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Re: st: inconsistent results for two-dimensions fixed effects regressions using xtreg reg areg ivreg2
From
Nahla Betelmal <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: st: inconsistent results for two-dimensions fixed effects regressions using xtreg reg areg ivreg2
Date
Thu, 15 Aug 2013 10:36:24 +0100
Hi Mike,
Thanks for the reply and help again. Yes, I understand that at
industry level I got many firms observations, so I dent set the panel
at industry. I tried to get around that by having a group variable for
industry-year , so each firm-year observation will belong only to one
industry-year identifier. I got the idea from this thread
http://www.talkstats.com/showthread.php/26900-how-can-I-include-two-fixed-effect-in-one-model
I modified the variable to be industry-year instead (because as you
said a firm can not belong to different industries). So, to use
xtcommand, I set the panel at the group variable industry-year only
and then included the year dummy in the regression ( I hope this does
not contradict sound way of thinking)
egen industry_year= group(industry year)
xtset industry_year
xtreg IV DV, fe
and the result were the same as using
reg IV DV i.year i.industry,
areg IV DV i.year , absorb (industry)
Regarding your kind comment about fixed effect and clustering and the
same level ( say firm level as widely done). In the finance field,
papers seem to include both year and firm dummies as well as
clustering for firms.
The most used wordings are " reported t-statistics adjusted for
heteroskedasticity (White, 1980) and firm-level clustering" and "The
t-values are computed using Roger’s robust standard errors correcting
for firm clusters" with dummies for years and dummies for firms
already included in the regression.
for example see table 4 in this paper :
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1030359
Also, I found this thread which hints that fixed effect and cluster at
the panel variable is widely reported.
http://www.stata.com/statalist/archive/2006-09/msg00782.html
However, I totally got your point that the fixed effects will control
for correlation of error-terms within clusters. I wonder why large
number of finance papers published in well-known journals use firm
cluster as well!
Thanks a million, and I am sure that other users appreciate your
previous detailed explanation and help.
many thanks
Nahla
On 14 August 2013 19:57, Michael Barker <[email protected]> wrote:
> Hi Nahla,
>
> You are having trouble with the xtcommands, because you're not really
> doing a panel-data analysis. Panel data implies one observation per
> unit per year. You are analyzing this data using industry and year, so
> you have many observations (firms) per unit (industry) per year. That
> is why you got the error about repeated time values within panel. Your
> data may actually be panel data, at the firm-year level, but you are
> analyzing it as clustered data, not panel data.
>
> You said that you were using two-dimension fixed-effects, so I would
> keep industry and year as separate groups of dummy variables, rather
> than creating a single interaction. The results may come out the same,
> I'm not sure about that, but I think it is easier conceptually.
>
> Lastly, if you are including fixed effects at the industry-level, you
> don't have to compute clustered standard errors at the same level. You
> can just use the typical robust standard error estimator. The cluster
> fixed effects will control for correlation of error-terms within
> clusters.
>
> So I think you should use one of these two commands:
> reg IV DV i.year i.industry, robust
> areg IV DV i.year , absorb (industry) robust
>
> About the ivreg2 command, it is used for instrumental variables. I
> think your "IV" stands for independent variable, not instrumental
> variable, so it is not relevant to your topic. ivreg2 will not help
> you with a fixed-effects analysis.
>
> Mike
>
>
>
> On Wed, Aug 14, 2013 at 10:51 AM, Nahla Betelmal <[email protected]> wrote:
>> Thank you so much Mike, your detailed comments are great help. I do
>> appreciate it.
>>
>> As I am looking for industry year fixed effects rather than firm year,
>> I tried to set the panel accordingly, but did not work due to repeated
>> time values within panel.
>>
>> So, this time I grouped based on industry-year (thanks to ur note
>> about no repeated firms in different industries). I hope this time I
>> did it in the right way. Kindly let me know please. I got identical
>> coefficients for IV.
>>
>> Also, could you please explain more your comment about ivreg2 or give
>> and an example how to execute it right to get fixed effects please.
>>
>> the command are :
>> 1) egen industry_year= group(industry year) then xtset industry_year
>> then xtreg IV DV, fe vce (cluster industry)
>> 2) xi: reg IV DV i.year i.industry
>> 3)areg IV DV , absorb ( industry_year ) cluster (industry)
>>
>> In the first command , I could not put i.year as it is omitted because
>> of collinearity.
>> In the second, I could not apply cluster (industry) option as F-test
>> became missing.
>> The third command gave almost identical results to the previous two
>> with and without the cluster option. However, it gave slightly
>> different R-Square 0.645 than that of regress 0.621. Is this OK or
>> they should be identical.
