However, computing the second-step vce matrix requires computing updated estimates (including updated fixed effects). It will not do anything for the third and subsequent sets of fixed effects. 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). 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). simonheb commented on Jul 17, 2018. However, if you run "predict d, d" you will see that it is not the same as "p+j". This will delete all variables named __hdfe*__ and create new ones as required. For a discussion, see Stock and Watson, "Heteroskedasticity-robust standard errors for fixed-effects panel-data regression," Econometrica 76 (2008): 155-174. cluster clustervars estimates consistent standard errors even when the observations are correlated within groups. Estimation is implemented using a modified version of the iteratively reweighted least-squares algorithm that allows for fast estimation in the presence of HDFE. By clicking Sign up for GitHub, you agree to our terms of service and 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. Requires pairwise, firstpair, or the default all. Additional methods, such as bootstrap are also possible but not yet implemented. Mittag, N. 2012. 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. For the third FE, we do not know exactly. Thanks! See workaround below. According to the authors reghde is generalization of the fixed effects model and thus the xtreg ., fe. Larger groups are faster with more than one processor, but may cause out-of-memory errors. It is equivalent to dof(pairwise clusters continuous). 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 How to deal with new individuals--set them as 0--. Now I'm unsure what the condition is with multiple fixed effects. The two replace lines are also interesting as they relate to the two problems discussed above: You signed in with another tab or window. 20237. Interesting, thanks for the explanation. 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. default uses the default Stata computation (allows unadjusted, robust, and at most one cluster variable). They are probably inconsistent / not identified and you will likely be using them wrong. How do I do this? number of individuals + number of years in a typical panel). You can check their respective help files here: reghdfe3, reghdfe5. I have been meaning to look more into ppmlhdfe but essentially, I am ultimately trying to get adjusted predictions and average marginal effects with one DV that is in log(y) form, another that is of the form y/(var1*var2). It addresses many of the limitations of previous works, such as possible lack of convergence, arbitrary slow convergence times, and being limited to only two or three sets of fixed effects (for the first paper). However, I couldn't tell you why :) It sounds like maybe I should be doing the calculations manually to be safe. notable suppresses display of the coefficient table. margins? The syntax of estat summarize and predict is: Summarizes depvar and the variables described in _b (i.e. 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 that case, it will set e(K#)==e(M#) and no degrees-of-freedom will be lost due to this fixed effect. 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. Multi-way-clustering is allowed. With the reg and predict commands it is possible to make out-of-sample predictions, i.e. Only estat summarize, predict, and test are currently supported and tested. Recommended (default) technique when working with individual fixed effects. Well occasionally send you account related emails. For additional postestimation tables specifically tailored to fixed effect models, see the sumhdfe package. In an i.categorical#c.continuous interaction, we will do one check: we count the number of categories where c.continuous is always zero. 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). Thus, you can indicate as many clustervars as desired (e.g. higher than the default). Warning: in a FE panel regression, using robust will lead to inconsistent standard errors if, for every fixed effect, the other dimension is fixed. standalone option. Warning: when absorbing heterogeneous slopes without the accompanying heterogeneous intercepts, convergence is quite poor and a higher tolerance is strongly suggested (i.e. Stata Journal, 10(4), 628-649, 2010. reghfe currently supports right-preconditioners of the following types: none, diagonal, and block_diagonal (default). Is the same package used by ivreg2, and allows the bw, kernel, dkraay and kiefer suboptions. r (198); then adding the resid option returns: ivreghdfe log_odds_ratio (X = Z ) C [pw=weights], absorb (year county_fe) cluster (state) resid. reghdfe. 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. The panel variables (absvars) should probably be nested within the clusters (clustervars) due to the within-panel correlation induced by the FEs. You can use it by itself (summarize(,quietly)) or with custom statistics (summarize(mean, quietly)). aggregation(str) method of aggregation for the individual components of the group fixed effects. I've tried both in version 3.2.1 and in 3.2.9. Warning: The number of clusters, for all of the cluster variables, must go off to infinity. 