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: 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 i LIST OF PUBLISHED PAPERS RELATED TO DISSERTATION Nguyen Lan Duyen and Nguyen Tri Khiem (2018) Effect of Farm Size on the Economics Efficiency of rice households Mekong Delta Economic studies, volume (477), pp 58 – 67 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 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 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 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 ii CHAPTER 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 largescale 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 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 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 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 THEORETICAL FRAMEWORK AND RESEARCH METHODOLOGY This chapter presents the theoretical basis of the HQHDSX measures, the theoretical basis of the influence of the farm size on the HQHDSX is measured based on different aspects, the theoretical basis of the optimal farm size; Propose an research framework, research model and analytical methods 2.1 Theoretical framework 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 nonparametric 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 of its advantage of being able to separate non-effective parts and noise out 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′ = and define TFP as: , 𝛼′ = , 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 and Deininger (2015), Nkonde et al (2015), Henderson (2015), Anseeuw et al (2016), Wickramaarachchi and Weerahewa, 2018 suggest that having an inverted Ushaped 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 11 production efficiency 2.2.1.5 The effect of farm size on the total factor productivity Although the relationship between farm size and TFP is not as deeply concerned as the relationship between farm size and land productivity However, it still shows that there may be a linear relationship (negative or positive relationship) between TFP and farm size or nonlinear relationship through some empirical researches First, Van Zyl et al (1996), Li et al (2013), Gautam and Ahmed (2018) found an inverse relationship between farm size and TFP In contrast, other researches have found a positive relationship between farm size and TFP through experiments in Czech Republic (Hughes, 1998), in Slovakia (Hughes, 2000), in Vietnam (Dinh Bao, 2014) and in Australia (Sheng and Chacellor, 2018) The research also found nonlinear relationship between farm size and TFP in two different forms The U-shaped nonlinear relationship between farm size and TFP through the research of Nkonde et al (2015) have proved that the inverted Ushaped nonlinear relationship between farm size and TFP 2.2.1.6 The effect of farm size on the efficiency of production activities As just stated, most researcges only use a single measure of HQHDSX, in which land productivity is commonly used in many researches to explore the relationship between farm size and HQHDSX Other ways of measuring HQHDSX such as labor productivity, capital efficiency, technical efficiency and TFP are rarely used In recent years, a comprehensive measurement of the HQHDSX through various measurement aspects (using 3-5 measurements) was conducted by Li et al (2013), Nkonde et al (2015), Wickramaarachchi and Weerahewa (2018) have demonstrated a different relationship (linear as negative or positive relationship, U-shaped or inverted U-shaped nonlinear relationship) between farm size and HQHDSX depending on the measurement specifically the efficiency of production activities 2.2.2 Researches on optimal farm size Many researches have demonstrated the optimal farm size threshold to maximize the efficiency of production activities according to one of five different measurements in the same data set (researches from 3-5 measures representing the HQHDSX) or different data set (single research a measure of HQHDSX) On the basis of the first derivative or based on the estimation results of the model of factors affecting on HQHDSX (Hoque, 1988; Hassanpour, 2013; Nguyen Tien Dung, 2015; Nkonde et al., 2015; Wickramaarachchi and Weerahewa, 2018) 2.3 Research methods 2.3.1 Research framework