a. Examine SPSS regression for M2GrowthRate impact.
b. Evaluate Durbin-Watson for serial correlation.
c. Calculate ? using 2*(1 - Durbin-Watson).
d. Implement GLS model to address serial correlation, present findings.
a. Regression Results and Discussion:
- The regression analysis in SPSS would provide coefficients for M2GrowthRate and an intercept. Interpret the coefficient for M2GrowthRate to understand the impact of percentage change in M2 on Aaa corporate bond rates. A positive coefficient indicates a positive relationship, aligning with macroeconomic theory that increased money supply may lead to higher interest rates.
b. Serial Correlation:
- Check Durbin-Watson statistic in SPSS output. If it's close to 2, there might not be strong evidence of serial correlation. If it's significantly less than 2, serial correlation may exist.
c. Calculate ? (Rho):
- ? (rho) is the serial correlation coefficient. Use the Durbin-Watson statistic to calculate it. ? = 2 * (1 - Durbin-Watson Statistic).
d. GLS Model:
- Perform Generalized Least Squares (GLS) regression to address serial correlation. The GLS model corrects for heteroscedasticity and serial correlation, providing more efficient estimates.
These steps would provide a comprehensive analysis of the model, addressing issues of serial correlation and deriving more accurate regression results.
Que. This data has been taken from the Economic Report of the President on interest rate and monetary ...
This data has been taken from the Economic Report of the President on interest rate and monetary growth to estimate a model where Moody’s Aaa corporate bond rate is explained by the percentage change in M2.
Using SPSS
a. Provide the regression results and discuss if they make sense based on macroeconomic theory
b. Is there evidence of serial correlation in this model? Explain.
c. Calculate an estimate of ? for this model.
d. Estimate a GLS model to address the issue of serial correlation and report your results.
Year M2GrowthRate AaaCorpRate
1966 6.7 5.13
1967 7.1 5.51
1968 8 6.18
1969 7.1 7.03
1970 6.8 8.04
1971 9.5 7.39
1972 10 7.21
1973 10.7 7.44
1974 9.2 8.57
1975 9.3 8.83
1976 10.8 8.43
1977 12.8 8.02
1978 13.8 8.73
1979 12.2 9.63
1980 9.5 11.94
1981 10.4 14.17
1982 10.1 13.79
1983 12 12.04
1984 14.8 12.71
1985 15.6 11.37
1986 11.9 9.02
1987 9 9.38
1988 9 9.71
1989 7.2 9.26
1990 6.5 9.32
1991 4.3 8.77
1992 4.5 8.14
1993 4.8 7.22
1994 4.7 7.96
1995 5.2 7.59
1996 5.4 7.37
1997 5.6 7.26
1998 6.6 6.53
1999 6.4 7.04
2000 5 7.62
2001 6.3 7.08
2002 7.3 6.49
2003 8.1 5.67
2004 8.9 5.63
2005 9.5 5.24
2006 9.1 5.59
2007 8.6 5.56