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

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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

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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

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Chapter: 1
Introduction

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

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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.

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Chapter: 2
2.1 Country Profile

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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

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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.)

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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

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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

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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

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China, 1996-2013
Aggregate Indicator: Political Stability and Absence of Violence
China, 1996-2013
Aggregate Indicator: Government Effectiveness

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China, 1996-2013
Aggregate Indicator: Regulatory Quality
China, 1996-2013

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Aggregate Indicator: Rule of Law
China, 1996-2013
Aggregate Indicator: Control of Corruption

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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

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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

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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]

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-------------+----------------------------------------------------------------
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.

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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.