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- 1. 1 A Report on Multiple Regression Analysis of Chinese Economic Factors Based on Stata Sheikh TanjillaDipti Assistant Professor Department of Finance University of Dhaka GROUP # 04 Section: A Batch: 19th Department of Finance University of Dhaka Date of Submission: 20th February, 2015 PREPARED FOR PREPARED BY
- 2. 2 GROUP NO # 04 Sl. No. Name Name Roll No. Remarks Remarks1. Maruf Hossain 19-013 2. Md.Monjurul Ahsan 19-099 3. Md.Ripon Molla 19-123 4. Abdul Quyum 19-121 5. Raqib Hosssain 19-157 Group Profile
- 3. 3 Date: February 20 ,2015 Course teacher, Department of Finance, University of Dhaka. Subject: Submission of report. Dear Mam’am, With due respect, we are submitting here with our report on Multiple Regression Analysis of Chinese Economic Factors Based on Stata. It is a requirement of BBA program from department of finance, University of Dhaka. In spite of a number of limitations we have exerted our best effort to prepare this report and to make it a vivid and comprehensive one for accomplishing our academic requirement So, we request you to accept our report and give us a proper suggestion in this case. We shall always be obliged to furnish our clarification regarding this report, if required. If we did any mistake, we are looking forward to your important advice. Sincerely yours, On behalf of the group 04 .............................................. LETTER OF TRANSMITTAL
- 4. 4 First of all we would like to express our gratitude from heart to the Almighty Allah for giving us the strength and patience to prepare this report within the scheduled time. We would like to acknowledge the contributions of the various Authors, whose textbooks have been instrumental in preparing this Report. Finally, we are especially grateful to our honourable course teacher for giving his valuable suggestions and precious contributions .what he taught us in our course has worked as a beacon while preparing this report. Acknowledgement
- 5. 5 Statistics is a general term used to summarize a process that an analyst, mathematician or statistician can use to characterize a data set. If the data set is based on a sample of a larger population, then the analyst can extend inferences onto the population based on the statistical results from the sample. We have completed the course “Applied Statistics (F-207)” and the report is a part of the course.As we are the business students of country’s top renowned institution ,it is bound for us to know about the mechanism related to statistics tools specially Stata. We have tried to show our best competence in our report.Our report is basically based on the multiple regession software solution. It contains the most economically strong country China’s GDP and Inflation rate as dependent variables and political stability, government efficiency , regulatory quality, rule of law ,control of corruption as a independent variables . After the solution both of the variables equation on software is significant. After the entire model is valid because the F Value is less than 5%. We have collected the information about our report by browsing information , studying related pdfs from internet.We have made our best effort to make the report logical and interpretable to the users. Executive summary
- 6. 6 Table of contents S. N. Topics Page 1. Chapter: 1 Introduction 1.1: Background of The study 1.2: Origen of the Report 1.3 Objectiveof the report 1.4: Methodology of the Study 1.5: Limitation of the Study 01 02 02 03 03 03 2. Chapter: 2 Country Profile 05 3. Chapter: 3 World Banks GovernanceIndex 3.1: Introduction 3.2: WGI Data Sources O7 08 09 4. Chapter: 4 Multiple regression analysis of GDP (Y1) Process of working with this data on Stata Multiple regressionanalysis of Inflation (Y3) Process of working with this data on Stata 14 15 19 20
- 8. 8 1.1: Background of The study As a student of business we need to learn basic mechanism and skill to organize analyze and transfer of data and present of information .So bookish knowledge is not enough for us .In this semester we have studied Applied Statistic(course F-207) and learn many tactical tools and methods .So here we are given a chance to applied a practical knowledge, where we have to make a report on Russia on their various economic variables. 1.2: Origen of the Report The BBA Program under the department of finance offers a course named“Applied Statistics (F- 207)” which requires submitting a report on a specific topic on “Influence of Governance Index on Economy : A study on China. The report under the above headline has been prepared. 1.3 Objective of the report There are many objectives to make this report, from where we can come to know the various point such as To take GDP and Inflation as dependent variables and other five independent variables as political stability ,govt. efficiency ,role of law and regulator control . To show the raw data in excel. From using the value of excel on stata software and run the software. To draw equation multiple regression. To interpret the result of the equation. To solve the case of the study. 1.4: Methodology of the Study
- 9. 9 Preparing this report is very difficult for us.for this we have to need on help of seniors and some discussion of other group. To prepare this report we mainly depend on secondary data. But also take some help from our course instructor & seniors. 1.5: Limitation of the Study We have faced some typical constraints during our preparation for the report. The major limitations are as follows: To make this report we had to need various data such as politicalstability, law of control, government efficiency and other data from 1996 to 2013 but in some year here have not any data available on the internet .On where we have to average the previous and next data to complete the report. Before this time and about how to prepare a report and so faced some problems regarding this Report. Our calculations are mainly based on secondary data. When we stat to make this report there we have not find all the data such as Gini coefficient index and other ,then we come to know that we have to use only GDP and Inflation rate as dependent variables . All the variables are changing in nature and sometimes it has no relationship with share price.
- 10. 10 Chapter: 2 2.1 Country Profile
- 11. 11 Country Name: People's Republic of China China officially the People's Republic of China (PRC), is a sovereign state located in East Asia. It is the world's most populous country, with a population of over 1.35 billion.The PRC is a singlepartystate governed by the Communist Party, with its seat of government in the capital city of Beijing. It exercises jurisdiction over 22 provinces, five autonomous regions, four direct- controlled municipalities (Beijing, Tianjin, Shanghai andChongqing), and two mostly self- governing special administrative regions(Hong Kong and Macau). The PRC also claims the territories governed by the Republic of China (ROC), a separate political entity commonly known as Taiwan today, as a part of its territory, which includes the island of Taiwan asTaiwan Province, Kinmen and Matsu as a part of Fujian Province and islands the ROC controls in the South China Sea as a part of Hainan Province. These claims are controversial due to the complex political status of Taiwan. Covering approximately 9.6 million square kilometers, China is the world'ssecond-largest country by land area, and either the third or fourth-largest by total area, depending on the method of measurement China had the largest and most complex economy in the world for most of the past two thousand years, during which it has seen cycles of prosperityand decline. Since the introduction of economic reforms in 1978, China has become one of the world's fastest-growing major economies. As of 2013, it is the world's second-largest economy by both nominal total GDP andpurchasing power parity (PPP), and is also the world's largest exporter and importer of goods.China is a recognized nuclear weapons state and has the world's largest standing army, with the second-largest defence budget.The PRC has been a United Nations member since 1971, when it replaced the ROC as a permanent member of the U.N. Security Council. China is also a member of numerous formal and informal multilateral organizations, including the WTO, APEC, BRICS, the Shanghai Cooperation Organization, the BCIM and the G-20. China is a great power and a major regional power within Asia, and has been characterized as a potential superpower by a number of commentators. 2.1 China At a glance : Capital : Beijing Largest city: Shanghai
- 12. 12 Official language:Standard Chinese Area total: 9,596,961 sqkm Land: 3,705,407 sqkm Population: 1,357,380,000 (July 2013 EST.) Density: (145/km2) Unemployment rate: 5.6% (2013est.) 5.5% (2012 EST.)
- 13. 13 Chapter 3 World Banks Governance Index 3.1 Introduction Governance consists of the traditions and institutions by which authority in a country is exercised. This includes the process by which governments are selected, monitored and
- 14. 14 replaced; the capacity of the government to effectively formulate and implement sound policies; and the respect of citizens and the state for the institutions that govern economic and social interactions among them. The Worldwide Governance Indicators report on six broad dimensions of governance for 215 countries over the period 1996-2013: Voice and Accountability Political Stability and Absence of Violence Government Effectiveness Regulatory Quality Rule of Law Control of Corruption In the above, we have mentioned each of the six dimensions of governance, and a list of the individual indicators on which each aggregate indicator is based. The WGI are composite governance indicators based on 32 underlying data sources. These data sources are rescaled and combined to create the six aggregate indicators using a statistical methodology known as an unobserved components model. A key feature of the methodology is that it generates margins of error for each governance estimate. These margins of error need to be taken into account when making comparisons across countries and over time. 3.2 WGI Data Sources The WGI compile and summarize information from 32 existing data sources that report the views and experiences of citizens, entrepreneurs, and experts in the public, private and NGO sectors from around the world, on the quality of various aspects of governance. The WGI draw on four different types of source data: Surveys of households and firms Commercial business information providers Non-governmental organizations Public sector organizations
- 15. 15 Worldwide Governance Indicators (WGI) for China This Country Data Report summarizes the data from the Worldwide Governance Indicators (WGI) project for a single country. The WGI report six aggregate governance indicators for over 200 countries and territories over the period 1996-2013, covering i) Voice and Accountability, ii) Political Stability and Absence of Violence, iii) Government Effectiveness, iv) Regulatory Quality, v) Rule of Law, and vi) Control of Corruption. The line graphs on each page show the country's percentile rank on each of the six governance indicators. Percentile ranks indicate the percentage of countries worldwide that rank lower than the indicated country, so that higher values indicate better governance scores. The line graphs include margins of error shown as dashed lines, corresponding to 90% confidence intervals. Changes over time in the aggregate scores that are small relative to these margins of error should not be interpreted as signalling a statistically significant change in the indicators. The WGI are composite measures based on a large number of underlying data sources. The source data for each aggregate indicator are reported in a table on each page. Individual data sources have been rescaled to run from 0 (low) to 1 (high). These scores are comparable over time and across countries since most individual measures are based on similar methodologies over time. Scores from different individual indicators are not however directly comparable with each other since the different data sources use different units and cover different sets of countries. We show the WGI of china below in graph. China, 1996-2013 Aggregate Indicator: Voice &Accountability
- 16. 16 China, 1996-2013 Aggregate Indicator: Political Stability and Absence of Violence China, 1996-2013 Aggregate Indicator: Government Effectiveness
- 17. 17 China, 1996-2013 Aggregate Indicator: Regulatory Quality China, 1996-2013
- 18. 18 Aggregate Indicator: Rule of Law China, 1996-2013 Aggregate Indicator: Control of Corruption
- 19. 19
- 20. 20 Chapter 4 Multiple regression analysis of GDP (Y1)
- 21. 21 Process of working with this data on Stata . tssetyear time variable: year,1996 to 2013 delta: 1 unit . reg y1 x1 x2 x3 x4 x5 Source | SS df MS Numberof obs= 18 -------------+------------------------------ F( 5, 12) = 2.69 Model | 28.0327069 5 5.60654137 Prob> F = 0.0744 Residual | 25.0167362 12 2.08472801 R-squared = 0.5284 -------------+------------------------------ Adj R-squared= 0.3319 Total | 53.049443 17 3.12055547 RootMSE = 1.4439 ------------------------------------------------------------------------------ y1 | Coef. Std.Err. t P>|t| [95% Conf.Interval] -------------+---------------------------------------------------------------- x1 | -.3970101 .2709605 -1.47 0.169 -.9873823 .193362
- 22. 22 x2 | .0176029 .1684906 0.10 0.919 -.3495066 .3847125 x3 | .0014679 .1965445 0.01 0.994 -.4267658 .4297015 x4 | .0692561 .022989 3.01 0.011 .0191673 .1193449 x5 | .0220397 .1719012 0.13 0.900 -.3525009 .3965803 _cons | 8.784755 13.57164 0.65 0.530 -20.7853 38.35481 ------------------------------------------------------------------------------ . dwstat Durbin-Watsond-statistic( 6, 18) = 1.733433 . pwcorr x1 x2 x3 x4 x5 | x1 x2 x3 x4 x5 -------------+--------------------------------------------- x1 | 1.0000 x2 | 0.8056 1.0000 x3 | -0.7767 -0.7574 1.0000 x4 | 0.3945 0.3858 -0.1641 1.0000 x5 | -0.6898 -0.6043 0.6862 -0.4044 1.0000 . save "C:UsersRifatDesktopriff stat.dta",replace file C:UsersRifatDesktopriff stat.dtasaved . exit,clear
- 23. 23 Regression equation Y= 8.784755-.3970101X1+.0176029X2+.0014679X3+.0692561X4+.0220397X5+E Here, X1= Voice and Accountanbility X2= Political Stability No Voilance X3= Government Effectiveness X4= Regulatory Quality X5= Rule of Law Level 0f Significance is 5% T-test Analysis In our t-test analysis null hypothesis and alternative hypothesis is H0: β=0 H1: β≠0 From the regression table we can compare the P value with the level of significance. We know if the P-value is less than the level of significance H0 is rejected that means there is a relation between dependent variable and independent variables. In this case we can see that for all the variables p-value except X1 is greater than the level of significance so null hypothesis that means there is no significant relation between dependent variable and the independent variables at 5% level of significance. F-test Analysis In our F-test hypothesises are H0: β1=β2=β3=β4=β5 H1: β1≠β2≠β3≠ β4≠ β5 In our F-test analysis we found the p value is.0.0744that is far greater than 5% level of significance so H0 is not rejected that means as a whole dependent and independent variable
- 24. 24 doesn’t have significant relationship at 5% level of significance so we can say that model is invalid. R-squared In our analysis we found R-square is 0.5284 that means 52.84% change in Y is influenced by the independent variables. Durbin-Watson Test Using this we can find whether the model has a autocorrelation or not. Autocorrelation problem due to time series. In this case the value of d-stat is1.733433. PW Correlation We use pw correlation to find out whether there is any relation among the Independent variable.From the result we can see that there is a multicoilinerity problem. We try to solve it by logarithm, factoring and dropping. But after a number of trial and error we are failed to solve the problem.
