Xác định quy mô đất tối ưu trong sản xuất nông nghiệp của người dân đồng bằng sông cửu long tt tieng anh

The relationship between Farm Size and Land Productivity of rice farming households in the Mekong Delta.. Effect of Farm Size and Labor Size on the Labor Productivity of rice households

MINISTRY OF EDUCATION AND TRAINING

CAN THO UNIVERSITY

-o0o -

NGUYEN LAN DUYEN

DETERMINING THE OPTIMAL FARM SIZE

IN AGRICULTURAL PRODUCTION OF HOUSEHOLDS

MEKONG DELTA

DISSERTATION (ABSTRACT)

Major: Agricultural Economics Major code: 9 62 01 15

Can Tho, 07/2020

The research has been finished at Can Tho University

Supervisor: Assoc Prof Nguyen Tri Khiem, PhD

Discussant 1: Discussant 2: Discussant 3:

The dissertation will be defended at the council of the school level at:

On: …… hour…… date …… month……… year………

Citing of this the dissertation in available at following the libraries:

- Learning Resource Center – Can Tho University

- Vietnam National Library

LIST OF PUBLISHED PAPERS RELATED TO DISSERTATION

1 Nguyen Lan Duyen and Nguyen Tri Khiem (2018) Effect of Farm Size on the Economics Efficiency of rice households Mekong Delta Economic studies, volume 2 (477), pp 58 – 67

2 Nguyen Lan Duyen and Nguyen Tri Khiem (2018) The relationship between Farm Size and Land Productivity of rice farming households in the Mekong Delta Journal Science Ho Chi Minh City Open University, 61(4), pp 57 – 66

3 Nguyen Lan Duyen and Nguyen Tri Khiem (2019) Effect of Farm Size and Labor Size on the Labor Productivity of rice households in the Mekong Delta Journal Science Ho Chi Minh City Open University, 14(1), pp 68 – 78

4 Nguyen Lan Duyen and Nguyen Tri Khiem (2019) Effect of Farm Size on the Total Factor Productivity of rice households Mekong Delta Journal of Economics & Development, volume 265, pp 82 – 92

5 Nguyen Lan Duyen and Nguyen Tri Khiem (2019) The effect of Farm Size

on the Profit Ratio of rice households in the Mekong Delta Can Tho University Journal of Science, episode 55, Special issue on Economics, pp 42 – 50

CHAPTER 1 INTRODUCTION

This chapter gives an overview of the research rationale, research objectives and scope of the thesis

1.1 Reason for research

Agricultural land area in Asia accounts for 20% of the world's total agricultural land area, but the landholdings are very small (from 1-2 ha/household) compared to the world average (3.7 ha/household) and the trend of small-scale ownership is increasing (Pookpakdi, 1992) Vietnam's agricultural land area is 0.12 ha/person, only one sixth of the world average, equivalent to Belgium and the Netherlands, higher than the Philippines and India, but lower than China and Indonesia (OECD, 2015) Due to the industrialization that transfers agricultural resources (such as labour and land) to the industrial sector, leaving less for agricultural production (Dinh Bao, 2014) In agricultural production, industry or services, producers are interested in many factors One of the crucial factors determining the success of production is the efficiency of production activities (HQHDSX), or to use optimally resources to improve HQHDSX In agricultural production, land is a scarce factor (Hoque, 1988), a vital factor of production (Adamopoulos and Restuccia, 2014) and is an especially irreplaceable means of production (Pham Van Dinh and Do Kim Chung, 2004), therefore, producers need

to determine the optimal farm size threshold for investment in order to maximize the efficiency of production activities

However, at different stages of the economy, the farm size is different In the 1960s, small scale was good and effective because of taking advantage of family resources (labor, land, production tools, ) but in the 1970s and 1980s due to the process of urbanization and specialization As an industrialization, attracting a large number of rural laborers makes production more efficient on a large scale (Fan and Chan-Kang, 2005) According to these researchers, by the 1990s, the application of science and technology to production increased the land use intensity, thus negatively affecting the land resources and the environment leading to production not as effective as before

The Inverse Relationship (IR) hypothesis between farm size and the efficiency

of agricultural production activities implies that small farm will be more effective than households with large farm, discussed in countries with developed agriculture

in recent centuries, first in Russia (Chayanov, 1926), then India, the main studies being done in Africa, Asia, and Asia Europe, Latin America, and even developing agriculture countries support this relationship The findings of the reverse relationship are an empirical discovery that is so popular that advocates of small

farm agriculture have proposed agricultural strategies that favor small farm (Nkonde

et al., 2015)

However, there are also many studies disagreeing with the above hypothesis and based on empirical evidence that have provided the opposite opinion, that large-scale producers will be more effective than small farm producers or positive relationship (PR) between farm size and the efficiency of production activities This

is reflected in policies that support large farm (Srivastava et al., 1973; Khan, 1979; Khan and Maki, 1979; Kevane, 1996; Adesina and Djato, 1996; Tadesse and Krishnamoorthy, 1997; Dorward, 1999)

Thus, farm size can have an impact on the efficiency of agricultural production

in two dimensions, showing economies of scale and non-economies of scale (Hoque, 1988; Byiringiro and Reardon, 1996; Heltberg, 1998b; Dorward, 1999; Helfand and Levine, 2004; Barrett et al., 2010; Henderson, 2015; Wickramaarachchi and Weerahewa, 2018) From a producer standpoint, it is not possible for households to decide whether to increase or decrease farm size when being unsure whether the current farming size is in an economic or non-economic stage, because a wrong decision will bring serious consequences affecting family livelihoods

Over the various stages of the economy, most researchers measure or define the efficiency of productive activities by land productivity when analyzing the relationship between farm size and HQHDSX, and there are a few other researches that replacing land productivity measure with technical efficiency or economic efficiency In Vietnam in general and the Mekong Delta in particular, this issue was also studied by some economists but mainly inherited one of two measures (land productivity or technical efficiency or economic efficiency) In recent years, Li et

al (2013), Nkonde et al (2015), Wickramaarachchi and Weerahewa (2018) combine traditional measurement (land productivity or technical efficiency) with total measures (labor productivity, capital efficiency and total factor productivity) to comprehensively assess the efficiency of household production activities

Agricultural policymakers who face difficult decisions in the choice of agricultural structure must ensure that achieving two goals of growth and equity (Khan and Maki, 1979) and contribute to stimulating rural growth and reducing poverty (Lipton, 1993) On that basis, the Government of Vietnam issued a new Land Law in 2013, increasing the area of agricultural production land to 03 ha/household in the Mekong Delta and the limit of receiving land use rights is not more than 30 ha/household in the hope of increasing the efficiency of production activities However, reality has a two-way effect, which means that at certain farm size when increasing the farm size will increase efficiency or sometimes reduce the efficiency of production activities and vice versa

On that basis, the thesis "Determining the optimal farm size in agricultural

production of households Mekong Delta" deeply analyzes the impact of farm size

on the efficiency of production activities through various measures (measures of land, labor, capital, economic efficiency, management techniques and technology improvement) to determine the optimal farm size threshold to maximize the efficiency of production activities At the same time, this result serves as a solid scientific basis for the State to assert or identify the validity of land allocation Policy

in the 2013 Land Law and make a useful contribution to a more rational adjustment

of land Policy in the future, especially helping households use the farm size appropriately to increase the efficiency of production activities, improve livelihoods and contribute to the development of the economy

1.2 Research objectives

To achieve the overall objective of the research that is determine the optimal farm size in rice production of Mekong Delta households, with the following specific objectives:

(1) Analyze the status of production and land use in rice production of households in the Mekong Delta

(2) Analyze the influence of farm size on the efficiency of rice production activities of households in the Mekong Delta

(3) Determine the optimal farm size in rice production of households in the Mekong Delta

(4) Proposing solutions to help use the appropriate farm size, contributing to increase the efficiency of rice production activities for households Mekong Delta 1.3 Scope of the research

