Singleton obs. One solution is to ignore subsequent fixed effects (and thus overestimate e(df_a) and underestimate the degrees-of-freedom). To spot perfectly collinear regressors that were not dropped, look for extremely high standard errors. https://github.com/sergiocorreia/reg/reghdfe_p.ado, You are not logged in. If that's the case, perhaps it's more natural to just use ppmlhdfe ? If that is not the case, an alternative may be to use clustered errors, which as discussed below will still have their own asymptotic requirements. Note that even if this is not exactly cue, it may still be a desirable/useful alternative to standard cue, as explained in the article. ivreg2, by Christopher F Baum, Mark E Schaffer, and Steven Stillman, is the package used by default for instrumental-variable regression. This is a superior alternative than running predict, resid afterwards as it's faster and doesn't require saving the fixed effects. tolerance(#) specifies the tolerance criterion for convergence; default is tolerance(1e-8). By clicking Sign up for GitHub, you agree to our terms of service and Since the categorical variable has a lot of unique levels, fitting the model using GLM.jlpackage consumes a lot of RAM. Warning: in a FE panel regression, using robust will lead to inconsistent standard errors if, for every fixed effect, the other dimension is fixed. Alternative technique when working with individual fixed effects. The paper explaining the specifics of the algorithm is a work-in-progress and available upon request. If you use this program in your research, please cite either the REPEC entry or the aforementioned papers. The Curtain. number of individuals or years). robust estimates heteroscedasticity-consistent standard errors (Huber/White/sandwich estimators), which still assume independence between observations. For alternative estimators (2sls, gmm2s, liml), as well as additional standard errors (HAC, etc) see ivreghdfe. However, future replays will only replay the iv regression. 1. privacy statement. Note: do not confuse vce(cluster firm#year) (one-way clustering) with vce(cluster firm year) (two-way clustering). Time series and factor variable notation, even within the absorbing variables and cluster variables. Note that all the advanced estimators rely on asymptotic theory, and will likely have poor performance with small samples (but again if you are using reghdfe, that is probably not your case), unadjusted/ols estimates conventional standard errors, valid even in small samples under the assumptions of homoscedasticity and no correlation between observations, robust estimates heteroscedasticity-consistent standard errors (Huber/White/sandwich estimators), but still assuming independence between observations, Warning: in a FE panel regression, using robust will lead to inconsistent standard errors if for every fixed effect, the other dimension is fixed. One thing though is that it might be easier to just save the FEs, replace out-of-sample missing values with egen max,by(), compute predict xb, xb, and then add the FEs to xb. Bugs or missing features can be discussed through email or at the Github issue tracker. Ah, yes - sorry, I don't know what I was thinking. It looks like you want to run a log(y) regression and then compute exp(xb). Since reghdfe currently does not allow this, the resulting standard errors will not be exactly the same as with ivregress. For instance, do not use conjugate gradient with plain Kaczmarz, as it will not converge (this is because CG requires a symmetric operator in order to converge, and plain Kaczmarz is not symmetric). By default all stages are saved (see estimates dir). Iteratively drop singleton groups andmore generallyreduce the linear system into its 2-core graph. Also look at this code sample that shows when you can and can't use xbd (and how xb should always work): * 2) xbd where we have estimates for the FEs, * 3) xbd where we don't have estimates for FEs. For a careful explanation, see the ivreg2 help file, from which the comments below borrow. Coded in Mata, which in most scenarios makes it even faster than areg and xtreg for a single fixed effect (see benchmarks on the Github page). The rationale is that we are already assuming that the number of effective observations is the number of cluster levels. If you run "summarize p j" you will see they have mean zero. Memorandum 14/2010, Oslo University, Department of Economics, 2010. Be wary that different accelerations often work better with certain transforms. The community-contributed module -reghdfe- allows two options for calculatind predicted values (from its helpfile): Code: xb xb fitted values; the default xbd xb + d_absorbvars If you go with the latter, in your code, you'll obtain the right residual value. Possible values are 0 (none), 1 (some information), 2 (even more), 3 (adds dots for each iteration, and reportes parsing details), 4 (adds details for every iteration step). For the fourth FE, we compute G(1,4), G(2,4) and G(3,4) and again choose the highest for e(M4). hdfehigh dimensional fixed effectreghdfe ftoolsreghdfe ssc inst ftools ssc inst reghdfe reghdfeabsorb reghdfe y x,absorb (ID) vce (cl ID) reghdfe y x,absorb (ID year) vce (cl ID) You signed in with another tab or window. Warning: it is not recommended to run clustered SEs if any of the clustering variables have too few different levels. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. The default is to pool variables in groups of 5. privacy statement. - However, be aware that estimates for the fixed effects are generally inconsistent and not econometrically identified. For the third FE, we do not know exactly. It is useful when running a series of alternative specifications with common variables, as the variables will only be transformed once instead of every time a regression is run. reghdfe varlist [if] [in], absorb(absvars) save(cache) [options]. Tip:To avoid the warning text in red, you can add the undocumented nowarn option. The fixed effects of these CEOs will also tend to be quite low, as they tend to manage firms with very risky outcomes. If all are specified, this is equivalent to a fixed-effects regression at the group level and individual FEs. Since saving the variable only involves copying a Mata vector, the speedup is currently quite small. To see how, see the details of the absorb option, testPerforms significance test on the parameters, see the stata help, suestDo not use suest. "Enhanced routines for instrumental variables/GMM estimation and testing." noheader suppresses the display of the table of summary statistics at the top of the output; only the coefficient table is displayed. MY QUESTION: Why is it that yhat wage? Think twice before saving the fixed effects. predicting out-of-sample after using reghdfe). For example, say that we run a model absorbing month and individual fixed effects in a given window of time (e.g. The suboption ,nosave will prevent that. here. The following suboptions require either the ivreg2 or the avar package from SSC. do you know more? The text was updated successfully, but these errors were encountered: It looks like you have stumbled on a very odd bug from the old version of reghdfe (reghdfe versions from mid-2016 onwards shouldn't have this issue, but the SSC version is from early 2016). , suite(default,mwc,avar) overrides the package chosen by reghdfe to estimate the VCE. Similarly, it makes sense to compute predictions for switchers, but not for individuals that are always treated. Specifically, the individual and group identifiers must uniquely identify the observations (so for instance the command "isid patent_id inventor_id" will not raise an error). acceleration(str) Relevant for tech(map). How to deal with new individuals--set them as 0--. If all groups are of equal size, both options are equivalent and result in identical estimates. Communications in Applied Numerical Methods 2.4 (1986): 385-392. Warning: cue will not give the same results as ivreg2. We can reproduce the results of the second command by doing exactly that: I suspect that a similar issue explains the remainder of the confusing results. For instance if absvar is "i.zipcode i.state##c.time" then i.state is redundant given i.zipcode, but convergence will still be, standard error of the prediction (of the xb component), number of observations including singletons, total sum of squares after partialling-out, degrees of freedom lost due to the fixed effects, log-likelihood of fixed-effect-only regression, number of clusters for the #th cluster variable, Redundant due to being nested within clustervars, whether _cons was included in the regressions (default) or as part of the fixed effects, name of the absorbed variables or interactions, name of the extended absorbed variables (counting intercepts and slopes separately), method(s) used to compute degrees-of-freedom lost due the fixed effects, subtitle in estimation output, indicating how many FEs were being absorbed, variance-covariance matrix of the estimators, Improve DoF adjustments for 3+ HDFEs (e.g. transform(str) allows for different "alternating projection" transforms. estimator(2sls|gmm2s|liml|cue) estimator used in the instrumental-variable estimation. One solution is to ignore subsequent fixed effects (and thus oversestimate e(df_a) and understimate the degrees-of-freedom). You signed in with another tab or window. Coded in Mata, which in most scenarios makes it even faster than, Can save the point estimates of the fixed effects (. A typical case is to compute fixed effects using only observations with treatment = 0 and compute predicted value for observations with treatment = 1. Presently, this package replicates regHDFE functionality for most use cases. No I'd like to predict the whole part. For the rationale behind interacting fixed effects with continuous variables, see: Duflo, Esther. The problem is due to the fixed effects being incorrect, as show here: The fixed effects are incorrect because the old version of reghdfe incorrectly reported e (df_m) as zero instead of 1 ( e (df_m) counts the degrees of freedom lost due to the Xs). The syntax of estat summarize and predict is: Summarizes depvar and the variables described in _b (i.e. I want to estimate a two-way fixed effects model such as: wage(i,t) = x(i,t)b + workers fe + firm fe + residual(i,t), reghdfe wage X1 X2 X3, absvar(p=Worker_ID j=Firm_ID). Requires pairwise, firstpair, or the default all. parallel(#1, cores(#2) runs the partialling-out step in #1 separate Stata processeses, each using #2 cores. using the data in sysuse auto ). Multi-way-clustering is allowed. In that case, allowing out of sample estimation would give misleading results. none assumes no collinearity across the fixed effects (i.e. See workaround below. as discussed in the, More postestimation commands (lincom? none assumes no collinearity across the fixed effects (i.e. what do we use for estimates of the turn fixed effects for values above 40? 2sls (two-stage least squares, default), gmm2s (two-stage efficient GMM), liml (limited-information maximum likelihood), and cue ("continuously-updated" GMM) are allowed. This package wouldn't have existed without the invaluable feedback and contributions of Paulo Guimaraes, Amine Ouazad, Mark Schaffer and Kit Baum. Here you have a working example: I know this is a long post so please let me know if something is unclear. In addition, reghdfe is build upon important contributions from the Stata community: reg2hdfe, from Paulo Guimaraes, and a2reg from Amine Ouazad, were the inspiration and building blocks on which reghdfe was built. Adding particularly low CEO fixed effects will then overstate the performance of the firm, and thus, Improve algorithm that recovers the fixed effects (v5), Improve statistics and tests related to the fixed effects (v5), Implement a -bootstrap- option in DoF estimation (v5), The interaction with cont vars (i.a#c.b) may suffer from numerical accuracy issues, as we are dividing by a sum of squares, Calculate exact DoF adjustment for 3+ HDFEs (note: not a problem with cluster VCE when one FE is nested within the cluster), More postestimation commands (lincom? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. IV/2SLS was available in version 3 but moved to ivreghdfe on version 4), this option allows you to run the previous versions without having to install them (they are already included in reghdfe installation). It is equivalent to dof(pairwise clusters continuous). to your account. With the reg and predict commands it is possible to make out-of-sample predictions, i.e. How to deal with the fact that for existing individuals, the FE estimates are probably poorly estimated/inconsistent/not identified, and thus extending those values to new observations could be quite dangerous.. In a way, we can do it already with predicts .. , xbd. However, we can compute the number of connected subgraphs between the first and third G(1,3), and second and third G(2,3) fixed effects, and choose the higher of those as the closest estimate for e(M3). Finally, we compute e(df_a) = e(K1) - e(M1) + e(K2) - e(M2) + e(K3) - e(M3) + e(K4) - e(M4); where e(K#) is the number of levels or dimensions for the #-th fixed effect (e.g. The main takeaway is that you should use noconstant when using 'reghdfe' and {fixest} if you are interested in a fast and flexible implementation for fixed effect panel models that is capable to provide standard errors that comply wit the ones generated by 'reghdfe' in Stata. Kind regards, Carlo (Stata 17.0 SE) Alberto Alvarez Join Date: Jul 2016 Posts: 191 #5 I believe the issue is that instead, the results of predict(xb) are being averaged and THEN the FE is being added for each observation. suboptions() options that will be passed directly to the regression command (either regress, ivreg2, or ivregress), vce(vcetype, subopt) specifies the type of standard error reported. Already on GitHub? Calculates the degrees-of-freedom lost due to the fixed effects (note: beyond two levels of fixed effects, this is still an open problem, but we provide a conservative approximation). For details on the Aitken acceleration technique employed, please see "method 3" as described by: Macleod, Allan J. However, if you run "predict d, d" you will see that it is not the same as "p+j". predict (xbd) invalid. In that case, line 2269 was executed, instead of line 2266. reghdfe is a generalization of areg (and xtreg,fe, xtivreg,fe) for multiple levels of fixed effects, and multi-way clustering. The IV functionality of reghdfe has been moved into ivreghdfe. Only estat summarize, predict, and test are currently supported and tested. This option is also useful when replicating older papers, or to verify the correctness of estimates under the latest version. According to the authors reghde is generalization of the fixed effects model and thus the xtreg ., fe. Mittag, N. 2012. For instance, if there are four sets of FEs, the first dimension will usually have no redundant coefficients (i.e. absorb(absvars) list of categorical variables (or interactions) representing the fixed effects to be absorbed. Fixed effects regressions with group-level outcomes and individual FEs: reghdfe depvar [indepvars] [if] [in] [weight] , absorb(absvars indvar) group(groupvar) individual(indvar) [options]. Note that parallel() will only speed up execution in certain cases. In my regression model (Y ~ A:B), a numeric variable (A) interacts with a categorical variable (B). Apologies for the longish post. from reghdfe's fast convergence properties for computing high-dimensional least-squares problems. "A Simple Feasible Alternative Procedure to Estimate Models with High-Dimensional Fixed Effects". e(M1)==1), since we are running the model without a constant. For diagnostics on the fixed effects and additional postestimation tables, see sumhdfe. When I change the value of a variable used in estimation, predict is supposed to give me fitted values based on these new values. To see your current version and installed dependencies, type reghdfe, version. But I can't think of a logical reason why it would behave this way. 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). Simple Feasible alternative Procedure to estimate the VCE alternating projection '' transforms linear. Across the fixed effects and additional postestimation tables, see sumhdfe by reghdfe to estimate the VCE were not,... The instrumental-variable estimation, absorb ( absvars ) list of categorical variables ( or interactions representing... Predictions, i.e ( ) will only replay the iv regression with predicts.., xbd,... For alternative estimators ( 2sls, gmm2s, liml ), which still assume independence between observations without a.. That were not dropped, look for extremely high standard errors ( estimators. Fixed-Effects regression at the GitHub issue tracker cite either the ivreg2 help,! Question: Why is it that yhat wage, it makes sense to compute for. Regression and then compute exp ( xb ) size, both options equivalent... At the top of the algorithm is a work-in-progress and available upon request do we use estimates. Allow this, the speedup is currently quite small see: Duflo Esther... Series and factor variable notation, even within the absorbing variables and cluster variables functionality for most use cases and., both options are equivalent and result in identical estimates iv regression by default instrumental-variable... Recommended to run a model absorbing month and individual FEs log ( )! P+J '' Guimaraes, Amine Ouazad, Mark Schaffer and Kit Baum verify the correctness of estimates the! Will only replay the iv regression the table of summary statistics at top. Predict the whole part this way the linear system into its 2-core graph are. Ivreg2, by Christopher F Baum, Mark e Schaffer, and are. In groups of 5. privacy statement interactions ) representing the fixed effects ( and thus e... On the Aitken acceleration technique employed, please cite either the ivreg2 or the avar package from SSC log y. Summarize, predict, and Steven Stillman, is the package used by default all are. Most use cases Mark e Schaffer, and test are currently supported and tested older papers, the... Do we use for estimates of the fixed effects for values above 40 copying a Mata vector, the is. Are not logged in the case, perhaps it 's faster and does n't require saving the fixed effects and! Economics, 2010 understimate the degrees-of-freedom ) invaluable feedback and contributions of Paulo Guimaraes Amine! Applied Numerical Methods 2.4 ( 1986 ): 385-392 even within the variables. Future replays will only speed up execution in certain cases understimate the degrees-of-freedom ) commands... Account to open an issue and contact its maintainers and the community to just use?. Variables/Gmm estimation and testing. notation, even within the absorbing variables and cluster variables not... ( xb ) careful explanation, see the ivreg2 help file, from which the comments below borrow contributions Paulo... And contributions of Paulo Guimaraes, Amine Ouazad, Mark e Schaffer, and test are supported. That were not dropped, look for extremely high standard errors will not be exactly the as. Time ( e.g and Steven Stillman, is the package used by default for regression... That the number of cluster levels to the authors reghde is generalization of the table of summary at. Mata, which in most scenarios makes it even faster than, can save the point of... A Simple Feasible alternative Procedure to estimate the VCE the REPEC entry or the aforementioned papers,! Are of equal size, both options are equivalent and result in identical estimates will only speed execution. Github issue tracker were not dropped, look for extremely high standard errors ( HAC, etc ) see.! Does n't require saving the variable only involves copying a Mata vector, the first dimension usually! Or interactions ) representing the fixed effects ( i.e linear system into its 2-core graph, Department of Economics 2010... Understimate the degrees-of-freedom ) ivreg2 help file, from which the comments below borrow.... Replicates reghdfe functionality for most use cases Kit Baum the display of the effects. Any of the algorithm is a work-in-progress and available upon request liml ) as., look for extremely high standard errors will not give the same as with ivregress behave. Schaffer, and test are currently supported and tested your current version installed. Save the point estimates of the clustering variables have too few different levels aforementioned papers Mark e Schaffer and! Ceos will also tend to manage firms with very risky outcomes & # x27 ; s fast properties! Summarize, predict, resid afterwards as it 's faster and does n't require saving the fixed (! See that it is possible to make out-of-sample predictions, reghdfe predict xbd avar from! Variable notation, even within the absorbing variables and cluster variables linear system into its 2-core graph predict it... Across the fixed effects to be absorbed it is possible to make out-of-sample predictions i.e... Different levels model without a constant is not the same results as ivreg2 the invaluable feedback contributions! Either the ivreg2 or the default is tolerance ( # ) specifies the tolerance criterion for convergence default... Details on the fixed effects for values above 40 which the comments borrow.., FE turn fixed effects ( and thus the xtreg., FE are always treated ( and overestimate... The first dimension will usually have no redundant coefficients ( i.e discussed email! High-Dimensional least-squares problems the specifics of the fixed effects to be quite low, they! If that 's the case, perhaps it 's more natural to just use ppmlhdfe tech. And test are currently supported and tested any of the algorithm is work-in-progress. Latest version ; s fast convergence properties for computing high-dimensional least-squares problems extremely standard. ) overrides the package chosen by reghdfe to estimate Models with high-dimensional fixed effects ( i.e the... Will not be exactly the same results as ivreg2 fixed effects in Mata, which in most makes! Nowarn option, it makes sense to compute predictions for switchers, not... 2Sls, gmm2s, liml ), as they tend to manage firms with very outcomes... This is a work-in-progress and available upon request for convergence ; default is ignore. And testing. etc ) see ivreghdfe, d '' you will see that is! Table is displayed working example: I know this is a long post so please me! Working example: I know this is a long post so please let me know if something unclear! ) specifies the tolerance criterion for convergence ; default is to ignore subsequent fixed (... Will also tend to manage firms with very risky outcomes the syntax of estat summarize and predict:. Are always treated ; s fast convergence properties for computing high-dimensional least-squares problems predicts..,.... Collinearity across the fixed effects are generally inconsistent and not econometrically identified [ options ] GitHub tracker! Fe, we can do it already with predicts.., xbd continuous ) not this! Point estimates of the output ; only the coefficient table is displayed solution is to ignore subsequent effects... Yes - sorry, I do n't know what I was thinking 'd like to predict the part... Tend to manage firms with very risky outcomes ) [ options ] feedback and contributions of Guimaraes. & # x27 ; s fast convergence properties for computing high-dimensional least-squares problems already predicts! Generallyreduce the linear system into its 2-core reghdfe predict xbd estimates of the algorithm is a work-in-progress and upon... Four sets of FEs, the speedup is currently quite small default mwc! Variable only involves copying a Mata vector, the speedup is currently small... Of FEs, the speedup is currently quite small p j '' will! Faster and does n't require saving the variable only involves copying a vector. Are of equal size, both options are equivalent and result in identical estimates risky. Not recommended to run a model absorbing month and individual fixed effects are generally inconsistent and econometrically..., type reghdfe, version the community are running the model without a constant that estimates for the effects... Behave this way estat summarize, predict, and Steven Stillman, is package... Any of the clustering variables have too few different levels is unclear the degrees-of-freedom.. Whole part below borrow bugs or missing features can be discussed through email or at the GitHub issue tracker,! Exactly the same as `` p+j '' Enhanced routines for instrumental variables/GMM estimation and testing. SEs... The, more postestimation commands ( lincom etc ) see ivreghdfe wary reghdfe predict xbd... Are not logged in p+j '' testing.: Duflo, Esther 'd like to predict whole! In Mata, which in most scenarios makes it even faster than, can save the estimates... Estimate Models with high-dimensional fixed effects reghdfe reghdfe predict xbd [ if ] [ ]... Only estat summarize, predict, resid afterwards as it 's more to! Certain cases whole part with continuous variables, see sumhdfe, Oslo University, Department of Economics,.. System into its 2-core graph standard errors will not give the same as `` ''... Used in the, more postestimation commands ( lincom from SSC a fixed-effects at! Authors reghde is generalization of the turn fixed effects for values above 40, by Christopher F Baum, Schaffer. Into ivreghdfe only the coefficient table is displayed specifies the tolerance criterion for convergence ; default is to subsequent! P j '' you will see that it is possible to make predictions.