Study on production efficiency and agricultural risk management the case of major crops in northern vietnam

STUDY ON PRODUCTION EFFICIENCY AND AGRICULTURAL RISK MANAGEMENT: THE CASE OF MAJOR CROPS IN NORTHERN VIETNAM... Graduate School of Bioresource and Bioenvironmental Sciences Department

STUDY ON PRODUCTION EFFICIENCY AND

AGRICULTURAL RISK MANAGEMENT: THE CASE OF

MAJOR CROPS IN NORTHERN VIETNAM

Graduate School of Bioresource and Bioenvironmental Sciences

Department of Agricultural and Resource Economics

Laboratory of Agricultural and Farm Management

STUDY ON PRODUCTION EFFICIENCY AND

AGRICULTURAL RISK MANAGEMENT: THE CASE OF

MAJOR CROPS IN NORTHERN VIETNAM

HO VAN BAC

FUKUOKA, JAPAN

2018

STUDY ON PRODUCTION EFFICIENCY AND

AGRICULTURAL RISK MANAGEMENT: THE CASE OF

MAJOR CROPS IN NORTHERN VIETNAM

By

HO VAN BAC

A Dissertation Submitted to Kyushu University in partial fulfillment

of the requirements for the degree of

DOCTOR OF PHILOSOPHY

in Agricultural and Resource Economics

Supervised by Professor Teruaki NANSEKI, Ph.D Assistant Professor Yosuke CHOMEI, Ph.D

Dissertation Committee:

1 Professor Teruaki NANSEKI, Ph.D

2 Professor Koshi MAEDA, Ph.D

3 Professor Mitsuyasu YABE, Ph.D

KYUSHU UNIVERSITY

2018

SUMMARY OF DISSERTATION

Vietnam has a favorable natural condition for agricultural production, with a large agricultural land accounting for 82.4% total natural area The sector has contributed significantly to the economy in terms of employment (48%), GDP share (18.1%), and food security Especially, agricultural production is essential income source for people living in rural area and the poor in the region with 75% and 90% respectively However, the sector has been facing many challenges such as low productivity and quality, scattered and small scale production, food safety etc Besides, the sector also is very sensitive and vulnerable to various kinds of risks Improving production efficiency and risk management could be seen as feasible measures contributing to the improvement of income for local people in the context

of limited production land expansion and inefficient used resources In Vietnam there have been several studies on production efficiencies of main crops such as rice, vegetable, tea etc However, understanding the risk sources and combination of efficiency and production risk are still limited Moreover, there is not any comparison study on productive efficiency of farmers using propensity score matching approach to control the selection bias Besides, the adoption of eco-friendly production practices such as VietGAP, organic methods are expected to increase household income and reduce concerns from food unsafety But the study on evaluating impact of VietGAP adoption on farmer’s livelihood in Vietnam is rare Thus, the objectives of the study are to: (1) explore the production efficiency of rice and tea farmers and factors affecting inefficient levels; (2) investigate the economics of adoption, source of risks facing by farmers and also understand their management response to the risks

The study was conducted in northern Vietnam where agricultural production plays

an important role in household’s income sources Tea and rice are two of major crops of the region and selected fort this study because of their representative and dominant importance While rice crop is mainly produced to serve household’s demand or self-sufficiency, tea plantation is grown as a commercial crop and provide cash income for other daily demands

of households At first location was purposely selected based on representative characteristics for rice and tea production areas, then rice and tea sampled farmers were randomly chosen from that province Total 120 rice farmers and 326 tea farmers were used to analyze in the study To achieve the purpose of the research, we applied several models to fit with specific objectives Stochastic frontier approach (SFA) was used to analyze production and profit

efficiency of farmers, while principal component analysis (PCA) and multiple linear regression were applied to determine the sources of risk and farmers’ response to the risks Farmers’ decision to adopt new practice was analyzed using probit regression model The findings of the study were derived from analyzing cross-sectional data of rice farmers and tea farmers collected in study area

The findings of chapter 2 and 3, analyzing productive efficiency of rice and tea production, indicate that there are still potential rooms for improving efficiency with given inputs and technology through the use of better practice production methods or more efficient decision In details, technical efficiency based on the SFA analysis with average score of 88 percent indicates that rice farmers could improve their technical efficiency for about 12 percent with given inputs and technology by improving farmer’s resource use efficiency The result also revealed that reducing technical inefficiency of rice farmers could be done by enhancing educational levels, and land consolidation While tea farmers have the potential of increasing their profit efficiency for about 25 percent Further analysis indicated that investing active irrigation system, joining cooperatives/production groups and good extension service are major factors for improving the tea farmers’ profit efficiency Notably, comparison the profit efficiency between two groups revealed that “safe” tea production practice (VietGAP) could achieve higher efficiency than conventional tea production practice

Chapter 4 and 5 determine factors underlying the probability of tea farmer’s decision

to adopt the new production practice and economic effect of VietGAP tea production on households’ income In order to achieve the purpose, we analyzed two groups of sample, namely adoption and conventional one The finding shows that farmers with better or more advantageous production features are more likely to adopt new production practice Positive incentives affecting both conversion decision and more farmland allocation of tea farmers include number of household members, tea farm size, ratio of tea income over total household income, access technical information on new production practice from extension agencies and using labor-saving machinery in tea production Furthermore, with the aim of estimating the casual effect of VietGAP adoption on farmers’ livelihood in Vietnam, PSM was employed The result indicates that farmers adopting VietGAP tea production received economic benefits with higher income in comparison with conventional tea farmers This also implies that VietGAP tea production should be supported for diffusion The premium

benefit is attributed to better price and higher tea yield of farming practice under VietGAP standards

Perception of farmers’ risk sources and their management response are an important part of the study And its detailed contents are presented in Chapter 6 Descriptive statistics, PCA, and multiple linear regression were applied to determine the risk sources and also find socio-economic factors influencing the farmers’ risk perception and their management response The result of descriptive analysis indicates that there are 17 sources of risk that perceived and listed by tea farmers in the study area The analysis result indicates that price volatility, disease risk and an increase of production cost are the most serious in farmer’s perception as single risks Moreover, there are no differences existing in farmer’s risk perception between VietGAP and conventional tea farming systems Analyzing variables affecting on risk perceptions indicates that agricultural educated farmers were found to be related to lower worries and risk perception Besides that, farmers with main occupation involving in farming activities worry more about production risk, yield and quality risk For risk management response, farmers considered pest and disease prevention, production cost minimization as the most important measures to limit damages from risk sources above

