Question

For the model ln(y) = β0 + β1x + ε, β1 is the approximate percentage change...

For the model ln(y) = β0 + β1x + ε, β1 is the approximate percentage change in Y when x increases by 1%. True or false?

Business   Economics   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #2

answered by: anonymous
0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Suppose y is determined by the true model y=β0+β1x+β2z+ε, and that β2 >0 and COV(z,x) <...
Suppose y is determined by the true model y=β0+β1x+β2z+ε, and that β2 >0 and COV(z,x) < 0. If someone were interested in estimating β1, and did so by using OLS to estimate y = β0 + β1x + u, would the OLS estimator of β1 be biased or not? If it is unbiased, explain why. If it is biased, is the bias positive or negative? Why?
In the model Y = β0 + β1X1 + β2X2 + ε, which of these parameters...
In the model Y = β0 + β1X1 + β2X2 + ε, which of these parameters represents a coefficient of an independent variable? Group of answer choices the β1 the X1 the Y the ε
Consider the complementary log log model log(− log(1 − π(x))) = β0 + β1x. Show the...
Consider the complementary log log model log(− log(1 − π(x))) = β0 + β1x. Show the greatest rate of change of π(x) occurs at x = −β0/β1.
Consider the complementary log log model log(− log(1 − π(x))) = β0 + β1x. Show the...
Consider the complementary log log model log(− log(1 − π(x))) = β0 + β1x. Show the greatest rate of change of π(x) occurs at x = −β0/β1.
Suppose you are given the following simple dataset, regress Y on X: y=β0+β1x+u X Y 1...
Suppose you are given the following simple dataset, regress Y on X: y=β0+β1x+u X Y 1 2 2 4 6 6 Calculate β0 andβ1Show algebraic steps. Interpret β0 and β1 Calculate the predicted(fitted)value of each observation Calculate the residual ofeach observation When x=3, what is the predicted value of Y? Calculate SSR, SST, and then SSE. How much of the variation in Y is explained by X? 8)Calculate the variance estimator
Consider the model ln(Yi)=β0+β1Xi+β2Ei+β3XiEi+ui, where Y is an individual's annual earnings in dollars, X is years...
Consider the model ln(Yi)=β0+β1Xi+β2Ei+β3XiEi+ui, where Y is an individual's annual earnings in dollars, X is years of work experience, and E is years of education. Consider an individual with a high-school degree (E=12yrs) who has been working for 20 years. The expected increase in log earnings next year (when X=21yrs) compared to this year is, dropping units, β1 β1+12β3 β1+β3 β0+21β1+12β2+252β3
Consider the multiple linear regression model y = β0 +β1x1 +β2x2 +β3x3 +β4x4 +ε Using the...
Consider the multiple linear regression model y = β0 +β1x1 +β2x2 +β3x3 +β4x4 +ε Using the procedure for testing a general linear hypothesis, show how to test a. H 0 : β 1 = β 2 = β 3 = β 4 = β b. H 0 : β 1 = β 2 , β 3 = β 4 c. H0: β1-2β2=4β3           β1+2β2=0
Model: Y = β0 + β1X + u If E(u|X) 6= 0, then we know the...
Model: Y = β0 + β1X + u If E(u|X) 6= 0, then we know the OLS estimator will be biased and all further inference like Hypothesis test and Confidence interval will be invalid. In presence of such violation, we can go to Instrument variable estimation/regression method to rebuild the valid empirical study. Assume there is a “good” instrument variable Z for X. (1) How would you argue this is a valid instrument variable?(Hint: validity condition and relevance condition) (2)...
Model: Y = β0 + β1X + u If E(u|X) 6= 0, then we know the...
Model: Y = β0 + β1X + u If E(u|X) 6= 0, then we know the OLS estimator will be biased and all further inference like Hypothesis test and Confidence interval will be invalid. In presence of such violation, we can go to Instrument variable estimation/regression method to rebuild the valid empirical study. Assume there is a “good” instrument variable Z for X. (1) How would you argue this is a valid instrument variable?(Hint: validity condition and relevance condition) (2)...
How to interpret coefficients in multi regression model like this? ln(PRICE) = β1 + β2SQFT +...
How to interpret coefficients in multi regression model like this? ln(PRICE) = β1 + β2SQFT + β3AGE + β4AGE^2 + ε
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT