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Which of the following is a good indication that nonlinear terms might be necessary as control variables? When the correlation is weak between the variables. a. O b. None of these. Oc. A clear, nonlinear relationship when plotting the data of the regressors. Failure to reject the null that the variable of interest is 0. d. A clear, nonlinear relationship in the residuals. е.

Which of the following is a good indication that nonlinear terms might be necessary as control variables? When the correlation is weak between the variables. a. O b. None of these. Oc. A clear, nonlinear relationship when plotting the data of the regressors. Failure to reject the null that the variable of interest is 0. d. A clear, nonlinear relationship in the residuals. е.

ENGR.ECONOMIC ANALYSIS
ENGR.ECONOMIC ANALYSIS
14th Edition
ISBN:9780190931919
Author:NEWNAN
Publisher:NEWNAN
Chapter1: Making Economics Decisions
Section: Chapter Questions
Problem 1QTC
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Which of the following is a good indication that nonlinear terms might be necessary as control variables? When the correlation is weak between the variables. None of these. Ob. A clear, nonlinear relationship when plotting the data of the regressors. OC. d. Failure to reject the null that the variable of interest is 0. A clear, nonlinear relationship in the residuals.
Transcribed Image Text:Which of the following is a good indication that nonlinear terms might be necessary as control variables? When the correlation is weak between the variables. None of these. Ob. A clear, nonlinear relationship when plotting the data of the regressors. OC. d. Failure to reject the null that the variable of interest is 0. A clear, nonlinear relationship in the residuals.
If two regressors are a linear combination of each other, what is the result if we run an OLS regressions with both of those regressors present? The regressors will cause the variance of the estimates to be higher but the estimates will still be unbiased. O a. We cannot run OLS because we have perfect multicollinearity. Ob. It will ensure our residuals are linear and not plagued by nonlinearity. OC. It will increase the power of our estimates since the two regressors are related. Od. None of these. Oe.
Transcribed Image Text:If two regressors are a linear combination of each other, what is the result if we run an OLS regressions with both of those regressors present? The regressors will cause the variance of the estimates to be higher but the estimates will still be unbiased. O a. We cannot run OLS because we have perfect multicollinearity. Ob. It will ensure our residuals are linear and not plagued by nonlinearity. OC. It will increase the power of our estimates since the two regressors are related. Od. None of these. Oe.
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