Determinants affecting vietnamese riceexport to philippines from 1992 to 2021

N ATIONAL E CONOMICS U NIVERSITY FACULTY O F E CONOMICS A SSIGNMENT O N E CONOMETRICS DETERMINANTS AFFECTING VIETNAMESE RICE EXPORT TO PHILIPPINES FROM 1992 TO 2021 Class F INANCIAL E CONOMICS 63 Group FE 63 01 N OVEMBER 11, 2022 Instructor B UI D UONG H AI November 11, 2022 G ROUP E VALUATION No Member (Full name − ID) Dang Phuong Anh − 11219526 Contribution Search data source, Find and write theory, Run data, Build models, Find empirical research, Give comments on assignments Do Mai Anh − 11210335 Find data, Find theory, Find empirical research, Support: figures, references, Do: build models, give comments on assignments, model specification, run data and text editor on overleaf Doan Tung Lam − 11212981 Search: data and references, Write: Theory, Do: verification of hypothesis, give comments on assignment Dinh Thi Quynh Trang − 11219558 Search: figures and references; Write: introduction, empirical research, research gap and conclusion, Do: tests and predictions, Support: run data and build model % 25% 25% 25% 25% S UPERVISOR E VALUATION A B C D E Introduction, structure, research questions Literature review Methodology Results, data and analysis Discussion, conclusions, recommendations Presentation/ format/ Reference A DVANTAGE I MPROVEMENT 1.1 1.2 1.3 1.4 Problem statement Research questions Reason for choosing the topic Object and scope of the study 1.4.1 Research objectives 1.4.2 Scope of the study 1.5 Research methods 4 4 5 2.1 Empirical Research 2.1.1 Previous research by Vietnamese authors 2.1.2 Previous research by foreign authors 2.2 Research gap 2.3 Theory 2.3.1 GDP 2.3.2 Value of agricultural production 2.3.3 Population 5 6 6 3.1 Methodology 3.2 Research framework 3.2.1 Research model 3.2.2 Describe the data and independent variables 3.2.2.1 Independent variables and dependent variables 3.2.2.2 Describe the data 3.2.2.3 Sample regression model 9 10 10 10 10 4.1 Summary statistics and correlation matrix 4.2 Diagnosing Model Problems and Correction 4.2.1 Multicollinearity 4.2.2 Heteroscedasticity 4.2.3 Autocorrelation 4.2.4 Ramsey RESET Test 4.3 Multiple Regression Analysis 12 13 13 13 14 14 14 Are the results consistent with the theory? Are regression coefficients statistically significant? Statistic for overall significant Estimate confidence interval of coefficients (at the 5% meaning) 15 15 16 17 6.1 Summary of the research result 6.2 Limitations of the research 17 18 5.1 5.2 5.3 5.4 D ETERMINANTS A FFECTING V IETNAMESE R ICE E XPORT T O P HILIPPINES F ROM 1992 T O 2021 A SSIGNMENT O N E CONOMETRICS N OVEMBER 11, 2022 − The assignment aims to estimate the factors affecting Vietnam’s export of rice to the Philippines, one of the largest rice export markets of Vietnam − The assignment applies the multivariable model, which models the effect of factors on the Vietnamese export of rice to the Philippines from 1992 to 2021 − The assignment results illustrate that the factors that influence rice exports from Vietnam to the Philippines include the Gross Domestic Product (GDP) of the Philippines, value of agricultural production in Vietnam and population of importers Factors that have positive coefficients are value of agricultural production in Vietnam and population of Philippines while GDP of Philippines has negative coefficient in the period 1992 − 2021 FC (Financial crisis) dummy variable has positive coefficient in this model − The study cannot identify all specific factors, also the limitation of observation (only 30 years from 1992 to 2021) due to the limitation of data availability − Many existing studies suggest that the exportation of agricultural products in Vietnam, especially rice, is significantly affected by natural factors and economic factors They not concentrate on the biggest market for exporting rice − the Philippines Our assignment proved the significant impacts on Vietnam’s export of rice to its biggest market, the Philippines Therefore, the Vietnamese government can contribute to predicting the improvement of rice export turnover in the future Exports have played an important role in the economic development of many developing countries in recent years Based on the available background, Vietnam is one of the countries with the oldest rice civilization in the world Therefore, rice export is always an industry that brings great economic value and has a positive impact on the economy, helping to exploit the relative as well as absolute advantages of Vietnam in the economic development period With a high and stable production growth rate, Vietnam’s ability to export rice products has gradually increased over the years Vietnam has been one of the three largest exporters in the world for decades, most of Vietnam’s population is empowering the agricultural sector, where 82% of agricultural land in Vietnam is devoted to producing rice, and 78% of the rice produced is used for domestic consumption and the remaining 22% is used for export to various countries Currently, Vietnam has expanded its rice export market to more than 80 countries, of which the Philippines has always been the leading market for Vietnam’s rice imports However, the export of rice is not simply affected by factors inside the economy, there are externalities that also strongly affect this process, including the trend of international economic integration and trade liberalization In terms of exports, Vietnam enjoys a lot of tariff reductions Over the past 27 years, rice exports in general to the Philippines, in particular, have also grown strongly So what factors affect Vietnam’s rice production in the Philippines, how to increase rice export output, and how to increase export turnover without changing demand? Recognizing the urgency of the problem, in order to better analyze the factors affecting the export of rice, we chose the topic: ”Determinants affecting Vietnamese rice export to the Philippines from 1992 to 2021.” By using econometric models, our team wishes to be able to perceive the problem immediately, thereby finding a development direction suitable to the current situation in our country To achieve the above basic research objectives, the thesis will focus on answering and clarifying the following main research questions: • What are the main factors affecting Vietnam’s rice exports to the Philippines? • What is the trend and level of impact of each of those factors on Vietnam’s rice exports to the? Philippines? Rice exportation is considered one of the most important indicators of Vietnam’s economy As can be seen from Statista, a global statistical unit of data, Vietnam was the second largest rice exporter, with about 6.5 million metric tons of rice worldwide in 2021 In which, the Philippines has been the leading country in importing rice from Vietnam for a decade Analyzing the determinants affecting rice exportation from Vietnam to the Philippines is a practical topic for our economy Because the study will point out the factors that have positive effects as well as the factors that hinder the export turnover of Vietnam’s rice to the Philippines, from which the results of the study contribute to predicting the improvement of rice export turnover in the future Errors are unavoidable in the process of doing group assignments We look forward to hearing from our lecturer, tutor, and everyone else • Analysis of the current situation of Vietnam’s rice exports to the Philippines in the period from before accession to the present accession (from 1992 to 2021) • Detecting which key factors are affecting the export situation, and determining the trend and level of impact of each factor • Examine the influence of the event Financial Crisis of Vietnam from 2007 to 2009 on rice exportation by applying dummy variables • Using the application of the gravity model • Regression model of the above research The thesis focuses on assessing and quantifying the influence of factors on Vietnam’s rice exports to the Philippines through specific indicators, indicators, and analytical models Service export is not within the scope of the thesis Due to the lag and lack of updating of data provided by countries, the most accurate and complete data set started in 1992 The thesis uses secondary data sources for research during the period of 1992 to 2021 The thesis focuses on assessing the influence of factors on Vietnam’s rice exports to the Philippines Collect information and data on media such as articles, essays, and scientific studies on this subject Quantitative research through the steps of collecting secondary data from: https://data.worldbank.org https://www.gso.gov.vn (General Statistics Office of Vietnam) https://www.imf.org Then processed and analyzed in order to make specific conclusions on the impact of determinants affecting the rice exportation from Vietnam to Philippines analyzes and compares the economic performance of the ASEAN Free Trade Area (AFTA) to the trade flows of Vietnam and