- 25. 25 Multiple regression analysis of GDP (Y3) Collection of Raw Data
- 26. 26 Process of working with this data on Stata name: <unnamed> log: C:UsersRifatDesktopriff stat2y2.smcl logtype: smcl opened on: 19 Feb2015, 01:19:51 . insheetusing"C:UsersRifatDesktopriffstat2staty2.csv" (7 vars, 18 obs) . tssetyear time variable: year,1996 to 2013 delta: 1 unit . reg y2 x1 x2 x3 x4 x5 Source | SS df MS Numberof obs= 18 -------------+------------------------------ F( 5, 12) = 16.52 Model | 333.989032 5 66.7978064 Prob> F = 0.0001 Residual | 48.520393 12 4.04336609 R-squared = 0.8732 -------------+------------------------------ Adj R-squared= 0.8203 Total | 382.509425 17 22.5005544 RootMSE = 2.0108 ------------------------------------------------------------------------------ y2 | Coef. Std.Err. t P>|t| [95% Conf.Interval]
- 27. 27 -------------+---------------------------------------------------------------- x1 | -1.37086 .3773573 -3.63 0.003 -2.193051 -.548669 x2 | -.0285262 .2346511 -0.12 0.905 -.5397871 .4827347 x3 | .404625 .2737207 1.48 0.165 -.1917613 1.001011 x4 | .029809 .032016 0.93 0.370 -.0399479 .099566 x5 | -.0948287 .2394009 -0.40 0.699 -.6164385 .4267811 _cons | 36.21159 18.90075 1.92 0.080 -4.969609 77.39278 ------------------------------------------------------------------------------ . dwstat Durbin-Watsond-statistic( 6, 18) = 1.47294 . pwcorr x1 x2 x3 x4 x5 | x1 x2 x3 x4 x5 -------------+--------------------------------------------- x1 | 1.0000 x2 | 0.8056 1.0000 x3 | -0.7767 -0.7574 1.0000 x4 | 0.3945 0.3858 -0.1641 1.0000 x5 | -0.6898 -0.6043 0.6862 -0.4044 1.0000 . save "C:UsersRifatDesktopriff stat.dta",replace file C:UsersRifatDesktopriff stat.dtasaved
- 28. 28 . exit,clear Regression equation Y= 36.21159-1.37086X1-.0285262X2+.404625X3+.029809X4-.0948287X5+E Here, X1= Voice and Accountanbility X2= Political Stability No Voilance X3= Government Effectiveness X4= Regulatory Quality X5= Rule of Law Level 0f Significance is 5% T-test Analysis In our t-test analysis null hypothesis and alternative hypothesis is H0: β=0 H1: β≠0 From the regression table we can compare the P value with the level of significance. We know if the P-value is less than the level of significance H0 is rejected that means there is a relation between dependent variable and independent variables. In this case we can see that for except x5 all the variables p-value is greater than the level of significance so null hypothesis that means except x5 there is no significant relation between dependent variable and the independent variables at 5% level of significance. In case of x1 as the p-value is less than the level of significance so the null hypothesis is rejected that means β≠0. So, the is significant relation between x1 and Y at 5% level significance. If x1 is increase by 1 unit then Y will decrease by 1.37086unit holding other variable constant.
- 29. 29 F-test Analysis In our F-testhypothesisesare H0: β1=β2=β3=β4=β5 H1: β1≠β2≠β3≠ β4≠ β5 In our F-test analysis we found the p value is 0.0001that is less than 5% level of significance so H0 is rejected that means as a whole dependent and independent variable have significant relationship at 5% level of significance so we can say that model is valid. R-squared In our analysis we found R-square is 0.8732that means 87.32% change in Y is influenced by the independent variables. Durbin-Watson Test Using this we can find whether the model has a autocorrelation or not. Autocorrelation problem due to time series. In this case the value of d-stat is 1.47294that means there is negative autocorrelation problem. PW Correlation We use pw correlation to find out whether there is any relation among the Independent variable.From the result we can see that there is a multicoilinerity problem. We try to solve it by logarithm, factoring and dropping. But after a number of trail and error we are failed to solve the problem.
- 30. 30 Conclusion We have learned about the practice and mechanism about using stata. We also can come to the country of China “an important developed country and also the largest land area of the world . After completing this report now con know how to applythis kind of difficult software.To make this report we use GDP and Inflation as a dependent variable and other such as Russian political stability Government effectiveness, rule of law, and control of corruption as independent variables effect on the model. After the solution of the software one variable control of corruption, is significant. After all the entire model is valid because the F Value is less than 5%. At first we solve by command but there is autocorrelation and multicollinearity problem in the project. Finally the whole model is valid because in both case Prob> F (,in y1,Prob>0.2338and y2,prob>0.1093) is less than 5% level of significance. So the endeavors are fruitful and the project is true.