1.3.1 Objective

The main objective of the study is to determine the optimal farm size in rice production of Mekong Delta households The research subjects are rice households and scientists, policy makers, local authorities, local officials, related to the farm size in rice production Mekong Delta

1.3.2 Content

The thesis focuses on analyzing cultivation activities with the main crop being rice because rice is the main product of Mekong Delta households and only analyzes the model of pure rice cultivation (ie 3 rice crops/year)

The thesis focuses on analyzing the influence of farm size on the efficiency of rice production activities through various measurement aspects to find the optimal farm size

1.3.3 Space

The thesis wants to find out about differences in rice production among provinces in a specific ecological region as a basis for forming subsequent studies for the remaining 2 regions as well as inter-provincial research of each region Therefore, the thesis focuses on three provinces (An Giang, Dong Thap and Can Tho) because according to some experts, the ecological zoning in rice production in the Mekong Delta is divided by annual floodplain (An Giang and Dong Thap) and freshwater alluvium (Can Tho) In addition, these 3 provinces have similar characteristics in terms of ecology, farm size and rice cultivation practices, which are provinces in the key rice production areas and have high rice production so the selection of locations is the survey site, the study will be highly representative for alluvial and freshwater areas

1.3.4 Time

Data were collected from 498 rice households in the Mekong Delta during the three crops (Autumn-Winter crop 2016, the Winter-Spring crop 2017 and Summer crop 2017) The primary data collection time is from September 2017 to December

2017 The time for analyzing secondary data is from 2010 to 2017 The time for analyzing data and conducting the thesis is from January 2018 to December 2018

CHAPTER 2 THEORETICAL FRAMEWORK AND

2.1.1 Theoretical framework for measuring the efficiency of production

The efficiency of agricultural production activities in general and rice production in particular is comprehensively measured through two main aspects: productivity (land productivity, labor productivity, capital efficiency and total factor productivity) and production efficiency (including technical efficiency, allocative efficiency, scale efficiency and economic efficiency) Li et al (2013) showed that the efficiency of agricultural production activities is a multi-dimensional concept in the production process, at least including land productivity, labor productivity, capital efficiency, technical efficiency and total factor productivity

According to Coelli et al (2005), productivity is the output index on the input index (such as land, labor, and capital), thereby forming land productivity, labor productivity and capital efficiency However, Li et al (2013) argue that each

measure of land, labor and capital is only an indicator of single factor productivity, and thus cannot reflect the whole agricultural production process comprehensively Land productivity was researched early on in two ways of measuring in kind and monetary value The thesis uses the measure of land productivity by money (Khan, 1977; Khan, 1979; Mahmood and Nadeem-ul-haque, 1981; Cornia, 1985; Newel et al., 1997; Heltberg, 1998b) are generalized by total value of output per farm size (NSDAT) This indicator reflects the efficiency of agricultural land use by rice households and is the most important goal for many developing countries in food security

Similarly, labor productivity can be measured in a variety of ways Since then, the research uses the measure of labor productivity (NSLD) by production output on the number of family workers involved in production of Shafi (1984), Li et al (2013), Wickramaarachchi and Weerahewa (2018) Freeman (2008) said that labor productivity is important in economic analysis and statistics of a country

Accordingly, capital efficiency is also measured in different ways and this research uses a measure of the ratio of profit per production cost (Schultz, 1964; Li

et al., 2013) because this is an indicator to evaluate the effectiveness of the return on investment costs on land

Going further in measuring the efficiency of production activities through measuring the production efficiency According to Farrell (1957), efficiency is the ability to produce a given level of output at lowest cost Therefore, economic efficiency (EE) is a basic goal of the producer and is a measure of the success of the producer in selecting optimal inputs and outputs Economic efficiency is the product

of technical and allocative efficiency Thus, to achieve economic efficiency in agricultural production in general or in rice cultivation in particular, households need

to achieve both technical efficiency and allocative efficiency (Farrell, 1957; Dhungana et al., 2004)