Singapore Using the gravity model, the study shows some interesting experimental results Firstly, the multilateral trade flows of Vietnam and Singapore are not significantly affected immediately after the signing of the AFTA agreement Second, the trade gap remains an obstacle to trade, research indicates that globalization and integration have not reduced the negative impact of geographical distance on trade despite industrial innovation Technology further helps reduce transportation costs Third, cultural factors, such as language differences and colonial relations have historically been important for bilateral trade flows Finally, differences in per Document continues below Discover more from: Econometrics 112 documents Go to course Bai giang Kinh te luong - co Hong Van 66 Econometrics 100% (6) Vi mô - laaaaa 92 Econometrics 100% (2) Baitap KTL - Exercise on chapter 30 Econometrics 100% (2) Huong Dan Su Dung Stata 2014 Tuan Anh UEH 65 Econometrics 100% (2) Lý thuyết tập kinh tế lượng chương có lời giải 19 Econometrics 100% (2) Examples Econometrics Econometrics 100% (1) capita income between trading partners have negative effects on bilateral trade Efforts to close the GDP gap among members, improve social infrastructure, and continue domestic reforms are seen as a means to overcome obstacles to the free flow of trade in the region analyzes the factors that affect Vietnam’s exports to ASEAN countries Using the gravity model, the study shows some useful experimental results for our research The export turnover of Vietnam’s goods to ASEAN countries tended to increase in the period 1997 − 2015 but was not stable The growth rate of export turnover decreased gradually The quality of Vietnamese goods is gradually improving, but the competitiveness is still low Therefore, Vietnamese goods often face many difficulties in the face of trade barriers in import markets examines the impact of AFTA on ASEAN member exports To analyze the effects, this paper has developed a basic gravity model to perform cross-sectional data analysis involving 60 countries, both members and non-members, for the following years 1991, 2001, and 2012 The estimated results of the gravity model show that the GDP of the exporting country has a positive effect on exports The GDP of importing countries positively affects exports Populations in exporting and importing countries have a large and positive influence on exports Therefore, income level and population have a great influence on the export flows of ASEAN member countries Distance variables related to transportation costs have become an important barrier to ASEAN members’ ability to export Contrary to the original topic, our research will only start from about 1992 − 2021 Due to the lack of data for the 90s, the lack of observations is a huge mistake on our part GDP, which stands for Gross Domestic Product, is the total monetary or market value of all the finished goods and services produced within a country’s borders in a specific time period As a broad measure of overall domestic production, it functions as a comprehensive scorecard of a given country’s economic health To calculate GDP, we use the formula: GDP C I where C is consumption, I is investment, G is government spending, NX is net exports G NX • GDP per capita measures a country’s economic output per person and is calculated by dividing the GDP of a country by its population • GDP is important because it gives information about the size of the economy and how an economy is performing The growth rate of real GDP is often used as an indicator of the general health of the economy In broad terms, an increase in real GDP is interpreted as a sign that the economy is doing well • GDP is not a measure of the overall standard of living or well − being of a country Although changes in the output of goods and services per person (GDP per capita) are often used as a measure of whether the average citizen in a country is better or worse off, it does not capture things that may be deemed important to general well − being Through the development of theories of trade and economic growth, exports have been identified as the driving force for the economic growth of countries for several basic reasons: Firstly, export growth will lead to the growth of a country’s aggregate demand Demand growth may not be sustained in a small, low-income economy, but export markets are seemingly endless, so openness to trade will not constrain aggregate demand growth Therefore, exports can be a catalyst for income growth Second, export expansion can enhance specialization in the production of exports, which in turn can raise productivity levels and lead to output growth Third, increased exports can ease foreign exchange stress This helps to increase the ability to import inputs for production, machinery, and equipment for investment, thereby boosting output growth Besides, openness to trade also helps promote technological progress and create more jobs, and factors of production will shift from less efficient areas to more efficient ones, thereby promoting economic growth In the opposite direction, economic growth can also have a positive effect on exports because faster output growth will increase productivity by exploiting economies of scale Increased productivity will help reduce labor costs in product costs if wages not increase in proportion to productivity growth, thereby contributing to lower domestic commodity prices This will help increase the countries’ competitive advantage and lead to increased export turnover Moreover, economic growth will accelerate the process of skill formation as well as technological progress, contributing to improved production efficiency, and leading to increased competitive advantages for countries in the international market, which in turn helps expand trade Value of agricultural production is an aggregate indicator reflecting the results of production and business activities in the agricultural sector in the form of physical products and services over a certain period of time The value of agricultural production is the target to promote the growth of agricultural production and output, which is a factor that directly affects exports An agrarian economy with a high production value means that it can produce a large enough output to meet import demand for the same amount of raw materials and inputs A population is a complete set group of individuals living in an economic geographical region or an administrative unit, being measured by census and represented by population pyramids over quantitative data Population is the labor force Population growth leads to growth in supply and demand and affects the social labor source, the organization of the social division of labor, and the material production process of society At the same time, it also affects all aspects of society’s life due to its suitability or inappropriateness with socio-political and economic development conditions The population of Vietnam and the partner country, specifically in this case, the Philippines, is a special factor On the one hand, the population is an important factor of production (labor force) that has a great influence on the output of manufactured goods On the other hand, the population is the source of the consumption of goods The population is used to measure the market size of each country A country with a large population has a large domestic market (Eita, 2008) The population is measured by the total number of people living in a country in year t The population of the importing country represents the potential demand for goods in the market as well as the labor force of that market When the population size increases, the demand for goods, especially essential goods such as agricultural products, increases, causing certain effects on the export turnover of the partner country is used to analyze and systematically interpret Vietnam’s export activities to the Philippines according to the process of integration and development of Vietnam, in this study specifically: the event of Financial Crisis from 2007 to 2009 of Vietnam, through which there is an objective and comprehensive comparison of rice export results over time to see the changes, especially the changes in the positive direction of Vietnam’s rice exports to potential markets like the Philippines is used to evaluate the results as well as identify the trends of Vietnam’s export activities to the Philippines over time This method is also used to evaluate fluctuations in the amount of rice exported to the Philippines by Vietnam in a certain period of time To ensure the accuracy of the data source used, the thesis has been collected from prestigious organizations in the world and in Vietnam As follows: • Data on GDP, and export turnover, are collected from the World Bank and GSO, United Nations Commodity Statistics Database (UN Comtrade); • Data on population is collected and calculated from WB; • Data on exchange rate data is collected from the International Monetary Fund (IMF); • In addition, the information on trade barriers of countries and regions, Vietnam’s import and export policies, trade agreements, etc is collected by looking up documents, texts, books, and previous studies used to describe the basic characteristics of the data collected during the research Through the system of research, indicators will have the most general view of Vietnam’s export activities to the Philippines market In addition to the general research methods used throughout the thesis, in order to better reflect the impact of factors on rice export turnover, at each stage of Vietnam’s integration into the region, the thesis uses the following methods: (through logarithm − linear model) Through the EVIEWS and EVIEWS 10 tools, we continue to check the reliability of the model and will make comments and forecasts on rice exports from Vietnam to the Philippines • Seeing the whole picture of Vietnam’s ASEAN integration process in 30 years, its achievements, and the problems facing Vietnam’s rice exports to the Philippines • Exploring and discovering factors affecting Vietnam’s rice export turnover to the Philippines Thereby, it is possible to detect new factors that have not been mentioned in previous studies • Select an appropriate quantitative research model • Explain some results of quantitative research • Provide some policy implications based on the research results Based on the research theory of the logarith-linear model Quantitative research is applied to consider the impact of quantifiable factors such as the value of agricultural production in Vietnam, GDP of the Philippines, the population of the Philippines, and integration variables such as Financial Crisis (FC) The built estimation model has the form EXPORT POPPHL GDPPHL VAPVNB Applying the least squares method (Least Square) to run a regression to measure the impact of factors such as the population of Philippines (POPPHL), Gross Product domestic of Philippines (GDPPHL), value of agricultural production of Vietnam (VAPVNB) on rice exportation from Vietnam to Philippines from 1992 to 2021 EXPORT POPPHL GDPPHL VAPVNB FC Rice exportation from Vietnam to Philippines (Billion USD) Population of Philippines (Million) Gross Domestic Product of Philippines (Billion USD) Value of agricultural production in Vietnam (Billion USD) World Bank indicator World Bank indicator World Bank indicator (+) (-) World Bank indicator (+) Financial Crisis in Vietnam (+) • Collected data shows information on basic factors related to rice exportation from Vietnam to Philippines: GDP and population of Philippines, value of agricultural production indicator by year • Data collections: We use data sources from 1992 to 2021 which are collected by the World Bank indicator – a verified source that is highly accurate and runs a model in Eviews 10 To test the influence of factors on EXPORT, we applied the theoretical basis and computing these models (1) EXPORT GDPPHL u, (2) EXPORT POPPHL u, (3) EXPORT VAPVNB u, (4) EXPORT FC (5) EXPORT GDPPHL POPPHL VAPVNB (6) EXPORT GDPPHL POPPHL VAPVNB (7) EXPORT GDPPHL POPPHL GDPPHL × POPPHL u, u, (8) EXPORT GDPPHL POPPHL VAPVNB (9) EXPORT GDPPHL POPPHL VAPVNB Dependent variable: EXPORT 10 FC u, u, u, FC u Var (1) 0.371 C (2) −3.624 (***) (3) 0.348 (*) (4) 1.624 (***) 0.007 (***) GDPPHL 0.06 (***) POPPHL 0.057 (***) VAPVNB FC GDPPHL × POPPHL R − sq Adj R − sq P − value (F − test) RMSE MAE MAPE P − value (RAMSEY TEST) P − value (WHITE TEST) P − value (JARQUE − BERA) P − value (BG) (5) 0.973 (6) 1.065 −0.014 (***) −0.005 −0.013 (***) −0.007 0.162 (***) 0.156 (***) 0.189 0.728 (7) −4.78 (***) 0.052 (***) 0.054 (**) (8) −2.201 (**) −0.009 (***) 0.026 (*) 0.082 (***) (9) −2.102 (**) −0.007 (***) 0.024 (*) 0.075 (***) 0.205 −0.000 (***) 0.6 0.586 0.646 0.634 0.736 0.726 0.044 0.01 0.837 0.819 0.84 0.814 0.755 0.73 0.866 0.85 0.872 0.852 0.000 0.000 0.000 0.264 0.000 0.000 0.000 0.000 0.000 0.655 0.488 36.564 0.616 0.475 30.988 0.532 0.385 26.025 1.013 0.907 87.591 0.418 0.29 20.205 0.415 0.294 20.248 0.513 0.379 26.886 0.472 0.334 22.358 0.461 0.329 21.654 0.0001 0.3543 0.0039 0.2125 0.2653 0.7484 0.0143 0.0291 0.002 0.025 0.005 0.234 0.312 0.333 0.225 0.808 0.733 0.076 0.14 0.552 0.255 0.002 0.0049 0.369 0.575 0.745 0.0077 0.021 0.059 0.0001 0.552 0.569 0.351 0.332 0.616 (*);(**);(***): sign at 10%; 5%; 1% The best model is EXPORT EXPORT − GDPPHL − POPPHL GDPPHL POPPHL VAPVNB FC VAPVNB FC We select the model (9) based on the following