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From |
"Dalhia Mani" <dalhia.mani@gmail.com> |

To |
"Rodrigo Alfaro A." <ralfaro@bcentral.cl> |

Subject |
Re: st: RE: SUR correction for autocorrelation |

Date |
Tue, 7 Oct 2008 21:27:54 -0500 |

Rodrigo, Thanks I just saw your response. This is helpful. I will try this. dalhia On Tue, Oct 7, 2008 at 4:07 PM, Rodrigo Alfaro A. <ralfaro@bcentral.cl> wrote: > > /// > > Dalhia, > > Your regression with clusters seems similat to FE+regression. I found > that F is missing under your setting, but you could deal with that using > -xtreg, fe cluster()- instead of -reg, cluster()-. The following example > shows you my point using the dataset available in Stata. Regression with > -reg- has the same coefficients than -xtreg-, but the latter computes > the standard errors under the assumption of FE at the cluster level. > Note that standard errors are different because degree of freedom are > computed dropping the id's dummies. > > I hope this helps you, > Rodrigo. > > **** Begin example > sysuse auto, clear > reg price mpg turn foreign, cluster(foreign) > xtreg price mpg turn, fe cluster(foreign) i(foreign) > **** End example > > > -----Mensaje original----- > De: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] En nombre de Benjamin > Villena Roldan > Enviado el: Martes, 07 de Octubre de 2008 03:41 p.m. > Para: statalist@hsphsun2.harvard.edu > Asunto: RE: st: RE: SUR correction for autocorrelation > > Hey, > Generally speaking -some other people could disagree- I think that > including cluster dummy regressors should be enough to adjust your > variance estimates. > It looks weird to put these regressors and a -cluster- option all > together (When I wrote you I did not know you are planning to add > cluster dummies as regressors as well!!). > Besides, I am not sure if your variable group assigns a code for every > cluster firm. Your output says that you have defined 344 clusters of > firms to compute variances, which seems way too much for a total sample > size of 1644. That seems to be the reason you don't get a well-computed > F test. > I am not aware of what your ultimate goal is but it seems to me that > your estimates look very noisy. You got very wide confidence intervals, > which means very little can be said about the behavior your dependent > variable. > Bottom line: if you are confident on your specification, that is, > cluster dummies are included as regressors, don't use the cluster option > (which anyway seems to be wrongly implemented) and only use -robust- > alone. If you have heteroskedastic and/or autocorrelated errors AND your > model is correctly specified, your OLS estimates are still consistent > and unbiased. > The robust option -White's correction- would provide you're a consistent > estimator for the variance under heteroskedasticity of unknown form. > > Finally, You can also be benefited from the collective wisdom of the > Stata list users.I hope someone else could give you some advice here. > > Hope it helps, > > Benjamin > > -----Mensaje original----- > De: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] En nombre de Dalhia Mani > Enviado el: Tuesday, October 07, 2008 2:53 PM > Para: statalist@hsphsun2.harvard.edu > Asunto: Re: st: RE: SUR correction for autocorrelation > > Benjamin, > > I ran the regression "y x1 x2, robust cluster(gr)" to control for > clustering among firms in my dataset, and I get the results I was > expecting. However, when I run this regression, the F statistics are > missing, and I am concerned that this means something is wrong with the > regression. > > All other aspects of the stata output look fine. However, the F > statistic is blank. See output below. > > Any suggestions will be much appreciated. > > thanks > dalhia > > > regress roa_dec2001 firm2 firm3 firm4 firm5 firm6 firm7 cluster1 > cluster1_1 cluster2 cluster3 cluster4 cluster5 clus >> ter6 cluster7 cluster8 cluster9 cluster10 overlappingcluster degree > aggregate_constraint prod_count age sum_knowhow ln_ >> totassets2001, robust cluster(group) > > Linear regression Number of obs = > 1644 > F( 16, 343) = > . > Prob > F = > . > R-squared = > 0.0143 > Root MSE = > .73013 > > (Std. Err. adjusted for 344 clusters in > group) > ------------------------------------------------------------------------ > ---- > -- > | Robust > roa_dec2001 | Coef. Std. Err. t P>|t| [95% Conf. > Interval] > -------------+---------------------------------------------------------- > -------------+---- > -- > firm2 | .0494928 .0840523 0.59 0.556 -.1158301 > .2148157 > firm3 | .0348837 .051861 0.67 0.502 -.0671218 > .1368893 > firm4 | -.0089329 .0124503 -0.72 0.474 -.0334215 > .0155557 > firm5 | -.0252334 .0236897 -1.07 0.288 -.0718287 > .0213619 > firm6 | -.0568828 .0481064 -1.18 0.238 -.1515034 > .0377378 > firm7 | -.0219176 .0636692 -0.34 0.731 -.1471488 > .1033137 > cluster1 | .0612633 .0790641 0.77 0.439 -.0942482 > .2167747 > cluster1_1 | -.000552 .0453069 -0.01 0.990 -.0896663 > .0885624 > cluster2 | -.1239266 .107221 -1.16 0.249 -.33482 > .0869668 > cluster3 | -.0797388 .0524637 -1.52 0.129 -.1829299 > .0234522 > cluster4 | -.0382077 .0255735 -1.49 0.136 -.0885083 > .012093 > cluster5 | -.0474023 .0399954 -1.19 0.237 -.1260693 > .0312648 > cluster6 | .0263318 .0509641 0.52 0.606 -.0739098 > .1265734 > cluster7 | -.0835975 .0745768 -1.12 0.263 -.2302829 > .0630878 > cluster8 | -.0926067 .092746 -1.00 0.319 -.2750292 > .0898159 > cluster9 | -.0182355 .0544206 -0.34 0.738 -.1252756 > .0888045 > cluster10 | -.0697966 .0707843 -0.99 0.325 -.2090227 > .0694294 > overlappin~r | -.0924298 .0661568 -1.40 0.163 -.222554 > .0376943 > degree | .0022567 .0019908 1.13 0.258 -.0016589 > .0061724 > aggregate_~t | -.1004189 .1637774 -0.61 0.540 -.4225534 > .2217155 > prod_count | .0034202 .0022548 1.52 0.130 -.0010148 > .0078553 > age | -.0008939 .000299 -2.99 0.003 -.001482 > -.0003059 > sum_knowhow | -.0011635 .0015493 -0.75 0.453 -.0042109 > .0018838 > ln_tota~2001 | .0470392 .0388523 1.21 0.227 -.0293796 > .1234581 > _cons | -.1456748 .0676188 -2.15 0.032 -.2786745 > -.0126752 > ------------------------------------------------------------------------ > ---- > -- > > > > > On Sun, Oct 5, 2008 at 12:31 AM, Benjamin Villena Roldan > <bvillena@troi.cc.rochester.edu> wrote: >> Hi Dalhia, >> I reread my answers. I'm sorry I wasn't that clear. You could >> implement robust cluster variance estimators in simple regressions >> -regress y x1 x2, robust cluster(gr)- The option -cluster- is >> available in most estimations commands in Stata. > The >> cluster variable -gr- defines groups of firms of a similar > characteristic. >> The errors are correlated among the cluster, but they are independent > across >> clusters. See Wooldridge "Econometric Analysis of Cross-Sectional and > Panel >> Data" page 134 for further details. >> Prais-Weinstein is not a good idea because you have to define that >> some firms are "closer"to other in some sense. The correlation among >> errors decays in the "distance" among firms. Unless you have a good >> reason your observations need to be ordered in a very specific way, >> this procedure doesn't make sense. In time series for instance, the >> time order among observations is obvious, so in that case it will > work. >> Regarding to the second point, your system is clearly a simultaneous >> equation model, since you have endogenous variables on the right-hand >> side of equations 2 and 3. You need to check your equations are >> identified > before >> running any procedure. This is very important. Any introductory >> textbook > in >> econometrics such as Gujarati or Maddala, could help you to address >> this question. >> After you have done this, you'll need instrumental variables to >> estimate > the >> structural form. Then you have several estimators you could choose >> from two-stage least square (2SLS), three-stage least square (3SLS), >> and even > the >> Limited-information-Max-Likelihood (LIML) which is preferable when you > have >> "weak instruments". You could implement these estimators using the >> Stata commands -ivreg- or -ivreg2-. >> >> I hope I was clearer than I was before. >> >> Best, >> >> Benjamin >> >> -----Mensaje original----- >> De: owner-statalist@hsphsun2.harvard.edu >> [mailto:owner-statalist@hsphsun2.harvard.edu] En nombre de Dalhia Mani > >> Enviado el: Saturday, October 04, 2008 11:43 PM >> Para: statalist@hsphsun2.harvard.edu >> Asunto: Re: st: RE: SUR correction for autocorrelation >> >> Benjamin, >> >> Thanks. This is useful but I'd like to clarify and make sure I >> understand your comments. I apologize if these are really elementary >> questions. I'm still trying to figure this stuff out. >> >> 1) The data is not time series. I have data about firms for a single >> time period, and I also have data indicating which firms belong to >> which cluster of firms. From what I understand, you are suggesting >> that I should use the Prais-Winston command in stata, with a "cluster" >> option?? Did I understand you correctly? >> >> 2) I am a bit confused about whether I should be using SUR or >> simultaneous equations. >> My three equations look something like this: >> y1=f(X+Z)+e_1 >> y2=g(X+Z)+y1+e_2 >> y3=g(X+Z)+y1+y2+e_3 >> This set of equations looks like simultaneous equations since >> independent variables in one equation become dependent variables in >> another. However, I also seem to remember that in cases where all >> equations use the same exogenous variables (X and Z), I should be >> using SUR. >> >> Thanks for your suggestions and help. I appreciate it. >> dalhia >> >> >> On Sat, Oct 4, 2008 at 4:41 PM, Benjamin Villena Roldan >> <bvillena@troi.cc.rochester.edu> wrote: >>> Hi >>> You don't mention whether your data is a cross-section or a panel. >>> That's quite important. >>> Regarding (1) you have clusters of firms, so you can estimate your >> variance >>> matrix using the option cluster. Cochrane-Orcutt works for time >>> autocorrelation, so you need a measure of "proximity"among the firms >> within >>> a cluster. I think you don't have that. In time-series, that measure >>> is given by the time dimension. >>> Regarding (2), I think you need to think carefully about the >>> relationship among your equations. Are you estimating structural or >>> reduced forms equations? For instance, is accounting performance >>> included as a > regressor >>> in your stock-market valuation?. If it is you have a simultaneous > equation >>> model. If it's not, you're estimating a reduced form, but you have to > >>> be very careful about the interpretation of your marginal effects. >>> >>> I hope it helps >>> >>> Benjamin >>> >>> -----Mensaje original----- >>> De: owner-statalist@hsphsun2.harvard.edu >>> [mailto:owner-statalist@hsphsun2.harvard.edu] En nombre de Dalhia >>> Mani Enviado el: Saturday, October 04, 2008 4:48 PM >>> Para: statalist@hsphsun2.harvard.edu >>> Asunto: st: SUR correction for autocorrelation >>> >>> hi, >>> >>> I have a set of equations that specify the relationship between a set > >>> of independent variables and outcome variables - survival, >>> stockmarket and accounting performance. I have two questions that I >>> would appreciate your help with. >>> >>> 1) The data is at the firm level. Some of the firms belong to >>> clusters of firms, and hence I expect autocorrelation in the >>> residuals when I run each equation separately. Therefore, I plan to >>> use the the Prais-Winston command, specifying the Cochran-Orcutt >>> option in stata to correct for autocorrelation when running each > equation separately. >>> I think this approach is correct, however I am not a 100% sure, and >>> will appreciate it if you think otherwise and can correct me. >>> >>> 2) I also need to use a simultaneous unrelated regression (SUR) model > >>> since it is possible that the set of equations are related (e.g. >>> survival might be related to performance). How do I correct for >>> autocorrelation for the SUR model in stata? >>> >>> Any suggestions and advice will be much appreciated. >>> >>> thanks >>> dalhia >>> * >>> * For searches and help try: >>> * http://www.stata.com/help.cgi?search >>> * http://www.stata.com/support/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/statalist/faq >>> * http://www.ats.ucla.edu/stat/stata/ >>> >> >> >> >> -- >> Dalhia Mani >> Department of Sociology >> University of Minnesota >> Office: 1052 Social Sciences >> 267 19th Avenue South, Minneapolis >> MN 55455 >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/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/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ >> > > > > -- > Dalhia Mani > Department of Sociology > University of Minnesota > Office: 1052 Social Sciences > 267 19th Avenue South, Minneapolis > MN 55455 > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/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/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > > ******************************************************************************** > ADVERTENCIA: La información contenida en esta transmisión, y en cualquier archivo adjunto, está sujeta a reserva legal conforme a la normativa aplicable al Banco Central de Chile, y no puede ser usada o difundida por personas distintas de su o sus destinatarios. Si usted ha recibido esta transmisión por error, por favor notifique inmediatamente al remitente respondiendo por este mismo medio y elimínela de su sistema. > El Banco Central de Chile no se hará responsable de la exactitud y veracidad de la información contenida en este mensaje, así como de su modificación, copia, divulgación o reenvío, total o parcial. Su uso no autorizado puede ser sancionado de conformidad con las leyes chilenas. > El Banco Central de Chile transmite sus decisiones a través de comunicados oficiales, los que pone a disposición del público en su página de Internet: www.bcentral.cl > > > DISCLAIMER: The information contained in this email or any attached file, is subject to legal privilege pursuant to the laws and regulations applicable to the Central Bank of Chile , and may not be used or disseminated by any person other than its intended recipients. If you have received this transmission in error, please notify the sender immediately by reply to this email address and delete it from your system. > The Central Bank of Chile shall not be liable for the accuracy or authenticity of the contents of this message, whether amended, copied, forwarded or disclosed in any form, in whole or in part. Please note that unauthorized use may be penalized in conformity with the Chilean law. > The Central Bank of Chile communicates its decisions by official releases, and > makes them available to the public in its WebPages: www.bcentral.cl > -- Dalhia Mani Department of Sociology University of Minnesota Office: 1052 Social Sciences 267 19th Avenue South, Minneapolis MN 55455 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: SUR correction for autocorrelation***From:*"Dalhia Mani" <dalhia.mani@gmail.com>

**st: RE: SUR correction for autocorrelation***From:*"Benjamin Villena Roldan" <bvillena@troi.cc.rochester.edu>

**Re: st: RE: SUR correction for autocorrelation***From:*"Dalhia Mani" <dalhia.mani@gmail.com>

**RE: st: RE: SUR correction for autocorrelation***From:*"Benjamin Villena Roldan" <bvillena@troi.cc.rochester.edu>

**Re: st: RE: SUR correction for autocorrelation***From:*"Dalhia Mani" <dalhia.mani@gmail.com>

**RE: st: RE: SUR correction for autocorrelation***From:*"Benjamin Villena Roldan" <bvillena@troi.cc.rochester.edu>

**RE: st: RE: SUR correction for autocorrelation***From:*"Rodrigo Alfaro A." <ralfaro@bcentral.cl>

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