(Tiểu luận) processing and preserving aquatic products invietnam from 2015 to 2017

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(Tiểu luận) processing and preserving aquatic products invietnam from 2015 to 2017

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52.Current situation of Processing and Preserving Aquatic Products industry in Vietnam.... 144.1.2.Index analysis of frozen aquatic products processing and preservationindustry code 1020

FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATIONAL ECONOMICS …… ***…… MIDTERM ASSIGNMENT INDUSTRIAL ORGANIZATION PROCESSING AND PRESERVING AQUATIC PRODUCTS IN VIETNAM FROM 2015 TO 2017 Group 18 No Name Student ID 04 Nguyễn Tú Anh 2114410022 27 Từ Thị Thu Huyền 2114410080 50 Đặng Minh Nguyệt 2114410139 Credit class: KTEE408CLC.1 Instructors: Assoc Prof Dr Tu Thuy Anh PhD Chu Thi Mai Phuong Hanoi, March 2023 Table of Contents Introduction Current situation of Processing and Preserving Aquatic Products industry in Vietnam 2.1 Definition .6 2.2 Classification 2.3 Current situation of Processing and Preserving Aquatic Products industry in Vietnam Theoretical framework 11 3.1 Overview of Concentration Indices 11 3.1.1 The CR4 Index 11 3.1.2 The Herfindahl–Hirschman Index (HHI) 12 3.2 Theory of the model 12 Index analysis and model estimation: .14 4.1 Index analysis: .14 4.1.1 Index analysis of aquatic products processing and canning industry (code 10201): 14 4.1.2 Index analysis of frozen aquatic products processing and preservation industry (code 10202): .15 4.1.3 Index analysis of dried aquatic products processing and preservation industry (code 10203): 16 4.1.4 Index analysis of fish sauce processing and preservation industry (code 10204): 17 4.1.5 Index analysis of processing and preserving aquatic and other products industry (code 10209): 17 4.2 Data description and the correlation between variables 18 4.2.1 Data collection method 18 4.2.2 Data analysis method 18 4.2.3 Model specification .19 4.2.4 Data description 19 4.2.5 4.3 The correlation between variables 20 Model estimation results and validity testing 22 Case study of a business game 25 Conclusion and implications .26 REFERENCES 28 Table of Figures Table 1: Indexes of aquatic products processing and canning industry in 2015 2017 14 Table Indexes of frozen aquatic products processing and preservation industry in 2015 - 2017 .15 Table 3: Indexes of dried aquatic products processing and preservation industry in 2015 - 2017 16 Table 4: Indexes of fish sauce processing and preservation industry in 2015 2017 17 Table 5: Indexes of processing and preserving aquatic and other products industry in 2015 - 2017 .18 Table 6: Data description .19 Table 7: Correlation Matrix 20 Table 8: Multicollinearity testing 21 Table 9: Estimation result 23 Introduction The fisheries and aquaculture sectors have been increasingly recognized for their essential contribution to global food security and nutrition in the twenty-first century Global apparent consumption of aquatic foods increased at an average annual rate of 3.0 percent from 1961 to 2019, a rate almost twice that of annual world population growth (1.6 percent) for the same period Therefore, having an understanding of the field of Processing and preserving aquatic products is essential in ensuring high-quality and safe aquatic products to be distributed and marketed domestically and internationally Given the aforementioned fact, we choose the industry: "Processing and Preserving Aquatic Products” for analysis since it is one of the key contributors to Vietnam’s economic development Our research studies the Concentration indices including HHI and CR4 Index, which are employed to measure the level of competition and also to build a CobbDouglas production function of Processing and Preserving Aquatic Products industry in Vietnam from 2015 - 2017 to obtain more knowledge of Vietnam aquatic products processing and preserving and provide sound suggestions for its development In order to serve the purpose mentioned above, we intend to observe and analyze the data set collected from the General Statistics Office of Vietnam - GSO which includes concentration and operational efficiency’s indicator of businesses in the Processing and Preserving Aquatic Products industry The data is collected in Vietnam, span years from 2015 to 2017 and cover all the businesses involved in this industry so as to obtain the most comprehensive result and arrive at a decisive conclusion To achieve the set objectives, the following main research methods are used: collecting data through the dataset provided by GSO and information through related research documents and articles on the Internet, using quantitative research using Random Effect Model (REM) with the help of STATA software to study the Concentration indices and build a Cobb-Douglas