MIDTERM REPORT OF ECONOMETRICS TOPIC THE FACTORS EFFECTING GPD OF COUNTRIES IN THE WORD IN 2015

BANKING ACADEMY INTERNATIONAL SCHOOL OF BUSINESS MIDTERM REPORT OF ECONOMETRICS TOPIC: THE FACTORS EFFECTING GPD OF COUNTRIES IN THE WORD IN 2015 Lecturer: PhD Dinh Thi Thanh Binh Class: CityU 7C Members of team: - Le Nhu Nguyet CA7-074 - Le Mai Phuong CA7-077 - Nguyen Thi Yen CA7-116 - Bui Thi Thao Van CA7-113 - Nguyen Thi Thanh Thuy CA7-098 HA NOI, THANG 12 NAM 2020 CONTENTS Introduction Chapter 1: Theoretical and practical basis of GDP and a number of factors affecting GDP 1.1 Rationale of the study 1.2 Definition 1.3 Literature review on the factors affecting GDP in countries around the world Chapter 2: Research methodology and econometric model 2.1 Method Research 2.1.1 Model building method 2.1.2 Methods of data collection and processing 2.2 Building econometric models 2.2.1 Overall model: 2.2.2 A random sample regression model 2.3 Description of the data 2.3.1 Data source 2.3.2 Describe the statistics 3.1 Regression model 3.2 Analyze the results after run regression model 3.3 Meaning of Partial Regression Coefficients 3.4 Check the suitability of the model 10 3.5 Check the model's defects 10 3.5.1: Multicollinearity 10 3.5.2 Variable error variance 12 3.6 Correct model errors 15 Conclusion 17 Reference 18 Appendix 19 Introduction Econometrics is a social science in which the tools of economic theory, mathematics and statistical speculation are applied to the analysis of economic problems Econometrics use methodological tools of accounting to find out the nature of the statistics, make conclusions about the collected statistics from which to make predictions about economic phenomenon Since its inception up to now, econometrics have provided economists with a sharp measuring tool for measuring economic relations As students studying economics major, they recognize the need to study and learn about econometrics in logic analysis and problem research In order to understand more deeply about bringing econometrics into real life and applying econometrics properly and effectively, the group cm would like to build the REPORT ON ECONOMETRICS under the guidance of PhD Dinh Thi Thanh Binh Gross domestic product (GDP) is a basic indicator reflecting economic growth, economic size, per capita economic development, economic structure and price changes a country Therefore, GDP is an important and suitable tool widely used around the world to survey developments and changes in the national economy Accurate perception and proper use of this indicator have important implications in surveying and evaluating the state of sustainable, smooth and comprehensive development of the economy Any country wants to maintain a growing economy with currency stability and jobs for the population whose GDP is one of the specific signals for government efforts Therefore, studying the key factors of GDP growth, the factors that influence GDP, can help the government change its policies to achieve its goals to promote economic growth These are macro issues that everyone working in the economic sector is concerned about That is why our team decided to study the topic: “Some factors affecting the gross domestic product (GDP) of countries in the world in 2015 This essay will use table data analysis methods to study and analyze some factors to GDP in 60 countries in 2016 The research object is the degree of influence of the four main influencing factors, including: investment, export, import and inflation rate By applying the knowledge from econometrics with socio-economic knowledge to analyze and find relationships between variables, the essay of the research team will answer the questions : How the main factors affecting GDP ? What is the specific level of influence? …During the study, usage data were collected from the World Bank and used the econometric analysis tool STATA software to analyze and research based on the data The research team has put a lot of effort in searching for information to complete this essay, but due to many limitations in