11.76738 0.14637 80.39 185.2261 1.517523 122.05 Cardiff 0.8305 12.66905 0.1562882 81.06 200.6933 1.285398 156.13 South end 0.8347 0.1375053 85.63 191.2164 1.413662 135.26 Brighton 0.8256 12.16372 0.1448235 83.99 187.0117 1.517392 123.25 Bristol 0.8350 0.1522111 78.32 193.3418 1.483988 130.29 Southampton 0.8005 11.82598 0.1478421 79.99 193.2944 1.500767 128.80 Carlisle 0.8013 11.76573 0.1644963 71.53 184.1587 1.463701 125.82 CHV 0.8490 0.1542591 80.83 Table Regression Coefficients and N-W S.E. – The and White tests will be conducted to test for Heteroscedasticity. The Null Hypothesis is that the error term has a constant variance, the error term is homoscedastic (Equation 12) and the alternate hypothesis is that the error variance varies with the dependent variables (Equation 13). H0: Homoscedasticity Equation H1:Heteroscedasticity Equation Table 34 illustrates that, with the exception of Manchester, all of the chosen locations either fail the Breusch-Pagan or White test, with Glasgow, Nottingham, Cardiff and Carlisle failing both tests. These two tests were also applied to the CHV regression, heteroscedasticity was found to be present using the White test, but the error term was found to be homoscedastic using the Breusch-Pagan test. Problems with heteroscedasticity cannot be ignored, it causes the estimators to be inefficient and have much larger variance, changing according to different values of the explanatory variables, hetero-consistent Standard Errors (S.E.) will be calculated after the models have been tested for serial correlation. As the regression is of AR (1) in nature,
11.76738 0.14637 80.39 Cardiff 185.2261 1.517523 122.05 0.8305 12.66905 0.1562882 81.06 South end 200.6933 1.285398 156.13 0.8347 0.1375053 85.63 Brighton 191.2164 1.413662 135.26 0.8256 12.16372 0.1448235 83.99 Bristol 187.0117 1.517392 123.25 0.8350 0.1522111 78.32 Southampton 193.3418 1.483988 130.29 0.8005 11.82598 0.1478421 79.99 Carlisle 193.2944 1.500767 128.80 0.8013 11.76573 0.1644963 71.53 CHV 184.1587 1.463701 125.82 0.8490 0.1542591 80.83 Table – Regression Coefficients and N-W S.E. The and White tests will be conducted to test for Heteroscedasticity. The Null Hypothesis is that the error term has a constant variance, the error term is homoscedastic (Equation 12) and the alternate hypothesis is that the error variance varies with the dependent variables (Equation 13). H0: Homoscedasticity Equation H1:Heteroscedasticity Equation Table 34 illustrates that, with the exception of Manchester, all of the chosen locations either fail the Breusch-Pagan or White test, with Glasgow, Nottingham, Cardiff and Carlisle failing both tests. These two tests were also applied to the CHV regression, heteroscedasticity was found to be present using the White test, but the error term was found to be homoscedastic using the Breusch-Pagan test. Problems with heteroscedasticity cannot be ignored, it causes the estimators to be inefficient and have much larger variance, changing according to different values of the explanatory variables, hetero-consistent Standard Errors (S.E.) will be calculated after the models have been tested for serial correlation. As the regression is of AR (1) in nature,
Alec_Horton_Dissertation.docx