Technical efficients of rice production

8/16/2019 Technical efficients of rice production

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DECLARATION

Candidate declaration

We, the under listed, declare that this dissertation is our original work which has not been

presented for any another degree in this university or elsewhere, and that all citations in the work

have been duly acknowledged. The study was undertaken in accordance with the guidelines and

procedure of the Faculty of Integrated Development Studies.

NAME OF STUDENTS ID NUMBERS SIGNATURE

ABDUL-AZIZ KHALID IDS/8087/10 ………………

AMOYAW PORTIA IDS/8284/10 ………………

ASARE-BOATENG MAXWELL IDS/8366/10 ………………

FRIMPONG FORDJOUR FESTUS IDS/8606/10 ………………

SALAM SAFIANU AKUDUGU IDS/8989/10 ………………

SUPERVISOR: Mr. Paul Bata Domanban

SIGNATURE:…………………………..

DATE:…………………………………..


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DEDICATION

This piece of work is dedicated to the families of all group members (authors of this dissertation)

for their kind support, long suffering, and cooperation in our education.


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ACKNOWLEDGEMENT

We are most grateful to the Almighty God for the providence and unprecedented guidance. Had

it not been for His mercies we would not have been able to complete this study.This dissertation

could not have been written without the hard work, wonderful cooperation, moral support, and

routine participation of all members of Group 9 of the 2013/2014 academic year, DEED.

Worth mentioning is the selfless and effective role played by our supervisor, Mr. Paul Bata

Domanban, whose help to us exceeded the responsibility as an academic supervisor.

We are also much grateful to Mr. Benjamin Musah Abu for his unfailing assistance, coaching,

and motivation throughout the work. Our work was almost impossible without you; we say God

bless you and your family.

Also to all lecturers of the University for Development Studies (UDS)-Wa campus especially

those in the Faculty of Integrated Development Studies, we say a big thank you for the

knowledge imparted on us throughout the four years of studies.

Our gratitude also goes to all rice farmers in the Wa West district for giving us the information

required during interviews granted with them. Finally, we express a profound gratitude to our

families and all those who contributed in a way or the other to make this work a success.


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ABSTRACT

Agricultural production determines the efficiency level of households in their farming activities.

Rice farmers in the Wa West district do not use all potential technological resources, thus

making inefficient decisions in their agricultural activities. The key objective of this study is to

estimate the level of technical efficiency of rice production in the Wa West district using the

Stochastic Frontier Approach. The study also attempts to determine the returns to scale as well as

determinants of rice production.

Data was collected from a sample of 200 respondents. Using random sampling approach,

structured questionnaires were used to collect primary data on age, sex, household size, ethnicity,

experience in rice farming, access to credit, and extension contact among others.

The results indicate that, mean technical efficiency is 0.40, implying that the realized output can

be increased by 60% even without any additional resources. Land, seed, and fertilizer, are

significantly positive, indicating that they impact positively on rice farming in the Wa West

district. The study shows rice farming exhibit increasing return to scale. The combined effects of

factors involved in the technical inefficiency model are responsible in explaining the level and

variations in the production of rice farming. The study recommends the periodic visits of agric

extension officers to aid farmers to increase rice production. Also, Ministry of Food and

Agriculture should help to improve the technical efficiency of rice farmers through training,

seminars etc. in order to increase output.


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TABLE OF CONTENTS

DECLARATION .................................................................................................... i

DEDICATION....................................................................................................... ii

ACKNOWLEDGEMENT .................................................................................... iii

ABSTRACT ......................................................................................................... iv

LIST OF TABLES ............................................................................................... vii

LIST OF FIGURES ............................................................................................ viii

LIST OF ACRONYMS ........................................................................................ ix

CHAPTER ONE .................................................................................................... 1

INTRODUCTION ................................................................................................. 1

1.1 Background of the Study .................................................................................. 1

1.2 Problem Statement ........................................................................................... 4

1.3 Objectives of the Study .................................................................................... 5

1.4 Justification of the Study .................................................................................. 6

1.5 Methodology .................................................................................................... 6

1.5.1 Introduction................................................................................................... 6

1.5.2 Data Collection Approach ............................................................................. 7

1.5.3 Data Presentation .......................................................................................... 8

1.5.4 Conceptual framework .................................................................................. 8

Theoretical framework and Estimation Procedure .................................................. 9

1.6 Scope of the Study ..........................................................................................14

1.7 Organisation of the study ................................................................................14

CHAPTER TWO ..................................................................................................15

PROFILE OF WA WEST DISTRICT ..................................................................15

2.1 Introduction ....................................................................................................15

2.2 Physical Characteristics ..................................................................................15

2.3 Demographic Characteristics ..........................................................................18

2.4 District Economy ............................................................................................19


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CHAPTER THREE ..............................................................................................22

LITERATURE REVIEW .....................................................................................22

3.1 Introduction ....................................................................................................22

3.1 Importance and uses of rice .............................................................................22

3.2 Production Potential and National Rice Policies and Development Strategies .22

3.3 Other Studies on Determinants and Technical Efficiency of Rice Farm ..........23

CHAPTER FOUR ................................................................................................26

DISCUSSION OF RESULTS ...............................................................................26

4.1 Introduction ....................................................................................................26

4.2 Socio-Demographic Characteristics ................................................................26

4.3 Determinants of Rice Productivity ..................................................................27

4.4 Level of Technical Efficiency .........................................................................30

4. 5 Returns to Scale of Rice Production ...............................................................31

4.6 Determinants of Technical Efficiency .............................................................32

CHAPTER FIVE ..................................................................................................34

SUMMARY, CONCLUSIONS AND RECOMMENDATION.............................34

5.1 Introduction ....................................................................................................34

5.2 Summary of Major Findings ...........................................................................34

5.2 Conclusion ......................................................................................................35

5.3 Recommendation ............................................................................................36

5.4 Limitations of the Study ..................................................................................37

5.5 Suggestions for Future Search .........................................................................37

REFERENCES .....................................................................................................38

APPENDICES ......................................................................................................41


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LIST OF TABLES

Table 1.1: Variable Name and Units of Measurement…………………………………………..12

Table 1.2: Variable Name and Units of Measurement..................................................................12

Table 4.2: Demographic Characteristics Surveyed Rice Farmers ……………………….….26-27

Table 4.6: Stochastic Frontier Translog Estimates ……………………………………………...28

Table 4.6: Elasticity of Significant Level output………………………………….......................31

