TABLE OF CONTENT
Content
1. Introduction
2. Methodology
3. Econometric model
4. Data description
5. Results and test
A. Results and analysis
1. Results
2. Analyze some basic content of results
B. Detect and cure default model
1. Normality
2. Multicollinearity
3. Heteroscedasticity
4. Autocorrelation
C. Detect and cure default new model
1. Normality
2. Multicollinearity
3. Heteroscedasticity
4. Autocorrelation
6.Conclusion and policy implication
Page
2
2
5
6
7
7
8
10
10
12
13
16
19
a. Conclusion
19
b. Recommendation
21
c. Policy implication
22
APPENDIX
23
REFERENCES
24
24
24
25
1
28
31
2
1. Introduction
a. Issue: Try to establish an econometrics model to analyse the
impacts and influences of Foreign Direct Investment (FDI) and
urban unemployment ratio U on Gross Domestic Products (GDP).
b. Reason for researching:
Firstly, this is an issue relating to economics. All the knowledge
we can gain from this researching will be helpful for other
economics subjects such as Macroeconomics, International
Economics….and our future jobs as well.
Secondly, our country started to innovate in 1986; foreign
investment law in Viet Nam was promulgated on 29 th December,
1987 to make a legal basis for the investment in Viet Nam from
foreign investors. The fact is that since Viet Nam opened to
integrate, foreign investment has become a very important source
of capital for Viet Nam economy in industrialization and
modernization. Being a member of World Trade Organization
(WTO), Viet Nam has many chances to gain more FDI. However,
now the issue is that how to use FDI effectively, make FDI be an
important factor to develop the economy.
The study of the effects of foreign direct investment and unemployment
on economic growth helps us to know the extent of the impact of FDI to
GDP as well as U to GDP. According to learning the theories and
features, understanding characteristics of this and trends to develop, we
3
can make the directions and solutions to attract FDI and use FDI in the
most effective way; besides, try to bring back unemployment ratio to
nature unemployment standard in order to help GDP grow up.
That is all the reasons why we choose to research this topic!
2. Methodology
*Economic theories:
a. Gross domestic product (GDP) is the market value of all final
goods and services produced within a country in a given period of
time.
In the real world, the market values of many goods and services must be
calculated to determine GDP. While the total output of GDP is
important, the breakdown of this output into the large structures of the
economy can often be just as important. In general, macroeconomists
use a standard set of categories to breakdown an economy into its major
constituent parts; in these instances, GDP is the sum of consumer
spending, investment, government purchases, and net exports, as
represented by the equation:
4
Y = C + I + G + NX
Because in this equation Y captures every segment of the national
economy, Y represents both GDP and the national income. This because
when money changes hands, it is expenditure for one party and income
for the other, and Y, capturing all these values, thus represents the net of
the entire economy.
Four components of GDP:
- Consumer spending, C, is the sum of expenditures by households
on durable goods, nondurable goods, and services. Examples
include clothing, food, and health care.
- Investment, I, is the sum of expenditures on capital equipment,
inventories, and structures. Examples include machinery, unsold
products, and housing.
- Government spending, G, is the sum of expenditures by all
government bodies on goods and services. Examples include naval
ships and salaries to government employees.
- Net export, NX, equals the difference between spending on
domestic goods by foreigners and spending on foreign goods by
domestic residents. In other words, net export describes the
difference between exports and imports.
b. FDI is a form of international investment, in which the investors
bring the means to invest abroad to directly organize the
production process management and business profits. FDI plays a
huge role in economic development:
5
Add to domestic capital.
Acquisition of technology and management know-how.
Join the global production network.
Increase the number of jobs and trained workers.
Bring a large budget inflow.
c. Unemployment is always a concern of society; long-term
macroeconomic policies of the government are aiming to achieve
the natural rate of unemployment in the economy. It reflects the
prosperity of the country in each period of time. The some
following simple analysis shows us that unemployment occupies
an important position, is one of the objectives of government
activities:
High unemployment rate means that GDP is lower – human
resource is not use effectively, we are wasting opportunities to
produce more products and services.
Unemployment also means less production, reducing the efficiency
of production scale.
Unemployment leads to social demand reduction. Moreover, goods
and services are less consumed, business opportunities are smaller,
quality
and
quantity
of
product
reduces.
Besides,
high
unemployment ratio can lead to the less consumers’ demand
6
compared with when they are employed, as the result, the
investment opportunities reduces.
d. Relationship between gross domestic product GDP and foreign
direct investment FDI:
The relationship between the GDP and the level of FDI has always been a matter
of discussion between economists. There is a widespread belief among
policymakers that foreign direct investment (FDI) generates positive
productivity effects for the host countries. The neoclassical growth
model states that FDI cause an increase in investments and their
efficiency leading to increases in growth. In the long-run, according to
the endogenous growth model, FDI promote growth, which is
considered a function of technological progress, originating from
diffusion and spillover effects. The main mechanism for these
externalities is the adoption of foreign technology, which can happen via
licensing agreements, imitation, competition for resources, employee
training, knowledge and export spillovers. These benefits, together with
the direct capital financing it provides, suggest that FDI can play an
important role in modernizing a national economy and promoting
economic development.
e. Relationship between gross domestic product GDP and utility U:
7
GDP only measures production and consumption, not the level of utility
people gain from producing and consuming. There is much economic
activity (for example, replacing a low quality product, or repairing
damage from war or natural disaster) that does not improve quality of
life (compared to having a high quality product to begin with, or no
war). The result can be a very high GDP combined with low customer
satisfaction.
*We collect the data and statistics of GDP, FDI and U to prove relations
between GDP, FDI and U and by using regression model in
econometrics.
3. Econometric model
Model includes three variables: dependent variable: GDP (billion dong),
independent variables: FDI( million USD) and U (%)
GDPi= β1 + β2 FDIi +β3Ui + Vi
This is multi regression model.
Many economic models express the negative relation between inflation
and unemployment (Phillip curve). Generally, high GDP leads to high
inflation because of growth objectives of government. As the result,
relation between GDP and unemployment is negative.
4. Data description
8
- Data collected from website: www.gso.gov.vn, GDP, FDI and U in
Vietnam from 1995-2009.
- Correlated analysis between variables: During one year, if the total
capital of foreign direct investment in Vietnam increases, there will be
more capital for other projects. This will encourage produce more;
therefore GDP increases accordingly. Unemployment rate increasing
means GDP decreasing.
- Table of data: see table in the appendix
- Relation between variables: see graph in the appendix
- Description:
Mean
Standard Minimum Maximum
Media
deviation
n
GDP(billion dong)
697572.1
441975.8
228292
1658389
535760
FDI(million USD)
4198.913
3028.292
2334.9
11500
2714.0
5.71
0.76
4.60
6.85
5.8800
U(%)
5. Results and test
A. Results and analysis
1. Results
9
Model’s result from the gretl software ( Model-> Ordinary Least
Squares )
Model 1: OLS, using observations 1995-2009 (T = 15)
Dependent variable: GDP
coefficient
std. error
t-ratio p-value
-------------------------------------------------------------------------------------------const
1.68744e+06
624740
2.701
0.0193 **
FDI
85.6018
23.6463
3.620
0.0035 ***
U
-236250
94698.9
-2.495
0.0282 **
Mean dependent var 697572.1
S.D. dependent var 441975.8
Sum squared resid
S.E. of regression 159783.1
R-squared
F(2, 12)
3.06e+11
0.887974
Adjusted R-squared 0.869303
47.55913
Log-likelihood
Schwarz criterion
P-value(F)
-199.3341
Akaike criterion
406.7923
Hannan-Quinn
10
1.98e-06
404.6682
404.6455
rho
0.525136
Durbin-Watson
0.766908
2. Analyze the basic content of results.
a.
Population regression model:
(PRM)
GDPi =
1+ 2 FDIi+ 3 Ui+
Vi
Sample regression model:
(SRM)
GDPi =
1
+
2
FDI i+
̂ 3Ui
+ei
( e i is estimator of
Vi)
(SRM) GDPi = 1.68744e+06 + 85.6018.FDIi – 236250.Ui + ei
1
= 1.68744e+06 means that if FDI=0 and U=0 then GDP =
1.68744e+06 billion dong (holding inflation rate, CPI equal to 0,
population is constant)
2
= 85.6018 means that when FDI increases 1 million USD then GDP
increases 85.6018 billion dong (holding other factors constant)
̂ 3
= – 236250 means that when U increases 1% then GDP decreases
236250 billion dong (holding other factors constant)
b. Measure of fit
+ Intercept:
1
11
H 0 : 1 0
H 1 : 1 0
Test the hypothesis:
t
1.68744e 06
624740
Se( 1 )
1 1
With = 5% :
Reject Ho if:
t
= 2.701
)
t(15/ 2 3) t 0(12
.025 =
>
2.179
)
t 0(12
.025
t 2.701
Reject H0 ->
0 -> intercept is statistical significance
1
+ Slope:
*
2
Test the hypothesis:
t
2 2
Se( 2 )
With = 5% :
Reject Ho if:
H 0 : 2 0
H 1 : 2 0
85.6018
=
23.6463
3.620
)
t(15/ 2 3) t 0(12
.025 =
t
>
2.179
)
t 0(12
.025
3.620 > 2.179
=> Reject H0
2 ≠
0 2 is statistical significance
12
* ̂ 3
Test the hypothesis:
t
3 3
Se( 3 )
236250
94698.9 =
With = 5% :
Reject Ho if:
H 0 : 3 0
H 1 : 3 0
t
-2.495
)
=
t(15/ 2 3) t 0(12
.025
>
2.179
)
t 0(12
.025
2.495 > 2.179
=> Reject H0
3 ≠
0 is statistical significance
3
+ Model
R2= 0.887974 indicates that FDI and U explain about 88.7974 % for the
variation of dependent variable GDP.
Test the hypothesis:
H 0 : R 2 0
2
H1 : R 0
(H0: the model is significant
H1: the model is not significant)
R2
0.887974
2
F k 12
1 0.887974
1 R
15 3
n k
= 47.5590
13
F0.05(2;12)= 3.89
Reject H0 if F > F0.05(2;12)
47.5590 > 3.89
=> reject H0 R2> 0 model is significant
B. Detect and cure default of model
1. Normality
H0: error is normal distribution
H1: error is non-normal distribution
Use gretl software: Test Normality of residual
Frequency distribution for uhat1, obs 1-15
number of bins = 5, mean = -3.88051e-010, sd = 159783
interval
midpt
frequency rel.
< -2.010e+005
-2.586e+005
cum.
3
20.00%
20.00% *******
-2.010e+005 - -8.598e+004
-1.435e+005
33.33% ****
14
2
13.33%
-8.598e+004 - 2.908e+004
-2.845e+004
0
0.00%
33.33%
2.908e+004 - 1.441e+005
8.662e+004
9
60.00%
2.017e+005
1
6.67%
93.33% *********************
>= 1.441e+005
100.00% **
Test for null hypothesis of normal distribution:
Chi-square(2) = 5.815 with p-value 0.05461
6e-006
uhat1
N(-3.8805e-010,1.5978e+005)
Test statistic for normality:
Chi-squared(2) = 5.815 pvalue = 0.05461
5e-006
Density
4e-006
3e-006
2e-006
1e-006
0
-400000
-200000
0
uhat1
15
200000
400000
p-value = 0.05461 > 0.05 accept H0
← => Error is normal distribution.
2. Multicollinearity
H0: No multicollinearity in the model
H1: Multicollinearity in the model
Use gretl software
Test collinearity
Variance Inflation Factors
Minimum possible value = 1.0
Values > 10.0 may indicate a collinearity problem
FDI 2.812
U
2.812
VIF(j) = 1/(1 - R(j)^2), where R(j) is the multiple correlation
coefficient
between variable j and the other independent variables
16
Properties of matrix X'X:
1-norm = 3.9324782e+008
Determinant = 5.4825961e+009
Reciprocal condition number = 1.4456799e-010
VIF (FDI) = VIF (U) = 2.812 < 10
Accept H0
No multicollinearity in the model.
3. Heteroscedasticity
H0: Var(ui)= σ2 for all i
H1: Var(ui) = σ2i
Use gretl software:
+ Tests heterokesdasticity white test
White's test for heteroskedasticity
OLS, using observations 1995-2009 (T = 15)
Dependent variable: uhat^2
17
coefficient
std. error
t-ratio
p-value
---------------------------------------------------------------------------const
-1.31163e+012
1.19540e+012
-1.097
0.3010
FDI
5.75038e+06
1.47086e+08
0.03910
0.9697
U
4.02859e+011
3.58620e+011
1.123
0.2904
sq_FDI -2697.74
2068.51
-1.304
0.2245
X2_X3
8.86852e+06
2.97815e+07
0.2978
0.7726
sq_U
-3.37756e+010
2.61055e+010
-1.294
0.2279
Warning: data matrix close to singularity!
Unadjusted R-squared = 0.278199
Test statistic: TR^2 = 4.172989,
with p-value = P(Chi-square(5) > 4.172989) = 0.524788
n.R2= 15x0.278199 = 4.172989
18
χ2α (k-1) = χ20.05(5) = 11.07
reject H0 if n.R2 > χ20.05(5)
4.172989 < 11.07
=> accept H0
+ Test heteroskedasticity white test ( squares only)
White's test for heteroskedasticity (squares only)
OLS, using observations 1995-2009 (T = 15)
Dependent variable: uhat^2
coefficient
std. error
t-ratio
p-value
----------------------------------------------------------------------------const
-1.55410e+012
8.34385e+011 -1.863
0.0921 *
FDI
4.84548e+07
3.11676e+07
1.555
0.1511
U
4.74663e+011
2.53071e+011
1.876
0.0902 *
sq_FDI
-2807.88
1940.23
-1.447
0.1785
sq_U
-3.81973e+010
2.04696e+010
-1.866
0.0916 *
Warning: data matrix close to singularity!
19
Unadjusted R-squared = 0.271087
Test statistic: TR^2 = 4.066311,
with p-value = P(Chi-square(4) > 4.066311) = 0.397106
n.R2 = 15x0.271087 = 4.066311
χ2α (k-1) = χ20.05(4)= 9.49
reject H0 if n.R2 > χ20.05(4)
4.066311 < 9.49
=> accept H0
Var(ui) = σ2 for all i
No hereroscedasticity in the model.
4. Autocorrelation
*Hypothesis:
H0: cov (ui;uj) = 0
H1: cov (ui;uj) ≠ 0
d=
11
(e t e t 1)2
t 1
=
11 2
et
1
0.766908
with n=15, α 5%
20
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