Reading 12: Multiple Regression and Issues in Regression Analy 2011, center, common, style

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Session 3: Quantitative Methods for Valuation
Reading 12: Multiple Regression and Issues in Regression Analysis

LOS k: Discuss the effects of model misspecification on the results of a regression analysis, and explain how to avoid the common forms of misspecification.

 

 

When utilizing a proxy for one or more independent variables in a multiple regression model, which of the following errors is most likely to occur?

A) Multicollinearity.

B) Heteroskedasticity.

C) Model misspecification.

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By using a proxy for an independent variable in a multiple regression analysis, there is some degree of error in the measurement of the variable.

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When constructing a regression model to predict portfolio returns, an analyst runs a regression for the past five year period. After examining the results, she determines that an increase in interest rates two years ago had a significant impact on portfolio results for the time of the increase until the present. By performing a regression over two separate time periods, the analyst would be attempting to prevent which type of misspecification?

A) Using a lagged dependent variable as an independent variable.

B) Incorrectly pooling data.

C) Forecasting the past.

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The relationship between returns and the dependent variables can change over time, so it is critical that the data be pooled correctly. Running the regression for multiple sub-periods (in this case two) rather than one time period can produce more accurate results.

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Which of the following is least likely to result in misspecification of a regression model?

A) Using a lagged dependent variable as an independent variable.

B) Transforming a variable.

C) Measuring independent variables with errors.

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A basic assumption of regression is that the dependent variable is linearly related to each of the independent variables. Frequently, they are not linearly related and the independent variable must be transformed or the model is misspecified. Therefore, transforming an independent variable is a potential solution to a misspecification. Methods used to transform independent variables include squaring the variable or taking the square root.

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Thank you very much