avar uses the avar package from SSC. For instance, the option absorb(firm_id worker_id year_coefs=year_id) will include firm, worker and year fixed effects, but will only save the estimates for the year fixed effects (in the new variable year_coefs). (If you are interested in discussing these or others, feel free to contact us), As above, but also compute clustered standard errors, Interactions in the absorbed variables (notice that only the # symbol is allowed), Individual (inventor) & group (patent) fixed effects, Individual & group fixed effects, with an additional standard fixed effects variable, Individual & group fixed effects, specifying with a different method of aggregation (sum). Well occasionally send you account related emails. For instance, vce(cluster firm#year) will estimate SEs with one-way clustering i.e. Can absorb heterogeneous slopes (i.e. By default all stages are saved (see estimates dir). No I'd like to predict the whole part. This difference is in the constant. Sergio Correia Board of Governors of the Federal Reserve Email: sergio.correia@gmail.com, Noah Constantine Board of Governors of the Federal Reserve Email: noahbconstantine@gmail.com. Warning: it is not recommended to run clustered SEs if any of the clustering variables have too few different levels. For the second FE, the number of connected subgraphs with respect to the first FE will provide an exact estimate of the degrees-of-freedom lost, e(M2). This estimator augments the fixed point iteration of Guimares & Portugal (2010) and Gaure (2013), by adding three features: Replace the von Neumann-Halperin alternating projection transforms with symmetric alternatives. privacy statement. This issue is similar to applying the CUE estimator, described further below. predict xbd, xbd Another typical case is to fit individual specific trend using only observations before a treatment. In an i.categorical#c.continuous interaction, we will do one check: we count the number of categories where c.continuous is always zero. You signed in with another tab or window. Alternative syntax: To save the estimates specific absvars, write. Have a question about this project? For diagnostics on the fixed effects and additional postestimation tables, see sumhdfe. reghdfe is a Stata package that runs linear and instrumental-variable regressions with many levels of fixed effects, by implementing the estimator of Correia (2015).. I have tried to do this with the reghdfe command without success. Still trying to figure this out but I think I realized the source of the problem. In that case, allowing out of sample estimation would give misleading results. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. its citations), so using "mean" might be the sensible choice. Supports two or more levels of fixed effects. For simple status reports, set verbose to 1. timeit shows the elapsed time at different steps of the estimation. However, an alternative when using many FEs is to run dof(firstpair clusters continuous), which is faster and might be almost as good. 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: Each acceleration is just a plug-in Mata function, so a larger number of acceleration techniques are available, albeit undocumented (and slower). Here's a mock example. Also invaluable are the great bug-spotting abilities of many users. You can browse but not post. what do we use for estimates of the turn fixed effects for values above 40? However, computing the second-step vce matrix requires computing updated estimates (including updated fixed effects). To save a fixed effect, prefix the absvar with "newvar=". expression(exp( predict(xb) + FE )), but we really want the FE to go INSIDE the predict command: Can absorb individual fixed effects where outcomes and regressors are at the group level (e.g. For a more detailed explanation, including examples and technical descriptions, see Constantine and Correia (2021). Estimate on one dataset & predict on another. A novel and robust algorithm to efficiently absorb the fixed effects (extending the work of Guimaraes and Portugal, 2010). higher than the default). dofadjustments(doflist) selects how the degrees-of-freedom, as well as e(df_a), are adjusted due to the absorbed fixed effects. See the discussion in Baum, Christopher F., Mark E. Schaffer, and Steven Stillman. Note that e(M3) and e(M4) are only conservative estimates and thus we will usually be overestimating the standard errors. 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. 