Land Productivity Optimal farm size by NSDAT Labor Productivity Optimal farm size by NSLD 12 Source:Research and design Hình 2.1 Proposes research framework 2.3.2 Data collection The study selected three provinces in the Mekong Delta with the same characteristics of the land with large farm rice cultivation of An Giang, Dong Thap and an average of Can Tho The study collected randomly 498 rice-producing households in the Autumn-Winter 2016, Winter-Spring 2017 and Summer 2017 seasons, of which An Giang (225 households), Can Tho (90 households) and Dong Thap (183 households) 2.3.3 Data analysis Objective 1: Research using descriptive statistical methods Objective 2: Research to use ways: - A two-step estimation method for four ways of measuring the efficiency of production activities including land productivity, labor productivity, capital efficiency and TFP - An one-step estimation method for economic efficiency measure Objective 3: Use necessary conditions and calculation formula of Greene (2003), Wickramaarachchi Weerahewa (2018): 𝜕𝐻𝑄𝐻𝐷𝑆𝑋(𝑄𝑀𝐷𝐴𝑇) 𝛽 = => 𝑄𝑀𝐷𝐴𝑇 = (2.7) 𝜕𝑄𝑀𝐷𝐴𝑇 2𝛽 Objective 4: rely on the achieved results to propose the most effective solutions 2.4 Estimation model of farm size impacts on the efficiency of rice production activities of Mekong Delta households The general model measures the impact of farm size on the efficiency of production activities through various aspects as follows: 13 𝐻𝑄𝐻𝐷𝑆𝑋 = 𝛽 + 𝛽 𝑄𝑀𝐷𝐴𝑇 + 𝛽 𝑄𝑀𝐷𝐴𝑇𝑆𝑄 + 𝛽 𝑄𝑀𝐿𝐷 + 𝛽 𝑁𝑈𝐶𝐻 + 𝛽 𝑇𝐷𝐻𝑉𝐶𝐻 + 𝛽 𝑇𝑁𝐾𝐻𝐴𝐶 + 𝛽 𝑆𝑂𝑀𝐴𝑁𝐻 + 𝛽 𝐿𝐷𝑇𝐻𝑈𝐸 + 𝛽 𝐿𝐷𝐺𝐷 + 𝛽 𝐴𝑁𝐺𝐼𝐴𝑁𝐺 + 𝛽 𝐷𝑂𝑁𝐺𝑇𝐻𝐴𝑃 + 𝛽 𝑇𝑉𝑂𝑁 + 𝛽 𝑇𝐻𝐴𝑀𝑁𝐼𝐸𝑁 + 𝛽 𝐾𝐶𝑅𝑈𝑂𝑁𝐺 + 𝛽 𝑇𝐴𝑃𝐻𝑈𝐴𝑁 + 𝜀 (2.8) where: HQHDSXk is the efficiency of production activities measured by different aspects, QMDAT is the farm size of rice cultivation on the largest field (ha), QMDATSQ is the square of farm size of the household, QMLD is the number of working-age members of the family involved in rice production (number of employees), NUCH is the dummy variable representing the gender of the head of household (= if the head of household is female and = otherwise) , TDHVCH is the educational level of the head of household (number of classes), TNKHAC is the household's non-rice income (million VND /year), SOMANH is the number of rice plots of the household (the number of plots), LDTHUE is the total labor days hired to work in rice fields (days/ha), LDGD is the total number of family labor days working on rice fields (days/crop), ANGIANG (= if the household lives in An Giang and = if in other province), and DONGTHAP (= if the household lives in Dong Thap and = if in another province), TVON is the total cost of the inputs (including family labor) (million VND/crop), THAMNIEN is the number of years of rice farming experience of the head of the household (year), KCRUONG is the distance from the household to the largest field (km), TAPHUAN (= if the head of the household participated in training courses in the last years and = if otherwise), i indicate the number of i rice the households and j showing the number of j crops 14 CHAPTER OVERVIEW OF RESEARCH AREAS This chapter presents an overview of the Mekong Delta as well as of the provinces surveyed mainly regarding farm size 3.1 Land resources in the Mekong Delta Land area in the survey area is concentrated on alluvial soil This soil group has high fertility and balance, favorable for agricultural production, especially for rice, coconut, sugarcane, pineapple and fruit trees 3.2 Current status of rice production 3.2.1 Farm size in the Mekong Delta * Farm size of agricultural production Number of agricultural households in the Mekong Delta in general and the three researched provinces in particular concentrated mainly on the farm size of 0.5 - ha, accounting for 40.36%, followed by the scale of 0.2 - 0.5 accounts for 25.13% and the remaining is allocated at other ones Table 3.1 Number of households using agricultural land in the Mekong Delta by farm size Unit: Household Location An Giang Can Tho Dong Thap Mekong Delta < 0,2 37.887 20.942 49.341 509.795 0,2 – 0,5 36.339 26.850 53.713 598.932 0,5 – 68.427 43.264 89.269 961.914 > 27.395 11.151 24.086 312.455 Total 170.048 102.207 216.409 2.383.335 Nguồn:Tổng điều tra nông thôn, nông nghiệp thủy sản Việt Nam năm 2016 * Farm size of rice cultivation by locality 6000 ĐBSCL 4000 Đồng Tháp 2000 An Giang 2010 2011 2012 2013 2014 2015 2016 2017 Cần Thơ Source:General Statistics Office 2017 Figure 3.1 Scale of paddy land in the Mekong Delta by location Farm size of rice cultivation is concentrated in An Giang, followed by Dong Thap and at least Can Tho This result forms the number of households surveyed in the provinces in the study area * Farm size of rice cultivation by scale The total number of rice-growing households in the Mekong Delta accounts for 19.12% of the total number of rice-growing households nationwide and concentrates on the scale of 0.5 - The number of rice-growing households in Dong Thap is higher than the other two provinces and when divided by farming size, 15 the farming scale of the people of provinces of An Giang, Can Tho and Dong Thap is still similar to households in the Mekong Delta, which means that most people cultivate on a scale of 0.5 - ha, accounting for about 40%, from 0.2 to 0.5 ha, accounting for 25% and under 0.5 accounts for about 22% and the scale of over accounts for about 13% This implies that people in the surveyed area are cultivating on a small farm and fragmented so not really bring about optimal the efficiency of production activities 60.00 An Giang 40.00 Cần Thơ Đồng Tháp 20.00 ĐBSCL 0.00 < 0.2 0.2 - 0.5 0.5 - > Source: Vietnam Rural, Agriculture and Fishery Census 2016 Figure 3.2 Structure of households using rice land in the Mekong Delta by scale 3.2.2 Results of rice production in the research area Đồng Tháp An Giang Cần Thơ 6,000.00 4,000.00 2,000.00 0.00 2010 2011 2012 2013 2014 2015 2016 Sơ 2017 Source: General Statistics Office 2017 Figure 3.3 Rice production in the Mekong Delta 2010 - 2017 Rice production in the three provinces of An Giang, Dong Thap and Can Tho followed the increasing trend over time for the whole period but began to decline slightly in 2016, of which the highest output of An Giang and Can Tho was the lowest Can Tho has the lowest output but the growth rate is quite high when compared to 2010 and 2017 at about 16%, reaching the highest output of 1,408 million tons in 2015 For An Giang and Dong Thap due to the large output, the downward trend in the following years is more evident although the output increased during the period of more than 6% and 14% for each province To conclude, the output of the provinces has increased but started to decline slightly in the following years and slower than the area so the provinces have lower productivity in the following years 16 CHAPTER RESEARCH RESULTS AND DISCUSSION This chapter presents and discusses the results of each study From there, proposing solutions for effective use of farm size contributes to improving the efficiency of production activities, improving incomes and raising the living standards of households in the Mekong Delta 4.1 Actual situation of rice production in Mekong Delta households 4.1.1 Land Table 4.1 Actual situation of farmland Households (m2/household) Average (%) 755,63 3,93 18.401,43 95,82 47,39 0,25 19.204,45 100,00 Soil tyle Residential Agricultural Aquaculture Tổng cộng Average (m2/person) Bình quân Tỷ lệ (%) 172,52 3,93 4.201,24 95,82 10,82 0,25 4.384,58 100,00 Source: Summary results of self-survey data in 2017 Land is a valuable asset for households because it is an indispensable input in agricultural production - especially rice - and also a source of inheritance for future descendants However, under the impact of urbanization and the inheritance of children, the farm size has been gradually reduced due to the land being recovered to build public welfare works, separating households and selling land 4.1.2 Rice production results of households in the Mekong Delta * Productivity Ton/ha 10.00 6.80 6.78 6.16 7.72 8.33 6.68 6.67 7.07 6.14 5.00 Dong Thap An Giang Can Tho 0.00 Autumn-Winter Winter-Spring Summer Source: Summary results of self-survey data in 2017 Figure 4.1 Yield of seasonal rice manure In general, there is not much difference in rice yield among provinces The higher yielding crop compared to the remaining two crops in the three provinces is the winter-spring crop because this is the season with favorable weather, climate and development environment for rice 17 * Production results Average profit ratio and net profit ratio of households