Question

Explain the rationale for including a lagged dependent variable in a regression equation.

Explain the rationale for including a lagged dependent variable in a regression equation.

Business   Economics   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

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
In regression analysis, a higher correlation between the dependent variable and the independent variable indicates a...
In regression analysis, a higher correlation between the dependent variable and the independent variable indicates a higher estimated slope.
Regression ____ (b values) indicate how much influence each independent variable has on the dependent variable....
Regression ____ (b values) indicate how much influence each independent variable has on the dependent variable. Regression analysis serves two main purposes: to define the relationship between variables and to ____ values of the dependent variable using what we know about the existing correlation between the variables. The coefficient of multiple determination, R^2, is interpreted as the percentage of ____ in the dependent variable that is explained by the independent variable.
When multiple regression analysis shows that variable Xi does not significantly affect the dependent variable Y,...
When multiple regression analysis shows that variable Xi does not significantly affect the dependent variable Y, it does necessary follow that Xi has no influence over Y? Explain and justify your answer. (10 POINTS)
Regression: It DOES NOT matter which is the explanatory/independent variable and which is the response/dependent variable...
Regression: It DOES NOT matter which is the explanatory/independent variable and which is the response/dependent variable for ____, but it DOES matter for ____.
Select two variables, one independent variable and the other the dependent variable. Explain the cause and effect the relation between the two.
Select two variables, one independent variable and the other the dependent variable. Explain the cause and effect the relation between the two. How would you construct the Simple Linear Regression (quantity of data and how you will measure the results), and what would you use to validate the equation forecasting an x value. What will be your expectation of the results of this investigation?
1) Write the regression equation. 2) Explain the value of unstandardized B coefficient. 3) Explain the...
1) Write the regression equation. 2) Explain the value of unstandardized B coefficient. 3) Explain the value of standardized B coefficient. 4) What null hypothesis is being tested? Regression Output - 3 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 15162.617 1108.148 13.683 .000 Appraised Land Value 3.496 .054 .793 64.286 .000 a. Dependent Variable: Sale Price
What does “regular” linear regression assume about the distribution of the dependent variable? Give an example...
What does “regular” linear regression assume about the distribution of the dependent variable? Give an example of a variable that would likely violate that assumption. Explain how it would violate the assumption. (Understanding & Using Statistics for Criminology and Criminal Justice)
Develop a regression model of dependent variable Y over an independent variable X. It is given...
Develop a regression model of dependent variable Y over an independent variable X. It is given the estimate of intercept is 11 and estimate of slope is 1.25. What is the value of Y when X=4
Multiple regression was used to explain stock returns using the following variables: • Dependent variable: RET...
Multiple regression was used to explain stock returns using the following variables: • Dependent variable: RET = annual stock returns (%) • Independent variables: MKT = market capitalization (per million $) IND = industry quartile ranking (IND = 4 is the highest ranking) FORT = Fortune 500 firm, where FORT = 1 if the stock is that of a Fortune 500 firm, and FORT = 0 if not a Fortune 500 stock. The regression results are presented in the table...
A trucking company considered a multiple regression model for relating the dependent variable of total daily...
A trucking company considered a multiple regression model for relating the dependent variable of total daily travel time for one of its drivers (hours) to the predictors distance traveled (miles) and the number of deliveries of made. After taking a random sample, a multiple regression was performed and the equation is (time) = 0.04*(distance) + 0.996*(deliveries) - 1.55. Suppose for a given driver's day, he is scheduled to drive 284 miles and make 6 stops. Suppose it took him 10.388...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT