To: statalist@hsphsun2.harvard.edu (1998). Subject: Re: st: Robust Standard Errors in Paneldatasets Googling around I Estimating robust standard errors in Stata 4.0 resulted in . It's still not clear to me when it's ok to deal with time effects (cross-sectional correlation) parametrically by including a time indicator variable and just correct for time-series dependence (serial correlation) with cluster (firm) or vice versa. * http://www.stata.com/help.cgi?search I have a panel data set in R (time and cross section) and would like to compute standard errors that are clustered by two dimensions, because my residuals are correlated both ways. College Station, TX: Stata press.' > package first) xtscc depvar varlist, fe On his web page he states: "The routines currently written into Stata allow you to cluster by only one variable (e.g. Subject The Accounting Review 85 (2):483. Papers by Thompson (2006) and by Cameron, Gelbach and Miller (2006) suggest a way to account for multiple dimensions at the same time. I present a new Stata program, xtscc, that estimates pooled or-dinary least-squares/weighted least-squares regression and xed-e ects (within) regression models with Driscoll and Kraay (Review of … Josh: I assume that you are using a version of Stata where the "robust" option is the same as "cluster(id)," where "id" is the cross section identifier. None of what you have found deals with clustering. Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches. Review of Financial Studies 22 (1), Petersen provides a link to his web site (http://www.kellogg.northwestern.edu/faculty/petersen/htm/papers/se/se_programming.htm). * http://www.ats.ucla.edu/stat/stata/, http://www.kellogg.northwestern.edu/faculty/petersen/htm/papers/se/se_programming.htm, mailto:owner-statalist@hsphsun2.harvard.edu, http://www.stata-press.com/books/isp.html, http://www.stata-press.com/books/imeus.html, http://www.stata.com/support/statalist/faq, Re: st: Robust Standard Errors in Paneldatasets, st: xtreg fe - using specific types of w/i group variation (HELP PLEASE), re: RE: st: Robust Standard Errors in Paneldatasets. See their papers and mine for more details and caveats. <> You can browse but not post. > Driscoll, J., & Kraay, A. my problem is this: I get NA where I should get some values in the computation of robust standard errors.. vce(oim) uses the observed information matrix (OIM); see[R] ml. The conventional heteroskedasticity-robust (HR) variance matrix estimator for cross-sectional regression (with or without a degrees of freedom adjustment), applied to the fixed effects estimator for panel data with serially uncorrelated errors, is inconsistent if the number of time periods T is fixed (and greater than two) as the number of entities n increases. Clustering allows you to deal with arbitrary heteroskedasticity across panels and aribtrary correlation within panels. * > Options SE/Robust vce(oim) is usually the default for models fit using maximum likelihood. > * found as well     A Miller (2006) and Thompson (2009). (See Carlo's advice on showing Stata output; it is much easier to receive advice on this board. Robust Standard Errors for Panel Regressions with Cross-Sectional Dependence. > > I found various methods to apply the regression in Stata and hope you can help me to choose the right one, if any. Also see Gow, I., G. Ormazabal, and D. Taylor. The importance of using cluster-robust variance estimators (i.e., “clustered standard errors”) in panel models is now widely recognized. That is why the standard errors are so important: they are crucial in determining how many stars your table gets. > In contrary to other statistical software, such as R for instance, it is rather simple to calculate robust standard errors in STATA. And like in any business, in economics, the stars matter a lot. Here I'm specifically trying to figure out how to obtain the robust standard errors (shown in square brackets) in column (2). In the new implementation of the robust estimate of variance, Stata is now scaling the estimated variance matrix in order to make it less biased. Daniel Hoechle Department of Finance University of Basel Basel, Switzerland daniel.hoechle@unibas.ch: Abstract. CONSISTENT COVARIANCE MATRIX ESTIMATION WITH SPATIALLY DEPENDENT PANEL DATA. xtreg without the fe option is random effects, which is a.s. inappropriate for finance panels. ”Robust” standard errors is a technique to obtain unbiased standard errors of OLS coefficients under heteroscedasticity. The Stata regress command includes a robust option for estimating the standard errors using the Huber-White sandwich estimators. The second data set is the Mitchell Petersen’s test data for two-way clustering. * http://www.ats.ucla.edu/stat/stata/ Share. To When I followed up on Kit's -xtivreg2_ suggestion, I found the following in the help for ivreg2: The standard errors determine how accurate is your estimation. See the discussion of clustering in Baum/Schaffer/Stillman papers, Stata Journal 3(1) [free] and 7(4), available in preprint form on my website. The conventional heteroskedasticity‐robust (HR) variance matrix estimator for cross‐sectional regression (with or without a degrees‐of‐freedom adjustment), applied to the fixed‐effects estimator for panel data with serially uncorrelated errors, is inconsistent if the number of time periods T is fixed (and greater than 2) as the number of entities n increases. Kit Baum | Boston College Economics & DIW Berlin | http://ideas.repec.org/e/pba1.html From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Christopher Baum But now I am having some trouble. > Petersen, M. A. Amy Dunbar In Stata's notation, the composite error term is u (i) + e (i,t). An Introduction to Stata Programming | http://www.stata-press.com/books/isp.html Two-way clustering also allows you to consider common effects hitting all firms at the same point in time. However, the standard errors generated assume the errors are iid. I recently read these two articles about robust standard errors in panel datasets and can't figure out which SE I should use and in case of the clustered method how to apply this to Stata. I have written a Stata ado file to implement this estimation procedure." Login or. I'm trying to figure out the commands necessary to replicate the following table in Stata. The help file above indicates that -ivreg2- does deal with both, so I'm not sure what I am missing. Robust standard errors for panel regressions with cross–sectional dependence. Amy Dunbar newey and ivregress fail to take the panel nature of the data into account (in fact the ivregress command you give will not run on multiple panels, and the newey with undocumented -force- option is likely to think your data are one long time series). I am trying to learn R after using Stata and I must say that I love it. 2008. The -ivreg2- help states, "Users should be aware of the asymptotic requirements for the consistency of the chosen VCE," so when T is short, is the best option the parametric option? Unclustered data. Having said that, you are asking a theoretical question.). * For searches and help try: Date Petersen (2007) reported a survey of 207 panel data papers published in the Journal of Finance,theJournal of Financial Economics,andtheReview of Financial Studies between 2001 and … * For searches and help try: Review of Financial Studies 22:435-80. Review of Financial Studies 22:435-80. -----Original Message----- * http://www.stata.com/support/statalist/faq The standard errors reported in the table of parameter estimates are the square root of the variances (diagonal elements) of the VCE. E.g. Hence, I wonder which regression type and which standard errors are most applicable as they should correct for heteroscedasticity and autocorrelation. > Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches.   one dimension such as firm or time). typical application would be panel data where one "category" is the panel and the other "category" is time; the I have used the modified Wald test to test for the presence of heteroskedasticity p values are low and hence the data does suffer from heteroskedasticity. Daniel Hoechle. contemporaneous cross-panel correlation (clustering on time). But e (i,t) can be autocorrelated. Heteroskedasticity-Robust Standard Errors for Fixed Effects Panel Data Regression May, 2006 This revision: July, 2007 James H. Stock Department of Economics, Harvard University and the NBER Mark W. Watson1 Department of Economics and Woodrow Wilson School, Princeton University and the NBER ABSTRACT The conventional heteroskedasticity-robust (HR) variance matrix estimator for cross … Take full advantage of the extra information that panel data provide, while simultaneously handling the peculiarities of panel data. Cluster-robust standard errors and hypothesis tests in panel data models James E. Pustejovsky 2020-11-03 . > > Robust standard errors for panel regressions with cross-sectional dependence Daniel Hoechle Department of Finance University of Basel Basel, Switzerland daniel.hoechle@unibas.ch Abstract. The second part deals with cluster-robust standard errors. Kit Baum wrote: "None of what you have found deals with clustering." An Introduction to Modern Econometrics Using Stata | http://www.stata-press.com/books/imeus.html I am about to do some multiple regressions with Panel Data so I am using the plm package.. Now I want to have the same results with plm in R as when I use the lm function and Stata when I perform a heteroscedasticity robust and entity fixed regression. The e-mail addresses that you supply to use this service will not be used for any other purpose without your consent. Review of Economics & Statistics, 80(4), 549-560. College Station, TX: Stata press.' 2009. The reason for robust standard errors in panel data is because the idiosyncratic errors can have heteroskedasticity or autocorrelation, or both. That is what you want, assuming you have a reasonable large cross section. Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org. It seems that way since you said the standard errors are "robust to heteroskedasticity and autocorrelation."   > * regression using Newey-West SEs * http://www.stata.com/support/statalist/faq > xtreg depvar varlist, fe robust I would look at Schaffer's -xtivreg2-, on SSC, which will allow you to estimate a model with one-way and two-way clustering (see my BOS'10 and UKSUG 2010 presentations, on my RePEc page below). Correcting for Cross-Sectional and Time-Series Dependence in Accounting Research. Downloadable! [Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index] Kit I observe important differences between clustered and non-clustered standard errors. cluster(varname1 varname2) provides 2-way cluster-robust SEs and statistics as proposed by Cameron, Gelbach and Thank you for considering my question. Social Media; Email; Share Access; Share this article via social media. "xtgls" allows for non-iid errors. > * regression using White SEs Therefore, it aects the hypothesis testing. HETEROSKEDASTICITY-ROBUST STANDARD ERRORS FOR FIXED EFFECTS PANEL DATA REGRESSION ... 2For example, at the time of writing, ΣˆHR−XS is the HR panel data variance estimator used in STATA and Eviews. 2010. vce(opg) uses the sum of the outer product of the gradient (OPG) vectors; see[R] ml. - ivreg2- has a small sample correction option, so when would that be appropriate as opposed to including a time indicator variable? > Estimating robust standard errors in Stata Author James Hardin, StataCorp The new versions are better (less biased). > xtreg depvar varlist, vce(robust) 2008. > newey depvar varlist, lag('T-1') force 4.1.1 Regression with Robust Standard Errors. Sent: Tuesday, October 26, 2010 7:56 AM All you need to is add the option robust to you regression command. Robust Inference for Regression with Clustered Data: ... Regression model … > ivregress gmm depvar varlist, vce(hac nwest opt) perfect Robust regression is an alternative to least squares regression when data is contaminated with outliers or influential observations and it can also be used for the purpose of detecting influential observations. resulting SEs are robust to arbitrary within-panel autocorrelation (clustering on panel id) and to arbitrary The rst data set is panel data from Introduction to Econometrics byStock and Watson[2006a], chapter 10. The rst part of this note deals with estimation of xed-e ects model using the Fatality data. RE: st: Robust Standard Errors in Paneldatasets "statalist@hsphsun2.harvard.edu" Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches. arbitrary within-group correlation in two distinct non-nested categories defined by varname1 and varname2. Robust Standard Errors in R. Stata makes the calculation of robust standard errors easy via the vce(robust) option. If I'm correct, -ivreg2- came out in 2008, so maybe Petersen wrote his paper before -ivreg2-, but his website doesn't mention -ivreg2-. In xtreg, stata automatically clusters on your panel variable when you type robust (in fact, it also does this when you don't). I recently read these two articles about robust standard errors in panel datasets and can't figure out which SE I should use and in case of the clustered method how to apply this to Stata. If you want to compute a Hausman test statistic that works also with cluster-robust standard errors you can follow the procedure outlined in Wooldridge (2010) "Econometric Analysis of Cross-Section and Panel Data". Microeconometrics using stata (Vol. 2). * http://www.stata.com/help.cgi?search and they indicate that it is essential that for panel data, OLS standard errors be corrected for clustering on the individual. > In a simple panel data analysis with data on 64 firms over 8 years, I use cluster-robust standard errors (at the firm level) to evaluate significance of coefficients. In Petersen, Mitchell A. > * normal panel regression Tue, 26 Oct 2010 13:24:06 +0000 This paper references Petersen's Stata code. Now, pooled OLS leaves u (i) in the error term, which is an obvious source of autocorrelation. > From How to implement heteroscedasticity-robust standard errors on regressions in Stata using the robust option and how to calculate them manually. > Hi, I am new to Stata and try to measure herd behavior as deviations in the return dispersion of a large panel dataset. On Oct 26, 2010, at 2:33 AM, Leon wrote: This approach allows for correlations among different firms in the same year and different years in the same firm, for example. The Stata Journal 2007 7: 3, 281-312 Share. "xtgls return monday january, p(c) c(p)" allows for heteroschedasticity and cross-sectional correlation across panels (countries in my example), in addition to panel-specific AR1 autocorrelation within each panel. You are not logged in. I have a panel of 49 observations, 7 countries, 7 years, running Panel fixed effects and IV fixed effects on Stata. I am trying to do a fixed effect panel regression with cluster-robust standard errors. > > > Petersen, M. A. RE: st: Robust Standard Errors in Paneldatasets Study the time-invariant features within each panel, the relationships across panels, and how outcomes of interest change over time. * The different robust estimators for the standard errors of panel models used in applied econometric practice can all be written and computed as combinations of the same simple building blocks. This table is taken from Chapter 11, p. 357 of Econometric Analysis of Cross Section and Panel Data, Second Edition by Jeffrey M Wooldridge. "Two-way cluster-robust" means the SEs and statistics are robust to Hence, obtaining the correct SE, is critical. > * regression using Driscoll-Kraay SEs (need to install the xtscc