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Questions and Answers
What are the consequences of violating CLRM assumptions?
What are the consequences of violating CLRM assumptions?
- Problems with coefficient estimates, standard errors, and test statistics (correct)
- Violations of CLRM assumptions do not occur
- No impact on coefficient estimates, standard errors, and test statistics
- Only a minor impact on coefficient estimates
What is the consequence of violating the CLRM assumptions?
What is the consequence of violating the CLRM assumptions?
- Problems with coefficient estimates, standard errors, and test statistics (correct)
- Increased precision of coefficient estimates
- No effect on coefficient estimates
- Improved coefficient estimates
What are the consequences of violating CLRM assumptions?
What are the consequences of violating CLRM assumptions?
- Problems with coefficient estimates, standard errors, and test statistics (correct)
- Violations of CLRM assumptions do not occur
- No impact on coefficient estimates, standard errors, and test statistics
- Only a minor impact on coefficient estimates
Which statistical distributions are used to test for violations of CLRM assumptions?
Which statistical distributions are used to test for violations of CLRM assumptions?
What statistical distributions are used to test for violations of CLRM assumptions?
What statistical distributions are used to test for violations of CLRM assumptions?
Which statistical distributions are used to test for violations of CLRM assumptions?
Which statistical distributions are used to test for violations of CLRM assumptions?
What is heteroscedasticity?
What is heteroscedasticity?
What is heteroscedasticity?
What is heteroscedasticity?
What is heteroscedasticity?
What is heteroscedasticity?
What method can be used to account for heteroscedasticity?
What method can be used to account for heteroscedasticity?
What method can be used to account for heteroscedasticity?
What method can be used to account for heteroscedasticity?
What method can be used to account for heteroscedasticity?
What method can be used to account for heteroscedasticity?
What is autocorrelation?
What is autocorrelation?
What is autocorrelation?
What is autocorrelation?
What is multicollinearity?
What is multicollinearity?
What test can be used to detect autocorrelation?
What test can be used to detect autocorrelation?
What test can be used to detect autocorrelation?
What test can be used to detect autocorrelation?
What is the consequence of perfect multicollinearity?
What is the consequence of perfect multicollinearity?
What are the consequences of ignoring autocorrelation?
What are the consequences of ignoring autocorrelation?
What is the Ramsey's RESET test used for?
What is the Ramsey's RESET test used for?
What are the consequences of ignoring autocorrelation?
What are the consequences of ignoring autocorrelation?
What is multicollinearity?
What is multicollinearity?
What is multicollinearity?
What is multicollinearity?
What is the Bera Jarque test used for?
What is the Bera Jarque test used for?
What test is used to test for mis-specification of functional form?
What test is used to test for mis-specification of functional form?
What test is used to test for mis-specification of functional form?
What test is used to test for mis-specification of functional form?
What is the consequence of omitting an important variable or including an irrelevant variable?
What is the consequence of omitting an important variable or including an irrelevant variable?
What are the consequences of omitting an important variable or including an irrelevant variable?
What are the consequences of omitting an important variable or including an irrelevant variable?
What is the recommended textbook for learning about introductory econometrics for finance?
What is the recommended textbook for learning about introductory econometrics for finance?
What are the consequences of omitting an important variable or including an irrelevant variable?
What are the consequences of omitting an important variable or including an irrelevant variable?
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Study Notes
- Lecture 4 focuses on violations of the CLRM assumptions.
- There are five assumptions of the CLRM disturbance terms.
- Violations of these assumptions can cause problems with coefficient estimates, standard errors, and test statistics.
- Tests for violations of these assumptions involve statistical distributions such as F and χ2.
- Heteroscedasticity is a violation of the assumption that the variance of the errors is constant.
- GLS is a method that can be used to account for heteroscedasticity.
- Autocorrelation is a violation of the assumption that there is no pattern in the errors.
- The Breusch-Godfrey test can be used to detect autocorrelation.
- Ignoring autocorrelation can lead to inefficient coefficient estimates and incorrect inferences.
- GLS procedures can be used to correct for autocorrelation, but they require assumptions about the form of the autocorrelation.
- Autocorrelation can present an opportunity to modify regression.
- Dynamic models can be used to account for previous values of y or x.
- Lags in regression can be used to measure time series as overlapping moving averages.
- Multicollinearity occurs when explanatory variables are highly correlated with each other.
- Perfect multicollinearity results in the inability to estimate all coefficients.
- Multicollinearity can be measured by looking at the matrix of correlations between variables.
- The Ramsey's RESET test is used to test for mis-specification of functional form.
- The Bera Jarque test is used to test residuals for normality.
- Omission of an important variable or inclusion of an irrelevant variable can lead to biased and inconsistent estimates.
- The textbook "Introductory Econometrics for Finance, 4th Edition" by Chris Brooks is essential reading.
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