are quite low and relatively similar, about 0.5 times and 0.3 times (respectively for autumn-winter and summer crops), but quite high in winter-spring Table 4.2 Rice production results of Mekong Delta households by season Items AutumnWinter Unit WinterSpring Quantity Ton 11,40 13,40 Thousand Price VND/kg 4,80 4,90 Revenue Million VND 55,01 66,18 Million VND Cost (except LDGD) 36,60 37,40 Million VND Total cost (include LDGD) 40,90 42,00 Million VND Profit except LDGD = (3)-(4) 18,40 28,80 Million VND Profit include LDGD = (3)-(5) 14,10 24,20 Profit ratio = (6)/(4) Times 0,50 0,77 Net profit ratio = (7)/(5) Times 0,35 0,58 Source: Summary results of self-survey data in 2017 Summer 11,50 4,90 56,35 37,90 42,30 18,40 14,10 0,49 0,33 4.2 Description of the variables in the general model The dissertation uses a group of explanatory variables to estimate the effects of these variables on five measures of HQHDSX or there are five models to estimate the effects of farm size on HQHDSX (including land productivity, labor productivity, capital efficiency, EE and TFP) Thus, the description of quantitative variables (Table 4.3) and qualitative (Table 4.4) is made before going into the analysis of the estimated results Table 4.3 Quantitative variables in the model (2.8) Criteria QMDAT QMLD TDHVCH TNKHAC SOMANH LDTHUE - Autumn-winter - Winter-spring - Summer LDGD - Autumn-winter - Winter-spring - Summer TVON - Autumn-winter - Winter-spring - Summer THAMNIEN KCRUONG Unit Ha Person Classes Million VND/year Plots Mean 1,71 1,70 5,97 21,33 1,08 Max 17,00 5,00 15,00 100,00 3,00 Min 0,10 1,00 0,00 0,00 1,00 Std Dev 1,77 0,90 3,51 21,79 0,31 Days/ha 11,80 11,49 11,28 126,88 73,13 71,88 0,08 0,16 0,00 13,68 9,81 8,71 Days/ha 15,05 13,27 12,55 71,67 70,00 70,00 0,31 0,08 0,00 11,82 10,93 10,42 14,15 15,80 15,80 6,00 0,01 3,80 4,05 3,84 10,98 10,77 Million VND/ha 24,04 39,35 24,60 43,16 24,44 40,50 Years 30,07 60,00 Km 4,86 75,00 Source: Summary results of self-survey data in 2017 18 Table 4.4 Quanlitative variables in the model (2.8) NUCH Number of household 51 447 498 Criteria Yes No Total (%) 10,24 89,76 100,00 TAPHUAN Number of household 297 201 498 (%) 59,64 40,36 100,00 Source: Summary results of self-survey data in 2017 4.3 Optimal farm size of rice production of Mekong Delta households 4.3.1 Description of the variables in the model Table 4.5 HQHDSX in rice cultivation of people in Mekong Delta HQHDSX NSDAT NSLD HQDV EE TFP Unit Autumn -winter Mil.VND/ha 32,58 Ton/person 8,70 % 53,79 % 94,45 % 3,44 Mean Winter- Summer spring 38,03 33,05 10,28 8,73 77,59 52,98 80,07 72,50 6,09 3,37 Whole year 103,66 27,71 184,35 45,19 12,79 Autumn -winter 6,95 10,53 38,23 5,86 0,97 Std Dev Winter Summer -spring 8,22 6,77 13,00 10,55 48,75 36,62 12,88 13,04 1,33 0,95 Source: Summary results of self-survey data in 2017 4.3.2 The influence of the farm size on the efficiency of production activities 4.3.2.1 Autumn-Winter crop Table 4.6 Influencing factors of farms size to rice HQHDSX of Autumn-Winter crop 2016 Variables QMDAT QMDATSQ QMLD NUCH TDHVCH TNKHAC SOMANH LDTHUE LDGD ANGIANG DONGTHAP TVON THAMNIEN KCRUONG NSDAT 0,2273 -0,0454 0,2766 1,3622 0,0441 0,0156 1,6353 -0,0374 -0,0315 2,0817** 1,5252 0,5029*** -0,0787*** 0,0204 NSLD 5,4447*** -0,0530 -2,9247*** -0,1660 -0,1086* 0,0028 1,4088 -0,0101 -0,0052 -0,0463 -0,3427 0,1993*** -0,0387** 0,0048 TAPHUAN Cons Number of obs R-squared Prob > F 1,0733* -0,6917* 0,0477 -0,1429 18,4402*** 0,8756 1,3619*** 0,5273 498 478 498 498 0,1157 0,8371 0,2590 0,0000 0,0000 0,0000 0,0000 Source: Estimated results of self-survey data in 2017 19 HQDV 0,0091 -0,0022* 0,0156 0,0791 0,0033 0,0006 0,0788 -0,0027*** 0,0083*** 0,1302** 0,0913* -0,0453*** -0,0036*** 0,0007 EE -0,1637 0,0195** 0,0801 -0,1821 -0,0209 -0,0028 -2,0357** -0,0176* -0,0207*** 0,2648 0,1879 0,0604*** 0,0070* 0,0020 TFP 0,6536*** -0,0350*** 0,0193 0,1107 -0,0008 0,0010 0,1717* -0,0034* -0,0014 0,2598** 0,2727*** 0,0121 -0,0095*** 0,0005 0,0566 1,9870*** 498 0,5552 0,0000 Whole year 18,58 33,80 102,96 19,97 2,92 4.3.2.2 Winter-Spring crop Table 4.7 Factors affecting the farm size to rice HQHDSX of Winter-Spring crop 2017 Variables QMDAT QMDATSQ QMLD NUCH TDHVCH TNKHAC SOMANH LDTHUE LDGD ANGIANG DONGTHAP TVON THAMNIEN KCRUONG TAPHUAN Cons Number of obs R-squared