>>
>>
>>
>> egen industry_year= group(industry year)
>> xtset industry_year
>> xtreg DV IV, fe vce (cluster industry )
>>
>> Fixed-effects (within) regression Number of obs = 23830
>> Group variable: industry_year Number of groups = 1179
>>
>> R-sq: within = 0.5516 Obs per group: min = 1
>> between = 0.5262 avg = 20.2
>> overall = 0.4955 max = 155
>>
>> F(1,57) = 2233.13
>> corr(u_i, Xb) = -0.1260 Prob > F = 0.0000
>>
>> (Std. Err. adjusted for 58 clusters in industry)
>> ------------------------------------------------------------------------------
>> | Robust
>> DV| Coef. Std. Err. t P>|t| [95% Conf. Interval]
>> -------------+----------------------------------------------------------------
>> IV| .4393407 .009297 47.26 0.000 .4207237 .4579577
>> _cons | 5.675498 .0673395 84.28 0.000 5.540653 5.810343
>> -------------+----------------------------------------------------------------
>> sigma_u | .40739078
>> sigma_e | .58512671
>> rho | .32648834 (fraction of variance due to u_i)
>> ------------------------------------------------------------------------------
>>
>>
>>
>> Also I tried
>> xi: reg DV IV i.year i.industry
>>
>> without a cluster(industry) as F-test became missing
>>
>> IV= .4397811 and SE= .0026298
>> If I run xtreg without the cluster option, I get the same SE= .0026322
>>
>> the output is too long
>>
>> In addition
>> areg DV IV, absorb ( industry_year ) cluster (industry)
>>
>> Linear regression, absorbing indicators Number of obs = 23830
>> F( 1, 57) = 2122.73
>> Prob > F = 0.0000
>> R-squared = 0.6458
>> Adj R-squared = 0.6274
>> Root MSE = 0.5851
>>
>> (Std. Err. adjusted for 58 clusters in industry)
>> ------------------------------------------------------------------------------
>> | Robust
>> DV | Coef. Std. Err. t P>|t| [95% Conf. Interval]
>> -------------+----------------------------------------------------------------
>> IV | .4393407 .0095357 46.07 0.000 .4202457
>> .4584357
>> _cons | 5.675498 .0690685 82.17 0.000 5.537191 5.813805
>> -------------+----------------------------------------------------------------
>> industry_year | absorbed (1179 categories)
>>
>>
>> Many thanks again
>>
>> Nahla
>>
>>
>> On 14 August 2013 14:29, Michael Barker <[email protected]> wrote:
>>> Hi Nahla,
>>>
>>> You are actually running several different models there. I'll describe
>>> each one below, so you can see how they differ:
>>>
>>>> 1) xi: reg DV IV i.year, vce (cluster industry)
>>> - Year fixed effects only.
>>> - Include one dummy variable for each year:
>>>
>>>> 2) xtset firm year then xtreg DV IV i.year, fe vce (cluster industry)
>>> - Year and firm fixed effects
>>> - Equivalent to including one dummy for each year and one dummy for each firm.
>>> - xtreg includes fixed effects for the panel variable, firm and you
>>> include year dummies manually
>>>
>>>> 3) egen industry_firm= group (industry firm) then xtset industry_firm year then xtreg DV IV i.year, fe vce (cluster industry)
>>> - year and industry-firm level fixed effects
>>> - equivalent to including one dummy for each year and one dummy for
>>> each industry-firm combination
>>> - apparently no firm is in multiple industries, so this regression is
>>> equivalent to regression 2.
>>>
>>>> 4) tsset industry_firm year then ivreg2 DV IV,cluster ( industry_firm year)
>>> - No fixed effects
>>> - You didn't specify the endogenous / IV variables, so this is just a
>>> regular regression with clustered standard errors
>>> - This is equivalent to "reg DV IV,cluster ( industry_firm year)"
>>>
>>>> 5) areg DV IV, absorb ( year ) cluster (industry)
>>> - Year fixed effects only
>>> - Equivalent to regression 1, without reporting year coefficients
>>> - Notice that the coefficient and standard error estimates are the
>>> same as the first regression.
>>>>
>>>
>>> If you want firm and year fixed effects, I would use regression 2. If
>>> you want to see equivalent results with alternative regressions, try
>>> these:
>>> xi: reg DV IV i.year i.firm, vce (cluster industry)
>>> areg DV IV i.year, absorb (firm) cluster (industry)
>>>
>>> The first suggestion might not run, since you will have to include
>>> many dummy variables for all of your firms. You may exceed the maximum
>>> number of variables allowed, depending on your version of Stata.
>>>
>>> Mike
>>>
>>>
>>>
>>>
>>> On Wed, Aug 14, 2013 at 8:22 AM, Nahla Betelmal <[email protected]> wrote:
>>>> Hi Statalist,
>>>>
>>>> I have a panel data of firms and years, however, I would like to
>>>> perform industry and year fixed effect regression. using different
>>>> approaches, I got different IV coefficient and standard error,
>>>> although it should be identical if I am doing it right. I would highly
>>>> appreciate it if someone kindly explain what I am doing wrong and what
>>>> is the right way to get industry and year fixed effects.
>>>>
>>>> the commands I used are:
>>>>
>>>> 1) xi: reg DV IV i.year, vce (cluster industry)
>>>>
>>>> 2) xtset firm year then xtreg DV IV i.year, fe vce (cluster industry)
>>>>
>>>> 3) egen industry_firm= group (industry firm) then xtset industry_firm
>>>> year then xtreg DV IV i.year, fe vce (cluster industry)
>>>>
>>>> 4) tsset industry_firm year then ivreg2 DV IV,cluster ( industry_firm year)
>>>>
>>>> 5) areg DV IV, absorb ( year ) cluster (industry)
>>>>
>>>>
>>>> under reg command: IV = 0.386 with SE= 0.022
>>>> under xtreg command with firm year panel set: IV = .418 with SE= .0241
>>>> under xtreg command with industry-firm year panel set: IV = .418 with SE= .024
>>>> under ivreg2 command: IV = .410 with SE= .007
>>>> under areg command: IV = 0.386 with SE= 0.022
>>>>
>>>>
>>>> . xi: reg DV IV i.year, vce (cluster industry)
>>>> i.year _Iyear_1992-2012 (naturally coded; _Iyear_1992 omitted)
>>>>
>>>> Linear regression Number of obs = 23830
>>>> F( 21, 57) = 768.66
>>>> Prob > F = 0.0000
>>>> R-squared = 0.5461
>>>> Root MSE = .6461
>>>>
>>>> (Std. Err. adjusted for 58 clusters in industry)
>>>> -------------------------------------------------------------------------------
>>>> | Robust
>>>> DV | Coef. Std. Err. t P>|t| [95%
>>>> Conf. Interval]
>>>> --------------+----------------------------------------------------------------
>>>> IV | .3869693 .0225831 17.14 0.000
>>>> .3417475 .4321911
>>>> _Iyear_1993 | .150389 .0239546 6.28 0.000 .1024208 .1983573
>>>> _Iyear_1994 | .2857099 .0271864 10.51 0.000 .2312702 .3401496
>>>> _Iyear_1995 | .2927993 .0307951 9.51 0.000 .2311331 .3544654
>>>> _Iyear_1996 | .4353512 .0304859 14.28 0.000 .3743044 .4963981
>>>> _Iyear_1997 | .5286896 .0292151 18.10 0.000 .4701874 .5871917
>>>> _Iyear_1998 | .5852497 .0337522 17.34 0.000 .5176621 .6528374
>>>> _Iyear_1999 | .6969439 .0523892 13.30 0.000 .5920364 .8018514
>>>> _Iyear_2000 | .8019949 .0666928 12.03 0.000 .6684448 .9355449
>>>> _Iyear_2001 | .7710818 .0486744 15.84 0.000 .673613 .8685507
>>>> _Iyear_2002 | .6978223 .0325914 21.41 0.000 .6325592 .7630854
>>>> _Iyear_2003 | .6427671 .0347611 18.49 0.000 .5731593 .712375
>>>> _Iyear_2004 | .7757021 .0394535 19.66 0.000 .6966978 .8547064
>>>> _Iyear_2005 | .7806429 .0418054 18.67 0.000 .6969291 .8643566
>>>> _Iyear_2006 | .7746051 .0462916 16.73 0.000 .6819076 .8673025
>>>> _Iyear_2007 | .7758041 .0484202 16.02 0.000 .6788444 .8727639
>>>> _Iyear_2008 | .7734638 .0508533 15.21 0.000 .6716317 .8752958
>>>> _Iyear_2009 | .7319797 .0564072 12.98 0.000 .6190263 .8449332
>>>> _Iyear_2010 | .8741285 .0506573 17.26 0.000 .772689 .975568
>>>> _Iyear_2011 | .8889354 .0532101 16.71 0.000 .782384 .9954869
>>>> _Iyear_2012 | .8979328 .0565989 15.86 0.000 .7845956 1.01127
>>>> _cons | 5.403047 .1238831 43.61 0.000 5.154975 5.651118
>>>> -------------------------------------------------------------------------------
>>>>
>>>>
>>>>
>>>>
>>>> xtset firm year
>>>> panel variable: firm (unbalanced)