Table 4.9: Technical Inefficiency Model Estimates…………………..........................................30


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LIST OF FIGURES

Figure.1.1: Conceptual Framework………….…….……………………………………………..8

Figure 4.2: Technical Efficiency Chart…....................................................................................30


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LIST OF ACRONYMS

ACDEP Association of Church-based Development

Age Age of respondent

AGRA Alliance for Green Revolution in Africa

BOP Balance of Payment

C_D Cobb Douglas

CEO Chief Executive Officer

COLS Corrected Ordinary Least Squares

Cov. Covariance

CRT Availability of credit

CSIR Council for Scientific and Industrial Research

DEED Department of Economics and Entrepreneurship Development

EDU years in education

EFF Experience of farmer

EXT Extension office

FAO Food and Agricultural Organization

FE Fertilizer input

FIDS Faculty of Integrated Development Studies

GRIB Ghana Rice Inter-professional Body

HH Household size

IR Inland Revenue

ISSER Institute Of Statistical Social And Economic Research

LB Labour


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LD Land (farm size)

LDCs Less Developed Countries

Ln Natural Log

MLE Maximum Likelihood Estimates

MoFA Ministry of Food and Agriculture

Mt Metric tons

Mt/Ha Metric Ton per Hectare

NGOs Non-governmental Organizations

NRDS National Rice Development Strategy

NPHC National Pan-Hellenic Council

OLS Ordinary Least Square

Sex Sex of respondent

SFA Stochastic Frontier Analysis

SHP Soil Health Program

SRID Statistics Research and Information Directorate

SS Quantity of seedling

TE Technical Efficiency

TICAD Tokyo International Conference on African Development

UDS University for Development Studies

UN United Nations

US United States


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USAID United States Agency for International Development

USDA U.S. Department of Agriculture

USID US agency for International Development

UWR Upper West Region

WARDA West Africa Rice Development Association

WWDA Wa West District Assembly


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CHAPTER ONE

INTRODUCTION

1.1 Background of the Study

Rice has become a major staple in Ghana in recent times although the crop has been cultivated

for several years. It is an important food for both rural and urban dwellers, and is gradually

taking over from traditional, mainly root and cereal crops, staples (Quaye et al., 2000).

Consumption of milled rice in Ghana went up from below 100,000 Mt to over 600,000Mt

between 1985 and 2003 (Tomlin et al., 2005). Ghana has great potential to expand its present

average rice production area of 89700ha by 200% if its vast area of inland valleys and swamps is

fully exploited (Obeng, 1994). The greatest potential lies in the Interior Savannah zone which

covers almost the whole of the northern half of the country and can only attained through

positive transformation of the sector, including increased availability and use of improved

technologies (Ampofo, 1990). The agricultural sector has benefited from myriad interventions

that seek to improve yield, reduce poverty and increase incomes (ISSER, 2008). Farmers

(including rice producers) have benefited from the dissemination of high-yielding crop varieties

in addition to other complementary technologies (Al-hassan et al., 2004).

Reflecting on the growing importance of agriculture and the rice sector in particular, the Ghana

Rice Inter-professional Body (GRIB) organized the first-ever national rice festival in November

2013. This was aimed at supporting the local rice industry and highlighting the importance of the

rice sector in ensuring food security, reducing poverty, and creating employment in the country.

However, the country’s rice self -sufficiency ratio is only about 30% as of December 2012


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leaving a 70% shortfall. Currently Ghana spends about US$450 million every year on rice

imports to meet its local demand. About 70% of rice is purchased from abroad given the report

by the US Department of Agriculture. According to Leticia (2013), Ghana can produce around

275,000 tons of rice compared to an estimated 600,000 tons that it will purchase from

international sources.

Ghana emerged as a significant rice importer in the mid 1980s coincided with the liberalization

of its economy under the programmes for economic recovery and structural adjustment of those

years. Prior to and following independence in 1957, Ghana had pursued a policy of food self

sufficiency, under which high tariff barriers and import restrictions protected indigenous rice

production, but over the 1995 – 2005 period total rice production has not been stable. From

202,000 tonnes in 1995 the rice output reduced to 142,000 tonnes after nine years. Rice output in

Ghana is also low compared with countries like Vietnam, Thailand and China. Whereas Ghana’s

rice output stood at only 142,000 tonnes in 2005, Vietnam produced as much as 32 million

tonnes of rice in the same year which was as result of advanced technology. Vietnam’s rice

cultivation has been rising at an average of 700,000 tonnes per year in the past five years (FAO,

2006). Despite the downward trend in rice output, the Ministry of Food and Agriculture (MoFA,

2005) indicated that the consumption of rice over the last decade almost doubled.

The Upper West region harvest rice in the October, deplete stock in the month of June and the

households are normally in rice insecurity in the month of May (MoFA, 2006). According to

MoFA (2009), a total of 1,303 farmers cultivated 2754.9 acres of rice in addition to maize under

the Expanded Crop Production Programmed (ECPP). The average yield for rice in the various


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districts of Upper West Region as at 2010 was very minimal. The data revealed that Wa West

district recorded 2.20, Wa East 2.08, Wa municipality 1.40, Lawra 1.60, Sissala East 2.08,

Sissala West 2.10, Jirapa-Lambussie 1.35 and Nadowli 1.66 metric tons per hector (SRID, 2011).

Although local rice production has increase in quality and quantity due to calculated government

interventions much can be done. The Wa West district is remotely located in the western part of

the region. Although 90% of the population is subsistence farmers, a major problem is seasonal

migration during the long period of dry seasons – most natives migrate to southern part of Ghana

to undertake jobs. This has as turning effects on the level of agricultural productivity within the

district. According to the 2010 Annual Crop Survey by RADU on production of selected crops,

rice is produced on 7180 acres of land and an annual output of 7100 metric tons. There have

been considerable contributions from government and NGOs towards increasing rice

productivity within the Upper West Region. Projects such as; Rice Sector Support Project (2009-

2013), West Africa Agriculture Productivity Project(2011- to date), Emergency Rice Initiative

Project(2005-2010) - all providing capacity building to rice farmers as well as ACDEP (2010 - to

date) -provide credit facilities to farmers.

On the production side growth and development of rice production have become completely

dependent on yield improvements in the district. To meet local demand, rice production can be

increased either by increasing rice growing area or by improving the efficiency of existing

resources allocated to rice production. Yield improvement is governed mainly in two ways;

either shifting the yield frontier or by developing and promoting yield-enhancing technologies.

Improving rice productivity can contribute to higher yield and in reducing poverty especially in


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rural areas; increased productivity may also help in increasing the income and food security of

small farmers, who depend on rice.

1.2 Problem Statement

Rice is an important food crop in the Upper West Region of Ghana and its consumption is

growing, particularly among urban dwellers. The importance of rice in the region’s economy is

also seen in its contribution to agricultural GDP and employment. Therefore, as the region and

Ghana as a whole struggle to achieve accelerated growth in food production, increasing the

output of rice has become an important goal. The strategic nature of rice has long drawn the

attention of policy makers who view promoting domestic rice production as a means of reducing

dependency on imports, lowering the pressure on foreign currency reserves, ensuring stable and

low-priced sources of food for people, generating employment and income for rice growers

(Randolph, 1995). Fluctuation in domestic rice production has a direct impact on food security,

especially for the poorest people of Philippines (Koide et al., 2012).

However, the ability of rice farmers in the Wa West district to adopt new agricultural

technologies is affected by farmer and farm characteristics. Examples of such characteristics

include age, household size of rice farmers, level of education, number of years of schooling,

total land area used for rice production, and experience in rice farming. Other characteristics are

extension visits and benefit of credit facility. Over 70% of the rice farmers in the region are

illiterate (regional assembly, 2009). High illiteracy rates affect farmers’ ability to adopt new

agricultural practices and to effectively mobilize and apply production inputs. Rice farmers also

face high input costs (fertilizer, pesticides and machine power) and they lack incentives because


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4. To estimate the magnitude and effects of factors influencing technical efficiency of rice

production.

1.4 Justification of the Study

One of the major factors that affect the increasing government balance of payment (BOP) deficit

is increase in rice importation. The study seeks to determine the factors which affect the

decreased rice productivity and the technical efficiency of rice farmers in the region. Findings

from this study will aid policy makers in formulating right policies that will help increase

domestic rice production, thereby reducing government BOP, as well as increase food security.

According to SRID (2011), Wa West district is the major producers of rice within the region.

The study area was chosen due to the easy accessibility to data. Also as a major producer, there

is the potential to increase annual yield if the right strategies are implemented.

1.5 Methodology

1.5.1 Introduction

This section of the chapter looks at the data collection approach, data presentation, theoretical

framework and estimation procedure.


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1.5.2 Data Collection Approach

Sources of Data

To carry out this research, the study made use of primary data. Cross-sectional data was

collected from 200 rice farmers using structured questionnaires to ascertain relevant information

on factors affecting rice production in the district. Data collected were on age, gender,

educational background, household size, experience of farmer, land size, labour, fertilizer

application, total rice output and land tenure system used in the district. Data was collected in the

Wa West district of the Upper West region. The district was chosen because, in Appendix A2,

the district is the highest with a total output of 2.20 metric tons per hectare out of the region’s

total output of 14.47 metric tons per hectare.

Sample Size and Sampling Approach

A sample size of 200 was used to represent the district. This was used because it is statistically

large for a generalization and due to logistics constraints such as time, etc. The probability

sampling approach was used in this study; specifically the simple random technique was used to

draw respondents. In the words of Miles and Huberman as presented by Punch (2004), “You

cannot study everyone everywhere doing everything.” To attain 200 respondents out of the 208

communities in the district, cluster sampling was used to group these communities into five

zones – via Wa West District Health centre to ensure representativeness of the population. Out of

the five zones, two communities were purposively selected from each. With 10 communities as

the sample frame, 200 rice farmers were administered questionnaires.


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1.5.3 Data Presentation

The Frontier software was used, the results was presented in tables and chart. A stochastic

frontier approach was used to estimate the level of efficiency and determinants of rice

production.

1.5.4 Conceptual framework

Figure 1.1 shows the conceptual framework of the study that link variable to the specific

objective.

Figure 1.1: Conceptual Framework

Efficient Production

Farmer Characteristics Institutional Characteristics Other Characteristics

e. g. Age, Sex, e. g. Credit, Training, e. g. Policy

Education, Experience, Extension contact

Household size.

Inefficient Production

Rice Yield(Output)

Inputs

e.g. land, labour, seed, fertilizer


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In figure 1.1, inputs such as land, labour, seed, and fertilizer determine output levels. Output

level tells whether rice production is efficient or inefficient given farmer characteristics (such as

age, sex), institutional characteristics (such as credit, training) as well as other characteristics

(such as policy).

Theoretical framework and Estimation Procedure

For a long time, econometricians have estimated average production functions. It is only after the

pioneering work of Farrell (1957) that serious considerations have been given to the possibility

of estimating the so-called frontier production functions in an effort to bridge the gap between

theory and empirical work (Aigner et al, 1977). The importance of efficiency as a means of

fostering production has being recognized by many researchers. Efficiency is the extent to which

time, effort and cost is well used for the intended purpose. There are three major types of

efficiency – Technical Efficiency, Allocative, and Economic Efficiency. Allocative Efficiency is

the ability of a farmer to use resources optimally given their respective prices whiles Technical

Efficiency is the ability of a farmer to produce the maximum output from a given set of inputs.

The multiplicative effect allocative and technical efficiency is what is referred to as economic

efficiency.

Empirically, technical efficiency is measured using parametric and non parametric approaches.

Non-parametric approach involves the use of simple mathematical calculations but is limited by

its inability to specify production function and does not account for the noise or stochastic error.

Due to these limitations the study employed the parametric approach. Specifically, the Stochastic


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Frontier Approach (SFA) was used because of its ability to decompose the error term into noise

and stochastic error.

The Stochastic Frontier Production Function as independently proposed by Aigner, et al. (1977)

and Meeusen and Van den Broeck (1977) using a cross sectional data, specified as;

= ; ∗ ∗ (−)……………………………………… . . () Where is the output of farmer , ; denotes a suitable function (e.g., Cobb-Douglas ortranslog), is the inputs, and β represents the unknown parameters to be estimated and is theerror term that is composed of two independent elements, and such that = (−).theterm is a random factor or systematic error accounting for statistical noise (e.g., measurementerrors, extreme weather, omission of significant variable, low rainfall, etc.) – not within the

control of the farmer and is a non-negative random variable associated with farm-specificfactors which contribute to the

ℎ farm not achieving maximum efficiency and ranges between

zero and one.

The maximum potential output for a given set of inputs, which can be expressed as:∗ = ; ∗ ………………………………………………… .(ii)

Thus, the measure of technical efficiency of the ith farm denoted by is defined as the ratio ofthe observed output to the corresponding potential output, which is evinced as:

= ∗ = ;∗( −) ;∗ = p (−)………………(iii)


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This expression demonstrates that the difference between and ∗ is embedded in . If = 0,then = ∗, implying that the production lies on the frontier.

The simple stage maximum likelihood estimation approach was adopted in this study since the

two stage approach violates the distributional assumption underlying the error term.

Although in literature, the Cobb – Douglas production function is commonly used in the

estimation of technical efficiency because of its simplicity. Its restrictiveness of constant returns

to scare makes it not applicable in this study. The translog production function is used instead

because it allows for the combination of square and cross product terms to improve the fit of the

model (Coelli, 1995 and Wilson et al ., 1998).

The translog production function is specified objectively is;

ln = 0 + 3

=1ln Xk і + 12

3

=1 + ln Xk і ln Xjі + і − і ……………………………………………….(iv)

3

=1

Where; Xk і represents the amount of input j used by the ith rice farmer and there is assumption of

symmetry in input cross effects by considering = .


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Table 1.2 shows the names of the variables in equation(), their variables and units ofmeasurement.

Table 1.2: Variable Name and Units of Measurement

Variables Description Unit Of Measurement

CRT Availability of credit GH¢

Age Age of respondent Years

EDU Years in education Years

EFF Experience of farmer Years in rice farming

EXT Extension office 1= extension contact

0= no extension contactGEN Sex of Respondent 1= male

0= female

HH Household size Number

The stochastic frontier estimated equation (v) and equation (vi) in a single stage.

With the Cobb-Douglas production function, the estimated parameters represent output elasticity

of the corresponding inputs. In the translog model (4), the elasticity of output with respect to the

different inputs are functions of the level of inputs involved and generally expressed as:

ln () ln = + + ≠1 ……………………… . .………………………… (vii)

However, when the output and input variables have been scaled by their respective means, the

first-order derivative or coefficient can be interpreted as elasticities of output with respect to the

different input. The sum total of the output elasticity is the estimated scale elasticity which


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measures return to scale for an industry. If the ε > 1, it indicates increasing return to scale, ε < 1,

it indicates decreasing return to scale, while if ε = 1, indicate constant return to scale.

1.6 Scope of the Study

The study focused on identifying the key economic factors affecting rice production, estimating

the level of technical efficiency, measuring the returns to scale of rice production as well as

estimating the magnitude and effects of the factors influencing technical efficiency of rice

production. The study will focus on the Wa West district which is one of the eleven districts of

the Upper West Region.

1.7 Organisation of the study

This study is organised into five chapters. Chapter two of the study deals with the profile of the

study, chapter three covers the literature review, chapter four covers discussion of results and

chapter five contains summary, conclusion and recommendation.


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CHAPTER TWO

PROFILE OF WA WEST DISTRICT

2.1 Introduction

This chapter covers the physical characteristics, demographic characteristics and the district

economy of Wa West.

2.2 Physical Characteristics

2.2.1 Location and Size

Wa West district is one of the communities in the Upper West Region with Wechiau as the

district capital. Wa West district is a community in one of the eleven districts that make up the

Upper West Region created in 2004 by legislative instrument 1751. The district is located in the

western part of the Upper West Region, approximately between Longitudes 9º40’N and 10º10ºN

and also between latitudes 2º20ºW and 2º50ºW. The total area of the district is approximately

1,856 square km. This constitutes about 10 % of the region’s total land area, which is estimated

at 18,478 square km. Based on the location and the nature of the economic activities of the

district, it is the food basket of the Wa Municipality. This means there is a ready market for the

district’s agricultural produce. There are very little commercial and no political activities

between the district and Burkina Faso. The proximity of Wa West District to Burkina Faso

however places it in a good position to take advantage of suggestions made by the “Northern

Development Initiative” in the Northern Development Strategy which proposes the promotion of

a Savannah-Sahel Regional Market amongst other initiatives.


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2.2.2 Topography, Drainage and Geology

The Wa West District topography is gently rolling with a few hills ranging between 180 and 300

meters above sea level. It is drained by one main river – the Black Volta, to the west marking the

boundary between the district and the Republic of Burkina Faso. The Black Volta and its

tributaries is the main drainage system in the District. The Black Volta and its several feeder

tributaries present opportunities for irrigation in the district that can promote all year round

farming. Most of the tributary streams are seasonal, thus disrupting communication during the

rainy season along all the major roads to the District capital.

The soil types found in the district are mostly Leptosols, Lixisols and Vertisols, which makes up

a greater proportion of the soils types found in the entire district. There are also strips of

Fluvisols along the flood plains of the Black Volta as well as sandy loams along some of its

tributaries. The general nature of the soils in district, coupled with the traditional land use

practices and limited rainfall, tend to have adverse effect on crop production. This forces the

youth to look for sustenance elsewhere at the expense of their lives or health.

2.2.3 Climate and Vegetation

The Wa West District lies within the Guinea Savannah Zone which is characterized mainly by

short grasses and only few woody shrubs and trees. Common trees found in the community

consist of drought and fire resistant trees such as baobab, dawadawa, shea trees and kapok.

Commercial tress such as Cashew and Mangoes are also found in the community. The vegetation

is very congenial for livestock production, which contributes significantly to household incomes

in the community. The greatest influence on the vegetation is the prolonged dry season. During


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this period, the grass becomes dry and the subsequent bush burning leaves the area patched and

mostly bears of vegetation. Consequently, the torrential early rains cause soil erosion. Bush

burning reduces the vegetative cover and adversely affects rainfall. Transpiration is reduced

considerably and this affects average annual rainfall totals.

The climate of the district is tropical continental type with the mean annual temperature ranging

between 22.5°C to 45°C. A lesser known and used environmental resource is what is referred to

as diurnal temperature variation. The Wa West District, like most of the other districts of the

three northern regions have the comparative advantage during the months of November to

February (the harmattan period) of having relatively cool night temperatures of between 18°C to

22°C and rather hot day temperatures of as high as 38°C to 40°C. The relatively cool nights are

very suitable for stimulating good flowering in fruits and vegetables, heavy fruit setting and good

ripening and colour turning in fruits. This gives the northern part of Ghana that comparative

advantage of this type of less known climatic resource for generating other economic benefits;

and Wa West District should not hesitate to take full advantage of this. The period between

February and April is the hottest. Between April and October, the Tropical Maritime air mass

blows over the area which gives the only wet season in the year; with the suitable rainfall for

agriculture being effectively only four to five months in a year. The poor rainfall pattern leads to

the migration of the youth, a factor associated with the underdevelopment of the human resource

base of the district.


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2.3 Demographic Characteristics

2.3.1 Population Size and Growth Rate

The National Population and Housing census carried out in 2000 put the community

population at 2627, out of which 1255 are males and 1372 being females.

The 2000 National Population and Housing census results put the entire Wa West District

population at 69,170. This is about 6.20% of the Upper West Region’s total population of

576,583. The population comprises 33,547 males and 35,623 females representing 48.50% and

51.50% respectively and the sex ratio is 94 males to 100 females (Source: 200 NPHC). Using

the growth rate of 1.7%, the projected population for 2009 is 80,502, comprises 39,043 males

and 41,459 females representing 48.50% and 51.50% respectively and the sex ratio is 94 males

to 100 females (Source: WWDA 2009). There is intense pressure on the natural resources

particularly land for agricultural production as well as socio-economic facilities. The growth rate

of the District is estimated to be 1.7 %. This is below the national growth rate of 2.7%.

2.3.2 Reli gion and Ethnici ty

With respect to religious composition, all members of the community are Muslims. The most

predominant tribe in the District is the Brefor with dialectical variations, followed by Waales and

Dagaabas. There are other minor tribes within the district such as the Hausa, Asantes, etc. They

co-exist peacefully and inter-marry.


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2.4 District Economy

The major economic activities in the district include agriculture, commerce rural industry,

tourism and other services. Majority of the people in the district are subsistence farmers. Most of

the women in this community engage in rice production, pito brewing, petty trading and shea

butter extraction.

2.4.1 Agri cultur e

Agriculture accounts for 80% of the Wa West District economy. Most farmers undertake a

combination of crops and animal production. The main crop grown by the farmers in the

community are groundnut. They also cultivate some other crops alongside, some of which

include millet, cowpea and maize. However, productivity of crops is low due to a combination of

factors such as inadequate rainfall, low soil fertility, poor cultural practices and low technology

application. For example rainfall distribution and amount in the district are concentrated in

within the second and third quarters of the year. Since the community is dependent on rainfall

agriculture, the implication of such rainfall pattern is low crop productivity and inability to

produce all year round, hence there is a high risk of food insecurity. Low crop productivity is one

of the major causes of poverty in the community.

This situation calls for the need to enhance the provision of water for dry season gardening and

improved agricultural technologies. It is therefore strongly recommended that irrigated

agriculture should be increased substantially in all parts of Wa West District; by taking

advantage of the perennial water of Black Volta, developing irrigation water bodies from its

feeder tributaries and from the available underground water; as well as rain water harvesting.


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2.3.2 I rr igational In fr astructure

The Wa West District Assembly places a high priority on irrigation facilities to enhance dry

season gardening. There are sixteen dams and dugouts in various communities in the District.

However, few of them are used for irrigation purposes. The total land area under irrigation in the

District is 84Ha. This shows that irrigation is highly underdeveloped in the districts, despite its

critical role in the farming activities and poverty reduction strategies of the people. There is

need to expand the irrigatable area through appropriate technologies like creating small water

retention reservoirs during road construction as well as construction of dug-outs and check dams

along water ways. Such small dams will not only support dry season gardening on a small scale

but also provide water for animals, particularly during the dry season. The advantage of such

small dams located in various communities rather than one big dam is the spread of benefits

across the district.

2.3.3 Market Centers

There are eight major marketing outlets in the district. These are Dorimon, Dabo, Taanvare,

Wechiau, Vieri, Ponyentanga, Nyoli and Gurungu. These markets are organized on a 6-day

cycle. Agro-products and inputs are readily sold and purchased in these markets. Farm produce

in Tanina are mostly taken to Ponyentanga for sale on scheduled market days. Sometimes they

are also brought to the Wa market in case of large outputs. Marketing of food crops and

household commodities is mostly done by women. The purchase and sale of livestock is

however, in the hands of men. Physical access to markets is however poor due to poor road

network and condition. Thus the improvement of infrastructure has the potential of increasing the

district revenue.


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2.3.4 Financial Services

There are no banking and non-banking services in the community. This has made access to credit

very difficult thereby adversely affecting all aspects economic activities. Thus all workers

receive their salaries in Wa and all farmers depend on the profits from the sale of their farm

produce. This has implication for absenteeism.


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CHAPTER THREE

LITERATURE REVIEW

3.1 Introduction

This chapter looks at some works of researchers on the determinants and technical efficiency of

rice farm. It was employed to provide deductive explanations for the factors that rice production

and technical efficiency in other areas. This chapter discusses these factors, their magnitude and

effect on rice output in their respective areas. The chapter also looks at the importance of rice

farming and the necessary condition for rice farming as well as production potential and national

rice policies and development strategies.

3.1 Importance and uses of rice

Rice provides us with proteins, carbohydrates, lipids, plenty of vitamins and minerals. Rice,

highly rich in vitamin B1 is necessary for the brain to absorb glucose and to transform that food

into energy, vitamin A in rice, functions as anti-oxidant in preventing diseases (The health daily,

2011). Rice consumption in Ghana increased from 7.4 kg per caput/annum between 1982 and

1985 to 13.3 kg per caput/annum (MoFA, 1996) resulting in a total annual consumption of 239

400 tonnes of milled rice (i.e. estimated on 18 million population).

3.2 Production Potential and National Rice Policies and Development Strategies

Ghana has great potential to expand its present average rice production area of 89 700 ha by 200

percent if its vast area of inland valleys and swamps is fully exploited (Obeng, 1994). The


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successful control of the black flies which cause onchocerciasis (river blindness), particularly in

the White Volta basin, has opened up for development the vast lands of the fertile Fumbesi

Valley in the Interior Savannah zone, and this has been the main factor allowing for an increase

in rice area from 61 000 ha in 1990 to 89 700 ha in 1996. The government over the years has

introduced a number of policies and strategies to rice production in the country. Some policies

and strategies under the Medium-Term Agricultural Development Programme include; the

exploitation of the vast lands of the inland valleys and swamps, reduced emphasis on

conventional irrigation schemes as well as increased research and technology transfer aimed at

an efficient utilization of agricultural inputs.

3.3 Other Studies on Determinants and Technical Efficiency of Rice Farm

Diagne et al. (2013) studied the production and technical efficiency of rice farmers in the

Senegal River Valley. They obtained technical efficiency scores in the range of 55% to 60% and

estimated that land size, fertilizer, herbicides, credit facilities, farming practices and labour.

Others include storage facilities, seedling and irrigation. Krishna et al (2014) argued that, the

average Filipino rice farmer operates about 1.22 ha farm area ranging from 0.1 to 4.8 hectares,

suggesting a significant variability in farm sizes among rice farmers. The total value of farming

retained by the farmer after harvest is about averagely 109.02 cavan. With the expectation of

higher return from rice farming, total acreage is positively significant factor indicating a 1%

increase in acreage, increases rice production by 0.48%. Farm size is a critical factor associated

with the individual farmer productivity. A Research Paper presented by Nicholas (2010) on

factors determining rice production in Kenya revealed that Paddy is significant at 99%

confidence interval with a positive coefficient of 0.0000896 ton/ha.


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Availability of water also plays a vital role on the performance of an irrigation project and also

indirectly influences the cost of the project. It was observed in Kenya that, for the last 25 years,

the agricultural production has not matched the increasing population. Therefore, development of

irrigation is critical in addressing this challenge despite the high costs involved (Ngigi, 2002).

Chambers and Moris (1973) observed that, planting in dry season reduces technical efficiency of

rice production by 8%. A study by Bogahawatte (2010) on Sri Lanka concluded that, the

proportion of land planted to modern varieties of irrigation was statistically significant at 5%.

For the dry zone lagged rainfall, the proportion of rice area planted to modern varieties was

statistically significant at the either 1% level. The values of the R2 were 0.559 and 0.870 for thewet and dry zones respectively.

Fertilizer usage is another factor that affects rice productivity. In 1981, Food and Agriculture

Organization of the United Nation noted that, after land and water, fertilizer is probably the most

important input leading to increasing yields, and they were responsible for some 55% of the

increase in yields in developing countries between 1965 and 1976. In the Philippines Koirala et

al (2014) noted that, the cost of fertilizer is a positive and statistically significant in explaining

rice production at 10%. Fertilizer cost is negative and statistically significant; indicating a 1% in

total fertilizer cost reduces technical efficiency by 2.85% (Diagne et al., 2013). The amount of

labour hired is another factor that affects rice productivity. Noij and Niemeijer (1988) observed

that, by varying the amount of labour hired, or optimizing the moment at which labour is hired,

they can try to increase paddy yields. The study revealed that, though labour is a determinant of

rice production, the quality of the labour force helps to increase yield significantly.


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Other studies argue that, the level of education of a farmer also affects rice productivity.

Kalirajan and Shand (1985) argued that, even though the level of schooling affects productivity,

the level of education of a farmer is not necessarily significantly related to the level of yield.

Their findings revealed that, formal education of a farmer had an independent effect on yield, but

it was not significant while non-formal education was found to have a significant and greater

influence on yield. Pudasaini (1983) found that, even though education enhances agricultural

production, the way in which it is done differs from environment to environment – that is, in a

technological dynamic agricultural system, education improves farmers’ allocative ability,

enabling them to select improved inputs and optimally allocate existing and new inputs among

competing uses. Adesina and Djato (1996) investigated the extent to which education affects

inefficiency in agriculture using a sample of 410 rice farmer s in northern Côte d’Ivoire. They

concluded that educated farmers are not more efficient than non-educated farmers because the

latter may have an empirical knowledge obtained from cumulative farming experience..

Agricultural extension represents a mechanism by which information on new technologies, better

farming practices and better management can be transmitted to farmers. Kalirajan (1981)

explained that, extension workers’ limited contacts with farmers were responsible for the

difference between the actual and maximum yields. Owens et al. (2001) investigated the impact

of farmer contact with agricultural extension services on farm productivity using panel data

obtained during the period 1993 – 1997 in Zimbabwe. The results shows access to agricultural

extension services raises production by about 15% and differed across individual crop years. In

Nigeria, Ogundele and Okoruwa (2004) computed the average technical efficiency for each rice

farm group at 90% with extension contact positively significant to rice production.


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CHAPTER FOUR

DISCUSSION OF RESULTS

4.1 Introduction

This chapter presents the summary of descriptive analysis, determinants of rice productivity,

level of technical efficiency, returns to scale of rice productivity and determinants of technical

efficiency.

4.2 Socio-Demographic Characteristics

Table 4.1 shows the demographic characteristic of the rice farmers in the Wa West district.

Table 4.1 Demographic Characteristics of Surveyed Rice Farmers.

Characteristics Mean Min. Max. Frequency Percentage (%)

Age: 36.03 18 75 - -18-35 - - - 114 57.0

36-50 - - - 68 34.0

51+ - - - 18 9.0

Sex: - - - - -

Male - - - 151 75.5

Female - - - 49 24.5

Household size: 9.18 1 25 - -

1-5 - - - 35 17.56-10 - - - 103 51.5

11-15 - - - 43 24.0

16+ - - - 14 7.0


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Continuation of table 4.1

Characteristics Mean Min. Max. Frequency Percentage (%)

Religion: - - - - -

Christian - - - 138 69.0Islam - - - 44 22.0

Traditional - - - 16 8.0

Others - - - 2 1.0

Ethnicity : - - - - -

Waala - - - 55 27.5

Dagaaba - - - 140 70.0

Kassenas - - - 1 0.5

Sisaala - - - 0 0

Chakali - - - 1 0.5

Others - - - 3 1.5

Educational level: - - - - -

No Education - - - 141 70.5

Primary - - - 20 10.0

JHS - - - 17 8.5

SHS - - - 19 9.5

Diploma - - - 3 1.5

Degree - - - 0 0

Source: computed from Rice farmers Survey Data, 2013

In table 4.1, majority of the farmers in the district are in their youthful age and most these

farmers have no formal education.

4.3 Determinants of Rice Productivity

The generalized likelihood ratio test specifies that the coefficients of the second order variables

in the translog model are zero meaning that the Cobb – Douglas frontier is strongly rejected. Thus,

the translog stochastic frontier production function is more suitable.


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Table 4.2 presents the estimates of the SFA, indicating the variables, their parameters,

coefficients, standard error and t-ratio. It also shows the significant levels of the variables.

