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| From | "Salikhov, Talgat" <talgat.salikhov11@imperial.ac.uk> |
| To | "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |
| Subject | RE: st: Dummy Variable Trap, urgent |
| Date | Fri, 6 Sep 2013 16:47:46 +0000 |
Steve, Thanks a lot for the comment. Talgat ________________________________________ From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Stephen Martin [stephen.martin@york.ac.uk] Sent: 06 September 2013 16:09 To: statalist@hsphsun2.harvard.edu Subject: Re: st: Dummy Variable Trap, urgent Hi Talgat, I tried to >>>> check the data set for potential collinearity with other variables >>>> (possible 'doubling' of fixed effects) and was deleting one variable by >>>> one from the model, but did not help. That's because the problem is not with your urban/rural dummies and other covariates, but between your urban/rural dummies and the fixed effects. I think that your problem is that there is no within county variation in your urban/rural dummies (and it is this within variation that is used by the FE estimator). You might want to try re-estimating your model using OLS but adding dummies for the counties. Then try re-estimating this adding your urban/rural dummies. I'd guess that the latter will be kicked out and this will illustrate that the problem is with your county and urban/rural dummies. Hope this helps. Steve On 06/09/2013, Maarten Buis <maartenlbuis@gmail.com> wrote: > I mean what I said, I cannot be clearer than that. > > On Fri, Sep 6, 2013 at 4:10 PM, Salikhov, Talgat > <talgat.salikhov11@imperial.ac.uk> wrote: >> Maarten, >> >> Do you mean completely removing these dummy variable from the model? Or >> just substituting all binary values by zero? >> >> Thanks >> >> Regards, >> Talgat >> ________________________________________ >> From: owner-statalist@hsphsun2.harvard.edu >> [owner-statalist@hsphsun2.harvard.edu] on behalf of Maarten Buis >> [maartenlbuis@gmail.com] >> Sent: 06 September 2013 15:00 >> To: statalist@hsphsun2.harvard.edu >> Subject: Re: st: Dummy Variable Trap, urgent >> >> If you have fixed effects, you automatically include area effects. So, >> dropping the variables does not mean you no longer adjust for them. >> So, just drop them, and you will adjust for region through the fixed >> effects. >> >> -- Maarten >> >> >> On Fri, Sep 6, 2013 at 3:53 PM, Salikhov, Talgat >> <talgat.salikhov11@imperial.ac.uk> wrote: >>> Maarten, >>> >>> Thank you for the comment. My theory strongly recommends including area >>> type variables so I cannot refuse them. If possible could you recommend >>> any tricks you've mentioned to be able to estimate correctly? >>> >>> Thanks for the advise as well. >>> >>> Regards, >>> Talgat >>> ________________________________________ >>> From: owner-statalist@hsphsun2.harvard.edu >>> [owner-statalist@hsphsun2.harvard.edu] on behalf of Maarten Buis >>> [maartenlbuis@gmail.com] >>> Sent: 06 September 2013 14:38 >>> To: statalist@hsphsun2.harvard.edu >>> Subject: Re: st: Dummy Variable Trap, urgent >>> >>> Your units appear to be counties, so it is no surprise that the region >>> is constant. With a fixed effects you filter out anything that is >>> constant within the unit, regardless of whether it is observed or not. >>> This is why fixed effects models are so popular. But it also means >>> that you cannot estimate (at least not without resorting to some >>> tricks) the effects of variables that are fixed within units, as you >>> noticed. If you added region because you wanted to adjust your >>> estimates for it, but