Econometrics Exam 2

Econometrics Exam 2 - Kate Brown Dr. Cuellar Econometrics...

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon

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

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Kate Brown Dr. Cuellar Econometrics Exam #2 1. lnPrice=B0+B1X1+B2X2+B3X3+Ui lnPrice is the average annual growth rates of all wines in the sample B0 is the base category Cabernet Sauvignon B1 is the change in price / change by 1year B2 is the difference in price between Cabernet Sauvignon and Pinot B3 is the difference in price between Cabernet Sauvignon and Merlot X1 effect of year on price X2 is the dummy for Pinot Noir; 1if Pinot, 0 if Merlot or Cabernet X3 is the dummy for Merlot; 1 if Merlot, 0 for the other varietals Ui is the error term 2. reg lnprice pinot merlot year Source | SS df MS -------------+-----------------------------Model | 431.474382 3 143.824794 Residual | 8816.74607 23400 .37678402 -------------+-----------------------------Total | 9248.22045 23403 .395172433 Number of obs = 23404 F( 3, 23400) = 381.72 Prob > F = 0.0000 R-squared = 0.0467 Adj R-squared = 0.0465 Root MSE = .61383 -----------------------------------------------------------------------------lnprice | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------pinot | .2029481 .0110605 18.35 0.000 .1812689 .2246273 merlot | -.1657477 .0089392 -18.54 0.000 -.1832691 -.1482263 year | -.0144551 .0014813 -9.76 0.000 -.0173586 -.0115516 _cons | 31.56131 2.96895 10.63 0.000 25.74198 37.38065 -----------------------------------------------------------------------------. predict pinhat if pinot==1 (option xb assumed; fitted values) (18963 missing values generated) . predict mehat if merlot ==1 (option xb assumed; fitted values) (14572 missing values generated) . predict cabhat if merlot==0 & pinot==0 (option xb assumed; fitted values) (13273 missing values generated) 3. lnPrice=B0+B1X1+B2X2+B3X3+Ui lnPrice is the average annual growth rates of all wines in the sample B0 is the base category Cabernet Sauvignon B1 is the change in price / change by 1year B2 is the difference in price between Cabernet Sauvignon and Pinot B3 is the difference in price between Cabernet Sauvignon and Merlot X1 effect of year on price X2 is the dummy for Pinot Noir; 1if Pinot, 0 if Merlot or Cabernet X3 is the dummy for Merlot; 1 if Merlot, 0 for the other varietals Ui is the error term reg lnprice year Source | SS df MS -------------+-----------------------------Model | 21.3593328 1 21.3593328 Residual | 9226.86112 23402 .394276605 -------------+-----------------------------Total | 9248.22045 23403 .395172433 Number of obs = 23404 F( 1, 23402) = 54.17 Prob > F = 0.0000 R-squared = 0.0023 Adj R-squared = 0.0023 Root MSE = .62791 -----------------------------------------------------------------------------lnprice | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------year | -.0111262 .0015117 -7.36 0.000 -.0140891 -.0081632 _cons | 24.8652 3.029743 8.21 0.000 18.9267 30.80369 -----------------------------------------------------------------------------Orange=pinot green= cab red = merlot 6 0 1998 2 4 2000 2002 year lnprice Fitted values 2004 2006 Fitted values Fitted values 2008 . reg lnprice year Sidewaysmovie after Source | SS df MS Number of obs = 23404 -------------+-----------------------------F( 3, 23400) = 21.53 Model | 25.4599465 3 8.48664882 Prob > F = 0.0000 Residual | 9222.76051 23400 .394135064 R-squared = 0.0028 -------------+-----------------------------Adj R-squared = 0.0026 Total | 9248.22045 23403 .395172433 Root MSE = .6278 -----------------------------------------------------------------------------lnprice | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------year | -.0175806 .0034824 -5.05 0.000 -.0244063 -.0107548 Sidewaysmo~e | -40.43697 12.54097 -3.22 0.001 -65.0181 -15.85584 after | .0201681 .0062547 3.22 0.001 .0079086 .0324277 _cons | 37.78585 6.971282 5.42 0.000 24.12168 51.45002 -----------------------------------------------------------------------------. predict afterhat if after==1 afterhat already defined r(110); . predict afterhat1 if after==1 afterhat1 already defined r(110); . predict afterhatnow if after==1 (option xb assumed; fitted values) (23404 missing values generated) . predict afterhatnow if after ==0 afterhatnow already defined r(110); . predict afterhatnow1 if after ==0 (option xb assumed; fitted values) (12111 missing values generated) . scatter lnprice afterhatnow afterhatnow1 year, c(. l l l) s(Oh i i i) . tab Sidewaysmovieyear Sidewaysmovieyear | Freq. Percent ------------+----------------------------------0 | 11,293 48.25 48.25 2005 | 2,940 12.56 60.81 2006 | 3,119 13.33 74.14 2007 | 3,205 13.69 87.84 2008 | 2,847 12.16 100.00 ------------+----------------------------------Total | 23,404 100.00 . tab Sidewaysmovie Sidewaysmov | ie | Freq. Percent Cum. ------------+----------------------------------0 | 11,293 48.25 48.25 1 | 12,111 51.75 100.00 ------------+----------------------------------Total | 23,404 100.00 . save "C:\Users\Kate\Documents\Sideways.dta", replace file C:\Users\Kate\Documents\Sideways.dta saved Cum. ...
View Full Document

Page1 / 6

Econometrics Exam 2 - Kate Brown Dr. Cuellar Econometrics...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online