In short, the result of the study highlighted that there is a scope for further increasing efficiency scores of tea and rice farmers in the study area More efficient resource allocation decision or better production management skills could lead to improve productive efficiency Moreover, conversion in tea production was promoted by economic incentives and adopting VietGAP tea production practice also contributed to increase the profit efficiency and households’ income of farmers Thus, it is important that interventions and government support should aim at improving current production efficiency and expanding the conversion Lastly, agricultural production is exposed to various types of risks based on farmers’ perception In which variability of output price, disease risk and increase of production inputs are perceived as the most serious risks To reduce risks for farmers, stabilizing market price

of output and production inputs, preventing disease risk with technical education programs that government should support for farmers would be meaningful

Keywords

Production efficiency, stochastic frontier, principle component analysis, risk source, management response, major crops, Vietnam

I am deeply indebted to the Ministry of Education, Science, Culture, and Sports of Japan (MEXT scholarship) for the great opportunity and providing financial support for my studies in Japan My special thanks are given to Kyushu University staffs for providing research facilities upon which the successful completion of this dissertation have critically depended

I am grateful to Thai Nguyen University of Agriculture and Forestry and my colleagues

in Vietnam, who always support and encourage me during my study period in Japan

I wish to extend my appreciation to the households and staffs at Department of Agricultural and Rural Development from Thai Nguyen province, Vietnam on their hospitality and kind collaboration helped me doing field survey successfully Without their assistance and cooperation in providing precious information, the study would not have been possible

I would like to thank all friends in Kyushu University, and special thanks for colleagues

in the Laboratory of Agricultural and Farm Management for their sharing of knowledge, skills and helping during my study period

Last but not least, special appreciation is given to my wife PHAM THI THANH HUYEN for her constant supporting, encouraging, kind understanding and together taking care of

our son HO GIA BAO during my study period I am very grateful to my lovely parents and all relatives for always understanding and encouraging me during the time for doing the research Finally, I wish to thanks everyone who has helped and encouraged me to strive for academic excellence