criteria • Overall significant test Hypothesis pair: H0: H1: Model is overall insignificant Model is overall significant P−value of F−test significant 000 05 ⇒ Reject H0, that means model (9) is overall • Ramsey test for one omitted variable According to the result above about Ramsey test, model (9) is no error in funtional form or it is unbiased • Model (9) has the lowest RMSE and MAE among nine models 11 • Adj R−sq Adjusted R−squared is a modified version of R−squared that has been adjusted for the number of predictors in the model The adjusted R−squared increases when the new term improves the model more than would be expected by chance It decreases when a predictor improves the model by less than expected As we can see model (9) Has the highest Adj R−sq among four model Summary Statistics, using the observations – 30 Mean Median Maximum Minimum Std Dev Skewness Kurtosis Jarque−Bera Probability Sum Sum Sq Dev Observations EXPORT GDPPHL POPPHL VAPVNB FC EXPORT 1.696398 1.38075 3.656807 0.363 1.053711 0.376589 1.723327 2.746461 0.253287 50.89195 32.19888 30 EXPORT 0.775034093 0.804010413 0.858125607 0.210565739 GDPPHL 184.1892 141.816 394.086 60.422 113.5273 0.51179 1.696753 3.432708 0.17972 5525.677 373765.2 30 GDPPHL 0.775034093 0.947930663 0.978820277 0.038812227 POPPHL 88.3734 88.6465 111.046 65.02 14.07273 −0.034108 1.789538 1.83734 0.399049 2651.202 5743.212 30 POPPHL 0.804010413 0.947930663 0.959378391 0.061029925 VAPVNB 23.54621 17.34761 48.6 4.209943 15.78876 0.23756 1.368926 3.607676 0.164666 706.3863 7229.267 30 VAPVNB 0.858125607 0.978820277 0.959378391 0.045590827 FC 0.1 0.305129 2.666667 8.111111 68.20988 2.7 30 FC 0.21056573 −0.03881222 0.06102992 0.04559082 • Cor EXPORT PGDPPHL 775 → The correlation between EXPORT and GDP Philippines is at the same dimension, with the percentage of 77.5% • Cor EXPORT POPPHL 804 → The correlation between EXPORT and Population is at the same dimension, with the percentage of 80.4% • Cor EXPORT VAPVNB 858 → The correlation between EXPORT and Value of agricultural production is not at the same dimension, with the percentage of 85.8% In general, the independent variables have a high correlation with the dependent variable, expect for the dummy variable FC In addition, the independent variables including the population, the GDP, the Value of agricultural production and Fc has a positive correlation with the dependent variable 12 EXPORT GDPPHL VAPVNB POPPHL FC EXPORT 1.07329616 89.6229861 13.8005741 11.5249294 0.06544383 GDPPHL VAPVNB POPPHL FC GDPPHL 89.6229861 12458.8405 1696.00947 1463.97008 −1.2996566 GDPPHL 0.978820278 0.947930664 −0.038812227 VAPVNB 13.8005741 1696.00947 240.975564 206.059789 0.21231722 POPPHL 11.5249294 1463.97008 206.059789 191.440416 0.25332666 FC 0.06544383 −1.2996566 0.21231722 0.25332666 0.09 VAPVNB POPPHL FC 0.978820278 0.947930664 −0.038812227 0.959378391 0.045590827 0.959378391 0.061029925 0.045590827 0.061029925 Because the correlation coefficients between the independent variables are less than 0.98, we can predict the model will not have multi−collinearity when model defects test Use VIF values Centered VIF GDPPHL 9.86 POPPHL 9.85 VAPVNB FC 1.002 1.22 The VIF value corresponds to the Centered VIF column on the resulting table VIF values are Smaller than 10 Therefore, we can see that the model has probability of low multicolinearity, suggest that multicollinearity does not exist in the model Heteroskedasticity Test: F−statistic Obs*R−squared Scaled explained SS White 842734 831069 10 45300 Prob Prob Prob F(4,25) Chi-Square(4) Chi-Square(4) 1522 1451 0335 Hypothesis: At the 5% meaning H H (Homoskedasticity),  (Heteroskedasticity) After conducting White’s General Heteroscedasticity Test, we found that the p-value of Chisquared is equal to 0.335, which is smaller than the significant level of 5%, therefore reject H0 (Homoskedassticity)so the regression model has the phenomenon of variable variance 13 The concept “autocorrelation” is intended to measure the relationship between a variable’s present value and any of its past values Our research was conducted using time series data, so we test for serial correlation − Breusch−Godfrey Serial Correlation LM Test: F−statistic 0.802312 Prob F(1,24) 0.3793 Obs*R−squared 0.970448 Prob Chi−Square(1) 0.3246 Hypothesis: At the 5% meaning H0: H1: No serial correlation, Serial correlation From the result: P−value 05 3793 05 → Not reject H0 → The regression model is not serial correlation Omitted Variables: t-statistic