expertise and experience, the essay cannot be avoided The research team is looking forward to receiving comments from TS.Dinh Thi Thanh Binh to be able to complete the essay better The team sincerely thanks! Chapter 1: Theoretical and practical basis of GDP and a number of factors affecting GDP 1.1 Rationale of the study Economic growth and development is the first goal of all countries in the world, the primary measure of the progress of nations in each stage Each country has its own definition of its own strategy for socio-economic development Not only a country, but in Vietnam, too, always considers economic development a very urgent task After more than 20 years of renovation, Vietnam has made remarkable progress, our country has moved from a stagnant subsidized economy to a market economy in the socialist orientation The annual gross national income has increased Moreover, our country is now joining the WTO global economy, integrating into the international economy This is a very important step and opens up a promising economy Economic growth takes place, it is manifested that the GDP growth rate is increasing and stable for a long time, the economy will have many great achievements Thus, the more stable people's income and living standard, the more developed the country is Therefore, economic growth is considered as an attractive issue in economic research, it is the focal point to reflect the changing face of the national economy To evaluate a country's economy, economists evaluate the gross domestic product GDP 1.2 Definition Gross domestic product or GDP is the monetary value of all final products and services produced within a territory over a specified period of time, usually a year GDP is a measure of the value of a country's economic activity In terms of nature, GDP is an index given to assess the overall growth rate of the economy, assessing the development level of a region / country Investing has different implications in finance and economics In economics, investment is related to saving and delaying consumption Investment is related to many sectors of the economy, such as business management and finance whether for households, businesses, or government In finance, financial investment is placing money in an asset with the expectation of capital appreciation, often in the long term This may or may not be supported by research and analysis Most or all investment involves some form of risk, such as investments in equity, real estate and even fixedrate securities that could, among other things, inflation risk According to classical international trade theory, when the division of social labor reaches a certain level, production specialization is carried out allowing for higher productivity, more and more goods not just respond To fully satisfy domestic consumption demand, which inevitably leads to the exchange of goods outside the national territory Thus, in essence, export is the exchange of goods between countries, there are many different interpretations of export such as: According to the Vietnam Open Learning Library (VOER), exporting is a basic activity of foreign trade, it has been around for a long time and has grown steadily From the first basic form of goods exchange between countries, up to now it has been very developed and manifested in many forms Today's export activities take place on a global scale, in all industries and sectors of the economy, not only tangible goods but also intangible goods with an increasing proportion Export is aimed at collecting foreign currencies, increasing accumulation for the State budget, developing production and business, exploiting the advantages of the country potentials and improving the quality of people's life Import means the import of goods and raw materials from other countries in the world to their own territory for consumption or to meet production needs This is how most people define an import normally However, in the Wikipedia and Vietnam's commercial law, imported goods are defined in more detail According to Wikipedia, imports are understood as