The picture shows that the estimation of the model with quarterly car sales in the U.S. from 1975 to 1990. Based on the parameter estimates, what is the predicted effect of a 10% increase in price on...

The picture shows that the estimation of the model with quarterly car sales in the U.S. from 1975 to 1990. Based on the parameter estimates, what is the predicted effect of a 10% increase in price on the number of cars sold? What would be the effect of that price increase on the value of car sales?

Number of obs =<br>F( 2,<br>Prob > F<br>Source<br>df<br>MS<br>64<br>61) =<br>12.21<br>Model<br>.32720224<br>2<br>.16360112<br>0.0000<br>R-aquared<br>Adj R-squared -<br>Root MSE<br>Residual<br>.817286587<br>61<br>.013398141<br>0.2859<br>0.2625<br>Total|<br>1.14448883<br>63<br>.018166489<br>.11575<br>1gne |<br>Coef.<br>Std. Err.<br>t<br>P>|t|<br>[954 Conf. Interval)<br>lprice<br>lincome<br>-.8280926<br>.1838504<br>-4.50<br>0.000<br>-1.195724<br>-.4604611<br>2.399991<br>.4860261<br>4.94<br>0.000<br>1.428121<br>3.37186<br>cons<br>5.92543<br>.4843662<br>12.23<br>0.000<br>4.95688<br>6.89398<br>

Extracted text: Number of obs = F( 2, Prob > F Source df MS 64 61) = 12.21 Model .32720224 2 .16360112 0.0000 R-aquared Adj R-squared - Root MSE Residual .817286587 61 .013398141 0.2859 0.2625 Total| 1.14448883 63 .018166489 .11575 1gne | Coef. Std. Err. t P>|t| [954 Conf. Interval) lprice lincome -.8280926 .1838504 -4.50 0.000 -1.195724 -.4604611 2.399991 .4860261 4.94 0.000 1.428121 3.37186 cons 5.92543 .4843662 12.23 0.000 4.95688 6.89398

Jun 07, 2022

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The picture shows that the estimation of the model with quarterly car sales in the U.S. from 1975 to 1990. Based on the parameter estimates, what is the predicted effect of a 10% increase in price on...

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