HO VAN BAC

Fukuoka, September 2018

Table of Contents

SUMMARY OF DISSERTATION i

ACKNOWLEDGEMENTS iv

LIST OF FIGURES ix

LIST OF TABLES x

ABBREVIATION xi

CHAPTER 1 INTRODUCTION 1

1.1 Background information 1

1.1.1 Agricultural sector 1

1.1.2 Major yearly-planted crops 3

1.1.3 Major perennial plants 4

1.2 Production efficiency, risk and VietGAP adoption in Vietnam 7

1.2.1 Production efficiency 7

1.2.2 Linkage between agricultural risk and efficiency 9

1.2.3 The situation of VietGAP adoption 10

1.3 Problem statement 11

1.4 Research objective 13

1.5 Organization and structure of the dissertation 13

1.6 Selection of study area 15

CHAPTER 2 PRODUCTIVE EFFICIENCY OF RICE FARMERS AND ITS DETERMINANTS 17

2.1 Introduction 17

2.2 Methodology 18

2.2.1 Overview of efficiency 18

2.2.2 Techniques of efficiency measurement 19

2.2.3 Analytical framework 21

2.2.4 Data collection 22

2.3 Results and discussion 23

2.3.1 Descriptive statistics of variables 23

2.3.2 Estimation of stochastic frontier production function 24

2.3.3 Input elasticity and its responsiveness to rice yield 25

2.3.4 Frequency distribution of technical efficiency 26

2.3.5 Analysis of determinants of technical inefficiency 27

2.3.6 Estimation of potential rice yield 29

2.4 Conclusions and recommendations 29

CHAPTER 3: PROFIT EFFICIENCY OF TEA FARMERS AND ITS DETERMINANTS 31

3.1 Introduction 31

3.2 Methodology and data collection 32

3.2.1 Measurement of production and profit efficiency 32

3.2.2 Impact evaluation approach 34

3.2.3 Empirical model 34

3.2.4 Propensity score matching 36

3.2.5 Description of used variables 38

3 2.6 Study area and data collection 39

3.3 Results and discussion 40

3.3.1 Socio-economic characteristics of tea farmers 40

3.3.2 Estimated result of profit frontier function 43

3.3.3 Factors explaining the profit efficiency of tea farmers 45

3.3.4 Distribution of profit efficiency and average treatment effect 47

3.3.5 Propensity score for VietGAP tea adoption 47

3.4 Conclusions and recommendations 50

CHAPTER 4 VIETGAP TEA PRODUCTION AND DETERMINANTS OF FARMER’S ADOPTION 52

4.1 Introduction 52

4.2 Methodology 53

4.2.1 Model specification 53

4.2.2 Variable selection in the model 55

4.3 Results and discussion 56

4.3.1 Comparative statistics of used variables 56

4.3.2 Factors affecting conversion decision of tea farmers 57

4.3.3 Factors influencing farmers’ farmland allocation 60

4.4 Conclusions and recommendations 63

CHAPTER 5 ASSESSING EFFECT OF VIETGAP TEA PRODUCTION ON

FARMER’S INCOME 65

5.1 Introduction 65

5.2 Methodology 66

5.2.1 Conceptual framework for VietGAP tea adoption 66

5.2.2 Econometric models for impact assessment 66

5.2.3 Specification of econometric models 67

5.3 Results and discussion 68

5.3.1 Descriptive statistics of variables 68

5.3.2 Econometric estimation 70

5.4 Conclusions and recommendations 73

CHAPTER 6 FARMER’S RISK PERCEPTION AND THEIR MANAGEMENT RESPONSES 75

6.1 Introduction 75

6.2 Methodology 76

6.2.1 Data collection 76

6.2.2 Theoretical framework and analysis technique 77

6.2.3 Description of variables used in the regression model 77

6.3 Results and discussion 79

6.3.1 Farmer’s perception on risk sources 79

6.3.2 Risk perception in relation to farm and farmer characteristics 83

6.3.3 Farmers’ perception on risk management 85

6.4 Conclusions and recommendations 87

CHAPTER 7 CONCLUSIONS AND POLICY IMPLICATIONS 88

7.1 Main conclusions 88

7.2 Policy implications 90

7.3 Study limitation and future research 91

REFERENCES 93

LIST OF PUBLISHED ARTICLES 106

LIST OF RELATED PRESENTATIONS 107

APPENDIX 108

LIST OF FIGURES

Figure 1 1 Planted area of major crops in Vietnam (1000 ha) 3

Figure 1 2 Planted perennial area of Vietnam 5

Figure 1 3 Planted tea distribution in Vietnam 5

Figure 1 4 Proportion of tea production among regions in Vietnam 6

Figure 1 5 Variability of tea yield in Vietnam 7

Figure 1 6 Overall structure of the dissertation 14

Figure 1 7 Map of study area 16

Figure 3 1 Density distribution of propensity scores……… 49

LIST OF TABLES

Table 1 1 Land statistics of Vietnam 1

Table 1 2 Land use structure in Northern mountainous region of Vietnam 2

Table 1 3 Structure land use of MNR 4

Table 2 1 Descriptive statistic of variables in the model……… 23

Table 2 2 Estimated parameters of stochastic frontier production function 25

Table 2 3 Frequency distribution of technical efficiency 27

Table 2 4 Determinants affecting technical inefficiency 28

Table 3 1 Variable definition of used models ………38

Table 3 2 Descriptive statistics of tea production practices 40

Table 3 3 Comparative statistics of model variables 42

Table 3 4 Estimation result of profit efficiency among tea farmers 44

Table 3 5 Factors affecting profit efficiency of tea farmers 46

Table 3 6 Frequency distribution of profit efficiency (PE) 47

Table 3 7 Logit estimates of the propensity to adopt VietGAP tea production 48

Table 3 8 Estimation of average treatment effects on the treated 49

Table 4 1 Definition of variables used in the models……….56

Table 4 2 Descriptive statistics of explanatory variables in the model 57

Table 4 3 Factors influencing farmer’s conversion decision of tea productions 58

Table 4 4 Marginal effects of factors associated with farmer’ adoption 60

Table 4 5 Factors affecting farmer’s farmland allocation 61

Table 4 6 Marginal effect of factors associated with allocation 62

Table 5 1 Basic features of two tea production practices ……… 69

Table 5 2 Coefficient estimation for adoption of VietGAP tea production 70

Table 5 3 Test of matching quality 71

Table 5 4 Balance condition 72

Table 5 5 Estimation of treatment effects (ATT) 73

Table 6 1 Statistics of variables used in multiple linear regression ………78

Table 6 2 Mean score and rank for risk sources perceived by tea farmers 80

Table 6 3 Varimax rotated factor loading for risk sources 82

Table 6 4 Estimation of multiple linear regression model for risk sources 83

Table 6 5 Mean score and rank for risk management 85

Table 6 6 Varimax rotated factor loading for risk management 86

ABBREVIATION

ATT: Average Treatment Effect on the Treated

ATE: Average Treatment Effect

ATU: Average Treatment Effect on the Untreated

AseanGAP: Asean Good Agricultural Practices

DEA: Data Envelopment Analysis

FAOSTAT: Food Agriculture Organization Statistics

FDA: Food and Drug Administration

GlobalGAP: Global Good Agricultural Practices

GDP: Gross Domestic Product

GSO: General Statistic Office of Vietnam

HACCP: Hazard Analysis and Critical Control Points

KM: Kernel Matching

MLE: Maximum Likelihood Estimation

MONRE: Ministry of Natural Resource and Environment

NMR: Northern mountainous region

NNM: Nearest Neighbor Matching

OLS: Ordinary Least Square

PSM: Propensity Score Matching

PE: Profit Efficiency

PCA: Principal Component Analysis

QD TTg: Prime Minister’s Decision

RM: Radius Matching

SFA: Stochastic Frontier Approach

TE: Technical Efficiency

VietGAP: Vietnamese Good Agricultural Practices

UN: United Nations

WTA: World Tea Association

Table 1 1 Land statistics of Vietnam

Source: Ministry of Natural Resource and Environment, 2016

Agricultural export increased consistently over years and bring in a substantial positive trade balance The major agricultural export products are rice, rubber, coffee, cashew nuts, fishery and forestry products In 2011 the total value of export reached $25 billion that doubled the export value in 2007 (JICA, 2013)

Although agriculture has achieved significant achievements contributing to poverty reduction, social economic development and food security of Vietnam, there are still many existing challenges and constraints The first one is unstable agricultural development and less competitiveness in world market Small production scale and scattered agriculture has led to high production cost Moreover, food safety issue and low production efficiency are becoming emerging and increasing concerns in agriculture Besides, support services and industry in agricultural development is less developed Most of exported agricultural commodities are under raw and less processed products As

a result, added value and product quality are quite low compared with other nations’ products In agriculture, cropping accounted for a high proportion (more than 50%) Of which, rice production is still the most important crop (MARD, 2009)

Table 1 2 Land use structure in Northern mountainous region of Vietnam

Northern mountainous region of Vietnam (NMR) has advantage of forestry production with about 2.1 million ha, accounting for 71.4% of total agricultural land of the region The agricultural production land covers about 28% According to the plan of agriculture and rural development (2011-2020) issued by MARD (2009), the NMR will focus on forestry development and advantageous industrial crops such as tea, coffee (Arabica type), maize, lychee, soybean etc

1.1.2 Major yearly-planted crops

In Vietnam, rice production takes the very high land proportion, accounting for 59.2% of total annual cropping land area (MONRE, 2016) Over the past 10 years (2007 – 2016), total sown rice area increased consistently, reached approximately 8 million ha

in 2016 (GSO, 2018) The figure 1.1 also indicates that rice production area is much more than than other crops in combination including maize, peanut, soybean, cotton

Figure 1 1 Planted area of major crops in Vietnam (1000 ha)

Source: General Statistic Office of Vietnam, 2018

Northern upland area of Vietnam has about 2.1 million ha of agricultural land area, in which yearly-planted area is about 77% And rice production is also an important crop, accounting for 35.4% of total cropping land area of the region While perennial cropping areas such as tea, fruit, coffee (Arabica) … accounts for about 23% of total agricultural land of the region (MONRE, 2016) In the region, more than 90% people out

of about 11 million people are living in rural area while agricultural activities such as cropping, animal husbandry, forest economics are their main income Notably, rice production still takes an important role in household’s income source, accounting for about 25% Besides, rice production is not for commercial purpose or export, but rice self-sufficiency also contributes to food security in the region where transportation system is still very difficult compared with flat area due to hilly and complex topography (Bac et al., 2013)