transactions related to goods or services from an external source through national borders This is an international business, not a single wholesaling, but operated under a system, including organizations inside and outside the importing country This exchange of goods, materials and services will be based on the principle of par value, with currency used as a broker In Article 28, Clause of the Commercial Law 2015, the import definition is as follows: “Import of goods means the goods brought into the territory of Vietnam from abroad or from a special area located in the territory of Vietnam is considered a private customs area as provided for by law.” Inflation is the continual increase in the general price of goods and services over time and the loss of the value of a currency When the overall price rises, a single currency can buy less goods and services than before, so inflation reflects a decrease in purchasing power per unit of currency When compared to other countries, inflation is a decrease in the monetary value of one country relative to the currencies of another In the first sense, one understands that inflation of a currency affects the scope of a country's economy, while in the second one understands that inflation of a currency affects the scope of the economy actual use of that currency The sphere of influence of these two components remains a controversial issue among macroeconomists The opposite of inflation is deflation An index of zero inflation or a small positive index is called "price stability" 1.3 Literature review on the factors affecting GDP in countries around the world There have been numerous studies on the factors affecting GDP in the world through quantitative and qualitative research In the 2015, Master Nguyen Minh Sang & Ngo Nu Dieu Khue's study is conducted to test the non-linear relationship between inflation and economic growth by using selfregression method with a sample of 17 developing countries, including Vietnam period from 2000 to 2012 The model estimation results showed that there exists an inflation threshold that when inflation exceeds this threshold, it will have a negative impact on economic growth Based on Vietnam's practice, the research team discusses the causes of the growth differences between Vietnam and other countries and makes some policy suggestions to improve inflation control capacity at a reasonable level and bring into play the positive impact that inflation can have on Vietnam's economy According to study of Rebeca and Marcelo (2006), This study assesses empirically the effects of oil price shocks on the real economic activity of the main industrialized countries Multivariate VAR analysis is carried out using both linear and non-linear models The latter category includes three approaches employed in the literature, namely, the asymmetric, scaled and net specifications Evidence of a nonlinear impact of oil prices on real GDP is found In particular, oil price increases are found to have an impact on GDP growth of a larger magnitude than that of oil price declines, with the latter being statistically insignificant in most cases Among oil importing countries, oil price increases are found to have a negative impact on economic activity in all cases but Japan Moreover, the effect of oil shocks on GDP growth differs between the two oil exporting countries in the sample, with the UK being negatively affected by an oil price increase and Norway benefiting from it Based on studies we just learned, we decided to choose variables for the model, including: Dependent variable: Y Gross Domestic Product GDP (Unit: billion USD) Independent variables: - Investment I (Unit: billion USD) - Export XK (Unit: billion USD) - Import NK (Unit: billion USD) - Inflation L (Unit: %) Chapter 2: Research methodology and econometric model 2.1 Method Research 2.1.1 Model building method Regression analysis method: Find the dependencies of a variable, called the dependent variable on one or more other variables, called independent variables for the purpose of estimating or predicting the expected value of the dependent variable of the foreseeable values of the independent variable, specifically in this study, analyzing the relationship between the independent variable (Investment, Export, Import and Inflation) and dependent variable (GDP) 2.1.2 Methods of data collection and processing - Methods of data collection For research and modeling purposes, the team collected samples and their estimated values based on data of 60 observations in 2015 from 60 countries around the world Data of the model are cross-sectional data, collected statistically with reliable data sources from World Bank - Data processing method By estimating the coefficients of the normal minimum average model OLS, the data is selected and checked the statistical significance of the regression coefficients and the suitability of the model based on observations, also as compared to previous and similar studies to find the best results to use for analysis During the homework, the group used the knowledge of econometrics and macroeconomics, quantitative methods with the main support of STATA, Microsoft Excel, and Microsoft Word software to synthesize and complete this essay 2.2 Building econometric models After studying and referencing studies that have been done before, our team decided to use multiple regression analysis to find out the dependence of GDP dependent variable for independent Investment, Export, Import and Inflation for the 2015 period The model consists of variables: - Dependent variable: Y Gross domestic product GDP (Unit: USD) - Independent variables: + Investment I (Unit: USD) + Export XK (Unit: USD) + Import NK (Unit: USD) + Inflation L (Unit: %) 2.2.1 Overall model: Based on economic theory, to analyze the effects of factors on average life expectancy, the group chose to study the linear regression model and take the logarithm of the variable GDP: Y =  +  I +  XK +  NK +  L+ ui Inside : • 1: Intercept factor • 2: Angular coefficient of variable I • 3: Angular coefficient of variable XK • 4: Angular coefficient of variable NK •5: Angular coefficient of variable L • ui: Population random error corresponding to ith observation, which represents other factors affecting GDP but not mentioned in the model 2.2.2 A random sample regression model = + + + + + Inside: : estimate of intercept : the estimated slope of the variable I : the estimated slope of the variable XK : the estimated slope of the variable NK : the estimated slope of the variable L : remainder, estimate of random error 2.2.3 Predict expectations between variables: positive: An increase in investment will lead to an increase in gross domestic product positive: When the export value increases, it will lead to an increase in gross domestic product - negative: When the import value increases, the gross domestic product of GDP will decrease negative: When the inflation rate increase, the gross domestic product of GDP will decrease 2.3 Description of the data 2.3.1 Data source - Data found from the World Bank - Sample space: The survey was conducted in 60 countries around the world, with different levels and development histories Therefore, we realize that this sample space is large enough, objective and reliable enough to build up a regression model 2.3.2 Describe the statistics In order to help the reader have the most overview as well as give some initial assessment, the group will describe the data before proceeding to analyze the data Through this description, the team is able to predict some possible errors when running the model due to lack of data The figures include: Total investment capital (I), Total Export value, Total import value, Inflation rate(L) and Gross Domestic Product (GDP) of countries in the world in 2015 Table 2.1 Statistical description of the variables Variable | Obs Mean Std Dev Min Max -+ country | gdp | 60 426.571 | 60 -1.316 export | 60 131.025 import | 60 164.4662 infation | 60 investment 1524.337 54 11061.55 -68.09 68.43 368.2428 36 2266.53 432.609 26 2583.35 -30.24 17.15 16.82543 1.790333 5.597395 -+ - In term of Gross Domestic Production, Germany has the highest proportion in comparing with 59 nations, being at 11%, while Dominica shows the lowest percentage of 0.54% In the rate of Investment, Germany continues to have the largest percentage, account for 68.43% when the lowest figure of -68.09% is China With regard to Export, China takes a lead with the highest rate at 22.6%, whereas, Dominica continues to stand at the end with the lowest number (0.36%) Concern about Import, China shows the biggest import rate at 25.8% compared to the smallest figure for Gambia, being at 0.26% In the last category, the highest inflation rate is Ghana with 17.15% while Bahamas has the lowest figure at -30.24% Chapter 3: Quantitative Analysis 3.1 Regression model Table 3.1 Regression Model reg gdp investment export import inflation Source | SS df MS -+ -Model | 133847507 33461876.7 Residual | 3245135.9 55 59002.4708 -+ -Total | 137092643 59 2323604.11 Number of obs F(4, 55) Prob > F R-squared Adj R-squared Root MSE = = = = = = 60 567.13 0.0000 0.9763 0.9746 242.9 -gdp | Coef Std Err t P>|t| [95% Conf Interval] -+ -investment | -26.54081 1.923016 -13.80 0.000 -30.39462 -22.687 export | 3.382309 274932 12.30 0.000 2.831333 3.933285 import | 3527466 2331067 1.51 0.136 -.1144097 819903 inflation | -4.512621 5.712118 -0.79 0.433 -15.95996 6.934719 _cons | -101.4596 35.13832 -2.89 0.006 -171.8784 -31.04083 3.2 Analyze the results after run regression model From the regression model above, we have the following table of data: Table 3.2 Data synthesis table from regression model Variable _cons Investment Export Import Inflation -101.4596 -26.54081 3.382309 3527466 -4.512621 t -2.89 -13.80 12.30 1.51 -0.79 p-value 0.006 0.000 0.000 0.136 0.433 Confidence Interval [-171.8784; - 31.04083] [-30.39462;-22.687] [2.831333;3.933285] [-.1144097;.819903] [-15.95996;6.934719] From the table above we have the sample regression equation SRF: = -101.4596 + -26.5408*investment+ 3.382309*export + 0.3527466*import + -4.512621*inflation + The model shows that: Investment, Export, Import and Inflation have an impact on Gross Domestic Product It means that the independent variable (Investment, Export, Import, and Inflation) in the model can explain 97.63% of the variation of GDP So, 2.37% of the variation of GDP is explained by other variation that is excluded from the model By theory, they are included in 3.3 Meaning of Partial Regression Coefficients - For 1: When the variables Investment, Export, Import, Inflation has value equal to 0, the average GDP is -101.4596 units, it is the average effect of other factors that are not in the model to GDP - For 2: : When the factors remain constant and if the investment capital increases multicollinearity Multicollinearity is a fault of the regression analysis model that occurs when the independent variables Xi look linearly correlated with each other b) The causes: There are causes of multicollinearity problem • Perfect multicollinearity occurs when wrong model is placed In fact, perfect multicollinearity occurs rarely • Incomplete multicollinearity occurs due to the socioeconomic phenomenon that independent variables already have collinearity relationship with each other • Incomplete multicollinearity occurs because the survey data are not large enough, or the survey data are not randomized c) How to detect multi-collinearity Method 1: Use the corr command to check multicollinearity If the independent variables are strongly correlated with each other (r> 0.8), the multicollinearity phenomenon can occur Using the corr command, the following output is obtained corr gdp investment export import inflation (obs=60) | gdp invest~t export import inflat~n -+ gdp | 1.0000 investment | -0.3898 1.0000 export | 0.9453 -0.1124 1.0000 import | 0.8972 -0.0732 0.9489 1.0000 inflation | 0.0071 -0.1417 -0.0197 -0.0174 1.0000 Method 2: Use the variance inflation factor (VIF) If VIF> 10, the phenomenon of multicollinearity occurs Using the vif command in stata software, we obtained the following result: vif Variable | VIF 1/VIF -+ -export | 10.25 0.097566 import | 10.17 