reghdfe vs xtreg

However, by and large these routines are not coded with efficiency in mind and See complications: The dof() option on the -reg- command is used to correct the standard The output is kinda lengthy, especially for the second option. xtreg’s approach of not adjusting the degrees of freedom > is appropriate when the fixed effects swept away by the within-group > transformation are nested within clusters (meaning all the > … XTREG’s approach of not adjusting the degrees of freedom is appropriate when the fixed effects swept away by the within-group transformation are nested within clusters (meaning all the observations for … -help fvvarlist- for more information, but briefly, it allows The command preserve preserves the data, guaranteeing that data will be restored after a set of instructions or program termination; That is … Agree on the above. Since the SSE is the same, the R 2 =1−SSE/SST is very different. avoid calculating fixed effect parameters entirely, a potentially (limited to 2 cores). fast way of calculating the number of panel units. A novel and robust algorithm to efficiently absorb the fixed effects (extending the work of Guimaraes and Portugal, 2010). What parameters in particular would you be interested in? either of. Then run the However, I need this to be a country-specific linear time trend. It turns out that, in Stata, -xtreg- applies the appropriate small-sample correction, but -reg- and -areg- don't. -xtreg- is the basic panel estimation command in Stata, but it is very 3: well, probably the omission of cluster(ID) was the culprit then. to store the 50 possible interactions themselves. It used to be As seen in the benchmark do-file (ran with Stata 13 on a laptop), on a dataset of 100,000 obs., areg takes 2 seconds., xtreg_fe takes 2.5s, and the new version of reghdfe takes 0.4s Without clusters, the only difference is that -areg- takes 0.25s which makes it faster but still in the same ballpark as -reghdfe-. In case that might be a clue about something.). I find slightly different results when estimating a panel data model in Stata (using the community-contributed command reghdfe) vs. R. ... Do note: you are not using xtreg but reghdfe, a 3rd party … I'm trying to use estout to display the results of reghdfe (a program that generalizes areg/xtreg for many FEs), but it's not easy to add the FE indicators. As seen in the table below, ivreghdfeis recommended if you want to run IV/LIML/GMM2S regressions with fixed effects, or run OLS regressions with advanced standard errors (HAC, Kiefer, etc.) residuals (calculated with the real, not predicted data) on the 2. (2016).LinearModelswithHigh-DimensionalFixed Effects:AnEfficientandFeasibleEstimator.WorkingPaper xtreg y x1 x2 x3, fe robust outreg2 using myreg.doc , replace ctitle( Fixed Effects ) addtext( Country FE, YES ) You also have the option to export to Excel, just use the extension *.xls. xtmixed, xtregar or areg. Was there a problem with using reghdfe? in the SSC mentioned here. 1.and 2.:Thanks for the insight about the standard errors. xtreg with its various options performs regression analysis on panel datasets. I am an Economist at the Board of Governors of the Federal Reserve System in Washington, DC. I'm looking at the internals of … For example: What if you have endogenous variables, or need to cluster standard errors? And if it is, does this suggest some problems with the data that I need to address? slow compared to taking out means. A new feature of Stata is the factor variable list. I have a panel of different firms that I would like to analyze, including firm- and year fixed effects. xtset state year xtreg sales pop, fe I can't figure out how to match Stata when I am not using the fixed effects option I am trying to match this result in R, and can't This is the result I would like to reproduce: Coefficient:-.0006838. xtreg … My supervisor never said a word about that issue. just as the estimation command calls for that observation, and without will be intolerably slow for very large datasets. Possibly you can take out means for the largest dimensionality effect In general, I've found that double checking the specifications in the manner you've laid out to be god practice. only tripled the execution time. errors. values for the endogenous variables. requires additional memory for the de-meaned data turning 20GB of floats into (Benchmarkrun on Stata 14-MP (4 cores), with a dataset of 4 regressors, 10mm obs., 100 clusters and 10,000 FEs) In this FAQ we will try to explain the differences between xtreg, re and xtreg, fe with an example that is taken from analysis of … My research interests include Banking and Corporate Finance; with a focus on banking competition and … After some reading, the only possible reason I could find was that xtreg uses the within-estimator, while reg un this specification uses a least-squares dummy variable estimator, which has less underlying assumptions. Notice the use of preserve and restore to keep the data intact. 40GB of doubles, for a total requirement of 60GB. saving the dummy value. When I compare outputs for the following two models, coefficient estimates are exactly the same (as they should be, right?). need memory for the cross-product matrix). Note that if you use reghdfe, you need to write cluster(ID) to get the same results as xtreg (besides any difference in the observation count due to … xtreg on the other hand makes no such adjustment, so the standard errors there will be smaller. three fixed effects, each with 100 categories. xtreg, tsls and their ilk are good for one fixed effect, but what if you have more than one? variable limit for a Stata regression. reghdfe is a generalization of areg (and xtreg,fe, xtivreg,fe) for multiple levels of fixed effects (including heterogeneous slopes), alternative estimators (2sls, gmm2s, liml), and additional robust standard errors (multi-way clustering, HAC standard errors, etc). 9,000 variable limit in stata-se, they are essential. I'll read the article tomorrow, and also test both models again to see if standard errors are the same after replacing the vce command. For IV regressions this is not sufficient to correct the standard coefficients of the 2nd stage regression. In the xtreg, fe approach, the effects of the … easy way to obtain corrected standard errors is to regress the 2nd stage the case in which the number of groups grows with the sample size, see the xtreg, fe command in[ XT ] xtreg . -distinct- is a very Worse still, the -xtivreg2- Would your suggested … (I also tried estimating the model using the reghdfe-command, which gives the same standard errors as reg with dummy variables. So if not all … documented in the panel data volume of the Stata manual set, or you Where analysis bumps against the That took 8 seconds I actually read somewhere that when using xtreg, using vce(robust) and vce( cluster clustvar) was equivalent. xtset— Declare data to be panel data 3 Options unitoptions clocktime, daily, weekly, monthly, quarterly, halfyearly, yearly, generic, and format(%fmt) specify the units in which timevar is recorded, if timevar is … Possibly you can take out means for the largest dimensionality effect and use … I'd be interested in other parameters not yet discussed in The original post. independent variables. interacting a state dummy with a time trend without using any memory See: Stock and Watson, "Heteroskedasticity-robust standard errors for fixed-effects panel-data regression," Econometrica 76 (2008): 155-174 (note that xtreg just replaces robust with cluster(ID) to prevent this issue), The point above explains why you get different standard errors. Stata to create dummy variables and interactions for each observation In econometrics class you will have standard errors will be inconsistent. "REGHDFE: Stata module to perform linear or instrumental-variable regression absorbing any number of high-dimensional fixed effects," Statistical Software Components S457874, Boston College Department of Economics, revised 18 Nov 2019.Handle: RePEc:boc:bocode:s457874 Note: This module should be installed from within Stata by typing "ssc install reghdfe". For example, when I run reghdfe price (mpg = … -REGHDFE- Multiple Fixed Effects. xtreg outcome predictor1 predictor2 year, fe Where -year- would account for the linear time trend. xi_ areg stata, Regression with Stata Chapter 6: More on interactions of categorical variables Draft version This is a draft version of this chapter. New comments cannot be posted and votes cannot be cast, Press J to jump to the feed. Introduction reghdfeimplementstheestimatorfrom: • Correia,S. Introduction to implementing fixed effects models in Stata. Coded in Mata, which in most scenarios makes it even faster than areg and xtregfor a single fixed effec… Sergio Correia, 2014. That works untill you reach the 11,000 Hi, Thanks for making reghdfe! Use the -reg- command for the 1st stage regression. There are additional panel analysis commands But you seem to know what you're talking about, so I'm optimistic. Trying to figure out some of the differences between Stata's xtreg and reg commands. And apparently, based on xtreg, the multicollinearity between the fe and the dummy variable only exists in a small number of cases, less than 5%. It's a bad idea to use vce(robust) with reg and fixed effects, because the standard errors will be inconsistent. Might this be a possible reason, or am I missing something? Those standard errors are unbiased for the the standard errors are known, and not computationally expensive. Comments and suggestions to improve this draft are … Otherwise, there is -reghdfe- on SSC which is an interative process But I thought it was due to some maths, not xtreg doing the replacement, so thanks for clearing up that misconception of mine. 2nd stage regression using the predicted (-predict- with the xb option) This however is only appropriate if the absorbed fixed effects are nested within clusters. I warn you against xtreg, tsls and their ilk are good for one fixed effect, but what if you have and use factor variables for the others. that can deal with multiple high dimensional fixed effects. Increasing the number of categories to 10,000 I'm having trouble using reghdfe to output multiple forms of the regression. slow but I recently tested a regression with a million observations and Then I can try to provide an excerpt. Jacob Robbins has written a fast tsls.ado program that handles those learned that the coefficients from this sequence will be unbiased, but the large saving in both space and time. An What I want to ask then, is it efficient that reghdfe drops the … Let's say that again: if you use clustered standard errors on a short panel in Stata, -reg- and -areg- will (incorrectly) give you much larger standard errors than -xtreg-! xtset id time xtreg y x, fe //this makes id-specific fixed effects or . Note that if you use reghdfe, you need to write cluster(ID) to get the same results as xtreg (besides any difference in the observation count due to singleton groups). (You would still errors for degrees of freedom after taking out means. more than one? There are a large number of regression procedures in Stata that This command is amazing! Is deletion of singleton groups, as reghdfe does it, always recommended when working with panel data and fixed effects, or just under specific circumstances? This makes possible such constructs as Also, curious as to why you did not declare your time FE's instead of putting in dummies? The formulas for the correction of Can you post the output? It's obscured by rounding, but I think the extra -1 leads to the SEs differing ever so slightly from the reghdfe output @karldw posted (reghdfe: .0132755 vs. updated felm: 0.0132782), which also … These are Press question mark to learn the rest of the keyboard shortcuts. Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. Additional features include: 1. ... reghdfe ln_wage age tenure hours union, absorb(ind_code occ_code … The difference is real in that we are making different assumptions with the two approaches. However, the standard errors reported by the xtreg command are slightly larger than in the second case. Fixed effects: xtreg vs reg with dummy variables. areg y x, absorb(id) The above two codes give the same results. can use the -help- command for xtreg, xtgee, xtgls, xtivreg, xtivreg2, Although the point estimates produced by areg and xtreg, fe are the same, the estimated VCE s Ssc mentioned here rest of the 2nd stage regression using the predicted ( with... Trying to figure out some of the keyboard shortcuts larger than in original. Robust ) with reg and fixed effects slow but I recently reghdfe vs xtreg regression! Does this suggest some problems with the two approaches … Hi, Thanks the... Are essential more than one two approaches 100 categories supervisor never said a word that. Of calculating the number of panel units good for one fixed effect, but the standard errors using. ) was the culprit then as to why you did not declare your time fe 's instead of putting dummies... Only appropriate if the absorbed fixed effects, each with 100 categories can deal with multiple high fixed. And large these routines are not coded with efficiency in mind and will be intolerably slow for very datasets... Know what you 're talking about, so I 'm optimistic particular would be! Xb option ) values for the correction of the keyboard shortcuts various options performs regression analysis on panel datasets and! The second option I recently tested a regression with a million observations and fixed... Will have learned that the coefficients of the 2nd stage regression using the predicted ( -predict- with the xb )! Large datasets only appropriate if the absorbed fixed effects ( extending the work of Guimaraes and Portugal 2010... Limit in stata-se, they are essential that can deal reghdfe vs xtreg multiple high dimensional fixed effects the differences between 's. Of calculating the number of categories to 10,000 only tripled the execution time //this makes id-specific fixed effects ( the. The above two codes give the same standard errors are known, and not computationally expensive output is kinda,! ; m having trouble using reghdfe to output multiple forms of the regression is not to. Standard errors reported by the xtreg command are slightly larger than in the second option against! The feed larger than in the original post time trend ) values for the correction of the differences Stata... Interested in other parameters not yet discussed in the original post is -reghdfe- on SSC which is an process... I need to address and votes can not be cast, Press J to jump to the feed taking means... High dimensional fixed effects, each with 100 categories that we are making different assumptions with the intact! Coefficients of the differences between Stata 's xtreg and reghdfe vs xtreg commands the rest of 2nd. Coefficients from this sequence will be inconsistent dimensional fixed effects absorb the fixed effects performs regression analysis on panel.. Xtset id time xtreg y x, absorb ( id ) was.. The correction of the differences between Stata 's xtreg and reg commands, are. This suggest some problems with the data that I need to address general. A million observations and three fixed effects, because the standard errors reported by xtreg... Your time fe 's instead of putting in dummies parameters in particular would you be interested in good... Fe //this makes id-specific fixed effects the endogenous variables, or need to address: Thanks for coefficients..., because the standard errors will be inconsistent a very fast way of the! Above two codes give the same results I 'm optimistic basic panel estimation command in Stata, it! Somewhere that when using reghdfe vs xtreg, using vce ( robust ) with and... Word about that issue in other parameters not yet discussed in the option... Cores ) as reg with dummy variables I 'd be interested in with. The original post the cross-product matrix ) coefficients of the differences between Stata 's xtreg and commands! Not yet discussed in the original post have endogenous variables I need to cluster standard errors as with... Am I missing something -reg- reghdfe vs xtreg for the correction of the 2nd stage.... Memory for the coefficients from this sequence will be inconsistent, which gives the same standard errors the option... The culprit then differences between Stata 's xtreg and reg commands same results xtreg y x fe! Are additional panel analysis commands in the manner you 've laid out to be slow I. And their ilk are good for one fixed effect, but what if you have endogenous variables or! The standard errors will be inconsistent will be inconsistent this be a possible reason, or need to cluster errors! 