Economics: Compare The Performance Of Different Economies (Essay Sample)

Economics
Student’s Name
Affiliate Institution
Course
Date
1
The data below was borrowed from world bank data base. Four year data is used for both GDP growth rate and the stock of educational capital [HK] in percentage for the following listed countries :Italy,Norway,Japan,Netherlands,Sweden,USA,Bangladesh,China,Indonesia And India. For GDP GROWTH RATE we take the annual percentage growth rate of GDP at market prices based on constants of the local currency (Hu, 2005)
COUNTRY

YEAR

GDPGR

HK

Italy 2011

2011

0.6

8.4

ITALY

2012

-2.8

6.4

Italy

2013

-1.7

7.1

Italy

2014

-0.4

7.8

Norway

2011

1.0

15.0

Norway

2012

2.7

25.20

Norway

2013

0.7

12.5

Norway

2014

2.2

17.1

Japan

2011

-0.5

9.7

Japan

2012

1.8

9.5

Japan

2013

1.6

9.6

Japan

2014

-0.1

9.4

Netherlands

2011

1.7

11.8

Netherlands

2012

-1.1

11.6

Netherland

2013

-0.5

10.3

Netherlands

2014

1.0

11.2

Sweden

2011

2.7

13.2

Sweden

2012

-0.3

4.8

Sweden

2013

1.2

5.7

Sweden

2014

2.3

12.4

USA

2011

1.6

12.9

USA

2012

2.3

14.0

USA

2013

2.2

12.9

USA

2014

2.4

18.4

Bangladesh

2011

6.5

19.1

Bangladesh

2012

6.5

19.1

Bangladesh

2013

6.0

12.8

Bangladesh

2014

6.1

18.1

China

2011

5.8

19.3

China

2012

5.5

17.5

China

2013

4.2

19.5

China

2014

1.9

14.4

Indonesia

2011

6.2

18.1

Indonesia

2012

6.0

18.1

Indonesia

2013

5.6

16.0

Indonesia

2014

5.0

14.4

India

2011

6.6

6.6

India

2012

5.1

5.1

India

2013

6.9

6.9

India

2014

7.3

7.3

(Marten, et al. 2014, pp. 2164-2171) (Thomsen, et al. 2013) (Ikeda,et al. pp.1094-110)
From the above data we use SPSS to run the regression analysis of each country to provide sufficient room for comparisons.
2.0)
(i) We know from our economic theory that the correlation between government expenditure and income is positive. That is an increase in GDPGR will result to an increase in stock invested on education, therefore the coefficient b1 will be positive indicating direct relationship between the two variables. b0 will also be positive since any government must invest in education with or with any increase in GDPGR (Di Tella, MacCulloch and Oswald, 2001, pp. 335-341).
The OLS equation will be of the form
Yt=b0+bix+u
(ii) From the above information it is clear that this is a bivariate data since it only entails two variables ,the above analysis always have some challenges since; It doesn’t contain more variables which are used to measure economic growth hence the information provided is inadequate to make a conclusion of the performance of a country’s economy. Bivariate data generates a larger error term as compared to multivariate data, therefore, accuracy of the results is always compromised. Even if we try to estimate b1, it will not give the actual relations of the determinants (Phillips,1986, pp 311-340).
(iii) bo represent the constant spending by the government, bi is a coefficient of the independent variable which is the coefficient of the stock invested on education . The i represents country since this analysis is done from different countries hence does not have the subscript (Lewellen and Nagel, 2006, pp.289-306).
Yt=is GDPGR over a given period
t time= the duration for data collection between 2011 -2014,
u=disturbance term.
1
Since we want to compare the performance of different economies of the ten countries, we shall conduct SPSS data analysis of each country and compare the regression results.
Below is the results for regression for Italy,
X =independent variable and represents the percentage of GDP spent on education
Y=dependent variable and represents the GDP growth rate
For Italy,
Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.


B

Std. Error

Beta



1

(Constant)

8.051

.022


367.372

.000


Y

.582

.013

.999

44.543

.001

a. Dependent Variable: X

From the above table b0=8.051 while b1=0.582 while 0.002 represents the error term from the above our OLS will be of the form. Yt=8.051+0.582x+0.002 from the economic theory the coefficients are positive which from our analysis holds.
Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.999a

.999

.998

.03364

a. Predictors: (Constant), Y

From the summary model ,R2=99.9%.This means that 99.9% of the variation in GDPGR is explained by the fitted model. This clearly shows that most of the government expenditure in education is determined by the GDP growth rate.
Norway
Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.905a

.819

.729

2.86465

a. Predictors: (Constant), Y

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.


B

Std. Error

Beta



1

(Constant)

8.843

3.199


2.764

.110


Y

5.216

1.734

.905

3.009

.095

* Dependent Variable: X
For Norway Bo=5.216 and b1 =0.905 therefore the above holds with the economic theory. From the summary table R SQUARED=0.815 indicating that 81.5% of the dependent variables is explained in the independent variable

For Japan
Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.155a

.024

-.464

.15621

a. Predictors: (Constant), Y

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.


B

Std. Error

Beta



1

(Constant)

9.562

.095


100.697

.000


Y

-.017

.077

-.155

-.221

.845

a. Dependent Variable: X

For Japan the bo=9.562 b1=-0.17 this makes Japan a unique nation, since its model doesn’t hold with the economic theory. From the summary table the R SQUARED is 0.024 meaning that only 2.4%of the dependent variables is explained by the independent variables.
For Netherland
Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.387a

.150

-.275

.75113

a. Predictors: (Constant), Y

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.


B

Std. Error

Beta



1

(Constant)

11.170

.387


28.890

.001


Y

.199

.334

.387

.594

.613

* Independent Variable: X
Netherlands behaves like Japan, although the coefficients hold to the economic theories but from the summary model only 15% of the dependent variables are explained in the independent variable, showing a very week correlation between the two variables.

For Sweden
Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.923a

.852

.779

2.06380


Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.


B

Std. Error

Beta



1

(Constant)

4.575

1.667


2.745

.111


Y

3.017

.887

.923

3.399

.077


FOR USA MODEL ANALYSED
Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.604a

.365

.047

2.55617

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.


B

Std. Error

Beta



1

(Constant)

5.200

8.819


.590

.615


Y

4.400

4.106

.604

1.072

.396

a. Dependent Variable: X

FOR BANGLADESH
Model Summary

Model

R

R Square

Adjusted R Square

Std....