0.098337 investment | inflation | 1.05 1.02 0.955256 0.978255 -+ -Mean VIF | 5.62 11 We see that all VIF values are chi2 = 0.0000 chi2 = 0.0000 Therefore, the model has variable error variance 13 Method 3: Plot the error and estimated value of variable Y and observed reg gdp investment export import inflation Source | SS df MS -+ Number of obs = 60 F(4, 55) = 567.13 Model | 133847507 33461876.7 Prob > F = 0.0000 Residual | 3245135.9 55 59002.4708 R-squared = 0.9763 Adj R-squared = 0.9746 Root MSE = 242.9 -+ -Total | 137092643 59 2323604.11 -gdp | Coef Std Err t P>|t| [95% Conf Interval] -+ -investment | -26.54081 1.923016 -13.80 0.000 -30.39462 -22.687 export | 3.382309 274932 12.30 0.000 2.831333 3.933285 import | 3527466 2331067 1.51 0.136 -.1144097 819903 inflation | -4.512621 5.712118 -0.79 0.433 -15.95996 6.934719 _cons | -101.4596 35.13832 -2.89 0.006 -171.8784 -31.04083 - rvfplot, yline(0) The blue dots in the figure represent the positions of the errors for each fitted values of variable Y (fitted values) If the distances of these blue dots to the mean are similar, we can 14 imply that no variance occurs However, in the figure above, the further to the right we see, the further away the blue dots are from the mean This implicitly signals us that a variable variance has occurred Method 4: Jacque-Beratest predict u, residual histogram u, normal (bin=7, start=-810.34424, width=227.90202) sktest u Skewness/Kurtosis tests for Normality joint -Variable | Obs Pr(Skewness) Pr(Kurtosis) adj chi2(2) Prob>chi2 -+ u | 60 0.0005 0.0001 19.91 0.0000 As-p-value= 0.0000 F = 0.0000 R-squared = 0.9763 Root MSE = 242.9 -| gdp | Robust Coef Std Err t P>|t| [95% Conf Interval] -+ -investment | -26.54081 4.72646 -5.62 0.000 -36.01285 -17.06877 export | 3.382309 2684598 12.60 0.000 2.844304 3.920315 import | 3527466 1825633 1.93 0.058 -.0131183 7186116 inflation | -4.512621 2.980837 -1.51 0.136 -10.48635 1.461109 _cons | -101.4596 28.85043 -3.52 0.001 -159.2772 -43.64204 From the test of the fixed model, we see that only the import variable, inflation has no statistically significant effect on the GDP variable in the model We will run the new model to test as follows: reg gdp investment export Source | SS df MS -+ -Model | 133678328 66839164 Residual | 3414314.59 57 59900.256 -+ -Total | 137092643 59 2323604.11 Number of obs = 60 F(2, 57) = 1115.84 Prob > F = 0.0000 R-squared = 0.9751 Adj R-squared = 0.9742 Root MSE = 244.75 -gdp | Coef Std Err t P>|t| [95% Conf Interval] -+ -investment | -26.01453 1.905834 -13.65 0.000 -29.8309 -22.19817 export | 3.779609 0870797 43.40 0.000 3.605235 3.953983 _cons | -102.8874 33.59125 -3.06 0.003 -170.1527 -35.6221 After running the new model, the relevance of the model R = 0.4742, slightly reduced compared to the previous R2 = 0.4763 The p-value values are all less than 0.05, so the independent variables in the model are statistically significant at the 5% significance level Thus, the model's variable error variance has been overcome 16 Conclusion A research report on factors influencing GDP of 60 countries over the world is completed by the knowledge contribution of five group members The research method of this paper is to uses stata software to analyze and measure economic relations by the logic of data This exercise gives us many opportunities to apply the knowledge learned in econometrics and have a sea of chance to learn and compare in depth about the relationships that affect GDP of 60 countries all over the world as well as the development and creation on team work The introductory research paper provides background assessments of the research problem and introduces relevant problem tissues through specific, carefully selected and accurate data Next is the statistic description of the variables using the sum command and quantitative analysis to produce a concise and complete essay The research paper is not only written on the accumulated knowledge of the group after one semester but also completed by the enthusiastic and dedicated teaching of teacher Dinh Thi Thanh Binh We sincerely thank