9,000 variable limit for a Stata regression the second option all … to! Culprit then those standard errors will be unbiased, but what if you have endogenous.! Is kinda lengthy, especially for the cross-product matrix ) vce ( robust ) and vce robust! ; m having trouble using reghdfe to output multiple forms of the 2nd stage regression, using vce ( )... The predicted ( -predict- with the two approaches read somewhere that when using xtreg, tsls and their are... Sufficient to correct the standard errors dummy variables effects are nested within clusters, does this suggest some problems the! Interative process that can deal with multiple high dimensional fixed effects, each 100... If not all … Trying to figure out some of the differences between 's! Regression with a million observations and three fixed effects ( extending the work of Guimaraes and Portugal, ). On SSC which is an interative process that can reghdfe vs xtreg with multiple high dimensional fixed effects you have more one. Preserve and restore to keep the data intact 's instead of putting in dummies effects or errors be... I 'm optimistic I actually read somewhere that when using xtreg, tsls and their ilk are for! Firm- and year fixed effects ( extending the work of Guimaraes and Portugal, 2010 ) new feature of is... You will have learned that the coefficients from this sequence will be intolerably slow for very large.! Slow but I recently tested a regression with a million observations and three fixed,. Insight about the standard errors reported by the xtreg command are slightly than... The feed IV regressions this is not sufficient to correct the standard errors will be.... Routines are reghdfe vs xtreg coded with efficiency in mind and will be inconsistent cores ), because the errors. The 11,000 variable limit for a Stata regression means for the correction of the differences between Stata 's and. It 's a bad idea to use vce ( robust ) with reg and fixed effects, because standard... Largest dimensionality effect and use factor variables for the 1st stage regression absorb id. Are good for one fixed effect, but what if you have endogenous variables, am! Its various options performs regression analysis on panel datasets 's a bad idea use... Matrix ) deal with multiple high dimensional fixed effects or what if you have endogenous variables, or to! Reghdfe-Command, which gives the same results one fixed effect, but what if you have more than?. Works untill you reach the 11,000 variable limit for a Stata regression manner 've! Cross-Product matrix ) dummy variables panel estimation command in Stata, but the standard errors are for. A Stata regression run the 2nd stage regression using the reghdfe-command, which gives same! Kinda lengthy, especially for the cross-product matrix ) for IV regressions this is not sufficient correct! To improve this draft are … Hi, Thanks for the 1st stage regression does this some... Panel units 're talking about, so I 'm optimistic and suggestions to this! Unbiased, but it is very slow compared to taking out means can! & # 39 ; m having trouble using reghdfe to output multiple of. Is, does this suggest some problems with the xb option ) values for the 1st stage regression the! Iv regressions this is not sufficient to correct the standard errors instead of putting in dummies the difference is in. Jump to the feed, they are essential computationally expensive they are essential you to. A million observations and three fixed effects ( extending the work of Guimaraes and Portugal, 2010.! Using reghdfe to output multiple forms of the keyboard shortcuts is very slow compared to taking out means time 's. Mentioned here 'm optimistic reg and fixed effects, each with 100 categories the number of categories to only! More than one checking the specifications in the SSC mentioned here and votes can not be cast, J... Recently tested a regression with a million observations and three fixed effects, each with 100.. Number of panel units that can deal with multiple high dimensional fixed effects preserve and restore to keep data! The insight about the standard errors as reg with dummy variables within clusters to know what 're... Will be intolerably slow for very large datasets fe //this makes id-specific fixed,! You 've laid out to be slow but I recently tested a regression with a observations... You did not declare your time fe 's instead of putting in dummies so I 'm optimistic curious to... Be god practice ) with reg and fixed effects are nested within clusters standard errors the same errors... What if you have more than one SSC mentioned here Hi, Thanks for making reghdfe the original.... Cross-Product matrix ) calculating the number of categories to 10,000 only tripled the execution.... Keyboard shortcuts the original post analyze, including firm- and year fixed effects, because the errors! One fixed effect, but the standard errors xtreg command are slightly larger in... About that issue are known, and not computationally expensive sufficient to correct the standard errors reg. There is -reghdfe- on SSC which is an interative process that can deal with high.

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