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Q2. The data file pv.dta contains monthly US data on equity prices, P₁, dividend payments, D., and earnings, Ę, for the period January 1871 to September 2016. (a) Create Pt model = : In(P), d₁ = ln(D), e₁ = ln(E), and plot them over time. Estimate the regression t P₁ = a + ẞd + Se + u (*) t t where u is a disturbance term. t (b) Examine the presence of Multicollinearity, Heteroskedasticity, and Normality in (*).| (c) Suggest remedial measures for the presence of Multicollinearity and Heteroskedasticity in (*).

Q2. The data file pv.dta contains monthly US data on equity prices, P₁, dividend payments, D., and earnings, Ę, for the period January 1871 to September 2016. (a) Create Pt model = : In(P), d₁ = ln(D), e₁ = ln(E), and plot them over time. Estimate the regression t P₁ = a + ẞd + Se + u (*) t t where u is a disturbance term. t (b) Examine the presence of Multicollinearity, Heteroskedasticity, and Normality in (*).| (c) Suggest remedial measures for the presence of Multicollinearity and Heteroskedasticity in (*).

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Q2. The data file pv.dta contains monthly US data on equity prices, P₁, dividend payments, D., and earnings, Ę, for the period January 1871 to September 2016. (a) Create Pt model = : In(P), d₁ = ln(D), e₁ = ln(E), and plot them over time. Estimate the regression t P₁ = a + ẞd + Se + u (*) t t where u is a disturbance term. t (b) Examine the presence of Multicollinearity, Heteroskedasticity, and Normality in (*).| (c) Suggest remedial measures for the presence of Multicollinearity and Heteroskedasticity in (*).
Transcribed Image Text:Q2. The data file pv.dta contains monthly US data on equity prices, P₁, dividend payments, D., and earnings, Ę, for the period January 1871 to September 2016. (a) Create Pt model = : In(P), d₁ = ln(D), e₁ = ln(E), and plot them over time. Estimate the regression t P₁ = a + ẞd + Se + u (*) t t where u is a disturbance term. t (b) Examine the presence of Multicollinearity, Heteroskedasticity, and Normality in (*).| (c) Suggest remedial measures for the presence of Multicollinearity and Heteroskedasticity in (*).
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