phân tích chuỗi giá trị và hiệu quả sản xuất của các hộ nuôi cá tra ở đồng bằng sông cửu long tt tiếng anh

MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HO CHI MINH CITY LE THI THANH HIEU ANALYSIS OF THE VALUE CHAIN AND PANGASIUS FARMING HOUSEHOLDS’ PRODUCTION EFFICIENCY IN THE MEKONG DELTA Major: Development Economics Code: 9310105 SUMMARY OF DOCTORAL DISSERTATION IN ECONOMICS Ho Chi Minh City – 2019 Work is completed at: University of Economics Ho Chi Minh City Supervisors: Referee 1: ………………………………………… …………… ………………………………………… ………………………… Referee 2: ………………………………………… …………… ………………………………………… ………………………… Referee 3: ………………………………………… …………… ………………………………………… ………………………… The dissertation will be defended against the school dissertation council at: ………………………………………… …………… ………………………………………… ………………………… At…… O’clock…… Day…….Month…….Year ABSTRACT This dissertation combines the value chain analysis (VCA) with the stochastic frontier production and cost function analyses to determine actors’advantages and gaps in operation in the pangasius value chain, especially for pangasius farming households (PFHs) and exporting and processing enterprises (EPEs) in order to finally develop solutions for upgrading pangasius value chain in the Mekong Delta (MD), through the use of SWOT matrix analysis Research results show that PFHs still have the ability to cut production costs from the use of inputs to enhance production efficiency In addition, the research results have indicated that the issue of using fingerlings certified as disease-free has a good and significant impact on the PFHs’ production efficiency Also from the research results, the author has proposed solutions to upgrade pangasius value chain in the Mekong Delta for PFHs, and solutions for EPEs Key words: Pangasius, Technical efficiency, Cost efficiency, Productive efficiency, Value chain REASONS FOR CHOOSING RESEARCH THEMES Vietnamese Pangasius product in general and MD in particular is one of the important products ò the fishery, as it contributes 28.6% and 21.2% of the toatl export turnover of fishery sector, corresponding to USD 1.754 and USD 1.785 billion in 2012 and 2017 However, in recent years, Pangasius production and export situation has become more difficult due to various subjective and objective causes Among the subjective causes leading to this situation, the problem of excess use of input materials (fingerlings, aquatic feed) of Pangasius farmers was acknowledged by many authors from their studies (Khoi, L.N.D and Son, N.P, 2012; Khoi L.N.D ctv, 2008; Vo Thi Thanh Loc, 2009; Nguyen van Thuan and Vo Thanh Danh, 2014) In fact, to measure this issue, some authors, often scientists in the field of technology, have used financial efficiency analysis, or some researchers in the economic field have used Data Envelopment Analysis (DEA) to measure and evaluate PE of households raising aquaculture in general and Pangasius farming in particular Although these methods also reflect somewhat the PE of farming households, these methods have not yet shown how much households can save on the use of inputs, with available technology and input prices, still maintain a constant level of output (in the case of using the financial analysis method of Phuong and ctv, 2007; Nguyen Thanh Long, 2015; Pham Thi Thu Hong et al, 2015) Also, some domestic and foreign studies not show the true efficiency of farming households in the context of being affected by uncontrollable non-random factors, along with inefficiency due to the limitations of farming techniques of farming households (in case of using DEA method of Sharma, 1999, Kaliba and Angle, 2004; Cinamre, 2006; Bui Le Thai Hanh, 2009; Nguyen Phu Son, 2010; Dang Hoang Xuan Huy, 2011) Therefore, there are other authors who have used SFA to overcome the limitations of DEA Although this method-based analysis has been widely used abroad for many sectors of the economy (agriculture, fisheries, industry, services, etc.), such as researches by MA Alam and ctv (2005); Kehar Singh (2008) Huy (2009); Nguyen Hong Phong (2010); Kehar Singh and colleagues (2008); Onumah and Acquah (2011) but in Vietnam the use of SFA is not very popular in the fisheries sector, especially for the pangasius industry Therefore, in this study, the author uses SFA method to measure production efficiency of farming households, as well as to assess factors affecting technical and cost inefficiency to indicate The bottleneck in the production of pangasius in order to eventually improve the PE of farming households, and thus improve the profit for the whole Pangasius VC in MD In addition, to discover the strengths and