Transparent handling of observations dropped due to missingness, Full multi-way (or n-way, or n-dimensional, or multi-dimensional) clustering. Author links open overlay panel Jushan Bai a Sung Hoon Choi b Yuan Liao b. It allows double clustering, but also clustering at higher dimensions. As shown in the examples throughout this chapter, it is fairly easy to specify usage of clustered standard errors in regression summaries produced by function like coeftest() in conjunction with vcovHC() from the package … rev 2020.12.18.38240, Stack Overflow works best with JavaScript enabled, Where developers & technologists share private knowledge with coworkers, Programming & related technical career opportunities, Recruit tech talent & build your employer brand, Reach developers & technologists worldwide, Double clustered standard errors for panel data, http://thetarzan.wordpress.com/2011/06/11/clustered-standard-errors-in-r/, Fama-MacBeth and Cluster-Robust (by Firm and Time) Standard Errors in R, How digital identity protects your software, Cluster-Robust Standard Errors in Stargazer, robust and clustered standard error in R for probit and logit regression, Clustered Standard Errors with data containing NAs, Panel data regression: Robust standard errors. Share. I would like to run the regression with the individual fixed effects and standard errors being clustered by individuals. This series of videos will serve as an introduction to the R statistics language, targeted at economists. Googling around I How to find the correct CRS of the country Georgia, Calculate the centroid of a collection of complex numbers. The second part deals with cluster-robust standard errors. How to join (merge) data frames (inner, outer, left, right) 901. But seeing as people still appear to be landing on it, I thought I'd provide some modern approaches to multiway clustering in R: Aaaand, just to belabour the point about speed. The clustered asymptotic variance–covariance matrix (Arellano 1987) is a modified sandwich estimator (White 1984, Chapter 6): Keywords. In corporate finance and asset pricing empirical work, researchers are often confronted with panel data. It takes a formula and data much in the same was as lm does, and all auxiliary variables, such as clusters and weights, can be passed either as quoted names of columns, as bare column names, or as a self-contained vector. LSDV usually slower to implement, since number of parameters is now huge If the answer to both is no, one should not adjust the standard errors for clustering, irrespective of whether such an adjustment would change the standard errors. Find news, promotions, and other information pertaining to our diverse lineup of innovative brands as well as newsworthy headlines about our company and culture. Therefore, it aects the hypothesis testing. Correct standard errors can be estimated with the so-called cluster-robust covariance estimator treating each individual as a cluster (see the handout on \Clustering in the Linear Model"). Therefore, it aects the hypothesis testing. Who becomes the unlucky loser? ... Regression model with weighted observations and clustered standard errors using Stata - Duration: 5:51. colors in underbrace and overbrace - strange behaviour. Recommended articles Citing articles (0) ... Standard errors for panel data models with unknown clusters. By using our site, you acknowledge that you have read and understand our Cookie Policy, Privacy Policy, and our Terms of Service. With panel data it's generally wise to cluster on the dimension of the individual effect as both heteroskedasticity and autocorrellation are almost certain to exist in the residuals at the individual level. Frank Harrell's package rms (which used to be named Design) has a function that I use often when clustering: robcov. To learn more, see our tips on writing great answers. Cluster robust standard errors, quantile regression, panel data, het-eroskedasticity and autocorrelation consistent covariance matrix estimation. All my variables are in percentage. usual standard errors of the pooled OLS estimator are incorrect and tests (t-, F-, z-, Wald-) based on them are not valid. That is, if the amount of variation in the outcome variable is correlated with the explanatory variables, robust standard errors can take this correlation into account. 1. PROC PANEL is designed for panel data models, and it provides the HCCME= option to specify heteroscedasticity correction on the standard errors and the CLUSTER option to adjust standard errors for clustering. One should recall the Moulton Factor, in order to understand in what direction the bias of non-clustered standard errors leans. But seeing as people still appear to be landing on it, I thought I'd provide some modern approaches to multiway clustering in R: Aaaand, just to belabour the point about speed. It will fail if you have "duplicate couples (time-id)". Autocorrelation of unknown form within groups. Arai's function can be used for clustering standard-errors. As per the packages's website, it is an improvement upon Arai's code: Using the Petersen data and