoes in different states and CAGR to arrive annual fluctuations and are presented in table 4.1 and 4.5 respectively.

It is evident that, area under mango cultivation is increasing in all the states over the period of time except Bihar and Kerala. In Maharashtra the annual increase in area was found to be maximum i.e. it increased at the rate of about 28000 ha annually during the study period.

Maharashtra state is known for cultivating Alphonso varieties of mangoes particularly Rantnagiri Alphonso which has lot of demand in international market. The steady increase in demand for this variety has influenced the orchard owners to expand the area under mango cultivation. The R

2 value also indicates that eighty six per cent of the change in area was due

to the influence of independent variable, time which clearly indicates that over the years the increase in area under mangoes in Maharashtra was rapidly increasing.

Apart from this, area under mangoes in Andhra Pradesh, Karnataka, Gujarat, Tamil Nadu, West Bengal and Orissa also increased positively with a high value of coefficient of determination.

The increase in area dedicated to mango cultivation was mainly due to conversion of paddy fields into mango orchards because of relatively higher profitability of the crop in West Bengal and Orissa. This was partly due to greater profitability and partly because cultivation under food crop cannot be carried out within close proximity of well-grown mango orchards due to shade effect and chemical effect at the time of mango blossoms. However area under crop in Bihar and Kerala was decreasing year by year but the decrease was not significant due to low value of coefficient of determination. Decrease in cropping pattern is not substantial may be due to so some developmental activities in 2000-01 and 2001-02 (table 4.5), then onwards there was a steady increase over the years.

At all India level the area under mangoes was found to be increasing rapidly year by year indicating the economic importance of the crop which might have been triggered because of increased export potential in the international market and increased demand for mango fruits and its products in domestic market.

5.1.2 Annual growth and trend in mango production across the states

Linear trend and growth analysis of 20 years mango production data in India presented in table 4.2 revealed that the annual increase in mango production was highest in Uttar Pradesh with an yearly increment of 91197 MT. This increment was lowest in case of West Bengal where production was rising by 6720 MT per year and in other states (2370 MT per year). Mango production in Bihar, which is an important mango growing region, had a declining trend. Production in the state was declining every year by 29784 MT but this decline was not attributed completely to the variable included in the study, time, as indicated by the R

2 value of 0.29. There might be some other factors which led to this kind of phenomenon in

mango production in Bihar state. Figures in the table for rest of the states revealed that quantum of mango production were increasing every year.

In long run, in all India basis, country experienced an yearly increment of 28572 MT in mango production and this increment was fairly explained by the time variable (R

2 value 0.79)

during the study period. One of the major factors behind this spectacular increase in the production of mangoes is the Government’s policy to set up Agri Export Zones for mangoes in major mango producing states. These zones have helped in establishing a continuity factor and an assured supply base for export of quality mangoes. Establishment of cooperatives in important mango growing states like Maharashtra (Maha Mango, Mangrow etc) and Andhra Pradesh (Vijaya) during the study period, also helped in boosting mango production in the country.

5.1.3 Annual growth and trend in mango productivity across the states

In order to ascertain the long-run movement for analysing trend in productivity of mango in different states, the linear trend was computed and to study short term annual differences CAGR was conducted. The results henceforth are presented in the Table 4.3 and 4.7.

Over the years, productivity of mango was noticed to increase only in the states of Karnataka, Uttar Pradesh and Kerala with productivity rising at the rate of 0.67, 0.32 and 0.14 MT per ha every year respectively. In rest all the states, mango productivity was declining over the years which is evident from the table. The outcome of this decline was that productivity of mango crop in India as a whole came down by 0.14 MT every year and the time variable explained this decline to the extent of 68 per cent.

There are many factors which are leading to this decrease in productivity of mango in India. Even now, in many parts of the country unproductive orchards of seedling origin are being maintained. These orchards with unmanageable canopy neither produce fruits nor the quality. Thus production of mango in India is not at par with the area attributed to the crop hence leading to decreasing productivity. From the previous subsection (i.e. table 4.1), it is noticed that a large area has come up under mango cultivation. Since such new orchards require a minimum of five to six years for full bearing, the productivity on the whole might seem to have come down which might not be a real factor. When these orchards start bearing full, the productivity is hoped to increase normally. The Maharashtra state, is known for alphonso varieties of mangoes which are having low productivity but have very high export potential. Over the years the orchards with other varieties having higher productivity were replaced with alphonso to usher to the needs of export markets.

In the traditional low density cultivation where most of the varieties are either poor yielders or alternate bearers, per ha plant population in mango orchard ranges from 75 – 100. In such situation, mango trees become very big, which make it difficult to perform the needed cultural operations, like training, pruning, disease pests control etc. As a result, irregular bearing of fruits becomes the rule rather than an exception (Source: Kumar and Biswas, 2011). Low yield or no yield is also common due to alternate bearing. The yield loss due to pest and diseases is accounted to more than 15 to 20 per cent in a normal year and even to the extent of 40 to 60 per cent in severe infection. Physiological disorder is also one of the reasons that accounts for low productivity of mango in India. Spongy tissue in Alphonso is a typical example for physiological disorder in mango which affects both the domestic and international trade. Similarly, flower malformation, black tip and alternate bearing are the other disorders associated with mango cultivation. Depleting water table in fields is also one of the reasons behind low productivity of mango crop in India.

5.1.4 Annual growth and trend in mango exports to different countries

The export trend of fresh mangoes from India for the period 1990-91 to 2010-11 has been furnished in the table 4.4. The table revealed that countries such as UAE, Bangladesh, UK, Nepal, Singapore and Malaysia grew in positive direction whereas Saudi Arabia, Kuwait, Bahrain and Qatar depicted a negative growth over the years in mango exports from India.

Among the countries which established a positive growth in Indian mango imports, Bangladesh stood at the top followed by UAE, Nepal, UK, Malaysia and Singapore. This rising trend was possible because of different reasons. Free Trade Agreement signed by India with Bangladesh, Nepal and Malaysia led to the increase in quanta of mango by these countries demanded from India (SAFTA in case of Bangladesh and Nepal; India and Malaysia both are part of ASEAN). Nepal and Bangladesh being very near to India is also one of the reasons for high Indian mango imports by these countries. UAE exhibited higher growth in its mango imports from India mainly because quality standards are not very stringent in Middle East countries and also because of increasing Indian migrant population particularly to UAE. As per 2010 data out of total UAE population 35 per cent is constituted by Indians (Source: www.wikipedia.org). As far as UK is concerned, they have been preferring Indian mangoes for their premier quality since the colonial era. The same tradition has been continued over the years which led to significant growth in mango exports to this country.

Most international trade in fresh mangoes takes place within short distances. In Asian continent Pakistan, Thailand and Philippines are well known mango suppliers to the world and hence big competitors for India. India and Pakistan are catering to the needs of West Asian markets where Pakistan is better off with a world ranking of 7 whereas India ranks 13

th in

mango exports (Source: APEDA). Diversification of trade in mangoes by these competing markets might have led to negative growth in mango exports to Saudi Arabia, Kuwait, Bahrain and Qatar.

Since 1990-91 to 2010-11 mango exports have diversified from 28 countries to 42 countries.US and Japan which had imposed ban on import of Indian mangoes have again opened their markets as mangoes are now subjected to vapour heat treatment for irradiation of maggots. China also opened its market for import of Indian mangoes. India is one of the first countries to export its mangoes to China under bilateral trade agreement. This became possible with the two governments signing the protocol of phyto-sanitary requirements for exporting mangoes.

Divergence of Indian population throughout the world, initiatives to meet the phyto-sanitary requirements of mango importing countries so as to reach more international markets and many other related factors have led to a spectacular annual increment of 2943 MT per year in demand of Indian mangoes internationally and this increment is successfully explained by the time variable up to 81 per cent as per the indications of R

2 value.

5.2 Trend in behaviour of export prices of mangoes to different countries

The trend analysis provides an intuition to analyse the behaviour of a variable in long run. Table 4.9 represents the behaviour of export prices of mangoes from India to different destinations.

Results of trend analysis were striking as it revealed that price at which all the countries under study imported mangoes from India, was increasing every year with Nepal as an exception. The table depicted that yearly hike in Indian mango export prices was maximum in case of Kuwait i.e. Rs 3092 per MT per year. Interestingly, this result is contrary to the trend of Indian mango export to Kuwait in terms of quantum as the Metric Tonnes of Indian mangoes exported to the country depicted a declining trend. Similar trend was noticed in case of Qatar which followed Kuwait in Indian mango imports. In case of both the countries the R

2

values were sufficient to explain the yearly increase in mango prices from India (R2 values

0.68 and 0.73 respectively).

Indian mango imports to UK are successfully fetching Rs 2252 per MT more every year which signifies that popularity of Indian mangoes which existed among Europeans since colonial era is still dominating. The demand for mangoes in UK is the highest during May to July which is the harvesting season for Indian mangoes. This helps India in encashing the opportunity and fetching remunerative prices for its mangoes in UK.

Other nations i.e. Singapore, Saudi Arabia, Bahrain, UAE, Malaysia and Bangladesh also imported mangoes from India at higher prices every year with the rise ranging from Rs 1416 to Rs 150.70 per MT per year. This increase was successfully supported by the corresponding R

2 values of each country except Bangladesh whose coefficient of

determination was 0.29. This yearly price rise might be due to inflationary trend also. Nepal was the only country among the studied ones that experienced decrease in prices at which mangoes are exported from India to Nepal. It depicted a decline of Rs 325.30 per MT per year during the study period of 20 years. But this decrease was not because of the time factor as the explanatory variable in question i.e. time, is explaining the variations in mango export prices to Nepal only up to 7 per cent which signifies that there might be some other reasons which led to this cause. There might be certain legal and political issues pertaining to the country that resulted in reduction in Indian mango prices.

Due to varied climate and soil, mangoes are harvested in India over a long period of time which enables the country to meet the demand of international markets for a longer duration hence aiding in fetching better prices.


India has been endowed with bountiful natural resources in terms of soil, climate, rainfall etc., which are suitable for the production of various crops in general and the horticulture crops in particular. The potential capacity of competitiveness of the export in terms of mango has been analysed country-wise with the help of Nominal Protection Coefficients (NPC) for the year 2010-11 and presented in the Table 4.10.

Europe’s acceptance of different varieties is greater, because of a large demand from Asian immigrant groups and also because phyto-sanitary restrictions are less stringent there. UK imports of mango are concentrated during May to July which is the harvesting season for Indian mangoes. This makes UK highly competitive market. Similarly in UAE, huge Indian population resides which helps in fetching remunerative prices for Indian mangoes. The results also support the fact of a lower value of NPC, making UAE and UK as the most trusted destinations for Indian exports.

Malaysia and Thailand which are potential mango exporters and are geographically located very close to Singapore making Singapore moderately competitive for Indian mangoes. Likewise Saudi Arabia, Bahrain, Kuwait and Qatar are also moderately competitive in absorption of Indian mangoes as they would be depending on Pakistan rather than India to meet their mango demand.

Exports to Bangladesh and Nepal are very high as it is convenient to export to these markets due to geographical proximity with loose or no quality control specifications for mango. But the low prices received by Indians on mango export to these markets make it comparatively less competitive than UK and UAE.


Transitional probabilities of Indian mango export destinations presented in Table 4.11 depict a broader idea of change of direction of trade of mango export over a period of fifteen years. The major countries considered for study were Bangladesh, UAE, United Kingdom, Nepal and Saudi Arabia. The mango exports to remaining countries were pooled under ‘other’ countries.

Interestingly, Bangladesh and UAE both have gained and lost simultaneously from each other and retained their share to the tune of 50 and 56 per cent respectively, thus safeguarding themselves as stable markets. Nepal, which is comparatively most stable one amongst the studied markets as it has retained its share up to 58 per cent, has lost a huge quantum to no other country but Bangladesh up to 41 per cent.