Table 1 3 Structure land use of NMR

Source: Ministry of Natural Resource and Environment, 2016

1.1.3 Major perennial plants

The trend over the last ten years of production are presented below for the major perennial plants in Vietnam There has been a major expansion of rubber planting area, while coffee and pepper planted areas has rose moderately Tea planted area remained fairly steady over the years

Figure 1 2 Planted perennial area of Vietnam Source: General Statistic Office of Vietnam, 2018

Vietnam is amongst few nations in the world that have advantages of natural and climatic conditions for tea production (SOMO, 2007) Tea production is taking place in

39 out of 64 provinces all over the country with total 130 thousand ha NMR has the largest tea production area in comparison with other four regions of Vietnam, with about

93 thousand ha accounting for 72% of total planted tea area of Vietnam

Figure 1 3 Planted tea distribution in Vietnam

Similarly, the region also provide the highest tea production quantity of Vietnam,

accounting for 66% of total produced tea quantity

Figure 1 4 Proportion of tea production among regions in Vietnam

Source: General Statistic Office of Vietnam, 2011

Tea production plays an important role in both cultural and economic aspects In Vietnam tea plantation has a long history and tea drinking custom, dating back about 3000 years (Tran, 2008) In 2012, tea production has contributed to total exported value of $224.8 million, with more than 146.8 thousand tons of exported tea products (FAO, 2012b) The sector also attracts about 400 thousand households involving in production and relevant activities for their income and livelihood In total, tea sector provides employments for about 1.5 million people (SOMO, 2007)

Figure 1 5 Variability of tea yield in Vietnam Source: General Statistic Office of Vietnam, 2014

1.2 Production efficiency, risk and VietGAP adoption in Vietnam

Production efficiency is composed of two components including technical efficiency and allocative efficiency The purely technical or physical component is defined as the farmer’s ability to avoid waste during production In other words, a farmer uses the given inputs to create an output as high as possible, or produce a given output by applying inputs as low as possible Thus, the target of an estimation of technical efficiency

is to find solutions to increase output or decrease inputs in the context of available

Vietnam's tea yield

conditions While the allocative or price component is determined by combination of inputs and outputs in the optimal level in term of considering market prices Measuring technical efficiency implies use of input and output quantity without introducing their prices Technical efficiency can also be further decomposed into three subcomponents, which are scale efficiency (the potential productivity gain from achieving the optimal size

of a firm), congestion (increase in some inputs could decrease output), and pure technical efficiency (Farrell, 1957)

Economic efficiency involves in increasing output without using more than conventional inputs The use of existing technologies is more cost-effective than applying new technologies if farmers currently cultivate their products inefficiently with current technologies (Shapiro, 1977) Economic efficiency can be classified into two types: technical efficiency and allocative efficiency Technical efficiency measures the ability

of a farmer to achieve maximum output with given and obtainable technologies While allocative efficiency tries to capture a farmer’s ability to apply the inputs in optimal proportions with respective prices (Farrell, 1957, Shapiro, 1977) The technical efficiency (TE) of a firm always varies from 0 to 1 value (0 ≤ TE ≤ 1) If TE is equal to 1, the firm produces with full technical efficiency For instance, the firm could achieve full technical efficiency

Production efficiency is considered as means of fostering production, thus large number of studies has focused on agricultural efficiency (Thiam, 2001) In Vietnam, agricultural sector has contributed significantly to the economic growth, food security, social stability and poverty reduction Thus, improving the sector efficiency also receives much attention from Vietnam government and scientists In research aspect, there are few researches on production efficiency of crops such as rice, tea, vegetable etc Almost of studies found that Vietnamese farmers did not operate at fully efficient level (Hong et al., 2015; Bac et al., 2013; Tran, 2008; Vu, 2005) This implies that there is a significant potential for farmers to reduce their costs by increasing efficiency Moreover, efficiency improvement becomes more important in context of limited land source Also, applying technology requires more capital investment and longer time Another constraint for higher technology application is that agricultural production in Vietnam is characterized

by scattered and small scale production

1.2.2 Linkage between agricultural risk and efficiency

Production could be defined as a process of transforming inputs such as land, labor, capital, fertilizer etc into output such as goods and services This process is not only applied in agricultural production, but also in other production sectors In other words, production activities are generally linked closely to natural conditions and environment in which farmers operate In agriculture, production process is subject to many uncertainties and risks Any producers’ decision is closely linked with various potential outputs with different probability The producers or farmers could not control events, including weather, market, policy, but these factors have direct effects on returns from farming activities and businesses In the context, it is important that farmer has to manage farming risk as part of farm operation in general In response to the multiple possible effect of those events, risk management strategies for farming systems may include decisions on-farm, changes in structure, use of market instruments, government support, and diversification of farming income sources A standard approach to analyze aspects of risk management response involve in 3 steps The first step is to determine or measure the risk source and possible variability The next one is select the optimal risk management tool based on this information Finally, appropriate government policies are designed to improve the risk management strategy (OECD, 2009) Another approach in risk analysis is called as holistic approach In this approach, the linkage among three sets

of element is considered as multiple relationship (not linear as in standard approach above)

As a certain part of agricultural production, risk study has been received many attentions from researchers Thus, literature in this study field is abundant Agricultural production is exposed to various sources of risks and uncertainties (Akcaoz and Ozkan, 2005) Similarly, agricultural production in Vietnam is also affected by those risky factors Risk types and uncertainties are not uniformly spread over all farmers due to complexity and change of natural and climatic conditions (Riwthong et al., 2017) Risk source is very diversified and can be grouped into five sources of risk namely production risk, marketing risk, financial risk, legal and environmental risk, human resource risk (USDA, 1997) The relationship between production risk and efficiency was studied by Tiedemann (2013) The results also indicate that output variability in German organic and

conventional farming is mainly caused by production risk Since risks have negatively affected production output of farmers, it is very important for farmers to identify and manage the risks (Drollette, 2009)

1.2.3 The situation of VietGAP adoption

As the same with many other Asian countries, the VietGAP adoption was motivated by the importance of GlobalGAP that is one of the most important private standards in the area of food safety and sustainability (Nabeshima, 2015) Besides, conventional agricultural production has been facing many challenges because excessive use of pesticides and chemical fertilizers has led to extremely negative impacts on human health and environment Together with increasing concerns on food safety from domestic consumers, Good Agricultural Practices (GAPs) was encouraged to apply in agriculture Basically, GAP principle is a set of standards and guidelines which must be applied to all phases of production from field selection, pre-plant field preparation, production, harvest and post-harvest (FDA, 1998) To fit with specific conditions of Vietnam’s agriculture, the Vietnamese government has tried to initiate its own Good Agricultural Practice development, called Vietnamese Good Agriculture Practice (VietGAP), based on the Hazard Analysis Critical Control Points (HACCP) and principle of AseanGAP On 28 Jan 2008 Ministry of Agriculture and Rural Development of Vietnam (MARD) issued the decree No 379/QD-BNN-KHCN on VietGAP implementation VietGAP was considered as the main standard, procedure and guidelines for production of safe fruit and vegetables The aim of VietGAP adoption is to prevent and minimize the risk hazards which often occur in production, harvesting and post-harvesting processes of fruit and vegetables Adopting GAP and/or safe standard package are also expected to return producer or farmers with economic benefits such as increasing and/or stabilizing revenue, reducing average costs, improving market access, reducing vulnerability to poor agricultural practices as well (Hobb, 2003)

Although VietGAP adoption has returned a wide range of practical benefits, the number of farmers who are certified VietGAP has not been high yet Several barriers are attributed to the limited spreading of VietGAP adoption in Vietnam The first one is low popularity of VietGAP in compared with other standards in the market as GlobalGAP

Moreover, this domestic standard has not been yet recognized internationally Thus, farmers or producers has no incentives to invest more on less credible certification The next reason is that adopting VietGAP requires higher level of infrastructure This seems

to be more difficult for most of Vietnamese farmers who have very small land areas (0.25

ha on average) An other important reason is high cost for applying fro and getting VietGAP certificates for most of farmers or production firms The high cost does not only limit new producers to apply the standards, but also discourage farmers to renew their certificates (Nabeshima, 2015)

1.3 Problem statement

Agriculture has achieved very impressive growth over the last two decades, but Vietnam is still a developing country with low average income Although agricultural contribution to Vietnam’s GDP tends to decrease due to faster increase of industry and services, but the agricultural sector remains an important component to the economy Moreover, in Vietnam about 65.5% of population is living in rural area and agricultural activities are still main income sources of most of rural households With remarkable achievement in agricultural development, national poverty rate has been declined from 58.1% in 1993 to 13.5% in 2014, many challenges still exist Most of the poor are living

in rural areas and also heavily rely on agricultural production Especially, rate of ethnic minority is 35.7%, but the rates among some groups are extremely high: La Hu 84.9% and H’Mong 82.9% (UNDP, 2017) In addition, the northern mountainous region of Vietnam has the highest poverty rate amongst regions (GSO, 2018) Thus, agriculture development, rural and farmers are under special attention of Vietnam government

Over the last two decades, impressive increase in Vietnam agriculture has been partly motived by planting land expansion Up to date horizontal growth seems to reach its limitation because the availability of undeveloped agricultural land in Vietnam is very limited Moreover, Vietnam’s population density is considered as one of the highest ones

in the world This mean that there is no opportunity for horizontal expansion of cropping Findings of previous studies indicate that Vietnamese farmers are not fully efficient for many cropping activities such as rice, tea, vegetable etc Thus, improving production efficiency and optimization of land production is a key factor when assessing growth

goals recognized by Vietnam government in coming years (JICA, 2013) In 1999, the Vietnamese government established a tea production development plan for the period of 2005-2010 (Decision 43/1999 QD-TTg) Of which objective of its development plan was

to increase production, export turnover and create employment opportunities for farmers who their income source heavily depends on tea production The implementation of this policy was expected to reduce poverty rate in the uplands tea producing areas, which are often poor mountainous regions with small scale farming, and limited off-farm income opportunities In addition, other important policy measures also were implemented to promote the development of the tea value chain and strengthen greater access to market for the rural poor farmers such as “the law of Private Enterprise” which was promulgated in

1990, and “the Enterprise Law” which was enacted in 1999 and revised in 2005

Agricultural activities are generally linked to natural conditions and environment

in which they operate And the sector is often characterized by high variability of production outcomes due to production risk The risk sources are also closely associated with negative outcomes originating from unpredictable biological, climatic and price variables that is not in control of agricultural producers (WB, 2005) In Vietnam, agricultural production is also under those situations Besides, Vietnam agriculture is characterized by small scale and scattered production with low adoption of technology Thus, agricultural productivity and product quality is not high, less competitive in the market High technology application and managing risk sources are very important in increasing agricultural production and farmer’s income

The start of VietGAP standards had been considered as indispensable measure to issues of food safety in Vietnam that originated from increasing concerns of consumers

in both domestic and international market The safe production standards called Vietnamese Good Agriculture Practices (VietGAP) was issued by MARD in 2008, and was established in GlobalGAP, ASEAN Good Agriculture practices and Hazard analysis and critical control points It is also considered as eco-friendly production practice because of maximal usage of organic component in cultivation and protection (Ha, 2014)

At first the standard package was targeted to vegetable production in Vietnam, then it was opened to apply in fruit and tea production in 2009 The applying VietGAP standards is expected to give farmers with more economic values and reducing production risks

through premium price, better access to market and lower average production cost However, in reality spreading of VietGAP adoption has not yet been high as expectation Also, farmers have different points of view on economic value on adopting this standard package A large number of studies have been focused on production efficiency, but there are few researches on production efficiency of crops adopting VietGAP, and its impact

on household income

1.4 Research objective

From statements above, overall objective of the study is to analyze the current level of production efficiency of tea and rice farmers, contribution and importance of VietGAP tea production for livelihood of farmers, and risk sources facing farmers and their management response in northern Vietnam The specific objectives of the study are

to (1) explore the production efficiency of rice and tea farmers, and factors affecting inefficient levels; (2) investigate the economics of adoption, farmer’s perception on sources of risks and also understand their management responses

To achieve the overall objective, three main research questions need to be investigated:

1 Do tea and rice farmers operate at fully efficient levels or is there any potential for improving farmer’s production efficiency? And which factors have effects on improving production efficiencies of farmers?

2 How does VietGAP tea production affect household’s income in the study area? And what are determinants for shifting from conventional to VietGAP tea production?