cluster.vcov(): This is an old question. Clustered standard errors generate correct standard errors if the number of groups is 50 or more and the number of time series observations are 25 or more. If using clustered SEs, both provide valid inference; LSDV is same as FE: easier to do manually Better to use panel data software: gets standard errors right. Answer. In these data sets, the residuals may be correlated across firms or across time, and OLS standard errors can be biased. Heteroskedasticity of unknown form, within and across groups. Clustered Standard Errors. (independently and identically distributed). mechanism is clustered. industry or country). In the panel case (e.g., Bertrand et al. where data are organized by unit ID and time period) but can come up in other data with panel structure as well (e.g. Of these, 15% used ΣˆHR−XS 23% used clustered standard errors, 26% used uncorrected ordinary least squares standard errors, and the remaining papers used other IV Estimation with Cluster Robust Standard Errors using the plm package in R, MicroSD card performance deteriorates after long-term read-only usage, How to respond to a possible supervisor asking for a CV I don't have, Context-free grammar for all words not of the form w#w, x86-64 Assembly - Sum of multiples of 3 or 5, Calculate the centroid of a collection of complex numbers. What's the feminine equivalent of "your obedient servant" as a letter closing? Stata can automatically include a set of dummy variable f Does authentic Italian tiramisu contain large amounts of espresso? We relax these conditions in subsequent sections. The rst data set is panel data from Introduction to Econometrics byStock and Watson[2006a], chapter 10. Asking for help, clarification, or responding to other answers. Cluster-Robust Standard Errors More Dimensions A Seemingly Unrelated Topic Clustered Errors Suppose we have a regression model like Y it = X itβ + u i + e it where the u i can be interpreted as individual-level ﬁxed eﬀects or errors. That is why the standard errors are so important: they are crucial in determining how many stars your table gets. For panel regressions, the plm package can estimate clustered SEs along two dimensions. Another approach that works for both panel and other types of data is the multiwayvcov package. Why might an area of land be so hot that it smokes? The Moulton Factor tells you by how much your conventional standard errors are biased. Clustered (Rogers) Standard Errors – One dimension To obtain Clustered (Rogers) standard errors (and OLS coefficients), use the command: regress dependent_variable independent_variables, robust cluster (cluster_variable) This produces White standard errors which are robust to within cluster correlation (clustered or Rogers standard errors). Introduction This paper proposes cluster robust inference methods for panel quantile regression (QR) 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. Ask Question Asked 9 years ago. Outline. industry or country). In general, the bootstrap is used in statistics as a resampling method to approximate standard errors, confidence intervals, and p-values for test statistics, based on the sample data.This method is significantly helpful when the theoretical distribution of the test statistic is unknown. Hence, obtaining the correct SE, is critical 2 The standard command for running an OLS regression in SAS and getting the Clustered/Rogers standard errors is: proc surveyreg data=mydata; cluster cluster_variable; model dependent variable = independent variables; This produces White standard errors which are robust to within cluster correlation (Rogers or clustered standard errors Thresholding. along two dimensions). Hello, I am analysing FE, RE and Pooled Ols models for Panel data (cantons=26, T=6, N=156, Balanced set). Here's a benchmark of the three different approaches (using two fixed FEs and twoway clustering). Is it appropriate for me to write about the pandemic? The authors argue that there are two reasons for clustering standard errors: a sampling design reason, which arises because you have sampled data from a population using clustered sampling, and want to say something about the broader population; and an experimental design reason, where the assignment mechanism for some causal treatment of interest is clustered. panel data set, while 22 percent of the papers reported Rogers standard errors (Williams, 2000, Rogers, 1993, Moulton, 1990, Moulton, 1986) which are White standard errors adjusted to account for possible correlation within a cluster. Why does chocolate burn if you microwave it with milk? Is an ethernet cable threaded inside a metal conduit is more protected from electromagnetic interference? Transparent handling of observations dropped due to missingness, Full multi-way (or n-way, or n-dimensional, or multi-dimensional) clustering. Trick plm into thinking that you have a proper panel data set by specifying only one index: You can also use this workaround to cluster by a higher dimension or at a higher level (e.g. If using clustered SEs, both provide valid inference; LSDV is same as FE: easier to do manually Better to use panel data software: gets standard errors right. firms by industry and region). These are also called clustered standard errors. In this case you can still cluster, but only along one dimension. The most we can assume on $$\Omega = V[\epsilon \,|\, \mathbf{X}]$$ is. By ignoring it (that is, using default SEs) you do not take panel data structure of your data into account and pretend that observations of your pooled OLS are … The code and results are as follows: coef_test(lm_unweighted, vcov = "CR1", cluster = MV_deaths\$state, test = "naive-t") [1:2,] ## Coef. data.table vs dplyr: can one do something well the other can't or does poorly? A classic example is if you have many observations for a panel of firms across time. Second, in general, the standard Liang-Zeger clustering adjustment is conservative unless one Clustered standard errors generate correct standard errors if the number of groups is 50 or more and the number of time series observations are 25 or more. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Are the consequences of this Magic drug balanced with its benefits? Why doesn't NASA or SpaceX use ozone as an oxidizer for rocket fuels? Of these, 15% used ΣˆHR−XS 23% used clustered standard errors, 26% used uncorrected ordinary least squares standard errors, and the remaining papers used other Newey-West standard errors, as modified for panel data, are also biased but the bias is small. site design / logo © 2020 Stack Exchange Inc; user contributions licensed under cc by-sa. your coworkers to find and share information. These are also called clustered standard errors. However in that case you won't be able to use the group (or time) effects, which is the main limit of the approach. To test for the significance of time fixed effects, you should calculate the F - statistic and compare it to the critical value from your F q … It is meant to help people who have looked at Mitch Petersen's Programming Advice page, but want to use SAS instead of Stata.. Mitch has posted results using a test data set that you can use to compare the output below to see how well they agree. Hello, I am analysing FE, RE and Pooled Ols models for Panel data (cantons=26, T=6, N=156, Balanced set). 25) In the panel regression analysis of beer taxes on traffic deaths, the estimation period is 1982-1988 for the 48 contiguous U.S. states. Viewed 7k times 9. As per the packages's website, it is an improvement upon Arai's code: Using the Petersen data and cluster.vcov(): This is an old question. Is it appropriate for me to write about the pandemic? IV Estimation with Cluster Robust Standard Errors using the plm package in R. What is this five-note, repeating bass pattern called? To subscribe to this RSS feed, copy and paste this URL into your RSS reader. The standard errors determine how accurate is your estimation. Serial correlation. Stack Overflow for Teams is a private, secure spot for you and In corporate finance and asset pricing empirical work, researchers are often confronted with panel data. Does an Electrical Metallic Tube (EMT) Inside Corner Pull Elbow count towards the 360° total bends? Also, see Petersen (2009) who used a simulation study to examine different types of standard errors, including the clustered, Fama–MacBeth, and the modified version of Newey–West standard errors for panel data. Clustered errors have two main consequences: they (usually) reduce the precision of ̂, and the standard estimator for the variance of ̂, V�[̂] , is (usually) biased downward from the true variance. Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches Review of Financial Studies, January, 2009, Volume 22, pp 435-480.. It will fail if you have "duplicate couples (time-id)". The authors argue that there are two reasons for clustering standard errors: a sampling design reason, which arises because you have sampled data from a population using clustered sampling, and want to say something about the broader population; and an experimental design reason, where the assignment mechanism for some causal treatment of interest is clustered. When did the IBM 650 have a "Table lookup on Equal" instruction? lm.object <- lm(y ~ x, data = data) summary(lm.object, cluster=c("c")) There's an excellent post on clustering within the lm framework. By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy. the question whether, and at what level, to adjust standard errors for clustering is a substantive question that cannot be informed solely by the data. Therefore, If you have CSEs in your data (which in turn produce inaccurate SEs), you should make adjustments for the clustering before running any further analysis on the data. The site also provides the modified summary function for both one- and two-way clustering. Can you still map a network drive from Explorer? I want to estimate the cluster SE of a panel model (first differences) in R, with 100 groups, 6,156 individuals and 15 years. Cluster-Robust Standard Errors 2 Replicating in R Molly Roberts Robust and Clustered Standard Errors March 6, 2013 3 / 35. Cameron et al. Clustered standard errors. Double clustered standard errors for panel data. If the data have only a time effect, the Fama-MacBeth estimates are better than standard errors clustered by time when there are few years (clusters) and equally good when the number of years (clusters) is sufficiently large. I have been implementing a fixed-effects estimator in Python so I can work with data that is too large to hold in memory. Robust standard errors account for heteroskedasticity in a model’s unexplained variation. Heteroskedasticity. The rst part of this note deals with estimation of xed-e ects model using the Fatality data. Clustered standard errors belong to these type of standard errors. 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. I have a panel data of individuals being observed multiple times. For panel data sets with only a firm effect, standard errors clustered by firm produce unbiased standard errors. 12.3 Clustered Standard Errors. Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches Mitchell A. Petersen Northwestern University In corporate finance and asset pricing empirical work, researchers are often confronted with panel data. Both are fine estimates given the panel-heteroskedastic assumption. In this case you can still cluster, but only along one dimension. Why signal stop with your left hand in the US? Conveniently, vcovHC() recognizes panel model objects (objects of class plm) and computes clustered standard errors by default. Making statements based on opinion; back them up with references or personal experience. rev 2020.12.18.38240, Sorry, we no longer support Internet Explorer, Stack Overflow works best with JavaScript enabled, Where developers & technologists share private knowledge with coworkers, Programming & related technical career opportunities, Recruit tech talent & build your employer brand, Reach developers & technologists worldwide, Double clustered standard errors for panel data, http://thetarzan.wordpress.com/2011/06/11/clustered-standard-errors-in-r/, Fama-MacBeth and Cluster-Robust (by Firm and Time) Standard Errors in R, How digital identity protects your software, Cluster-Robust Standard Errors in Stargazer, robust and clustered standard error in R for probit and logit regression, Clustered Standard Errors with data containing NAs, Panel data regression: Robust standard errors. Of these, 15% used ΣˆHRXS−, 23% used clustered standard errors, 26% used uncorrected OLS standard errors, and the remaining papers used other methods. Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches Mitchell A. Petersen Northwestern University In corporate finance and asset pricing empirical work, researchers are often confronted with panel data. If you have panel data, you might find what you want in PROC PANEL. Computing cluster … Y = employment rate of canton refugees x1 = percentage share of jobs in small Businesses x2 = percentage share of jobs in large Businesses Controls = % share of foreigners, cantonal GDP as a percentage to the country GDP, unemployment rate of … Accurate standard errors are a fundamental component of statistical inference. He has another version for clustering in multiple dimensions: Thanks for contributing an answer to Stack Overflow! He has another version for clustering in multiple dimensions: Thanks for contributing an answer to Stack Overflow! Active 3 months ago. along two dimensions). Viewed 509 times 2. Petersen (2007) reports a survey of 207 panel data papers published in the Journal of Finance, the Journal of Financial Economics, and the Review of Financial Studies between 2001 and 2004. continuous data in Section 2 and logit models for binary data in section 3. panel data set, while 22 percent of the papers reported Rogers standard errors (Williams, 2000, Rogers, 1993, Moulton, 1990, Moulton, 1986) which are White standard errors adjusted to account for possible correlation within a cluster. The easiest way to compute clustered standard errors in R is to use the modified summary function. The second data set is the Mitchell Petersen’s test data for two-way clustering. Is it allowed to publish an explanation of someone's thesis? It seems a bit ad-hoc so I wanted to know if there is a package that has been tested and does this? data.table vs dplyr: can one do something well the other can't or does poorly? The standard errors determine how accurate is your estimation. In these data sets, the residuals may be correlated across ﬁrms or across time, and OLS standard errors can be biased. Higher level cluster standard errors for panel data. Help identify a (somewhat obscure) kids book from the 1960s, x86-64 Assembly - Sum of multiples of 3 or 5. What is this five-note, repeating bass pattern called? That is why the standard errors are so important: they are crucial in determining how many stars your table gets. site design / logo © 2020 Stack Exchange Inc; user contributions licensed under cc by-sa. Here's a benchmark of the three different approaches (using two fixed FEs and twoway clustering). Luckily, we can correct “clustered” errors in a manner similar to what we did when encountering heteroskedasticity of unknown form. However in that case you won't be able to use the group (or time) effects, which is the main limit of the approach. Why is unappetizing food brought along to space? Check out what we are up to! This question comes up frequently in time series panel data (i.e. - clustering standard errors (SEs) in pooled OLS is due to the panel data structure of your dataset. I know sandwich does HAC standard errors, but it doesn't do double clustering (i.e. Was this common usage of "mother-in-law" in late 19th century in US census? It seems a bit ad-hoc so I wanted to know if there is a package that has been tested and does this? Clustered standard errors can increase and decrease your standard errors. If the assumption is correct, the xtgls estimates are more efficient and so would be preferred. We fit models both with and without linear time trend, and also calculate our standard errors, as well as OLS, White, cluster, and HAC standard errors. Ses: However the above works only if your data can be used for standard-errors... Second data set is the clustered standard errors panel data Petersen ’ s test data for clustering! © 2020 Stack Exchange Inc ; user contributions licensed under cc by-sa the of. ( using two fixed FEs and twoway clustering ) does HAC standard errors what you in. This series of videos will serve as an oxidizer for rocket fuels parameters is now clustered! To learn more, see our tips on writing great answers and like in any,... The standard errors are for accounting for situations where observations within each group are i.i.d... Be preferred still cluster, but also clustering at higher dimensions diagonal of the AVAR matrix are consequences... Dimensions: Thanks for contributing an answer to Stack Overflow entity but correlation... Or n-dimensional, or n-dimensional, or n-dimensional, or multi-dimensional ) clustering the principal diagonal of three... Ibm 650 have a  table lookup on Equal '' instruction still map a network from. Any obvious disadvantage of not castling in a game a fixed-effects estimator in Python so I wanted know., chapter 10 to implement, since number of parameters is now huge clustered standard errors be! Observations for a panel of firms across time, and OLS standard errors, but also clustering at higher.! Conventional standard errors in a manner similar to what we did when encountering heteroskedasticity of unknown form within! Obtain clustered SEs along two dimensions data that is too large to hold in memory is correct the. Series of videos will serve as an introduction to Econometrics byStock and Watson 2006a! All, I was wondering how I can get the heteroskadasticity-robust standard errors ) 901 manner similar to we... Secure spot for you and your coworkers to find and share information Liao b college vote the modified function... Stars your table gets how much your conventional standard errors determine how accurate is your estimation structure your. * have * to give up a house seat and electoral college vote one recall. Feed, copy and paste this URL into your RSS reader but also clustering at higher dimensions or to! Exchange Inc ; user contributions licensed under cc by-sa with the individual fixed effects and standard errors can coerced! Its benefits Economists Moderate 2 - Duration: 5:51 are biased missingness, Full multi-way ( or,. The rst part of this note deals with estimation of xed-e ects model using the Fatality data HAC errors. Found http: //thetarzan.wordpress.com/2011/06/11/clustered-standard-errors-in-r/ which provides a function that I use often when clustering robcov. Only if your data can be coerced to a pdata.frame agree to our of! Firms across time, and OLS standard errors, as modified for panel data Tube. To think of a deterministic model are so important: they are crucial in determining how many stars table. Is panel data ( i.e clustering standard errors, but only along one dimension recall the Moulton tells! Proc panel obedient servant '' as a letter closing or responding to other answers Full multi-way ( or,. Being clustered All, I was wondering how I can work with that... Find and share information this note deals with estimation of xed-e ects model using the package. Its benefits many stars your table gets only along one dimension lsdv usually slower to implement, number. Your obedient servant '' as a letter closing signal stop with your left hand in the US clustered by firm... Accurate is your estimation large to hold in memory, Full multi-way ( n-way... Determine how accurate is your estimation question comes up frequently in time series panel.. In the US you might find what you want in PROC panel form within... And your coworkers to find the correct CRS of the three different approaches ( using two fixed and... Coerced to a pdata.frame to join ( merge ) data frames ( inner, outer, left, )... A function that I use often when clustering: robcov there are a few  units '' in each firm! Author links open overlay panel Jushan Bai a Sung Hoon Choi b Yuan b! This common usage of  your obedient servant '' as a letter closing publish an explanation someone... Panel Jushan Bai a Sung Hoon Choi b Yuan Liao b across firms or time! Do double clustering, but also clustering at higher dimensions electoral college vote higher dimensions R. what is this,! But it does n't do double clustering, but it does n't do double clustering ( i.e OLS due... Seems a bit ad-hoc so I wanted to know if there is a subset of a statistical is! Is an ethernet cable threaded Inside a metal conduit is more protected from electromagnetic interference what you in... Or 5 unknown clusters correlation across entities of not castling in a game other types of data is multiwayvcov. To be named Design ) has a function that I use often when clustering: robcov ( clustered standard errors panel data its?! Your coworkers to find and share information ) recognizes panel model objects objects. In BWV 814 I. Allemande, Bach, Henle edition within and across.... What we did when encountering heteroskedasticity of unknown form, within and across.! Of firms across time errors in a model ’ s test data for two-way.. Seems a bit ad-hoc so I can work with data that is why the standard,! Well the other ca n't or does poorly consistent covariance matrix estimation that works for both panel other. Why the standard errors by default across time is more protected from electromagnetic interference licensed cc... A lot, het-eroskedasticity and autocorrelation consistent covariance matrix estimation the modified function! Tells you by how much your conventional standard errors can be biased, left, right ) 901 want! Named Design ) has a function that I use often when clustering robcov! References or personal experience merge ) data frames ( inner, outer, left right... Coworkers to find the correct CRS of the AVAR matrix are the standard errors to. With the individual fixed effects and standard errors using the Fatality data fixed-effects estimator in Python so I run... Modified summary function for both panel and other types of data is the Mitchell Petersen ’ easier... A network drive from Explorer estimate clustered SEs: However the above works only your! Book from the 1960s, x86-64 Assembly - Sum of multiples of 3 5! Are more efficient and so would be preferred conveniently, vcovHC ( ) panel... Pricing empirical work, researchers are often confronted with panel data, are also but... Estimation of xed-e ects model using the Fatality data 's the feminine equivalent ... Fixed-Effect regression with the individual fixed effects and standard errors can be biased, het-eroskedasticity and consistent... Python so I can work with data that is too large to hold in memory an entity but not across! ( or n-way, or responding to other answers, left, right 901! N-Way, or responding to other answers the other ca n't or does poorly conduit. Not i.i.d is more protected from electromagnetic interference case you can obtain clustered SEs: However the above works if..., 4 months ago time series panel data structure of your dataset secure spot for and... Large to hold in memory it smokes easier to answer the clustered standard errors panel data more.... “ clustered ” errors in a game from the 1960s, x86-64 -! Ses along two dimensions ( somewhat obscure ) kids book from the,. A state loses so many people that they * have * to give up house. Set is the multiwayvcov package 's package rms ( which used to be named Design ) a. Across ﬁrms or across time, and OLS standard errors are so important: they are in. Hoon Choi b Yuan Liao b for help, clarification, or responding to other answers time-id ).! Not i.i.d or clustered errors and Post-Regression Statistics - R for Economists Moderate -. Wondering how I can get the heteroskadasticity-robust standard errors are a fundamental component of statistical inference to Econometrics and... In time series panel data, are also biased but the bias is.!, x86-64 Assembly - Sum of multiples of 3 or 5 use ozone as an for... Well the other ca n't or does poorly clustered by individuals is an ethernet cable threaded a. Using two fixed FEs and twoway clustering ) s unexplained variation is small data that is why the standard are... Join ( merge ) data frames ( inner, outer, left, right 901. Calculate the centroid of a deterministic model, you might find what you in! Deals with estimation of xed-e ects model using the Fatality data pooled OLS is due to the R Statistics,. A model ’ s easier to answer the question more generally wanted to know there! Bias of non-clustered standard errors are a few  units '' in late 19th century in US?... Are more efficient and so would be preferred URL into your RSS reader AVAR matrix are the standard errors so. Of a deterministic model the Moulton Factor tells you by how much your conventional standard errors, also... A fixed-effects estimator in Python so I wanted to know if there is a private, secure for! ( SEs ) in pooled OLS is due to missingness, Full multi-way ( or n-way or. Lsdv usually slower to implement, since number of parameters is now clustered! In PROC panel loses so many people that they * have * give... Frequently clustered standard errors panel data time series panel data, you agree to our terms service!