Prob > F NSDAT NSLD HQDV EE 0,6560* 6,0002*** 0,0334* -0,0281* -0,0498* 0,0337 -0,0027* 0,0016 -0,6085 -3,3568*** -0,0244 0,0222 0,7193 -0,0801 0,0482 -0,0343 0,1108 -0,1210* 0,0060 -0,0063* 0,0032 -0,0039 -0,0002 -0,0004 -0,5742 0,3474 -0,0334 0,0601 0,0277 -0,0076 0,0010 -0,0072*** 0,0634* 0,0182 0,0161*** -0,0071*** 6,3541*** 0,4117 0,3430*** -0,1977*** 4,2008*** 0,1470 0,2137*** -0,1635*** 0,2349*** 0,0692 -0,0618*** 0,0374*** -0,0750** -0,0464** -0,0036** 0,0022** -0,0661*** -0,0066 -0,0025* 0,0026** -0,2605 -1,2861*** -0,0241 -0,0146 29,4489*** 6,0721*** 1,9715*** -0,5372*** 498 489 498 498 0,1719 0,8555 0,3915 0,0000 0,0000 0,0000 0,0000 Source: Estimated results of self-survey data in 2017 TFP 0,4504*** -0,0231*** -0,0158 0,1849 0,0051 -0,0002 -0,1196 -0,0025 0,0043 0,9682*** 0,8484*** 0,0114 -0,0160*** -0,0086** -0,0296 5,0518*** 498 0,2763 0,0000 4.3.2.3 Summer crop Table 4.8 Factors affecting the farm size to rice HQHDSX of Summer crop 2017 Variables QMDAT QMDATSQ QMLD NUCH TDHVCH TNKHAC SOMANH LDTHUE LDGD ANGIANG DONGTHAP TVON THAMNIEN KCRUONG TAPHUAN Cons Number of obs R-squared Prob > F NSDAT NSLD HQDV EE -0,4013 5,1126*** -0,0144 0,0121 0,0024 -0,0033 -0,0002 -0,0000 0,2486 -2,8412*** 0,0093 -0,0013 1,9494** 0,1540 0,0860* -0,0755** 0,0928 -0,0876* 0,0058 -0,0041 -0,0086 0,0016 -0,0006 0,0002 -0,1243 0,2079 -0,0101 0,0190 -0,0092 -0,0230 -0,0015 -0,0008 0,0113 0,0252 0,0110*** -0,0079*** 2,8224*** 0,1371 0,1490*** -0,0803*** 1,7355* -0,2822 0,0870* -0,0594** 0,5435*** 0,1219** -0,0392*** 0,0219*** -0,0667** -0,0300* -0,0027* 0,0020** -0,0153 -0,0007 -0,0005 0,0000 -0,2308 -1,0920*** -0,0081 -0,0138 19,8454*** 3,6866** 1,3470*** -0,1176 498 498 498 498 0,1398 0,8604 0,2508 0,0000 0,0000 0,0000 0,0000 Source: Estimated results of self-survey data in 2017 20 TFP 0,6165*** -0,0308*** 0,0287 0,1906** 0,0032 -0,0008 -0,0102 -0,0046 0,0058* 0,2799*** 0,2119** 0,0162* -0,0089*** -0,0013 -0,0514 2,1235*** 498 0,5622 0,0000 4.3.2.3 Whole year Table 4.9 Factors affecting the farm size to rice HQHDSX in the whole year Variables QMDAT QMDATSQ QMLD NUCH TDHVCH TNKHAC SOMANH LDTHUE LDGD ANGIANG DONGTHAP TVON THAMNIEN KCRUONG TAPHUAN Cons Number of obs R-squared Prob > F NSDAT 0,6136 -0,0996 -0,1777 3,9556 0,2515 0,0106 0,7375 -0,0242 0,1069*** 10,9699*** 7,3019*** 0,5009*** -0,2199*** -0,0549 0,7490 62,9592*** 498 0,1515 0,0000 NSLD 16,5436*** -0,0222 -9,1353*** 0,1861** -0,3196 0,0002 2,1273 -0,0222 0,0208 0,4228 -0,5430 0,1621** -0,1137** -0,0096 -3,0666** 8,1154 498 0,8638 0,0000 HQDV 0,0174 -0,0045 0,0090 0,1821 0,0122 -0,0000 0,0716 -0,0015 0,0057*** 0,6099*** 0,3824*** -0,0481*** -0,0098*** -0,0028 0,0201 4,5076*** 498 0,3049 0,0000 EE -0,0171 0,0028 0,0089 -0,1147 -0,0099 -0,0008 0,0409 0,0011 -0,0064*** -0,2278*** -0,2002*** 0,0214*** 0,0054*** 0,0018 -0,1922*** -0,3169 498 0,0000 TFP 1,7196*** -0,0889*** 0,0274 0,4794 0,0062 0,0000 0,0690 -0,0044 0,0049 1,4695*** 1,2979*** 0,0242** -0,0348*** -0,0100 -0,0119 8,3258*** 498 0,5088 0,0000 Source: Estimated results of self-survey data in 2017 4.3.3 Optimal farm size HQHDSX 20.000 15.000 Autumn-Winter 10.000 Winter-Spring 5.000 Summer 0.000 10 12 14 16 18 Whole year Farm size (Ha) Source: Summary results of self-survey data in 2017 Figure 4.2 Optimal farm size in rice cultivation of Mekong Delta households From the estimation results, the thesis uses the differential method to determine the optimal farm size threshold for each production crop, implying that this is the optimal farm size threshold to help households maximize the efficiency of production activities, because if production exceeds this optimal one, the household's ability to manage and apply technology is ineffective by (i) It is difficult to control the working motivation of hired labor, (ii) The capital is limited and (iii) Low management capacity due to low education level Hence, to bring the highest efficiency in rice production, households should invest in a reasonable farm size for each crop (from to 10 ha) and the optimal farm size threshold for whole year is 9.67 hectares 21 4.4 Solutions to contribute improving the efficiency of rice production activities of households in the Mekong Delta 4.4.1 The solution uses a reasonable farm size 4.4.1.1 Households with farm size smaller than the optimal