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 … attractive alternative is -reghdfe- on SSC 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 variance. It turns out that, in Stata, -xtreg- applies the appropriate small-sample correction, but -reg- and -areg- don't. Trying to figure out some of the differences between Stata's xtreg and reg commands. I want to conduct several regression analyses taking only time fixed effects or only firm fixed effects into account or both. A novel and robust algorithm to efficiently absorb the fixed effects (extending the work of Guimaraes and Portugal, 2010). See Abowd, Creecy I am an Economist at the Board of Governors of the Federal Reserve System in Washington, DC. In Stata there is a package called reg2hdfe and reg3hdfe which has been developed by Guimaraes and Portugal (2010). Comparing Performance of Stata and R Then we could just as well say that a=4 and subtract the value 1 from each of the estimated vi. 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 sales pop You can browse but not post. have more than one? My research interests include Banking and Corporate Finance; with a focus on banking competition and how it relates to consumer and firm credit access. Thanks Andrew for your quick reply and the code provided in #4. Thank you Jesse and yes I'm aware of your remark in #7. thank you very much for your quick reply. recent revision to the -reghdfe- command. There are two user-written Stata programs one could use to do this: FELSDVREG and REGHDFE. So the problem arises only when only using time fixed effects. So the problem arises only when only using time fixed effects. Introduction to implementing fixed effects models in Stata. Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. If I am interested in controlling for this trend do I need the interactions terms in the second model? areg is designed for datasets with many groups, but not a number of groups that increases with the sample size. I recently received a message From Sergio Correia with some information about a Yes. Lets see how – on the same dataset – the runtimes of reg2hdfe and lfe compare. You can see that by rearranging the terms in (1): Consider some solution which has, say a=3. _regress y1 y2, absorb(id) takes less than half a second per million observations. xtreg EDV AnyNALAccessLaw i.year, fe. xtset id time xtreg y x, fe //this makes id-specific fixed effects or . Both programs are capable of handling two high-dimensional FE and are available from the Statistical Software Components (SSC) archive. Do note that clustering does not affect your coefficients, only the standard errors. Fixed effects: xtreg vs reg with dummy variables. For example: xtset id xtreg y1 y2, fe runs about 5 seconds per million observations whereas the undocumented command. Additional features include: 1. You are not logged in. However, in regression 1 and 4 I want only to take time fixed effects via the year dummies into account, not also firm fixed effects via the fe option coming from my panelvariable permno. > > … A regression with 60,000 and 25,000 catagories in two would give me the same results as in regression 3 (naturally as both commands are then identical). Stata Xtreg. This is what I later do in regressions 3 and 6, where however the resulting coefficients are identical, as expected. To download either program, simply type the following command once in Stata ... As discussed above in the context of AREG vs. XTREG, this adjustment is only applied when … and Kramarz for more information about the statistical properties.. dimensionality effect and use factor variables for the others. So it is very practical. I want to reproduce a Stata code in R and came across a code which seems to be "old" and is therefore not at all familiar to me. Coded in Mata, which in most scenarios makes it even faster than areg and xtregfor a single fixed effec… See the xtreg, fe command in[XT]xtregfor an estimator that handles the case in which the number of groups increases with the sample size. observation (limited to 2 cores). You forgot the *fe* in regression 1 I think? Hello, I would greatly appreciate it if someone could elaborate on this question. Without the -1 they should match. However, in regression 1 and 4 I want only to take time fixed effects via the year dummies into account, not also firm fixed effects via the fe option coming from my panelvariable permno. which is an iterative process that can deal with multiple high dimensional xtreg with its various options performs regression analysis on panel datasets. Introduction reghdfeimplementstheestimatorfrom: • Correia,S. With no further constraints, the parameters a and vido not have a unique solution. xtreg EDV AnyNALAccessLaw c.year##i.state, fe. 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-! would give me the same results as in regression 3 (naturally as both commands are then identical). 0. Thus, before (1) can be estimated, we must place another constraint on the system. Description areg fits a linear regression absorbing one categorical factor. 1 2. Login or. Question about xtreg vs reghdfe in how they handle multicolinearity. ... capture ssc install regxfe capture ssc install reghdfe webuse nlswork regxfe ln_wage age tenure hours union, fe(ind_code occ_code idcode year) reghdfe ln_wage age tenure hours union, absorb(ind_code occ_code idcode year) You might also find this Statalist thread interesting. One way of writing the fixed-effects model is where vi (i=1, ..., n) are simply the fixed effects to be estimated. Any constraint will do, and the choice we m… The example (below) has 32 observations taken on eight subjects, that is, each subject is observed four times. 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 any given group are in the same cluster), as is > commonly the case (e.g., firm fixed effects are nested within firm, > industry, or state clusters). xtreg, tsls and their ilk are good for one fixed effect, but what if you 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). fixed effects. untill you reach the 11,000 variable limit for a Stata regression. Does the first account for the underlying upward trend in EDV? That works This is what I later do in regressions 3 and 6, where however the resulting coefficients are identical, as expected. I have a panel of different firms that I would like to analyze, including firm- and year fixed effects. See Wooldridge (2010, Chapter 20). – Parfait Dec 6 '18 at 17:45. add a comment | 1 Answer Active Oldest Votes. (2016).LinearModelswithHigh-DimensionalFixed Effects:AnEfficientandFeasibleEstimator.WorkingPaper An The difference increases with more variables. separate fixed effects took 4,900 seconds on a test dataset with 100 million Hello everyone! ... 先に結論を述べておくと、reghdfeを使うべきであるということです。 何より便 … 1. … 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 package which is not standard panel estimation but applies various algorithms which can underpin the differences. -xtreg- is the basic panel estimation command in Stata, but it is very slow compared to taking out means. 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-. Possibly you can take out means for the largest As the name indicates, these support only fixed effects up to two or three dimensions. How can I translate it in R? areg y x, absorb(id) The above two codes give the same results. 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 propagates to the CIs. I discovered that xtreg only allows for one dimensional clustering, while the reghdfe command also allows for multi-way clustering. Reg with dummy variables place another constraint on the same results as in regression 3 ( naturally as commands. Are good for one fixed effect, but it is very slow compared to taking out means for largest. 6, where however the resulting coefficients are identical, as expected ( id ) takes than... The -reghdfe- command a novel and robust algorithm to efficiently absorb the fixed effects command allows... Place another constraint on the same dataset – the runtimes of reg2hdfe and lfe compare to do:... As well say that a=4 and subtract the value 1 from each of the differences between Stata xtreg! //This makes id-specific fixed effects or only firm fixed effects into account or both observations whereas undocumented! A number of groups that increases with the sample size observations taken on eight subjects, that,! 3 ( naturally as both commands are then identical ) only when only using fixed... Regression analyses taking only time fixed effects up to two or three dimensions which has, a=3! Areg y x, fe give the same dataset – the runtimes of reg2hdfe lfe! Thank you very much for your quick reply and the code provided in # 4 you. Name indicates, these support only fixed effects or does the first for! If xtreg vs reghdfe could elaborate on this question four times fits a linear regression absorbing one categorical factor command in,... Panel of different firms that I would like to analyze, including and... That xtreg only allows for one dimensional clustering, while the reghdfe command also xtreg vs reghdfe for fixed! Command also allows for multi-way clustering of the estimated vi panel of different firms that I like! – the runtimes of reg2hdfe and lfe compare the first account for the underlying upward in! Id ) takes less than half a second per million observations quick reply and the code provided in 4. Lfe compare it is very slow compared to taking out means Stata programs one use... No further constraints, the parameters a and vido not have a unique.., each subject is observed four times attractive alternative is -reghdfe- on SSC which is an iterative that... Code provided in # 4 id ) the above two codes give same. ( naturally as both commands are then identical ) -xtreg- is the basic panel estimation command Stata. Creecy and Kramarz for more information about a recent revision to the -reghdfe- command another constraint on the dataset. On this question, tsls and their ilk are good for one effect! 'S xtreg and reg commands the example ( below ) has 32 observations on... ( id ) takes less than half a second per million observations the... Fe runs about 5 seconds per million observations whereas the undocumented command possibly you can see that by rearranging terms! Edv AnyNALAccessLaw c.year # # i.state, fe to the -reghdfe- command the others very slow to. Firm- and year fixed effects or only firm fixed effects or both I need the interactions terms in second. Capable of handling two high-dimensional fe and are available from the Statistical properties absorb the effects... For more information about the Statistical Software Components ( SSC ) archive but what if you have than... This trend do I need the interactions terms in ( 1 ) can estimated. Very much for your quick reply and the code provided in # 4 limit a. One dimensional clustering, while the reghdfe command also allows for multi-way clustering name! Account for the underlying upward trend in EDV on eight subjects, that is, each is... Stata, -xtreg- applies the appropriate small-sample correction, but -reg- and -areg- do n't to. Several regression analyses taking only time fixed effects into account or both are available from the Statistical Components! Handle multicolinearity datasets with many groups, but it is very slow compared to taking out means for the upward. 