Hi i am running a tobit regresison for data across 2 years 2007-2008:
My variables include 10 log price categories for alcohol types on trade and off trade : l_p_wine_on l_p_wine_off etc
I also have a log income variable : log_income
My dependent variables are the expenditure shares of the alcohol type expenditure divided by total expenditure : e.g exp_share_wine_on expshare_wine_off
I am looking at the price elasticities of demand and the cross price elasticities of demand vary across each alcohol type and vary across socio-economic groups, government regions and gender
My prices for alcohols are constant throughout the year (i am using the average year price) however they vary between years
here is a data-ex for some of my variables
I am then running a tobit regression as follows:
I have censored the data at zero since some households report no consumption of alcohol
However my results are as follows:
Q1. Why are my price variables other than the price of the same dependent variable omitted (as i am trying to work out cross price elasticity of demand) i understand its due to collinearity but what is causing this and how do i overcome it?
Q2. Why is the year dummy variable omitted?
I am following a model which has done close to the same thing and they didn't have this problem
Thanks so much in advance
My variables include 10 log price categories for alcohol types on trade and off trade : l_p_wine_on l_p_wine_off etc
I also have a log income variable : log_income
My dependent variables are the expenditure shares of the alcohol type expenditure divided by total expenditure : e.g exp_share_wine_on expshare_wine_off
I am looking at the price elasticities of demand and the cross price elasticities of demand vary across each alcohol type and vary across socio-economic groups, government regions and gender
My prices for alcohols are constant throughout the year (i am using the average year price) however they vary between years
here is a data-ex for some of my variables
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float(l_p_wine_on l_p_beer_on l_p_spirits_on l_p_wine_off l_p_spirits_off > l_p_beer_off expshare_wine_on expshare_beer_off logincome) byte(socio_group > gor) int year byte sexhrp .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 4.433789 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .01142119 > 5.898746 3 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 4.898213 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .0550356 .015000853 > 6.399842 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .0016348386 > 5.584012 3 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .015073973 > 7.020905 2 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.225338 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 4.911331 3 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.219934 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.533279 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 4.2492094 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .00609936 > 6.168564 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 4.835587 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.940566 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .006249688 > 5.331317 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.786775 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .003858888 > 7.201894 2 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.476967 2 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.009435 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .010382757 > 6.377679 3 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.982862 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.11283 2 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .0023888294 > 6.279646 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .001813489 > 6.294915 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .005435922 > 6.704463 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.747566 3 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .005957043 > 6.11456 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .014408222 .016718158 > 6.605068 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .018981254 0 > 6.019785 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.088818 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 4.779476 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .008590408 > 6.514719 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .005628793 .018012136 > 6.960443 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .005657709 > 6.424075 3 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.920457 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .008473212 0 > 6.898255 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .02177079 > 5.623837 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 4.812526 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.182973 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 4.514611 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.109314 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.362559 3 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.30903 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.26414 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 4.3593974 3 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .017695729 0 > 4.77104 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.069847 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .01336186 > 6.690271 2 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.80408 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.628306 5 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .016276948 > 6.522627 5 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.519619 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .035966147 > 6.422951 3 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.557673 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.602438 2 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.402017 3 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .0029820926 0 > 7.401286 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .015186014 > 7.176426 2 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.746554 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.474176 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .01607261 > 6.874416 3 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .010095213 > 6.662046 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .024986824 .0423164 > 6.069906 3 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .001250104 0 > 7.438652 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .03693495 0 > 7.021414 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .02268917 > 6.5658 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.958667 2 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.192117 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .0016070686 0 > 5.815264 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.34921 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.279 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.516609 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.554516 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.347932 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .01880577 0 > 5.93925 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .07133046 > 6.985651 2 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .005728897 .005415315 > 7.12227 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .01053234 .021376746 > 6.8088 2 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .0019776237 0 > 6.519822 3 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.490757 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.787439 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.457868 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.921752 2 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 7.098411 2 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 4.400603 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .013181653 0 > 6.857086 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .003744323 0 > 6.710182 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.136498 6 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .02200635 0 > 7.438652 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .0019496685 0 > 6.911319 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .0006786454 > 6.854755 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 7.438652 2 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 6.609726 1 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 .004789272 0 > 6.868133 3 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.182907 4 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.823194 1 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 4.812526 6 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .04808098 > 5.530222 4 2 2007 2 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 0 > 5.793585 3 2 2007 1 .60158 -.010050327 .662688 -.9416085 -.967584 -.967584 0 .11235794 > 6.436151 1 2 2007 2 end label values gor gor label def gor 2 "north west", modify label values sexhrp sexhrp label def sexhrp 1 "male", modify label def sexhrp 2 "female", modify
Code:
tobit expshare_wine_on l_p_wine_on l_p_beer_on l_p_cider_on l_p_spirits_on l_p_alcopops_on l_p_wine_off l_p_beer_off l_p_spirits_off l_p_cider_off l_p_alcopops_off logincome i.socio_group i.gor i.year i.sexhrp , ll(0)
However my results are as follows:
Code:
. tobit expshare_wine_on l_p_wine_on l_p_beer_on l_p_cider_on l_p_spirits_on l_p_alcopops_on l_p_wine_off > l_p_beer_off l_p_spirits_off l_p_cider_off l_p_alcopops_off logincome i.socio_group i.gor i.year i.sex > hrp , ll(0) note: l_p_beer_on omitted because of collinearity note: l_p_cider_on omitted because of collinearity note: l_p_spirits_on omitted because of collinearity note: l_p_alcopops_on omitted because of collinearity note: l_p_wine_off omitted because of collinearity note: l_p_beer_off omitted because of collinearity note: l_p_spirits_off omitted because of collinearity note: l_p_cider_off omitted because of collinearity note: l_p_alcopops_off omitted because of collinearity note: 2008.year omitted because of collinearity Refining starting values: Grid node 0: log likelihood = -5976.9775 Fitting full model: Iteration 0: log likelihood = -5976.9775 Iteration 1: log likelihood = -640.92644 Iteration 2: log likelihood = 1103.185 Iteration 3: log likelihood = 1808.8673 Iteration 4: log likelihood = 1909.2432 Iteration 5: log likelihood = 1910.562 Iteration 6: log likelihood = 1910.5625 Iteration 7: log likelihood = 1910.5625 Tobit regression Number of obs = 11,962 Uncensored = 2,312 Limits: lower = 0 Left-censored = 9,650 upper = +inf Right-censored = 0 LR chi2(14) = 927.97 Prob > chi2 = 0.0000 Log likelihood = 1910.5625 Pseudo R2 = -0.3207 ------------------------------------------------------------------------------------------- expshare_wine_on | Coef. Std. Err. t P>|t| [95% Conf. Interval] --------------------------+---------------------------------------------------------------- l_p_wine_on | -.028118 .0162136 -1.73 0.083 -.0598992 .0036632 l_p_beer_on | 0 (omitted) l_p_cider_on | 0 (omitted) l_p_spirits_on | 0 (omitted) l_p_alcopops_on | 0 (omitted) l_p_wine_off | 0 (omitted) l_p_beer_off | 0 (omitted) l_p_spirits_off | 0 (omitted) l_p_cider_off | 0 (omitted) l_p_alcopops_off | 0 (omitted) logincome | .0125922 .0006706 18.78 0.000 .0112778 .0139066 | socio_group | 2 | .0014811 .0010997 1.35 0.178 -.0006745 .0036368 3 | -.0078991 .0012672 -6.23 0.000 -.0103829 -.0054152 4 | -.0098159 .003836 -2.56 0.011 -.0173351 -.0022968 5 | .0065436 .0035439 1.85 0.065 -.0004031 .0134903 6 | -.0027114 .0010429 -2.60 0.009 -.0047556 -.0006672 | gor | north west | -.0004291 .0014892 -0.29 0.773 -.0033481 .00249 merseyside | -.0009579 .0014654 -0.65 0.513 -.0038303 .0019145 yorkshire and the humber | .0017352 .0014609 1.19 0.235 -.0011284 .0045987 east midlands | -.0012567 .0021903 -0.57 0.566 -.00555 .0030366 west midlands | -.0024181 .0018331 -1.32 0.187 -.0060112 .0011751 eastern | -.0016493 .0017609 -0.94 0.349 -.005101 .0018023 | year | 2008 | 0 (omitted) | sexhrp | female | .0011694 .000803 1.46 0.145 -.0004046 .0027435 _cons | -.0853166 .0110156 -7.75 0.000 -.106909 -.0637242 --------------------------+---------------------------------------------------------------- var(e.expshare_wine_on)| .0007865 .0000268 .0007357 .0008408 ------------------------------------------------------------------------------------------
Q2. Why is the year dummy variable omitted?
I am following a model which has done close to the same thing and they didn't have this problem
Thanks so much in advance
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