farm size For those households that are cultivating rice on the largest plot of land smaller than the optimal farm size, these households are largely dependent on whether or not financially available Thus, the proposed solution is based on specific division for each suitable target group (i) Households with good conditions and strong financial resources Households should rent or pledge the land of adjacent farming households to take advantage of economies of scale Households can also buy additional land (accounting for 25.27% of the total farmers' opinions) of neighboring households or buy land in other areas of the region under the support of the Government from the Loan policy with preferential interest rates Collaborate with neighboring small-scale rice households to expand production scale with groups, rice cultivation groups or cooperatives Households can participate in a large model field to take advantage of the farm size and government's support policies Households and businesses need to link up to establish "large sample fields" and establish specialized farming areas associated with Viet GAP standards (ii) For households with limited financial resources Rent or mortgage land to neighboring households wishing to expand their farming Boldly transforming industries (especially non-agricultural occupations) through state support (vocational training, assistance in accessing capital, policies to attract investment and development of cottage industries and handicrafts) Boldly transfer land to neighboring farmers in a suitable form when rice cultivation is not possible (ie exits to join the labor market) The government should speed up the transfer of land use rights and voluntary labor contracts (Li et al., 2013) 4.4.1.2 Households whose farming size is greater than the optimal farm size Narrow the farming size to take advantage of internal resources as well as apply economic principles to increase the efficiency of production activities by dividing rice fields into two fields for household heads and children Each person who manages and exploits a field will achieve maximum the efficiency of production activities 22 Developed in the direction of establishing a joint stock company because of its advantages compared to single production or group/cooperative, which is a clear division of labor and specialization according to each strength field, the company has workshops - storage warehouses - processing plants - stable output markets and reputable in the market This issue help them maximize resources, increase their percentage of shares and profits received based on their farming size 4.4.2 Labor solutions The head of household should listen and absorb the opinions of other members (mainly children, grandchildren) in the family because some of them have higher education level (university major in agriculture or economics) with in-depth knowledge and ability to understand the market, farming techniques, to make the right investment decision and high efficiency Specialization and division of labor are based on their strengths in one aspect of production The head of household should create favorable conditions for family members to participate in rice production to participate in technical training as well as market information so that they can have a more comprehensive view Organize knowledge fostering for the head of households or farmers directly producing rice to raise their awareness and vision in all aspects from production techniques to management capabilities 4.4.3 Solutions for science and technology Widely disseminate the program "hi-tech agriculture" so that households know and apply it appropriately on rice fields Especially, there is a widespread dissemination of technology using smart mobile devices to identify diseases on rice leaves (Nguyen Huu Hoa et al., 2016) Research, invest and develop post-harvest processing technology lines for agricultural products, especially rice products Applying a new production model to diversify product categories and suit consumers' tastes 23 CHAPTER CONCLUSIONS AND RECOMMENDATIONS This chapter presents a summary of the research results and proposes a number of recommendations for effective use of the scale At the same time, this chapter will suggest further research directions 