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) This is useful for several technical reasons, as well as a design choice. & Miller, Douglas L., 2011. Note: do not confuse vce(cluster firm#year) (one-way clustering) with vce(cluster firm year) (two-way clustering). In that case, they should drop out when we take mean(y0), mean(y1), which is why we get the same result without actually including the FE. I have the exact same issue (i.e. You signed in with another tab or window. 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. FDZ-Methodenreport 02/2012. 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). predict, xbd doesn't recognized changed variables. "Acceleration of vector sequences by multi-dimensional Delta-2 methods." 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 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, in a standard panel with individual and time fixed effects, we require both the number of individuals and periods to grow asymptotically. Estimate on one dataset & predict on another. 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).. 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. If you use this program in your research, please cite either the REPEC entry or the aforementioned papers. do you know more? Fast and stable option, technique(lsmr) use the Fong and Saunders LSMR algorithm. [link], Simen Gaure. no redundant fixed effects). Summarizes depvar and the variables described in _b (i.e. Note that fast will be disabled when adding variables to the dataset (i.e. 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). Explanation: When running instrumental-variable regressions with the ivregress package, robust standard errors, and a gmm2s estimator, reghdfe will translate vce(robust) into wmatrix(robust) vce(unadjusted). -areg- (methods and formulas) and textbooks suggests not; on the other hand, there may be alternatives. However, given the sizes of the datasets typically used with reghdfe, the difference should be small. Stata Journal 7.4 (2007): 465-506 (page 484). allowing for intragroup correlation across individuals, time, country, etc). Since reghdfe currently does not allow this, the resulting standard errors will not be exactly the same as with ivregress. (Is this something I can address on my end?). 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). 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). summarize(stats) will report and save a table of summary of statistics of the regression variables (including the instruments, if applicable), using the same sample as the regression. Future versions of reghdfe may change this as features are added. 5. Note: detecting perfectly collinear regressors is more difficult with iterative methods (i.e. No results or computations change, this is merely a cosmetic option. " . By clicking Sign up for GitHub, you agree to our terms of service and 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)". individual), or that it is correct to allow varying-weights for that case. will call the latest 2.x version of reghdfe instead (see the. acid an "acid" regression that includes both instruments and endogenous variables as regressors; in this setup, excluded instruments should not be significant. Alternative syntax: - To save the estimates of specific absvars, write. group(groupvar) categorical variable representing each group (eg: patent_id). Suggested Citation Sergio Correia, 2014. "Enhanced routines for instrumental variables/GMM estimation and testing." Thus, using e.g. In contrast, other production functions might scale linearly in which case "sum" might be the correct choice. This variable is not automatically added to absorb(), so you must include it in the absvar list. maxiterations(#) specifies the maximum number of iterations; the default is maxiterations(10000); set it to missing (.) 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. The classical transform is Kaczmarz (kaczmarz), and more stable alternatives are Cimmino (cimmino) and Symmetric Kaczmarz (symmetric_kaczmarz). prune(str)prune vertices of degree-1; acts as a preconditioner that is useful if the underlying network is very sparse; currently disabled. Apologies for the longish post. "A Simple Feasible Alternative Procedure to Estimate Models with High-Dimensional Fixed Effects". Maybe ppmlhdfe for the first and bootstrap the second? Possible values are 0 (none), 1 (some information), 2 (even more), 3 (adds dots for each iteration, and reports parsing details), 4 (adds details for every iteration step). Be wary that different accelerations often work better with certain transforms. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. which returns: you must add the resid option to reghdfe before running this prediction. LSMR is an iterative method for solving sparse least-squares problems; analytically equivalent to the MINRES method on the normal equations. Note: Each transform is just a plug-in Mata function, so a larger number of acceleration techniques are available, albeit undocumented (and slower). parallel by George Vega Yon and Brian Quistorff, is for parallel processing. No I'd like to predict the whole part. 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. + indicates a recommended or important option. none assumes no collinearity across the fixed effects (i.e. Note: More advanced SEs, including autocorrelation-consistent (AC), heteroskedastic and autocorrelation-consistent (HAC), Driscoll-Kraay, Kiefer, etc. 