FEEDBACK: The standard error of a regression is not an unbiased estimator for the standard deviation of the error in a multiple regression model.

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1 Introutory Eonometris: A Moern Approh 6th Eition Woolrige Test Bnk Solutions Complete ownlo: Solutions Mnul for Introutory Eonometris A Moern Approh 6th Eition Jeffrey M. Woolrige Solutions Mnul, Instrutor Mnul, Answer key for ll hpters, Appenix hpter, Dt Sets - Minitb, Dt Sets - R re inlue. Downlo link: 1. Whih of the following sttements is true?. The stnr error of regression,, is not n unbise estimtor for, the stnr evition of the error, u, in multiple regression moel. b. In time series regressions, OLS estimtors re lwys unbise.. Almost ll eonomists gree tht unbiseness is miniml requirement for n estimtor in regression nlysis.. All estimtors in regression moel tht re onsistent re lso unbise. FEEDBACK: The stnr error of regression is not n unbise estimtor for the stnr evition of the error in multiple regression moel. 2. If j, n unbise estimtor of j, is onsistent, then the:. istribution of j beomes more n more loosely istribute roun j s the smple size grows. b. istribution of j beomes more n more tightly istribute roun j s the smple size grows.. istribution of j tens towr stnr norml istribution s the smple size grows.. istribution of j remins unffete s the smple size grows. b FEEDBACK: If j, n unbise estimtor of j, is onsistent, then the istribution of j beomes more n more tightly istribute roun j s the smple size grows. Pge 1

2 3. If j, n unbise estimtor of j, is lso onsistent estimtor of j, then when the smple size tens to infinity:. the istribution of j ollpses to single vlue of zero. b. the istribution of j iverges wy from single vlue of zero.. the istribution of j ollpses to the single point j.. the istribution of j iverges wy from j. FEEDBACK: If j, n unbise estimtor of j, is lso onsistent estimtor of j, then when the smple size tens to infinity the istribution of j ollpses to the single point j. 4. In multiple regression moel, the OLS estimtor is onsistent if:. there is no orreltion between the epenent vribles n the error term. b. there is perfet orreltion between the epenent vribles n the error term.. the smple size is less thn the number of prmeters in the moel.. there is no orreltion between the inepenent vribles n the error term. FEEDBACK: In multiple regression moel, the OLS estimtor is onsistent if there is no orreltion between the explntory vribles n the error term. 5. If the error term is orrelte with ny of the inepenent vribles, the OLS estimtors re:. bise n onsistent. b. unbise n inonsistent.. bise n inonsistent.. unbise n onsistent. FEEDBACK: If the error term is orrelte with ny of the inepenent vribles, then the OLS estimtors re bise n inonsistent. Pge 2

3 6. If 1 = Cov(x 1,x 2 ) / Vr(x 1 ) where x 1 n x 2 re two inepenent vribles in regression eqution, whih of the following sttements is true?. If x 2 hs positive prtil effet on the epenent vrible, n 1 > 0, then the inonsisteny in the simple regression slope estimtor ssoite with x 1 is negtive. b. If x2 hs positive prtil effet on the epenent vrible, n 1 > 0, then the inonsisteny in the simple regression slope estimtor ssoite with x 1 is positive.. If x 1 hs positive prtil effet on the epenent vrible, n 1 > 0, then the inonsisteny in the simple regression slope estimtor ssoite with x 1 is negtive.. If x1 hs positive prtil effet on the epenent vrible, n 1 > 0, then the inonsisteny in the simple regression slope estimtor ssoite with x 1 is positive. b FEEDBACK: Given tht 1 = Cov(x 1,x 2 )/Vr(x 1 ) where x 1 n x 2 re two inepenent vribles in regression eqution, if x 2 hs positive prtil effet on the epenent vrible, n 1 > 0, then the inonsisteny in the simple regression slope estimtor ssoite with x 1 is positive. 7. If the moel stisfies the first four Guss-Mrkov ssumptions, then v hs:. zero men n is orrelte with only x1. b. zero men n is orrelte with x1 n x2.. zero men n is orrelte with only x2.. zero men n is unorrelte with x1 n x2. FEEDBACK: If the moel stisfies the first four Guss- Mrkov ssumptions, then v hs zero men n is unorrelte with x1 n x2. 8. If OLS estimtors stisfy symptoti normlity, it implies tht:. they re pproximtely normlly istribute in lrge enough smple sizes. b. they re pproximtely normlly istribute in smples with less thn 10 observtions.. 2 they hve onstnt men equl to zero n vrine equl to.. they hve onstnt men equl to one n vrine equl to. Pge 3

4 Feebk: If OLS estimtors stisfy symptoti normlity, it implies tht they re pproximtely normlly istribute in lrge enough smple sizes. 9. In regression moel, if vrine of the epenent vrible, y, onitionl on n explntory vrible, x, or Vr(y x), is not onstnt,.. the t sttistis re invli n onfiene intervls re vli for smll smple sizes b. the t sttistis re vli n onfiene intervls re invli for smll smple sizes. the t sttistis n the onfiene intervls re vli no mtter how lrge the smple size is. the t sttistis n the onfiene intervls re both invli no mtter how lrge the smple size is FEEDBACK: If vrine of the epenent vrible onitionl on n explntory vrible is not onstnt the usul t sttistis n the onfiene intervls re both invli no mtter how lrge the smple size is. 10. If j is n OLS estimtor of regression oeffiient ssoite with one of the explntory vribles, suh tht j = 1, 2,., n, symptoti stnr error of j will refer to the:. estimte vrine of j when the error term is normlly istribute. b. estimte vrine of given oeffiient when the error term is not normlly istribute.. squre root of the estimte vrine of j when the error term is normlly istribute.. squre root of the estimte vrine of j when the error term is not normlly istribute. FEEDBACK: Asymptoti stnr error refers to the squre root of the estimte vrine of j when the error term is not normlly istribute. 11. A useful rule of thumb is tht stnr errors re expete to shrink t rte tht is the inverse of the:. squre root of the smple size. b. prout of the smple size n the number of prmeters in the moel.. squre of the smple size. Pge 4

