The variable income (yearly) is examined in a regression setting where the predictor variable is lag...
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The variable income (yearly) is examined in a regression setting where the predictor variable is lag (1) of income and the following output is produced. a) Write down the regression equation. (3 marks). b) Interpret the meaning of the slope. (3 marks). c) A dummy variable for gender (male=0, female-1) was added to the model. Interpret its coefficient of -0.2. (3 marks). us_change f model (TSLM (log (Income) log (LagIncome))) %>% report () #> Series: Consumption #> Model: TSLM #> #> Residuals: Min <# N 10 Median #> -2.5824 -0.2778 0.0186 0.3233 #> Coefficients: #> #> (Intercept) 0.5445 #> Log (LagIncome) 1.1000 #> 30 Max 1.4223 Estimate Std. Error t value Pr (>|t|) 0.0540 10.08 2e-16 *** 0.0467 5.82 2.4e-08 *** F #> Signif. codes: 0 ***** 0.001 **** 0.01 *** 0.05 . 0.1 #> #> Residual standard error: 0.591 on 196 degrees of freedom #> Multiple R-squared: 0.147, Adjusted R-squared: 0.143 #> F-statistic: 33.8 on 1 and 196 DF, p-value: 2.4e-08 The variable income (yearly) is examined in a regression setting where the predictor variable is lag (1) of income and the following output is produced. a) Write down the regression equation. (3 marks). b) Interpret the meaning of the slope. (3 marks). c) A dummy variable for gender (male=0, female-1) was added to the model. Interpret its coefficient of -0.2. (3 marks). us_change f model (TSLM (log (Income) log (LagIncome))) %>% report () #> Series: Consumption #> Model: TSLM #> #> Residuals: Min <# N 10 Median #> -2.5824 -0.2778 0.0186 0.3233 #> Coefficients: #> #> (Intercept) 0.5445 #> Log (LagIncome) 1.1000 #> 30 Max 1.4223 Estimate Std. Error t value Pr (>|t|) 0.0540 10.08 2e-16 *** 0.0467 5.82 2.4e-08 *** F #> Signif. codes: 0 ***** 0.001 **** 0.01 *** 0.05 . 0.1 #> #> Residual standard error: 0.591 on 196 degrees of freedom #> Multiple R-squared: 0.147, Adjusted R-squared: 0.143 #> F-statistic: 33.8 on 1 and 196 DF, p-value: 2.4e-08
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a The regression equation can be written as logIncome 05445 11000 logLagIncome b The slope coefficie... View the full answer
Related Book For
Statistics Unlocking The Power Of Data
ISBN: 9780470601877
1st Edition
Authors: Robin H. Lock, Patti Frazer Lock, Kari Lock Morgan, Eric F. Lock, Dennis F. Lock
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