Statistics Project Work - Essay Example

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STATISTICAL COMPUTATION OF GLOBAL COMPETITIVENESS INDICES By: Presented to: Institution: Date: Introduction Below is a computation of economic and governance indicators including GDP/ Capita, Price Inflation and Savings Rate for 20 countries selected randomly from across the globe…
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Download file to see previous pages 2 Coefficients(a) Model Unstandardized Coefficients Standardized Coefficients t Sig. 95% Confidence Interval for B B Std. Error Beta Lower Bound Upper Bound 1 (Constant) 19.212 2.953 6.505 .000 12.981 25.443 GDP per Capita 7.072E-05 .000 .243 1.028 .318 .000 .000 Price Inflation .103 .401 .061 .258 .800 -.742 .949 a Dependent Variable: Savings Rate SR = 19.212 + 0.0000707(GDP) + 0.103(PINF) + u ‘u’ is the noise- an identically and independently distributed (iid) random variable. i) b0, the intercept would be expected to assume a positive sign; b1, the coefficient of GDP is expected to have a positive sign since GDP is intended to contribute positively to the ability of a nation to save; b2, the coefficient of price inflation is expected to have a negative coefficient since inflation has a negative contribution to the ability of a nation to save. ii) The marginal propensity to consume is worked out when disposable income and change in consumption are both available in a dataset. The disposable income is in this case the amount left after the individual has spent out on all the essential needs. It could be equated to the savings rate. Therefore using the above obtained equation we can formulate it to be: SR = 19.212 + 0.0000707(GDP) + 0.103(PINF) + u iii) b0 is positive (19.212). This value has an impact on the general values obtained using the model, though not necessarily on b1 and b2 since the model was developed from a purely randomized data- the GDP, SR and PINF for any country are the products of many other factors that cannot be controlled with certainty (Wood, Hewlin & Lah, 2011). iv) The ‘u’ term in these equations stands for the noise (the uncontrollable random variable) whose nature is random and unpredictable. 3. ANOVA(b) Model Sum of Squares df Mean Square F Sig. 1 Regression 85.335 2 42.667 .612 .554(a) Residual 1184.575 17 69.681 Total 1269.910 19 a Predictors: (Constant), Price Inflation, GDP per Capita b Dependent Variable: Savings Rate Coefficients(a) Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 19.212 2.953 6.505 .000 GDP per Capita 7.072E-05 .000 .243 1.028 .318 Price Inflation .103 .401 .061 .258 .800 a Dependent Variable: Savings Rate Both the GDP per Capita and the tice inflation (PINF) have positive coefficients, which means that they contribute positively to the ability of the nationals to save. The situation is as real as it happens in real sense. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .259(a) .067 -.043 8.34751 a Predictors: (Constant), Price Inflation, GDP per Capita From the adjusted R-square statistic, it is noted that only 4.3% of the variation in the ability of nationals to save can be explained by the two independent variables together (GDP per capita and price inflation of commodities). This is a clear indication that there are other more powerful determinants of the the ability of a nation to save. The unrepresented factors account for as much as 95.7% of the total variation observed. 4. Descriptive Statistics N Std. ...Download file to see next pagesRead More
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