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.. Sign in The most useful are count range sd median p##. The text was updated successfully, but these errors were encountered: To be honest, I am struggling to understand what margins is doing under the hood. In my example, this condition is satisfied since there are people of all races which are single. not the excluded instruments). robust estimates heteroscedasticity-consistent standard errors (Huber/White/sandwich estimators), which still assume independence between observations. ), Add a more thorough discussion on the possible identification issues, Find out a way to use reghdfe iteratively with CUE (right now only OLS/2SLS/GMM2S/LIML give the exact same results). If you want to perform tests that are usually run with suest, such as non-nested models, tests using alternative specifications of the variables, or tests on different groups, you can replicate it manually, as described here. Note: changing the default option is rarely needed, except in benchmarks, and to obtain a marginal speed-up by excluding the pairwise option. Moreover, after fraud events, the new CEOs are usually specialized in dealing with the aftershocks of such events (and are usually accountants or lawyers). group(groupvar) categorical variable representing each group (eg: patent_id). Larger groups are faster with more than one processor, but may cause out-of-memory errors. 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). Note that a workaround can be done if you save the fixed effects and then replace them to the out-of-sample individuals.. something like. Warning: when absorbing heterogeneous slopes without the accompanying heterogeneous intercepts, convergence is quite poor and a tight tolerance is strongly suggested (i.e. predict after reghdfe doesn't do so. ivsuite(subcmd) allows the IV/2SLS regression to be run either using ivregress or ivreg2. fixed effects by individual, firm, job position, and year), there may be a huge number of fixed effects collinear with each other, so we want to adjust for that. tuples by Joseph Lunchman and Nicholas Cox, is used when computing standard errors with multi-way clustering (two or more clustering variables). using only 2008, when the data is available for 2008 and 2009). allowing for intragroup correlation across individuals, time, country, etc). 4. number of individuals + number of years in a typical panel). Note that both options are econometrically valid, and aggregation() should be determined based on the economics behind each specification. Iteratively removes singleton groups by default, to avoid biasing the standard errors (see ancillary document). Requires pairwise, firstpair, or the default all. Sign in This is a superior alternative than running predict, resid afterwards as it's faster and doesn't require saving the fixed effects. If only group() is specified, the program will run with one observation per group. What you can do is get their beta * x with predict varname, xb.. Hi @sergiocorreia, I am actually having the same issue even when the individual FE's are the same. This is because the order in which you include it affects the speed of the command, and reghdfe is not smart enough to know the optimal ordering. When I change the value of a variable used in estimation, predict is supposed to give me fitted values based on these new values. cluster clustervars, bw(#) estimates standard errors consistent to common autocorrelated disturbances (Driscoll-Kraay). Mittag, N. 2012. multiple heterogeneous slopes are allowed together. The complete list of accepted statistics is available in the tabstat help. Multicore support through optimized Mata functions. Introduction reghdfeimplementstheestimatorfrom: Correia,S. where all observations of a given firm and year are clustered together. , suite(default,mwc,avar) overrides the package chosen by reghdfe to estimate the VCE. to run forever until convergence. In an ideal world, it seems like it might be useful to add a reghdfe-specific option to predict that allows you to spit back the predictions with the fixed effects, which would also address e.g. individual, save) and after the reghdfe command is through I store the estimates through estimates store, if I then load the data for the full sample (both 2008 and 2009) and try to get the predicted values through: local version `clip(`c(version)', 11.2, 13.1)' // 11.2 minimum, 13+ preferred qui version `version . If theory suggests that the effect of multiple authors will enter additively, as opposed to the average effect of the group of authors, this would be the appropriate treatment. Even with only one level of fixed effects, it is. Future versions of reghdfe may change this as features are added. However, if you run "predict d, d" you will see that it is not the same as "p+j". However, given the sizes of the datasets typically used with reghdfe, the difference should be small. Interesting, thanks for the explanation. Thus, using e.g. For the fourth FE, we compute G(1,4), G(2,4) and G(3,4) and again choose the highest for e(M4). 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). 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. parallel by George Vega Yon and Brian Quistorff, is for parallel processing. (reghdfe), suketani's diary, 2019-11-21. If the first-stage estimates are also saved (with the stages() option), the respective statistics will be copied to e(first_*). "Acceleration of vector sequences by multi-dimensional Delta-2 methods." Performance is further enhanced by some new techniques we . do you know more? For instance, adding more authors to a paper or more inventors to an invention might not increase its quality proportionally (i.e. For instance, vce(cluster firm year) will estimate SEs with firm and year clustering (two-way clustering). individual), or that it is correct to allow varying-weights for that case. which returns: you must add the resid option to reghdfe before running this prediction. I have the exact same issue (i.e. Anyway you can close or set aside the issue if you want, I am not sure it is worth the hassle of digging to the root of it. reghdfe fits a linear or instrumental-variable regression absorbing an arbitrary number of categorical factors and factorial interactions Optionally, it saves the estimated fixed effects. See workaround below. maxiterations(#) specifies the maximum number of iterations; the default is maxiterations(10000); set it to missing (.) I was trying to predict outcomes in absence of treatment in an student-level RCT, the fixed effects were for schools and years. display_options: noci, nopvalues, noomitted, vsquish, noemptycells, baselevels, allbaselevels, nofvlabel, fvwrap(#), fvwrapon(style), cformat(%fmt), pformat(%fmt), sformat(%fmt), and nolstretch; see [R] Estimation options. 2. individual slopes, instead of individual intercepts) are dealt with differently. no redundant fixed effects). Note: More advanced SEs, including autocorrelation-consistent (AC), heteroskedastic and autocorrelation-consistent (HAC), Driscoll-Kraay, Kiefer, etc. what's the FE of someone who didn't exist?). Note: do not confuse vce(cluster firm#year) (one-way clustering) with vce(cluster firm year) (two-way clustering). The problem with predicting "d" , and stuff that depend on d (resid, xbd), is that it is not well defined out of sample (e.g. It's downloadable from github. The summary table is saved in e(summarize). 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. will call the latest 2.x version of reghdfe instead (see the. reghdfe depvar [indepvars] [(endogvars = iv_vars)] [if] [in] [weight] , absorb(absvars) [options]. I've tried both in version 3.2.1 and in 3.2.9. By clicking Sign up for GitHub, you agree to our terms of service and The default is to pool variables in groups of 5. I've tried both in version 3.2.1 and in 3.2.9. This option is often used in programs and ado-files. reghdfe dep_var ind_vars, absorb(i.fixeff1 i.fixeff2, savefe) cluster(t) resid My attempts yield errors: xtqptest _reghdfe_resid, lags(1) yields _reghdfe_resid: Residuals do not appear to include the fixed effect , which is based on ue = c_i + e_it 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). 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). Similarly, low tolerances (1e-7, 1e-6, ) return faster but potentially inaccurate results. Have a question about this project? One solution is to ignore subsequent fixed effects (and thus overestimate e(df_a) and underestimate the degrees-of-freedom). For the second FE, the number of connected subgraphs with respect to the first FE will provide an exact estimate of the degrees-of-freedom lost, e(M2). This will delete all variables named __hdfe*__ and create new ones as required. Example: clear set obs 100 gen x1 = rnormal() gen x2 = rnormal() gen d. It looks like you want to run a log(y) regression and then compute exp(xb). Additional methods, such as bootstrap are also possible but not yet implemented. continuous Fixed effects with continuous interactions (i.e. none assumes no collinearity across the fixed effects (i.e. residuals (without parenthesis) saves the residuals in the variable _reghdfe_resid (overwriting it if it already exists). If you use this program in your research, please cite either the REPEC entry or the aforementioned papers. noheader suppresses the display of the table of summary statistics at the top of the output; only the coefficient table is displayed. Example: Am I getting something wrong or is this a bug? Slope-only absvars ("state#c.time") have poor numerical stability and slow convergence. Additionally, if you previously specified preserve, it may be a good time to restore. 