Wooldridge PPT ch4

# C α 1 α29 f f f the f statistic cont reject fail to

• Notes
• 38
• 100% (1) 1 out of 1 people found this document helpful

This preview shows pages 31–38. Sign up to view the full content.

c α (1 -α29 f( F ) F The F statistic (cont) reject fail to reject Reject H 0 at α significance level if F > c

This preview has intentionally blurred sections. Sign up to view the full version.

Fall 2008 under Econometrics Prof. Keunkwan Ryu 32 The R 2 form of the F statistic Because the SSR’s may be large and unwieldy, an alternative form of the formula is useful We use the fact that SSR = SST(1 – R 2 ) for any regression, so can substitute in for SSR u and SSR ur ( 29 ( 29 ( 29 ed unrestrict is ur and restricted is r again where , 1 1 2 2 2 - - - - k n R q R R F ur r ur
Fall 2008 under Econometrics Prof. Keunkwan Ryu 33 Overall Significance A special case of exclusion restrictions is to test H 0 : β 1 = β 2 =…= β k = 0 Since the R 2 from a model with only an intercept will be zero, the F statistic is simply ( 29 ( 29 1 1 2 2 - - - = k n R k R F

This preview has intentionally blurred sections. Sign up to view the full version.

Fall 2008 under Econometrics Prof. Keunkwan Ryu 34 General Linear Restrictions The basic form of the F statistic will work for any set of linear restrictions First estimate the unrestricted model and then estimate the restricted model In each case, make note of the SSR Imposing the restrictions can be tricky – will likely have to redefine variables again
Fall 2008 under Econometrics Prof. Keunkwan Ryu 35 Example: Use same voting model as before Model is voteA = β 0 + β 1 log( expendA ) + β 2 log( expendB ) + β 3 prtystrA + u now null is H 0 : β 1 = 1, β 3 = 0 Substituting in the restrictions: voteA = β 0 + log( expendA ) + β 2 log( expendB ) + u , so Use voteA - log( expendA ) = β 0 + β 2 log( expendB ) + u as restricted model

This preview has intentionally blurred sections. Sign up to view the full version.

Fall 2008 under Econometrics Prof. Keunkwan Ryu 36 F Statistic Summary Just as with t statistics, p-values can be calculated by looking up the percentile in the appropriate F distribution Stata will do this by entering: display fprob( q, n – k – 1, F ), where the appropriate values of F, q, and n – k – 1 are used If only one exclusion is being tested, then F = t 2 , and the p -values will be the same
Eg. Salary-pension tradeoff for teachers Log(totcomp)=f(productivity characteristics, other factors) Totcomp=salary+benefits=salary(1+benefits/salary) Log (salary) = β 0 + β 1 (benefits/salary)+other factors Fall 2008 under Econometrics Prof. Keunkwan Ryu 37

This preview has intentionally blurred sections. Sign up to view the full version.

Fall 2008 under Econometrics Prof. Keunkwan Ryu 38
This is the end of the preview. Sign up to access the rest of the document.
• Fall '10
• H.Bierens
• Econometrics, Statistical hypothesis testing, Prof. Keunkwan Ryu

{[ snackBarMessage ]}

### What students are saying

• As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

Kiran Temple University Fox School of Business ‘17, Course Hero Intern

• I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

Dana University of Pennsylvania ‘17, Course Hero Intern

• The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

Jill Tulane University ‘16, Course Hero Intern