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Quantitative Techniques ( use Eviews and Excel ) - Essay Example

Error t-Statistic Prob.   C 1.486055 0.105763 14.05076 0.0000 DLCPI 9.369895 9.630384 0.972951 0.3335 GAP 26.69825 6.550314 4.075873 0.0001 R-squared 0.215946     Mean dependent var 1.548800 Adjusted R-squared 0.196097     S.D. dependent var 0.765175 S.E. of regression 0.686061     Akaike info criterion 2.120198 Sum squared resid 37.18365     Schwarz criterion 2.208248 Log likelihood -83.92811     Hannan-Quinn criter. 2.155549 F-statistic 10.87919     Durbin-Watson stat 0.067376 Prob(F-statistic) 0.000067 Table 7 shows that only the output gap is significant in predicting the interest rate or the policy rate. Additionally, neither of the coefficients takes values that are close to 0.5. 2.c) The stated hypothesis implies that the policy rate responds identically to variations in the output gap and inflation. Table 2 Wald Test: Equation: Untitled Test Statistic Value   df     Probability F-statistic 10.39767 (2, 79)   0.0001 Chi-square 20.79535 2   0.0000 Null Hypothesis Summary: Normalized Restriction (= 0) Value   Std. Err. ...
This graph gives a general idea of how well the model fits the data. 2.e) Table 3 Chow Breakpoint Test: 2001Q1  Null Hypothesis: No breaks at specified breakpoints Varying regressors: All equation variables Equation Sample: 1990Q2 2010Q3 F-statistic 26.00470 Prob. F(3,76) 0.0000 Log likelihood ratio 57.91748 Prob. Chi-Square(3) 0.0000 Wald Statistic  78.01409 Prob. Chi-Square(3) 0.0000 Table 9 shows that the chow breakpoints test reject the null hypothesis that

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there were no breaks at the 1st quarter of 2001. Thus, we conclude that there was a structural break in the relationship in the 1st quarter of 2001. 3.a) I will choose my model based on the principle of parsimony and information criterion. Higher values of AIC and SIC will imply including higher orders of k leads to a better model. Tables 10 through 14 present the results of running OLS regressions for the provided specification for k=0,1,2,3,4. The SIC has gone up with the inclusion of each additional lag. However, the AIC falls until the 2nd last specification. It increases and is higher compared to even the 1st specification (table 10) as is the SIC for the last specification (table 14). However, it should be noted that stock market value emerges as being significant only in the 1st specification. In all following specifications, neither the current period neither the lagged values of the variable are significant. But in these specifications, the gain in values of the information criterion are not substantially high. Table 4 Dependent Variable: I Method: Least Squares Date: 12/31/11 Time: 13:27 Sample (adjusted): 1990Q2 2010Q3 Included observations: 82 after adjustments Coefficient Std. Error t-Statistic Prob.   C 11.56005 1.809245 6.389434 0.0000 INFLATION_RATE -0.018618 0.083502 -0.222962
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Monetary policy and Stock Market 2. a) To compute the GDP gap, we use the Hodrick-Prescott filter. Figure 1 Figure 2 Figure 3 Figures 5-7 are the required graphs. We see that both the output gap as well as the inflation shows volatility. Interestingly both series show signs of a sharp dip around the 1st quarter of 2008 and then a late recovery during the last couple of quarters reflecting the global recession…
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Quantitative Techniques ( use Eviews and Excel )
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macejkovicrosar added comment 17 days ago
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Nice paper! Used it to finish an assignment for a statistics course. It was easy as ABC, for the first time in my life.
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