3 What is source of risks facing by farmers and how do they respond to those risk sources?

1.5 Organization and structure of the dissertation

The content of study consists of 2 main objectives and is organized into 7 chapters Objective 1 covers chapter 2 and chapter 3, while chapter 4, 5 and 6 belong to the objective 2 The detail of each chapter is as follow The chapter 1 with title “Introduction” presents general information of agricultural sector, major crops and perennial plants, problem statement and objective of the study as well While detailed analysis on current level of production and profit efficiency of rice and tea farmers would be found in chapter

2 and chapter 3 respectively Moreover, determinants of improving technical and profit

efficiency for farmers will also be included in these chapters Chapter 4 will focus on analyzing factors affecting farmers’ decision to adopt VietGAP tea production Contribution and importance of VietGAP tea production on household’s income will go into chapter 5 Farmer’s risk perception and their risk management response is one of important components of the study that will be detailed presented in chapter 6 Finally, main findings of the research and policy implications will be included in chapter 7

The structure of the dissertation is presented as figure 1.6 below

Figure 1 6 Overall structure of the dissertation

Chapter 1 Introduction

Objective 1 To analyze productive efficiency of tea and rice farmers

Chapter 2 Analysis of technical efficiency of rice farmers and its determinants

Chapter 3 Analysis of profit efficiency of tea farmers and its determinants

Objective 2 To determine the economics of adoption, risk sources and farmers’ risk

management response

Chapter 4 Factors affecting farmers’ decision to adopt VietGAP production

Chapter 5 Assessing impacts of VietGAP production on farmers’ income

Chapter 6 Farmer’s perception of risk sources and their management response

Chapter 7 Conclusion and policy implication

1.6 Selection of study area

Northern Vietnam, including midland and northern mountainous region, has total natural land area of 95,222 km2 and population of 11.98 million people belonging to various ethnic minority groups (GSO, 2016) The region consists of 14 provinces locating

in the northwest and northeast regions The region is covered with mountains and hill ranges And agricultural and forestry economics are dominated in the region due to favorable natural and climatic conditions for the sectors The major cropping and perennial plants of the region include rice, maize, tea, rubber, Arabica-coffee etc The study was conducted in Thai Nguyen province where its socio-economic and demographic characteristics could be a representative of Northern upland area of Vietnam The province has a total population of 1,227.4 thousand persons with an average density of 384 persons per squared kilometer (GSO, 2016) Thai Nguyen province is divided into 09 administrative units including 7 districts, one city and one town: Dinh Hoa, Dai Tu, Dong Hy, Vo Nhai, Phu Binh, Phu Luong, Pho Yen district, Song Cong town and Thai Nguyen city The smallest administrative unit in Vietnam is commune Moreover, tea and rice farming plays an essential role in household’s livelihood, especially in rural areas While rice production is mainly produced for self-demand/sufficiency, tea plant is producing to serve as commercial purpose, bring back income as cash for daily life The sampled farmers were randomly selected from representative districts of study area Field survey was taken in two periods of time Data

of rice production was collected from 120 rice farmers, while primary data of tea production was gathered in 2016 through face to face interview of 116 VietGAP and 210 conventional tea farmers Some observations with missing information was got rid out of dataset Only observations with fully required information were used for analysis in the study Prior to field survey, pretest survey was also conducted to adjust content of questionnaire following the real understanding of farmers and time management Numerators were selected from experienced staffs in field survey and also were carefully trained to ensure capturing the objective of research and get much information as possible Rice data was used in chapter 2, while data of tea production was used in all remaining chapters

Surveyed location

(3 districts)

Figure 1 7 Map of study area

CHAPTER 2 PRODUCTIVE EFFICIENCY OF RICE

FARMERS AND ITS DETERMINANTS

2.1 Introduction

Rice is a staple food of Vietnamese people, and is one of the main food crops that play an important role in household income in rural areas Impressive growth of agriculture has brought significant benefits The agricultural achievement has contributed significantly to poverty reduction in Vietnam However, there are still many difficulties and challenges facing Vietnam now Firstly, poverty rate is still as high as 13.5% nationwide in 2014, and the rate is very high for ethnic minority groups Secondly, income disparity is relative wide between urban and rural area, delta and mountainous area due to unequal growth amongst regions Notably, ethnic minority groups of the region share only 7% of total population, but its poverty rate is 25.4% in compared with total number of the poor of the country (Nguyen et al, 2017) Northern upland area has total annual cropping land area of about 1.6 million ha, in which rice area is 579 thousand hectares, accounting for 35.4% and ranked 4th in Vietnam The region’s economy is characterized by agricultural production Farmer’s income depends mainly on agricultural activities such as cropping, animal husbandry, fishery raising and forestry activities, in which rice production plays an important role in household’s income, especially in the rural and mountainous area, accounting for about 25% (GSO, 2009) Moreover, rice self-sufficiency also contributes to food security in upland area where public transportation system is still very difficult due to high and complex topography

Although several studies on productive efficiency of agricultural crops were conducted in Vietnam (Nguyen et al 2003; Linh, 2008), there are few studies on technical efficiency of rice production And most of these studies were conducted in two main rice production areas such as Mekong river delta and Red river delta Other studies tried to estimate the technical efficiency of rice production nationwide under an important assumption that there was no large difference among areas in Vietnam (Khai and Yabe in 2011) Therefore, our study would investigate technical efficiency and estimate the impact of various fertilizers on rice production Its result will contribute more to comprehensive insight on whole picture of rice production in Vietnam

2.2 Methodology

2.2.1 Overview of efficiency

Technical efficiency (TE) is one of the important and interesting index used in production firms It is often used to measure efficiency of using resources such as land, labor, capital, materials and so on And measuring technical efficiency is one of concerns

of researchers with the objective to estimate efficient level of farmers involved in agricultural production Technical efficiency helps researchers to answer question in short run: Can rice farmers increase their productivity under given conditions? Technical efficiency (TE) and allocative efficiency (AE) are two components of economic efficiency (EE)

2.2.1.1 Economic, technical and allocative efficiency

Production is a process of transforming inputs such as land, labor, capital, fertilizer… into output such as goods and services This process is not only applied in agricultural production, but also in other production sectors The difference of production performance is generally displayed at different inputs and outputs Ultimate objective of agricultural production may be profit or revenue maximization, cost minimization, maximum output etc They can vary from time to time or firm to firm Some concepts cover technical efficiency such as productive efficiency or economic efficiency