production function The study is organized as follows: Introduction Current situation of Processing and Preserving Aquatic Products industry in Vietnam Theoretical framework Regression model evaluating the performance of Processing and Preserving Aquatic Products industry Real life business game Conclusion and implications Current situation of Processing and Preserving Aquatic Products industry in Vietnam 2.1 Definition Vietnam Standard Industrial Classification System (Issued together with the Prime Minister's Decision No 10/2007/QD-TTg dated January 23, 2007) classify Processing and Preserving Aquatic Products industry as following: - Sector code 102 - 1020: Industry code for processing and preserving aquatic products This group includes: Processing and preserving fish, shrimp, shellfish and molluscs; chilled, dried, smoked, salted, in brine, packed Producing fish, shrimp and crab products and molluscs; cooked fish, chunks, fried fish, caviar, caviar by-products Producing food for humans or animals from fish; Producing food from fish and other aquatic animals not for human consumption - This group also includes: Operations of ships engaged in fish processing and preservation; Processing seaweed - Excluding: Processing of whales on land or on specialized ships, which is classified as 1010 (Processing and preserving of meat and meat products); Document continues below Discover more Industrial from: Organization KTE408 Trường Đại học… 38 documents Go to course [ KTE408][Tiểu luận 20 cuối kì] PHÂN TÍCH… Industrial Organization 100% (2) Tiểu luận tổ chức 26 ngành Industrial Organization 100% (1) The Art of the 218 Storyboard Industrial Organization None How to draw comic 44 Industrial Organization None Report Internship 11 Industrial Organization None Lecture buổi 2 Industrial Organization None Manufacture of fats and oils from aquatic materials, which is classified as 10401 (Manufacture of animal oils and fats); Manufacture of ready-made seafood dishes, which is classified as 10752 (Manufacture of ready-made seafood dishes and foods); Manufacture of fish soup, which is classified as 10790 (Manufacture of other food not elsewhere classified) 2.2 Classification The industry is classified as ways as following: 1: As sector code : - 10201: Processing and canning seafood - 10202: Processing and preserving of frozen seafood: This group includes: Processing mainly frozen seafood and Preservation of aquatic products is mainly by freezing method - 10203: Processing and preserving of dried aquatic products: This group includes: Processing food mainly dried aquatic products and Preservation of aquatic products is mainly by drying, smoking, salting and canning methods - 10204: Processing and preserving fish sauce: This class includes: Processing and preservation of fish sauce and other aquatic animals - 10209: Processing and preserving other aquatic products This class includes: Activities of processing and preserving other fishery products, which have not been where to divide According to the data set collected from GSO, our study summarized the following table by running: Year Nganh_kd 2015 2016 2017 Total 10201 19 10202 100 89 88 277 10203 10 22 10204 12 11 10 33 10209 10 25 Total 141 122 113 376 2: As types of business: - State owned enterprises: if types of business are smaller than - Private enterprises: if types of business are bigger than and smaller than 11 - Foreign enterprises: if types of business are bigger than 10 According to the data set collected from GSO, our study summarized the following table: Year loaihinh 2015 2016 2017 Total 132 115 108 355 21 Total 141 122 113 376 3: As size of business: According to the Government's Decree 39/2018/ND-CP, the criteria for evaluating micro, small and medium-sized enterprises include the average number of employees participating in social insurance per year - Micro enterprises: less than 10 persons employed - Small enterprises: 10-99 persons employed - Medium-sized enterprises: 100-200 persons employed - Large enterprises: more than 200 persons employed According to the data set collected from GSO, our study summarized the following table: Year quymo 2015 2016 2017 Total 1 50 36 36 122 18 21 19 58 72 62 56 190 Total 141 122 113 376 2.3 Current situation of Processing and Preserving Aquatic Products industry in Vietnam Processing and Preserving is one of the most important steps to create added value in the seafood production chain This industry in Vietnam in recent years has developed rapidly and there are more opportunities for development in the future In Vietnam, in recent years, the seafood processing and preserving industry has developed rapidly, contributing to the overall growth of the whole seafood industry In the period 2010-2020, seafood export turnover increased by an average of 5.3%/year In 2021, despite being heavily affected by the Covid-19 epidemic, seafood export turnover still reached 8.89 billion USD, up 5.7% compared to 2020 Vietnam has become a group of seafood exporters in the region and is well-known in the world market In August 2021, the Vietnam Government approved the "Project to develop the seafood processing industry in the 2021-2030 period" with the intention to soon turn Vietnam into a global, modern and safe seafood processing center In the future, when our country expands its market, participating in cross-regional economic and trade organizations will create 2017 0.878 0.300 CR4 index: During the period 2015 - 2017, CR4 index was highly volatile The numbers show that the dried aquatic products processing and preservation industry was highly concentrated in 2015, but became quite competitive in 2016 However, in 2017, the industry was very concentrated again, with CR4 nearly 0.9 HHI: From the table, we can see that the HHI values in this period were quite different The industry has a high level of concentration at first Then, in 2016, it became quite competitive But the level didn’t last long In 2017, HHI became 0.3, which means the industry became strongly concentrated, with the level even higher than in 2015 4.1.4 Index analysis of fish sauce processing and preservation industry (code 10204): Using STATA to calculate CR4 and HHI, we have the following table: Table 4: Indexes of fish sauce processing and preservation industry in 2015 - 2017 Year Number of firms CR4 HHI 2015 12 0.807 0.218 2016 11 0.844 0.219 2017 10 0.906 0.231 CR4 index: 16 Between 2015 and 2017, CR4 index was always above 0.8, which shows a very high level of concentration In this period, CR4 increased gradually, meaning that the level of competition in the industry has fallen steadily over time HHI: From 2015 to 2017, the HHI was quite stable The index varied from 0.21 to 023, which means this industry has a high level of concentration During this time period, the HHI increased slowly but stably, showing that there was a steady rise in the level of concentration 4.1.5 Index analysis of processing and preserving aquatic and other products industry (code 10209): Using STATA to calculate CR4 and HHI, we have the following table: Table 5: Indexes of processing and preserving aquatic and other products industry in 2015 - 2017 Year Number of firms CR4 HHI 2015 10 0.806 0.199 2016 0.812 0.233 2017 0.834 0.223 CR4 index: From 2015 to 2017, it can be seen that the CR4 index was always above 0.8 The data shows that this industry was highly concentrated In this period, CR4 increased with a steady pace, proving that the level of competition in the industry has decreased gradually HHI: 17 Between 2015 and 2017, the HHI increased at first, but then decreased in 2017 The index shows that the industry had a high level of concentration, and this level increased then decreased, with a small amount of change 4.2 Data description and the correlation between variables 4.2.1 Data collection method Our group uses secondary panel data from the Enterprise survey data set of the Government Statistics Office We collected 376 observations of the firms in the Processing and Preserving Aquatic Products Industry (code 10) from 2015 to 2017 4.2.2 Data analysis method The study approaches the determinants of sales value of processing and preserving aquatic products firms, from 2015 to 2017, using a random effect model (REM) by STATA 4.2.3 Model specification We suggest the following population regression model lnsales = β0 + β1.lnL + β2.lnK + β3i.i.loaihinh + β4i.i.nganh_kd + β5i.i.quymo + uit Where: lnsales: Sales of products in the period This variable is taken logarithmically lnL: Average total number of employees in the period ((beginning + ending)/2) This variable is taken logarithmically lnK: Average total assets in the period ((beginning + ending)/2) This variable is taken logarithmically i.loaihinh: control variable representing the type of firms (i=1: state-owned enterprises, i=2: private enterprises, i=3: foreign-invested enterprises) 18 i.nganh_kd: control variable representing the industries that firms are in (i equals to the industry code) i.quymo: control variable representing the size of firms (i=1: micro enterprises, i=2: small enterprises, i=3: medium enterprises, i=4: large enterprises) uit: random error term 4.2.4 Data description By using the command ‘sum’ in STATA, we have the following data description table: Table 6: Data description VARIABLES N mean sd max nganh_kd 376 10,203 1.818 10,201 10,209 sales 376 547,488 1.194e+06 235.1 1.027e+07 L 376 435.7 779.8 6,938 K 376 380,823 962,097 1,144 9.427e+06 loaihinh 376 2.056 0.230 quymo 376 3.149 0.935 147 147 147 147 147 Number of ma_thue 4.2.5 The correlation between variables 19

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