bottlenecks in the VC, as well as the opportunities and challenges that actors involved in VC have and encounter, researchers have used differential methods such as VCA of German Technology Organization (GTZValuelinks, 2008), The Department for International Development, UK (DFID-M4P), Food and Agriculture Organzation (FAO), etc to assess the impact of internal factors on activities of actors in the chain, combined with some other qualitative analysis to assess the impact of external factors on the activities of actors in VC, including PEST analysis and Porter’s Five Forces Analysis However, this approach has only been applied relatively much abroad, such as Rui Xu's study (2009); Kristina Al Farova (2011); Muzi (2014) and Roman Anton (2015) In Vietnam, not many studies have used this approach It is from the practical and theoritical context as presented above, the author decided to choose the research topic "Analysis of Value Chain and Production Efficiency of Pangasius farming households in the Mekong Delta" as my doctoral thesis with the desire to get a small contribution in theory and empirical research related to the field of VCA and PE analysis, especially the combination of these two analyzes into a study to both increase the scientific content of the research, and to strengthen the scientific basis for the proposed solutions, and thus expect to provide policy makers in the study area, as well as for actors involved in VC, especially households with useful information for giving making decisions on policies and production and business acts to promote the development of the pangasius industry of MD Therefore, this dissertation is conducted to achieve the objectives shown in the next section RESEARCH OBJECTIVES 2.1 Overall objective Proposing solutions to upgrade VC and improving pangasius farming households’ PE in MD, through analyzing the pangasius VC as well as measuring and assessing the factors affecting the pangasius farming households’ PE in MD 2.2 Specific objective In order to achieve the above-mentioned overall objective, this dissertation is conducted to meet the following specific objectives: (i) Pangasius VCA in MD to detect bottlenecks and advantages in the activities of actors involved in VC; (ii) Analysis of PE and factors affecting the pangasius farming households’ PE in MD; and (iii) Proposing solutions to upgrade pangasius VC and improving PE of farmers raising Pangasius in MD METHODOLOGY 3.1 Data collection The dissertation is done through the use of both types of information, including secondary and primary information 3.1.1 Secondary data The secondary information used in this study includes annual reports of the Department of Agriculture and Rural Development (DARD), the General Department of Customs, the Directorate of Fisheries, Vietnam Association of Seafood Exporters and Processors (VASEP) and available scientific research reports, related to research issues 3.1.2 Primary data Primary information used in this study was collected from direct interviews with 227 households in the area of provinces of An Giang, Dong Thap, Vinh Long and Can Tho City Households were selected to interview according to the non-random, multi-stage sampling method Before conducting direct interviews with farming households, the author conducted group discussions with farming households in the study area to get general information In addition, other actors in VC were also interviewed directly by the chain link method, including fingerling supply facilities, agents / stores providing aquatic feed, SEPEs, 10 local scientists and managers in the study area 3.2 Analytical methods Secondary and primary information was collected above to meet the requirements for the two main analytical methods in this study, namely VCA and PE analysis 3.2.1 Value chain analysis (VCA) This dissertation uses the main VCA tools of DFID-M4P to assess the impact of internal factors on the activities of actors in VC These analysis tools include: Value chain mapping; Analyzing the interaction between actors in VC; Analysis of horizontal and vertical linkages of actors in VC; Upgrade VC; Risk analysis; Analysis of cost distribution, added value and net added value (profit) of actors in VC Besides, this study also uses analysis tools, PEST and Porter's five forces analysis to analyze the impact of external factors on VC In addition, the author has also used the method of stochastic frontier production and cost analysis to measure and evaluate PE of farming households Finally, use SWOT matrix analysis to develop solutions to upgrade pangasius VC in MD, using the results obtained from the above