>>>> time variable: year, 1992 to 2012, but with gaps
>>>> delta: 1 unit
>>>>
>>>> . xtreg DV IV i.year, fe vce (cluster industry)
>>>>
>>>> Fixed-effects (within) regression Number of obs = 23830
>>>> Group variable: firm Number of groups = 2312
>>>>
>>>> R-sq: within = 0.4113 Obs per group: min = 1
>>>> between = 0.5998 avg = 10.3
>>>> overall = 0.5456 max = 21
>>>>
>>>> F(21,57) = 463.93
>>>> corr(u_i, Xb) = -0.0970 Prob > F = 0.0000
>>>>
>>>> (Std. Err. adjusted for 58 clusters in industry)
>>>> ------------------------------------------------------------------------------
>>>> | Robust
>>>> DV | Coef. Std. Err. t P>|t| [95% Conf. Interval]
>>>> -------------+----------------------------------------------------------------
>>>> IV | .4183645 .0241281 17.34 0.000 .3700488
>>>> .4666802
>>>> |
>>>> year |
>>>> 1993 | .1560772 .0200202 7.80 0.000 .1159874 .196167
>>>> 1994 | .2929982 .0224807 13.03 0.000 .2479813 .3380151
>>>> 1995 | .3019359 .0268163 11.26 0.000 .2482373 .3556345
>>>> 1996 | .4272691 .0264501 16.15 0.000 .3743038 .4802344
>>>> 1997 | .5209287 .0266063 19.58 0.000 .4676506 .5742069
>>>> 1998 | .5877827 .0276877 21.23 0.000 .5323391 .6432264
>>>> 1999 | .6989115 .0427304 16.36 0.000 .6133453 .7844777
>>>> 2000 | .7988406 .0477286 16.74 0.000 .7032657 .8944154
>>>> 2001 | .7589164 .0375573 20.21 0.000 .6837091 .8341236
>>>> 2002 | .687617 .034973 19.66 0.000 .6175848 .7576492
>>>> 2003 | .6310008 .0488884 12.91 0.000 .5331035 .7288982
>>>> 2004 | .7611996 .0507837 14.99 0.000 .659507 .8628921
>>>> 2005 | .7687923 .0552525 13.91 0.000 .6581511 .8794336
>>>> 2006 | .7524079 .0609127 12.35 0.000 .6304324 .8743834
>>>> 2007 | .7519399 .0642041 11.71 0.000 .6233734 .8805064
>>>> 2008 | .750493 .0684401 10.97 0.000 .6134441 .887542
>>>> 2009 | .7118027 .067056 10.62 0.000 .5775254 .8460799
>>>> 2010 | .8504969 .0632919 13.44 0.000 .7237569 .9772368
>>>> 2011 | .8674839 .0664437 13.06 0.000 .7344328 1.000535
>>>> 2012 | .863437 .0733127 11.78 0.000 .7166308 1.010243
>>>> |
>>>> _cons | 5.18669 .152373 34.04 0.000 4.881568 5.491812
>>>> -------------+----------------------------------------------------------------
>>>> sigma_u | .4935113
>>>> sigma_e | .47151369
>>>> rho | .52278302 (fraction of variance due to u_i)
>>>> ------------------------------------------------------------------------------
>>>>
>>>>
>>>> . egen industry_firm= group (industry firm)
>>>>
>>>> . xtset industry_firm year
>>>> panel variable: industry_firm (unbalanced)
>>>> time variable: year, 1992 to 2012, but with gaps
>>>> delta: 1 unit
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> . xtreg DV IV i.year, fe vce (cluster industry)
>>>>
>>>> Fixed-effects (within) regression Number of obs = 23830
>>>> Group variable: industry_firm Number of groups = 2312
>>>>
>>>> R-sq: within = 0.4113 Obs per group: min = 1
>>>> between = 0.5998 avg = 10.3
>>>> overall = 0.5456 max = 21
>>>>
>>>> F(21,57) = 463.93
>>>> corr(u_i, Xb) = -0.0970 Prob > F = 0.0000
>>>>
>>>> (Std. Err. adjusted for 58 clusters in industry)
>>>> ------------------------------------------------------------------------------
>>>> | Robust
>>>> DV | Coef. Std. Err. t P>|t| [95% Conf. Interval]
>>>> -------------+----------------------------------------------------------------
>>>> IV | .4183645 .0241281 17.34 0.000 .3700488 .4666802
>>>> |
>>>> year |
>>>> 1993 | .1560772 .0200202 7.80 0.000 .1159874 .196167
>>>> 1994 | .2929982 .0224807 13.03 0.000 .2479813 .3380151
