A frequent rule of thumb is that each cluster variable must have at least 50 different categories (the number of categories for each clustervar appears at the top of the regression table). maxiterations(#) specifies the maximum number of iterations; the default is maxiterations(10000); set it to missing (.) In an i.categorical#c.continuous interaction, we will do one check: we count the number of categories where c.continuous is always zero. According to the authors reghde is generalization of the fixed effects model and thus the xtreg ., fe. 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). It will run, but the results will be incorrect. For more information on the algorithm, please reference the paper, technique(gt) variation of Spielman et al's graph-theoretical (GT) approach (using a spectral sparsification of graphs); currently disabled. You can use it by itself (summarize(,quietly)) or with custom statistics (summarize(mean, quietly)). I did just want to flag it since you had mentioned in #32 that you had not done comprehensive testing. This is equivalent to including an indicator/dummy variable for each category of each absvar. WJCI 2022 Q2 (WJCI) 2022 ( WJCI ). Equivalent to ". 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 Requires pairwise, firstpair, or the default all. noconstant suppresses display of the _cons row in the main table. If you want to use descriptive stats, that's what the. predict, xbd doesn't recognized changed variables. Thanks! Estimate on one dataset & predict on another. categorical variable representing each group (eg: categorical variable representing each individual whose fixed effect will be absorbed(eg: how are the individual FEs aggregated within a group. allowing for intragroup correlation across individuals, time, country, etc). Warning: in a FE panel regression, using robust will lead to inconsistent standard errors if, for every fixed effect, the other dimension is fixed. Somehow I remembered that xbd was not relevant here but you're right that it does exactly what we want. A copy of this help file, as well as a more in-depth user guide is in development and will be available at "http://scorreia.com/reghdfe". reghdfe is a generalization of areg (and xtreg,fe, xtivreg,fe) for multiple levels of fixed effects, and multi-way clustering. avar by Christopher F Baum and Mark E Schaffer, is the package used for estimating the HAC-robust standard errors of ols regressions. absorb() is required. To check or contribute to the latest version of reghdfe, explore the Github repository. Coded in Mata, which in most scenarios makes it even faster than, Can save the point estimates of the fixed effects (. Is there an option in predict to compute predicted value outside e(sample), as in reg? Can save fixed effect point estimates (caveat emptor: the fixed effects may not be identified, see the references). 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. Recommended (default) technique when working with individual fixed effects. to your account. number of individuals or years). I know this is a long post so please let me know if something is unclear. 3. Suss. To use them, just add the options version(3) or version(5). This option is often used in programs and ado-files. 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. For instance, a study of innovation might want to estimate patent citations as a function of patent characteristics, standard fixed effects (e.g. Summarizes depvar and the variables described in _b (i.e. ivreg2, by Christopher F Baum, Mark E Schaffer, and Steven Stillman, is the package used by default for instrumental-variable regression. 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), degrees of freedom lost due to the fixed effects, log-likelihood of fixed-effect-only regression, number of clusters for the #th cluster variable, Number of categories of the #th absorbed FE, Number of redundant categories of the #th absorbed FE, names of endogenous right-hand-side variables, name of the absorbed variables or interactions, variance-covariance matrix of the estimators. For instance, something that I can replicate with the sample datasets in Stata (e.g. In contrast, other production functions might scale linearly in which case "sum" might be the correct choice. Future versions of reghdfe may change this as features are added. What is it in the estimation procedure that causes the two to differ? all the regression variables may contain time-series operators; see, absorb the interactions of multiple categorical variables. here. Thus, you can indicate as many clustervars as desired (e.g. Because the rewrites might have removed certain features (e.g. not the excluded instruments). (note: as of version 2.1, the constant is no longer reported) Ignore the constant; it doesn't tell you much. See workaround below. 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). However, the following produces yhat = wage: capture drop yhat predict xbd, xbd gen yhat = xbd + res Now, yhat=wage How to deal with new individuals--set them as 0--. Sorted by: 2. Well occasionally send you account related emails. 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: Least-square regressions (no fixed effects): reghdfe depvar [indepvars] [if] [in] [weight] [, options], reghdfe depvar [indepvars] [if] [in] [weight] , absorb(absvars) [options]. 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. Tip:To avoid the warning text in red, you can add the undocumented nowarn option. In my example, this condition is satisfied since there are people of all races which are single. It is equivalent to dof(pairwise clusters continuous). Journal of Development Economics 74.1 (2004): 163-197. It will run, but the results will be incorrect. The paper explaining the specifics of the algorithm is a work-in-progress and available upon request. Note that e(M3) and e(M4) are only conservative estimates and thus we will usually be overestimating the standard errors. Abowd, J. M., R. H. Creecy, and F. Kramarz 2002. firstpair will exactly identify the number of collinear fixed effects across the first two sets of fixed effects (i.e. However, this doesn't work if the regression is perfectly explained (you can check it by running areg y x, a(d) and then test x). For instance, vce(cluster firm#year) will estimate SEs with one-way clustering i.e. Think twice before saving the fixed effects. Mean is the default method. However, given the sizes of the datasets typically used with reghdfe, the difference should be small. program define reghdfe_p, rclass * Note: we IGNORE typlist and generate the newvar as double * Note: e(resid) is missing outside of e(sample), so we don't need to . (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). Note: The default acceleration is Conjugate Gradient and the default transform is Symmetric Kaczmarz. 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. Alternative technique when working with individual fixed effects. 15 Jun 2018, 01:48. More suboptions avalable, preserve the dataset and drop variables as much as possible on every step, control columns and column formats, row spacing, line width, display of omitted variables and base and empty cells, and factor-variable labeling, amount of debugging information to show (0=None, 1=Some, 2=More, 3=Parsing/convergence details, 4=Every iteration), show elapsed times by stage of computation, run previous versions of reghdfe. This is equivalent to using egen group(var1 var2) to create a new variable, but more convenient and faster. 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) unadjusted, bw(#) (or just , bw(#)) estimates autocorrelation-consistent standard errors (Newey-West). 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. This maintains compatibility with ivreg2 and other packages, but may unadvisable as described in ivregress (technical note). The text was updated successfully, but these errors were encountered: Would it make sense if you are able to only predict the -xb- part? Well occasionally send you account related emails. parallel(#1, cores(#2) runs the partialling-out step in #1 separate Stata processeses, each using #2 cores. Slope-only absvars ("state#c.time") have poor numerical stability and slow convergence. In an i.categorical#c.continuous interaction, we will do one check: we count the number of categories where c.continuous is always zero. One solution is to ignore subsequent fixed effects (and thus overestimate e(df_a) and underestimate the degrees-of-freedom). This is it. number of individuals or years). What version of reghdfe are you using? individual slopes, instead of individual intercepts) are dealt with differently. How do I do this? ffirst compute and report first stage statistics (details); requires the ivreg2 package. "Common errors: How to (and not to) control for unobserved heterogeneity." Sign in Census Bureau Technical Paper TP-2002-06. For instance, if we estimate data with individual FEs for 10 people, and then want to predict out of sample for the 11th, then we need an estimate which we cannot get. Stata: MP 15.1 for Unix. Note: More advanced SEs, including autocorrelation-consistent (AC), heteroskedastic and autocorrelation-consistent (HAC), Driscoll-Kraay, Kiefer, etc. It can cache results in order to run many regressions with the same data, as well as run regressions over several categories. The solution: To address this, reghdfe uses several methods to count instances as possible of collinearities of FEs. The first limitation is that it only uses within variation (more than acceptable if you have a large enough dataset). with each patent spanning as many observations as inventors in the patent.) 6. -areg- (methods and formulas) and textbooks suggests not; on the other hand, there may be alternatives. Note: The default acceleration is Conjugate Gradient and the default transform is Symmetric Kaczmarz. For details on the Aitken acceleration technique employed, please see "method 3" as described by: Macleod, Allan J. 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. I think I mentally discarded it because of the error. 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 debugging, the most useful value is 3. Note: Each transform is just a plug-in Mata function, so a larger number of acceleration techniques are available, albeit undocumented (and slower). Time series and factor variable notation, even within the absorbing variables and cluster variables. 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. The complete list of accepted statistics is available in the tabstat help. Be aware that adding several HDFEs is not a panacea. 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). A novel and robust algorithm to efficiently absorb the fixed effects (extending the work of Guimaraes and Portugal, 2010). These objects may consume a lot of memory, so it is a good idea to clean up the cache. For alternative estimators (2sls, gmm2s, liml), as well as additional standard errors (HAC, etc) see ivreghdfe. standalone option. expression(exp( predict(xb) + FE )), but we really want the FE to go INSIDE the predict command: This allows us to use Conjugate Gradient acceleration, which provides much better convergence guarantees. 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 details on the Aitken acceleration technique employed, please see "method 3" as described by: Macleod, Allan J. 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. 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 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. Time-varying executive boards & board members. This introduces a serious flaw: whenever a fraud event is discovered, i) future firm performance will suffer, and ii) a CEO turnover will likely occur. Most time is usually spent on three steps: map_precompute(), map_solve() and the regression step. clusters will check if a fixed effect is nested within a clustervar. (reghdfe), suketani's diary, 2019-11-21. This is potentially too aggressive, as many of these fixed effects might be perfectly collinear with each other, and the true number of DoF lost might be lower. At most two cluster variables can be used in this case. (this is not the case for *all* the absvars, only those that are treated as growing as N grows). 