Tiểu luận tiếng anh Kinh tế chuyển nhượng the factors affecting monthly expenditure of FTU's studen.doc

Tiểu luận tiếng anh Kinh tế chuyển nhượng the factors affecting monthly expenditure of FTU's studen

TABLE OF CONTENTS

Page

I INTRODUCTION 1

II METHODOLOGY 2

1 DEFINITION 2

1.1 Income 2

1.2 Expenditure 3

2 THEORIES OF CONSUMERS’ BEHAVIOR 3

3 THE KEYNESIAN CONSUMPTION FUNCTION 5

III ECONOMETRIC MODEL 7

1 MODEL CONSTRUCTION 7

2 COEFFICIENTS PREDICTION 8

IV DATA DESCRIPTION 9

V EMPERICAL RESULTS 13

1 USING THE ABOVE DATA TO ESTIMATE THE REGRESSION MODEL BY OLS METHOD 13

2 MEANING OF THE REGRESSION COEFFICIENTS 14

3 TESTING THE SIGNIFICANCE OF THE REGRESSION COEFFICIENTS AND THE RELEVANCE OF THE REGRESSION FUNCTION 14

4 FIRST CURE: FOR THE REGRESSION MODEL 17

5 TESTING THE CONFORMITY WITH THE ASSUMPTIONS OF OLS METHOD 21

6 SECOND CURE: FOR THE HETEROSKEDASTICITY 23

7 FINAL REGRESSION MODEL 28

VI CONCLUSION 29

VII REFERENCES 30

I INTRODUCTION

Vietnam in recent years, along with nearly 200 countries around the world, hasbeen integrating into the trend of globalization and exercising national campaignstowards the overall development in economic, political, social and cultural aspects

In this context, human capital is considered one of the key factors for Vietnam’slong-term revolution, and it is university students that make up an indispensablepart in the domestic labor force in the future

Regarded as one of the most privileged universities in Vietnam, Hanoi ForeignTrade University has long attracted thousands of students from North to Southevery year Each student, as a matter of fact, has his own family background,distinctive personalities as well as certain level of knowledge and experience.Such factors, certainly, have significant impacts on students’ daily life, in whichstudents’ expenditure should be mentioned first of all

Therefore, after taking everything into consideration, we decided to choose andstudy the project: “THE FACTORS AFFECTING MONTHLY EXPENDITURE

OF FTU’S STUDENT” Although the government has tried to implementfinancial aid programs for university learners, we, especially those coming fromprovincial areas, have still met many difficulties in managing our spending everyday It is really not easy to allocate our limited source of money into a range ofactivities in the most effective way Thus through our project, we would like toprovide you with more in-depth understanding about some main factorsdominating daily spending of FTU’s students We hope that arguments andstatistics in this project will be helpful for you in drawing a reasonable plan ofexpenditure for the time being

Income, by contrast, is a quantitative variable It can be said that income andexpenditure are two critical elements of the market economy, as everyone has toconsider how to spend their disposable income in the most reasonable way Therealso exists a close-knit relationship between those two factors, thus we will usemicroeconomic and macroeconomic theories and models to interpret it

1 DEFINITIONS

1.1 Income

There are two main types of income, which can be listed as personal incomeand disposable income

1.1.1 Personal income (PI)

Personal income is the income earned by households and non-corporatebusinesses Unlike national income, it excludes retained earnings, which is theamount of revenue corporations have earned but have not paid out to stockholders

as dividend It also subtracts corporate income taxes and contributions for socialinsurance (mostly Social Security taxes) In addition, personal income includesinterest income, the amount households receive from their holdings of governmentdebt, and transfer payment, the amount they get form government transfer programsuch as welfare and social security

1.1.2 Disposable income (DI)

Disposable personal income is the net income that households and corporate businesses earn after fulfilling all their obligations to the government Itequals personal income minus personal taxes and certain non-tax payments (such

non-as traffic tickets)

DI = PI – personal taxes

In the scope of our project, however, our studied subjects are FTU’s studentswho have no obligation to pay income tax Thus they have entire disposal of whatthey earn, which means that their personal income also equals their disposableincome Besides, students’ earnings generally come from two main sources:family financial support and income from part-time jobs Family financial support

is the monthly amount supported by students’ families so that they can fulfill theirdaily life Income from part-time jobs is what students earn when participating inthe labor market, which is tax-free

2 THEORIES OF CONSUMERS’ BEHAVIOR

 We assume that university students always try to maximize their ownutility by using a number of certain resources This means that although there aremany ways of planning expenditure, students will only follow the choice that ismost likely to optimize their satisfaction Moreover, as there always exists a limit

to students’ income, they have to consider how to allocate that restricted source for

a variety of daily activities

In short, this part of our project has two main objectives The first one is tostudy how students use their income to bring about maximum benefit forthemselves And the second one is to explain how income affects expendituretheoretically and realistically

 The theories of consumers’ behavior, in microeconomics, begin withthree basic assumptions about consumers’ preference

Firstly, preferences are complete This means that consumers can rank theirbaskets of goods based on personal preferences or different levels of utility theymay provide Prices of goods have no effects on consumers’ choice in this case Secondly, preferences are transitive If a person prefers good A to good B, andgood B to good C, certainly he will prefer good A to good C

Thirdly, in case of normal goods, consumers always prefer more to less This is

an obvious argument, because everyone feels more satisfied when consumingmore goods and services

 Generally our project still relies on those basic assumptions, but instead

of goods, we aim to study different ways of planning expenditure of FTU’sstudents Thus in the scope of this project, we will adjust the three assumptions asfollows

Firstly, students can compare and rank different choices of spending based ontheir satisfaction

Secondly, of a student prefers choice A to choice B, and choice B to choice C,this means that he prefers choice A to choice C

Thirdly, students will choose the choice of expenditure that benefits them most

3 THE KEYNESIAN CONSUMPTION FUNCTION

In general, the basic form of consumption function is as follows:

C = f(Yd)

with Yd representing disposable income But as afore-mentioned, since there is

no personal income tax levied on university students, their disposable income alsoequals their personal income In this case, the consumption function can berewritten as :

If consumption rises at a lower speed than income does, the ratio consumption/income will decrease as income increases We use a linear function in the form of

y = a + bx to build the consumption function.

In particular, we have the standard Keynesian consumption function asfollows:

1( )

where C = Students’ expenditure

C = Autonomous consumption This is the level of consumption that will take place even if income is zero If an individual's income falls to zero, some of his existing spending can be sustained by using savings This is known as dis-saving spending

MPC = Marginal propensity to consume This is the change

in consumption divided by the change in income, or in other words, it determines the slope of the consumption function The MPC reflects the effect of an additional VND of disposable income on consumption

C MPC

Y







As you can see from the graph above, we always have: 0 < MPC < 1 If MPC

equals to 1, this means that students’ spending always equals students’ income,which is irrational in reality Actually when a student’s income reaches a certainlevel, he will not spend all the money but keep a certain amount as savings

Certainly, savings will increase as income increases, thus MPC can never equal to

1

In conclusion, there is a positive relationship between disposable income (Yd)and students’ spending (C) The gradient of the consumption curve gives themarginal propensity to consume The intercept gives the autonomousconsumption, which exists even if students have no current disposable income

III ECONOMETRIC MODEL

+ FFS: Family financial support (unit: thousand dong)

+ INC: Student’s monthly income (from tuition, part-time jobs, etc) (unit:

thousand dong)

b) Regression model:

- Population regression function:

(PRF): EXP i 12.CHA i 3.HOM i 4.FFS i 5.INC U i  i

(Ui: disturbance term)

- Sample regression function:

(SRF): EXP i ˆ1ˆ2.CHA i ˆ3.HOM i ˆ4.FFS i ˆ5.INC ie i (ei: residual)

2 COEFFICIENTS PREDICTION

- 2: positive – A generous student (CHA = 1) tends to spend more than an

economical one (CHA = 0)

- 3: positive – A student who comes from an urban area (HOM = 1) tends to

spend more than one who comes from a rural area (HOM = 0)

- 4: positive – If monthly family financial support increases, student’s

monthly expenditure increases too

- 5: positive – If a student’s monthly income increases, his/her expenditure

increases too

IV DATA DESCRIPTION

The primary data is collected from a survey which has been conducted among

83 FTU students in April 22, 2011 The dataset is interpreted as cross-sectional.The results of the survey has been obtained as follows:

V EMPERICAL RESULTS

1 USING THE ABOVE DATA TO ESTIMATE THE REGRESSION MODEL BY OLS METHOD

Model 1: OLS, using observations 1-83

Dependent variable: EXP

S.D dependent var 870.302

1Sum squared resid 7810729 S.E of regression 316.4452

0

2.67e-34Log-likelihood -

593.0369 Akaike criterion 4 1196.07Schwarz criterion 1208.16

Excluding the constant, p-value was highest for variable 2 (HOM)

From the above result, we obtain the following regression function:

(SRF) EXP i = -23.7348 + 158.541 CHA i + 15.2599 HOM i + 0.864879 FFS i +

2 MEANING OF THE REGRESSION COEFFICIENTS

- ˆ1 = -23.7348 means that if an economical student who comes from an ruralarea has no family financial support and no income, he/she will spend -23.7348thousand dong on average every month

- ˆ2 = 158.541 means that a generous student will spend 158.541 on averagemore than an economical one, provided that they come from the same homelandareas and have the same family financial support and income every month.