5 . sum of the smple size n the number of prmeters in the moel. FEEDBACK: Stnr errors n be expete to shrink t rte tht is the inverse of the squre root of the smple size. 12. An uxiliry regression refers to regression tht is use:. when the epenent vribles re qulittive in nture. b. when the inepenent vribles re qulittive in nture.. to ompute test sttisti but whose oeffiients re not of iret interest.. to ompute oeffiients whih re of iret interest in the nlysis. FEEDBACK: An uxiliry regression refers to regression tht is use to ompute test sttisti but whose oeffiients re not of iret interest. 13. The n-r-squre sttisti lso refers to the:. F sttisti. b. t sttisti.. z sttisti.. LM sttisti. FEEDBACK: The n-r-squre sttisti lso refers to the LM sttisti. 14. The LM sttisti follows :. t istribution. b. f istribution.. istribution.. binomil istribution. FEEDBACK: The LM sttisti follows istribution. Pge 5

6 15. Whih of the following sttements is true?. In lrge smples there re not mny isrepnies between the outomes of the F test n the LM test. b. Degrees of freeom of the unrestrite moel re neessry for using the LM test.. The LM test n be use to test hypotheses with single restritions only n provies ineffiient results for multiple restritions.. The LM sttisti is erive on the bsis of the normlity ssumption. FEEDBACK: In lrge smples there re not mny isrepnies between the F test n the LM test beuse symptotilly the two sttistis hve the sme probbility of Type 1 error. 16. When the error term is not normlly istribute, then is sometimes lle the:. symptoti stnr error. b. symptoti t sttisti.. symptoti onfiene intervl.. symptoti normlity. FEEDBACK: When the error term is not normlly istribute, then is sometimes lle the symptoti stnr error. 17. Whih of the following sttements is true uner the Guss-Mrkov ssumptions?. Among ertin lss of estimtors, OLS estimtors re best liner unbise, but re symptotilly ineffiient. b. Among ertin lss of estimtors, OLS estimtors re bise but symptotilly effiient.. Among ertin lss of estimtors, OLS estimtors re best liner unbise n symptotilly effiient.. The LM test is inepenent of the Guss-Mrkov ssumptions. FEEDBACK: Uner the Guss-Mrkov ssumptions, mong ertin lss of estimtors, OLS estimtors re best liner unbise n symptotilly effiient. Pge 6

7 Asymptoti Effiieny of OLS 18. The Cuhy-Shwrtz inequlity implies tht the symptoti vrine of is:. greter thn. b. less thn or equl to.. equl to.. less thn. b FEEDBACK: The Cuhy-Shwrtz inequlity implies tht the symptoti vrine of is less thn or equl to. Asymptoti Effiieny of OLS 19. If vrine of n inepenent vrible in regression moel, sy x 1, is greter thn 0, or Vr(x 1 ) > 0, the inonsisteny in 1 (estimtor ssoite with x 1 ) is negtive, if x 1 n the error term re positively relte. Flse FEEDBACK: If vrine of n inepenent vrible, sy x 1, is greter thn 0, the inonsisteny in 1 (estimtor ssoite with x 1 ) is positive if x 1 n the error term re positively relte. 20. In the multiple regression moel, if x1 is orrelte with u but the other inepenent vribles re unorrelte with u, then ll of the OLS estimtors re generlly onsistent. Flse FEEDBACK: In the multiple regression moel, if x1 is orrelte with u but the other inepenent vribles re unorrelte with u, then ll of the OLS estimtors re generlly inonsistent. Pge 7

8 21. Even if the error terms in regression eqution, u 1, u 2,, u n, re not normlly istribute, the estimte oeffiients n be normlly istribute. Flse FEEDBACK: Even if the error terms in regression eqution, u 1, u 2,, u n, re not normlly istribute, the estimte oeffiients nnot be normlly istribute. 22. A normlly istribute rnom vrible is symmetrilly istribute bout its men, it n tke on ny positive or negtive vlue (but with zero probbility), n more thn 95% of the re uner the istribution is within two stnr evitions. True FEEDBACK: A normlly istribute rnom vrible is symmetrilly istribute bout its men, it n tke on ny positive or negtive vlue (but with zero probbility), n more thn 95% of the re uner the istribution is within two stnr evitions. 23. The F sttisti is lso referre to s the sore sttisti. Flse FEEDBACK: The LM sttisti is lso referre to s the sore sttisti. 24. The LM sttisti requires estimtion of the unrestrite moel only. Pge 8

9 Flse FEEDBACK: The LM sttisti requires estimtion of the restrite moel only. 25. If Cov(z,x) 0, then z n x re orrelte. True If Cov(z,x) 0, then z n x re orrelte. Asymptoti Effiieny of OLS More ownlo links: introutory eonometris moern pproh test bnk ownlo free smple introutory eonometris moern pproh 6th eition solutions mnul free smple ownlo pf eonometris test bnk questions introutory eonometris moern pproh 5th eition solutions mnul pf introutory eonometris woolrige 5th eition solutions pf introutory eonometris test bnk introutory eonometris moern pproh 6th eition solutions pf introutory eonometris woolrige solution mnul pf woolrige introutory eonometris solutions 5e Pge 9