TRENDS IN PRODUCTION AND TRADE

OF

MAJOR CROP PRODUCTS IN FIJI

by

Premila Sadhni Naicker

A thesis

submitted for partial fulfilment of the requirements for the

Degree of Master of Agriculture in Agricultural Economics

Copyright©2012 by Premila Sadhni Naicker

School of Agriculture and Food Technology

Faculty of Business and Economics

The University of the South Pacific

Alafua Campus,

Apia, Samoa.

December 2012

iii

DEDICATION

This work is dedicated to my husband who had inspired me the most throughout the journey.

iv

ACKNOWLEDGEMENTS

First of all I would like to thank Almighty God for being with me during the completion of this work.

Heartfelt thanks to my children and family for their unwavering support and encouragement during the course of this research.

I am grateful to my thesis supervisors, Dr Sonny Lameta (School of Agriculture) and Dr Jagdish Bhati (School of Economics), for their professional guidance and support throughout this study.

Finally, the financial assistance given to me by the University of the South Pacific in the preparation of this thesis is thankfully acknowledged.

Premila Sadhni Naicker

v

ABSTRACT

Agriculture and its allied activities sustain bulk of rural population in developing

countries such as Fiji. Development of agricultural sector not only helps in alleviation

of rural poverty but also supports sustained economic growth in the country through its

forward and backward linkages with other sectors of the economy. But, the growth of

agricultural sector in Fiji has been very sluggish. For designing effective development

strategies a thorough understanding of the country’s agricultural situation, especially

about the strengths and weaknesses of the farm production and trading systems is very

essential. Keeping this research gap in view and the importance of evidence-based

agricultural development planning, the present study was undertaken to analyse trends in

production and export of major crop products of Fiji and to identify the constraints faced

by farmers in moving forward. Knowledge of root causes of the tardy growth in

production and trade of agricultural commodities helps in finding solutions for

acceleration of agricultural development in the country.

The study analysed time-series data for the period 1991 to 2010 for sugarcane, coconut,

taro, papaya and ginger crops. Linear trend equations and growth rates were estimated

for area, yield, production and export of each of the crops under study. National level

data about the crops were obtained from the government sources. Data about the

constraints faced in production and trading of crop products were obtained by a sample

survey of farmers and exporters.

vi

The study revealed that during 1991-2010 in Fiji, the area, yield and production of

sugarcane crop were decreasing continuously at significant rates. Consequently, the

quantity of sugar exported from the country was also declining over time. This

decreasing trend in sugarcane production was due to decline in area as well as yield rate

of this crop. As most of the area under sugarcane crop was under lease from Mataqali

(the Fijian clans), due to expiry of old land leases from 1997 onward there has been

exodus of a large number of sugarcane tenant farmers and their families into informal

settlements in the periphery of urban centres in the country or abroad. Yield per hectare

was declining because in sugarcane farming, an intensive mono-cropping system was

practised on the same piece of land continuously for the past 3-4 generations without

crop rotation. This resulted in soil fertility decline on the sugarcane farming lands. Also,

frequent breakdown of sugarcane crushing mills leads to harvested cane deteriorating on

stand. The trend analysis showed that if things remain as they are the area and

production of sugarcane (and hence sugar exports) would further decline in Fiji.

As regards coconut crop, its area, production and export also had negative trends

overtime. The decline in coconut production was mainly due to the decrease in the area

of this crop. Coconut is a long term (about 40 years) income generating crop. It has

about 5 year gestation period for the farmer to start benefiting from investment in this

crop. Continuous fall in copra prices have changed mind-set of the coconut farmers

forcing them to neglect replanting of coconut trees and opting for short duration

profitable crops. Furthermore, as most of the coconut farms are located in the Maritime

Provinces, cost of transportation was high as farmers have to pay a hefty sum to boat

owners for transporting their products to markets. Yield rate of coconut crop was also

declining as most of the trees are quite old.

vii

In the case of Taro crop, during 1991-2010, there were rapid and significant increases in

its area, yield and production. Growth rate of taro export was also positive and

significant. The analysis revealed that in the growth of taro production, the contribution

of yield-effect was stronger than the effect of area. This positive outcome was due to

major emphasis placed by government on increasing production of taro to meet the

growing demand for taro in the external markets. The trend analysis indicated that

production and export of taro will further increase in Fiji.

As regards papaya crop, its area, yield, production and export increased at significant

rates during the period 1991-2010.The major contribution to the overall rapid growth of

papaya production in Fiji was by the ‘interaction-effect’ of area and yield of the crop.

However, there were high fluctuations in papaya production from year to year as this

crop is very susceptible to natural disasters, especially to flooding and cyclones. Poor

drainage affects the crop causing rot. As majority of the papaya area was under native

lease, the tenant farmers were reluctant to make long-term investments in improving

drainage system on their leased-in farms. The other major factor that hindered expansion

of papaya area was low prices received by the farmers. Papaya fruit being highly

perishable farmers cannot hold their produce longer. Hence, they are price takers and the

marketing middleman (buyer) determines the price.

The situation of ginger crop was a little different. Its area, yield, production and the

quantity exported was decreasing significantly. Main cause for decline in ginger

production and export was high cost of production. Ginger crop production requires

higher level of skills starting from sowing till harvesting. Continuous increases in the

prices of agro-inputs (e.g., fertilizer, chemicals, and planting material) and high

transportation costs decreased farmers’ profit margin forcing them to shift to other, low

viii

input crops. To boost production of this spice crop in Fiji, it is essential to provide

farmers with proper incentives and to develop agricultural marketing infrastructure in

the rural areas of the country.

The study concludes that despite negative growth rates in sugarcane area and production

and exports of sugar, this crop will remain lifeline of the Fiji’s rural economy.

Therefore, it is essential to give due attention to the problems of this crop. Similarly,

coconut crop is a strong source of income for the people in the outer islands, its

importance in rural household income and food security should not be undermined in the

agricultural development planning of the country.

Taro and papaya are the cash crops produced for export and domestic markets. Area and

production of these crops have been increasing steadily which should be further

strengthened. Ginger is also a high value crop and the agro-climatic conditions of Fiji

are quite suitable for its production. Government should support farmers in expansion of

ginger area and production.

As a long term strategy to raise production and exports of farm products, it is suggested

that farming areas lying unused after expiry of the land leases should be fully utilised.

Secondly, to augment yield rates of crops, new sustainable farm technologies should be

evolved by enhancing research and extension efforts in the country so that higher

outputs could be obtained from the available land resources.

ix

ABBREVIATIONS

WTO World Trade Organisation

GDP Gross Domestic Product

ARIMA Autoregressive Integrated Moving Average

FAO Food and Agricultural Organisation of the United Nations

FSC Fiji Sugar Corporation

FIBOS Fiji Islands Bureau of Statistics

MPI Ministry of Primary Industries

ROI Rural and Outer Island Project

EPP Export Promotion Programs

ISP Import Substitution Programs

CDF Commodity Development Framework

FJD Fijian Dollars

CIDA Coconut Industry Development Authority

ACRP Accelerated Cane Replanting Program

CRP Cane Replanting Program

NLTB Native Land Trust Board

ALTA Agricultural Landlord and Tenants Act

NDP Northern Development Project

DDA Demand Driven Approach

PICs Pacific Island Countries

LDCs Least Developed Countries

x

TABLE OF CONTENTS

Title Page #

Declaration…………………………………………………………………. ii Acknowledgements………………………………………………………… iv Abstract…………………………………………………………………….. v Abbreviations……………………………………………………………… ix List of tables………………………………………………………………. xii List of figures……………………………………………………………… xiv

Chapter 1: INTRODUCTION………………………………………….. 1 1.1 General Background................................................................................ 1 1.2 Importance of the study........................................................................... 4 1.3 Objectives of the study……………………………………………........ 7 1.4 Organisation of the thesis………………………………………………. 8 Chapter 2: REVIEW OF LITERATURE 9 2.1 Agriculture in Fiji ................................................................................ 9 2.2 Pacific Island Rural Economy………………………………………….. 11 2.3 Trends in agricultural trade and production in other countries…………. 15 Chapter 3: RESEARCH METHODOLOGY…………………………. 21 3.1 Sources of data……………………………………………………….. 21 3.2 Data analysis…………………………………………………………. 22 Chapter 4: RESULTS AND DISCUSSION………………………….. 26 4.1 Sugarcane Crop …………………………………………….. 26 4.1.1 Trend of sugarcane crop area………………………………................. 26 4.1.2 Trend of sugarcane crop yield ………………………………………. 28 4.1.3 Trend in sugarcane production……………………………………….. 30 4.1.4 Growth rates and instability of sugarcane area, yield and production . 30 4.1.5 Decomposition of changes in sugarcane production into area and yield effects ……. . . . . . . . . . . ……………………………………… 33 4.1.6 Trend on sugar exports……………………………………………….. 35 4.1.7 Growth rate and instability of sugar exports…………………………. 37 4.1.8 Constraints in production of sugarcane production………………….. 39 4.1.9 Summing up…………………………………………………………. 41

4.2 Coconut Crop . . . . . . . . . . . .. . . . . . . ……………………. 43 4.2.1 Trend of coconut crop area ………………………........................... 43 4.2.2 Trend of coconut crop yield ………………………………………… 45 4.2.3 Trend in coconut production…………………………………………. 45 4.2.4 Growth rates and instability of coconut area, yield and production … 47 4.2.5 Decomposition of changes in coconut production into area and yield effects …………………………. . . . . . . . . . . ………………… 50 4.2.6 Trend on Coconut oil exports……………………………………....... 52

xi

4.2.7 Growth rate and instability of coconut oil exports…………………… 54 4.2.8 Constraints in production of Coconut………………………………… 56 4.2.9 Summing up………………………………………………………….. 57

4.3 Taro Crop 60 4.3.1 Trend of taro crop area ……………………..................................... 60 4.3.2 Trend of taro crop yield …………………………………………… 62 4.3.3 Trend in taro production……………………………………………… 62 4.3.4 Growth rates and instability of taro crop area, yield and production .. 64 4.3.5 Decomposition of change in taro production into area and yield effects . . . . . . . . . . . .. ……..………………………… 67 4.3.6 Trend on taro exports………………………………………………… 69 4.3.7 Growth rate and instability of taro exports………………………….. 71 4.3.8 Constraints in production of taro…………………………………….. 73 4.3.9 Summing up…………………………………………………………. 74

4.4 Papaya Crop 77 4.4.1 Trend of papaya crop area…………………......................................... 77 4.4.2 Trend of papaya yield………………………………………………… 79 4.4.3 Trend in papaya production…………………………………………... 79 4.4.4 Growth rates and instability of papaya area, yield and production 81 4.4.5 Decomposition of change in papaya production into area and yield effects . ……..……………………………………………….. 84 4.4.6 Trend on papaya exports…………………………………………........ 87 4.4.7 Growth rate and instability of papaya exports………………………... 87 4.4.8 Constraints in production of papaya………………………………….. 91 4.4.9 Summing up………………………………………………………….. 92

4.5 Ginger Crop 95 4.5.1 Trend of ginger crop area……………………...................................... 95 4.5.2 Trend of ginger crop yield ………………………………………… 97 4.5.3 Trend in ginger production…………………………………………... 97 4.5.4 Growth rates and instability of ginger area, yield and production …. 99 4.5.5 Decomposition of change in ginger production into area and yield effects ……..…………………………………………………… 102 4.5.6 Trend on ginger exports…………………………………………….... 104 4.5.7 Growth rate and instability of ginger exports………………………… 105 4.5.8 Constraints in production of ginger………………………………….. 109 4.5.9 Summing up………………………………………………………….. 109 Chapter 5- Summary, Conclusions and Recommendations 112 5.1 Summary……………………………………………………………… 112 5.2 Conclusions…………………………………………………………… 115 5.3 Recommendations……………………………………………………. 117

5.4 Limitations of the study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ….. 118

Bibliography ……………………………………………………………. 119-125

xii

LIST OF TABLES Table No. Title Page No 1.1.1 Basic features of Fiji’s economy…………………………………….. 2 4.1.1 Five year averages of sugarcane area, yield and production……....... 27 4.1.2 Growth rates of area, yield and production of sugarcane……………. 32 4.1.3 Instability of area, yield and production of sugarcane………………. . 32 4.1.4 Decomposition of changes in sugarcane production into area and yield effects ………………………………………..………………………. 34 4.1.5 Trend of sugar export from Fiji…………………………………………. 36 4.1.6 Growth rate of sugar export…………………………………………….. 38 4.1.7 Instability of sugar export………………………………………….……. 38 4.1.8 Regression coefficients of trend lines of area, yield, production of sugarcane and export of sugar……………………..…………………….. 42

4.2.1 Five year averages of coconut area, yield and production………………. 44 4.2.2 Growth rates of area, yield and production of coconut …………………... 49 4.2.3 Instability of area, yield and production of coconut …………….……..…. 49 4.2.4 Decomposition of changes in coconut production into area and yield effects …………………………………………. ………………….. 51 4.2.5 Trend of coconut export from Fiji ………………………………………. 53 4.2.6 Growth rate of coconut export…………………………………………... 55 4.2.7 Instability of coconut export…………………………………………….. 55 4.2.8 Regression coefficients of trend lines of area, yield, production and export of coconut ………………..…………………………………. 59 4.3.1 Five year averages of taro area, yield and production……………….…. 61 4.3.2 Growth rates area, yield and production of taro…………………….….. 66 4.3.3 Instability of area, yield and production of taro……………………....... 66 4.3.4 Decomposition of changes in taro production into area and yield effect.. 68 4.3.5 Trend of taro export from Fiji …………………………………………. 70 4.3.6 Growth rate of taro export……………………………………………… 72 4.3.7 Instability of taro export………………………………………………... 72 4.3.8 Regression coefficients trend lines of area, yield, production and export of taro………………………………………………………. 75

4.4.1 Five year averages of papaya area, yield and production……………… 78 4.4.2 Growth rates area, yield and production of papaya…………………….. 83 4.4.3 Instability of area, yield and production of papaya…………………….. 83 4.4.4 Contribution of area and yield effects to changes in papaya production…………………………………………………………..….. 86 4.4.5 Trend of papaya export from Fiji………………………………………. 88 4.4.6 Growth rate of papaya export…………………………………………... 90 4.4.7 Instability of papaya export…………………………………………….. 90 4.4.8 Regression coefficients trend lines of area, yield, production and export of papaya…………………………………………………... 93 4.5.1 Five year averages of ginger area, yield and production………………. 96 4.5.2 Growth rates area, yield and production of ginger…………………….. 101

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4.5.3 Instability of area, yield and production of ginger…………………….. 101 4.5.4 Decomposition of changes in ginger production of area and yield effects ………………………………….……………………………… 103 4.5.5 Trend of ginger export from Fiji……………………………………….. 106 4.5.6 Growth rate of ginger export…………………………………………… 108 4.5.7 Instability of ginger export……………………………………………... 108 4.5.8 Regression coefficients trend lines of area, yield, production and export of ginger……………………………………………………. 110

xiv

LIST OF FIGURES Figure No Title Page No. 4.1.1 Trend of area of sugarcane crop ………………………….… 27 4.1.2 Trend of sugarcane yield…………………………………… 29 4.1.3 Trend of sugarcane production……………………………... 29 4.1.4 Trend of sugar export………………………………………. 36 4.2.1 Trend of area of coconut crop……………………………… 44 4.2.2 Trend of coconut yield……………………………….……. 46 4.2.3 Trend of coconut production…………………………….… 46 4.2.4 Trend of coconut export……………………………….…… 53 4.3.1 Trend of area of taro crop…………………………………… 61 4.3.2 Trend of taro yield………………………….……………… 63 4.3.3 Trend of taro production……………………….…………… 63 4.3.4 Trend of taro export………………………………………… 70 4.4.1 Trend of area of papaya crop………………………………... 78 4.4.2 Trend of papaya yield………………………………………. 80 4.4.3 Trend of papaya production………………………………… 80 4.4.4 Trend of papaya export……………………………………... 88 4.5.1 Trend of area of ginger crop………………………………… 96 4.5.2 Trend of ginger yield……………………………………….. 98 4.5.3 Trend of ginger production…………………………………. 98 4.5.4 Trend of ginger export……………………………………… 106

CHAPTER – 1

INTRODUCTION

This introductory chapter is organised in four sections. Firstly, general background

information on the basic features of the Fiji’s economy is provided so as to clarify the

context of the study. Secondly, importance of the study is elucidated. Thirdly, the

objectives of the study are presented. Finally, the layout structure of the thesis is

explained.

1.1 General Background

Fiji, officially known as Republic of Fiji, is an island nation located in the South Pacific

Ocean. Its geographical location is between latitudes 15 to 22 degrees South and

longitudes 174 degrees East to 17 degrees West.The archipelago has about 332 small

islands with a total land area of 18,333 km2.Its two largest islands, Vitilevu and

Vanualevu, make up about 88 percent of the total land area of Fiji. As of 2007, Fiji has a

population of 837,271 persons (FIBOS 2008). The population is mainly comprised of

native Fijians (56.8 percent); Indo-Fijians (37.47 percent) and the others include Part

Europeans, Chinese and Europeans (FIBOS, 2008). Almost half the population lives in

rural areas and earns its livelihood from agriculture and allied activities (Fiji

Agriculture, 2011). The density of population is about 46 persons per square kilometer.

But most areas of the country are hilly and mountainous terrains and about 30 percent

land area is suitable for agriculture. The overall average size of farms is 6.2 hectares, but

majority (56.2 percent) of total landholdings is comprised of small farms of size less

than 2 hectares (see Table 1.1.1).

2

Table 1.1: Basic features of Fiji’s economy, 2008.

Particulars Amount

Total population (2007 census)

- Native Fijians (% of total)

- Indo-Fijians (% of total)

- Others (% of total)

837,271

56.8

37.5

5.7

Rural population (% of total) 49.3

Total land area (km2 ) 18,271

Agricultural land area (km2 ) 5,480

Arable permanent crops area (km2) 2,850

Average farm holding size (Ha) 6.2

Percent of total holdings below 2 hectares 56.2

Land area by tenure system (Percent of total):

- Land under communal tenure

- State or public land

- Freehold land

87

6

7

Gross National Income per person (2007) (USD) 3,750

Structure of the economy:

- Share of Agricultural sector in the Gross Domestic Product (%)

- Share of Industrial sector in the Gross Domestic Product (%)

- Share of Services in the Gross Domestic Product (%)

13.1

21.1

65.8

Source: Fiji Key Statistics, Fiji Islands Bureau of Statistics (FIBOS), Suva, 2009.

3

About 87 percent of the total land holdings in Fiji are under communal tenure.

The communal owners are the indigenous Fijians, who own the land collectively under

the traditional Fijian clan system. The law and traditional conventions governing the

collective ownership of land are quite complicated for an outsider (France 1969). The

protocol governing the distribution of land rent proceeds is also quite complex and

sometimes controversial.

The government owns six percent of the land and the remaining seven percent

land is regarded as freehold that can be bought and sold by individuals, where certain

restrictions exist depending on the size of the land involved in sales. The land ownership

pattern is frozen by law and native land sales are prohibited. The Indo-Fijians, who are

the descendants of the indentured laborers brought from India by the British from 1879

onwards for work in sugarcane plantations, make up around 38 percent of the

population. Historically, Indo-Fijians dominate the sugarcane farming in Fiji as about 90

percent of the sugarcane crop (which is the main export crop of Fiji) is produced by

Indo-Fijians who must lease the land from the Fijian communal system, where the

option of buying such land does not exist (Kingi & Kompas 2010). In the South Pacific

region, land tenure issues are the major hindrance to agricultural development as

insecure land tenure creates crisis of confidence among farmers in making long term

investment in farm development (Acaqaye & Crocombe 1984; Barbour & McGregor

1998; Prasad & Kumar 2000; Prasad 2006, Prasad & Roy 2008; Rao, et al. 2008, Chand

2011; Prasad 2010; Bhati & Kumar 2011; Kumar & Bhati 2011).

Fiji’s economy is quite diverse and it depends on natural resources like plants, livestock,

marine, mineral resources and tourism (Maps of World, 2011). Sugarcane is the main

crop of Fiji, but farmers also grow root and tuber crops, fruits, coconuts and spices.

4

Although the share of agriculture sector in the total gross domestic product of Fiji is

only 13 percent, it is the mainstay of the people and hence priority for agriculture in the

development planning of the country should not be undermined (Ward & Procter 1980;

Prasad & Ray 2008; Singh & Bhati 2009; Kumar & Bhati 2011).

Fiji’s trade is very important part of the economy of the country. Both exports and

imports have equivalent contribution. International trade has proved to be the major

component in the improvement of Fiji’s economy. In the foreign trade of Fiji, sugar

industry is the main pillar and earns much of the foreign money. The textile industry has

good results in case of internal and external trade. Travel and tourism are also part of the

whole trade fetching high profits (Maps of World, 2011). Agricultural production and

exports will be enhanced sustainably if there are incentives to farmers to become

competitive, and supply of their farm products is efficiently linked to the domestic and

foreign markets (McGregor 1999; Bhati & Kumar 2011; Kumar & Bhati 2011, Singh &

Bhati 2012; Singh, Umar & Bhati 2012). Fiji joined the World Trade Organisation

(WTO) in 1996 (Kalouniviti, 2012). Fiji's major trading partners are Australia, New

Zealand, United Kingdom, United States and other Pacific Islands (Encyclopaedia of

Nations, 2012).The three major aspects of Fiji’s foreign trade are: Bilateral Trade

Agreement, Regional Trade Agreement and Multilateral Trade Agreement (Fiji

Government Online, 2009).

1.2 Importance of the Study

Poverty is the outstanding characteristic of traditional agriculture. The causes of poverty

are resource constraints and technological stagnation (Ghatak & Ingersent, 1984;

Stevens & Jabra 1988). Sustainable growth of agricultural sector is important for the

5

economic development of small island countries such as Fiji, where bulk of population

earns its living from agriculture and allied activities. Transformation of traditional

agriculture system not only helps in improving farmers’ income, but also helps in rapid

growth of the economy as a whole due to its forward and backward linkages with other

sectors. Agricultural sector in LDCs is potentially capable of making four types of

contributions to overall national economic growth and development (Kuznets 1964;

Johnston & Mellor 1961; Myint 1975; Ghatak & Ingersent, 1984; Stevens & Jabra

1988): (i) Product contribution – providing food and raw materials; (ii) Market

contribution – it is home market for the products of domestic industry, including market

for producer goods as well as consumer goods; (iii) Factor contribution – source of

capital for investment elsewhere in the economy and transfer of surplus labour from

agriculture to non-agricultural occupations; and (iv) Foreign exchange contribution –

augmenting export earnings of the country. Hence, a productive and fast growing

agricultural sector not only helps alleviate rural poverty but also broadens the domestic

market to absorb output of other sectors of the country. In other words, strengthening of

agricultural production and trade in developing countries such as Fiji would provide

both the basis and the means for a broader and more rapid growth of economy.

The critical importance of agricultural growth for rapid national economic development

is often not well understood. Government development plans in LDCs often assume that

increases in agricultural production would be forthcoming without much government

policy attention and without much additional investment. Therefore, low priority is

given to agricultural sector in the industry-first strategies, which often leads to serious

food shortages (Ghatak & Ingersent, 1984; Stevens & Jabara, 1988; Singh & Bhati,

2009). With the increase in population and urbanisation in Fiji there is a further demand

for crop products and trading. To meet the growing demand for food, it is also essential

6

to increase agriculture production. In developing countries the creation and sustained

increase of marketable surplus of agricultural products is a precondition of sectoral

diversification and hence of development itself (Ghatak & Ingersent, 1984).

Various studies have analysed the trends and changes that are taking place in the Fijian

economy and have also recommended solutions for tackling various developmental

problems (cf. Ward & Proctor, 1980, Chand 2007; Duncan 2007; Prasad & Narayan

2008; Prasad & Roy 2008; Mahadevan 2009; Prasad 2010). While foresight of

upcoming economic challenges is crucial for developmental planning and risk

mitigation, equally crucial is remembering agricultural history of the country. Detailed

studies on the agricultural economy of Fiji and the considerations of the diversity of

farmers’ aspirations and economic incentives in agriculture are scarce.

Improvements in agricultural production and commercialization are influenced by the

institutions and policies that the government implements to change the social and

economic context within which the production, consumption and trade of agricultural

products takes place. Constraints are imposed on agricultural development by defects in

the institutions controlling the distribution of land, access to agricultural credit and

capital, and the competitive structure of agricultural markets (Acqaye & Crocombe

1984; Ghatak & Ingersent, 1984; Stevens & Jabara, 1988; Prasad 2006; Rao, et al.,

2008; Prasad & Kumar, 2000; Singh & Bhati, 2012). Achieving a broad based

agricultural development is a very challenging task for the policy planners. Agricultural

development policies and supporting institutions would be efficient and effective only if

these are based on in-depth analysis and understanding of the agricultural situation of

7

the country, especially about the strengths and weaknesses of the farm production and

trading systems. It is also important to know the root causes behind the changes taking

place in the production and trade of agricultural commodities in the country so that

appropriate development programmes could be undertaken to ameliorate the adverse

trends.

Hence, this study has been undertaken to provide insight about the trends in area, yield,

production and export of major crop products of Fiji. It is hoped the study would be

useful in endeavours designing policies for integrated balanced development of

agricultural sector in Fiji.

1.3 Objectives of the Study

The present study assesses trends in area, production and trade of five major export

crops of Fiji. The crops selected for the study were: (i) sugarcane (Saccharum

officinarum), (ii) coconut (Cocos nucifera), (iii) Taro (Colocasia esculenta), (iv) papaya

(Carica papaya) and (v) ginger (Zingiber officinale). Specific objectives of the study

were:

1. To analyse trends in area, yield and production of five major export crops of

Fiji;

2. To study trends in exports of major crop products in Fiji

3. To analyze sensitivities of area, yield, production and exports of major crops in

Fiji and decompose the observed changes in their production into area and yield

effects; and

4. To highlight constraints faced by farmers in the production and export of crop

products in Fiji.

8

1.4 Organisation of the Thesis

The thesis is organised in five chapters. Chapter 1 provides introduction of the study. It

has four sections. Firstly, background information and basic features of Fiji’s economy

are presented to clarify the context of the study. Secondly, importance of the study is

elaborated. Thirdly, objectives of the study are explained. Lastly, layout arrangement of

thesis is given. In Chapter 2, a review of selected literature on trends in agricultural

production and trade in the South Pacific island countries and in other countries is

presented. In Chapter 3, the research methodology of the study is described. In Chapter

4, results of the study are discussed. To provide a coherent and integrated discussion of

production and trade of crop products, this chapter is divided into five sub-sections, each

dealing with one of the five major crops under study—sugarcane, coconut, taro, papaya

and ginger. Finally, in the last chapter, summary, conclusions and recommendations of

the study are presented.

9

CHAPTER – 2

REVIEW OF LITERATURE

The literature review presented here focuses on trends of crops production and trade in

agricultural dominated countries. Review is organised in five sub-headings:(i)

Agriculture in Fiji; (ii) Pacific Islands rural economy - crop production, trade and

constraints; and (iii) Trends in agricultural production and trade in other countries.

2.1 Agriculture in Fiji

Reserve Bank of Fiji’s quarterly review 2009 highlighted the decline in the agriculture’s

share of GDP from 15.3 percent to 11.3 percent over the period of 1995-2007. The data

indicated that the non-sugar crops and livestock sectors contributed an average of 13.7

percent of total agricultural exports.

Sugarcane was Fiji’s major agricultural industry. It comprised of one-third of Fiji’s

industrial activity. In the past, sugar was driving Fiji’s economy but it did not effectively

compete in globalised markets. Fiji sugar industry had drawbacks due to quality

concerns, poor administration, expiring land leases and pricing problems (Bureau of

Public Affairs, 2010). Majority of the sugarcane farms are owned by the Indigenous

Fijians. However, bulk of the sugarcane that is produced in these areas is by the Indo-

Fijians who are cultivating on lease. The largest export market for Fiji sugar is the

European Union (Fiji Agriculture, 2011).

Coconut is a commodity mainly cultivated in the Northern part of Fiji for export and

local purposes. Fiji also grows root crops, fruits and vegetables. Coconut had always

played a major role in terms of coconut oil, copra and refreshing drink in the subsistence

10

economy. About 4,000 tonnes of coconut had been exported annually (McGregor,

2007).

Taro, kava and ginger had been the major crops exported although horticultural products

(particularly papaya, vegetables and chillies) had been rapid growing components of

agricultural exports. Papaya production had accelerated in terms of area of production

and established significant export markets. Ever since clearance for export to New

Zealand in 1996 and Australia in 2002, papaya sales to these countries had developed

fast amounting to 1000 tonnes per year (McGregor, 2007). Papaya is highly consumed

in Fiji by both local consumers and tourists. The subsistence and commercial level of

production had both improved. The Fiji Department of Agriculture 2008 Report had

estimated sales of papaya in the local market to $F7.3 million in 2007.

Taro is one of the major non-sugar export commodities for Fiji. According to the Fiji

Department of Agriculture (2008), about 900 farmers had been cultivating Tausala

variety for export in 2007. During the 2007 to 2009 average export value of taro had

been $F22 million (Fiji Islands Business, 2010).

The 2007 Annual Report of the Ministry of Primary Industries noted that the area of

production for ginger had reduced by one-third due to withdrawal by the Chinese

farmers and disease problems. Ginger exports had averaged from $F5.7 million between

the period of 2007-2009 (Duncan, 2010).

Fleming (2007) highlighted that the broad picture in the agricultural sector of Fiji had

been one of extensive fluctuations around declining productivity trends and he

concluded that productivity change had aroused from four sources: (i) technological

change incorporating the introduction of new products; (ii) change in technical

efficiency; (iii) change in scale efficiency and (iv) change in diversification economies.

11

2.2 Pacific island rural economy - crop production, trade and constraints

In the Pacific island countries, large numbers of people live in rural areas and they

depend heavily on agricultural activities for their livelihoods and apart from the

Polynesian countries, their population is growing quite rapidly. For this reason, and

because prospects for income growth and improvements in welfare depend so heavily

on agriculture, the productivity and performance of the agricultural sector is critical to

the food security (Reddy, 2007). Agricultural research played an important role in

agricultural and rural development innovations and policy development however; Bhati

(2005) argued that the links between agricultural research and policy had been very

weak in the South Pacific due to which the effectiveness of rural development initiatives

was being adversely affected. Fleming (2007) and Reddy (2007) in their studies had also

identified that the answers to higher productivity lied primarily in pushing out the

production frontier by research to increase yields through the implementation of higher-

yielding varieties and improved farming systems. Singh, et .al (2007) also agreed that

throughout the Pacific region there was little agriculture research and development to

improve productivity, and if it had happened the results had not been publicized well.

They concluded that it was a huge challenge on most of the Pacific island countries to

address these problems keeping in mind the high cost of research and limited capacity.

Research is the basis for progress and meeting the challenges that modern agriculture

faces, as it adapts to the changes thrown at it by the economic, environmental and social

environments. Research provides evidence-based information for policy making. The

impact of research on economic development and livelihoods of people would have been

higher if there had been strong links between research and policy (Bhati, 2005). Fleming

(2007) also stressed that a lot of emphasis was placed on tree and root crops in terms of

12

research whereas very little had been done on developing higher yielding and better

adapting varieties.

Fleming (2007) and Reddy (2007) had pointed out that greater level of productivity

could have been also be obtained by addressing the constraints on the supply response

for instance more secure access to land, economies of scale, and improved education,

infrastructure, and access to credit. Satish Chand in an interview stated that the

challenges of development were much larger than geography and one of the things that

could not be changed was geography. Low lying islands had more problems of climate

change while high lands face difficulty with transportation and access ( MacDonald,

2010).

McGregor (2007) made a very important recommendation for a region-wide effort to

overcome these barriers. This effort was to comprise market evaluations to identify the

best opportunities for agricultural exports, scientific input to develop the necessary steps

for overcoming the quarantine barriers, and assistance in the negotiations with potential

importing countries for the entry of Pacific island country products.

Bammann (2007) highlighted that for efficient application of value chain concept, there

was a need for unrestricted interaction among government agencies, non-governmental

agencies and private agribusinesses, and all should have had a common aim of

increasing income and employment through enhanced farming and potential research

priorities. Public–private partnerships in research and dissemination could improve the

technologies available to small-scale producers and processors, while capacity building

could have helped farmers meet new quality and safety requirements. He suggested that

for the Pacific island region, processed food products based on readily common staple

13

food crops could be used for agribusiness ventures even in remote areas. They had the

prospective to substitute for food imports and improve national food security and more

prominence given to formation of agribusiness in rural areas. Government support in

terms of improvement of rural infrastructure, transportation, communication, market

access would have avoided the rural urban drift and ultimately increased production and

exports.

Rogers (2010) reported that in PICs agriculture sector was essential for livelihoods and

for ensuring food security in the face of economic and weather related shocks,

globalised trade, high energy costs, labour migration and climate change. He also stated

that there was a need for thorough understanding of the involvement of agriculture in the

economy of Pacific island countries could help in policy formulation. It would

strengthen the basis for effective decision making and induce better recognition of

agriculture’s fundamental role in maintaining an economic base, social protection, food

security and resilience in the face of economic and weather related shocks.

Reddy (n.d.), in his paper on Competition and Competitiveness of Pacific Small States

emphasized that for effective implementation of policies or policy amendments, farmers

needed to actively participate and invest through intellectuality, physical, and monetary

means. He further emphasized that development agencies had a vital role to play by

investing in need based research and facilitating the technical aspects of farming as gaps

had been seen in the implementation stages of the policies leading to failure of reforms.

He further argued that unless the PICs developed and adopted a Competition Policy the

PICs would face great difficulty in advancing a competitive economy capable of

harnessing growth from a highly competitive and rapidly changing global economy.

14

Chand (2011) argued that as majority of the land in Pacific Islands remained under

customary tenure, land reforms were important means to improve the welfare of the

population as a whole and this had the capacity to assist landowners, investors, national

government and other stakeholders. He also pointed out that these reforms had proved

extremely difficult to introduce. He concluded that land tenure reforms could confirm

security for the investor increasing scope of investments in farms and consequently

raising productivity and household income and thereby lowering the proportion of

people living in poverty.

Prasad (2006) noted that a permanent solution to land problems would have a positive

impact on investment and agricultural productivity and indirectly on the whole

economy. The study suggested that the state should lease all agricultural land from the

Native Land Trust Board (NLTB) and then sub-lease it to the tenants to smoothen the

land lease process which would well satisfy both the tenants and land owners. It was

pointed out that sugarcane farming had driven the development agenda for Fiji for 125

years. Sugar production was the only key export in the economy. But, sugar industry in

Fiji was failing due to the following reasons: inappropriate investment in the sugar mills,

transportation, research, poor allocation of resources and profits derived as a result of

the sugar exports to undertake reforms. It was further pointed out that Fiji’s economic

performance in the last 5 years, since the coup in 2000 had been relatively low and its

export performance had been weak.

Fleming and Blowes (2003) assessed commodity export performance in ten South

Pacific countries (Cook Islands, Fiji, Kiribati, Niue, Papua New Guinea, Samoa,

Solomon Islands, Tonga, Tuvalu and Vanuatu) over four decades (1960-1999). Their

study showed that a trend had been formed by the South Pacific countries to direct their

15

production towards greater international competition in current and future markets.

Production process had been catalysed to add value to the export chain. Results from the

study revealed that only three countries (Fiji, Papua New Guinea and Solomon Islands)

experienced a noteworthy positive trend in total commodity exports. The remaining six

countries had a downward trend while Tuvalu was inconsequential. They pointed out

that six factors exerted significant influences on the comparative advantage and export

performance in the South Pacific countries: (i) geographical factors, (ii) build-up of

physical and human capital, (iii) changes in relative popularity of primary and

manufactured exports, (iv) the policy direction of governments, (v) governance issues

and (vi) export market access (Fleming and Blowes, 2003).

2.3. Trends in Agricultural Trade and Production in Other Countries

Salami, Kamara, and Brixiova (2010) found that in East Africa, to improve production

on smallholder farms concerted efforts of all stakeholders, including Government,

NGO’S and development practitioners was needed to remove the existing bottlenecks to

increase production and growth. Performance of agriculture (including small holders)

had declined. The region’s rapid growth during the period of 2005-2008 has remained

limited. The agriculture sector had failed to provide basis for development despite the

series of reform attempts undertaken.

Another case study conducted by Chigwada and Mudzonga (2009) on Zimbabwe’s food

security found that food production had reached below subsistence level since 2000.

According to this study, foreign direct investments had been limited between 1998 and

2002. This led to upward trend in food imports since 2005. The study highlighted that

the country needed to concentrate on local production, improve post–harvest capacity

through improvements to infrastructure and food storage facilities and needed to

16

continue negotiating for a positive outcome of the Doha Development Agenda on

agricultural exports that would assist the development of agriculture.

Tarimo’s (1998) study on sugarcane production processing and marketing in Tanzania,

reported declining trends in sugarcane production during mid 1980’s. The annual

production figures stated an increase during early 1990’s due to favourable economic

situation in the country after trade liberalization. The prices of agricultural commodities

including sugar experienced noticeable increase. This encouraged farmers to enter into

“contract grower” system adopted by sugar factories because of better cane prices.

A research study conducted on trends in Zambian agriculture sector by the Department

for International Development Group (2002) found that, between the periods of 1990-

2000, agricultural growth had been 4.5 percent. However, there had been annual

fluctuations in productivity as much as 30 percent due to rainfall. Rains fed crops were

extremely vulnerable to these fluctuations. Small scale farms had an added advantage of

diversifying into more marketable crops. Trends indicated increase in more profitable

drought resistant crops as sorghum, cassava, millet and tubers as they required less

chemical and fertilizer inputs. There was an increase of 20 -50 percent in cassava,

ground nuts and millets in the past decade. Remarkable trends in terms of production

and potential economic growth was experienced from the commercial sector with

relevance to sugarcane wheat and cotton. The constraints affecting rural poor

highlighted in the study were; distance from the market, high input cost, poor market

opportunity and services.

17

A time series trend analysis conducted by Gitu (2004) on agricultural development and

food security in Kenya found that there was strong linear relationship between

agriculture and the whole economy development. The study concluded that agricultural

performance was negative for the period 1994 to 2000. However, mixed trends were

seen in various commodities. This occurred due to area expansion or contraction,

climate, technological, price changes and policy related issues.

A study conducted by Australian Productivity Commission found that in Australia,

agriculture sector production increased by two and a half times from $10 billion in 1963-

64 to $27 billion in 2003-2004. The output declined by one-fifth in droughts of early-

eighties and mid-nineties. The harshest recorded drought had been in 2002-2003 with

real output growth (in trend terms) of 2.4 percent per year. Overall agricultural output

declined by 6.7 percent in the first three quarters of 2004-2005. The major reasons stated

for the decline in agriculture were; shifts in consumer demand as income rises, changes

in relative price of goods and services and technological change. The trends in

agricultural trade showed that export values were largely driven by trends in agricultural

output. The long run decline in agricultural export had been due to accelerated growth in

other industries. In 1969-70 wool cereals and wheat were the major export commodities.

By 2003-2004 their combined share declined to half. Within this period other processed

foods such as dairy products, tinned and frozen foods, animal feed, wood chips and

other edible products increased from 16-39 percent (Trends in Australian Agriculture,

2009).

A study (Mangabat 1998) on the effects of trade liberalization on agriculture in the

Philippines showed that during 1980-1997, the value of combined exports and imports

on average had a yearly growth of 9 percent. A negative growth in total trade in early

18

1980’s led to a slow economy. The impact of devaluation reduced imports and increased

exports in 1984 but it was not maintained from 1984-1986. On average, the total trade

and value of exports was 40 percent. In early 1980s agriculture exports which included

processed agricultural products (e.g. coconut oil and pineapple juice) accounted for one-

third of total export values. This share dropped to 9 percent in 1997.The share of

agricultural imports declined from 11 percent in 1980’s to 9 percent in 1997. The Tariff

Reform Program and Import Liberalization Program led to increased trade in 1998 but

gradually dropped by 1994. A consistent pattern was seen from 1995-1997 (Mangabat,

1998).

Rosario (2009) analysed trend of agriculture and food trade in Alberta (Canada). His

findings depicted that exports of agriculture and food products from Alberta had

declined since 2000 as compared to 1980s and 1990s. The study found that there was an

increase of about 82 percent during 2001/2002 to 2006/2007 period. This marked

increase was due to value added agricultural products, food safety and quality, new

attributes such as environmentally friendly production methods, organic health and

nutrition considerations, foreign direct investments, trade policy and market

developments.

A study in Vietnam by Thanh &Singh (2006) analysing trends in rice production and

exports during 1965-2004 (40 years period) found that overall compound growth rate

was positive. The growth in rice production was more explained by yield-effect than

area-effect. It concluded that since increase in area was difficult as it is a limiting factor,

there was a need to increase rice yields by application of high yielding and quality

varieties with appropriate production technologies.

Abang and Ndfion (2002) analysed world cocoa production trends and their production

share coefficients (1975-1996) using a linear regression function. Their results revealed

19

that on average world cocoa production had been on increase due to expansion by large

producers, new entrants as well as reasonably smaller ones.

A study by Hafner in 2003 on trends in maize, rice and wheat yields for 188 nations over

the past 40 years, revealed that linear growth yields had been the most common trend

ultimately in more than half of all the nation crop data sets. To compute these past trends

linear models were used.

Okun, et al. (2011) studied China’s agricultural trade and noted there were gradual shifts

in the composition of agricultural production and trade. There had been long term

concentration on production of staple foods, such as grains and tubers, but there was a

move towards increased production of non-staple foods, such as fruits and vegetables.

In 1980, grains accounted for 80 percent of total sown area while vegetables made up 2

percent and orchards 1 percent. By 2008 grains sowed decreased to 68 percent,

vegetables increased to 11 percent and orchards increased to 7 percent. They argued that

this trend was because of changing consumer demand as a result of rising income,

urbanization, increasing returns available to farmers from producing non-staple food

products. During the period 2005-2010, there was an increase in horticultural

production, especially fresh and processed fruits which experienced double digit annual

growth

A report based on the FAO (1999) symposium on global trends of agricultural

production and trade noted that agricultural production had been increasing gradually

outstripping world population growth by widening the scope since 1960’s. However,

world agricultural growth for all products had actually been declining from 3 percent per

annum in 1960’s to 2 percent per annum in mid 1990s and further decreased to 1.34

percent in 1995 to 2000. From 1970s the quantity of agricultural trade had improved by

75 percent. About 25 percent of the developing countries’ contribution of agricultural

20

exports had exceeded to two-thirds of total exports in mid 1990s (FAO, 1999). There

had been a structural move in trade from mass commodities to value added products as a

result of increasing income.

21

CHAPTER – 3

RESEARCH METHODOLOGY

This study analyses trends in area, yield, production and export of five major crop

products of Fiji for the period 1991-2010. In this chapter, the sources of data and the

techniques of data analysis used in the study are discussed. Time-series data regarding

five crops under study were examined on four aspects: trend lines of area, yield,

production and export during last two decades, growth rates, instability analysis, and

decomposition of the contributions of area and yield effects in the changes in the

production of the crop.

3.1 Sources of Data

3.1.1 Area, yields, production and export

Data on area, yields, production and trade of five crop products for the period 1991-2010

were obtained from the published and unpublished records of the Ministry of Primary

Industries (MPI), Annual Reports of the Fiji Sugar Corporation (FSC), Fiji Bureau of

Statistics, FAO Production Year books of different years, and the Bio-Security

Authority of Fiji.

3.1.2 Method of selection of sample size of farmers and other stakeholders

Data on production and export constraints of the five selected agricultural commodities

in Fiji were collected through personal interview with progressive farmers, food

processors, exporters and traders. With the assistance of Ministry of Agriculture

Extension Officers a sample of ten progressive farmers of each crop was purposively

selected based on their previous cultivation and production performance. A structured

questionnaire was used to collect the required data. The Food Processors is the oldest

22

and the only commercially-oriented food processing company in Fiji. Its manager was

interviewed regarding the constraints faced by them in marketing products.

3.2. Data Analysis

The data analysis techniques used in the study are: time series trend analysis, growth

rate analysis, instability analysis and decomposition analysis of change in production of

crops. Each of these is described below.

3.2.1 Time series trend analysis

Trends are the drifts in data over long periods of time. Gradual changes in the variable

data over a long period of time and cause clear increase or decrease in it that may not be

detected in a year to year analysis (Goodwin, 1994). Trend analysis uses time variable as

a surrogate for capturing the effect of changes in other variables that either cannot be

measured or in groups of variables that change so gradually that collecting the

information isn’t worth the effort (Tomek & Kenneth, 2003). Land use has been

commonly studied and understanding is gained through recognized changes in land

cover or land use patterns (Aspinall, 2004).

Trends of time-series data for the period from 1991 to 2010 on area, production, yield

and exports of each of five major crops (sugarcane, coconut, taro, papaya and ginger)

were analysed. Following linear trend line equation was fitted by regression technique

for area, yield, production and export of each crop separately:

Yt = a + bXt

Where,

Y = dependent variable (which may denote area, yield, production, export of a

crop product under study);

Yt= value of the dependent variable (Y) in year t;

23

Xt = value of independent variable (in this case time) in year t (starting as t =1, 2,

… n) (i.e. starting with 1991 = 1 in this study);

a = constant coefficient, i.e. value of Y-axis intercept of the computed trend line

(value of the Y variable when X = 1); and

b= coefficient of slope of regression line/trend line (i.e. rate of change in Y for a

given change in X).

The trend analysis not only depicts the past behaviour pattern of the dependent variable,

but also provides forecast about its future prospects.

3.2.2 Growth rate analysis

The time-series data of each crop for the period from 1991 to 2010 was further divided

into four sub-periods each of five years: (i) 1991-1995; (ii) 1996-2000; (iii) 2001-2005;

and (iv) 2006-2010. To compute compound annual growth rates for each period, the

following formulae (Weil, 2009) was used:

g = [(Yt+n / Yt )1/n] – 1

Where,

g = Compound average rate of growth;

Y = Variable whose growth rate is estimate. Here it may denote crop area, yield,

production or export;

Yt = Value of Y in the year 1 (i.e. in the base /first year);

Yt+n = value of Y in the last year (i.e. after n years);

t = first (base) year; and

n = number of years Y grows at rate g.

24

The trend analysis for the 20 years period from 1991 to 2010 was analysed. To compare

growth rates during different macroeconomic environment of the country the total study

period of twenty years was divided into four five-year sub-periods denoting: (i) The Pre-

Coup period (1991-1995); (ii) The Coup period (1996-2000); (iii) The Post-Coup period

(2001-2005), and (iv) The Assistance Withdrawal Period (2006-2010).

3.2.3 Instability analysis

The data were also analysed to find out whether in each sub-period the growth in the

area, production and export of crops was stable or unstable. Instability shows degree of

variability. Variability in the values of a parameter can be measured as the range,

standard deviation, variance or coefficient of variation. In this study, the coefficient of

variation (CV) has been used to assess the stability and instability in different variables

(area, yield, production and export) of selected crops.

The time series data on these parameters were decomposed initially by fitting the linear

regression equations for each of them, as has been used by Kumar (2000) and Siddayya

(2002).

The coefficients of variation (CV) for area, yield, production and quantity exported were

computed by the formulae given below:

CV = (Standard deviation (σ) of variable Y ÷ Mean of Y) x 100

A higher percentage of the CV indicates a higher instability in the variable during total

period and between the sub-periods. Similarly a stable coefficient of variation indicates

25

that sub-periods are relatively synchronic for all the variables (e.g., area, yield,

production or export).

3.2.4 Decomposing changes in crop production into area and yield effects

Change in crop product overtime takes place either due to change in the crop area or

crop yield or a combination of both of these two factors. Hence, the observed change in

the total productions of each crop can be decomposed into three components: (i) change

due to area-effect, (ii) change due to yield-effect, and (iii) change due to interaction

effect of area and yield.

The changes in the total productions of five major crops during the period 1991-2010

were decomposed by using the additive scheme of decomposition (Thanh & Singh,

2006) as shown below:

Change in crop output = Area effect + yield effect + Interaction effect of area and

yield

∆ P = (Y΄ ∆ A) + (A΄∆Y) + (∆ A ∆ Y)

΄

Where,

∆ P = Difference in production from the base year to last year (periods)

∆ Y= Difference in yield from base year to last year (periods)

∆ A = Difference in area from base year to last year (periods)

A΄ = Area in the base year (of each period)

Y΄ =Yield of crop during base year (of each period)

The level of contribution of each factor was denoted in percentage terms.

26

CHAPTER – 4

RESULTS AND DISCUSSION

In this chapter trends in area, yield, production and exports of five crop products are

discussed separately. Five crops studied are sugarcane, coconut, taro, papaya and ginger.

Discussion for each crop is organised in seven sub-headings: (i) trends in area, (ii) trends

in yields, (iii) trends in production, (iv) decomposition of changes in production, (v)

trends in exports, (vi) growth rates and instability, and (vii) constrains in crop production

and exports.

4.1 SUGARCANE CROP

In this section trends and growth rates in area, yield and production of sugarcane and

export of sugar are analysed. Each of these variables is examined separately.

4.1.1 Trend of sugarcane crop area

Five year averages of sugarcane area, yield and production are presented in Table 4.1.1.

Figure 4.1.1 illustrates trend in sugarcane area in Fiji. The results show declining trend of

sugarcane area in Fiji during the 20 year period (1991-2010) under study. Although

government intervention was prevalent through policy implementations in development

of sugar industry, factors such as disasters, high input costs and non-renewal of expired

land leases contributed to this situation.

During the sub-period of 1991-1995, area under sugarcane was 73,600 hectares which

decreased to 67,000 hectares in the sub-period 1996-2000. Flood and cyclone Kina in

1993 led to substantial decline of area. The area of sugarcane continued to decrease from

27

Table 4.1.1 Five-year averages of sugarcane area, yield and production in Fiji during

1991-2010

Periods

Area (ha)

Yield (tons /ha)

Production (tons)

1991-1995 73,600 51.1 3,758,200 1996-2000 67,000 52.2 3,500,400 2001-2005 65,600 44.6 2,925,600 2006-2010 51,400 46.9 2,410,000

Source: Based on data of FIBOS and MPI, last accessed August 2012.

28

65,600 hectares in the sub-period 2001-2005 to 51,400 hectares in the sub-period 2006-

2010. Continuous expiring of land leases and non-renewal of leases were the major

factors .The trend line is drawn on the data for the whole period (1991-2010).It is clear

from the Figure 4.1.1 that the area under sugarcane was declining continuously during

last two decades.

4.1.2 Trend of sugarcane crop yield

Five-year averages of sugarcane yields in Fiji are shown in table 4.1.1. The average

yield of sugarcane slightly increased from 51.06 tons per hectare in the sub-period

1991-1995 to 52.2 tons per hectare in the sub-period 1996-2000.Then, it decreased to

44.6 tons per hectare in the sub-period 2001-2005. There was a slight increase to 46.9

tons per hectare to sub-periods 2006-2010. This increase can be contributed to the

implementation of Accelerated Cane Replanting Program (ACRP). But overall there

remained a declining trend in per hectare output of sugarcane. Figure 4.1.2 shows that

sugarcane yields per hectare was continuously declining during in the past two decades.

29

30

4.1.3 Trend of sugarcane production

Five year averages of sugarcane production are shown in table 4.1.1. There was a

consistent decline of sugarcane production. From the sugarcane production of 3,758,200

tons in the sub-period 1991-1995, the production declined to 3,500,400 tons in the sub

period 1996-2000. It further declined to 2,925,600 tons in the sub-period 2001-2005 due

to political instability in the country which led to insecurity amongst the tenant farmers

and development of slight racial barriers within the two major ethnic groups in Fiji

(Indigenous Fijian land owners and the Indo-Fijian tenant farmers). This was a major

contributing factor in the non-renewal of the land leases. The sugarcane production

further declined to 2,410,000 tons in the sub-period 2006-2010.

Trend of sugarcane production is shown in Figure 4.1.3 which also reveals that there

was a continuous decline in sugarcane production in Fiji during the period 1991-2010.

4.1.4 Growth rates and instability of sugarcane crop area, yield and production

Table 4.1.2 indicates the compound growth rates (CGRS) of area, yield and production

of sugarcane in Fiji from 1991-2010. The results reveal that in the Pre-Coup Period

(1991-1995), the sugarcane area in Fiji had shown positive and significant growth rate of

0.27 percent per annum and this was significant at 1 percent level of probability. The

growth rates of both yield and production were positive and significant at 1 percent level

of probability.

The Coup Period (1996-2000) was signified by the political instability in the country

resulting in the military coup in 2000. The growth rates of area, yield and production

were all negative at 2.26, 0.63 and 2.9 percent respectively, and these were significant at

31

1 percent level of probability. In the Post-Coup Period (2001-2005), due to vigorous

efforts of government there was a significant growth in the per hectare yield of

sugarcane (2.5 percent). But, the growth rates of area and production were still

negatively significant.

In the Assistance Withdrawal Period (2006-2010), the growth rates for area, yield and

production of sugarcane were significantly negative at 4.95; 6.8 and 11.2 percent per

annum, respectively. This shows that the sugar sector was unable to make innovations in

the economy of agriculture. For the overall period of 1991-2010 the growth rates of

sugarcane area, yield and production were negative and significant at 2.3, 0.78 and 3.16

percent per annum, respectively.

Instability analysis with respect to sugarcane area, yield and production was done for the

entire period (1991-2010) based on coefficients of variations (CVs) of area, yield and

production of sugarcane. Results are presented in Table 4.1.3. The most stable CV was

in sugarcane area in the sub-period of 1991-1995 (CV=1 percent).The highest instability

was observed in the sub-period of 2001-2005 (CV = 15 percent) which was followed by

the sub-periods of 2006-2010 and 1996-2000 (CV = 10 percent each).

In case of sugarcane yield the highest stability was in the observed in the sub-periods of

1991-1995 and 2001-2005(CV=8 percent).The highest instability was observed in the

sub-period of 1996-2000 (CV= 20 percent) followed by the sub-period of 2006-2010

(CV = 12 percent).

32

Table 4.1.2: Annual growth rates of area, yield and production of sugarcane (percentages)

Periods Area Yield Production 1991-1995 0.27** 3.7** 4** 1996-2000 -2.26** -0.63** -2.9** 2001-2005 -2.55** 2.5** -0.11** 2006-2010 -4.95** -6.8** -11.2** 1991-2010 -2.3** -0.78** -3.16**

** = Statistically significant at 1 percent probability; * = Significant at 5 percent level of probability.

Table 4.1.3: Coefficients of variation (percent) of area, yield and production of sugarcane

Periods Area Yield Production 1991-1995 1 8 9 1996-2000 10 20 25 2001-2005 15 8 11 2006-2010 10 12 22 1991-2010 15 14 24

Source: Based on FIBOS and MPI, last accessed August 2012.

33

In case of sugarcane production the highest stability was observed in the sub-

period1991-1995 (CV=9 percent). For the other sub-periods 1996-2000 and 2006-2010

the CVs were 25 and 22 percent respectively. For the entire period of 1991-2010 the

instability analysis showed that the sugarcane production had higher variation (CV=24

percent) as compared to variations in sugarcane area (CV=15 percent) and sugarcane

yield (CV=14 percent).

4.1.5 Decomposition of change in sugarcane production into area and yield effects

Results of decomposition of contributions of area and yield effects to the changes in

sugarcane production in different sub-periods are presented in table 4.1.4. In the sub-

period 1991-1995, the increase in sugarcane production in Fiji was mainly contributed

by the increase in yield; the yield effect was 92.39 percent, followed by area effect of

6.34 percent. The interaction effect of these two factors was very small (1.27 percent

only). In the sub-period of 1996-2000, the production of sugarcane declined. In this

decline the area effect was major contributor (79.72 percent) followed by the yield effect

(22.7 percent). During the sub-period 2001-2005, sugarcane production further declined

drastically and in this decline the major contributor was the area effect (2125.5 percent)

i.e., decrease in area under sugarcane, followed by the interaction effect (279.31

percent). The yield effect was in the opposite direction (- 2304.31 percent). In the sub-

period of 2006-2010 sugarcane production further declined. In this contribution of yield

effect and area effect was 64.53 percent and 49.94 percent respectively.

34

Table 4.1.4: Decomposition of change in sugarcane production into area and yield effects (percentages)

Periods Area effect

Y'∆ A Yield (t/ha)

A'∆Y Interaction effect

∆ A ∆Y 1991-1995

463000 (6.34)

674459.46 (92.39)

9239.17 (1.27)

1996-2000

-473520 (79.72)

-135090.91 (22.7)

14604.42 (-2.46)

2001-2005

-340000 (2125.00)

368689.66 (-2304.31)

-44698.66 (279.31)

2006-2010

-723060 (49.94)

-934355.56 (64.53)

209424.52 (-14.46)

1991-2010

-1296400 (80.93)

-495688.89 (30.94)

190127.25 (-11.87)

Note: Area (ha), Yield (t/ha) and Production (tons).

Figure in parentheses indicate the contributions (in percentages) of area, yield and interaction effect on change in production of sugarcane.

35

Overall, during the entire period of 1991-2010, the contribution of area effect and yield

effect in the reduction of sugarcane production was 81 percent and 31 percent

respectively. The interaction effect was in the opposite direction (-11.87 percent). From

the findings it can be said that decrease in the sugarcane production in Fiji was mainly

because of decrease in sugarcane area followed by yield-effect. The interaction effect

was mostly the lowest in sub-periods as well as the entire period.

The results show declining trends of area, yield and production of sugarcane in Fiji during

the 20 year period under study. Although government intervention was prevalent through

policy implementations in development of the sugar industry, factors such as natural

disasters, high input costs and non-renewal of expired land leases contributed to this

situation.

4.1.6 Trend of sugar export.

Data in Table 4.1.5 show quantity and value of sugar exported from Fiji. Trend of sugar

export is shown by graph in Figure 4.1.4.

In the first sub-period 1991- 95, the sugar export was 2077 tons. In the sub-periods of

1996-2000, 2000-2005 and 2006-2010 the sugar exports decreased to 1702 tons, 1366

tons and 999 tons respectively. This sharp decline in export was attributed mainly to the

political instability and expiring of sugarcane land leases. Since sugar production had

decreased rapidly in Fiji, obviously, the sugar export from the country has also declined

considerably. The value of sugar export was FJ$ 240 million in 1991-95 which

decreased to FJ$174 million by 2006-2010.

36

Table 4.1.5: Trend in sugar export from Fiji, 1991-2010 (5-year averages)

Periods Sugar quantity (tons) Sugar value (FJD)

1991-1995 2077 240129200

1996-2000 1702 249402000

2001-2005 1366 218719200

2006-2010 994 174554800

Source: Based on FIBOS and MPI, last accessed August 2012.

37

4.1.7 Growth rate and instability of sugar export

Growth rates of quantity and value of sugar exports from Fiji during 1991-2010 are

presented in Table 4.1.6. This period is divided into four sub-periods. In the period of

1991-1995, the growth rate for sugar export quantity and value were positive and

significant at 4.5 and 4.6 percent per annum respectively. For the Coup period (1996-

2000), the growth rate of sugarcane exports quantity and value were negative at 9.6 and

4.9 percent per annum and significant at 1 percent level of probability. The effect of the

2000 coup is clearly seen in this period with negative growth rates. In the Post-Coup

period (2001-2005), the growth rate for export quantity was positive at 4.2 percent per

annum and though growth in value of export was negligible due decrease in

international prices of sugar. The Assistance Withdrawal Period (2006-2010) witnessed

the highest negative growth rate for quantity and value of sugar exports at 15 percent

and 18.4 percent per annum. For the entire period of 1991-2010, the annual growth rate

of quantity and value of sugar exports were negative at 5.6 and 5 percent respectively

and these figures were significant at 1 percent level of probability.

The results of instability analysis of sugar exports in Fiji are presented in Table 4.1.6.

The results show that during 1991-2010 period generally the quantities and values of

sugar export were instable (having high values of variance), except for the period of

2001-2005 with low CV of 8 percent and 4 percent respectively. The most unstable

period was the sub-period of 2006-2010 with CV of 32 and 38 percent for quantity and

value of sugar export respectively.

38

Table 4.1.6: Growth rates of sugar exports from Fiji during 1991-2010 (percent)

Periods Sugar (quantity) Value (FJD)

1991-1995 4.5** 4.6**

1996-2000 -9.6** -4.9**

2001-2005 4.2** -0.2**

2006-2010 -15.0** -18.4**

1991-2010 -5.6** -5**

Note: ** = Statistically significant at 1 percent probability; * = Statistically significant at 5 percent probability.

Table 4.1.7: Instability of sugar export from 1991 to 2010 (percent)

Periods Sugar Value

1991-1995 12 10

1996-2000 29 13

2001-2005 8 4

2006-2010 32 38

1991-2010 39 30

39

4.1.8. Constraints in production of sugarcane crop

(a) Land tenure system: Most of the area under sugarcane crop in Fiji is under lease

from Mataqali, the Fijian clans and administered by the Native Land Trust Board

NLTB). Many of these old leases are about to expire for which the tenant farmers have

no guarantee of renewal. The maximum length of new lease is 30 years and the

leaseholders complain that this uncertainty is a major constraint to investment and

hence agricultural development generally. Due to the expiry of land leases under

Agricultural Landlord and Tenants Act (ALTA) since 1997 has seen the movement of a

large number of farmers and their families abroad or into informal settlements in the

periphery of urban centres

(b) Natural disasters: Sugarcane farming in Fiji is generally practised on flood plains

and low lying areas. Cyclones and flash flooding have affected production and

cultivation of sugarcane and this has resulted into lower exports. Flooding, cyclones and

drought have had considerable level of impact on the growth and production of

sugarcane. Losses in terms of crop damage, land degradation, production and

infrastructure damages have indeed led to the fall of the sugar industry.

(c) Financial constraints (limited budget) : Due low income and high cost of

production majority of the sugarcane farmers have complained about lack of capital and

credit.

40

(d) Declining sugarcane production: Majority of the farmers interviewed mentioned

that sugarcane farming has been practised on their farm for the past 3-4 generations.

This intensive mono-cropping system on the same piece of land being continuously

cultivated with nutrient loss through sugarcane harvest and top soil erosion has led to

significant losses in terms of yield per hectare, sugarcane quality and sugar content.

(e) Poor mill performance: Frequent breakdown of sugarcane crushing mills leads to

harvested cane stand on the carts and deteriorate. This leads to weight and quality loss of

produce.

(f) Increasing cost of sugarcane production: The general running of a sugarcane farm

is expensive especially with relevance to land rent, transportation, fertilizer, land

preparation, weed control and harvesting.

(g) Brain drain: Because of expiry of sugarcane land leases, experienced tenant farmers

and their families have migrated from farming to non-farming activities. This has led a

creation of a vacuum especially with the number of expert sugarcane producers.

(h) Low sugar price from contractor compared to world market: The reform in the

European Union market or phasing out of the European Commission led to Fiji getting

low export prices for sugar. These low prices affect the revenue status of all the actors

involved in the value chain.

41

4.1.9 Summing Up

It is clear from the above discussion that, in general, the trends in area, yield and

production of sugarcane in Fiji were negative during 1991-2010. The linear regression

equations fitted to time-series data of sugarcane area, yield, production and sugar

exports are presented in table 4.1.8. Analysis shows that the b coefficients for the slope

of equations are all negative except for yield and are significantly different from zero.

This analysis reconfirms the previous discussion of this section.

There are several contributing factors for this scenario: natural disasters (cyclones,

floods), high input cost and expiring of land leases. Washing away of the Sigatoka rail

bridge disconnected Olosara sector sugarcane farmers from the Lautoka sugar mill and

thereby forcing them to venture into alternative crop farming reducing sugarcane area

and production in Fiji. Government through its rehabilitation policies has implemented

Cane Replanting Programme (CRP) and Accelerated Cane Replanting Program

(CRP).But the declining trend in area and production of sugarcane could not be arrested.

42

Table 4.1.8: Regression coefficients of linear equations (Yt = a + bXt) (trend lines) of sugarcane crop area, yield and production and sugar export in Fiji.

Dependent variable (Y)

Estimate of constant ‘a’

Estimate of coefficient ‘b’

R2

N

Area 77,243*** (1543)

- 1,457*** (139)

0.67 20

Yield 52.20*** (2.84)

- 0.322 NS (0.256)

0.001 20

Production 4,003,443*** (228,312)

- 89,989*** (20,544)

0.52 20

Export 439.6*** (26.2)

- 13.96*** (2.36)

0.66 20

Note: Figures in parenthesis denote standard errors of respective coefficients.

*** = Significant at 1percent level of probability; ** = Significant at 5percent level of probability; * = Significant at 10 percent level of probability; NS = Not significant.

43

4.2 COCONUT CROP

In this section firstly, the trends, growth rates, and instability analysis of area, yield and

production and export of coconut are discussed. Secondly, contribution of area and yield

to coconut production is analysed. Thirdly, trends in copra export are discussed. Finally,

the constraints faced by the coconut farmers are presented.

4.2.1 Trends in coconut crop area

Five year averages of area, yield and production of coconut in Fiji are presented in Table

4.2.1. Figure 4.2.1 illustrates trend of coconut area. The trend analysis for the 20 years

from 1991-2010 has been divided into four five-year sub-periods. The results in Table

4.2.1 and Figure 4.2.1 have shown reasonable level of change in area yield and

production in Fiji during the 20 year period.

The five year average of area of coconut in Fiji during the sub-period of 1991-1995 was

64,870 hectares. Despite great emphasis being placed on replanting of senile coconuts in

all divisions the area of planting did not improve, rather decreased to 58,705 hectares in

the sub-period 1996-2000.The main influence on the fall in area was low price in the

international market in 1987 that led to reduced interest of farmers in replanting.

Introduction of demo-plots for coconut hybrids which take three to five years to mature

was one of the major strategies adopted in 1995. The revival of the industry was

attempted through Commodity Development Framework (CDF) under coconut

rehabilitation program in 1997. The Coconut Industry Development Authority (CIDA)

was developed in 1998 and introduced in 2001 to assist the industry. However, long term

44

Table 4.2.1 Trends in coconut area, production and yield from 1991-2010

Periods

Area (Ha)

Yield (tons /ha)

Production (tons)

1991-1995 64870 0.2 12120.6 1996-2000 58705.2 0.3 15897.8 2001-2005 36440.4 0.4 13300.8 2006-2010 19450 0.5 10078.6

Source :Based on FIBOS and MPI, last accessed August 2012.

45

farming like coconut planting could not be revived to the expectation. The area of

production continued to decrease from 36,440 hectares in the sub-period of 2001-2005

to 19,450 hectares in the sub-period of 2006-2010. The changes in government policies

were still not able to help farmers invest more in coconut production.