UK has not gained any considerable share from any country but lost 48.5 per cent to Bangladesh and 17.2 per cent to UAE and managed to retain 34.25 per cent of mango imports from India. Saudi Arabia lost as well as gained from other countries keeping itself moderately stable at 45.60 per cent. Other countries have lost their major share of 33 per cent to Bangladesh retaining 41 per cent. Hence it is evident that among all the studied markets, Bangladesh has gained from all the countries except Saudi Arabia, losing majorly to UAE alone (rest are meagre shares of 3, 2 and 6 per cent). However markov chain model has clearly indicated that Bangladesh, UAE, Nepal and Saudi Arabia were the most loyal countries as far as Indian mango export destinations are concerned.

Projections shown in the table 4.12 indicate that rise in exports in 2015-16 will be maximum in case of Bangladesh. It will increase from 38.92 per cent in 2010-11 to 47.01 per cent in 2015-16. As per projections, in 2015-16 India is expected to export mangoes to Bangladesh to an extent of 25,816 MT whereas the exports in 2010-11 were 23,049 MT.

Therefore, Bangladesh proves to be an important destination for Indian mangoes. The free trade agreements under BIMSTEC (The Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation, a seven-nation regional grouping comprising Bangladesh, India, Myanmar, Sri Lanka, Thailand, Bhutan and Nepal) and SAARC (The South Asian Association for Regional Cooperation, an eight-nation regional grouping comprising Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan, Sri Lanka and Afghanistan) would be helpful in encouraging greater cooperation and trade between the countries.


In order to study the integration between domestic and international markets, five years monthly data was subjected to co-integration analysis and the results obtained have been presented in table 4.13. Two or more predictive variables in a time-series model are co-integrated when they share a common stochastic drift. Variables are considered co-integrated if a linear combination of them produces a stationary time series.

Since the objective is to study co-integration between domestic market price and international market price, attempt has been made to establish relationship beween Delhi market with other international markets.

In Augmented Dickey Fuller- Unit Root Test (ADF Test) it was found that Kuwait, Qatar and Bahrain markets were already stationary. Hence these three markets were removed from the data set. Rest of the markets i.e. UAE, Bangladesh, Saudi Arabia, Nepal, Singapore, Malaysia and Delhi were made stationary by taking first difference. Gragner Causality test which aims at identifying presence or absence of co-integration between two markets revealed that Delhi market was co-integrated with Malaysia, Singapore was co-integrated with Delhi and UAE was co-integrated with Delhi.

Vector Error Correction Test (table 4.13), which represents short term adjustments, revealed that any fluctuations in mango prices in Saudi Arabia and UAE markets will be absorbed in approximately one and three days respectively.

The vector error correction mechanism also revealed that one month previous prices of Delhi market would have an impact on Malaysia market to an extent of 18.66 per cent in opposite direction i.e. if Delhi market mango prices increase by Rs 100 in present month, the effect of this cause would be in the form of decrease in next month mango prices in Malaysia by Rs 18.66. Other than this if any change occurs in the prices of mangoes in Malaysia, it would be because of some other factors. Similarly two month lagged prices of Delhi market mangoes would affect Singapore market prices up to 29.2 per cent in same direction and to UAE market to an extent of 18.2 per cent in opposite direction as depicted by Gragner Causality Test. Vector error correction test revealed that a change of 1 rupee in Singapore market in present month would be responsible for decreasing next month’s Delhi market mango prices by 0.51 paise.


India which is close to half of the world’s mango production and is a home to more than 1000 mango varieties, fails to compete with other mango producing countries in terms of exports. Some of the problems pertaining to mango exports from India have been identified and listed in table 4.14. As per the sample respondents, all agreed that perishability of mango fruit was the major problem because if the fruit is not dispatched timely it leads to huge losses since mango importing countries are very particular about quality.

It has been reported that more than 20 per cent of the produce is lost in the post-harvest operations. This is mainly because of factors like non-availability of proper facilities for handling the produce, inadequate transport facilities and lack of storage facilities at the ports. Exporters in the study also expressed problem of lack of consistency in quality. Maintaining quality standards as per each market is a problem as every country has its own SPS standards which are difficult to maintain and this problem is amplified by unavailability of proper information of export markets.

Comparing India to selected countries, across destination markets, modes of transport, and commodities traded indicates that, on average, India’s international transportation costs are 20–30 per cent higher than those faced by other countries. Since transportation costs are found to account for nearly 45 per cent of retail price when air transport is used and 25 per cent in case of maritime transport, Indian products are 5 to 15 per cent more expensive than their foreign counterparts simply on account of high international transportation costs which is one of the major hurdle in mango exports from India as stated by mango exporters.

6. SUMMARY AND POLICY IMPLICATIONS

India, known as fruit and vegetable basket of the world, is the second largest producer of fruits (71.52 million MT), after China, obtained from 6.33 million ha area and contributing about 12 per cent share in global fruit production. The horticulture sector contributes about 30.4 per cent of the agriculture GDP, besides providing employment for 19 per cent of the labour force. The country ranks first in production of bananas (28%) papayas, mangoes (39%) lemons, limes, pomegranate, sapota and aonla. The quantum of mangoes produced by India constitutes huge share of world’s mango production. But it contributes only 0.37 per cent to the export earnings from the agricultural products.

The total agri-exports from India to the world in 2010-11 stood at Rs 43, 62, 688 Lakhs with the share of fresh mangoes to the extent of Rs 16292.13 Lakhs. Though India's share in the global market is still nearly 1% only, there is increasing acceptance of horticulture produce from the country. The research and development programmes in horticulture have greatly contributed to the present scenario. Still there are a few gaps which need to be addressed for consolidation of strengths.

Mango (Mangifera indica l.) belonging to the Anacardiaceae family, is the most important fruit of India. It is known as “King of fruits” and is the most important commercially grown fruit crop of India. Mango covers an area of 4,369 thousand ha (as per 2010 data) where India occupies top position among mango growing countries of the world and produces 52 per cent of the total world mango production. Among internationally traded tropical fruits, mango ranks only second to pineapple in quantity and value. The major markets for fresh and dried mangoes are Malaysia, Japan, Singapore, Hong Kong and the Netherlands.

India has the richest collection of mango cultivars with nearly 1000 varieties mango in India but only about 30 are grown commercially. Andhra Pradesh tops the list of mango producing states with 27.1 per cent share, followed by Uttar Pradesh with 23.88 per cent. India is one of the 15 leading exporters of agricultural products in the world. As per the International trade Statistics 2011, published by the World Trade Organization (WTO), India’s agricultural exports amounted to US $ 23.2 billion with a 1.7 per cent share of world trade in agriculture in 2010 (Source: APEDA). India exports mango to over 50 countries worldwide. Exports to UAE and Bangladesh alone accounted to 73 per cent (in terms of value) in 2010-11. Other major importing nations for Indian mango are Saudi Arabia, Qatar, Bahrain, UK, Kuwait, Singapore and Malaysia. Although a lion’s share of Indian mangoes is exported to the Gulf countries, efforts are being made to tap the European, American and Asian markets also. About 13,000 tonnes of Alphonso variety is exported to Middle East, the UK and the Netherlands every year.

Varieties such as Alphonso, Dashehari, Kesar and Banganapalli, that are currently in demand in the international markets are produced and exported from India. ‘Mahamango’, a cooperative society, was established in 1991 with the support of the Maharashtra State agricultural & Marketing Board (MSAMB, Pune). It was mainly formed to boost the export of Alphonso mangoes as well as for domestic marketing. A similar association named ‘Mangrow’ has been formed for the export of Kesar mangoes from Aurangabad district of Maharashtra.

Even after having innumerable domestic advantages, India ranks thirteenth in mango export with a meagre share of 1.51 per cent (in 2010). Mexico, Thailand and Brazil rank first second and third respectively in mango exports.

Therefore, it was imperative to study the market opportunities and to plan for appropriate export marketing strategy and policy so as to strengthen the export trade in mango.