Table 4.2 Estimates for the Stochastic Frontier Translog Model

Variables Parameter Coefficient Standard-Error t-ratio

Constant 0 0.82*** 0.15 5.60Lnlabour 1 -0.02 0.02 -1.14Lnland 2 0.50*** 0.05 9.78Lnseed 3 0.26*** 0.10 2.67Dfertilizer 4 -1.50*** 0.63 -2.37Lnfertilizer

5 1.96*** 0.72 2.73

Dother 6 -0.15** 0.09 -1.67Lnother 7 0.12 0.11 1.090.5()2 8 -0.001 0.038 -0.0140.5()2 9 0.56*** 0.20 2.880.5()2 10 0.42*** 0.18 2.380.5()2 11 -0.83** 0.39 -2.120.5(ℎ)2 12 -0.08 0.09 -0.87Lnlabour * Lnland 13 -0.08 0.07 -1.27Lnlabour * Lnseed

14 0.00007 0.063 0.001

Lnlabour * Lnfertilizer 15 0.19*** 0.07 2.70Lnlabour * Lnother 16 0.14** 0.06 2.20Lnland * Lnseed 17 -0.43*** 0.18 -2.37Lnland * Lnfertilizer 18 -0.57*** 0.23 -2.50Lnland * Lnother 19 0.35 0.32 1.09Lnseed * Lnfertilizer 20 0.13 0.14 0.92Lnseed * Lnother 21 0.14 0.23 0.61Lnfertilizer * Lnother 22 -0.03 0.09 -0.30 N 200

σ2 = (

σ2 +

σ2 ) 0.328*** 22.82

ϒ = (σ2 /σ2) 0.9999*** 444625.4σ2 0.0001σ2 0.3279Statistically significant at levels of * 0.10; ** 0.05; and *** 0.01.


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The coefficients of the fertilizer and othercost (both dummy) are significant at 1% and 5% levels

respectively which show that the estimates would have been biased if they were not included in

the model. Gamma (ϒ) is a measure of level of the inefficiency in the variance parameter; it

ranges between 0 and 1. For the translog model, ϒ is estimated at 0.999, this can be interpreted

as follows: 99.9 percent of random variation in maize production is explained by inefficiency

and only 0.1 is coming from stochastic noise. The input coefficients have a straightforward

interpretation of the input variables since they were scaled before estimation.

The estimates show that, land, seed and fertilizer are positively and statistically significant at 1%

level and therefore they are the major determinants of rice production. This means that, any

increment in these variables will increase affect output positively. For land, a 1% increase in land

size (hector) will increase output by 50%. This implies, for any additional hectare farmed, rice

farmers can increase output by 50%. These findings confirm the conclusions reached by

Ogundele and Okoruwa (2004) that farm size significantly determines levels of technical

efficiency and the results of Parikh and Shah (1995) that land fragmentation leads to technical

inefficiency.

The estimate shows that, fertilizer application is positively significant at 1% level. It is the

highest significant variable of 1.96 the influences rice production in the district, showing that a

1% increase in fertilizer will increase output by 196%. This implies that, if a farmer increases the

bags of fertilizer he or she used in the 2013 planting season by 1%, the farmer will cultivate

output almost twice he or she cultivated. This finding is consistent with the findings of Koirala

(2012) in the study of Determinants of Rice Productivity and Technical Efficiency in the


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Philippines. For seedling, a percentage increase in quantity of seed for sowing will increase

output by 26%. This means that, farmers in the region can increase rice output by 26% if they

add an additional bowl of seed for planting.

4.4 Level of Technical Efficiency

The predicted mean technical efficiency is estimated to be 0.40 in the 2013 production year. This

indicates that on the average, rice farmers produced 40% of the potential output, given the

present state of technology and input level. However, 60% of potential output is not realized.

Therefore, the possibility of increasing rice farming productivity in the district by an average of

60% can be achieved in the short run by adopting best rice farming practices.

Figure 4.1 depicts the level technical efficiency of individual rice farmers grouped into ranges

shown in Appendix A4.

Figure 4.1 Technical Efficiency Chart

0

10

20

30

40

50

60

70

80

90

0-20 21-40 41-60 61-80 81-100

F

R E Q U E N C Y

LEVEL OF EFFICIENCY


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The estimated technical efficiencies for rice farmer in the district range between 0.11 and 0.98.

About 42.5% of the farmers have technical efficiency index above 21 - 40, whereas 9.5% of the

farms have efficiency indices between 81- 98.

4. 5 Returns to Scale of Rice Production

Table 4.4 shows the summation of the partial elasticity of production with respect to significant

input for the homogeneous function which is 2.72. In this case, the production function can be

used to estimate the magnitude of returns-to-scale to rice farming.

Table 4.3 Technical Elasticity of Significant Level Output.

Elasticity with respect to

Land Seed Fertilizer Total

0.50*** 0.26*** 1.96*** 2.72

All are statistically significant at levels of *** 0.01

Constant returns to scale only hold if the sum of all partial elasticity is equal to one. In this study,

land, seed and fertilizer were all positively significant at 1% showing increasing returns to scale.

Therefore, an increase in all inputs by 1% will increase rice yield by more than 2.72%. This

result is consistence with estimate of Sharma and Leung (1998) that had a corresponding

estimate of 1.86.


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4.6 Determinants of Technical Efficiency

In table 4.6, the coefficient estimated for gender dummy is significantly negative at 10%,

indicating that farm decision makers who are males operate more efficiently than their female

counterparts. This might have resulted by the division of labour that assigns a domestic role to

women in Wa West district as noted by Assibey - Mensah (1998).

Table 4.4 shows the various technical efficiency variables, their parameters, coefficients,

standard error and t-ratio.

Table 4.4 Technical Inefficiency Model Estimates

Variables Parameter Coefficient Se t-ratio

Constant 0 1.51*** 0.19 7.94Age 1 0.01 0.01 1.26Gender 2 -0.24* 0.16 -1.54Education 3 -0.019 0.015 -1.26Household

4 -0.06*** 0.016 -4.00

Extension 5 -0.36*** 0.15 -2.44Years of rice 6 0.007 0.009 0.759Credit 7 -0.006 0.207 -0.029Statistically significant at levels of * 0.10; ** 0.05; and *** 0.01.

The coefficient of the extension contact (dummy) was significantly negative at 1%. This

indicates that farmers that received extension visits are more technically efficient than farmers

that did not get any extension service. This was consistent with the findings of Parikh and Shah

(1994) who concluded in Pakistan that extension service was important factor in explaining the

technical efficiency of rice farmers.


