Sketched out answers Final Econ140A 2013Fall

# The probability of survival for a female who paid a

This preview shows page 1. Sign up to view the full content.

This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: probability of survival for a female who paid a \$400 fare is ( ) ( ) d. The probability that a female who paid a \$400 fare survived is 142% 2 page 3 e. No, this does not make sense because we cannot have probabilities greater than 1. A probit model would restrict the predicted probability to somethin g between 0 and 1 for any values of the right hand side variables. 6. ̂ therefore, ̂ () which implies: ̂ () or ̂ ̂ b. There are a couple of ways to do this. The easy one is to use the theorem (̂ ) ̂ )= ̂) ( ( c. We know that the formula for the reported variance is and that ̂ () therefore, the denominator is unchanged. What about ? For Data set 1 the residuals are , and for the Data set 2 they are . , so the value of for ̂ a. is equal to 16 . Thus the reported standard error for ̂ is √ . d. The t-stat is just the ratio of the coefficient and the standard error so the t -stat for the same as the t stat for . 7. a. ( ̂ ) ̂ Therefore, ̂ is consistent. b. This is just the standard OLS estimator, but our “Y” variable is now “X” and our RHS variable is “Z”: ̂ c. Similarly, is also a valid equation to estimate (this is often called the reduced form equation). Write down the OLS estimator ̂ . As above, the OLS estimator for is: ̂ ̂ d. Show that the ratio ̂ is equal to ̂ . 3 is page 4 ̂ ̂ 8. a. b. , [ [ [ c. ( ̂ ) ( ) [ ̂] d. ( ̂) [( ̂ [ ̂ ]) ] [( ̂ *Note that all of the terms with so… )] [( )] are 0 after taking the expectation and that ( ( ) ) ( 4 )...
View Full Document

## This test prep was uploaded on 03/19/2014 for the course ECON 140a taught by Professor Staff during the Spring '08 term at UCSB.

Ask a homework question - tutors are online