Production efficiency is composed of two components including technical efficiency and allocative efficiency The purely technical or physical component is defined as the firm’s ability to avoid waste during production In other words, a firm use the given inputs to create an output as high as possible, or produce a given output by applying inputs as low as possible Thus, the target of an estimation of technical efficiency

is to find solutions to increase output or decrease inputs in the context of available conditions While the allocative or price component is determined by combination of inputs and outputs in the optimal level in term of considering market prices Measuring technical efficiency implies use of input and output quantity without introducing their prices Technical efficiency can also be further decomposed into three subcomponents, which are scale efficiency (the potential productivity gain from achieving the optimal size

of a firm), congestion (increase in some inputs could decrease output), and pure technical efficiency (Farrell, 1957)

Economic efficiency involves in increasing output without using more than conventional inputs The use of existing technologies is more cost-effective than applying new technologies if farmers currently cultivate their products inefficiently with current technologies (Shapiro, 1977) Economic efficiency can be classified into two types: technical efficiency and allocative efficiency Technical efficiency measures the ability

of a farmer to achieve maximum output with given and obtainable technologies While allocative efficiency tries to capture a farmer’s ability to apply the inputs in optimal proportions with respective prices (Farrell, 1957, Shapiro, 1977) The technical efficiency (TE) of a firm always varies from 0 to 1 value (0 ≤ TE ≤ 1) If TE is equal to 1, the firm produces with full technical efficiency For instance, the firm could achieve full technical efficiency

2.2.1.2 Concept of production frontier

In microeconomic theory, a production function is a function that specifies the output of a firm for all combinations of inputs Given the set of all technically feasible combinations of output and inputs, only the combination encompassing a maximum output for a specified set of inputs would constitute the production function Alternatively, a production function can be defined as a specification of the minimum input requirements needed to produce an output, given available technologies By assuming that the maximum output technologically possible from a given set of inputs is achieved, economists are using production function in analysis to solve problems of technical efficiency and allocative efficiency The observed outputs below the production frontier show the firm producing inefficiently

2.2.2 Techniques of efficiency measurement

There are two methods widely applied to estimate the technical efficiency of a firm: parametric and non-parametric The parametric approach assumes a functional relationship between output and inputs and uses statistical techniques to estimate the parameters of the function The non-parametric approach, in contrast, constructs a linear piecewise function from empirical observations on inputs and output without assuming

any functional relationship between them Non-parameter and parametric approach method are called in term of DEA and SFA respectively The comprehensive reviews of the two methods are carried out by Kalirajan and Shand (1999); Bravo-Utera and Pinheiro (1997) The choice as the best method is unclear Some rigorous empirical analyses have been conducted in assessing the sensitivity of efficiency measures to the choice of DEA and SFA in agriculture (Sharma et al 1999) The limited findings show that efficient score estimated from each approach is quantitative change, although the ordinal efficiency ranking of farms achieved from two methods are quite similar So the choice

of other method application depends on the objectives of the study, type of farms and some assumptions regarding the data generating process

Data envelopment analysis (DEA) is a mathematically programming method that

is useful for multiple-input and multiple output production technologies The method, initially studied by Charnes et al (1978), uses linear programming methods to build a non-parametric piece-wise surface or frontier over the data and estimate each data point’s efficiency relative to the frontier The DEA method assumes that the variables are reasonably separated into inputs and outputs Each data point in DEA represents a decision-making unit (DMU), or a producer in practice The decision of a unit is to create outputs by using inputs as efficiently as possible (Zheng et al, 2004)

Stochastic frontier approach (SFA) uses econometrics based on the deterministic parameter frontier Aigner et al (1977) independently proposed the stochastic frontier production function model of the form: lnqi = xiβ + νi – ui, where qi represents the output

of the ith firm; xi is a vector containing the logarithms of inputs; β is a vector of unknown parameters; vi accounts for statistical noise; ui represents for technical inefficiency The different techniques are applied to generate the strengths and weaknesses of the two methods The econometric approach is stochastic and parametric It has ability to separate the effects of noise from the effects of inefficiency and confound the effects of misspecification of functional form with inefficiency, but generate good results only for single output and multiple inputs In contrast, DEA method is not stochastic and parametric It does not separate the effect of noise and inefficiency during the computation of technical efficiency, and less sensitive to the type of specification error, but could be useful to apply for farms with multiple inputs and multiple outputs

production The calculation of technical efficiency using the production frontier model is only applied to single output production Depending on the structure of the data (whether cross-sectional data or panel data), different estimate techniques are applied in reality

2.2.3 Analytical framework

As described in sections above, two methods have been widely used to estimate technical efficiency, including Data Envelope Analysis (DEA) and Stochastic Frontier Analysis (SFA) Both methods have different strengths and weaknesses In the study, we use SFA technique because it can separate the effects of noise from technical inefficiency And it only can generate good results for production systems with only one output and multi-inputs Rice production in Vietnam has one output of quantity and inputs of seed, fertilizers, labor, pesticide and hired machine And Cobb-Douglas production function was extensively used in the literature In the research rice yield is used as dependent variable instead of rice production as well as Nguyen et al (2003), because it is a realistic assumption that a similar harvest regularity about scale for each farmer existed in the study area due to small rice area per household, given applied technology in rice production and similar natural conditions in the region Logarithm both side of the function will result in the model as below

The Cobb-Douglas production function can be expressed by following equation

Where yi is rice yield of ith farm, xij is the jth input (j=1-7) used by ith farmer βo is intercept and βj are parameters to be estimated or elasticity corresponding to each input (j=1-7), including used seed, nitrogen, phosphorus, potassium, pesticide, working day and hired machinery, respectively and εi is an error term consisting of two components, Vi and Ui Where Vi is random variable error associated with random factors such as measurement errors and other statistical noise and exogenous factors beyond the farmer’s control such

as natural disasters Vi is assumed to be independently and identically distributed, and independent of Ui While Ui is non-negative random variable associated with farm’s specific factors which would affect technical efficiency of rice farmers Ui is assumed to

be independently truncated-normal distribution with mean µ and variance δ2 Although

Ui can also have other distributions, FRONTIER 4.1c computer program used in the study can only harmonize with above assumption The term µi is defined as follows

µi = δo + δ1Z1j + δ2Z2j + δ3Z3j + δ4Z4j + δ5Z5j + δ6Z6j + ωi (2.2) Where µi is inefficiency effects that could be estimated by 2 stage estimation technique

in FRONTIER 4.1c spontaneously δo is the intercept term, δj is the parameter for jth independent variables Z1j is experience of farmers (years); Z2j is education level of farmers (years); Z3j is household size (persons); Z4j is number of land plots; Z5j is area variable, Z5j = 1 means Northeast and 0 means Northwest area; Z6j is credit access, if Z6j