F-statistic Likelihood ratio Squares of fitted values Value df Probability 1.140457 24 0.2653 1.300641 (1,24) 0.2653 1.583277 0.2083 F-test summary: Test SSR Restricted SSR Unrestricted SSR Sum of Sq df 0.265225 5.159274 25 4.894049 24 Mean Squares 0.265225 0.206371 0.203919 LR test summary: Value Restricted LogL −16.16213 Unrestricted LogL −15.37049 Hypothesis: At the 5% meaning H H no omitted variable,  omitted variable From the result: P−value 2653 05 → Not reject H0, no omitted variable → The regression model didn’t omit the variable On average 14 = −2.102 − − Average Rice exportation from Vietnam to Philippines is -2.102 (Billion USD) that no have population of the Philippines (POPPHL), Gross Product domestic of Philippines (GDPPHL), value of agricultural production of Vietnam (VAPVNB) on rice exportation from Vietnam to Philippines = −0.007 When GDP Philippines increased by USD, average rice exportation of VietNam to Philippines decreased by 0.007% USD = 0.024 When population of Philippines increased by USD, average rice exportation of VietNam to Philippines increased by 0.024% USD =0.075 When values of agricultural production increased by USD, average rice exportation of VietNam to Philippines increased by 0.075% USD =0.205 In Financial Crisis in Vietnam, average rice exportation of VietNam to Philippines increased by 0.205% USD 0.872 The model’s independent variables explain about 87.2% of the change of the Rice exportation from Vietnam to Philippines 0.000 Based on the correlation table between dependent variables and independent variables and the expectation table on the effect of independent variables on independent variables, we can draw the observation that this result is consistent with the theory, specifically: • Population of the Philippines (sign of expectation (+)), correlation coefficient of 023 represents the positive correlation • Gross domestic product of the Philippines (sign of expectation (-)), correlation coefficient of − 007 represents the positive correlation • Value of agricultural production in Vietnam (sign of expectation (+)), correlation coefficient of 075 represents the positive correlation • Financial Crisis in Vietnam (sign of expectation (+)), correlation coefficient of 205 represents the positive correlation 15 − − − − − Hypothesis: At the 5% meaning H H 0,  → p − value 0033 05 → Reject H At significant level of 5%, coefficient of GDPPHL is significant H H 0,  → p − value 0865 05 → Not reject H At significant level of 5%, coefficient of POPPHL is significant H H 0,  → p − value 0005 05 → Reject H At significant level of 5%, coefficient of VAPVNB is significant H H 0,  → p − value 2782 05 → Not reject H At significant level of 5%, coefficient of VAPVNB is significant − So, at the 5% level of significance, all variables such as population of the Philippines, gross domestic product of the Philippines, value of agricultural production in Vietnam and financial crisis in Vietnam affect rice exporting H H 0,  From results F − statistic 42 71209 p − value 000 05 → Reject H , coefficient of independent variables is significant → The regression model is overall significant 16 • Estimate confidence interval of −0 008 069 × 002 −0 012 −0 008 069 × 002 −0 004 → Confident interval 95% of gross domestic production of Philippines is −0 012 −0 004 • Estimate confidence interval of 023 069 × 013 −0 004 023 069 × 013 049 → Confident interval 95% of population of the Philippines is −0 004 049 • Estimate confidence interval of 075 069 × 018 037 075 069 × 018 112 → Confident interval 95% of value of agricultural in Vietnam is 037 112 • Estimate confidence interval of 205 069 × 185 −0 177 205 069 × 185 587 → Confident interval 95% of financial crisis in Vietnam is −0 177 587 It would not be offensive to say that Philippines is currently Vietnam’s largest import market In the past, China has also been for many years the country with the highest proportion of Vietnam’s rice imports However, we cannot completely depend on anything − especially in the field of rice import and export Therefore, to prepare for bad cases in export such as: ”rescuing dragon fruit”, ”rescuing lobster”, then longan, lychee, Vietnamese agricultural products cannot be exported to the market In the ”neighborhood friend” market, our country urgently needs to expand into markets in other countries with this competitive advantage And our research paper is part of the explanation for this In this study, we have focused on solving some of the