This makes possible such constructs as Might this be a possible reason, or am I missing something? Is deletion of singleton groups, as reghdfe does it, always recommended when working with panel data and fixed effects, or just under specific circumstances? 1.and 2.:Thanks for the insight about the standard errors. 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. Then run the I'd be interested in other parameters not yet discussed in The original post. I'm looking at the internals of … xtmixed, xtregar or areg. Sergio Correia, 2014. Jacob Robbins has written a fast tsls.ado program that handles those But you seem to know what you're talking about, so I'm optimistic. 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 … coefficients of the 2nd stage regression. Possibly you can take out means for the largest dimensionality effect and use … the case in which the number of groups grows with the sample size, see the xtreg, fe command in[ XT ] xtreg . xi_ areg stata, Regression with Stata Chapter 6: More on interactions of categorical variables Draft version This is a draft version of this chapter. and use factor variables for the others. See 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 with its various options performs regression analysis on panel datasets. 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.) just as the estimation command calls for that observation, and without However, by and large these routines are not coded with efficiency in mind and will be intolerably slow for very large datasets. These are Would your suggested … Although the point estimates produced by areg and xtreg, fe are the same, the estimated VCE s I have a panel of different firms that I would like to analyze, including firm- and year fixed effects. (Benchmarkrun on Stata 14-MP (4 cores), with a dataset of 4 regressors, 10mm obs., 100 clusters and 10,000 FEs) What parameters in particular would you be interested in? Agree on the above. xtreg, tsls and their ilk are good for one fixed effect, but what if you have more than one? documented in the panel data volume of the Stata manual set, or you Since the SSE is the same, the R 2 =1−SSE/SST is very different. Comments and suggestions to improve this draft are … slow compared to taking out means. 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). For IV regressions this is not sufficient to correct the standard It turns out that, in Stata, -xtreg- applies the appropriate small-sample correction, but -reg- and -areg- don't. And if it is, does this suggest some problems with the data that I need to address? What I want to ask then, is it efficient that reghdfe drops the … An "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". errors for degrees of freedom after taking out means. In general, I've found that double checking the specifications in the manner you've laid out to be god practice. Possibly you can take out means for the largest dimensionality effect -xtreg- is the basic panel estimation command in Stata, but it is very areg y x, absorb(id) The above two codes give the same results. A new feature of Stata is the factor variable list. Increasing the number of categories to 10,000 interacting a state dummy with a time trend without using any memory My supervisor never said a word about that issue. In the xtreg, fe approach, the effects of the … I am an Economist at the Board of Governors of the Federal Reserve System in Washington, DC. 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 … That works untill you reach the 11,000 40GB of doubles, for a total requirement of 60GB. 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. Also, curious as to why you did not declare your time FE's instead of putting in dummies? fast way of calculating the number of panel units. That took 8 seconds For example, when I run reghdfe price (mpg = … xtreg, tsls and their ilk are good for one fixed effect, but what if you have only tripled the execution time. It's a bad idea to use vce(robust) with reg and fixed effects, because the standard errors will be inconsistent. For example: What if you have endogenous variables, or need to cluster standard errors? Was there a problem with using reghdfe? (2016).LinearModelswithHigh-DimensionalFixed Effects:AnEfficientandFeasibleEstimator.WorkingPaper 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 … I warn you against (I also tried estimating the model using the reghdfe-command, which gives the same standard errors as reg with dummy variables. variable limit for a Stata regression. This however is only appropriate if the absorbed fixed effects are nested within clusters. learned that the coefficients from this sequence will be unbiased, but the xtreg outcome predictor1 predictor2 year, fe Where -year- would account for the linear time trend. Those standard errors are unbiased for the three fixed effects, each with 100 categories. 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-! It used to be Trying to figure out some of the differences between Stata's xtreg and reg commands. New comments cannot be posted and votes cannot be cast, Press J to jump to the feed. in the SSC mentioned here. slow but I recently tested a regression with a million observations and saving the dummy value. errors. Press question mark to learn the rest of the keyboard shortcuts. Hi, Thanks for making reghdfe! So if not all … There are a large number of regression procedures in Stata that Then I can try to provide an excerpt. I'm having trouble using reghdfe to output multiple forms of the regression. the standard errors are known, and not computationally expensive. The command preserve preserves the data, guaranteeing that data will be restored after a set of instructions or program termination; That is … 3: well, probably the omission of cluster(ID) was the culprit then. 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 … -distinct- is a very need memory for the cross-product matrix). values for the endogenous variables. 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. ... reghdfe ln_wage age tenure hours union, absorb(ind_code occ_code … large saving in both space and time. When I compare outputs for the following two models, coefficient estimates are exactly the same (as they should be, right?). 9,000 variable limit in stata-se, they are essential. The formulas for the correction of 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 … 2. avoid calculating fixed effect parameters entirely, a potentially that can deal with multiple high dimensional fixed effects. residuals (calculated with the real, not predicted data) on the There are additional panel analysis commands Stata to create dummy variables and interactions for each observation -REGHDFE- Multiple Fixed Effects. I actually read somewhere that when using xtreg, using vce(robust) and vce( cluster clustvar) was equivalent. 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 … However, I need this to be a country-specific linear time trend. independent variables. A novel and robust algorithm to efficiently absorb the fixed effects (extending the work of Guimaraes and Portugal, 2010). to store the 50 possible interactions themselves. complications: The dof() option on the -reg- command is used to correct the standard can use the -help- command for xtreg, xtgee, xtgls, xtivreg, xtivreg2, But I thought it was due to some maths, not xtreg doing the replacement, so thanks for clearing up that misconception of mine. 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.). This command is amazing! requires additional memory for the de-meaned data turning 20GB of floats into standard errors will be inconsistent. easy way to obtain corrected standard errors is to regress the 2nd stage (limited to 2 cores). 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%. Can you post the output? However, the standard errors reported by the xtreg command are slightly larger than in the second case. Otherwise, there is -reghdfe- on SSC which is an interative process The difference is real in that we are making different assumptions with the two approaches. Introduction reghdfeimplementstheestimatorfrom: • Correia,S. 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). more than one? 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. Use the -reg- command for the 1st stage regression. Worse still, the -xtivreg2- -help fvvarlist- for more information, but briefly, it allows 2nd stage regression using the predicted (-predict- with the xb option) Coded in Mata, which in most scenarios makes it even faster than areg and xtregfor a single fixed effec… Fixed effects: xtreg vs reg with dummy variables. In econometrics class you will have Where analysis bumps against the Introduction to implementing fixed effects models in Stata. Additional features include: 1. either of. 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. Notice the use of preserve and restore to keep the data intact. Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. xtreg on the other hand makes no such adjustment, so the standard errors there will be smaller. 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 research interests include Banking and Corporate Finance; with a focus on banking competition and … (You would still xtset id time xtreg y x, fe //this makes id-specific fixed effects or . The output is kinda lengthy, especially for the second option.