are not substantively interested in it, then you >>> can just leave those variables out and let the fixed effects take care >>> of the adjusting (as it is already doing automatically). If you are >>> substantively interested in these region effects you will need to do >>> something else. >>> >>> -- Maarten >>> >>> Ps. I realize that your plea for urgency is sincere, but I would >>> strongly advise against it. To quote the Statalist FAQ: >>> "Urgency is only your concern. Pleas of urgency, desperation, and the >>> like are widely deprecated by Statalist members. What is urgent for >>> you is unlikely to translate into urgency for other members of the >>> list. It is simplest and best to just ask your question directly." >>> >>> On Fri, Sep 6, 2013 at 3:27 PM, Salikhov, Talgat >>> <talgat.salikhov11@imperial.ac.uk> wrote: >>>> Dear All, >>>> >>>> I need some help with my model. This is for my dissertation, which is >>>> due very soon, so I would greatly appreciate if anyone could reply >>>> asap. >>>> >>>> Context: >>>> >>>> I have a panel data. I am using STATA 11. I am running an employment >>>> model with fixed effects. I have a number of various variables to >>>> control for various factors and area characteristics, including 6 >>>> categorical dummy variables to control for the area type according to >>>> the level of urbanization. I also introduced year 7 dummies. >>>> >>>> Problem: >>>> >>>> When I run the model with fixed effects specification the coefficients >>>> for area type dummies get omitted because of collinearity. I realise >>>> this is a dummy variable trap. Note that coefficients for year dummies >>>> are estimated withoutany problems (with one year omitted as expected). >>>> However even though I drop one of the area type dummy variables, it >>>> still shows as omitted. I don't know what is the problem. I tried to >>>> check the data set for potential collinearity with other variables >>>> (possible 'doubling' of fixed effects) and was deleting one variable by >>>> one from the model, but did not help. >>>> >>>> The list of my commands with the results is as follows: >>>> >>>> clear >>>> >>>> . *(26 variables, 1050 observations pasted into data editor) >>>> >>>> . summarize output >>>> >>>> Variable | Obs Mean Std. Dev. Min Max >>>> -------------+-------------------------------------------------------- >>>> output | 1050 6636.304 5337.696 1497 33800.75 >>>> >>>> . sum >>>> >>>> Variable | Obs Mean Std. Dev. Min Max >>>> -------------+-------------------------------------------------------- >>>> country | 0 >>>> year | 1050 2007 2.000953 2004 2010 >>>> region | 0 >>>> uacountyname | 0 >>>> tot_emp | 1050 150599.6 117570 12800 632963 >>>> -------------+-------------------------------------------------------- >>>> priv_tot_emp | 1050 120319.6 96998.76 10000 541053 >>>> road_density | 1050 6.399432 4.106369 .1963984 18.20378 >>>> output | 1050 6636.304 5337.696 1497 33800.75 >>>> propertytax | 1050 1068.173 197.2193 552.77 1782.42 >>>> expen_edu | 1050 28032.39 23728.64 0 207409 >>>> -------------+-------------------------------------------------------- >>>> expen_pss | 1050 2208.517 2677.185 0 30889 >>>> expen_transp | 1050 16999.31 15949.01 23 132291 >>>> expen_hous~g | 1050 23994.46 38973.29 0 612599 >>>> expen_libc~r | 1050 2840.263 4349.239 -30 54474 >>>> unemployment | 1050 6.361048 2.550556 1.2 16.3 >>>> -------------+-------------------------------------------------------- >>>> nvq3 | 1050 47.42981 7.48426 27.6 71.9 >>>> nvq4 | 1050 27.90019 8.680573 12 63.6 >>>> under16 | 1050 64679.43 48988.63 7100 