you for imparting endless knowledge We look forward to your comments on our mistakes and carelessness in the article 17 Reference  World Bank (WB) Website https://data.worldbank.org/indicator/NY.GDP.MKTP.CD?most_recent_year_d esc=true https://data.worldbank.org/indicator/BM.GSR.TOTL.CD?most_recent_year_d esc=false https://data.worldbank.org/indicator/BX.GSR.TOTL.CD?most_recent_year_de sc=false https://data.worldbank.org/indicator/BN.KLT.DINV.CD?name_desc=true https://data.worldbank.org/indicator/FP.CPI.TOTL.ZG?name_desc=false  Econometric report (by Econometric Group, 2014) https://www.tandfonline.com/doi/abs/10.1080/0003684042000281561?fbclid=Iw AR32Cpmgxnb3Z-7YqttIsHcwmy3REjIFgZ10Uu7tq9Hvy47F-YKcN3fyEwM  Oil price shocks and real GDP growth: empirical evidence for some OECD countries (by Rebeca Jiménez-Rodríguez & Marcelo Sánchez, 2006) https://static-cdn.uef.edu.vn/newsimg/tap-chi-uef/2015-03-04-21/4-so21.pdf?fbclid=IwAR0gt78F5mkKDzHQo7Iy0rGX6kJnjUS3zngNg6gE3n7fVgFV EdSS_P8tJHQ 18 Appendix  Commands and results in STATA * Statistic description of variable: sum gdp investment export import inflation Variable | Obs Mean Std Dev Min Max -+ gdp | 60 426.571 1524.337 54 11061.55 investment | 60 -1.316 16.82543 -68.09 68.43 export | 60 131.025 368.2428 36 2266.53 import | 60 164.4662 432.609 26 2583.35 inflation | 60 1.790333 5.597395 -30.24 17.15 * Regression model: reg gdp investment export import inflation Source | SS df MS -+ -Model | 133847507 33461876.7 Residual | 3245135.9 55 59002.4708 -+ -Total | 137092643 59 2323604.11 Number of obs F(4, 55) Prob > F R-squared Adj R-squared Root MSE = = = = = = 60 567.13 0.0000 0.9763 0.9746 242.9 -gdp | Coef Std Err t P>|t| [95% Conf Interval] -+ -investment | -26.54081 1.923016 -13.80 0.000 -30.39462 -22.687 export | 3.382309 274932 12.30 0.000 2.831333 3.933285 import | 3527466 2331067 1.51 0.136 -.1144097 819903 inflation | -4.512621 5.712118 -0.79 0.433 -15.95996 6.934719 _cons | -101.4596 35.13832 -2.89 0.006 -171.8784 -31.04083 * P-value method ovtest Ramsey RESET test using powers of the fitted values of gdp Ho: model has no omitted variables F(3, 52) = 234.47 Prob > F = 0.0000 * Use the corr command to check multicollinearity corr gdp investment export import inflation (obs=60) | gdp invest~t export import inflat~n -+ gdp | 1.0000 investment | -0.3898 1.0000 19 export | 0.9453 -0.1124 1.0000 import | 0.8972 -0.0732 0.9489 1.0000 inflation | 0.0071 -0.1417 -0.0197 -0.0174 1.0000 * Use the variance inflation factor (VIF) vif Variable | VIF 1/VIF -+ -export | 10.25 0.097566 import | 10.17 0.098337 investment | 1.05 inflation | 1.02 0.955256 0.978255 -+ -Mean VIF | 5.62 * White test imtest, white White's test for Ho: homoskedasticity against Ha: unrestricted heteroskedasticity chi2(14) = 58.00 Prob > chi2 = 0.0000 Cameron & Trivedi's decomposition of IM-test Source | chi2 df p -+ Heteroskedasticity | 58.00 14 0.0000 Skewness | 11.55 0.0210 Kurtosis | 7.18 0.0074 -+ Total | 76.73 19 0.0000 - * Breusch-Pagan test hettest Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of gdp chi2(1) = 121.44 Prob > chi2 = 0.0000 20 * Plot the error and estimated value of variable Y and observed reg gdp investment export import inflation Source | SS df MS -+ Number of obs = 60 F(4, 55) = 567.13 Model | 133847507 33461876.7 Prob > F = 0.0000 Residual | 3245135.9 55 59002.4708 R-squared = 0.9763 Adj R-squared = 0.9746 Root MSE = 242.9 -+ -Total | 137092643 59 2323604.11 -gdp | Coef Std Err t P>|t| [95% Conf Interval] -+ -investment | -26.54081 1.923016 -13.80 0.000 -30.39462 -22.687 export | 3.382309 274932 12.30 0.000 2.831333 3.933285 import | 3527466 2331067 1.51 0.136 -.1144097 819903 inflation | -4.512621 5.712118 -0.79 0.433 -15.95996 6.934719 _cons | -101.4596 35.13832 -2.89 0.006 -171.8784 -31.04083 - rvfplot, yline(0) 21 * Jacque-Beratest predict u, residual histogram u, normal (bin=7, start=-810.34424, width=227.90202) sktest u Skewness/Kurtosis tests for Normality joint -Variable | Obs Pr(Skewness) Pr(Kurtosis) adj chi2(2) Prob>chi2 -+ u | 60 0.0005 0.0001 19.91 0.0000 As-p-value= 0.0000 F R-squared Root MSE = = = = = 60 75.59 0.0000 0.9763 242.9 -| Robust gdp | Coef Std Err t P>|t| [95% Conf Interval] -+ -investment | -26.54081 4.72646 -5.62 0.000 -36.01285 -17.06877 22 export import inflation _cons | | | | 3.382309 3527466 -4.512621 -101.4596 2684598 1825633 2.980837 28.85043 12.60 1.93 -1.51 -3.52 0.000 0.058 0.136 0.001 reg gdp investment export Source | SS df MS -+ -Model | 133678328 66839164 Residual | 3414314.59 57 59900.256 -+ -Total | 137092643 59 2323604.11 2.844304 -.0131183 -10.48635 -159.2772 Number of obs F(2, 57) Prob > F R-squared Adj R-squared Root MSE 3.920315 7186116 1.461109 -43.64204 = = = = = = 60 1115.84 0.0000 0.9751 0.9742 244.75 -gdp | Coef Std Err t P>|t| [95% Conf Interval] -+ -investment | -26.01453 1.905834 -13.65 0.000 -29.8309 -22.19817 export | 3.779609 0870797 43.40 0.000 3.605235 3.953983 _cons | -102.8874 33.59125 -3.06 0.003 -170.1527 -35.6221 23 Table Data GDP (billion USD) 19.90 Investment (billion USD) -0.17 Export (billion USD) 8.56 Import (billion USD) 1.70 Inflation (%) -0.66 Albania 11.38 -0.91 5.35 3.51 1.90 Algeria 166.36 0.64 69.89 40.10 4.78 1.33 -0.99 0.96 1.03 0.97 10.55 -0.15 4.87 4.02 3.73 2.91 0.03 2.30 2.48 0.47 1351.69 -38.63 338.64 282.50 1.51 381.81 5.83 209.82 219.96 0.90 Azerbaijan 53.07 -0.83 21.73 21.28 4.01 Bahamas, The 11.71 -0.07 4.67 3.46 -30.24 Bahrain 31.05 3.12 26.27 27.88 1.84 195.07 -2.77 48.29 35.10 6.19 5.64 -0.36 2.74 2.63 -1.11 Belarus 56.45 -1.54 35.77 33.40 13.53 Belgium 462.14 26.84 413.73 426.80 0.56 Benin 11.38 -0.11 3.65 2.83 0.22 Bhutan 2.00 -0.01 1.37 748.14 4.55 33.00 -0.55 13.14 10.03 4.06 16.21 -0.28 9.13 6.28 -1.04 14.42 -0.19 8.79 7.44 3.06 1802.21 -61.64 283.35 226.12 9.03 Brunei Darussalam 12.93 -0.17 5.31 7.86 -0.49 Bulgaria 50.64 -2.07 35.25 33.50 -0.10 Burkina Faso 11.83 -0.21 4.26 2.91 0.72 Burundi 31.04 -0.04 0.85 193.49 5.54 1.59 -0.11 0.98 672.36 0.13 Cambodia 18.04 -1.73 16.87 13.64 1.22 Cameroon 30.92 -0.63 8.40 6.91 2.69 1556.12 23.92 619.87 568.47 1.13 Chile 243.91 -4.94 86.85 79.30 4.35 China 11061.55 -68.09 2266.53 2583.35 1.44 293.48 -7.50 74.47 50.48 4.99 Congo, Dem Rep 37.91 -1.16 13.98 10.60 0.74 Congo, Rep 11.95 -3.72 9.62 5.13 3.17 Costa Rica 54.77 -2.54 19.84 17.46 0.80 Cote d'Ivoire 45.81 -0.48 12.58 12.72 1.25 Croatia 49.52 -0.24 24.03 23.85 -0.46 Curacao 3.15 -0.12 2.59 2.12 -0.48 Country Afghanistan Antigua and Barbuda Armenia Aruba Australia Austria Bangladesh Barbados Bolivia Bosnia and Herzegovina Botswana Brazil Cabo Verde Canada Colombia 24 GDP (billion USD) 19.84 Investment (billion USD) 15.28 Export (billion USD) 44.90 Import (billion USD) 45.29 Inflation (%) -2.10 Czech Republic 188.03 2.02 158.00 158.79 0.31 Denmark 302.67 5.40 166.62 196.46 0.45 Djibouti 2.43 -0.14 3.04 3.56 -0.85 Dominica 0.54 -0.02 0.36 0.27 -0.84 Dominican Republic 71.16 -2.20 23.56 17.53 0.84 Ecuador 99.29 -1.32 25.76 21.58 3.97 329.36 -6.74 73.27 37.87 10.37 El Salvador 23.43 -0.39 12.14 7.03 -0.73 Estonia 23.04 0.14 18.45 18.85 -0.49 Eswatini 4.06 -0.03 2.09 1.99 4.95 Ethiopia 64.58 -2.62 20.17 6.02 9.57 4.68 -0.24 2.80 2.34 1.37 Finland 234.44 -18.12 100.78 102.00 -0.21 France 2438.20 8.40 914.86 955.75 0.04 Gabon 14.38 -0.03 5.26 5.50 -0.34 1.37 0.00 0.49 0.26 6.81 14.95 -1.41 9.83 6.95 4.00 3356.23 68.43 1468.86 1800.72 0.51 Ghana 48.56 -2.97 22.28 16.85 17.15 Greece 196.59 0.30 72.05 71.00 -1.74 0.99 -0.13 0.63 0.52 -0.52 Country Cyprus Egypt, Arab Rep Fiji Gambia, The Georgia Germany Grenada 25 ... on the factors affecting GDP in countries around the world There have been numerous studies on the factors affecting GDP in the world through quantitative and qualitative research In the 2015, ... estimating or predicting the expected value of the dependent variable of the foreseeable values of the independent variable, specifically in this study, analyzing the relationship between the independent... variables, the essay of the research team will answer the questions : How the main factors affecting GDP ? What is the specific level of influence? …During the study, usage data were collected from the