>>>> 1995 | .3019359 .0268163 11.26 0.000 .2482373 .3556345
>>>> 1996 | .4272691 .0264501 16.15 0.000 .3743038 .4802344
>>>> 1997 | .5209287 .0266063 19.58 0.000 .4676506 .5742069
>>>> 1998 | .5877827 .0276877 21.23 0.000 .5323391 .6432264
>>>> 1999 | .6989115 .0427304 16.36 0.000 .6133453 .7844777
>>>> 2000 | .7988406 .0477286 16.74 0.000 .7032657 .8944154
>>>> 2001 | .7589164 .0375573 20.21 0.000 .6837091 .8341236
>>>> 2002 | .687617 .034973 19.66 0.000 .6175848 .7576492
>>>> 2003 | .6310008 .0488884 12.91 0.000 .5331035 .7288982
>>>> 2004 | .7611996 .0507837 14.99 0.000 .659507 .8628921
>>>> 2005 | .7687923 .0552525 13.91 0.000 .6581511 .8794336
>>>> 2006 | .7524079 .0609127 12.35 0.000 .6304324 .8743834
>>>> 2007 | .7519399 .0642041 11.71 0.000 .6233734 .8805064
>>>> 2008 | .750493 .0684401 10.97 0.000 .6134441 .887542
>>>> 2009 | .7118027 .067056 10.62 0.000 .5775254 .8460799
>>>> 2010 | .8504969 .0632919 13.44 0.000 .7237569 .9772368
>>>> 2011 | .8674839 .0664437 13.06 0.000 .7344328 1.000535
>>>> 2012 | .863437 .0733127 11.78 0.000 .7166308 1.010243
>>>> |
>>>> _cons | 5.18669 .152373 34.04 0.000 4.881568 5.491812
>>>> -------------+----------------------------------------------------------------
>>>> sigma_u | .4935113
>>>> sigma_e | .47151369
>>>> rho | .52278302 (fraction of variance due to u_i)
>>>> ------------------------------------------------------------------------------
>>>>
>>>>
>>>>
>>>> ivreg2 DV IV,cluster ( industry_firm year)
>>>>
>>>> OLS estimation
>>>> --------------
>>>>
>>>> Estimates efficient for homoskedasticity only
>>>> Statistics robust to heteroskedasticity and clustering on
>>>> industry_firm and fyear2
>>>>
>>>> Number of clusters (industry_firm) = 2312 Number of obs = 23830
>>>> Number of clusters (fyear2) = 21 F( 1, 20) = 2849.29
>>>> Prob > F = 0.0000
>>>> Total (centered) SS = 21896.66904 Centered R2 = 0.4955
>>>> Total (uncentered) SS = 1891568.745 Uncentered R2 = 0.9942
>>>> Residual SS = 11046.6797 Root MSE = .6809
>>>>
>>>> ------------------------------------------------------------------------------
>>>> | Robust
>>>> DV | Coef. Std. Err. z P>|z| [95% Conf. Interval]
>>>> -------------+----------------------------------------------------------------
>>>> IV | .410624 .0075071 54.70 0.000 .3959104 .4253377
>>>> _cons | 5.883496 .0562149 104.66 0.000 5.773317 5.993675
>>>> ------------------------------------------------------------------------------
>>>> Included instruments: IV
>>>>
>>>>
>>>>
>>>>
>>>> areg DV IV, absorb ( year ) cluster (industry)
>>>>
>>>> Linear regression, absorbing indicators Number of obs = 23830
>>>> F( 1, 57) = 293.62
>>>> Prob > F = 0.0000
>>>> R-squared = 0.5461
>>>> Adj R-squared = 0.5457
>>>> Root MSE = 0.6461
>>>>
>>>> (Std. Err. adjusted for 58 clusters in twodigit)
>>>> ------------------------------------------------------------------------------
>>>> | Robust
>>>> DV | Coef. Std. Err. t P>|t| [95% Conf. Interval]
>>>> -------------+----------------------------------------------------------------
>>>> IV | .3869693 .0225831 17.14 0.000 .3417475 .4321911
>>>> _cons | 6.05483 .1337655 45.26 0.000 5.786969 6.322691
>>>> -------------+----------------------------------------------------------------
>>>> year | absorbed (21 categories)
>>>>
>>>>
>>>>
>>>> Many thanks in advance,
>>>>
>>>> Nahla Betelmal
>>>> *
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>>> *
>>> * For searches and help try:
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>> *
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