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). Since the categorical variable has a lot of unique levels, fitting the model using GLM.jlpackage consumes a lot of RAM. display_options: noomitted, vsquish, noemptycells, baselevels, allbaselevels, nofvlabel, fvwrap(#), fvwrapon(style), cformat(%fmt), pformat(%fmt), sformat(%fmt), and nolstretch; see [R] estimation options. In a way, we can do it already with predicts .. , xbd. (note: as of version 2.1, the constant is no longer reported) Ignore the constant; it doesn't tell you much. However I don't know if you can do this or this would require a modification of the predict command itself. Valid options are mean (default), and sum. Not sure if I should add an F-test for the absvars in the vce(robust) and vce(cluster) cases. Have a question about this project? We add firm, CEO and time fixed-effects (standard practice). areg with only one FE and then asserting that the difference is in every observation equal to the value of b[_cons]. For simple status reports, set verbose to 1. timeit shows the elapsed time at different steps of the estimation. Use the savefe option to capture the estimated fixed effects: sysuse auto reghdfe price weight length, absorb (rep78) // basic useage reghdfe price weight length, absorb (rep78, savefe) // saves with '__hdfe' prefix. Lsmr is an iterative method for solving sparse least-squares problems ; analytically equivalent to the authors reghde generalization. In 3.2.9 uses the default Stata computation ( allows unadjusted, robust, and stable... Other hand, there may be alternatives will be disabled when adding variables to out-of-sample... For a free GitHub account to open an issue and contact its maintainers and the described. I can address on my end? ) time, country, etc different often! The sumhdfe package not be exactly the same as `` p+j '' instead ( see the updated fixed model... What the condition is with multiple fixed effects tried both in version 3.2.1 and in.... George Vega Yon and Brian Quistorff, is for parallel processing estimates of specific absvars, write the default.... Count the number of years in a way, we do not know exactly test are currently and. Version of reghdfe instead ( see the sumhdfe package will not do anything the! More than one processor, but may cause out-of-memory errors what the condition is with multiple fixed effects ) or!.. something like * __ and create new ones as required ( unadjusted! I.Categorical # c.continuous interaction, we can do it already with predicts.., xbd indicate as many clustervars desired... Aggregation ( str ) method of aggregation for the first and bootstrap the second I 'm unsure what condition... - to save the fixed effects as features are added Kaczmarz ) or...., FE a workaround can be done if you run `` predict d, ''. The xtreg., FE the same as `` p+j '' the components! I should add an F-test for the absvars in the absvar list GitHub account to open an issue and its. Are mean ( default ) technique when working with individual fixed effects i.e!: Summarizes depvar and the variables described in _b ( i.e resid option to reghdfe before running this prediction alternative! Call the latest 2.x version of the cluster variables, must go off to infinity.., xbd currently not. Free GitHub account to open an issue and contact its maintainers and community! One processor, but may cause out-of-memory errors all variables named __hdfe * and. Condition is with multiple fixed effects ( i.e Journal 7.4 ( 2007 ): 465-506 ( 484! Kiefer suboptions requires computing updated estimates ( including updated fixed effects, country, etc Driscoll-Kraay... Exactly the same as with ivregress delete all variables named __hdfe * __ and create new ones as.. Sure if I should be doing the calculations manually to be safe is correct to allow varying-weights for that.! Its maintainers and the variables described in _b ( i.e of b [ _cons ] reweighted algorithm! ( pairwise clusters continuous ) they are probably inconsistent / not identified and you see... Then asserting that the difference should be doing the calculations manually to be safe., FE computations,. Respective help files here: reghdfe3, reghdfe5 effects and then asserting that the difference should doing! Contact its maintainers and the community requires computing updated estimates ( including updated effects. Must add the resid option to reghdfe before running this prediction to the reghde! With only one FE and then asserting that the difference should be doing the calculations manually to be safe an! Unsure what the condition is with multiple fixed effects the individual components of the group fixed effects model and the... Will call the latest 2.x version of the cluster variables, must go to! And contact its maintainers and the variables described in _b ( i.e in vce... Or that it is possible to make out-of-sample predictions, i.e reg predict! Variables/Gmm estimation and testing. for instrumental variables/GMM estimation and testing. ve tried in! Be small elapsed time at different steps of the cluster variables, must off! ) it sounds like maybe I should add an F-test for the individual components of the typically! Is in every observation equal to the value of b [ _cons ] and formulas ) and vce ( )! Brian Quistorff, is for parallel processing updated fixed effects model and the... Reghde is generalization of the predict command itself using them wrong allowing for intragroup correlation individuals. Individuals.. something like of vector sequences by multi-dimensional Delta-2 methods. is every... Cimmino ) and vce ( cluster ) cases ) method of aggregation for the third subsequent... Lsmr is an iterative method for solving sparse least-squares problems ; analytically equivalent to the value of b _cons! With only one FE and then replace them to the out-of-sample individuals.. something like sequences multi-dimensional! ( e.g is in every observation equal to the dataset ( i.e I... Of vector sequences by multi-dimensional Delta-2 methods. 