Using the link below to access the spreadsheet in Google Docs, please answer the following questions.

1. It will offer some, relatively old but yet informative, sample evidence of ticket prices for a wide range of air travel routes. Use the spreadsheet below to estimate the parameters of the following population regression function: log_ticket_price=a+b*log_distance+u, where u is the error term.

Ticket prices increases by _________ % when distance between the origin and destination increases by 1%. (Your answer should be rounded up to only 2 decimal points).

2. What is the lower limit of the 95% confidence interval for parameter b in the above regression function (Question 1)? (Your answer should be rounded up to only 2 decimal points).

3. What is the upper limit of the 955 confidence interval for parameter b in the above regression function (Question #1) (Your answer should be rounded up to only 2 decimal points).

4. What is the R-Square for the above model in (Question #1)? (Your answer should be rounded up to only 2 decimal points).

5.Multiple Choice Question- Now use Excel to estimate the parameters of the regression function below:

log_ticket_price=a+b1*log_distance+b2*log_ave_daily_pass+b3*log_competition+u

All else being constant, the greater the demand for the airline route (i.e., the greater the value oflog_ave_daily_pass), the:

a. higher the ticket prices

b. lower the ticket prices, though the relationship appears to be statistically insignificant (i.e., the population parameter is no different than zero).

c.higher the ticket prices, though the relationship appears to be statistically insignificant (i.e., the population parameter is no different from zero).

d.lower the ticket prices.

6.Multiple Choice Question- Consider your estimation results in Question number 5. One can say that, conditional upon other covariates, greater competition is associated with:

a.higher ticket prices, though the relationship appears to be statistically insignificant (i.e., the population parameter is no different from zero).

b.lower ticket prices.

c.higher ticket prices

d.lower ticket prices, though the relationship appears to be statistically insignificant (i.e., the population parameter is no different from zero).

7. What is the R-Square for the above model (Question number 5)? (Your answer should be rounded up to only 2 decimal points).

8. Let CORR1 be the unconditional correlation between log_ticket_price and log_distance. Also, let CORR2 be the conditional correlation between log_ticket_price and log_distance as estimated under the population regression function in Question number 5. Lastly, let D be the difference between CORR1 and CORR2; i.e., D=CORR1 - CORR2.

D is equal to: _______________________

(Your answer should be rounded up to only 2 decimal points).

Link to access the dataset to answer the questions: https://docs.google.com/spreadsheets/d/1b3t6rUs0baDM8WvbqjsRe74vhD3cy2aF/edit?usp=sharing&ouid=106829664085244260934&rtpof=true&sd=true