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The coefficient of the household size is positively related to technical efficiency and significant

at 1%, suggesting that a large family size enhances technical efficiency on rice production. The

significance of larger household size is to free farmers from scarcity of hired labour for farm

activities. This is consistent with the findings of Al-hassan (2008) in his study of technical

efficiency of rice farmers in Northern Ghana.


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CHAPTER FIVE

SUMMARY, CONCLUSIONS AND RECOMMENDATION

5.1 Introduction

This chapter outlines the major findings of the study, conclusions, policy recommendations,

limitations of the study and suggestions for future research.

5.2 Summary of Major Findings

The frontier results show that, farm size, fertilizer, and quantity of seed were observed to affect

rice output significantly and hence are the determinants of rice production in the Wa West

district. Farm size, land and quantity of seed were significant at 1%. About 70% of the rice

farmers did not apply fertilizer to their rice farm in the 2013 planting season. The maximum land

size for rice cultivation is 10 hectares with a minimum of 0.5 hectare given the mean value of 2.2

hectare. On the average, rice farmers in the district sowed 17.8 bowls of rice seeds per hectare

with a maximum of 61.9 bowls and minimum as 2.5 bowls.

The study found that, rice farmers in the Wa West district are approximately 40% technically

efficient. The highest efficient farmer is approximately 98% technically efficient while the least

is approximately 11% technically efficient.


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The return to scale on rice farming in Wa West district is 2.27 showing increasing returns to

scale in the district. Therefore, an increase in all inputs by 1% will increase rice yield by more

than 2.72%.

The coefficients of gender, household and extension contact is significant from the technical

inefficiency estimates. The coefficient of household is 0.06, extension contact is 0.36 and gender

is 0.24. Household and extension contact is significant at 1% whiles gender is significant at 10%.

They are all positively affecting technical efficiency of rice farmers in the region.

5.2 Conclusion

This study was conducted to initiate a formulation of research and primarily studies on the

analysis of rice production in the Wa West district. Ultimately, it is apparent that, rice production

in region is an important economic activity to indigenes with a very lucrative benefit.

Findings from the study indicated that rice farming in the region is influenced by fertilizer, land,

and quantity of seed. It was also revealed that, majority of the rice farmers agree to fertilizer

usage as a very important factor but fertilizer usage was low among the farmers – because they

cannot afford it though they knew the importance of its usage.

Most of the farmers in the district are technically inefficient. Rice farming in the district is

characterized by increasing returns to scale. Also, majority of the respondents do not have access

to credit facility due to lack of knowledge on how to apply, inadequate collateral and high


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repayment rate among others. Also contact with extension officers also enhances efficiency

among rice farmers.

5.3 Recommendation

The rice industry has played a major role in helping the Ghanaian economy in achieving

economic stability, poverty reduction, and income equality as well as feeding the economy.

Nevertheless, the rice industry faces some challenges that require special attention to overcome

these challenges of the rice industry.

Government has an important role to play in determining rice output. Government should

therefore subsidize the cost of rice farming inputs such as fertilizer and provides farmers with

improved rice seedlings at a very low price. Access to seeds - particularly to varieties with

import substitution potential - needs to be increased.

From the analysis, enough evidence was found to support literature that extension contacts

enhance the technical efficiency of rice farmers in the Wa West district. Therefore the study

recommends that, the Ministry of Food Agriculture should increase the number of extension visit

to rice farmers in the district and also provide training, seminars etc in order to increase output.


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5.4 Limitations of the Study

The study was limited by its inability to include capital as one of its inputs due to difficulties in

measuring the aspect of the capital that was used in the said farming season to yield the rice

outputs.

Also, out of 208 communities within the district, the study analyzed data from 10 communities.

This was due to logistics reasons such as time.

Lastly, the study was unable to test Cobb-Douglas production function against the translog

production function to determine which is suitable for the model.

5.5 Suggestions for Future Search

The study recommends for future studies to measure and include capital as one of the inputs,

include more sample size and test for hypothesis between the Cobb-Douglas production function

and translog production function to determine which of them is suitable for the study.


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Ogundele, F.O., & Okoruwa, V.O. (2004). A comparative Analysis of Technical EfficiencyBetween Traditional and Improved Rice Variety Farmers in Nigeria. African Journal of Economic Policy, 11(1), 91 – 108.

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Al-hassan, S., Sarpong, D. A., & Al-hassan, R. (2004). Allocative Efficiency, Employment andRice Production Risk: An Analysis of Smallholder Paddy Farms in the Upper East Region ofGhana. Ghana Journal of Development Studies, 1(2), 142 – 163.

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APPENDICES

Appendix A1

Crop Production Levels for 2009

Type of Crop maize rice sorghum groundnut millet

2009 output 5850 3500 6270 30260 5040

Source: Wa West District Agricultural Development Unit, 2009

Appendix A2

Total output per hectare of rice cultivation in 2011 for the districts in the Upper West

region.

District Output (Per Hectare) Percentage

Wa Municipal 1.40 9.7

Lawra 1.60 11.1

Wa West 2.20 15.2

Wa East 2.08 14.4

Sissila East 2.08 14.4

Sissila West 2.10 14.7

Jirapa-Lanbussa 1.37 9.3

Nadouli 1.66 11.5

Total 14.47 100

Percentages are group’s own calculation.

Source: MoFA - SRID, 2011


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Appendix A3

Descriptive Statistics of Variables

Variables Unit Minimum Maximum Mean Std. Deviation

Output Bags 1.00 50.00 7.3425 7.38353 Land size hectare 0.5 10.0 2.185 1.5436

Labour Man days 0 19162 2614.25 3291.81

Seed Bowls 1.00 25.00 7.2575 3.93923

Fertilizer Bags 0 12 0.38 1.246

Othercost Gh¢ 0 1152 39.23 118.474

Age Years 18 75 36.03 11.512

Sex Dummy

School Years 0 15 2.58 4.563

Extension Dummy

Household No. of pple 1 25 9.18 4.632

Credit Dummy

Source: computed from Rice farmers Survey Data, 2013

Appendix A4

Technical Efficiency Frequency of Rice Farmers.

Efficiency Frequency Percentage%

0-20 28 14

21-40 85 42.5

41-60 44 22

61 – 80 24 12

81 – 100 19 9.5

Mean Technical efficiency 0.3951

Source: Group calculations

Technical efficients of rice production

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