- ˆ3 = 15.2599 means that a student who comes from an urban area spend15.2599 on average more than another student who comes from a rural area,provided that they have the same character, family financial support and incomeevery month

- ˆ4 = 0.864879 means that every month if the family financial support of onestudent increases (or decreases) by one thousand dong, he/she will spend 0.864879dong more (or less) on average; provided that his/her character, homeland andmonthly income remain unchanged

- ˆ5 = 0.81998 means that every month if the income of one student increases(or decreases) by one thousand dong, he/she will spend 0.81998 dong more (orless) on average; provided that his/her character, homeland and monthly familyfinancial support remain unchanged

3 TESTING THE SIGNIFICANCE OF THE REGRESSION COEFFICIENTS AND THE RELEVANCE OF THE REGRESSION FUNCTION

a) The significance of the regression coefficients:





Since | t | = 0.2209 < t0.05(78) = 1.66, we accept H0 There is sufficient sampleevidence to claim that 10, that is, the intercept is not significant.





H R Hypothesis

R n k F

4 FIRST CURE: FOR THE REGRESSION MODEL

a) The coefficient 3 and the variable HOM:

- From the above analysis, when conducting T-test with respect to ˆ3, we have

- If the variable HOM is omitted, we obtain the following result when running

a regression model having three independent variables: CHA, FFS, INC

Model 1: OLS, using observations 1-83

Dependent variable: EXP

93

Hannan-Quinn 1198.0

05After the variable HOM is omitted, R increases from 0.867792 to 0.8693962

 The variable HOM will be omitted.

b) The intercept 1:

- From the above analysis, when conducting T-test with respect to ˆ1, we havesufficient evidence to conclude that 10, that is, the intercept is not significant

- If the variable X1 (X1 = 1) is omitted, or in other words the intercept 10,

we obtain the following result when running a regression model having three independentvariables: CHA, FFS, INC

Model 2: OLS, using observations 1-83

Dependent variable: EXP

Coefficien t

S.D dependent var 870.30

21Sum squared resid 78164

91

Hannan-Quinn 1195.0

50After the variable X1 = 1 is omitted, R increases from 0.869396 to 0.9758762

 The variable X 1 = 1 will be omitted

The regression function has the intercept 10

c) New regression function

(SRF) EXP i = 154.635 CHA i + 0.859465 FFS i + 0.816912 INC i + e i (2) d) Meaning of the regression coefficients:

- ˆ1 = 0 means that if an economical student who comes from an rural area has

no family financial support and no income, he/she will spend zero every month

- ˆ2 = 154.635 means that a generous student will spend 154.635 thousanddong on average more than an economical one, provided that they have the samefamily financial support and income every month

- ˆ3 = 0.859465 means that every month if the family financial support of onestudent increases (or decreases) by one thousand dong, he/she will spend 0.859465thousand dong more (or less) on average; provided that his/her character andmonthly income remain unchanged.

- ˆ4 = 0.816912 means that every month if the income of one student increases(or decreases) by one thousand dong, he/she will spend 0.816912 thousand dongmore (or less) on average; provided that his/her character and monthly familyfinancial support remain unchanged

e) Testing the significance of the regression coefficients and the relevance

of the regression function:

H R Hypothesis

R n k F

Correlation coefficients, using the observations 1 - 83

5% critical value (two-tailed) = 0.2159 for n = 83

From the above matrix, in which there is no rij (i2, 4;j 2, 4) greater than0.8, we can claim that multicollinearity does not exist.

- Variance Inflation Factors (VIF) method:

The following result is obtained:

Variance Inflation Factors

Minimum possible value = 1.0

Values > 10.0 may indicate a collinearity problem

Reciprocal condition number = 6.3086927e-008

From the above analysis, since VIF(i) < 10 (i 2, 4), we can claim thatmulticollinearity does not exist

- Conclusion: Multicollinearity does not exist.

b) Testing heteroskedasticity with White’s test:

0 1

: The regression model is homoskedastic:

: The regression model is heteroskedastic

H Hypothesis

H







White's test for heteroskedasticity

OLS, using observations 1-83

Dependent variable: uhat^2

coefficient std error t-ratio p-value

CHA -59510.8 135663 -0.4387 0.6622

FFS 38.4485 77.7873 0.4943 0.6226

INC -2.86511 106.989 -0.02678 0.9787