analysis 3.2.2 Production efficiency analysis This study uses the stochastic frontier production and cost function analysis to measure pangasius farming households’PE that includes technical efficiency (TE) and cost efficiency (CE), and to identify factors that affect pangasius farming households’ technical and cost inefficiency 3.2.2.1 Choosing the suitable stochastic frontier production function Through using Likelihood Ratio Test – LR test (Coelli, 1996), form of the stochastic frontier production function in this study is determined This form of production function may be Translog or Cobb-Douglas depending on a set of available data This statistic test is conducted based on the following formula LR = -2[L0 – L1] (3.11) If the statistic value of LR is greater than the critical value of Chi-square distribution with the degree of fredom k (difference between the number of independent variables used in Cobb-Douglas and Translog models) at statistically significal level of α%, then the hypothesis that the apropriate function form of Cobb-Douglas is rejected and vice versa In which L0 is LR statistic value in the case of appropriate Cobb-Douglas form, and L1 for the case of appropriate Translog form The test results show that the appropriate form of production function is Translog Thus, Do vậy, the model of Translog stochastic frontier production function look like as follows (3.14) In which, yi : yield of the ith farming household; β : regression parameter; xni : nth input used by the ith farming household ui: errors due to technical inefficiencies of the ith farming household vi: random errors of the ith farming household Then, the model of Translog stochastic frontier cost function is as follows: ++ With the subject to αnm = αmn for all n and m (i) (m=1,…,N) (ii) The subject to (i) is set up to ensure the symmetry 17 through the form that farming households raise pangasius raw materials for SEPEs This is considered a strong point of SEPEs SEPEs have been investing in developing value-added products from pangasius this is considered a strong point of actors participating in VC (including farmers and SEPEs) Fingerling quality is low while farmers’ production behaviors towards using fingerlings with cheap prices in order to compensate for the death of fish, leading to an average loss of 23% Therefore, this is considered one of the challenges for farming households Input prices tend to increase Through surveying 227 farming households, all farming households said that although the price of raw fish products fluctuated strongly (at increase and decrease), the prices of most inputs were variable moving in the direction of increase As a result, this affects the profitability of farmers Therefore, this is considered a challenge for farmers 18 19 4.2 Pangasius farming households’ production efficiency 4.2.1 Measure and analyze pangasius farrming households’ production efficiency the pangasius farming households’ TE and CE are measured based on the formulas of 3.14 3.15 The measured results of TE are presented in Table 5.3 The estimation of TE coefficient of farming households, using model 3.14, is presented in Table 5.3, showing that the average TE of farming households reached 80.6% with a standard deviation of 20.4% That is, farmers can simultaneously reduce 19.4% of all inputs of labor, fingerlings and aquatic feed, but still maintain a constant level of production This shows that farmers are still technically limited, especially in the use of combination of inputs In 20 other words, for pangasius farmers in MD, there is still an opportunity to improve PE through the reduction of production costs Table 5.3 Allocating frequency of TE coefficients of pangasius farming households Eficiency TE coefficient (%) No of households Rate (%) 90 123 55 Total 227 100 Mean 80,6 Minimum 28,1 Maximum 97,6 Standard Deviation 20,4 For pangasius farming, according to industry experts, 19.4% reduction in input, especially for aquatic feed, has a very big financial significance because investments for pangasius farming are very high (about 5-6 billion VND / / crop) The results of this study are similar to many research results of other authors in the fisheries sector For example, the study results of Huy (2009) and Phong (2010) In general, from the research results as mentioned above, the farmers in MD have opportunities to improve their PE through reducing the amount of inputs In addition, the reduction of production costs will contribute to stabilizing the input materials for SEPEs, and thus contributing to stabilizing the supply of pangasius fillets for export Therefore, it will also make the income of farming households more stable In addition, having good competitive prices will create opportunities for the linkage between farmers and SEPEs to become more sustainable 21 The results of TE estimation as analyzed once again confirm that farmers should reduce stocking density and thus reduce the amount of aquatic feed to improve TE In addition, the data in Table 5.3 also show that the lowest and highest TE achieved between farms is very high, indicating that the farming techniques are not uniform among households Moreover, the analysis also showed that nearly 30% of households reached TE below the mean TE This shows that the farming techniques of farming households are still limited The results in Table 5.8 show that the mean CE of farming households is 78.1% with a fluctuation of 21.5%, meaning that farmers can cut the cost of using inputs by 21.9%, but still maintain a constant output The results of these households are relatively high, however, the CE difference between households is quite high, indicating that the production level among households is not equal Up to 34% of farmers achieved CE below the mean CE Table 5.8 Allocating frequency of cost efficiency coefficients of pangasius farming households Efficiency CE coefficiency (%) No of households Rate (%) 90 114 50 Total 227 100 Mean 78,1 Minimum 17,9 Maximum 97,3 Standard Deviation 21,5 In short, the research results show that farmers can improve their production level to increase their production efficiency Like the 22 above analysis, this reduction in production costs has a great significance to the survival and development of the pangasius industry in MD in general and of pangasius farming households in particular 4.2.2 Analyze factors affecting the production efficiency of farming households Through the literature review as well as the survey process, it is recognized that, in addition to the factors related to the use of production factors that affect the TE of farming households, factors that belong to socio-economic characteristics of farmers also has a certain influence on their TE The impact of these factors on the TE of the farmersis presented in Table 5.5 Table 5.5: The results of regression analysis on the effect of socioeconomic variables of farm households to technical inefficiencies Sign Name of Coefficien St.Dev P>[Z] variables t Z1 Education level -0.0187 0.0806 0.816 Z2 Experience -0.0311 0.0526 0.554 Z3 Squares the 0.0004 0.0019 0.838 number of years of experience Z4 Rate of hired -0.0128 0.0051 0.012** labour in the total number of used employees Z5 Fingerling source -4.2325 1.9636 0.031** is certified to be free of disease 23 Sign Coefficien t -0.3684 St.Dev P>[Z] 0.2996 0.219 0.4580 0.2893 0.113 0.0334 0.0449 0.457 Constant lnϭ2 0.2989 -1.1794 0.5254 0.3606 ilgtgamm a ϭ2 γ 3.7128 0.4959 0.569 0.001** * 0.000** * Z6 Z7 Z8 Name of variables Join in the input and output link Participating in technical and economic training courses Areas for raising pangasius 0.3075 0.1109 0.9762 0.0115 0,3001 0,1109 0,0073 0,0023 Notes: (**): Significant level of 5%; (***): Significant level of 1% The evaluation results are presented in Table 5.5, showing that, among the independent variables included in the regression equation, only two independent variables have a significant influence on TE The results indicated that farmers using the disease-free fingerlings were better than those who did not use a certified diseasefree fingerlings, at the 5% significance level In addition, the study results also showed that the more households using hired labor, the less the inefficiency of farmers, at the 5% significance level In other words, the more households use the hired labor, the more likely it is for farmers to raise TE 24 Like TE, through the use of equation 3.16, the impact of the socio-economic characteristics of households has an impact on the cost inefficiency The evaluation results are presented in Table 5.9 The results of analysis in Table 5.9 show that the rate of hired labor on the total number of employed workers has the effect of increasing the cost ineffective of farmers (at the 1% significance level) The results of analysis in Table 5.9 show that the rate of hired labor on the total number of employed workers has the effect of increasing the cost ineffective of farmers (at the 1% significance level) This is due to the labor shortage in rural areas that has pushed up the price of hired labor, forcing farmers to bear the cost of hiring labor, thus reducing CE's pangasius farming households The contradictory results of the effect of hired labor in the total number of used employees on technical and cost inefficiencies, according to the author, the proposed general solution for this issue is to encourage farmers to make the most of available family labor and increase investment in machinery and equipment to replace manual labor in stages that can be mechanized and automated Table 5.9: The results of regression analysis on the effect of socioeconomic variables of farm households to cost inefficiencies Sign Name of Coefficien St.Dev P>[Z] variables t Z1 Education level -0.1845 0.0984 0.061 Z2 Experience 0.1006 0.0716 0.160 Z3 Squares the -0.0040 0.0026 0.126 number of years of experience Z4 Rate of hired 0.0116 0.0042 0.006** labour in the total * 25 Sign Name of variables number of used employees Fingerling source is certified to be free of disease Join in the input and output link Participating in technical and economic training courses Areas for raising pangasius St.Dev P>[Z] -3.7943 2.5874 0.143 0.0791 0.2996 0.765 -0.2348 0.2642 0.243 -0.0985 0.2046 0.059 Constant lnϭ2 0.3396 -1.0862 0.0521 0.6077 ilgtgamm a ϭ2 γ 1.8486 0.3288 0.576 0.001** * 0.000** * 0.3375 0.8639 0.2916 0.0459 0.4197 0.1109 0.1113 0.0067 Z5 Z6 Z7 Z8 Coefficien t Note: (***): Significant level of 1% In summary, through the analysis of farming households’ PE, although the TE and CE of farming households are quite high, there is a quite large difference in production level between farming households, and there are still limitations in farming techniques Tóm lại, qua phân tích HQSX hộ ni cho thấy, TE CE hộ nuôi cao, có chênh lệch trình độ sản xuất hộ ni lớn có hạn chế định kỹ thuật ni In addition, the analysis results also 26 show that the quality of linkage between farmers and between farmers and EPEs is not really effective 4.3 Solutions for VC upgradation and the farming households’ production efficiency From the analytical results in Section 4.1 and 4.2, using analysis of SWOT matrix to propose solutions for VC upgradation and the farming households’s PE These solutions include: (i) Expanding linkage with EPEs based on production according to quality standards (VietGap, GlobalGap, ASC, BMP), (ii) Expanding farming area according to VietGap, GlobalGap, ASC, BMP standards, (iii) Reprogramming farming region according to VietGap production process and other international standards, along with strengthening vertical links between farmers and export processing enterprises, (iv) Raising awareness and level of production and business of farmers in the use of fingerlings, along with expanding the link between farmers and suppliers of disease free fingerlings, (v) Improving the quality of horizontal link among farmers, based on cutting production costs and raising production levels for farmers, (vi) Strengthen linkages between farming areas and provide market information for farms and businesses, and (vii) mprove communication quality and train information and market knowledge for farmers 4.4 Solutions for improving EPEs’ operating efficiency For EPEs, the author has also suggested solutions They are (i) expanding the development of value added processed products, (ii) expanding form of “farming processing” with PFHs, 27 farmer groups and cooperatives, (iii) expanding raw material areas of enterprises themselves to take initiative in material sources, and (iv) strengthening the horizontal linkages among the EPEs, on the basis of linking farming regions and sharing resources among the EPEs CONCLUSION AND THE DISSERTATION’S NEW CONTRIBUTIONS 5.1 Conclusion There are distribution channels in Pangasius VC in MD, in which the distribution channel from farmers directly to SEPEs is the main channel, accounting for 91.1% of total Pangasius of the whole VC This main distribution channel is mainly the consumption of exported pangasius SEPs play an important role in VC due to the simultaneous implementation of four market functions, including production, collection, processing and trade Profit distribution between farming households and SEPEs in the main consumption channel is quite reasonable During the operation of actors, organizations supporting and promoting the VC include DARD; Companies that provide inputs; Institutes; Universities; Local authorities at all levels and Banks The biggest gap in the stage of input supply is the lack of supply of clean fingerling for farmers In production, the biggest gap is that farmers use irrational inputs with production techniques and prices of available inputs In the processing stage, the gap discovered here is the instability of pangasius material source for processing, the momentary imbalance occurs frequently In the trading stage, the biggest difficulty is still the instability in output and price of output 28 products In addition, technical barriers of importing countries of Vietnam pangasius are increasing The results obtained from pangasius farrming households’ PE analysis show that, although Pangasius farmers have achieved relatively high PE, there are still certain limitations in farming techniques, especially for effective combination of inputs with the available technology and price of inputs Research results have shown that the use of disease-free fingerlings helps farmers raise TE In addition, the use of many hired workers also helps farmers get better TE and CE.