= 1 then farmer has borrowed credit loans from financial agencies and zero otherwise; ωi

is an error term (unobservable random variables) Maximum likelihood estimates (MLEs) for all parameters of the stochastic frontier production (1) and inefficiency model (2) and were simultaneously estimated by using the FRONTIER 4.1c computer program (Coelli, 1996) This program also presented the coefficients of variance parameters

2.2.4 Data collection

The study was conducted in Thai Nguyen province, locating in the center of the northern upland area of Vietnam A multistage sampling technique was used to select 120 sample farmers in 18 villages belonging two districts of the province For the sampling method, some aspects were considered in selecting households such as geographical location, rice production area, family status The farm-level data was collected by interviewing farmers based on detail questionnaire, including information about general characteristics of household, farm size, inputs and output information such as rice yield, rice varieties, fertilizer applications, credit and agricultural extension service While

secondary data was collected through General Statistic Office of Vietnam and communal report during field survey in 2011

2.3 Results and discussion

2.3.1 Descriptive statistics of variables

Table 2 1 Descriptive statistic of variables in the model

Note: *1 unit = 1000m2; **vnd: monetary unit of Vietnam

Source: Author’s data was surveyed in 2011 (n=120)

Summary statistics of all variables in production function and some farm specific characteristics affected technical inefficiency was shown in table 2.1 Average rice yields

o sampled farmers were 427 kg/unit Seed quantity was applied to reach 6.91 kg/unit Other physical inputs of rice production include fertilizer, pesticide For fertilizers, farmers apply various types such as nitrogen, phosphorous and potassium And no respondents replied that organic fertilizers were applied in their rice farm In study area chemical pesticide was also popularly applied in reducing damage from pest and insect

It often varies annually from crop to crop due to specific pest status Due to small scale, scattered and sloping land production, mechanization in rice production is quite low Machinery tool was mainly used in land preparation only In addition to descriptive statistics of output and all input variables in analysis of technical efficiency, summary statistics of determinants on technical inefficiency are also presented in Table 2.1 above Average age of household head is about 44 years old Educational level of household head is primary and secondary school with 30 percent and 59.17 percent, respectively While number of labors each family are 4.78 persons on average And it ranges from 1 to

11 labors Number of land plots is 5.55 plots per household on average In the study there are two dummy variables such as area and credit access Area variable is used to measure different natural conditions between North west and North east Meanwhile, dummy variable on credit access aims at estimating the effect of using credit on improvement of rice yield in the study area

2.3.2 Estimation of stochastic frontier production function

The MLEs of stochastic frontier production function is shown in Table 2.2 below Gamma values (γ) of model are 0.863 and its value is statistically significant at 1% level

As explained in the previous section, that value implies that 86.3% of variation of rice yield are attributed to technical inefficiency in rice production And the rest is due to random noises This also confirms that application of stochastic frontier function model

is adequate in this research Moreover, presence of technical inefficiency was tested by the Likelihood Ratio (LR) test Null hypothesis (Ho) implies that gamma value is equal

to zero In other words, variations of rice yield are due to random noises or stochastic frontier model is inadequate Alternative hypothesis (H1) implies that gamma value is different from zero or application of stochastic frontier model is adequate LR test has mixed Chi square (χ2

R) distribution with R equal to restrictions in the model According

to statistic principles, Null hypothesis (Ho) will be rejected if LR test is greater than critical Chi-square value table In this study, LR values is 35.86 And critical Chi-square value (χ2 (1%,8)) is equal to 20.09 (taken from table of Kodde & Palm, 1986) As explained above, LR test is greater than critical Chi-square value in the case Therefore, null hypothesis (H0) is rejected It means that farmers in the study site were not fully technical efficient

Table 2 2 Estimated parameters of stochastic frontier production function

The estimated coefficients of variables including seed, nitrogen, phosphorous, potassium, labor and hired machine were positive, indicating that these inputs had positive relationships with rice yield However only estimated coefficients of nitrogen, potassium and using machinery variable were statistically significant at 1%, 1% and 5% levels, respectively It implies that rice farmers could increase the yield by using more nitrogen, potassium And result also indicated that applying hired machinery could return higher rice yield This could be explained as the result of better land preparation in rice cultivation The coefficients of other variables such as seed, phosphorous and labor were not significant at any levels And only estimated coefficient of pesticide variable was negative with rice yield This might be explained that overusing pesticide will affect negatively rice growth ability leading to loss of rice yield, but it was not statistically significant

2.3.3 Input elasticity and its responsiveness to rice yield

The elasticity of all variables is determined to estimate the quantitative effect of each input on rice yield According to principle/characteristics of Cobb-Douglas production function and natural logarithm, parameters of Cobb-Douglas production function could be used to interpret as elastic coefficients of inputs to output These coefficients indicate relative importance of each variable on output explained in percentage (%) All coefficients of Cobb-Douglas production function are presented in Table 2.2

The result shows that rice yield of sampled farmers has highest response on nitrogen input with elasticity of 0.031 The next is potassium input with elastic level of 0.011, the third position is machinery input with elasticity of 0.003 These imply that one percent increase of inputs such as nitrogen, potassium and machinery unit will lead to an increase of rice yield of 0.031 percent, 0.011 percent, and 0.003 percent, respectively Other inputs such as seed, use of phosphorus, cost of pesticide and use of working days also have positive/negative relationship with rice yield However, coefficients of these inputs are not statistically significant at any level This could be explained that farmers

overused these factors or reach at frontier level

2.3.4 Frequency distribution of technical efficiency

Frequency distribution of technical efficiency in Northern upland area is presented in Table 2.3 Average technical efficiency scores (TE) of rice production were

88 percent This indicates that farmers could improve technical efficiency 12% on average with the given set of inputs and given technology at that time TE of this study

is smaller than the finding of Hassan and Ahmad (2005), but it is little bit higher than study result of Shehu et al (2007), Nguyen et al (2003)

The technical efficiency level in the study area varies from 45% to 98%, suggesting that the best practice farmers achieved at about 98% on average, while least efficient farmers in study area operated at 45% only Moreover, table of frequency distribution also indicates that about 80% of farmers in the study area achieved technical efficiency higher than 80%, indicating that more than three-fourth of farmers operated at fairly efficient level