274400 >>>> over65 | 1050 54866 47158.07 6400 258500 >>>> benefitcla~s | 1050 29992.23 20152.8 1230 147780 >>>> -------------+-------------------------------------------------------- >>>> majorurban | 1050 .38 .4856177 0 1 >>>> largeurban | 1050 .1733333 .3787156 0 1 >>>> otherurban | 1050 .1466667 .3539419 0 1 >>>> significan~l | 1050 .1466667 .3539419 0 1 >>>> rural50 | 1050 .1266667 .3327577 0 1 >>>> -------------+-------------------------------------------------------- >>>> rural80 | 1050 .0266667 .1611841 0 1 >>>> >>>> . replace expen_edu = 1 if (expen_edu == 0) >>>> (20 real changes made) >>>> >>>> . replace expen_pss = 1 if (expen_pss == 0) >>>> (20 real changes made) >>>> >>>> . replace expen_transp = 1 if (expen_transp == 0) >>>> (0 real changes made) >>>> >>>> . replace expen_housing = 1 if (expen_housing == 0) >>>> (187 real changes made) >>>> >>>> . replace expen_libculher = 1 if (expen_libculher == 0) >>>> (19 real changes made) >>>> >>>> . tabulate year, gen(y) >>>> >>>> year | Freq. Percent Cum. >>>> ------------+----------------------------------- >>>> 2004 | 150 14.29 14.29 >>>> 2005 | 150 14.29 28.57 >>>> 2006 | 150 14.29 42.86 >>>> 2007 | 150 14.29 57.14 >>>> 2008 | 150 14.29 71.43 >>>> 2009 | 150 14.29 85.71 >>>> 2010 | 150 14.29 100.00 >>>> ------------+----------------------------------- >>>> Total | 1,050 100.00 >>>> >>>> . gen log_priv_tot_emp = ln(priv_tot_emp) >>>> >>>> . gen log_road_density = ln(road_density) >>>> >>>> . gen log_output = ln(output) >>>> >>>> . gen log_propertytax = ln(propertytax) >>>> >>>> . gen log_expen_edu = ln(expen_edu) >>>> >>>> . gen log_expen_pss = ln(expen_pss) >>>> >>>> . gen log_expen_transp = ln(expen_transp) >>>> >>>> . gen log_expen_housing = ln(expen_housing) >>>> >>>> . gen log_expen_libculher = ln(expen_libculher) >>>> (1 missing value generated) >>>> >>>> . replace log_expen_libculher = 0 if (log_expen_libculher == .) >>>> (1 real change made) >>>> >>>> . gen log_under16 = ln(under16) >>>> >>>> . gen log_over65 = ln(over65) >>>> >>>> . gen log_benefitclaimants = ln(benefitclaimants) >>>> >>>> . bysort uacountyname : gen county_id = _n == 1 >>>> >>>> . replace county_id = sum(county_id) >>>> (1049 real changes made) >>>> >>>> . xtset county_id year, yearly >>>> panel variable: county_id (strongly balanced) >>>> time variable: year, 2004 to 2010 >>>> delta: 1 year >>>> >>>> . xtreg log_priv_tot_emp log_road_density log_output log_propertytax >>>> log_expen_edu log_expen_pss log_expen_transp log_exp >>>>> en_housing log_expen_libculher unemployment nvq3 nvq4 log_under16 >>>>> log_over65 log_benefitclaimants majorurban largeurban >>>>> otherurban significantrural rural50 rural80 y1 y2 y3 y4 y5 y6 y7, fe >>>>> vce(robust) >>>> note: majorurban omitted because of collinearity >>>> note: largeurban omitted because of collinearity >>>> note: otherurban omitted because of collinearity >>>> note: significantrural omitted because of collinearity >>>> note: rural50 omitted because of collinearity >>>> note: rural80 omitted because of collinearity >>>> note: y1 omitted because of collinearity >>>> >>>> Fixed-effects (within) regression Number of obs = >>>> 1050 >>>> Group variable: county_id Number of groups = >>>> 150 >>>> >>>> R-sq: within = 0.3287 Obs per group: min = >>>> 7 >>>> between = 0.7905 avg = >>>> 7.0 >>>> overall = 0.7888 max = >>>> 7 >>>> >>>> F(20,149) = >>>> 11.83 >>>> corr(u_i, Xb) = 0.5373 Prob > F = >>>> 0.0000 >>>> >>>> (Std. Err. adjusted for 150 clusters in >>>> county_id) >>>> ------------------------------------------------------------------------------ >>>> | Robust >>>> log_priv_t~p | Coef. Std. Err. t P>|t| [95% Conf. >>>> Interval] >>>> -------------+---------------------------------------------------------------- >>>> log_road_d~y | -.0308976 .0190012 -1.63 0.106 -.0684442 >>>> .006649 >>>> log_output | .2778278 .0626751 4.43 0.000 .1539811 >>>> .4016746 >>>> log_proper~x | -.2212403 .1382738 -1.60 0.112 -.4944711 >>>> .0519905 >>>> log_expen_~u | .0002099 .0024071 0.09 0.931 -.0045467 >>>> .0049664 >>>> log_expen_~s | -.0005283 .002037 -0.26 0.796 -.0045535 >>>> .0034969 >>>> log_expen_~p | -.0037324 .0038912 -0.96 0.339 -.0114214 >>>> .0039566 >>>> log_expen_~g | .0048323 .0014797 3.27 0.001 .0019083 >>>> .0077563 >>>> log_expen_~r | -.0013391 .0009824 -1.36 0.175 -.0032803 >>>> .0006021 >>>> unemployment | -.003091 .0012582 -2.46 0.015 -.0055772 >>>> -.0006049 >>>> nvq3 | .0002088 .0009244 0.23 0.822 -.0016178 >>>> .0020353 >>>> nvq4 | .0006803 .0011502 0.59 0.555 -.0015925 >>>> .002953 >>>> log_under16 | .0060861 .0982632 0.06 0.951 -.1880832 >>>> .2002555 >>>> log_over65 | .4174694 .0960725 4.35 0.000 .2276289 >>>> .6073099 >>>> log_benefi~s | -.0309202 .0774981 -0.40 0.690 -.1840575 >>>> .1222171 >>>> majorurban | (omitted) >>>> largeurban | (omitted) >>>> otherurban | (omitted) >>>> significan~l | (omitted) >>>> rural50 | (omitted) >>>> rural80 | (omitted) >>>> y1 | (omitted) >>>> y2 | .0067527 .0071768 0.94 0.348 -.0074287 >>>> .0209341 >>>> y3 | .012156 .0135523 0.90 0.371 -.0146236 >>>> .0389355 >>>> y4 | .0122614 .0202253 0.61 0.545 -.0277041 >>>> .0522268 >>>> y5 | .0143446 .0249928 0.57 0.567 -.0350415 >>>> .0637307 >>>> y6 | .0523563 .028217 1.86 0.066 -.0034009 >>>> .1081135 >>>> y7 | .0167271 .0312961 0.53 0.594 -.0451144 >>>> .0785686 >>>> _cons | 6.445186 1.679938 3.84 0.000 3.125607 >>>> 9.764764 >>>> -------------+---------------------------------------------------------------- >>>> sigma_u | .36708293 >>>> sigma_e | .03455236 >>>> rho | .99121795 (fraction of variance due to u_i) >>>> ------------------------------------------------------------------------------ >>>> Sincerely, >>>> Talgat >>>> * >>>> * For searches and help try: >>>> * http://www.stata.com/help.cgi?search >>>> * http://www.stata.com/support/faqs/resources/statalist-faq/ >>>> * http://www.ats.ucla.edu/stat/stata/ >>> >>> >>> >>> -- >>> --------------------------------- >>> Maarten L. Buis >>> WZB >>> Reichpietschufer 50 >>> 10785 Berlin >>> Germany >>> >>> http://www.maartenbuis.nl >>> --------------------------------- >>> >>> * >>> * For searches and help try: >>> * http://www.stata.com/help.cgi?search >>> * http://www.stata.com/support/faqs/resources/statalist-faq/ >>> * http://www.ats.ucla.edu/stat/stata/ >>> >>> * >>> * For searches and help try: >>> * http://www.stata.com/help.cgi?search >>> * http://www.stata.com/support/faqs/resources/statalist-faq/ >>> * http://www.ats.ucla.edu/stat/stata/ >> >> >> >> -- >> --------------------------------- >> Maarten L. Buis >> WZB >> Reichpietschufer 50 >> 10785 Berlin >> Germany >> >> http://www.maartenbuis.nl >> --------------------------------- >> >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/faqs/resources/statalist-faq/ >> * http://www.ats.ucla.edu/stat/stata/ >> >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/faqs/resources/statalist-faq/ >> * http://www.ats.ucla.edu/stat/stata/ > > > > -- > --------------------------------- > Maarten L. Buis > WZB > Reichpietschufer 50 > 10785 Berlin > Germany > > http://www.maartenbuis.nl > --------------------------------- > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/