4.2.2 Trends in yield of coconut crop

As can be seen in table 4.2.1 the five year average yield of copra in Fiji was 0.2 tons per

hectare in the sub-period 1991-1995 which rose to 0.3 tons per hectare in the sub-period

1996-2000. The yield of copra further increased to 0.4 tons in the sub-period 2001-2005

and reached to 0.5 tons per hectare during the sub-period 2006-2010.

4.2.3 Trend of coconut production

Copra production as shown in table 4.2.1 has been changing after each sub-period.

Figure 4.2.3 illustrates the trend of production. There was an increase in production from

12120.6 tons in the sub-period of 1991-1995 to 15897.8 tons in the sub period 1996-

2000. This is due to the effect of government policies emphasis on the replanting of

senile coconuts. However from the sub-period of 2001-2005 to 2006-2010, the

production level continued to decrease from 1300.8 tons to 10078.6 tons. The declining

trend is clear from the trend line of coconut production shown in Figure 4.2.3.

47

4.2.4 Growth rates and instability of coconut crop area, yield and production

Table 4.2.2 shows compound growth rates (CGRS) of area, yield and production of

coconuts in Fiji from 1991 to 2010. The four five-year sub-periods of Fiji mentioned in

the previous section were; (i) Pre- Coup period (1991-1995); (ii) Coup period (1996-

2000); (iii0 Post-Coup period (2001-2005) and (iv) Assistance Withdrawal period

(2006-2010) were taken into consideration.

The results shown in table 4.2.2 revealed that in the period 1991-1995 the coconut

farming in Fiji had shown insignificant growth rates in terms of area and yield. The

growth rate for production was negative at the rate of 7 percent per annum and

significant at 1 percent level of probability due to slow rate of replanting of coconuts.

In the period 1996-2000 negative growth rates of area and production were observed.

Area declined at the rate of 3.4 percent per annum and the production declined at the rate

of 8 percent per annum which were at 1 percent level of probability. The yield of

coconut was showed insignificant growth. During the period 2001-2005, growth rates of

area, yield and production were negative at 3.6 percent; 0 5.6 percent and 7.4 percent per

annum and these were negative at 1 percent level of probability. The effect of coup in

Fiji was highly reflective in this period. During the period 2006-2010 the magnitude of

negative growth rates further increase; it was -12 percent for area and -10 percent for

production of coconut.

Overall for period of 20 years (1991-2010) the CGRS of coconuts area and production

were negative at 7 and 4.1 percent per annum. However, the growth rate of yield was

positive at 3.1 percent per annum.

48

Results presented in Table 4.2.3 indicate the level of instability for the entire period

(1991-2010) based on coefficient of variations (CVs) of area, yield and production. The

results show that area, yield and productions were mostly stable as their variations were

low during different periods. However, if we take whole 20 years duration in to account

the variances of the three variables became apparent. But still their CVs were below 50

percent showing their relative stability as compared to other crops.

In case of coconut yield the highest stability, i.e. least CV, was in the observed in the

sub-period 1996-2000 (CV=14 percent). In case of coconut production the highest

stability was observed in the sub-period 2001-2005(CV=21 percent). For the entire

period of 1991-2010 the instability analysis showed that the area was more unstable than

yield and yield was more unstable than production.

49

Table 4.2.2: Compound growth rates of area, yield and production of Coconuts (percent)

Periods Area Yield (t/ha) Production(t) 1991-1995 0.01 NS 0.01 NS -7** 1996-2000 -3.4** 0.01 NS -8** 2001-2005 -3.6** -5.6** -7.4** 2006-2010 -12** 0.01 NS -10.2** 1991-2010 -7** 3.1** -4.1**

Note: ** = Statistically significant at 1 percent probability; * = statistically significant at 5 percent probability; NS = Not significant

Table 4.2.3: Coefficient of variation of area, yield and production of coconut (percent)

Periods Area Yield (t/ha) Production(t) 1991-1995 0 27 27 1996-2000 6 20 23 2001-2005 12 14 21 2006-2010 30 26 22 1991-2010 42 45 28

Source: Based on FIBOS and MPI, last accessed August 2012.

50

4.2.5 Decomposition of changes in coconut production into area and yield effects

In the sub-period 1991-1995, coconut production in Fiji was mainly contributed by yield

effect which explained 99.9 percent of change in production. Again for the sub-period

1996-2000, increase in copra production was mainly explained by the yield effect at

329.21 percent while the area effect was negative at -176.49 percent and the interaction

effect were also negative at -52.72 percent. This means that the first two periods were

relatively synchronic for the factors of area and yield effect on change in production of

coconut.

In the sub-period 2001-2005 the change in copra production was mainly explained by

the area effect (170.4 percent) followed by the interaction effect (14.34 percent). The

yield effect was negative at -84.74 percent. During the sub-period 2006-2010, the

change in copra production was more explained by the area effect of 175.14 percent and

followed by the interaction effect (68 percent) while the yield effect was negative at -

143.17 percent There was synchronic between the factors of area and yield within the

period.

For the entire period of 1991-2010, the contribution to change in copra production was

because of both area effect and interaction effect each being about 142 percent while the

effect was in opposition direction at -184 percent. It can be said that the change in copra

production during the total period was more explained by the area and interaction effects

51

Table 4.2.4: Decomposing change in coconut production into area-effect and yield-effect (tons)

Periods Area effect

Y’∆ A Yield effect (t/ha)

A’∆Y Interaction effect

∆ A ∆Y 1991-1995

-5.82

(0.13)

- 4,464.21

(99.91)

1.99

(- 0.04)

1996-2000

- 2,992.50

(-176.49)

5,582.06

(329.21)

- 893.97

(-52.72)

2001-2005

- 2,852.00

(170.4)

1,418.31

(- 84.74)

- 240.03

(14.34)

2006-2010

- 5,440.00

(175.14)

4,447.11

(-143.17)

- 2,113.23

(68.03)

1991-2010

- 9,992.40

(142.58)

1,2911.07

(-184.23)

- 9,926.79

(141.65)

Note: Area (ha), Yield (t/ha) and Production (tons). Figure in parentheses indicate the percentage changes of production due to area, yield and interaction effects.

52

4.2.6 Trend in coconut oil exports

Data in Table 4.2.5 show average quantities and values of coconut oil exports for

different periods. Figure 4.2.4 shows trend of coconut oil exports during 1991-2010. It

can be seen in Table 4.2.5 that in the sub-period 1991-1995 average annual coconut oil

export was 5,133 tons which decreased to 4,330 tons during 1996-2000. Quantity of

exports kept declining and average quantity exported was 501 tons only during 2006-

2010. This sharp decline in coconut oil export was attributed mainly to the fall in the

price of coconut oil in the international market during the early stages of the 1990s.

The value of coconut oil exports was also decreased over time. As the coconut

production had been decreasing rapidly in the country, the export of coconut oil also

decreased accordingly.

53

Table 4.2.5: Trend in coconut oil export in Fiji from 1991-2010 (5- year averages)

Periods Quantity(Tons) Value (FJD)

1991-1995 5,133.6 12,120

1996-2000 4,330.5 37,389

2001-2005 813.4 9,546

2006-2010 500.6 11,187

Source: Based on FIBOS and MPI, last accessed August 2012.

54

4.2.7 Growth and instability of coconut oil export

Results of growth rates of coconut oil exports for both quantity and value are presented

in Table 4.2.6. The period under study is divided into four sub-periods. Data show that

during the period 1991-1995) the growth rate of quantity of coconut oil exported was

2.3 percent per annum. During the period 1996-2000 the growth was – 64 percent per

annum. Again during 2001-2005 the growth was –49 percent per annum. However,

during 2006-2020 the growth rate of coconut export was 31.6 percent per annum. On

the whole during the entire period (1991-2010) the growth of coconut oil export was

–10 percent which was significant at 1 percent level of probability. Growth in the value

of coconut exports was also negative during this period.

Instability analysis of coconut oil exports in Fiji is presented in Table 4.2.7. Data shows

that the quantities and values of coconut oil exports were mostly instable (CV being

above 50 percent) accept the initial period of 1991-95. The most instable period was the

sub-period during 2001-2005 with CVs of quantity and values being 191 percent and

167 percent respectively.

55

Table 4.2.6: Growth rate of coconut oil export from 1991-2010 (percent)

Periods Coconut oil Value (FJD)

1991-1995 2.3** -6.7**

1996-2000 -63.9* -42.0 NS

2001-2005 -49.3 NS -37.4 NS

2006-2010 31.6* 30.6*

1991-2010 -9.9** -25.0*

Note: ** = Statistically significant at 1 per cent probability; * = statistically significant at 5 per cent probability; NS = Not significant.

Table 4.2.7: Coefficient of variation of coconut oil export from 1991 to 2010 (percent)

Periods Coconut oil Value

1991-1995 35 27

1996-2000 60 125

2001-2005 191 167

2006-2010 74 48

1991-2010 99 176

56

4.2.8 Constraints in production and export of coconut

(a) Long term crop: Coconut is a long term income generating crop. It takes more than

4-6 years for the farmer to start benefiting from the investment. The faster returns and

demand of other crops have changed the mind-set of the farmers forcing them to neglect

replanting of coconut areas.

(b) Low prices: During 1990s copra prices have remained as low as $300 per tonne.

This made this crop the lowest return per unit area as compared to all other agricultural

activities in the country.

(c) Labour cost and availability: Due to the increased rural to urban drift, there is a

shortage of labour in coconut growing areas and therefore the cost of labour is quite

high. Many farmers complained that the cutting of copra was a hard job with little

return. Some planters observed that drying copra requires a lot of wood and there was

not enough labour to cut the wood. The current generation feel that copra cutting is a

low profile job and therefore prefer other sources of income.

(d) Natural disasters: Coconuts are very susceptible to cyclones. It takes 2-3 years for

the coconuts to come back to the normal production after being hit by a cyclone.

57

(e) Rhinoceros Beetle: Once the crop is affected by pests like rhinoceros beetle

(Oryctes rhinoceros) the production declines. This beetle has a very high capacity to

reproduce and stand harsh environmental conditions. The rhinoceros beetle mainly

affects process of photosynthesis as it affects the leaves by feeding on it hence

affecting production.

(f) Competition with other types of cooking oils in the world market: Higher

preference is given to other cooking oils out of fear of the fat content of coconut oil.

(g) Transportation cost: As most of the coconut farms are located in the Maritime

Provinces, the farmers have to pay a hefty sum for transportation of their products

especially boat and taxi fares. There is no provision for farm gate collection.

(h) Senile coconut trees: Coconut trees have been on the plantation for more than 50

years old and they have crossed their maximum potential stage. Therefore, the

production level is low.

4.2.9 Summing Up

In general a decline in coconut crop area, yield and production was observed throughout

the period under review. Regression analysis of trend in coconut crop area, yield,

production and exports of coconut is shown in Table 4.2.8. It can be seen in table that l

coefficients (slopes) of all trend lines are negative and statistically significant. Though

there was a positive growth in the yield, but it could not outweigh the negative trend in

58

Table 4.2.8 Coefficients of linear (Y = a + bT) regression equations of trend lines for coconut crop area, yield, production and export in Fiji.

Dependent variable (Y)

Estimate of constant (a)

Estimate of coefficient (b)

R2

n

Area 74,239*** (2,148)

- 3, 092*** (193)

0.93 20

Yield 0.13** (0.0396)

0.0218*** (0.004)

0.67 20

Production 15,065*** (1,442)

- 233 NS (130)

0.15 20

Export 6,093*** (718)

- 357.7*** (64.6)

0.63 20

Note: Figures in parentheses denote standard errors of respective coefficients. *** = Significant at 1percent level of probability. ** = Significant at 5percent level of probability. * = Significant at 10 percent level of probability. NS = Not significant.

59

production as the area effect was dominant. Thus, the ultimate outcome was a declining

trend in production and export of this crop.

Government attempts through policies relating to production did not have tangible

effects. The low price proved to be the main determinant factor to the growth of this

crop. Another issue was the long term nature of the crop; requiring long-term investment

in the crop and giving revenue after a lapse of 3-5 years, under unstable prices farmers

were reluctant to invest in this crop. Hence, despite being a very suitable crop for

tropical island countries, coconut farming has shown a negative trend in Fiji.

60

4.3 TARO CROP

In this section firstly, trends, growth rates, and instability analysis of area, yield and

production of taro are discussed. Secondly, contributions of area and yield to taro

production are analysed. Thirdly, trends in sugar export are discussed. Finally, the

constraints faced by the farmers in producing taro are presented.

4.3.1 Trend in taro crop area

Five year averages of area, yield and production of taro in Fiji are presented in table

4.3.1. Table shows trends of area, yield and production. The trend analysis in taro

production for the 20 years from 1991-2010 has been divided into 5 sub-periods starting

from 1991-1995 to 2006-2010.The results from Table 6.1.1 and Fig. 6.1 have shown

reasonable level of change in area, yield and production in Fiji during the 20 year period.

The change is mainly after 1995. This is a result of the outbreak of taro leaf blight in

Samoa which brought Fiji to participate freely in the export market. The government

policies have been always very supportive and this industry has shown impressive results.

The five year averages of area of taro in Fiji have shown increasing trend from an area

of 1,694 hectares in sub-period 1991-1995 to 2,563 hectares in the sub-period 1996-

2000 to 4,065 hectares in the sub-period 2001-2005 to 3590 hectares in the sub-period

of 2006-2010. This increase was possible through government policy renovation in the

form of CDF program in 1997 and formulation and implementation Flat Land

Assistance Programs and the FAO Crop Rehabilitation Program. Attractive prices in

both local and export market confirmed increased demand for the

61

Table 4.3.1 :Trends in taro area, yield and production from 1991-2010

Periods Area (ha) Yield (tons /ha) Production (tons) 1991-1995 1694.6 5.9 10004.2 1996-2000 2563.2 9.96 25521.2 2001-2005 4065.4 12.59 51146.6 2006-2010 3590.4 19.04 68394.6

Source : Based on FIBOS and MPI, last accessed August 2012.

62

commodity. The sub-period of 2006-2010 experienced a drop in area and production of

taro. It was due to the impacts of taro beetle infestation and because of withdrawal of the

government assistance and also due to Cyclones Mick and Tomas in this period.

4.3.2 Trend in taro crop yield

The average yield of taro in Fiji decreased after 2005. It continued to increase year after

year (see Table 4.3.1). Figure 4.3.2 also shows trend of taro yield in different years. Taro

yield was 5.9 tons per hectare in the sub-period 1991-1995 and reached about 10 tons per

hectare in the sub-period 1996-2000.The yield further increased and reached to 12.6 ton

per hectare in 2001-2005. In sub-period 2006-2010 the yield was 19.1 tons per hectare.

4.3.3 Trend of taro crop production

As regards taro production, data in Table 4.3.1 and Figure 4.3.3 show that there was a

considerable increase in taro production during the period of study. In the sub-period

1991-1995 the taro production in Fiji was averaging at 10,000 tons. The production level

increased to 25,521 tons in the sub period 1996-2000. This is largely due to high demand

for taro exports and support from other funding agencies. During the sub-period of 2001-

2005 there was an impressive taro output of 5, 1146 tons which later increased to 6,8394

tons during the sub-period of 2006-2010.

In general there was a remarkable increase in taro area, yield and production throughout

the period under review. Despite climatic disorders as drought in 1998, disasters as

cyclone Tomas and Mick and the political upheaval due to 2000 coup the production of

taro was impressive. Government policies and programs have shown progressive results.

.

63

64

4.3.4 Growth rates and instability of taro crop area, yield and production

Table 4.3.2 shows compound growth rates (CGRS) of area, yield and production of taro

in Fiji from 1991 to 2010. The results presented in table revealed that in the period

1991-1995, area of taro in Fiji had shown a negative growth rate of 7.56 percent per

annum which was significant at 1 percent level of probability. However, the growth

rates of yield and production were positive at 32 percent and 22.1 percent per annum,

respectively.

During 1996-2000 there was substantial increase in taro area and production. In this

period respective growth rates of area and production were 25 and 9.6 percent per

annum. How3ever, the growth rate for the yield was negative. During this period taro

was not classified as a potential export commodity.

During the 2001-2005 periods, there was a high growth rate for both yield and

production of taro. These high rates were due to the sharp and creative policies that were

put in place for economic development in the country. Growth rates in terms of yield

and production of taro were 34 and 22 percent per annum respectively. The area,

however, showed a negative growth rate at 8 percent. The area and production growth

rates were significant at 1 percent level of probability while the growth in yield was

insignificant.

65

During the Assistance Withdrawal period (2006-2010) the growth rates for area and

production were negative at 13.5 percent and 4 percent per annum respectively .These

values were significant at 1 percent level of probability. The growth rate of yield was

10.3 percent. This was the ultimate effect of withdrawal of assistance given by the

government to the farmers. Overall, during the period 1991to 2010, growth rates of taro

area, yield and production were 1.6 percent, 8.7 percent and 10.5 percent per annum,

respectively.

Results presented in Table 4.3.3 indicate level of instability/changes in area, yield and

production of taro for different year groups and the entire period (1991-2010), based on

the coefficient of variation (CV). The results show that in case of taro area, for different

periods, the coefficients of variations have been stable (CV being below 50 percent).

Relatively more stable CV (17 percent) was in the sub-period of 1991-1995. The highest

variation in CV for area (41 percent) was in the sub-period of 1996-2000, followed by

CV in the sub-period of 2006-2010 (33 percent) and the sub-period of 2006-2010 (22

percent). This is because of this crop was given recognition as the high valued

commodity for export after the outbreak of taro leaf blight disease in the neighbouring

country Samoa.

In case of taro yield the highest stability (CV being 33 percent) was in the sub-period of

2006-2010. The highest instability (CV being 88 percent) was in the sub-period of 1991-

1995 followed by the sub-period of 2001-2005 (CV = 65 percent) and the sub-period of

1996-2000 (CV = 33 percent).

66

Table 4.3.2: Compound growth rates in area, yield and production of Taro (percent)

Periods Area Yield (t/ha) Production(t)

1991-1995 -7.56** 32 NS 22.1* 1996-2000 25** -12 NS 9.6** 2001-2005 -8** 34 NS 22.3** 2006-2010 -13.5** 10.3 NS -4** 1991-2010 1.6** 8.7 NS 10.5**

Note: ** = Statistically significant at 1 percent probability; * = statistically significant at 5 percent probability; NS = Not significant

Table 4.3.3: Coefficient of variation of area, yield and production of taro (percent)

Periods Area Yield (t/ha) Production(t) 1991-1995 17 88 68 1996-2000 41 33 24 2001-2005 22 65 44 2006-2010 33 23 10 1991-2010 42 59 67

Source: Based on FIBOS and MPI, last accessed August 2012.

67

In case of taro production highest stability (CV=10 percent) was in the sub-period of

2006-2010. For the sub-period 1991-1995 instability was 68 percent, for 1996-2000 it

was 58 percent and for the period 2006-2010 CV was 67 percent.

For the entire period of 1991-2010, the instability analysis showed that the taro area was

stable (CV=42 percent). Taro yield and production were relatively instable, their CVs

being 67 percent and 59 percent respectively. Taro production was more unstable than

taro yield and yield was more unstable than taro area. This means that there was

considerable quantitative increase in terms of production and yield.

4.3.5 Decomposition of change in taro production into area and yield effects

In the sub-period of 1991-1995, the positive change in taro production in Fiji was

mainly due to the yield-effect which accounted for 176.29 percent of total change in

production. On the other hand, the area and interaction effects were – 18.97 percent and

-57.32 percent, respectively. In the sub-period 1996-2000, change in production was

mainly due to the area effect which accounted for 371.83 percent) change while the yield

and interaction effects were negative –85.72 percent and –186.11 percent, respectively.

In the sub-period of 2001-2005, the positive change in taro production was mainly

contributed by the yield effect of 190 percent. Interaction effect and area effect were

negative at -69.01 percent and – 20.86 percent respectively. In the sub-period of 2006-

2010, the main contribution to growth in taro production was due to the area effect

68

Table 4.3.4: Decomposition of change in taro production into area-effect and yield-effect (tons).

Note: Figure in parentheses indicate the percentage changes in production due to area, yield and interaction effects. Area (ha), Yield (t/ha) and Production (tons)

Periods Area effect Yield effect Interaction effect

Y'∆ A A'∆Y ∆ A ∆Y

1991-1995

- 2,626.68

(-18.97)

24,410.35

(176.29)

- 7,937.11

(-57.32)

1996-2000

49,086.95

(371.83)

- 11,316.04

(- 85.72)

- 24,569.29

(-186.11)

2001-2005

-11,097.90

(- 20.86)

101,012.12

(189.87)

-36,712.82

(- 69.01)

2006-2010

-39,295.00

(247.49)

48,375.7

(- 304.68)

- 24,958.11

(157.19)

1991-2010

3,159.45

(-39.10)

- 8,080

(99.99)

- 3,160.12

(39.11)

69

(247.49 percent) followed by the interaction effect (157.19 percent). The yield- effect

was negative at -304.68 percent.

During the entire period of 1991-2010, the change in taro production was contributed

most by the yield effect (99.99 percent) followed by the interaction effect (39.1 percent)

while the area effect was negative (– 39.11 percent). It can be said that for the total

period the progress in taro production was mainly due to the yield effect.

With interesting findings it can be said that for the increase in the taro production in Fiji,

was due to more emphasis placed on increasing the taro crop yield by implementing

suitable technologies.

4.3.6 Trend in taro exports

Data in Table 4.3.5 taro export quantity and its export value in a 5 year average. Figure

4.3.4 illustrates trend of taro export quantity. It can be seen in Table 4.3.5 that in the first

sub-period average taro export was about 2,500 tons per annum. During the sub-period

1996-2000 taro export increased to 7025 tons. In 2000-2005 it further increased to 8,248

tons. During 2006-2010 the average taro exports were 10,862 tons. This rapid increase

in taro export was attributed to the outbreak of the taro leaf blight disease in Samoa

reducing their competition in taro export markets and resulted in the gain of momentum

for taro exports from Fiji. Hence, the taro production and export quantity had increased

rapidly in Fiji.

70

Table 4.3.5: Trend in taro export in Fiji (5-year averages)

Periods Quantity(Tons) Value (FJD) 1991-1995 2401.4 17,055,205 1996-2000 7025.4 48,218,996 2001-2005 8248.6 73,970,246 2006-2010 10862 110,871,301

Source: Based on FIBOS and MPI, last accessed August 2012.

71

In the case of export values, there was also an increase in each period following the

export quantity. The value of taro export was FJ$17 million in the sub-period 1991-1995

which rose to FJ$110.87 million during 2006-2010.

In general the success of taro production and export in Fiji resulted from the outbreak of

taro leaf blight in Samoa, implementation of the CDF program, EPP, and other

incentives offered by the government. Taro development programme was relatively

comprehensive and sustainable.

4.3.7 Growth rates and instability of taro exports

The results for growth rates of taro exports for both quantity and value are presented in

Table 4.3.6. The whole time period is divided into four five-year sub-periods. In the

period of 1991-1995); Coup period the growth rate for both taro export quantity and

value was positive and insignificant at 45.3 and 52.7 percent respectively.

During the period 1996-2000 the growth rate of quantity of taro export was 1.1 percent

per annum and significant at 5 percent level of probability. During the same period the

growth in value of export was 5.6 percent per annum and this was significant at 1

percent level of probability.

In the period 2001-2005) the growth rate of export quantity and value of taro was 10.6

percent and 13.1 percent per annum respectively. These growth rates were significant at

1 percent level of probability. This rapid growth in taro export was the result of

renovation in the economic and agricultural development programmes.

72

Table 4.3.6: Average growth rates of taro exports during different periods (percent)

Periods Taro quantity Value 1991-1995 45.3 NS 52.7 NS 1996-2000 1.1* 5.6** 2001-2005 10.6** 13.1** 2006-2010 -1.4* 2.8** 1991-2010 13.3** 17.4**

Note: ** = Statistically significant at 1 percent probability; * = statistically significant at 5 percent probability; NS = Not significant

Table 4.3.7: Coefficient of variation of taro export from 1991 to 2010 (percent)

Periods Taro quantity (tons) Value 1991-1995 88 95 1996-2000 68 16 2001-2005 22 28 2006-2010 8 9

73

However, during Assistance Withdrawal period (2006-2010), the growth rate of export

quantity was negative (-1.4 percent). The growth rate for value of exports was positive

at 2.8 percent/annum. If we consider the entire period of 1991-2010 together, the growth

rates of export quantity and value were positive at 13.3 percent and 17.4 percent

respectively.

Instability analysis of taro exports is presented in table 4.3.7. Analysis showed that

quantity of taro exports was instable during the period 1991 to 2000. However, 2001

onwards the export quantity was stable. As regards values of the exported quantities,

these were mostly stable, except during the period 1991-95. The quantities and values of

taro exports were most stable during in the period of 2006-2010 with the CV of 8

percent and 9 percent, respectively.

The most unstable period for their exports was during 1991-1995 when the CV was 88

percent and 95 percent for export quantity and export value, respectively.

4.3.8 Constraints in production and export of taro

The concerns expressed by taro growers and exporters are as follows:

(a) Declining soil fertility: As there is an increased demand for export of taro a lot of

emphasis is placed on increasing its area, yield and production. Due to continuous

mono-cropping for more than a decade, the production per hectare has been declining.

(b) Cost of production: There is an increased cost of production of taro because of

increased costs of fertilizers, labour, land preparation and transport.

(c) Theft of produce: When the prices of taro are attractive in the market, the level of

theft from taro fields increased. Reluctance and slow action by police adds to the

74

situation as by the time the police reaches the farm for investigation the stolen taro has

already been sold to the middleman/buyers. So there is no proof for further action

against the suspected thieves.

(d) Climate change: Change in climatic condition, especially drought affects taro

production the most. The extreme drought conditions causes the peanut-shaped taro

which is regarded as rejects in the market.

(e) Price fluctuations: The economic principles of supply and demand affects price.

When the supply is high the price of taro is low and as result even the reasonable sized

taro is classed as reject. One the other hand once the supply is low the price increases

and even the very small corms are accepted by the buyers. The price fluctuations affect

ability of farmers to properly plan allocation of area for taro crop.

(f) Farm roads: Most of the taro farm roads were constructed during the CDF era

(early 1990s). However, over the past years condition of roads has deteriorated and now

they are almost inaccessible by the farm vehicles. This delays the farmers work plans,

especially in the rainy weather.

4.3.8 Summing up

Regression analysis of trend of area, yield, production and exports of taro presented in

Table 4.3.8 provides the salient overview of the situation of this crop. The analysis

75

Table 4.3.8: Coefficients of linear (Y = a + bT) regression equations of trend lines for taro crop area, production and export in Fiji.

Dependent variable (Y)

Estimate of constant ‘a’

Estimate of coefficient ‘b’

R2

N

Area 1,808*** (457)

123.2** (41.1)

0.33 20

Yield 3.76 NS (2.22)

0.961*** (0.199)

0.56 20

Production 546 NS (4521)

4,023*** (408)

0.84 20

Export 1,923 NS (1080)

548.5*** (97.2)

0.64 20

Note: Figures in parentheses denote standard errors of respective coefficients.

*** = Significant at 1percent level of probability; ** = Significant at 5 percent level of probability; * = Significant at 10 percent level of probability; NS = Not significant.

76

shows that there was positive and highly significant growth in taro area, yield,

production and export.

As has been pointed out previously, in addition to the effort of the individual farmers,

this positive outcome for taro crop was the result of the effective of policies and support

of the government for enhancing production of this crop.

77

4.4 PAPAYA CROP

In this section, firstly the trends, growth rates, and instability analysis of area, yield and

production of papaya are discussed. Secondly, contribution of area and yield effects to

papaya production is decomposed. Thirdly, trend and instability of papaya export are

discussed. Finally, constraints faced by the papaya farmers are pointed out.

4.4.1 Trend of area under papaya crop

The trend analysis of papaya area and production for 20 years from 1991-2010 has been

divided into four sub-periods starting from 1991-1995 to 2006-2010. Five year averages

of area, yield and production of papaya in Fiji are presented in the Table 4.4.1. Figure

4.4.1 illustrates the trend in area. There have shown considerable changes in area, yield

and production in Fiji after 20 years. The change mainly happened after 1997 due to the

implementation of Commodity Development Framework (CDF).

The five year averages of area of papaya crop shows that after 1996-2000 the papaya area was 57.7

hectares. However, within this period there was a huge increase in the area of papaya during 1997-

1999 but it later on declined. The area of crop continued to show a slight decline during the sub-

period of 2001-2005 which was 57.4 hectares. In the last sub-period of 2006-2010 the papaya area

had changed to 122.6 hectares.

78

Table 4.4.1:Trends in papaya crop area, production and yield, 1991-2010 ( 5-year averages)

Periods Area (ha) Yield (tons /ha) Production (tons) 1991-1995 21.2 11.61 210.6 1996-2000 57.79 16.1 933 2001-2005 57.45 36.5 2095.2 2006-2010 122.6 44.3 4752

Source: Based on FIBOS and MPI, last accessed August 2012.

79

4.4.2 Trend of papaya crop yield

Five year averages of papaya yield in Fiji are shown in Table 4.4.1. The data show that there was a

rapid increase in yields. During 1991-1995 yield was 11.6 tons per hectare. It rose to 16.1 tons per

hectare by the sub-period of 1996-2000.The yield continuously increased reaching 37 tons in 2001-

2006 and further increased to 46 tons per hectare during the period of 2006-2010.

4.4.3 Trend in production of papaya

As regards papaya production, data in Table 4.1.1 and Figure 4.4.3 reveal that there was a

considerable increase after each sub-period. There was a decline in production in 1993 due to

damages caused by cyclone Kina in January. However, there was a quick recovery and by the end of

the sub-period of 1991-1995 the production reached production of 210 tons. The papaya production

gained momentum in the sub-period of 1996-2000. Remarkable change was seen during the last

phase of the sub-period due to political upheaval caused by the 2000 coup. The production dropped

from 1146 tons in 1999 to 752 tons in 2000. In early 2000’s papaya production in Fiji had been

increasing. Average production reached up to 2,095 tons in 2001-2005 and later increased to 4,752

tons in 2006-2010.

.

81

4.4.4 Growth rates and instability of papaya crop area, yield and production

Table 4.1.2 shows the compound growth rates (CGRS) of area, yield and production of

papaya in Fiji during 1991-2010. This whole period is sub-divided into four sub-periods

of Fiji’s economy as mentioned previously: (i) Pre- Coup period (1991-1995); (ii) Coup

period (1996-2000); (iii) Post-Coup period (2001-2005) and (iv) Assistance Withdrawal

period (2006-2010).

The results given in Table 4.4.2 revealed that in the period 1991-1995 the papaya area in

Fiji had shown a negative growth rate at 13 percent per annum. However, the growth

rate of yield was 18.1 which has outweighed the negative area effect and resulted in

positive 3 percent growth in production per annum during this period. The CGR for area

has been negative as the cyclone Kina had a devastating effect on reduction in crop area.

During the period 1996-2000 there were positive and significant growth rates in area and

production at 29.7 and 17.9 percent per annum. In the period 2001-2005 growth rates of

area and production of papaya were negative at 4.6 and 3.8 percent per annum

respectively. The yield rate did not vary significantly.

The assistance withdrawal period (2006-2010) had clear effects on growth rates. The

growth rates of yield and production were negative at 9.5 and 4.5 percent per annum

respectively .The area growth rate was 5.4 percent per annum, positive and insignificant.

The production growth rate was significant at 5 percent level of probability while the

yield growth rate was insignificant. This was the eventual effect of the withdrawal of

assistance given by the government to farmers.

82

When we view the overall period of 1991-2010 the CGRS of papaya area, yield and

production were all positive at the respective rate of 4.3 percent; 9.5percent and 14.3

percent per annum. The area and production growth rates were significant at 5 percent

and 1 percent level of probability, respectively.

Results presented in Table 4.4.3 indicate level of instability of area, yield and production

based on the coefficient of variation (CV). The results in Table 4.4.3 show that growth

in papaya area has been very unstable. It was relatively more stable (CV=39 percent) in

the sub-period of 2001-2005 followed by 1996-2000 (CV=42 percent). The highest

instability in papaya area was during the sub-period of 1991-1995 (CV = 90 percent)

which was followed by the sub-period of 2006-2010 (CV = 78 percent).

83

Table 4.4.2: Compound growth rates in area, yield and production of papaya (percent)

Periods Area Yield (t/ha) Production (t) 1991-1995 -13 NS 18.1 NS 3 NS 1996-2000 29.7* -9* 17.9* 2001-2005 -4.6* 0.9 NS -3.8** 2006-2010 5.4 NS -9.5 NS -4.6* 1991-2010 4.3* 9.5 NS 14.3**

Note: * = Statistically significant at 5 per cent probability; ** = statistically significant at 1 per cent probability; NS = Not significant

Table 4.4.3: Coefficient of variation of area, yield and production of papaya (percent)

Periods Area Yield (t/ha) Production (t) 1991-1995 90 85 78 1996-2000 42 35 58 2001-2005 39 68 29 2006-2010 56 52 67 1991-2010 80 81 117

Source: Based on FIBOS and MPI, last accessed August 2012.

84

In the case of papaya, the highest instability in yield was observed in the sub-period of

1991-1995 (CV= 85 percent) followed by the sub-period of 2001-2005 (CV = 68

percent). The yield was relatively stable (CV=35 percent) in the sub-period of 1996-

2000.

As regards papaya production, the highest stability in it (CV=29 percent) was in the sub-

period of 2001-2005. In other sub-periods the production was instable; CV being 78

percent in 1991-1995; 67 percent in 2006-2010 and 58 percent during the period 1996-

2000.

On the whole, for the entire period of 1991-2010 the instability analysis for papaya

showed that area, yield and production of papaya had high instability as compared to the

sub-periods. Instability in papaya production was 117percent), in papaya yield was 81

percent, and for papaya area was 80 percent. Hence, for the entire period, papaya

production was more unstable than its yield and papaya yield was more unstable than the

area under papaya crop.

4.4.5. Decomposition of changes in papaya production into area and yield effects

In the sub-period 1991-1995, change in papaya production in Fiji was mainly due to the

yield effect which explained 905.27 percent of change. The contribution of area effect

and interaction effect was negative at -455.87 percent and - 349.4 percent respectively.

85

In the sub-period 1996-2000, role of the factors changed. The area effect on production

was positive at 207.96 percent while the yield effect and interaction effect were negative

at -29.42 percent and -78.56 percent respectively. This means that the first two periods

were not synchronic for the area, yield and production.

In the sub-period of 2001-2005, the change in papaya production was mainly

contributed by the area effect (120.37 percent) while the yield effect was negative (–

25.81 percent) and the interaction effect was negligible (5.44 percent). This period was

more favourable in terms of area effect as compared to yield and interaction effects.

In the sub-period 2006-2010 the change in papaya production was mainly contributed by

the yield effect (187.44 percent) and the interaction effect was (56.23 percent) while area

effect was negative (-143.67 percent). Again these values show that these factors were

not synchronic in their effect on changes in papaya production.

For the entire period of 1991-2010, the contribution to changes for papaya production

was mainly (50.43 percent) by the interaction effect of area and yield. The contribution

of yield effect alone was 38.17 percent and that of area effect alone was 11.4 percent. It

can be said that the changes in papaya production for the total period was more

explained by the interaction effect area and yield followed by the yield effect and area

effect alone.

With this interesting finding it can be said that the increase in papaya production was

mainly due to a lot of emphasis placed by government with regards to increasing crop

yield

86

Table 4.4.4: Contribution of area and yield effects to changes in production of papaya.

Note: Figures in parentheses indicate the percentage changes of area, yield and interaction effect on production. Area (ha), Yield (t/ha) and Production (tons)

Periods Area effect

Y'∆ A Yield (t/ha)

A'∆Y Interaction effect

∆ A ∆Y

1991-1995

-87.56

(-349.40)

226.86

(905.27)

-114.24

(-455.87)

1996-2000

885.91

(207.96)

-125.23

(-29.4)

-334.67

(-78.56)

2001-2005

-477.88

(120.37)

102.47

(-25.81)

-21.6

(5.44)

2006-2010

830.40

(-143.67)

-1083.38

(187.44)

-325.02

(56.23)

1991-2010

229.77

(11.4)

769.38

(38.17)

1016.69

(50.43)

87

4.4.6 Trend in export of papaya

Papaya trade quantity and value on five year averages are presented in Table 4.4.5.

Figure 4.4.4 also illustrates papaya export trend in Fiji. It can be seen from Table 4.4.5

that in the sub-period 1991-95 average papaya export was 32 tons per year. In the

subsequent periods it has risen to 88.3 tons in sub-period 1996-2000, to 211.5 tons in

2000-2005 and to 539.8 tons during 2006-2010. This sharp increase in export was

attributed mainly to the policies identified and implemented by the government and the

investment by the private enterprises, such as the Natures Way Co-operative. The

papaya production had been increasing rapidly and thus exports have also increased

considerably.

In the case of values of papaya exported, there was an increase over time. Papaya export

was worth FJD1.7 million per year during the sub-period 1991-1995 which increased to

FJD 2.5 m during 1996-2000 and then to FJD 6.9 m during 2001-2005. During the sub-

period 2006-2010 the average annual value of papaya exports was FJD5.9 million.

4.4.7 Growth rate and instability in papaya export

The growth rates of papaya export quantity and value for different periods are presented

in Table 4.4.6.

In the period 1991-1995, average annual growth rates for papaya export quantity and

value were negative at -22 and -15 percent respectively. However, for the period 1996-

2000 the growth rates of papaya export quantity and value were positive at 48 and 224

percent respectively.

88

Table 4.4.5: Trend in papaya export in Fiji from 1991-2010 (5- year averages)

Source: Based on FIBOS and MPI, last accessed August 2012

Periods Quantity (Tons) Value (FJD) million 1991-1995 18.18 1.7

1996-2000 78.41 2.5

2001-2005 211.5 6.9

2006-2010 539.8 5.9

89

In the period 2001-2005 the growth rate of quantity of papaya export was positive at 19

percent but the growth rate of value of exports was negative at -1.4 percent per annum.

During the period 2006-2010 the growth rates of quantity and value of exports were

positive.

The growth rate for quantity exported was 8.7 percent and for the value was 2.4 percent

per annum, and these rates were significant at 5percent and 1 percent level of probability

respectively.

For the entire period of 1991-2010, on the whole the growth rate for papaya quantity

exported was 19.5 percent and the growth rate of value of exports was 12.2 percent per

annum respectively, and the growth rates were significant at 1 percent level of

probability.

Instability analysis of papaya exports from Fiji was done and the data are presented in

Table 4.4.7. The analysis revealed that the quantity of papaya exported and the values of

export earnings were mostly stable in the period 2001-2005 the respective variances

being 38 percent and 7 percent.

The most unstable period papaya export was during the sub-period of 1991-1995 with

CV of 114 and 121 percent for export quantity and export value, respectively.

90

Table 4.4.6: Annual growth rate of papaya exports from Fiji, 1991-2010 (percent)

Periods Papaya Value

1991-1995 -22** -15*

1996-2000 48* 224*

2001-2005 19.6* -1.4*

2006-2010 8.7* 2.4*

1991-2010 19.6* 12.3*

Note: **=Statistically significant at 1 percent probability; * = statistically significant at 5 per cent probability; NS = Not significant.

Table 4.4.7: Coefficient of variation of papaya exports from Fiji (percent)

Periods Papaya quantity Value

1991-1995 114 121

1996-2000 51 133

2001-2005 38 7

2006-2010 58 7

1991-2010 120 84

91

4.4.8 Constraints to production and export of papaya in Fiji

The problems faced by producers and exporters of papaya in Fiji are explained below:

(a) Natural disasters: Papaya is one commodity that is a highly disaster susceptible

crop especially with relevance to flooding and cyclones. These affect the general

operation of the papaya farming business.

(b) Drainage: Poor drainage affects the crop causing rot. Therefore, a lot of farmer’s

money is used for improving drainage of his farm.

(c) Land ownership pattern: Majority of the farms under papaya farming are under

native land lease. This affects the general development of the farm as the farmers are

reluctant to do any long term investments on leased-in farms.

(d) Low price of produce: In most of the cases it is the middleman/buyer who decides

sale price of papaya. The farmer is the price taker. Therefore the lowest price is offered

to the producer (farmer) while others along the value chain enjoy a better profit margin.

(e) High cost of production: High cost of production is affecting the interest of many

farmers especially with regards to seedlings, land preparation, fertilizer, labour and

chemicals.

(f) Availability of seedlings: As there is an agreement between the trading partners that

all the seeds of papaya have to be sourced from the Ministry of Agriculture so as to

preserve the genetic makeup, farmers do not receive papaya seedlings on a timely basis.

This affects the production as well as the consistency in supply.

(g) Poor infrastructure: Poor farm roads and drainage is also an on-going problem in

the main papaya growing areas.

92

4.4.9 Summing Up

Regression analysis of time-series data on area, yield, production and exports of papaya

is presented in Table 4.4.8. The analysis summarizes the direction of trends of papaya

area, yield, production and exports in Fiji during the twenty year period (1991-2010).

The regression coefficients of the variables denoting slopes of the respective trend lines

show that there was statistically significant positive growth in area, yield, production

and exports of papaya.

93

Table 4.4.8: Coefficients of linear (Y = a + bT) regression equations of trend lines for papaya crop area, yield, production and export in Fiji.

Dependent variable (Y)

Estimate of constant ‘a’

Estimate of coefficient ‘b’

R2

n

Area 3.5 NS (18.6)

5.83*** (1.55)

0.44 20

Yield 4.37 NS (9.12)

2.347** (0.761)

0.35 20

Production -849 NS (4521)

270.5*** (67.8)

0.47 20

Export 126.3 NS (77.3)

32.67*** (6.46)

0.58 20

Note: Figures in parentheses denote standard errors of respective coefficients.

*** = Significant at 1percent level of probability. ** = Significant at 5percent level of probability. * = Significant at 10 percent level of probability. NS = Not significant.

94

In general, it may be noted that there were remarkable increases in the area, yield and

production of papaya during the period 1991-2010. This good performance can be

attributed to many factors: (i) initiative and hard work of papaya entrepreneurs, (ii)

Rural and Outer Island (ROI) program, (iii) Export Promotion Program (EPP), and (iv)

Import Substitution Program (ISP). There has been a large change in papaya farming

from subsistence, to self-sufficient farming to commercial agricultural production. This

makes clear that changes in agricultural policies especially in relation to land and

production can make a lot of difference in boosting agricultural production in the

country.

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4.5 GINGER CROP

In this section of Chapter 4, firstly, the trends, area, yield and production of ginger are

discussed. Then their growth rates and instability are analysed. Thirdly, contributions of

area and yield effects in changes in the ginger production are estimated. Fourthly, trends

in ginger export are analysed. Finally, the constraints faced by the ginger farmers are

discussed.

4.5.1 Trend of ginger crop area

The trends in ginger area and production for the 20 years period from 1991-2010 have

been divided into four five-year sub-periods. Five year averages of area, yield and

production of ginger in Fiji are presented in Table 4.5.1. The table shows that there were

wide fluctuations in area, yield and production of ginger crop. Figure 4.5.1 illustrates

changes in ginger area in Fiji during the 20 year period under study.

The five year averages of area of ginger in Fiji show that there was remarkable increase

in area from 145.5 hectare in the sub-period of 1991-1995 to 312.2 hectares in the sub-

period of 1996-2000 the ginger. This was due to the establishment of Ginger Council in

1993 due to disease problems. However, the area of ginger crop decreased from 184.6

hectares in the sub-period of 2001-2005 to 142.3 hectares in the sub-period of 2006-2010.

Unattractive prices encouraged farmers to reduce acreage and shift to other alternative

crops. The progress in years after 1997 was due to government intervention with policies

that led to formation of Commodity Development Framework (CDF). This ultimately led

to increased interest of farmers in ginger production.

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Table 4.5.1: Trends of ginger area, production and yield from 1991-2010

Periods Area (Ha) Yield (tons /ha) Production (tons) 1991-1995 145.5 23.8 3456 1996-2000 312.2 9.5 2963.4 2001-2005 184.6 17.1 3153.72 2006-2010 142.3 19.6 2786.8

Source: Based on FIBOS and MPI, last accessed August 2012.

97

4.5.2 Trend of ginger crop yield

The five year average yield of ginger in Fiji decreased rapidly from 23.8 tons per hectare

to 9.5 tons per hectare during the sub-periods of 1991/1995 to 1996/2000.The

investment through CDF programs led to a substantial level of change in the yield of

ginger from 9.5 tons per hectare in the sub-period of 1996/2000 to 17.1 tons per hectare

in the sub-period of 2001/2005. The yield continued to slightly increase to 19.6 tons per

hectare in the final sub-period of 2006/2010.This slow increase was due to many factors:

heavy rainfall affecting flat land cultivation, withdrawal of assistance to subsistence

farmers, and lack of project submission for ginger under Export Promotion Project in

2009.

4.5.3 Trend of ginger production

Ginger production data from Table 4.5.1 and Figure 4.5.2 show that there was

considerable decrease in ginger production from 3,456 tons in 1991/1995 to 2,963 tons

in 1996/2000. The increase in production in 2001 was in response to a sudden demand

for Fijian ginger in the Canadian market. But this Canadian demand for ginger declined

in 2006. The change in government policies directing towards export orientation led to

investment in programs as CDF in 1997 which led to an increase in production from

2,963.4 tons in the sub-period of 1996/2000 reaching 3,153.7 tons in the sub-period of

2001/2005. However, competition in the open market forced Fiji to reduce its export

quota and this forced exporters to reduce their buying capacity which ultimately led

farmers to reduce production of ginger.

98

99

Despite several attempts by the government through renovation policies, strategic plans

and implementation of programs, the area, yield and production of ginger continued

declining. There has been a shift from production of ginger to other crops. Insecurity of

ginger markets coupled with contract arrangement introduced by the traders through

quota system and too much reliance on assistance by the government are the major

reasons for this continuous decline in ginger production.

4.5.4 Growth rates and instability of ginger crop area, yields and production

Average compound growth rates (CGRS) of area, yield and production of ginger in Fiji

for the four sub-periods from 1991-2010 are shown in Table 4.5.2.The results from the

table revealed that in the period 1991-1995, the ginger performance was the worst in

terms of area and production. The growth rates of area and production of ginger were

significantly negative at 19.6 and 19.5 percent per annum respectively. Stiff competition

and unattractive prices were contributing factors for this negative growth. The growth in

yield was 0.57 percent per annum and this was significant at 1 percent level of

probability.

During the period 1996-2000, there was a distinct increase in area of ginger with an

annual growth rate of 3.1 percent. The growth rates for yield and production of ginger

were negative at 15 and 9.3 percent per annum respectively.

Again during the period 2001-2005 there was negative growth in ginger area at 3.5

percent per annum. The growth rates for yield and production of ginger were positive at

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24.9 and 20.5 percent per annum respectively. During the Assistance Withdrawal Period

(2006-2010), growth rate of ginger area was positive at 6.5 percent per annum. But the

average annual growth rates of ginger yield and production were negative at 11.9 and

6.1 percent respectively. The withdrawal of assistance to farmers had great negative

effect on the yield and production of ginger.

Hence, taking whole period of 1991-2010 into account, the annual growth rates of the

area, yield and production of ginger in Fiji were significantly negative at the rate of 1.2

percent; 3.7 percent and 4.9 percent, respectively. The overall performance of the crop

has been negative.

Results in Table 4.5.3 indicate high level of instability for the entire period (1991-2010)

based on coefficient of variations (CVs) of area, yield and production. The results in

Table 4.5.3 show that in case of ginger area, the coefficient of variation has been very

unstable. The more stable CV was found to be (CV=50 percent) in the sub-period 1991-

1995. The highest instability (CV=98 percent) was observed in the sub-period 1996-

2000 followed by the sub-period 2006-2010 (CV = 55 percent) and the sub-period 2001-

2005 (CV=53 percent).

In the case of ginger yield, the highest stability (CV=33 percent) was observed in the

sub-period 1991-1995. The highest instability (CV = 91 percent) was observed in the

sub-period 2006-2010 followed by the sub-period 1996-2000 (CV = 59 percent) and

the sub-period 2001-2005 (CV=49 percent).

As regards ginger production, the highest stability (CV=14 percent) was observed in the

sub-period 2006-2010 and highest instability (61 percent) in the sub-period 1991-1995.

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Table 4.5.2: Compound growth rates of area, yield and production of Ginger (percent)

Periods Area Yield (t/ha) Production(t) 1991-1995 -19.6* 0.57** -19.5* 1996-2000 3.1NS -15 NS -9.3** 2001-2005 -3.5* 24.9 NS 20.5** 2006-2010 6.5* -11.9 NS -6.1** 1991-2010 -1.2** -3.7** -4.9**

**=Statistically significant at 1 percent probability; *=statistically significant at 5 per cent probability; NS = Not significant

Table 4.5.3: Coefficients of variations (CV) of area, yield and production of ginger (percent)

Periods Area Yield (t/ha) Production(t) 1991-1995 50 33 61 1996-2000 98 59 19 2001-2005 53 49 31 2006-2010 55 91 14 1991-2010 87 70 37

Source: Based on FIBOS and MPI, last accessed August 2012.

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For the entire period of 1991-2010, instability analysis showed that changes in area had

high instability (CV= 87percent). The instability for ginger yield was also high (CV=70

percent). But, the ginger production has stability (CV= 37 percent). The area of ginger

was more unstable than the ginger yield.

4.5.5 Decomposition of changes in ginger production into area and yield effects

Data on decomposition analysis of area effect and yield effect on changes in the quantity

of ginger produced are presented in table 4.5. In the sub-period 1991-1995, in ginger

production main contribution was by area effect (which explained 101.47 percent

change in production) followed by interaction effect (2.9 percent). The contribution of

the yield effect was negative (-4.38 percent).

In the sub-period 1996-2000, change in ginger production was mainly explained by the

area effect contributing 137.7 percent change. While the other effects were negative;

yield effect was -11.05 percent and the interaction effect was -26.6 percent. This means

that during this period (and during the previous period also), the area effect and yield

effect on production were not synchronic.

In the sub-period 2001-2005, increase in ginger production was mainly explained by the

area effect (94.7 percent). The yield effect was 6.34 percent only. The interaction effect

was negative at1 percent. As compared to previous period, during this period the area

effect had decreased while the yield effect has increased.

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Table 4.5.4: Contributions of area and yield effects to change in production of ginger

Periods

Area effect Y΄∆ A

Yield (t/ha) A΄∆Y

Interaction effect ∆ A ∆Y

1991-1995

-4266.00

(101.47)

184.21

(-4.38)

-122.35

(2.9)

1996-2000

5791.24

(137.7)

-464.75

(-11.05)

-1119.61

(-26.6)

2001-2005

-236.33

(94.7)

-15.81

(6.34)

2.6

(-1)

2006-2010

1189.96

(50.2)

861.02

(36.33)

319.23

(13.5)

1991-2010

-1445.70

(35.36)

-3409.87

(83.41)

767.53

(-18.8)

Note: Area (ha), Yield (t/ha) and Production (tons).

Figures in parentheses indicate percentage contribution of area effect, yield effect and interaction effect on changes in production of ginger.

104

During the sub-period 2006 to 2010, the change in ginger production was more

explained by area effect (50.2 percent), followed by the yield effect (36.33 percent) and

the interaction effect (13.5 percent). In this period all factors were synchronic as all

contributed positively to the change in production. However, as compared to previous

period, the area effect had decreased whereas the yield effect has increased.

Overall for the entire period of 1991-2010, the contribution of area effect to change in

ginger production was 35.36 percent and the yield effect was 83.41. The interaction

effect decreased was negative (-18.8 percent). It can be said that during the total period

the change in ginger production was more explained by the yield effect while the area

effect was continuously decreasing.

4.5.6 Trend of ginger export

Data analysis presented in Table 4.5.5 show ginger export and its export value. Figure

4.5.4 also illustrates trend of ginger export. The trend of ginger production shown in

table 4.5.1 highlighted that ginger production during the period 1991 to 2010 had been

decreasing rapidly. Consequently, the quantity of ginger exported is also showing a

decreasing trend (see table 4.5.5). The average annual quantity of ginger exported was

1718.8 tons during 1991-95 which reduced to 1267.9 tons during 1996-2000 and

ultimately during 2006-2010 it was 1173 tons only.

However, if we consider the money value of the quantity of ginger exported, due to

sharp increases in the prices of ginger in export markets, it was continuously increasing

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in each period except the sub-period of 2006-2010. The export earnings from ginger for

the first three sub-periods (1991/1995; 1996/2000 and 2001/2005) were FJD1.7 million;

FJD 3.5m; and FJD 6.9 m, respectively. During the period 2005/2010 the annual average

value of ginger quantity exported decreased to FJD5.9 million.

4.5.7 Growth rate and instability of ginger export

Growth rates of ginger exports are presented in table 4.5.6. Data revealed that during the

period of 1991-1995 the annual growth rate of quantity of ginger exported was

negative at 19.7 percent. However, the money value of export had positive growth at 18

percent per annum which was significant at 1 percent level of probability.

For the period 1996-2000, the annual growth rates for both the quantity of ginger

exported and the value of export were positive at 16 percent and 28.2 percent

respectively. These growth rates were significant at 5 percent level of probability.

During 2001-2005 the annual growth rate of quantity of ginger exported was positive at

5.2 percent, but the growth rate of the value of exports was negative at 1.4 percent.

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Table 4.5.5: Trend of ginger export from Fiji, 1991-2010 (5-year averages)

Periods Quantity(Tons) Value (FJD)

1991-1995 1718.8 1,770,717

1996-2000 1267.9 3,507,812

2001-2005 1211 6,960,578

2006-2010 1173.2 5,984,171

Source: Based on FIBOS and MPI, last accessed August 2012.

107

The period 2006-2010 witnessed a negative growth rate for the quantity exported at -3.5

percent while the growth rate of the value of exports was positive at 2.4 percent. Both of

these growth rates were significant at 1 percent level of probability.

During the entire period of 1991-2010, the growth rate of quantity of ginger exported

was negative at 5.4 percent per annum. However, the growth rate of the value ginger

exports was positive at 12.5 percent per annum. Both of these growth rates were

significant at 1 percent level of probability.

The instability analysis of ginger exports in Fiji is presented in Table 4.5.7. It can be

seen from the table that the quantities of ginger export were relatively stable (having low

CV) except during the period 1991-95. As regards money values of the ginger exports,

these were instable (CV 66-77 percent) during the period 1991-2000, but were highly

stable (CV 7 percent) during the period from 2001 to 2010.

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Table 4.5.6: Growth rate of ginger exports (percent)

Periods Ginger quantity Value (FJD)

1991-1995 -19.7* 18.0**

1996-2000 16.0* 28.2*

2001-2005 5.2** -1.4**

2006-2010 -3.5** 2.4**

1991-2010 -5.4** 12.5**

Note: **=Statistically significant at 1 per cent level of probability; *= statistically significant at 5 per cent probability; NS =Not significant

Table 4.5.7: Coefficients of variations of ginger exports during 1991 to 2010 (percent)

Periods Ginger quantity Value of ginger 1991-1995 58 66 1996-2000 41 77 2001-2005 22 7 2006-2010 13 7 1991-2010 43 55

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4.5.8 Constraints in production and trade of ginger

(a) High cost of production: Ginger is one commodity that requires a lot of inputs

starting from land preparation till harvesting. Drastic increase in the prices of agro inputs

e.g., fertilizer, chemicals, planting material, decreases the farmers’ profit margins.

(b) Declining soil fertility: Interviewed farmers mentioned that yields have decreased

over the years. It was apparent that soil erosion was the major cause of this problem.

(c) Natural disasters: Natural disasters normally have a substantial effect on ginger

production especially during cyclones and flood and hence lead to rotting of the

rhizomes.

(d) Climate: Ginger crop does well in average climatic conditions. Extremes of climate

affect its growth; lead to low yields and causes high levels of pest and disease incidence.

4.5.9 Summing Up

The analysis presented in table 4.5.8 depicts the situation of ginger crop production and

export in Fiji. The ‘b’ coefficient shows the direction of change in area, yield,

production and export of ginger during the period 1991-2010. The changes were

negative sign indicates decline of area, production and export of ginger over time. The

change in yield has positive sign but its magnitude was insignificant.

This slow growth was due to heavy rainfall affecting flat land cultivation and sudden

withdrawal of assistance to subsistence farmers and lack of project submission for

ginger under Export Promotion Project in 2009.

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Table 4.5.8: Coefficients of linear (Y = a + bT) regression equations of trend lines for ginger crop area, yield, production and export in Fiji.

Dependent variable

Estimate of constant ‘a’

Estimate of coefficient ‘b’

R2

n

Area 206.5* (75.4)

-1.09 NS (6.78)

0.001 20

Yield 18.76* (6.99)

0.410 NS (0.629)

0.02 20

Production 3,518*** (488)

- 45.1 NS (43.9)

0.05 20

Export 1,680*** (239)

- 35.5 NS (21.5)

0.13 20

Note: Figures in parentheses denote standard errors of respective coefficients. *** = Significant at 1 percent level of probability. ** = Significant at 5 percent level of probability. * = Significant at 10 percent level of probability. NS = Not significant.

111

Competition in the open market forced Fiji to reduce its export quota and this forced

exporters to reduce their buying capacity which led farmers to reduce production.

Despite several attempts by the government through renovation of policies, strategic

plans and implementation of programs ,the area, yield and production had shown

declining results. There has been a shift from production of ginger to other crops.

Insecurity of ginger markets coupled by contract arrangement introduced by the buyers

through quota system and too much of reliance on assistance by the government are the

major reasons for this continuous decline. Yield and area effect caused decrease in

ginger production.

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CHAPTER - 5

SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

5.1 Summary

In developing countries such as Fiji, where agriculture is the main stay of people, but its

growth is sluggish, giving priority to agricultural development is essential. It will not

only help alleviate rural poverty but would also support sustainable development of

economy through forward and backward linkages with other sectors.

Effective agricultural development planning requires a thorough understanding of the

agricultural situation of the country, especially the strengths and weaknesses of the farm

production and trading systems.

Hence, keeping in view this gap in the research the present study was undertaken with

the objective to analyse the trends in production and export of five major crop products

of Fiji and to identify constraints faced by the farmers in moving forward. The crops

studied are sugarcane, coconut, taro, papaya and ginger. Time-series linear trend

equations and growth rates were estimated for area, yield, production and export of each

of the crop product for the period 1991 to 2010. The time-series data for the study were

obtained from the government sources. Data about constraints were obtained by a

sample survey of farmers and exporters.

Analysis of data revealed that in Fiji sugarcane area, yield and production were

decreasing continuously at the significant rates. Consequently, the quantity of sugar

exported from the country was also declining over time. Decreasing trend in sugarcane

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production was mainly due to decline in the area as well as yield rate of this crop. As

most of the area under sugarcane crop was under lease from Mataqali (the Fijian clans),

due to expiry of old land leases from 1997 onward there has been exodus of a large

number of sugarcane tenant farmers and their families into informal settlements in the

periphery of urban centres in the country or abroad. Yield per hectare were declining

because sugarcane farming being an intensive mono-cropping system where the same

crop was cultivated on the same piece of land continuously for the past 3-4 generations

resulted in soil fertility decline. Continuous breakdown of sugarcane crushing mills

leads to harvested cane stand on the carts and deteriorate. The analysis of trend revealed

that area and production of sugarcane (and hence sugar exports) would further decline in

Fiji.

As regards coconut crop, its area, production and export had negative trend overtime.

The decline in coconut production was mainly due to the decrease in the area of this

crop. Coconut is a long term (35-40 years) income generating crop. It has about 5 year

gestation period for the farmer to start benefiting from the investment in this crop. The

faster returns and demand of other short duration high-value crops have changed the

mind-set of the coconut farmers forcing them to neglect replanting of coconut crop and

opting for short duration annual crops. Furthermore, as most of the coconut farms are

located in the Maritime Provinces, the farmers have to pay a hefty sum for transporting

their products to markets, as there is no facility for farm gate procurement/collection of

produce. Yields were also declining as coconut trees are old and are very susceptible to

cyclones; it takes them 2-3 years to come back to the normal production after being hit

by a cyclone.

114

In the case of taro crop, during 1991-2010, there was a rapid and significant increase in

its area, yield and production in Fiji. Growth rate of taro export was also positive and

significant. The analysis revealed that in the growth of taro production, the contribution

of yield effect was stronger than the area effect. This positive outcome was due to major

emphasis placed by government on increasing area, and yield of taro to meet the

increasing demand for taro in export markets. The predictor model indicated that there

will be further increases in the production and export of taro.

Similarly, in the case of papaya area, yield, production and export all have increased

significantly during the period 1991-2010.The interaction of effect of area and yield was

the major contributor to the rapid growth of papaya production in Fiji. But papaya

production showed high fluctuations from year to year as this crop is very susceptible to

natural disasters, especially to flooding and cyclones. Poor drainage affects the crop

causing rot. As the majority of the area under papaya crop is under native lease, the

tenant farmers are reluctant to make long-term investments in improving drainage

system on their leased farms. The other major factor that constrained expansion of

papaya crop area was low prices received by farmers. Papaya fruit being a highly

perishable product needs a speedy disposal. As they farmers cannot hold the product

longer they are price takers and the marketing middleman (buyer) decides the price.

The situation of ginger crop was different. Its area, yield, production and the quantity

exported decreased significantly. The main causes of decline in ginger production and

export were high costs of production and transportation. Ginger crop requires a lot of

purchased inputs starting from sowing till harvesting. Continuous increases in the prices

of agro inputs (e.g. fertiliser, chemicals, and planting material) and high transportation

costs decrease farmers’ profit margin forcing them to shift to other, low input crops. To

115

boost production of this spice crop in Fiji, it is essential to provide proper incentives to

the garlic farmers and to develop agricultural marketing infrastructure in the country.

It is concluded that despite negative growth rates in area and production of sugarcane

and exports of sugar, the sugarcane farming will remain lifeline of the Fiji’s rural

economy. Hence, its revival should be given a priority. Similarly, coconut crop is a

strong source of income for the people in the Maritime Provinces and thus its

importance in rural household income and food security should not be undermined in the

agricultural development planning in the country. Taro and papaya are the cash crops

produced for home consumption and export. Area and production these crops have been

increasing steadily which should be further strengthened. Ginger is also a high value

crop and the agro-climatic conditions of Fiji are quite suitable for its production. So,

farmers should be supported by the government in expansion of ginger area and

production.

5.2 Conclusions

During the period 1991-2010, the area, yield, production of sugarcane and the quantity

of sugar exported from Fiji were decreasing continuously at the significant rates. The

decline in area and yield reduced sugarcane production in the country. Area declined due

expiry of land leases and yield declined due to poor management of soil fertility. Similar

was the case of coconut crop. Its area and yield were declining during last two decades

and consequently production and exports of coconut were declining continuously. Main

reason for this was that area under coconut trees was not replanted with this crop.

Another reason was lack of transportation facilities in the outer islands where this crop is

mainly grown. Increasing coconut farm productivity and income will not only ensure

116

food security among rural people but will also contribute to supply reliability and

competitiveness of the coconut industry in the global market.

The area, yield, production and export of taro showed significant increases during the

period 1991-2010. In the growth rate of taro production, contribution of yield-effect

was higher than the area-effect. The positive outcome for this crop was the result of

major emphasis placed by the government on increasing area and yield of taro crop to

meet the increasing demand for taro in export markets.

Similarly, in the case of papaya area, yield, production and export all have been

increasing significantly during the last two decades. The interaction of effect of area and

yield was the major contributor to the rapid growth of papaya production in Fiji. The

major factors that constrained expansion of papaya production were short-term nature of

land leases and the low prices paid by marketing middlemen to the farmers.

In case of ginger crop also, its area, yield, production and the quantity exported had a

negative trend, i.e., all decreasing over the years. High cost of cultivation of ginger crop

was cited as the main reason for reducing farmers’ profit margins thereby forcing them

to shift to other, low input crops.

It is concluded that negative growth rates in area and production of sugarcane crop is not

a good omen. The sugarcane farming which is the lifeline of the Fiji’s rural economy, its

revival should be given a top priority. Similarly, coconut crop is a strong source of

income for the people in the Maritime Provinces and thus its importance in rural

household income and food security should not be undermined in the agricultural

development planning in the country. Taro and papaya are the cash crops produced for

117

home consumption and export. Area and production these crops have been increasing

steadily which should be further strengthened. Ginger is also a high value crop and the

agro-climatic conditions of Fiji are quite suitable for its production. So, the government

should support farmers in expansion of ginger area and production.

All arable land of the country should be fully utilised for crop production, including the

farming areas lying unused after expiry of their leases. Secondly, yield rates of crops

should be improved in the country by enhancing adoption of new farm technologies on

farms by improved research and extension efforts. Finally, agricultural marketing

infrastructure should be improved to facilitate commercialisation and trade of farm

products.

5.3 Recommendations

1. Since sugarcane farming is the lifeline of the Fiji’s rural economy, its revival should

be given a top priority in the agricultural development planning.

2. Coconut farming is a strong source of rural household income and food security of

the people in the Maritime Provinces. Government should encourage farmers to

rejuvenate coconut industry by extending technical assistance to them for coconut tree

planting and replanting especially in the coastal areas of the country.

3. Taro crops production for home consumption and export farmers should be further

encouraged to boost their production.

4. Ginger and papaya are high value crops for which agro-climatic conditions are quite

suitable in Fiji. Government should provide necessary support to farmers for expansion

of production of these crops.

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5. In increasing crop production in Fiji, the most concern should be to increase the yield

by using suitable production technologies as it is difficult to increase area due to the

limitation of this factor. Land lying unused after expiry of land tenure leases should be

fully utilised for crop production.

6. To get more output from the available land resources, crop yields per hectare should

be increased by enhancing efforts to generate new farm technologies and to extend them

to farmers. Knowledge is a powerful source of economic growth.

7. To link farmers with supply chains, a network of roads and communication systems,

and marketing facilities should be built in rural areas of the country.

8. In increase in crop production in Fiji, the most concern should be to increase the yield

by using suitable production technologies as it is difficult to increase area due to the

limitation of this factor.

5.4 Limitation of the Study

In a countrywide macro study like this, the intra-regional variations in time-series trends

of area, yield and production are smoothened due to averaging. A time-series study

using disaggregated data at divisional or provincial level will thorough more insights in

to the agricultural problems identifying the farming locations where the problem is more

acute and appropriate solution could be applied at the local level where the problem

exists. Since such disaggregated data was not readily available for Fiji, this study has

been undertaken using national level macro data only

119

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