This study uses the data collected from a household survey on 100 farmers in Lung Ngoc Hoang Nature reserve. Economic efficiency in the present study was estimated from stochastic profit frontier function. Farm household makes an average profit of about 18,33 and 8,02 million dongs in Winter-Spring and Summer-Autumn crop, respectively.
AGU International Journal of Sciences – 2019, Vol (3), 65 – 74 ASSESSING ECONOMIC EFFICIENCY AND IMPACTS OF GLOBAL WARMING, ACIDIFICATION, EUTROPHICATION OF RICE PRODUCTION IN LUNG NGOC HOANG NATURE RESERVE, HAU GIANG PROVINCE Lam Kim Nhung1, Truong Hoang Dan2 Nam Can Tho University Can Tho University Information: Received: 03/12/2017 Accepted: 06/12/2018 Published: 11/2019 Keywords: Economic efficiency, Environmental impacts, Life Cycle Assessment, Lung Ngoc Hoang, Stochastic profit frontier function ABSTRACT This study uses the data collected from a household survey on 100 farmers in Lung Ngoc Hoang Nature reserve Economic efficiency in the present study was estimated from stochastic profit frontier function Farm household makes an average profit of about 18,33 and 8,02 million dongs in Winter-Spring and Summer-Autumn crop, respectively The average economic efficiency level was 58,51% and 47,38% in Winter-Spring and Summer-Autumn crop, respectively The efficiency level largely varied across farms due to the big gap in farming techniques and the ability of choosing optimal inputs across farms The life cycle assessment method (LCA) was used to assess the environmental impact The results showed that the impact of global warming in the production of one kilogram of rice was largely due to CH4 emissions from rice soil (94,19%) The use of fertilizer caused the most acidified (94,94%) and eutrophicated (98,03%) INTRODUCTION approach rather than the decentralized approach with greater involvement of the local community in the management process Lack of cooperation from the local people in the management process harms the local communities living in nature reserves, and also arises conflicts for the use of wetland resources, which leads to restrict the efficiency of conservation activities Based on those backgrounds, the study was conducted to determine the effects of input factors on profit, economic efficiency and estimate the impact of global warming, acidification, eutrophication of rice production in Lung Ngoc Hoang Nature reserve The research results partly form the basis for managers to develop community- Wetlands play a vital role as trapping pollutants, toxic substances or general wastes from human activities, providing favorable breeding grounds for a variety of aquatic species, as well as contributing many other benefits to the lives of the local people About one-fifth of Vietnam population live in wetland areas and directly depend on the wetlands for their livelihood, mainly for rice cultivation As a result, wetland conservation and management cannot be separated from community development (Gill & Lý Minh Đăng, 2008) However, The wetland management system in Vietnam is characterized by a top-down 65 AGU International Journal of Sciences – 2019, Vol (3), 65 – 74 based biodiversity conservation policies and develop sustainable rice farming livelihoods in Lung Ngoc Hoang Nature Reserve assumed to be independently Where, vi, distributed N(0, σv2), is a two-sided error term, and ui > is a one-sided error term and a halfnormal distribution (u~ |N(0, σu2)|) The parameter gamma (𝛾) 𝛾 = σu2/σ2 takes the value between and A value of (σu 🡪 σ) suggests the variability in profits among farms is mainly due to the existing differences in the level of technical and allocative inefficiencies, whereas a value of can be seen as evidence about the existence of statistical noise Phạm Lê Thông cs (2011) found that the unknown parameters in the model (1) can be determined by using maximum likelihood estimation method (MLE) which is widely used to measure the effectiveness of individual producers METHODOLOGY 2.1 Method of data collection The study was carried out in Lung Ngoc Hoang Nature reserve, the economic efficiency and the environmental impact of paddy production in Summer-Autumn (02/2015-06/2015 