The specific objectives of the study were

a. To analyze the growth and trends in area, production, productivity and export of mangoes from India.

b. To study the behavior of export prices of Indian mangoes to different destinations over the years.

c. To study the export competitiveness and direction of trade of mangoes.

d. To study the integration of domestic and export markets for mangoes with respect to prices.

e. To identify the problems associated with export of mangoes.

The study was based on both primary and secondary data. The data on area, production, productivity, price and volume of trade on exchanges for a period of twenty years from 1991 to 2010 was compiled from APEDA, various published journals, periodicals and websites. For studying the problems involved in export of mangoes, a sample of thirty mango exporters was selected. Sample was selected through random sampling technique. The information was collected from the respondents through mailed questionnaire method.

The salient findings of the study

6.1 Annual growth and Trend in area, production, productivity and export of mango

The time series data collected on yearly on area, production, productivity and export of Indian mangoes were subjected to linear trend analysis and CAGR to arrive at annual fluctuations.

Area under mango cultivation was increasing in all the states over the period of time except Bihar and Kerala. In Maharashtra the annual increase in area was found to be maximum i.e.it increased at the rate of about 28000 ha annually during the study period. Maharashtra state is known for cultivating Alphonso varieties of mangoes particularly Rantnagiri Alphonso which has lot of demand in international market. The steady increase in demand for this variety has influenced the orchard owners to expand the area under mango cultivation. The increase in area dedicated to mango cultivation was mainly due to conversion of paddy fields into mango orchards because of relatively higher profitability of the crop in West Bengal and Orissa. However area under crop in Bihar and Kerala was decreasing year by year but the decrease was not significant due to low value of coefficient of determination.

At all India level the area under mangoes was found to be increasing rapidly year by year indicating the economic importance of the crop which might have been triggered because of increased export potential in the international market and increased demand for mango fruits and its products in domestic market.

Annual increase in mango production was highest in Uttar Pradesh with an yearly increment of 91197 MT. In long run, on all India basis, country experienced an yearly increment of 28572 MT in mango production and this increment was fairly explained by the time variable (R

2 value 0.79) during the study period. One of the major factors behind this

spectacular increase in the production of mangoes is the Government’s policy to set up Agri Export Zones for mangoes in major mango producing states. These zones have helped in establishing a continuity factor and an assured supply base for export of quality mangoes.

Establishment of cooperatives in important mango growing states like Maharashtra (Maha Mango, Mangrow etc) and Andhra Pradesh (Vijaya) during the study period, also helped in boosting mango production in the country.

Over the years, productivity of mango was noticed to increase only in the states of Karnataka, Uttar Pradesh and Kerala. In rest all the states, mango productivity was declining over the years. The outcome of this decline was that productivity of mango crop in India as a whole came down by 0.14 MT every year. There are more than 1000 mango varieties existing in India. Most of these varieties are either poor yielders or alternate bearers. Adoption of improved and commercially accepted cultivars and varieties is slow among people. Several pest and diseases are affecting the mango all through the year. These all factors together are leading to low productivity of crop in India. Depleting water table is an add on to this declining productivity.

Indian mango exports to countries such as UAE, Bangladesh, UK, Nepal, Singapore and Malaysia grew in positive direction whereas Saudi Arabia, Kuwait, Bahrain and Qatar depicted a negative growth over the years in mango exports from India.

Free Trade Agreement signed by India with Bangladesh, Nepal and Malaysia led to the increase in quanta of mango demanded from India by these countries. Nepal and Bangladesh being very near to India is also one of the reasons for high Indian mango imports by these countries. UAE exhibited higher growth in its mango imports from India mainly because quality standards are not very stringent in Middle East countries and also because of increasing Indian migrant population to these countries. As far as UK is concerned, they have been preferring Indian mangoes for their premier quality since the colonial era. The same tradition has been continued over the years which led to significant growth in mango exports to this country from India. Most international trade in fresh mangoes takes place within short distances. In Asian continent, Pakistan, Thailand and Philippines are well known mango suppliers to the world and hence big competitors for India. India and Pakistan are catering to the needs of West Asian markets where Pakistan is better off with a world ranking of 7 whereas India ranks 13

th in mango exports (source: APEDA). Diversification of trade in

mangoes by these competing markets might have led to negative growth in mango exports to Saudi Arabia, Kuwait, Bahrain and Qatar.

Divergence of Indian population throughout the world, initiatives to meet the phyto-sanitary requirements of mango importing countries so as to reach more international markets and many other related factors have led to a spectacular annual increment of 2943 MT per year in demand of Indian mangoes internationally.

6.2 Trend in behaviour of export prices of mangoes to different countries

Trend analysis revealed that price at which all the countries under study imported mangoes from India, was increasing every year with Nepal as an exception. The table 4.9 depicted that yearly hike in Indian mango export prices was maximum in case of Kuwait i.e. Rs 3092 per MT per year. Interestingly, this result is contrary to the trend of Indian mango export to Kuwait in terms of quantum as the Metric Tonnes of Indian mangoes exported to the country depicted a declining trend. Similar trend was noticed in case of Qatar which followed Kuwait in Indian mango imports.

Due to varied climate and soil, mangoes are harvested in India over a long period of time which enables the country to meet the demand of international markets for a longer duration hence aiding in fetching better prices.


Europe’s acceptance of different varieties is greater, because of a large demand from Asian immigrant groups and also because phyto-sanitary restrictions are less stringent there. UK imports of mango are concentrated during May to July which is the harvesting season for Indian mangoes. This makes UK highly competitive market. Similarly in UAE, huge Indian population resides which helps in fetching remunerative prices for Indian mangoes.

Malaysia and Thailand which are potential mango exporters and are geographically located very close to Singapore making Singapore moderately competitive for Indian mangoes. Likewise Saudi Arabia, Bahrain and Qatar are non competitive and Kuwait is moderately competitive in absorption of Indian mangoes as they would be depending on Pakistan rather than India to meet there mango demand.

Exports to Bangladesh and Nepal are very high as it is convenient to export to these markets due to geographical proximity with loose or no quality control specifications for mango. But the low prices received by Indians on mango export to these markets make it non competitive.


Bangladesh and UAE both have gained and lost simultaneously from each other and retained their share to the tune of 50 and 56 per cent respectively, thus safeguarding themselves as stable markets. Nepal, which is comparatively most stable one amongst the studied markets as it has retained its share up to 58 per cent, has lost a huge quantum to no other country but Bangladesh up to 41 per cent.

UK has not gained any considerable share from any country but lost 48.5 per cent to Bangladesh and 17.2 per cent to UAE but managed to retain 34.25 per cent. Saudi Arabia lost as well as gained from other countries keeping itself moderately stable at 45.60 per cent. Other countries have lost their major share of 33 per cent to Bangladesh retaining 41 per cent.

Projections shown in the table 4.11 indicate that rise in exports in 2015-16 will be maximum in case of Bangladesh. Therefore, Bangladesh proves to be an important destination for Indian mangoes. The free trade agreements under BIMSTEC (Bay of Bengal initiative for Multi-Sectoral Technical and Economic Cooperation) and SAARC (The South Asian Association for Regional Cooperation) would be helpful in encouraging greater cooperation and trade between the countries.


In Augmented Dickey Fuller- Unit Root Test (ADF Test) it was found that Kuwait, Qatar and Bahrain markets were already stationary. Hence these three markets were removed from the data set. Rest of the markets i.e. UAE, Bangladesh, Saudi Arabia, Nepal, Singapore, Malaysia and Delhi were made stationary by taking first difference.

The vector error correction mechanism also revealed that one month previous prices of Delhi market will have an impact on Malaysia market to an extent of 18.66 per cent in opposite direction i.e. if Delhi market mango prices increase by Rs 100 in present month, the effect of this cause will be in the form of decrease in next month mango prices in Malaysia by Rs 18.66. Other than this if any change occurs in the prices of mangoes in Malaysia, it will be because of some other factors. Similarly two month lagged prices of mangoes in Delhi market would affect the present prices in Singapore up to 29.2 per cent in same direction and in UAE market to an extent of 18.2 per cent in opposite direction. As depicted in Gragner Causality Test Singapore Gragner caused Delhi, vector error correction test revealed that a change of 1 rupee in Singapore market in present month will be responsible for decreasing next month’s Delhi market mango prices by 0.51 paise.