Currently, the two most commonly used methods in most researchs are the parametric estimation method (DEA) and the parameter estimation method (SFA) The research used parameter estimation method through stochastic frontier analysis model (SFA) to estimate the economic efficiency of rice farming households because

non-of its advantage non-of being able to separate non-effective parts and noise out non-of errors

in the estimation model but this estimation method requires determining the shape

of functions and errors Accordingly, EE is estimated through the stochastic profit frontier function (Ali and Flinn, 1989; Ali et al., 1994; Rahman, 2003; Nwachukwu and Onyenweaku, 2007; Thong, 1998; Pham Le Thong, 2011a&b; Pham Le Thong

et al., 2011) have the form:

𝜋 = 𝑓(𝑃 , 𝑍 , 𝛼 )𝑒 (2.1)

Therefore, the economic efficiency of rice production households in the concept of the stochastic profit frontier function is calculated as follows:

𝐸𝐸 = 𝐸 𝑒( ) 𝜀 (2.2) Overall, EE is considered to be a better indicator of the three indicators because

it measures both production techniques and input selection However, this is still not the perfect target to measure the efficiency of production activities so it is bound by the market price

Total factor productivity (TFP) was defined and formed by Tinberger (1942) early in empirical research in Germany However, TFP is widely available and used

by many economists from the definition of Solow (1957), according to Solow, TFP

is a technological level or technological progress through the formula:

𝑌 = 𝐴(𝑡) × 𝐹(𝐿, 𝐾) (2.3) According to Farrel (1957) the origin of TFP growth was due to changes in technical efficiency and technological advances (Nishimizu and Page, 1992; Coelli

et al., 2005) Sigit (2004) said that TFP is a measure of productivity of all inputs This is a qualitative change (such as skills, management methods, technology) TFP

is understood as growth through technological innovation, the efficiency gained from improving labor and capital management According to Li et al (2013), TFP which can comprehensively reflect the efficiency of the whole agricultural production process Hence, Li et al (2013), Nkonde et al (2015) use the production function of the Cobb-Douglas from to calculate TFP Following Fan (1991) and Zhang and Carter (1997), they use the following function form:

𝑆𝐿𝑈𝑂𝑁𝐺 = 𝐴 𝑒 𝐾 𝐿 𝐹𝑆 exp(𝜀) (2.4) where SLUONG is rice quantity produced by households; K, L, FS represent the value of capital (all costs of production except imputed family costs), total number of labor days (hired and family labor), and land inputs (farm size) of households, respectively; αK, αL and αFS are the output elasticities for capital, labor, and land, correspondingly; t is time trend term and η is the rate of technoligical progress Using natural logarithm, equation (2.4) is estimated as follows:

𝑙𝑛𝑆𝐿𝑈𝑂𝑁𝐺 = (𝑙𝑛𝐴 + ηt) + 𝛼 𝑙𝑛𝐾 + 𝛼 𝑙𝑛𝐿 + 𝛼 𝑙𝑛𝐹𝑆 + 𝜀 (2.5) Given that this production function is estimated with cross sectional data, the time trend variable is t=1 and thus the lnA0 + ηt term becomes the constant term To get the TFP indicator, the research first compute the returns to scale (RTS) coefficient, which is the sum of factor output elasticities (𝑅𝑇𝑆 = 𝛼 + 𝛼 + 𝛼 ), then normalize each factor’s output elasticity and obtain 𝛼′ = , 𝛼′ = , 𝛼′ = and define TFP as:

𝑇𝐹𝑃 = 𝑆𝐿𝑈𝑂𝑁𝐺

𝐾 𝐿 𝐹𝑆 (2.6) Based on the theory of TFP, this is an indicator which can comprehensively reflect the efficiency of the whole agricultural production process because it includes the use of management techniques with the relevant technology level (Li et al., 2013) and this is also the index not affected by the price of inputs as well as the price of output products Therefore, the thesis uses TFP criteria to determine the optimal farm size threshold to maximize HQHDSX, at the same time, the thesis still analyzes the other four criteria as a basis to prove the assertion that “each of these indicators is not the best measure the efficiency of production activities”

2.1.2 Theoretical basis of the influence of farm size on the efficiency of production activities

Wickramaarachchi and Weerahewa (2018) productivity is defined as the ability

of an input unit to produce a given output unit Agricultural productivity shows the level of efficiency of households in using a specific input with a certain level of technology

The inverse relationship between farm size and the efficiency of production activities plays an important role in many regions at different times and this relationship was first discovered in agricultural production in Russia by Chayanov (1926), then inherited and developed widely in the 1960s and 1970s (Sen, 1962; Bardhan, 1973) Sen (1962) the small farms in India, which obtaining higher the efficiency of production activities as they apply more inputs (especially family labor) Berry and Cline (1979) also demonstrated a relationship similar to Sen in other developing countries and Deolalikar (1981) argued that this relationship was only true in traditional agriculture This relationship became a hotly debated topic between agricultural economists and development economists (Carter, 1984; Feder, 1985; Benjamin, 1995)

Imperfections in the market of inputs also contribute to the formation of a strong inverse relationship between farm size and the efficiency of production activities First, the analysis of data from fifteen developing countries, Cornia (1985) shows that systematic output per unit of agricultural land decreases as the farm size

of increase by labor is more abundant and cheaper for small farm Head of households' knowledge of land and local climatic conditions accumulated over generations contributes to an advantage over hiring workers (Rosenzweign and Wolpin, 1985) The advantage of supervision and knowledge of small farm will compensate for difficulties in accessing capital and formal insurance in rural markets (Feder, 1985) An inverse relationship between fram size and the efficiency of production activities is caused by the imperfections of credit and labor markets when

combined with fixed costs of production (Eswaran and Kotwal, 1986) Imperfection land and insurance motivate smallholders to use more family labor to reduce the potential adverse effects of price fluctuations (Barrett, 1996) Assuncao and Ghatak (2003) demonstrated an inverse relationship after controlling households' heterogeneity of skills Thapa (2007) also discovered this relationship in Nepal because it used more labor and cash than large farms Ansoms et al (2008) found a strong inverse relationship between farm size and the efficiency of production activities Rwanda due to the scarcity of land that forced households to over-exploit their resources in the case of main household income from agricultural production The research also found that increases in non-farm wages and technological advances will affect the exchange rate, management capacity, presence and level of market imperfections It is these factors that will form the inverse relationship between farm size and HQHDSX (Otsuka, 2013)

However, a number of other studies also explain the existence of inverse relationships due to the omission of other factors that affect the HQHDSX such as knowledge and technical understanding as well as socio-economic environmental issues In which households must make decisions (Kalirajan, 1990) and based on previous researches, two of the socio-economic environmental indicators (include education and income other than agriculture) have been selected to measure the relationship between farm size and HQHDSX (Bravo – Ureta and Pinheiro, 1997), differences between households (Assuncao and Ghatak, 2003), land fragmentation (Wu et al., 2005), differences in soil quality (Benjamin, 1992; Lamb, 2003; Assuncao and Braido, 2007), soil characteristics and sand content (Barrett et al., 2010) and the other factors, at the same time omitting the different definitions that show the HQHDSX Therefore, Li et al (2013), Wickramaarach and Weerahewa (2018) added exogenous variables to control the influence of these factors on the efficiency of rice production activities of households However, the level of the impact of the inverse relationship between farm size and HQHDSX tends to decline over time (Deininger and Byerlee, 2012; Deininger et al., 2015) due to the emergence of imperfect labor markets and technological change

On the contrary, some researches have demonstrated a positive relationship between farm size and the efficiency of production activities, meaning that large farm are more effective than small farm The emergence of a Green Revolution has increased the role of capital and knowledge, which has led to the emergence of large farm achieving a higher level of HQHDSX in districts suitable for new technologies (Deolalikar, 1981) Recent innovations in plant breeding, tillage and information technology help households easier monitor labor, thus increasing the efficiency of production activites in traditional agriculture at Eastern Europe and South America (Helfand and Levine, 2004; Lissitsa and Odening, 2005) And this positive

relationship was also discovered in Nigeria due to the high quality inputs used by large farm of the households (Obasi, 2007), in Japan that having relatively well factor markets (Kawasaki, 2010) and China due to technological development and technological transformation (Chen et al., 2011)

Mixed results obtained by Rahman and Rahman (2009) suggest that a positive relationship between HQHDSX and farm size occurs in advanced technology areas and the inverse relationship still exists in developing regions Tamel (2011) in the

US agriculture sector showed that in some areas, farm size and the efficiency of production activities is positive but in others may have a positive relationship (Kawasaki, 2010; Ali and Deininger, 2015; Lu et al., 2018) or the negative relationship (Paul and Githinji, 2017) with farm size depending on the fragmentation process Hence, the inverse relationship is a local phenomenon rather than an indispensable law in production

The researches not only stop at a simple relationship (negative or positive relationsgip) but also show a nonlinear relationship (U-shaped or ∩-shaped) between farm size and HQHDSX First, Mahmood and Nadeem-ul-haque (1981) have demonstrated the U-shaped nonlinear relationship between farm size and HQHDSX when estimating the inputs (farm size, square farm size) with output Inheriting that achievement, researchers Byiringiro and Reardon (1996), Heltberg (1998b) have added the characteristics of soil and region characteristics, followed by Helfand and Levine (2004) and Ali and Deininger (2015) developed Heltberg's model on the basis

of adding soil characteristics

However, Dorward (1999), Kimhi (2006), Barrett et al (2010), Ali and Deininger (2015), Nkonde et al (2015), Henderson (2015), Anseeuw et al (2016), Wickramaarachchi and Weerahewa (2018) argue that there is an inverted U-shaped nonlinear relationship between farm size and HQHDSX through different models from simple (only farm size variables and squared farm size) to the complete model

of information and characteristics of the head of household, land characteristics and quality, the ability to manage and care for rice fields, all show this relationship 2.1.3 Theoretical backgrounds of optimal farm size

According to economic theory and economics of agricultural production theory, Debertin (2002) demonstrated the optimal input threshold to maximize the output through the first derivative calculation method based on specific inputs

According to Greene (2003), consider finding the x where f(x) is maximized

or minimized Because f’(x) is the slope of f(x), either optimum must occur where

𝑓 (𝑥) = 0 Otherwise, the function will be increasing or decreasing at x This result implies the first-order or necessary condition for an optimum maximum or minimum

is = 0 Hence, to maximize or minimize a function of several variables, the

first-order conditions are ( ) = 0

According to microeconomic theory, when the smaller farm, the higher the average cost will increase, and the larger farm expands, the lower the average cost will decrease, until a certain farm size (or the maximum farm size) the average cost will be the minimum and if the optimal farm size is exceeded, the average cost will increase with increasing farm size, which results in the opposite of the production function, implies obtain the largest average yield for the optimal farm size

According to Wickramaarachchi and Weerahewa (2018), the optimal farm size

is the farm size at which the HQHDSX is maximized Because when farm size is still small, if farm size continues to expand, the effectiveness will increase and achieve the highest efficiency at the optimal farm size threshold At this farm size threshold, if farm size continues to expand, the efficiency decreases and the optimal farm size threshold is determined by

2.2 Overview of references

2.2.1 The research of the effects of farm size on the efficiency of production activities

2.2.1.1 Effect of farm size on land productivity

The inverse relationship is discussed and discovered through theory and experiment on many countries around the world (Mazumdar, 1965; Bharadwaj, 1974; Khan, 1977; Chaddha, 1978; Berry and Cline, 1979; Carter, 1984 ; Cornia, 1985; Feder, 1985; Bhalla and Roy, 1988; Chattopadhyay and Sengupta, 1997; Heltberg, 1998a&b; Assuncao and Ghatak, 2003; Fan and Chan-Kang, 2005; Barrett

et al., 2010; Chen et al., 2011; Sial et al., 2012; Carletto et al., 2013; Holden and Fisher, 2013; Ali and Deininger, 2015; Desiere and Jolliffe, 2017) but with a focus

on India (Sen, 1962; Bardhan, 1973; Ghose, 1979; Newell et al., 1997; Assuncao and Braido, 2007; Gaurav and Mishra, 2015)