lunar calendar) and Winter-Spring crop (11/2015 – 02/2016 lunar calendar) were examined The data were collected from 100 rice farmers by the simple random sampling method Information from these farm households was gathered through a structured questionnaire containing the following information: rice farming household characteristics, items of rice production costs, input uses, output prices, returns, fertilizer and pesticide applications The explicit form of the stochastic profit frontier model used in the study is specified as: lnπi = β0 + β1lnPPi + β2lnPTi + β3lnPGi + β4lnPCi + β5lnFi + ei 2.2 Methods of analyzing data Where: 2.2.1 The stochastic frontier model ● πi is normalized profit of the ith farm defined as gross revenue less variable cost, divided by farm specific price of kg output rice Ali and Flinn (1989) claimed that farmer has different factor endowments and faces different input and output prices As a result, farms may exhibit different “best practice” production functions and operate at different optimal points Economic efficiency and the highest possible profit can be estimated by the stochastic frontier function model: ● PPi is normalized price of fertilizer defined as the weighted mean of the price of kg input fertilizers divided by price of kg output rice ● PTi is normalized price of pesticide defined as(1)the weighted mean of the price of kg input pesticides divided by price of kg output rice Yi= f (xi) exp (vi – ui) hay lnYi = ln [f(xi)] + (vi – ui) = ln [f(xi)] + ei The essential idea behind the stochastic frontier model is that the error term is composed of two parts A two-sided error term captures the effects of measurement random error which measures statistical noise and random shocks outside the firm’s control A one-sided error term captures the effects of inefficiency relative to the stochastic frontier They are both ● PGi is normalized price of seed defined as the price of kg of input seed divided by price of kg of output rice ● PCi is land preparation cost (thousand VND/1.000m2) 66 AGU International Journal of Sciences – 2019, Vol (3), 65 – 74 ● Fi is family labor for farming activities (man-days/1.000m2) international database In order to evaluate impacts related to the on-field activities, the referenced methane emission was 212,41 kg/ha (Huỳnh Quang Tín & et al., 2012) Based on N fertilizer application rates, the referenced N2O emission was about 0,42% of the applied N (Jianwen & et al., 2009), the estimated N losses by NH3 volatilization was 14,6% and 1,7% of the applied N in the dry and the wet season, respectively (Wantanabe & et al., 2010), the amount of NO3- leached was 1,19% of the total chemical N applied (Iqbal, 2011) The amount of emitted SO2 from fuel combustion was 0,00589 kg/kg fuel (Michaelis, 1998 cited from Lê Thanh Phong & Hà Minh Tâm, 2015; Lê Thanh Phong & Phạm Thành Lợi, 2012) All impact values are given relative to a common unit, which is gain of kg rice ● ei is an error term 2.2.2 Life cycle assessment (LCA) LCA has been widely used to quantify and evaluate the environmental impacts of products through all stages in their life cycle (ISO 14040, 2006) In the study, method of LCA was used to assess the environmental impacts in rice production from rice seeding to harvesting Survey data on the use of fertilizers, pesticides, and gasoline from 100 farmers were collected However, some data such as fertilizer, pesticide, and fuel manufacturing were impossible to be collected Thus they were cited from GaBi6 as software program which is an Table Environmental impact category Impact Category Global warming (g CO2-eq) Acidification (g SO2-eq) Eutrophication (g PO4- -eq) Substances Equivalent weight CO2 CH4 25 N2O 298 SO2 NOx 0,7 NH3 1,88 NO3- 0,42 NOx 0,1 NH3 0,35 TN 0,42 TP 3,06 (Source: Bentrup & et al., 2004; IPCC, 2007) 67 AGU International Journal of Sciences – 2019, Vol (3), 65 – 74 RESULTS AND DISCUSSION 3.1 General socio-economic characteristics of the study sites In general, the average age of sample farmers was 50,07 years old The number of household’s labors were low, on average, people In terms of small farm size, the number of household’s labors play an important