Economics Compare The Performance Of Different Economies - 275 Words

Economics: Compare The Performance Of Different Economies (Essay Sample) Content: EconomicsStudents NameAffiliate InstitutionCourseDate 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 i ncrease in GDPGR (Di Tella, MacCulloch and Oswald, 2001, pp. 335-341).The OLS equation will be of the formYt=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 doesnt 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 countrys 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 periodt 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 educationY=dependent variable and represents the GDP growth rateFor 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.NorwayModel 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: XFor 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 JapanModel 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 doesnt 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 NetherlandModel 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: XNetherlands 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, showin g a very week correlation between the two variables. For SwedenModel 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 ANALYSEDModel 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 BANGLADESHModel Summary Model R R Square Adjusted R Square Std....