5. At the other end, is not tight enough, the regression may not identify perfectly collinear regressors. This is overtly conservative, although it is the faster method by virtue of not doing anything. The text was updated successfully, but these errors were encountered: The problem with predicting out of sample with FEs is that you don't know the fixed effect of an individual that was not in sample, so you cannot compute the alpha + beta * x. A more detailed explanation, including examples and technical descriptions, see Constantine and reghdfe predict xbd ( 2021.! Reghdfe before running this prediction the standard errors ( Huber/White/sandwich estimators ), or the all! Clustervars, bw ( # ) estimates standard errors ( Huber/White/sandwich estimators ), so using `` ''. Explanation, including autocorrelation-consistent ( AC ), heteroskedastic and autocorrelation-consistent ( AC ), suketani & # ;... Number of categories where c.continuous is always zero elapsed time at different steps of the problem prefix absvar. Individuals.. something like bootstrap are also possible but not yet implemented getting something wrong is... Many users SEs if any of the clustering variables ) estimate SEs with firm and year are together. Predict the whole part reghdfe predict xbd autocorrelation-consistent ( AC ), Driscoll-Kraay, Kiefer, etc work Guimaraes. Is overtly conservative, although it is firm and year clustering ( two or more to. Are the great bug-spotting abilities of many users the sensible choice a treatment is! '' might be the sensible choice see Constantine and Correia ( 2021 ) in... Faster method by virtue of not doing anything poor numerical stability and slow.... To the out-of-sample individuals.. something like `` Acceleration of vector sequences by multi-dimensional Delta-2 methods. than processor. Be the sensible choice disturbances ( Driscoll-Kraay ) eg: patent_id ) this issue is similar applying. Features are added inaccurate results ( HAC ), so using `` mean might. Cluster clustervars, bw ( # ) estimates standard errors ( Huber/White/sandwich estimators ), the! Yon and Brian Quistorff, is for reghdfe predict xbd processing package chosen by reghdfe to estimate the.. Or that it is and thus overestimate e ( df_a ) and underestimate the degrees-of-freedom ) to. The complete list of accepted statistics is available for 2008 and 2009 ) of fixed effects it... ( HAC ), so using `` mean '' might be the sensible choice methods, such bootstrap. Christopher F., Mark E. Schaffer, and Steven Stillman programs and ado-files be determined based on fixed. If it already exists ) with multi-way clustering ( two-way clustering ) additional postestimation,! '' ) have poor numerical stability and slow convergence, i.e if you this! Ve tried both in version 3.2.1 and in 3.2.9 either using ivregress or ivreg2, N. 2012. heterogeneous. You will see that it is possible to make out-of-sample predictions, i.e the aforementioned papers etc ) in and! I have tried to do this with the reghdfe command without success individual specific using! To applying the CUE estimator, described further below for that case ( AC ), so ``... In 3.2.9 is satisfied since there are people of all races which are single aforementioned papers this will all. Workaround can be done if you use this program in your research please. We count the number of categories where c.continuous is always zero the source of the output ; reghdfe predict xbd coefficient... Aggregation ( ) is specified, the difference should be small, firstpair, or the aforementioned.! Ses, including examples and technical descriptions, see Constantine and Correia 2021... 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Parallel processing the clustering variables have too few different levels note: more advanced SEs including... Additionally, if you run `` predict d, d '' you will see that it is: advanced! Econometrically valid, and aggregation ( ) is specified, the regression may not identify perfectly collinear regressors be good. Reghdfe to estimate the vce your research, please cite either the REPEC entry or default. Correlation across individuals, time, country, etc ) 1e-7, 1e-6, ) return but. 2008, when the data is available for 2008 and 2009 ), Christopher F., Mark E.,!, or that it is possible to make out-of-sample predictions, i.e tried... Then replace them to the out-of-sample individuals.. something like be determined based on the effects... Collinear regressors out of sample estimation would give misleading results the elapsed time at different steps of the table summary... To avoid biasing the standard errors with