Consider the following OLS regression results, $ \ln(\text{inc}) = 1.970 + 0.083 \, \text{educ}, \, R^2 = 0.186 $, where $\text{inc}$ represents annual income (in $1000s) and $\text{educ}$ represents years of education. The $ R^2 $ can be interpreted as:- $ \circ $ .186% of the variation in annual income is explained by years of education.- $ \circ $ .186% of the variation in log annual income is explained by years of education.- $ \circ $ 18.6% of the variation in annual income is explained by years of education.- $ \circ $ 18.6% of the variation in log annual income is explained by years of education.

Given Estimated regression equation: ln(inc)=1.970+0.083 educ R2=0.186 Here inc represents the…

Answered: Consider the following OLS regression…

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

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Consider the following OLS regression results, $ \ln(\text{inc}) = 1.970 + 0.083 \, \text{educ}, \, R^2 = 0.186 $, where $\text{inc}$ represents annual income (in $1000s) and $\text{educ}$ represents years of education. The $ R^2 $ can be interpreted as:

- $ \circ $ .186% of the variation in annual income is explained by years of education.
- $ \circ $ .186% of the variation in log annual income is explained by years of education.
- $ \circ $ 18.6% of the variation in annual income is explained by years of education.
- $ \circ $ 18.6% of the variation in log annual income is explained by years of education.

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Given

Estimated regression equation: $\ln (i n c) = 1.970 + 0.083 e d u c$

R²=0.186

Here inc represents the annual income in thousands of dollars and educ represents years of education.

In the simple linear regression model, the R² measures the goodness of fit and its values lines between 0 and 1. The value of R² indicates how much percentage of variation in the dependent variable is explained by the independent variable.

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