State if the following is True or false and provide a brief explanation for your answer. Consider Population model Y = Bo + B1X1+ B2X2 + B3X3 +µ. Now consider the following statements a to c. Assumption MLR 1 – 4 is satisfied if and only if: a. X3has no effect on Y after X, & X, have been controlled for which means ß3 = 0 b. X3 may or maynot be correlated with X, & X,. All that matters is that X, & X, are controlled for X,has no effect on Y. c. Given that ß3 = 0 we are inclined to estimate the equation to include X3. Serial correlation (also called Autocorrelation) is where error terms in a time series transfer from one period to the same period. d. One of the assumptions that needs to hold for the process {yt} to be weakly stationary is that cov(yt,yt-k is constant over time and depends on both t and k.
State if the following is True or false and provide a brief explanation for your answer. Consider Population model Y = Bo + B1X1+ B2X2 + B3X3 +µ. Now consider the following statements a to c. Assumption MLR 1 – 4 is satisfied if and only if: a. X3has no effect on Y after X, & X, have been controlled for which means ß3 = 0 b. X3 may or maynot be correlated with X, & X,. All that matters is that X, & X, are controlled for X,has no effect on Y. c. Given that ß3 = 0 we are inclined to estimate the equation to include X3. Serial correlation (also called Autocorrelation) is where error terms in a time series transfer from one period to the same period. d. One of the assumptions that needs to hold for the process {yt} to be weakly stationary is that cov(yt,yt-k is constant over time and depends on both t and k.
A First Course in Probability (10th Edition)
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ISBN:9780134753119
Author:Sheldon Ross
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Chapter1: Combinatorial Analysis
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Transcribed Image Text:State if the following is True or false and provide a brief explanation for your answer.
Consider Population model Y = Bo + B1X1+ B2X2+ B3X3 + µ. Now consider the
following statements a to c. Assumption MLR 1– 4 is satisfied if and only if:
a. X,has no effect on Y after X, &X, have been controlled for which means B3 = 0
%3D
b. X3 may or maynot be correlated with X, & X,. All that matters is that X, & X, are controlled
for X, has no effect on Y.
c. Given that B3 = 0 we are inclined to estimate the equation to include X3.
Serial correlation (also called Autocorrelation) is where error terms in a time series transfer
from one period to the same period.
d. One of the assumptions that needs to hold for the process {yt} to be weakly stationary is
that cov(yt,yt-k is constant over time and depends on both t and k.
Transcribed Image Text:A white noise process is a non-stationary process for which all autocorrelations are equal
to zero.
e.
f. If our series are non-stationary, it is safe to use OLS as our estimation method.
g. Heteroscedasticity occurs when the disturbance term in a regression model is correlated
with one of the explanatory variables
h. In the presence of heteroscedasticity, ordinary lease squares (OLS) is an inefficient
estimation technique and this causes t tests and F tests to be invalid.
i. Heteroscedasticity can be detected with the Chow test.
j. In the presence of autocorrelation, ordinary lease squares (OLS) produce unbiased
estimates and hence t tests and F tests are still valid.
k. One problem with the use of a lagged dependent variable as an explanatory variable is
that it always gives rise to autocorrelation.
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