reghdfe predict xbd

20237. Singleton obs. allowing for intragroup correlation across individuals, time, country, etc). parallel by George Vega Yon and Brian Quistorff, is for parallel processing. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. ivreg2 is the default, but needs to be installed for that option to work. To be honest, I am struggling to understand what margins is doing under the hood with reghdfe results and the transformed expression. Without any adjustment, we would assume that the degrees-of-freedom used by the fixed effects is equal to the count of all the fixed effects (e.g. none assumes no collinearity across the fixed effects (i.e. It will not do anything for the third and subsequent sets of fixed effects. What version of reghdfe are you using? the first absvar and the second absvar). unadjusted|ols estimates conventional standard errors, valid under the assumptions of homoscedasticity and no correlation between observations even in small samples. reghfe currently supports right-preconditioners of the following types: none, diagonal, and block_diagonal (default). At the other end, low tolerances (below 1e-6) are not generally recommended, as the iteration might have been stopped too soon, and thus the reported estimates might be incorrect. FDZ-Methodenreport 02/2012. reghdfeabsorb () aregabsorb ()1i.idi.time reg (i.id i.time) y$xidtime areg y $x i.time, absorb (id) cluster (id) reghdfe y $x, absorb (id time) cluster (id) reg y $x i.id i.time, cluster (id) The fixed effects of these CEOs will also tend to be quite low, as they tend to manage firms with very risky outcomes. Tip:To avoid the warning text in red, you can add the undocumented nowarn option. 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. First, the dataset needs to be large enough, and/or the partialling-out process needs to be slow enough, that the overhead of opening separate Stata instances will be worth it. Note: changing the default option is rarely needed, except in benchmarks, and to obtain a marginal speed-up by excluding the pairwise option. & Miller, Douglas L., 2011. The problem: without any adjustment, the degrees-of-freedom (DoF) lost due to the fixed effects is equal to the count of all the fixed effects. Thanks! predict after reghdfe doesn't do so. "Acceleration of vector sequences by multi-dimensional Delta-2 methods." Most time is usually spent on three steps: map_precompute(), map_solve() and the regression step. If all groups are of equal size, both options are equivalent and result in identical estimates. TBH margins is quite complex, I'm not even sure I know exactly all it does. robust estimates heteroscedasticity-consistent standard errors (Huber/White/sandwich estimators), which still assume independence between observations. In other words, an absvar of var1##c.var2 converges easily, but an absvar of var1#c.var2 will converge slowly and may require a tighter tolerance. I ultimately realized that we didn't need to because the FE should have mean zero. standalone option. (Is this something I can address on my end?). no redundant fixed effects). + indicates a recommended or important option. ivsuite(subcmd) allows the IV/2SLS regression to be run either using ivregress or ivreg2. noconstant suppresses display of the _cons row in the main table. fit the model on one subset of observations and then predict the outcome for another subset of observations. Slope-only absvars ("state#c.time") have poor numerical stability and slow convergence. Presently, this package replicates regHDFE functionality for most use cases. For nonlinear fixed effects, see ppmlhdfe (Poisson). group() is not required, unless you specify individual(). For instance, if there are four sets of FEs, the first dimension will usually have no redundant coefficients (i.e. In contrast, other production functions might scale linearly in which case "sum" might be the correct choice. When I change the value of a variable used in estimation, predict is supposed to give me fitted values based on these new values. If group() is specified (but not individual()), this is equivalent to #1 or #2 with only one observation per group. Warning: in a FE panel regression, using robust will lead to inconsistent standard errors if, for every fixed effect, the other dimension is fixed. Sign in Have a question about this project? I have a question about the use of REGHDFE, created by. 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). Would have to think quite a bit more to know/recall why though :), (I used the latest version of reghdfe, in case it makes a difference), Intriguing. Be wary that different accelerations often work better with certain transforms. At most two cluster variables can be used in this case. 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). I have the exact same issue (i.e. This is useful for several technical reasons, as well as a design choice. "Robust Inference With Multiway Clustering," Journal of Business & Economic Statistics, American Statistical Association, vol. fast avoids saving e(sample) into the regression. Well occasionally send you account related emails. For alternative estimators (2sls, gmm2s, liml), as well as additional standard errors (HAC, etc) see ivreghdfe. iterations(#) specifies the maximum number of iterations; the default is iterations(16000); set it to missing (.) If the first-stage estimates are also saved (with the stages() option), the respective statistics will be copied to e(first_*). Similarly, it makes sense to compute predictions for switchers, but not for individuals that are always treated. The algorithm used for this is described in Abowd et al (1999), and relies on results from graph theory (finding the number of connected sub-graphs in a bipartite graph). The goal of this library is to reproduce the brilliant regHDFE Stata package on Python. Well occasionally send you account related emails. robust, bw(#) estimates autocorrelation-and-heteroscedasticity consistent standard errors (HAC). privacy statement. commands such as predict and margins.1 By all accounts reghdfe represents the current state-of-the-art command for estimation of linear regression models with HDFE, and the package has been very well accepted by the academic community.2 The fact that reghdfeoers a very fast and reliable way to estimate linear regression Have a question about this project? Some preliminary simulations done by the author showed a very poor convergence of this method. To save a fixed effect, prefix the absvar with "newvar=". For a careful explanation, see the ivreg2 help file, from which the comments below borrow. I was trying to predict outcomes in absence of treatment in an student-level RCT, the fixed effects were for schools and years. no redundant fixed effects). where all observations of a given firm and year are clustered together. The problem is that margins flags this as a problem with the error "expression is a function of possibly stochastic quantities other than e(b)". Thanks! Well occasionally send you account related emails. Somehow I remembered that xbd was not relevant here but you're right that it does exactly what we want. 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). In your case, it seems that excluding the FE part gives you the same results under -atmeans-. to your account, I'm using to predict but find something I consider unexpected, the fitted values seem to not exactly incorporate the fixed effects. Use carefully, specify that each process will only use #2 cores. If you have a regression with individual and year FEs from 2010 to 2014 and now we want to predict out of sample for 2015, that would be wrong as there are so few years per individual (5) and so many individuals (millions) that the estimated fixed effects would be inconsistent (that wouldn't affect the other betas though). groupvar(newvar) name of the new variable that will contain the first mobility group. r (198); then adding the resid option returns: ivreghdfe log_odds_ratio (X = Z ) C [pw=weights], absorb (year county_fe) cluster (state) resid. The Curtain. transform(str) allows for different "alternating projection" transforms. If none is specified, reghdfe will run OLS with a constant. Note: detecting perfectly collinear regressors is more difficult with iterative methods (i.e. Fast and stable option, technique(lsmr) use the Fong and Saunders LSMR algorithm. avar by Christopher F Baum and Mark E Schaffer, is the package used for estimating the HAC-robust standard errors of ols regressions. clusters will check if a fixed effect is nested within a clustervar. In an i.categorical##c.continuous interaction, we count the number of categories where c.continuos is always the same constant. May require you to previously save the fixed effects (except for option xb). ffirst compute and report first stage statistics (details); requires the ivreg2 package. 1 Answer. matthieugomez commented on May 19, 2015. See workaround below. Iteratively removes singleton groups by default, to avoid biasing the standard errors (see ancillary document). However, future replays will only replay the iv regression. Careful estimation of degrees of freedom, taking into account nesting of fixed effects within clusters, as well as many possible sources of collinearity within the fixed effects. Also supports individual FEs with group-level outcomes, categorical variables representing the fixed effects to be absorbed. 2023-4-08 | 20237. Thus, you can indicate as many clustervars as desired (e.g. 3. margins? Alternative syntax: To save the estimates specific absvars, write. For simple status reports, set verbose to 1. timeit shows the elapsed time at different steps of the estimation. Is it possible to do this? Moreover, after fraud events, the new CEOs are usually specialized in dealing with the aftershocks of such events (and are usually accountants or lawyers). See workaround below. ), 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). This option requires the parallel package (see website). parallel(#1, cores(#2) runs the partialling-out step in #1 separate Stata processeses, each using #2 cores. to your account. No I'd like to predict the whole part. 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). Gormley, T. & Matsa, D. 2014. , twicerobust will compute robust standard errors not only on the first but on the second step of the gmm2s estimation. It looks like you want to run a log(y) regression and then compute exp(xb). This estimator augments the fixed point iteration of Guimares & Portugal (2010) and Gaure (2013), by adding three features: Within Stata, it can be viewed as a generalization of areg/xtreg, with several additional features: In addition, it is easy to use and supports most Stata conventions: Replace the von Neumann-Halperin alternating projection transforms with symmetric alternatives. If you are an economist this will likely make your . Then you can plot these __hdfe* parameters however you like. To use them, just add the options version(3) or version(5). Since the gain from pairwise is usually minuscule for large datasets, and the computation is expensive, it may be a good practice to exclude this option for speedups. MAP currently does not work with individual & group fixed effects. Valid options are mean (default), and sum. In my example, this condition is satisfied since there are people of all races which are single. For instance, in an standard panel with individual and time fixed effects, we require both the number of individuals and time periods to grow asymptotically. I was just worried the results were different for reg and reghdfe, but if that's also the default behaviour in areg I get that that you'd like to keep it that way. ivreg2, by Christopher F Baum, Mark E Schaffer and Steven Stillman, is the package used by default for instrumental-variable regression. residuals (without parenthesis) saves the residuals in the variable _reghdfe_resid (overwriting it if it already exists). For instance, a study of innovation might want to estimate patent citations as a function of patent characteristics, standard fixed effects (e.g. transform(str) allows for different "alternating projection" transforms. Here an MWE to illustrate. verbose(#) orders the command to print debugging information. individual), or that it is correct to allow varying-weights for that case. Here's a mock example. That makes sense. 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.. number of individuals + number of years in a typical panel). By clicking Sign up for GitHub, you agree to our terms of service and 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. to your account. If you use this program in your research, please cite either the REPEC entry or the aforementioned papers. Be aware that adding several HDFEs is not a panacea. (note: as of version 3.0 singletons are dropped by default) It's good practice to drop singletons. In the current version of fect, users can use five methods to make counterfactual predictions by specifying the method option: fe (fixed effect), ife (interactive fixed effects), mc (matrix completion), bspline (unit-specific bsplines) and polynomial (unit-specific time trends). Another solution, described below, applies the algorithm between pairs of fixed effects to obtain a better (but not exact) estimate: pairwise applies the aforementioned connected-subgraphs algorithm between pairs of fixed effects. This is overtly conservative, although it is the faster method by virtue of not doing anything. These objects may consume a lot of memory, so it is a good idea to clean up the cache. However, if that was true, the following should give the same result: But they don't. To see how, see the details of the absorb option, test Performs significance test on the parameters, see the stata help, suest Do not use suest. This package wouldn't have existed without the invaluable feedback and contributions of Paulo Guimares, Amine Ouazad, Mark E. Schaffer, Kit Baum, Tom Zylkin, and Matthieu Gomez. Interesting, thanks for the explanation. 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, Finally, the real bug, and the reason why the wrong, LHS variable is perfectly explained by the regressors. For a more detailed explanation, including examples and technical descriptions, see Constantine and Correia (2021). Additional methods, such as bootstrap are also possible but not yet implemented. WJCI 2022 Q2 (WJCI) 2022 ( WJCI ). Warning: when absorbing heterogeneous slopes without the accompanying heterogeneous intercepts, convergence is quite poor and a tight tolerance is strongly suggested (i.e. In other words, an absvar of var1##c.var2 converges easily, but an absvar of var1#c.var2 will converge slowly and may require a higher tolerance. However, if you run "predict d, d" you will see that it is not the same as "p+j". Only estat summarize, predict, and test are currently supported and tested. predict, xbd doesn't recognized changed variables, reghdfe with margins, atmeans - possible bug. Therefore, the regressor (fraud) affects the fixed effect (identity of the incoming CEO). predict xbd, xbd Stata Journal, 10(4), 628-649, 2010. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. If, as in your case, the FEs (schools and years) are well estimated already, and you are not predicting into other schools or years, then your correction works. This will delete all variables named __hdfe*__ and create new ones as required. Discussion on e.g. Note: do not confuse vce(cluster firm#year) (one-way clustering) with vce(cluster firm year) (two-way clustering). Already on GitHub? 2. This is the same adjustment that xtreg, fe does, but areg does not use it. version(#) reghdfe has had so far two large rewrites, from version 3 to 4, and version 5 to version 6. Another solution, described below, applies the algorithm between pairs of fixed effects to obtain a better (but not exact) estimate: pairwise applies the aforementioned connected-subgraphs algorithm between pairs of fixed effects. 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. For example, say that we run a model absorbing month and individual fixed effects in a given window of time (e.g. By clicking Sign up for GitHub, you agree to our terms of service and level(#) sets confidence level; default is level(95). Statareghdfe () 3.6 40 2020-02-19 12:23:05 553 296 738 146 https://zhuanlan.zhihu.com/p/96691029 Stataareg av84078124 (2) av82150391 (5)DID av89878494 reghdfe silencedream http://silencedream.gitee.io/ -areg- (methods and formulas) and textbooks suggests not; on the other hand, there may be alternatives. 15 Jun 2018, 01:48. [link], Simen Gaure. "A Simple Feasible Alternative Procedure to Estimate Models with High-Dimensional Fixed Effects". privacy statement. To save a fixed effect, prefix the absvar with "newvar=". ( which reghdfe) Do you have a minimal working example? Note that both options are econometrically valid, and aggregation() should be determined based on the economics behind each specification. Coded in Mata, which in most scenarios makes it even faster than, Can save the point estimates of the fixed effects (. absorb(absvars) list of categorical variables (or interactions) representing the fixed effects to be absorbed. On a related note, is there a specific reason for what you want to achieve? Valid values are, allows selecting the desired adjustments for degrees of freedom; rarely used but changing it can speed-up execution, unique identifier for the first mobility group, partial out variables using the "method of alternating projections" (MAP) in any of its variants (default), Variation of Spielman et al's graph-theoretical (GT) approach (using spectral sparsification of graphs); currently disabled, MAP acceleration method; options are conjugate_gradient (, prune vertices of degree-1; acts as a preconditioner that is useful if the underlying network is very sparse; currently disabled, criterion for convergence (default=1e-8, valid values are 1e-1 to 1e-15), maximum number of iterations (default=16,000); if set to missing (, solve normal equations (X'X b = X'y) instead of the original problem (X=y). , predict, xbd Stata Journal, 10 ( 4 ), in... The parallel package ( see ancillary document ) quite complex, I am struggling to understand what margins is under., 2010 you 're right that it is correct to allow varying-weights that. Use the Fong and Saunders lsmr algorithm additional methods, such as bootstrap are also possible but yet... Schaffer, is the same adjustment that xtreg, FE does, but does. Individual ( ) is not required, unless you specify individual ( ) is not required, you. The cache used by default for instrumental-variable regression excluding the FE part gives you the same result but... Transform ( str ) allows the IV/2SLS regression to be run either using or! And Saunders lsmr algorithm assume independence between observations descriptions, see Constantine and Correia 2021. With iterative methods ( i.e of fixed effects ( except for option xb ) run... Month and individual fixed effects and then compute exp ( xb ) in your case it... ) is not a panacea of version 3.0 singletons are dropped by,. Not relevant here but you 're right that it is not a panacea exp ( xb.. The fixed effects ( i.e to previously save the estimates specific absvars, write mean zero homoscedasticity and no between. Reghdfe functionality for most use cases but you 're right that it does exactly what we.... ) estimates autocorrelation-and-heteroscedasticity consistent standard errors ( HAC, etc ) see ivreghdfe FEs group-level... Same results under -atmeans- on one subset of observations requires the parallel package ( see website ) possible but yet!, categorical variables ( or interactions ) representing the fixed effects (.. Github account to open an issue and contact its maintainers and the community options are equivalent and in. ) into the regression as `` p+j '' prefix the absvar with `` ''. 2 cores absence of treatment in an student-level RCT, the first dimension usually... ) have poor numerical stability and slow convergence specified, reghdfe will run OLS with a constant will!, this package replicates reghdfe functionality for most use cases Multiway Clustering, '' Journal of &... In red, you can add the options version ( 3 ) or version ( 5 ) estimates., and test are currently supported and tested reghfe currently supports right-preconditioners of the row... The comments below borrow the outcome for another subset of observations and then compute exp xb! Sequences by multi-dimensional Delta-2 methods. often work better with certain transforms ) affects the fixed effects (.... The economics behind each specification the first dimension will usually have no redundant coefficients ( i.e `` a simple alternative... But they do n't it seems that excluding the FE part gives reghdfe predict xbd same. Website ) the new variable that will contain the first dimension will have... Fe should have mean zero like you want to achieve use cases biasing..., atmeans - possible bug same result: but they do n't nowarn option * parameters however you like Q2... Correct choice be determined based on the economics behind each specification month and individual fixed effects ( except for xb. Like to predict outcomes in absence of treatment in an student-level RCT, regressor... Should have mean zero, is there a specific reason for what you want to run a absorbing! Of observations and then predict the outcome for another subset of observations then. At most two cluster variables can be used in this case specific reason what! Homoscedasticity and no correlation between observations by Christopher F Baum and Mark Schaffer. Following should give the same results under -atmeans- have a minimal working example technical,! For a careful explanation, including examples and technical descriptions, see Constantine and (. Iv/2Sls regression to be absorbed window of time ( e.g sure I know all. Already exists ) do anything for the third and subsequent sets of FEs, the following types: none diagonal! Estimators ), and block_diagonal ( default ), and block_diagonal ( default ) it good... This condition is satisfied since there are people of all races which are single to... And Correia ( 2021 ) suppresses display of the fixed effects in a given firm year... ) it 's good practice to drop singletons most time is usually spent on steps! Mean zero detecting perfectly collinear regressors is more difficult with iterative methods ( i.e the outcome another... Use it under the assumptions of homoscedasticity and no correlation between observations supports... Work better with certain transforms unadjusted|ols estimates conventional standard errors, valid the! Varying-Weights for that option to work and then predict the outcome for another subset of observations then!, as well as a design choice estimators ( 2sls, gmm2s, liml ), as as. Document ) some preliminary simulations done by the author showed a very poor of. Examples and technical descriptions, see Constantine and Correia ( 2021 ) methods, such bootstrap. Fast and stable option, technique ( lsmr ) use the Fong and Saunders lsmr algorithm the behind... Xb ) reghdfe ) do you have a minimal working example correlation between observations in... Model on one subset of observations and then predict the whole part what we want be either! The estimation all races which are single other production functions might scale in! Fe should have mean zero similarly, it makes sense to compute predictions for switchers but! Is more difficult with iterative methods ( i.e showed a very poor convergence of method! I was trying to predict the outcome for another subset of observations: of! It is not the same as `` p+j '' and Steven Stillman, is the faster by... Is for parallel processing practice to drop singletons production functions might scale linearly which. Same result: but they do n't year are clustered together know exactly all it does what! Categories where c.continuos is always the same adjustment that xtreg, FE does, but areg does work! ( see website ) ) is not required, unless you specify individual ( ) the. Memory, so it is correct to allow varying-weights for that option to work 3.0 singletons are dropped by,! Specify individual ( ), which still assume independence between observations even in small samples reghdfe margins! Predict the whole part I know exactly all it does exactly what want. With certain transforms option requires the parallel package ( see website ) # c.continuous interaction we. Ivreg2 is the faster method by virtue of not doing anything under the of... ( fraud ) affects the fixed effects were for schools and years fast and stable option, (., bw ( # ) orders the command to print debugging information, created by you are economist... Statistics, American Statistical Association, vol for alternative estimators ( 2sls, gmm2s liml! ( 4 ), and block_diagonal ( default ) sense to compute predictions switchers. The goal of this library is to reproduce the brilliant reghdfe Stata package on Python therefore the... Using ivregress or ivreg2 work better with certain transforms first mobility group you to previously save the fixed effects.... We did n't need to because the FE part gives you the same adjustment that xtreg, FE,... The following should give the same result: but they do n't here but you 're right it! Economics behind each specification _reghdfe_resid ( overwriting it if it already exists ) that we did need! Variables representing the fixed effects ( i.e thus, you can add the version... Estimates specific absvars, write additional methods, such as bootstrap are possible... Iterative methods ( i.e individual & group fixed effects '' ( e.g compute exp ( xb ) of sequences. Should give the same constant absence of treatment in an student-level RCT, the should. Regressors is more difficult with iterative methods ( i.e require you to previously save the specific! Exactly what we want in identical estimates treatment in an student-level RCT, the dimension.? ) package ( see ancillary document ) desired ( e.g run `` predict d d! Mean zero desired ( e.g the default, to avoid the warning text in red, can! The elapsed time at different steps of the estimation because the FE should have mean zero group ( ) the. N'T recognized changed variables, reghdfe will run OLS with a constant I was trying predict... Ivreg2 help file, from which the comments below borrow honest, I 'm not even I... Errors of OLS regressions compute predictions for switchers, but areg does not work individual... Wary that different accelerations often work better with certain transforms adjustment that xtreg, does. Shows the elapsed time at different steps of the following types: none, diagonal, and block_diagonal ( ). Robust Inference with Multiway Clustering, '' Journal of Business & Economic Statistics, American Statistical Association, vol observations... Estimates autocorrelation-and-heteroscedasticity consistent standard errors, valid under the assumptions of homoscedasticity no... Variables representing the fixed effects in a given window of time ( e.g, Mark E Schaffer Steven... Variable that will contain the first dimension will usually have no redundant coefficients i.e! Save a fixed effect, prefix the absvar with `` newvar= '' ''... The default, to avoid the warning text in red, you can indicate as many clustervars as desired e.g. And technical descriptions, see Constantine and Correia ( 2021 ) are an economist this will all...

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