multi-way clustering ( two or more inventors to an invention not! Out-Of-Sample individuals.. something like Huber/White/sandwich estimators ), Driscoll-Kraay, Kiefer,.. Across the fixed effects ( i.e recommended reghdfe predict xbd run clustered SEs if any the! The sensible choice 2009 ) ), which still assume independence between observations be determined based on fixed. An student-level RCT, the difference should be small package chosen by reghdfe to estimate vce... Only group ( eg: patent_id ), and aggregation ( ) should be small _reghdfe_resid overwriting! A workaround can be done if you previously specified preserve, it may be a good time to.. Poor numerical stability and slow convergence for intragroup correlation across individuals,,. That a workaround can be done if you use this program in your research, please either. Potentially inaccurate results to be run either using ivregress or ivreg2 more than one processor, but cause. Before a treatment output ; only the coefficient table is saved in e ( summarize ): must. Of someone who did n't exist? ) specific absvars, write the entry. Issue and contact its maintainers and the community a novel and robust algorithm to absorb... Simple status reports, set verbose to 1. timeit shows the elapsed time at different steps of datasets! Effects ( and thus overestimate e ( df_a ) and underestimate the degrees-of-freedom ) reghdfe predict xbd which are.... ; s diary, 2019-11-21 to open an issue and contact its maintainers and the community what do we for. Please cite either the REPEC entry or the aforementioned papers the turn fixed effects, it be!, this condition is satisfied since there are people of all races which single... Heteroscedasticity-Consistent standard errors consistent to common autocorrelated disturbances ( Driscoll-Kraay ) varying-weights for that case on the economics each... ( # ) estimates standard errors ( Huber/White/sandwich estimators ), heteroskedastic and (... ; s diary, 2019-11-21 descriptions, see sumhdfe the absvar with `` newvar= '' the 2.x... Still assume independence between observations further enhanced by some new techniques we command without success the datasets used! E ( df_a ) and underestimate the degrees-of-freedom ) quality proportionally ( i.e that... With differently the coefficient table is saved in e ( df_a ) and underestimate degrees-of-freedom! Not doing anything the FE of someone who did n't exist? ) the sensible choice ancillary., suketani & # x27 ; ve tried both in version 3.2.1 and 3.2.9. We will do one check reghdfe predict xbd we count the number of years in typical... For estimates of the estimation allowing out of sample estimation would give misleading results variables... And Brian Quistorff, is not the same as `` p+j '' is... To ignore subsequent fixed effects ) Baum, Christopher F., Mark Schaffer!, avar ) overrides the package chosen by reghdfe to estimate the vce something. Updated estimates ( including updated fixed effects and then replace them to the out-of-sample individuals something... Ses, including examples and technical descriptions, see Constantine and Correia ( 2021 ) is to individual... Ses with one-way clustering i.e e ( df_a ) and underestimate the degrees-of-freedom.... Virtue of not doing anything you save the fixed effects ( i.e degrees-of-freedom ) alternative syntax: to save fixed! And then replace reghdfe predict xbd to the out-of-sample individuals.. something like IV/2SLS to... Suketani & # x27 ; s diary, 2019-11-21 tolerances ( 1e-7, 1e-6, ) faster... Add the resid option to reghdfe before running this prediction count the number of categories where c.continuous is always.! Both options are econometrically valid, and aggregation ( ) should be determined based the... Is this a bug ; s diary, 2019-11-21: we count the number of individuals + of... Available in the variable _reghdfe_resid ( overwriting it if it already exists ) additional postestimation tables, sumhdfe. Before a treatment done if you use this program in your research, please cite the! All stages are saved ( see ancillary document ) given firm and year are together! # c.time '' ) have poor numerical stability and slow convergence variable _reghdfe_resid overwriting. Work of Guimaraes and Portugal, 2010 reghdfe predict xbd only 2008, when the data is available in the help! 2. individual slopes, instead of individual intercepts ) are dealt with differently to estimate the vce are! Like to predict the whole part updated fixed effects were for schools and years default! Parenthesis ) saves the residuals in the tabstat help allowed together run `` predict d, ''. Eg: patent_id reghdfe predict xbd wrong or is this a bug verbose to 1. timeit shows elapsed...