tiểu luận kinh tế lượng THE INFLUENCE OF FACTORS ON UNITED KINGDOMS GDP FROM 1965 TO 2010

Therefore, studying the relationship between GDP and the important factors that affect GDP such as Family Expenditure, Exports, and Government Debt will help government look for trends i

FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATIONAL ECONOMY

REPORT ECONOMETRICS

THE INFLUENCE OF FACTORS

ON UNITED KINGDOM'S GDP FROM 1965 TO 2010

Instructor: Dr Chu Thi Mai Phuong Class: Anh 7 - KDQT – K57

1 Đỗ Thu Trang 1815520229

2 Nguyễn Thị Thúy Quỳnh 1815520217

3 Lê Thị Thu Hà 1815520163

Hanoi, October 2019

TABLE OF CONTENTS

I INTRODUCTION 3

II LECTURE REVIEW Error! Bookmark not defined III METHODOLOGY 7

1 Our model 7

2 Data Error! Bookmark not defined 3 Describe Variables 9

3.1 Summary Statistic 9

3.2 Correlation matrix 10

3.2.1 Correlation between independent variables and dependent variable 10 3.2.2 Correlation between independent variables 10

4 Regression run 11

IV.TESTING 12

1 Testing hypothesis: 12

1.1 Testing an individual regression coefficient 12

1.2 Testing the overall significance 13

2 Testing the model’s problems: 13

2.1 Multicollinearity 13

2.2 Heteroskedasticity 16

2.3 Autocorrelation 18

2.4 Normality of residual Test 19

3 Summary table: 23

V CONCLUSION 24

VI REFERENCES Error! Bookmark not defined.5

I INTRODUCTION:

One of the basic indicators reflecting economic growth in economic scale, level of economic development per capita, economic structure and changes in price level of a country is GDP Gross Domestic Product (GDP) is one of the determinants of country’s economic growth It represents the economic health of a country, presents a sum of a country's production which consists of all purchases of goods and services produced by a country and services used by individuals, firms, foreigners and the governing bodies

GDP is used as an indicator for most governments and economic decision-makers for planning and policy formulation GDP helps the investors to manage their portfolios by providing them with guidance about the state of the economy Calculation of GDP provides with the general health of the economy

With all its importance to economic growth, studying on GDP is vital for all nations

Any nation wants to maintain a growing economy along with monetary stability and jobs for the population; GDP is one of the concrete signals for government efforts Therefore, studying the relationship between GDP and the important factors that affect GDP such as Family Expenditure, Exports, and Government Debt will help government look for trends

in GDP growth and enable to change its policies to achieve set goals to promote economic growth

United Kingdom has the fifth largest economy in the world at the exchange rate on the market and the 6th in the world by purchasing power parity We can see the positive results today, the way each household's spending and export of the country plays a very important role for the economy of this union Besides the impact of the spending from households and exports of goods on the increase, the government debt is also a critical factor impacting GDP of the United Kingdom

Studying the theories and indicators of the relationship between household spending, exports, public debt and economic growth helps us understand the impacts of these factors

on GDP In addition, we can imagine the characteristics and development trends to control and propose orientations and solutions to attract investment capital, use them most effectively, reduce public debt and integrate extensively and develop sustainably not only

in United Kingdom but also our country For that reason, we choose the topic “Regression

model of the influence of factors on United Kingdom's GDP from 1965 to 2010”

II LITERATURE OVERVIEW

Many practical studies are carried out to investigate factors affecting GDP but you can find no one studied about factors affecting GDP of United Kingdom which includes Household Expenditure, Export and Government Debt The results of those seem to be different to kind of analysis and factors undertaken For instance, some researchers studied on literacy rate, natural resources, human capital, physical capital, standard of living while some others determined by government expenditure, consumption, … and revealed that there was a significant difference in how much that factors affect GDP

Table 1: A summary of previous study on factors impacting GDP in general

Author/Year Methodolog

y

Alex Reuben Kira (2013)

tabulation

Cross-Consumption and Export To analyze factors affecting

Gross Domestic Product (GDP)

in Developing Countries: The Case of Tanzania

Dhiraj Jain ,

K Sanal Nair and Vaishali Jain (2015)

tabulation

Cross-FDI, Net FII equity, Net FII debt, Import and Export

To investigate the impact of various macro economic factors

on GDP components

Sherilyn Narker (2015)

tabulation

Cross-Natural Resources ,Human Capital, Physical Capital, Entrepreneurship

-define key terms such as entrepreneurship, GDP per capita, gross domestic product, human capital, literacy rate, natural resources, physical capital, standard of living