role in bringing down hired labor cost Table Characteristics of surveyed farmers in the study sites Characteristics Average Value Age of respondents (years) 50,07±10,49 Number of household’s labors (people) 1,75±0,64 Experience in rice farming (years) 25,68±12,51 Education level (%) 100,00 No schooling 2,00 Primary school 50,00 Secondary school 37,00 High school 11,00 Farm size (%) Less than 0,5ha 7,00 From 0,5 to 1ha 43,00 More than 1ha 50,00 The education level of surveyed farmers in the study sites was low, 50% of them left school after primary school This limited their learning capacity in receiving scientific and technological knowledge The average farming experience were 25,68 years Farmers, who had a lot of experience in rice growing, could reach a high production efficiency However, they were self-righteous and not willing to adopt technological advances in rice production (Phạm Lê Thông & et al., 2011) The average rice area per household was 1,37 ha, 50% of farmers owned rice fields with production area smaller than 1ha Small farm size was also a limiting factor for the application of advanced technology in rice production (Nguyễn Tiến Dũng & Lê Khương Ninh, 2014) 3.2 Costs and returns analysis The total costs in both seasons are approximately the same (14,02 and 14,25 million dongs/ha in Winter-Spring and Summer-Autumn crop, respectively) In which, fertilizer and pesticide cost accounted for the highest proportion, accounting for about 46,82% and 45,79% of the total cost in WinterSpring and Summer-Autumn crop, respectively The T-test results indicated that there was no statistically significant difference in total as well as the composition of cost between the two crops due to the similarities in traditional farming technique applied by farmers between Winter-Spring and Summer-Autumn crop 68 AGU International Journal of Sciences – 2019, Vol (3), 65 – 74 Table The production cost per Winter-Spring Cost Category Amount (Million VND/ha) Summer-Autumn Index (%) Amount (Million VND/ha) Index (%) t-ratio Fertilizer 3.096,30 22,46 3.126,80 22.40 0.51ns Pesticide 3.512,00 24,36 3.496,60 23,39 0,92 ns Seed 1.884,00 13,56 1.831,70 13,15 0,18 ns 853,32 5,96 1.049,50 7,28 0,00*** 2.164,40 15,74 1.999,60 14,46 0,02** Labor 347,42 2,48 527,53 3,53 0,06* Other 2.164,00 15,43 2.213,30 15,79 0,18 ns Total 14.015,00 100,00 14.245,00 100,00 0,26 ns Land preparation Harvest The average yields, returns, output price of farm household were shown in Table Farm household made an average profit of about 18,33 and 8,02 million dongs/ha in WinterSpring and Summer-Autumn crop, respectively Net returns/cost ratio in Winter-Spring crop was 1,37 which is about twice as much as the one in Summer-Autumn crop Yields and output price declined while farming costs were still equivalent to the Winter-Spring crop which was the main reason for the sharp decline in profit in the Summer-Autumn crop Table The financial efficiency of rice production in Lung Ngoc Hoang Nature reserve Items Measure Yields T/ha Output price Winter-Spring Summer-Autumn 6,85 5,26 VND/kg 4.710 4.225 Returns Million VND/ha 32,35 22,27 Total cost Million VND/ha 14,02 14,25 Net returns Million VND/ha 18,33 8,02 3.3 Stochastic profit frontier model and Economic efficiency across farms mainly due to the big gap in farming technique The variance-ratio parameter implies that 84% of the variability in profits among farms in Winter-Spring and 91% the variability in profits among farms in Summer-Autumn due to the existing differences in the level of technical and allocative inefficiencies Linear regression models were statistically significant at 1% Because the LR statistic and variance-ratio parameter in both Winter-Spring and Summer-Autumn crop are statistically significant, there was sufficient evidence to conclude that the profit level largely varies 69 AGU International Journal of Sciences – 2019, Vol (3), 65 – 74 Table Coefficients of stochastic profit frontier model with MLE Winter-Spring Variables Constant Summer-Autumn Standard Deviation Coefficients Standard Deviation Coefficients 11,96*** 0,70 11,45*** 0,88 lnP -0,47 ns 0,39 -0,29ns 0,55 lnT -0,19** 0,09 -0,23** 0,12 lnG 0,27 ns 0,23 -0,37ns 0,25 lnC -0,26*** 0,10 -0,05ns 0,13 lnF -1,88*** 0,24 -2,27*** 0,37 No of Observations 100 100 Significance level 0,00*** 0,00*** LR statistic 4,75** 12,80*** The variance-ratio parameter 0,84*** 0,91** Although fertilizer costs accounted for the second-highest proportion of production costs, coefficients of fertilizer cost variables in both Winter-Spring and Summer-Autumn crop were statistically insignificant Compared to recommended quantities, majority of farmers in the study sites did not tend to overuse inorganic fertilizer, but fertilizer application rate was still improper leading to the negligible impact of fertilizer quality fluctuation represented in the fluctuation of fertilizer cost on rice yield so it was difficult to determine the effect of fertilizer cost on profit Table The average pure nitrogen, phosphorus, potassium application rate in the study sites Nutrients Application rates (kg/ha) Winter-Spring Summer-Autumn Recommended quantities (kg/ha) * N 74,93±18,95 79,78±25,76 80 – 100 P2O5 48,71±17,19 54,05±21,34 60 – 80 K2O 31,54±15,05 31,91±15,72 30-50 (Source: * Pham Sy Tan & Chu Van Hach, 2014) Coefficients of pesticide cost variables in both Winter-Spring and Summer-Autumn crop were statistically significant and negatively related to efficiency If pesticide price increases 1% and all other factors remain constant, profits will decrease by almost 0,19% and 0,23% in Winter-Spring and Summer-Autumn crop, respectively In this survey, the proportion of farmers applying pesticide dose equal to the recommended dosage instructed on pesticide container labels was 39% The rest farmers, based on their own experience or their 70 AGU International Journal of Sciences – 2019, Vol (3), 65 – 74 neighboring farmers’ advice, increased pesticide dose or mixed two or more types of pesticides in sprayers before application The average number of pesticide applications was times per crop season Farmers in study sites applied more times of spraying pesticide than the farmers participated in “1 Must- Reductions” model (Can Tho Department of Agriculture and Rural Development, 2013 cited from Nguyễn Tiến Dũng & Lê Khương Ninh, 2014) Improper use of pesticide caused increases in pest incidence (Nguyễn Phan Nhân & cs., 2015) When pest increases, farmers have to use more pesticides to cope with the situation These two actions push up production costs and reduce profits constant, profits will decrease by almost 0,26% The majority of farmers did not realize the benefits of the agricultural cultivation Rice Fish model, so they maintained a high level of investment in the plowing stage leading to a decrease in profits Coefficient of land preparation in Summer-Autumn crop was statistically non-significant Because of disadvantageous weather conditions, there was no considerable difference in yield and profit under different land preparation level Coefficients of family labors for farming activities in both Winter-Spring and SummerAutumn crop is statistically significant and negatively related to efficiency If total working hour that family labor spent on rice production increases by 1% and all other factors remain constant, profits will decrease by almost 1,88% and 2,27% in Winter-Spring and SummerAutumn crop, respectively Part of the reason was the limited labor quality, low technical level, the high average age of farmers causing a decrease in labor productivity Low labor productivity required increasing working hours while yield remains unchanged so profits will decrease Coefficients of seed cost variables are statistically insignificant High seeding rate (131 – 350 kg/ha) combined with improper fertilizer and pesticide use causing the negligible impact of seed quality fluctuation on rice yield so it was difficult to determine the effect of seed cost on profit Land preparation cost in Winter-Spring crop had a negative coefficient If land preparation cost increases 1% and all other factors remain Table Frequency distribution of farm specific profit efficiencies in rice production Winter-Spring Profit efficiency score (%) Number of farmers Summer-Autumn Number of farmers Index (%) Index (%) 90 – 100 0 0 80 -