` The quality of linkage among farmers to connect with input suppliers is almost not available Meanwhile, the quality of the output consumption link is not also really perfect In the link between farming households and SEPEs, there is an additional form that farming households raise pangasius raw material for SEPEs In order to upgrade the pangasius VC and improve PE for pangasius farming households in MD, the author proposed solutions as presented in section 4.3 5.2 The dissertation’s new contributions 5.2.1 In the side of theory According to the literature review on the database from the electronic libraries in the country and from the domestic and foreign scientific research journals, until the end of 2017, there has not been any research work on pangasius products in Vietnam, based on the approach that incorporates VC analysis and SFA or DEA analysis, to finally propose solutions to improve the actors’ performance in the pangasius VC, specifically for pangasius farming households in MD 29 Although in terms of analytical methods, some authors have applied this approach to achieve the same objectives mentioned, but these studies apply to plant objects Moreover, in these studies only DEA method was used, instead of using SFA Meanwhile, one of DEA's limitations is not taking into account errors due to uncontrolled external factors but actually affecting production inefficiency, especially in the aquaculture sector, because this industry is always heavily influenced by the external factors such as weather, climate, epidemics, etc Therefore, the combination of two methods of value chain analysis and PE analysis, using SFA in this dissertation is considered a new theoretical contribution 5.2.2 In the side of reality One of the new contributions of the dissertation in terms of the fact that although the solution to reduce production costs and enhance vertical linkages among production households, there are important contributions to the development of Pangasius VC However, at the time of the study, it was found that solutions to reduce production costs became more important than thoses to strengthen links Another new point is that in the vertical link between SEPEs and pangasius farming households, there is an additional form of linkage which is the form of farming households processing for SEPEs Compared to previous studies on pangasius VC in MD, this form not yet established or available but not yet popular Other practical contributions from the use of SFA as well as DEA to estimate technical and cost efficiencíe allow extension workers to inherit the results of the study to continue to implement demonstration models based on households with high technical and 30 cost efficiencíe Since then, perfecting the technical and economic process and then replicating the model to improve production efficiency for farmers LIST OF SCIENTIFIC WORKS PUBLISHED BY AUTHOR Le Thi Thanh Hieu, 2015.The pangasius farming households’ production efficiency in Dong Thap province, Cantho: Cantho University Le Thi Thanh Hieu 2016 The pangasius farming households’ production efficiency in An giang province Scientific Journal of Cantho University, 42d: 78 – 83 Le Thi Thanh Hieu, 2019 Analysis of the value chain and Pangasius farming households’ production efficiency in the Mekong Delta Journal of Scientific Research and Economic Development Taydo University, 6: 50-64 ... are still limitations in farming techniques Tóm lại, qua phân tích HQSX hộ ni cho thấy, TE CE hộ nuôi cao, có chênh lệch trình độ sản xuất hộ ni lớn có hạn chế định kỹ thuật ni In addition, the... and L1 for the case of appropriate Translog form The test results show that the appropriate form of production function is Translog Thus, Do vậy, the model of Translog stochastic frontier production... opposite case) Z7i: Participating in technical and economic training courses (valued at when the household attended technical and 10 economic training courses; in the opposite case) Z8i: Areas for