-explain how changes in a particular factor will influence the GDP of a country

-analyze economic data and identify to which type of resource the data refers

Mertha Endah Ervina (2018)

tabulation

Cross-populations, original local government revenue, government expenditure,

Analyzing Factors Affecting GRDP in Indonesia

domestic investment, and foreign investment

Besides factors mentioned in Table 1, there are 3 main other factors which caused controversy a lot They are Inflation, Foreign Direct Investment (FDI) and Female Labor Forces

GDP growth indeed has many controversial issues regarding the explanatory variables such as inflation According to Barro (1995), inflation is the determinant of economic growth, which has been further explained that if there is a high inflation, then the level of investment will be reduced Thus, the reduction in investment adversely affects economic growth Besides that, Mundell (1963) and Tobin (1965), have found the empirical evidence that support the findings that the inflation has huge impact on economic growth

However, other researchers for instance Gultekin (1983), mentioned that depending on the rate of return will affect the relationship between the inflation and GDP If the rate of return is decreased, then economic growth is definitely having a negative relationship with inflation Furthermore, the research was further investigated by Fischer (1993)

Moreover, according to Sidrauski (1967), the inflation has insignificant impact on economic growth This study was then supported by Sarel (1996)

Secondly, the explanatory variable that affects GDP is FDI FDI has always been the major source to finance the economic activities of a country There are some studies on the relationship between FDI and economic growth Based on the previous research, Herzer et al (2008), have mentioned that there is a positive relationship between FDI and economic growth Furthermore, economic instability will probably have a negative effect

on the FDI such as inflation and unstable exchange rate Wai-Mun et al (2008) Besides that, the study about the relationship was further explained by Yol and Teng-Teng (2009)

Their investigation shows that it is a negative relationship between Foreign Direct Investment and economic growth However, Lim (2001); Duasa (2007); Karim and Yusop (2009); Kogid (2010), found that there is no causal relation between FDI and GDP growth

Finally, the explanatory variable that affects GDP growth is female labor force participation Based on empirical studies it showed that female labor force participation rate has proved a significant impact on GDP growth Through the female labor force participation rate, the average household income has improved thus it did increase the

women tend to get better jobs, earn more and are less prone to be unemployed from research done by Bryant et al (2004), concluded that by increasing the labor force participation of women, it increases the rate of GDP This is primary due to more equal human capital investment

From this section, it can be inferred that there is no research on Factors affecting GDP of United Kingdom Therefore, we will take responsibility to make clear this topic

III METHODOLOGY

1 Our model:

Our model is based on the simple model raised before about the Gross Domestic Product using

expenditure approach: GDP is the sum of the final uses of goods and services (all uses except

intermediate consumption) measured in purchasers' prices:

GDP = Y = C + I + G + (X – M) And after consulting other researches about effects of household consuming, export and

government debt on GDP, in the narrow range of our model, we propose the following model

with these variables:

• Government debt: debt (% GDP)

➢ 𝜷𝟏, 𝜷𝟐, 𝜷𝟑, β4 are the coefficient of the independent variables to be estimated and Ui is

the random error term or disturbance error term that represent the missing variable or factors that are not mentioned in the model

2 Data:

Our model uses data for each variable (GDP, Household Consumption, Export and

Government debt of the UK from 1965 to 2010) on the website

Table 1: Economical numbers of the UK from 1965 to 2010

Table 2: Summary Statistic of variables

Variable Maximum Minimum Average GDP 1167792 394292 710745.3

3.2.1 Correlation between independent variables and dependent variable:

- According to theory, household consumption and GDP have positive relation Based

on the table, r (GDP, Con) = 0.9833, which means they are positively correlated Hence it is

suitable with the theory and the correlation is 98.33% which is very high

- Based on theory, when export increases, GDP increases r (GDP, Ex) = 0.9676 therefore they are positively correlated and the correlation is high which is 96.76% So it is

suitable with the theory

- When the government has more debt, it causes GDP to decrease From the table, r

(GDP, debt) = -0.6794, which means they are inverse correlated in 67.94% Therefore it is

suitable with the theory

→ In general, correlations between independent variables and dependent variable are quite high

3.2.2 Correlation among independent variables:

• r (ex, con) = 0.9870 Thus, variable ex and variable con are positively correlated

• r ( debt, con) = -0.5556 Thus, variable debt and variable con are inverse correlated

• r ( debt, ex) = -0.5048 Thus, variable ex and variable ex are inverse correlated

→ The correlation between ex and con is 0,9870 > 0,8 therefore we predict there happens

multicollinearity

Con, ex, debt all have statistically significant effects on GDP at the 5%

significant level (as all p-values are smaller than 0.05) In particular, those effects can be specified by the regression coefficients as follows:

• 𝛽0 = 638169 When all the independent variables are zero, the expected value

of UK GDP is 638169 (billions of GBP)

• 𝛽1 = 0.5966 When the number of household consumption increases by one, the expected value of UK GDP increases by 0.5966 (billions of GBP)

• 𝛽2 = 1 5 3 6 3 When the number of export increases by one, the expected value of UK GDP increases by 1.5363 (billions of GBP)

• 𝛽3= - 2039.7: When the percentage of government debt decreases by one, the expected value of UK GDP increases by 2039.7 (billions of GBP)

• The coefficient of determination R squared = 0.993785: all independent variables

(con, ex, debt) jointly explain 99.37% of the variation in the dependent variable

(GDP); other factors that are not mentioned explain the remaining 0.63% of the variation in the GDP

IV Testing:

1 Testing hypothesis:

1.1 Testing an individual regression coefficient:

➢ Purpose: Test for the statistical significance or the effect of independent

variables on dependent one We have: α = 0.05

➢ Testing the variable of Household Consumption (con):

Given that the hypothesis is:

0:

1 1

1 0





H H

We see: P-value of con is < 0.0001 < 0.05 → Reject H0 → The coefficient 𝛽1 is statistically significant

➢ Testing the variable of Export (ex):

Given that the hypothesis is:

0:

2 1

2 0





H H

We see: P-value of ex is < 0.0001 < 0.05 → Reject H0 → The coefficient 𝛽2 is statistically significant

➢ Testing the variable of Government Debt:

Given that the hypothesis is:

3 1

3 0





H H

We see: P-value of debt is < 0.0001 < 0.05 → Reject H0 → The coefficient 𝛽3 is statistically significant

1.2 Testing the overall significance

➢ Purpose: Test the null hypothesis stating that none of the explanatory variables

has an effect on the dependent variable We have: α = 0.05

Given that the hypothesis is:

=

=

=

0:

0321:

2 3

2 2

2 1 1

We have: P-value (F) = 2.41e - 46 < α = 0.05 → Reject H0 → All parameters are not simultaneously equal to zero→ At least one variable has an effect on dependent one

→ The model is statistically fitted

2 Testing the model’s problems:

2.1 Multicollinearity:

Multicollinearity is the high degree of correlation amongst the explanatory

variables, which may make it difficult to separate out the effects of the individual regressors, standard errors may be overestimated and t-value depressed The problem

of Multicollinearity can be detected by examining the correlation matrix of regressors and carry out auxiliary regressions amongst them In Gretl, the VIF command is used,

which stand for variance inflation factor

• Given that the hypothesis is:

Ho: no multicollinearity

H1 : Multicollinearity exists

Variance Inflation Factors Minimum possible value = 1.0 Values > 10.0 may indicate a collinearity problem

con 46.678 debt 1.618

ex 43.305 VIF(j) = 1/(1 - R(j)^2), where R(j) is the multiple correlation coefficient between variable j and the other independent variables

➢ The value of VIF here is higher than 10, indicating that Multicollinearity can be

a problem for this set of data

→ We’ll make another regression model with dependent variable ex and independent variable con and debt to determine whether the multicollinearity exists or not

• The second regression model:

Rule: If R – squared of the second regression model > 0.9 or > R – squared of the first

regression model then multicollinearity may be present

The regression with dependent variable ex and independent variable con and debt:

Model 2: OLS, using observations 1965-2010 (T = 46)

➢ R-squared = 0,9769 > 0,9 and P-value(F) is quiet small thus we can conclude that

multicollinearity exists

2.1.1 Correcting multicollinearity:

Removing con or ex from the model: