ECM3MEC Quiz 2 Solution.pdf

ECM3MEC Quiz 2 Solution.pdf - LA TRDBE uuuuuuuu Student lD...

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Unformatted text preview: % LA TRDBE :- uuuuuuuu Student lD number: MODELLING WITH ECONOMETRICS ECMSMEC QUIZ 2 -—_—__ 1. Which of the following correctly identifies a difference between cross—sectional data and time series data? (0.5 marks) a. Cross-sectional data is based on temporal ordering, whereas time series data is not. .Time series data is based on temporal ordering, whereas cross-sectional data is .._______, not. c. Cross-sectional data consists of only qualitative variables, where-as time series data consists of only quantitative variables. d. Time series data consists of only qualitative variables, whereas cross-sectional data does not include qualitative variables. 2. A process is stationary if: (0.5 marks) a. any collection of random variables in a sequence is taken and shifted ahead by h time periods; the joint probability distribution changes. .my collection of random variables in a sequence is taken and shifted ahead by h time periods, the 'oint robabilit distribution remains unchanged. 0. there is serial correlation between the error terms of successive time periods and the explanatory variables and the error terms have positive covariance. d. there is no serial correlation between the error terms of successive time periods and the explanatory variables and the error terms have positive covariance. 3. With base year 1990, the index of industrial production for the year 1929 is __1LZ. What will be the value of the index in 1999, if the base year is changed to 1982 and the index measured 96 in 1982? (0.5 marks) a. 112.24 b 116.66 :_ %%x 100 c 85.71 d. 92.09 4. Unit root processes, such as a random walk (with or without drift), are said to _—.'—'-—_-——_—. be: (0.5 marks) .integrated of order one. :2 IC 1) b. integrated of order mm. c. sequentially exogenous. d. asymptotically uncorrelated. ECMBMEC Semester 1 2017 £2 LMfififiE Student ID number: 5. Using the data in the VOLATRAW file provided with the textbook, the regression equation below was estimated. The variable rsp500 is the monthly return on the Wrepresemed as an annual rate. (This includes price changes as well as dividends.) The variable 1'3 is the return on three- mflfland 21:12 is the percentage change in industrial production; these are also specified as annual rates. T 6 standard errors are reported in the parentheses rsp500t = 18.84 + 0.036 pcipi— 1. 36 1'31. + ut .— (3.27) (0.129) (0.54) n=557 R2=0.012 a. Interpret the signs and magnitudes of the coefficients. (0.5 marks) «.11»— Q. 031; I1MMM-M.M11MMM1__ 11111-1111---.9MM/ Jung—___ ..._.—_ ___” ________ ”.115. :.--.::.L.315.-_'.---l-fiz--13111111414.1o.-__1é1_-£112~1&n-gn--11111M3m1mM T- bi ([9 M11111 _____ 115.1121.--La-------19.3.G..Z--_.QE111911<1.---11.1-1114.---mmiég :11wa 911-16.111.6‘Eav1mé19 _____________________________________________________ b. Which of the variables are statistically significant? (0. 5 marks) No.12. ______ E ca.___<tfi1.___§1§mc (M.-m--1211u13+--{1151---te. 11-10.---Q111‘J. 1%an 1-91: :MMM‘COMOT ....................................................... 3%.--- ___tffih.mb1flrfi.-;-_-________-.6._.:_ Q. Z?5.------:1;_:-_JltfidflL-fi._.__.=_—_:=_—.:... '— 23‘; ‘ 0 126 . CNEUAQ Hanan. L5 i C56 0.1 5‘& <43hld’lmncg [9142.115 PL Lt «9111111111223 .9451 c. Do your findings from part ([1) imply that the return on the S&P 500 IS qth'fi {éfifipredictablfl Explain. (0.5 marks) ----.“1.C?.‘.t_-__£1.c_11111_1 _____ 1i _S.--1£[email protected]¢M§.__119.. ______ 1.1 f1141___cg.n__¢m pm (19.113 “rifle.--114.--Lo:1c.119.11----1n.c;::11:1 ..... maneubcz..-111:;[email protected]:.--_-701 -11: ohm . (U -----M9.».---19.-:1n911-1111.---jEM.___.menrmui--1;3¢21. - m _____ 120 11me— "1-111121111111113... ........ QfiégizclMigEmf¢fic-mi1C-LELRMM_§_ 91.241190- 51“” ......... meflauied- ECM3MEC Semester 1 2017 5% LATROBE Student ID number: 6. The variable hrwage is the average hourly wage in the US. economy, and outphr is output per hour. Accordingly, the growth in hourly wage and in output per hour can be represented as the change in the natural log values: ghrirvage = Alog(hmvage) and gozrgohr =A log(outphr). Consider the following estimated equation: Pi ta ghrwage {2—0.0} 0+0. 728 gozuphrr+0.458 goutjmrw L fl) (0005) (0.167) (0.166) This allows an increase in productivity growth to have both a current and lagged effect on wage growth. a. Is the lagged value of goutphr statistically significant as per reported standard error in the parentheses? [sfiWhat does it indicate? (1 mark) armogapio _ ________i’:::f__?:iti: _____ Gathctaamflmaébmffid __;__-Y_L::__l':'__‘:_.lt+_-9§..:_.52,).__J25.- ...... 'fiaxlmtic. _-____lz_3:é___t__-_flfu_ afltdfiL _--le_:§£'il21fi-i‘l9;ii2__é£_[é_aé mm" 1. 66 _~____C:K:Ff ___________ @fi ______ QJHLL _ C} Id: of (“flab-f ”Man i fig Mama: 3 L I; 1;; :7 ----- a "777—77 ------------------------------ ____"fills._Lflam__first"Jaéeratmnragmtnyfa__Hn-_c_tzf_"Eliza 0qu (2mm fated mafiafimifia’i‘ifinl‘aq allege-z--.z{i___fi?roaéur;flurfy ymwflt hm cc C'ijflidi‘c'anf effictf on Way; 5' cal/t4) , Huge, Way, amufli all/M b. If [31 + [1’2 = 1, a permanent increase in produc ivity growth is fully passed on in {sfilhigher wage growth after one year. Test H0: 31 + 32 = 1 against the two- sided alternative. Please show all the possible steps and the new equation structure. (0.5 marks) (Hint: Remember, one way to do this is to write the equation so that 6 = [31 + 32 appears directly in the model, as an example of re—parameterization.) a3C)-;iti-1EL.__;)___1gi_;;___9__:_fi3h ________________________________________________ e.-- --CL--_.24:.EL4§1{IQD.__[__’D____E_€.§;an£JA.L-_-%_i’L£MJfl ._.;___f;0_t__a3c=_atf4[t + [31601; 10:30 . 62) ....... 99 -u LtellatnééuLfimtfhf 17-1-; cmtplhf -lu.r-fm--£LLzl__ffl_grQ1<LEW) £7Ami’7fc’fl -_-_L2=l____da_,__atcfla_£éza _____ gamma..- %_:&,_m‘éccigi__tawilfm (50% ‘6 7a--- a:___heuzae_;ia_c_r_aaia-mitu__MAL", _______________________________________ _____ 3 cufphgmw I: W” +2451" +£0.- 0 Ed Wm Hi: 9 13' ECM3MEC Semester 1 2017 cm 6'77 l dicta/fie." c??? / I ...
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