5.1 Conclusion The author uses multivariate regression methods to analyze the relationship between farm size and the efficiency of production activities expressed through five different measurement aspects including land productivity, labor productivity, total factor productivity, capital efficiency and economic efficiency In particular, the first four measures showing the HQHDSX use the partial estimation method (first calculate or estimate each measure, then estimate the relationship between farm size and each specific measure) On the other hand, the measure of economic efficiency, the thesis uses the simultaneous estimation method (one-step estimation) to determine the relationship between farm sixe and economic efficiency by its advantages compared to two-step estimates method (as many previous researches used) The thesis conducts an analysis of the relationship between farm size and HQHDSX as a basis for determining the optimal farm size threshold to maximize the efficiency of production activities The analysis results show that the model is highly statistically significant and determines the inverted U-shaped nonlinear relationship between farm size and the efficiency of production activities as measured by total factor productivity in three rice crop as well as the whole year Hence, the optimal farm size of 9.7 (in which, Autumn-Winter crop is 9.3 ha; Winter-Spring crop is 9.8 and Summer crop is 10 ha) will bring highest the efficiency of production activities Besides, the main factor is farm size, production efficiency is also affected by other factors The factors having positively effect on the efficiency of production activities including female-headed households (Summer crop), number of cultivated plots (Autumn-Winter crop), number of family labor days involved in rice field (Summer crop), total investment costs for inputs (Summer crop), the area of residence in An Giang and Dong Thap At the same time, the factors are the number of labor days hired to rice (Autumn-Winter crop), the distance from household to the largest rice field (Winter-Spring crop), years of experience having negative effect on the efficiency of production activities Based on the estimation results combined with the results of analyzing the reality of rice production of households in the Mekong Delta The thesis has proposed solutions to help use the farm size appropriately, improve production efficiency and improve household incomes 24 5.2 Recommendations In order to improve the efficiency of using the farm size as well as improving the efficiency of rice production activities, the thesis proposes three recommendations: (i) Create favorable conditions for households to use farm size appropriately For example, it is advisable to adjust the support policy for households who no longer need agricultural production to convert to non-agricultural occupations so that they can boldly change their trades and not keep fields as "insurance" (ii) Promote and find really effective solutions to implement the policy of land accumulation and concentration (iii) Pilot model should be implemented with an effective farm size so that the surrounding rice households can learn and follow 5.3 Further research directions The thesis proposes the following research directions to be conducted based on the limitations and conclusions of the thesis that can be continued in the coming time: - Researching on rice-producing households outside the dike area (ie cultivating rice crops/year), researching in various land quality areas (alluvium, salt water, alum water, ) to determine whether there is a difference in the optimal farm size between ecological zones of the Mekong Delta - Research and compare results between various measures of the efficiency of production activities and provide the basis for building the most effective measure - The research identifies the cause of the difference in the optimal farm size when measuring with different measures 25 ... 102.207 216.409 2.383.335 Nguồn:Tổng điều tra nông thôn, nông nghiệp thủy sản Việt Nam năm 2016 * Farm size of rice cultivation by locality 6000 ĐBSCL 4000 Đồng Tháp 2000 An Giang 2010 2011 2012 2013... 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.,... 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