6.6: Problems associated with mango export

Perishability of mango fruit was found to be the major problem because if the fruit is not dispatched timely it leads to huge losses since mango importing countries are very particular about quality. Next important constraints observed were high packing cost, followed by high cost of transportation and absence of refrigerated trucks. Exporters in the study also expressed problems like lack of storage facilities, lack of consistency in quality, absence of suitable export varieties, lack of knowledge on export varieties and lack of knowledge on market information.

Policy Implications In view of the limitation of the study i.e. unavailability of export data with respect to

mango varieties, following policy suggestions have been proposed.

1. The trend analysis and compound annual growth rate revealed that productivity of Indian mangoes is declining over the years. High density planting should be promoted in mango producing areas. Similarly old orchards with low producing trees can be replaced with high yielding varieties (eg. Alphonso) which have high market demand both domestically as well as internationally in order to increase productivity.

2. SPS specifications differ from country to country. So in order to prepare consignments to different countries there is need to build the capacity of exporters with SPS specifications for every country to which mango is exported.

3. In order to export quality mangoes and optimize export earnings, quality control labs can be established and quality assessment may be made mandatory in order to cope up with improvement in exports.

4. Post harvest losses in mangoes due to mishandling amount to a large proportion (approximately 20 %), leading to the rejection of the export lots as they suffer quality specifications. To prevent this, one of the impediments is the non availability of refrigerated transport means and storage at export points in sufficient quantities. The government can think of providing such facilities to boost quality export of mangoes.

5. The Markov chain analysis indicated that Bangladesh, UAE and Nepal are the most loyal destinations for export of Indian mangoes. The trade relationship can be further strengthened by bringing improvement in quality and providing better facilities for export.

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EXPORT PERFORMANCE OF INDIAN MANGOES

– AN ECONOMETRIC ANALYSIS

POOJA TRIVEDI 2012 DR. A. D. NAIK

MAJOR ADVISOR

ABSTRACT

India occupies top position among mango growing countries of world and produces 52 per cent of the total world mango production. India exports mango to over 50 countries world wide. Even after having innumerable domestic advantages, India ranks thirteenth in mango export with a meager share of 1.51 per cent.

The primary data was collected through mailed questionnaire method and secondary data from APEDA, various published journals, periodicals and websites. Area, production and export of Indian mangoes had a positive trend but productivity grew negatively. Trend analysis revealed that price at which all the countries under study imported mangoes from India, was increasing every year with Nepal as an exception. Export competitiveness of Indian mangoes revealed that UAE and UK were highly competitive markets, Saudi Arabia, Bahrain and Qatar were non-competitive and Kuwait moderately competitive. Transitional Probability Matrix showed that Nepal was a stable market retaining its share up to 58 per cent followed by UK, Saudi Arabia and UAE each retaining 48.5, 45.6 and 34.25 per cent respectively. Projections indicate that rise in exports in 2015-16 will be maximum in case of Bangladesh. Co-integration technique revealed that one month previous pries of Delhi market will have an impact on Malaysia market to an extent of 18.66 per cent in opposite direction. Two month lagged prices of mangoes in Delhi market would affect the present prices in Singapore upto 29.2 per cent in same direction and in UAE market to an extent of 18.2 per cent in opposite direction. As depicted in Gragner Causality Test, Singapore Gragner caused Delhi, vector error correction test revealed that a change of 1 rupee in Singapore market in present month will be responsible for decreasing next month’s Delhi market mango prices by 0.51 paise.

EXPORT PERFORMANCE OF INDIAN MANGOES – AN …€¦ · Mango peel and pulp contain other...

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Transcript of EXPORT PERFORMANCE OF INDIAN MANGOES – AN …€¦ · Mango peel and pulp contain other...