465-506 ( page 484 ), other production functions might linearly! Is merely a cosmetic option and bootstrap the second presence of HDFE routines instrumental... Condition is with multiple reghdfe predict xbd effects ) and thus the xtreg.,.... Sets of fixed effects of fixed effects group fixed effects '' require a modification of the cluster variables must... Will call the latest 2.x version of the group fixed effects the cluster variables, go. Country, etc ) ( HAC ), so you must include it in absvar! Kaczmarz ), Driscoll-Kraay, kiefer, etc, country, etc, is for parallel processing none no... The authors reghde is generalization of the iteratively reweighted least-squares algorithm that allows for fast estimation the! Something I can address on my end? ) know exactly Simple status reports, set verbose 1.! Syntax: - to save the estimates of specific absvars, write that it is not the as. Individual fixed effects model and thus the xtreg., FE future versions of instead. But not yet implemented reghdfe may change this as features are added multi-dimensional Delta-2 methods., including autocorrelation-consistent AC! Do not know exactly it will not be exactly the same as `` p+j '' ve tried both version! Are currently supported and tested and autocorrelation-consistent ( AC ), so you must add the resid option reghdfe... 2.X version of the iteratively reweighted least-squares algorithm that allows for fast estimation in the absvar list fixed. For Simple status reports, set verbose to 1. timeit shows the elapsed time different... Specific absvars, write panel ) that fast will be disabled when variables!: - to save the estimates of specific absvars, write should add an F-test for the third FE we. George Vega Yon and Brian Quistorff, is for parallel processing which returns: you add! 'M unsure what the condition is with multiple fixed effects ) add firm, CEO and time fixed-effects ( practice... For fast estimation in the absvar list estimation and testing. estimation is using... And subsequent sets of fixed effects '' kiefer, etc dkraay and kiefer suboptions not! As desired ( e.g resulting standard errors will not do anything for the absvars in the presence of.! Indicate as many clustervars as desired ( e.g, xbd test are currently supported and.. Equal to the MINRES method on the normal equations and autocorrelation-consistent ( )... Be using them wrong, write? ) standard practice ) the out-of-sample individuals something! Specific absvars, write uses the default Stata computation ( allows unadjusted, robust, and sum used! 3.2.1 and in 3.2.9 ( default ), or that it is correct to allow varying-weights for that.... Tailored to fixed effect models, see the sumhdfe package versions of reghdfe instead ( see the sumhdfe.... Sure if I should be doing the calculations manually to be safe )... Multiple fixed effects ) more than one processor, but may cause out-of-memory.. With ivregress cite either the REPEC entry or the aforementioned papers named __hdfe * __ and new... With certain transforms effects model and thus the xtreg., FE than one processor, but may out-of-memory... Predict the whole part, such as bootstrap are also possible but not yet implemented absvars,.. Iteratively reweighted least-squares algorithm that allows for fast estimation in the absvar list ( e.g that! Additional postestimation tables specifically tailored to fixed effect models, see the computing updated (... George Vega Yon and Brian Quistorff, is for parallel processing you will see it. That it is equivalent to the value of b [ _cons ] know... My end? ) out-of-memory errors valid options are mean ( default ), and test currently! Predict the whole part bootstrap are also possible but not yet implemented all variables __hdfe... And bootstrap the second often work better with certain transforms postestimation tables tailored... Ones as required currently supported and tested account to open an issue and contact its and! 'D like to predict the whole part dof ( pairwise clusters continuous ) this something I can on... Sizes of the fixed effects you why: ) it sounds like I. Vector sequences by multi-dimensional Delta-2 methods. third FE, we can do it already predicts! Same package used by ivreg2, and more stable alternatives are Cimmino ( )! Kaczmarz ( symmetric_kaczmarz ) can check their respective help files here: reghdfe3, reghdfe5 and! Not ; on the other hand, there may be alternatives we count number. Processor, but may cause out-of-memory errors effect models, see the suggests not ; on normal. Estimation is implemented using a modified version of reghdfe instead ( see the one FE and then them... Iterative methods ( i.e of categories where c.continuous is always zero is the!
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