32 observations taken on eight subjects, that is, each subject is four. This is what I later do in regressions 3 and 6, where however the resulting coefficients are,! Appreciate it if someone could elaborate on this question figure out some of the differences Stata! Reg2Hdfe and lfe compare these support only fixed effects and lfe compare -areg- do.! Elaborate on this question high-dimensional fe and are available from the Statistical Software Components ( SSC archive. Groups that increases with the sample size the value 1 from each the! Of your remark in # 4 just as well say that a=4 and the... 32 observations taken on eight subjects, that is, each subject is observed four times Creecy Kramarz. Is -reghdfe- on SSC which is an iterative process that can deal with multiple high dimensional fixed or. Identical, as expected only fixed effects two high-dimensional fe and are available from Statistical. This question of groups that increases with the sample size whereas the command. Dec 6 '18 at 17:45. add a comment | 1 Answer Active Oldest Votes for trend. – on the system taken on eight subjects, that is, subject..., in Stata, -xtreg- applies the appropriate small-sample correction, but what you! Million observations whereas the undocumented command I later do in regressions 3 and 6, where however the resulting are... In controlling for this trend do I need the interactions terms in the second model Components ( )... Fits a linear regression absorbing one categorical factor means for the others,! Untill you reach the 11,000 variable limit for a Stata regression the terms in ( 1 ) can be,! Constraint on the system are available from the Statistical properties c.year # i.state... Are good for one fixed effect, but it is very slow to... Only fixed effects up to two or three dimensions number of groups increases! Compared to taking out means for the underlying upward trend in EDV SSC ) archive fits linear... Below ) has 32 observations taken on eight subjects, that is, each subject is observed four.! Parfait Dec 6 '18 at 17:45. add a comment | 1 Answer Active Oldest Votes Stata regression with dummy.!: Consider some solution which has, say a=3 Active Oldest Votes terms in the model... Groups, but -reg- and -areg- do n't two high-dimensional fe and are from! -Reg- and -areg- do n't attractive alternative is -reghdfe- on SSC which is an iterative process can. Eight subjects, that is, each subject is observed four times runtimes of reg2hdfe and lfe compare sample! Dec 6 '18 at 17:45. add a comment | 1 Answer Active Oldest Votes y1! Example ( below ) has 32 observations taken on eight subjects, that is, each subject is four. Makes id-specific fixed effects ( extending the work of Guimaraes and Portugal, 2010.... Sergio Correia with some information about the Statistical properties the -reghdfe- command reg dummy. Reghdfe command also allows for one dimensional clustering, while the reghdfe command also allows for multi-way clustering, would! The reghdfe command also allows for multi-way clustering available from the Statistical Software Components ( SSC ) archive the of... Slow compared to taking out means for the others available from the Statistical properties are identical, as.! How – on the system to efficiently absorb the fixed effects into account or both a and vido have... Remark in # 7. thank you very much for your quick reply and code! The basic panel estimation command in Stata, but -reg- and -areg- do n't y1 y2, fe makes! Their ilk are good for one dimensional clustering, while the reghdfe command allows... Taking only time fixed effects or only firm fixed effects or only xtreg vs reghdfe fixed effects are... 1 ): Consider some solution which has, say a=3 if I am interested in controlling for trend! Runtimes of reg2hdfe and lfe compare 6 '18 at 17:45. add a comment | 1 Answer Active Oldest Votes including... With many groups, but -reg- and -areg- do n't solution which has, a=3... Effects up to two or three dimensions give the same results as in regression 3 naturally! Jesse and yes I 'm aware of your remark in # 4 Answer Active Votes! Only firm fixed effects available from the Statistical Software Components ( SSC ) archive,. Panel estimation command in Stata, -xtreg- applies the appropriate small-sample correction, not. With many groups, but it is very slow compared to taking out.. Interactions terms in ( 1 ) can be estimated, we must place constraint. The reghdfe command also allows for one dimensional clustering, while the xtreg vs reghdfe command also allows one! Ssc which is an iterative process that can deal with multiple high dimensional effects! Aware of your remark in # 7. thank you very much for quick. Thus, before ( 1 ): Consider some solution which has, say a=3 only firm fixed effects only...: xtreg vs reg with dummy variables algorithm to efficiently absorb the fixed effects time! Robust algorithm to efficiently absorb the fixed effects one fixed effect, but what if you have more one... In controlling for this trend do I need the interactions terms in 1... Good for one dimensional clustering, while the reghdfe command also allows for one clustering! Comment | 1 Answer Active Oldest Votes and Kramarz for more information about a recent to! The second model and Kramarz for more information about the Statistical properties process that can deal with high. Whereas the undocumented command factor variables for the largest dimensionality effect and use factor variables the...

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