following problems: Firstly, the study has reviewed many studies on Vietnam’s exports in general to countries around the world as well as ASEAN countries, examining the factors affecting rice exports to the Philippines in two ways aspects are research methods and research results Thereby, the study has pointed out the basic factors affecting the export of goods that previous studies have mentioned At the same time, the report also pointed out gaps for further research and practical improvement Secondly, the thesis has systematized and clarified more theoretical issues about rice exports By clarifying the basis for selecting influencing factors, the thesis has analyzed in depth the 17 influence of factors on Vietnam’s rice exports to the Philippines Through theoretical analysis, the thesis shows the trend of impact of each factor on Vietnam’s rice export turnover to the Philippines Third, the study uses different approaches combined with theoretical analysis to build a framework to analyze the factors affecting rice exports of Vietnam to the Philippines as well as making hypotheses for estimation and testing The analytical methods used include both qualitative and quantification methods, including the use of logarithmic-linear models for estimation and testing Fourth, Vietnam’s rice export turnover to the Philippines tends to increase during the period, but not stable The growth rate of export turnover decreased gradually Vietnam’s rice quality is gradually improving, but competitiveness is still low Fifth, the event of Vietnam’s financial crisis did not really affect rice exports too much Therefore, Vietnamese goods often face many difficulties in the face of trade barriers in import markets The use of logarithm-linear model shows the factors affecting the rice export turnover of Vietnam Includes: (i) GDP of the Philippines, (ii) Population of the Philippines, (iii) Value of agricultural production in Vietnam, (iv) The financial crisis (2007-2009) of Vietnam The analysis results have shown positive and negative factors, and the results also show that the trend of the effects of the factors is quite consistent with the expectations that the hypotheses have made Besides the problems that have been solved, the thesis still has some limitations such as not finding all the factors affecting Vietnam’s rice exports to the Philippines; The thesis has only analyzed independently each factor to rice export but not yet evaluate the interaction between factors affecting the export turnover of goods; or the proposed solutions only stop at the aspect of boosting output and export turnover, but have not studied in terms of enhancing added value for Vietnam’s exports Our team hopes that some of these limitations will be overcome through the suggestions of teacher and everyone 18 [1] Ammi Ardiyanti (2015), , Master of Arts in Development Studies, Economics of Development, The Hague, The Netherlands [2] Bui, T.H.H and Chen, Q (2017), , Journal of the Knowledge Economy, Vol No 3, pp 830-844 Available at: https://link.springer.com/article/10.1007/s13132-015-0279-y [3] Fulton, M.E and Reynolds, T (2015), , American Journal of Agricultural Economics, Vol 97 No 4, pp 1206-1226 Available at: https://onlinelibrary.wiley.com/doi/abs/10.1093/ ajae/aav019 [4] Gbetnkom D and Khan A S (2002), , AERC Research paper 120 [5] Le Ngoc (2008), , In Pro-ceedings of the 2018 Conference of International Association of Agricultural Economists (IAAE), Vancouver, BC, USA [6] Linnermann H (1966), nomics Journal,Vol 77, 366-368 s, The Eco- [7] Nguyen K Doanh, Yoon Heo (2009), Available at: https://journals.sagepub.com/ doi/10.1177/223386590901200109 [8] Nguyen Thi Chau and Tofael Ahamed (2022), , Sustainabilit, DOI: 10.3390/su14148842, Available at: https://www.mdpi.com/2071-1050/14/14/8842 [9] Nguyen, (2018), , EconomiA, Vol 19 No 2, pp 251-265 https://www.sciencedirect.com/ science/article/pii/S1517758017300164?via%3Dihub [10] Tran Lan Huong (2019), Doctoral thesis , [11] Tran, T.V.H., Nguyen, H.Tran, M.D., Hoang, V.H and Hoang, V.H (2019), , Uncertain Supply Chain Management, Vol 7, pp 727-740 Available at: https://www.growingscience.com/uscm/ Vol7/uscm_2019_6.pdf [12] Villano, R.; Bravo-Ureta, B.E.; Sol´ıs, D.; Fleming, E , J Agri Econ 2015, 66, pp 129–154 Available at: https://onlinelibrary.wiley.com/doi/ 10.1111/1477-9552.12081 [13] Vu, H.T and Doan, H.Q (2013), , MPRA Working Paper, No 63891 Available at: https://mpra.ub uni-muenchen.de/63891/ (accessed 22 March 2020) 19