500 words ecronometrics
£20-250 GBP
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Statistics and Econometrics, Semester Two, 2014/5 Project Work This study requires you to compile a sample of data initially for: (1) Total bilateral gross expenditure on aid by the UK for a specific country (GPEX) (2) Unemployment Rates (UR) (please note: there are different unemployment rate series) You will be told your years and country choices. You must then assemble the data. Sources: Data can be obtained via ONS for example in the Annual Abstract of Statistics. The specific data for GPEX is found in Table 3.2 in the Annual Abstract of Statistics (checked in 2010 edition) 1. Present your data in a table showing the names of the variables. Make sure the full definitions and sources of each variable are given. [10 marks] 2. The first equation to be estimated is : 〖GPEX〗_i=b_0+b_1 〖UR〗_i+u_i (Equation 1) Where u is a disturbance term and the i subscript represents year. Answer these questions: (i) In terms of economic theory what sign would you expect to find for the coefficients in the regression equation? [5 marks] (ii) This is a bivariate regression. Explain why this is likely to be inadequate (in comparison to a multivariate) even if we only want to know the impact of UR on GPEX. [5 marks] (iii) Why is there a constant term in equation (1)? [5 marks] (iv) Why do these types of equations have a ‘u’ term ? [5 marks] 3. Estimate equation (1) by OLS and present the results in a suitable table (n.b. marks will be lost for simply copy pasting the computer output) (i) Comment on the result for the coefficient on the UR variable. [5 marks] (ii) Comment on the R squared statistic. [5 marks] (iii) Is the estimated value of b_0 positive or negative? Does it matter for the reliability of your estimates for b_1 whether b_0 is positive or negative? [5 marks] (iv) Examine the residuals of your estimated equation to determine whether any of your years might be considered an outlier in the regression. [5 marks] 4. You are now required to estimate a multivariate model using OLS: 〖GPEX〗_i=b_0+b_1 〖UR〗_i+b_2 Z_i+u_i (Equation 2) where u is a classical disturbance term. Z is the additional variable. You must choose between either GDP per capita of the recipient nation or the male literacy rate in the recipient nation. [10 marks] Give an explanation for the use of both and go on to justify the choice you have made. Outline your reasoning for the expected sign of b_2 for your chosen variable. 5. Carry out the following hypothesis tests (i) b_0=0 against the two-sided alternative at the 10% level for both equations. [5 marks] (ii) b_1=0 against the two-sided alternative at the 5 % level for both equations. [5 marks] (iii) b_1=b_2=0 against the one-sided alternative at the 5% level for equation (2). [5 marks] (iv) Explain the meaning of the test done in part (iii) in terms of R squared. [5 marks] 6. Having estimated both equations, compare their results and consider whether equation (2) is an improvement over equation(1). [5 marks] 7. You should now write a short report of 450-600 words. This should briefly summarize your findings- marks will be given for further exploration of your model involving the provision of new estimates (different functional forms, additional or replacement variables etc.) and suggestions for improvement of the model you have estimated. [15 marks]
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