However, there are also many studies disagreeing with the above hypothesis and based on empirical evidence that have provided the opposite opinion, that large farm households will be more effective than households with small farm (Rao, 1966; Srivastave et al., 1973; Heltberg, 1998a&b; Khan, 1979; Khan and Maki, 1979; Rao and Chotigeat, 1981; Kevane, 1996; Akram-Lodhi, 2001; Van Hung and et al., 2007; Truong Hong Vo Tuan Kiet and Hua Tuan Tai, 2013; Akudugu, 2016)

Thus, farm size can have an impact on land productivity in two dimensions, showing economies of scale and non-economies of scale Studies (Mahmood and Nadeem-ul-haque, 1981; Byiringiro and Reardon, 1996; Heltberg, 1998b; Ali and Deininger, 2015) have demonstrated a U-shaped nonlinear relationship between farm size and land productivity However, Dorward (1999), Barrett et al (2010), Ali

and Deininger (2015), Nkonde et al (2015), Henderson (2015), Anseeuw et al (2016), Wickramaarachchi and Weerahewa, 2018 suggest that having an inverted U-shaped nonlinear relationship between farm size and land productivity

2.2.1.2 The effect of farm size on labor productivity

The efficiency of production activities is measured by labor productivity that

is not as commonly researched as land productivity but has been researched in recent years and shows a positive relationship between farm size and labor productivity (Lamb, 2003; Li et al., 2013; Adamopoulos and Restuccia, 2014)

Researchers Byiringiro and Reardon (1996), Nkonde et al (2015), Wickramaarachchi and Weerahewa (2018) also found an inverted U-shaped nonlinear relationship between farm size and labor productivity based on energy estimation labor productivity with different explanatory variables such as farm size, square farm size, variables showing the characteristics of the household head, the characteristics of the land, and differences in the residence area

2.2.1.3 Effect of farm size on capital efficiency

Although there are very few studies on this relationship, it still shows a clear relationship like other HQHDSX First, Li et al (2013), Wickramaarachchi and Weerahewa (2018) used capital efficiency measure to measure HQHDSX and show the positive relationship between farm size and capital efficiency However, Nkonde

et al (2015) measured the capital efficiency use through cost efficiency and found

an inverted U-shaped nonlinear relationship between farm size and capital efficiency

in all three cases from single, semi-complete to complete variables

2.2.1.4 The effect of farm size on economic efficiency

Many researches have demonstrated an inverse relationship between farm size and economic efficiency (Lau and Yotopoulos, 1971; Tadesse and Krishnamoorthy, 1997; Bagi, 1982; Townsend et al., 1998; Xu and Jeffrey, 1998; Gorton and Davidova, 2004; Manjunatha et al., 2013) In contrast, Hall and Leveen (1978), Lund and Hill (1979), Hoque (1988), Kalaitzandonakes et al (1992), Sharma et al (1999), Alvarez and Arias (2004), Rios and Shively (2005), Tipi et al (2009), Nguyen Huu Dang (2012) have demonstrated the positive relationship between farm size and production efficiency

Researchers not only stop in the linear relationship between farm size and production efficiency but also research and make judgments about the existence of nonlinear relationship between farm size and production efficiency The U-shaped relationship between farm size and production efficiency is shown through the varius research of (Helfand and Levine, 2004) In contrast, Hoque (1988), Nguyen Tien Dung and Le Khuong Ninh (2015), Nguyen Tien Dung (2015) have demonstrated the inverted U-shaped nonlinear relationship between farm size and