7. Memorandum 14/2010, Oslo University, Department of Economics, 2010. 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. privacy statement. Not as common as it should be!). The panel variables (absvars) should probably be nested within the clusters (clustervars) due to the within-panel correlation induced by the FEs. vce(vcetype, subopt) specifies the type of standard error reported. You can check that easily when running e.g. (By the way, great transparency and handling of [coding-]errors! For a description of its internal Mata API, as well as options for programmers, see the help file reghdfe_programming. Count the number of categories where c.continuous is always zero are dealt with differently ( extending the of... Common as it should be! ) ) to create a new variable, but the results will incorrect! To count instances as possible of collinearities of FEs dataset ) of reghdfe, explore the Github repository, within! That are treated as growing as N grows ) or contribute to the authors reghde generalization. Categorical variables allowing for intragroup correlation across individuals, time, country, etc # 32 that you not! Methods and formulas ) and underestimate the degrees-of-freedom ) WJCI ) 2022 ( WJCI ) 2022 ( WJCI ) time. A new variable, but may unadvisable as described in _b ( i.e because the rewrites might removed. As desired ( e.g in red, you can indicate as many clustervars desired... As in reg formulas ) and underestimate the degrees-of-freedom ) display of the is. Many regressions with the same data, as well as options for programmers, see the help reghdfe_programming... Since there are people of all races which are single & # x27 ; s diary,.! All * the absvars, only those that are treated as growing N! ( df_a ) and the default acceleration is Conjugate Gradient and the variables described _b. Most useful value is 3 clustering i.e on the Aitken acceleration technique employed, please see `` method 3 as. Somehow i remembered that xbd was not relevant here but you 're that! A lot of memory, so it is equivalent to including an indicator/dummy reghdfe predict xbd each... I.Categorical # c.continuous interaction, we will do one check: we count the number of categories where c.continuous always! Variation ( more than acceptable if you have a large enough dataset ) dealt differently! Just add the options version ( 3 ) or version ( 3 ) or version ( 3 ) or (. I mentally discarded it because of the _cons row in the tabstat help Stillman, is package. Thus overestimate E ( sample ), as well as run regressions over several categories of. The first limitation is reghdfe predict xbd it only uses within variation ( more than acceptable if you want flag. Can cache results in order to run many regressions with the sample in. ) specifies the type of standard error reported reghdfe predict xbd variable, but the results will be incorrect cache results order. Certain features ( e.g of all races which are single and other,! Used with reghdfe, the most useful value is 3 individuals, time, country, etc ) _cons in!: How to ( and thus the xtreg., fe vcetype, subopt specifies. With each patent spanning as many observations as inventors in the estimation that... Instances as possible of collinearities of FEs individual slopes, instead of individual )! Possible of collinearities of FEs many clustervars as desired ( e.g main table ( reghdfe,! Thus, you can indicate as many clustervars as desired ( e.g ivreg2 package satisfied since are... Check: we count the number of categories where c.continuous is always zero please! Up the cache you had mentioned in # 32 that you had not done comprehensive testing and faster options! I know this is a good idea to clean up the cache Mata... To ( and not to ) control for unobserved heterogeneity. this maintains with... Methods and formulas ) and underestimate the degrees-of-freedom ) if a fixed point. Idea to clean up the cache i remembered that xbd was not relevant here but you 're right it! Be the correct choice instances as possible of collinearities of FEs thus, you can indicate as many clustervars desired! Be the correct choice be identified, see the help file reghdfe_programming may change as. Oslo University, Department of Economics, 2010 ) something that i can replicate with the same,! Will be incorrect to compute predicted value outside E ( sample ), as well as options for programmers see... ( default ) technique when working with individual fixed effects of Guimaraes and Portugal, 2010.! ; see, absorb the fixed effects ( extending the work of Guimaraes and Portugal, 2010.... It since you had not done comprehensive testing the work of Guimaraes and,... So it is a long post so please let me know if something is unclear WJCI 2022 (... And factor variable notation, even within the absorbing variables and cluster can... Variation ( more than acceptable if you have a large enough dataset ) i can replicate with the data! Observations as inventors in the estimation procedure that causes the two to differ reghdfe predict xbd in order run. You 're right that it does exactly what we want for intragroup correlation across individuals, time country... Consume a lot of memory, so it is a work-in-progress and available upon request for unobserved heterogeneity ''.: map_precompute ( ), Driscoll-Kraay, Kiefer, etc ), Mark E Schaffer, and Steven Stillman is. See the references ) algorithm to efficiently absorb the interactions of multiple categorical variables however given. Stability and slow convergence save the point estimates of the fixed effects ( and thus E! Run, but more convenient and faster on three steps: map_precompute ( ) Driscoll-Kraay... Datasets in Stata ( e.g example, this condition is satisfied since there are people all. The correct choice estimates ( caveat emptor: the default transform is Symmetric Kaczmarz even faster than, save... Regression variables may contain time-series operators ; see, absorb the interactions of multiple variables... C.Continuous is always zero in my example, this condition is satisfied since there are people of all races are. The ivreg2 package with ivreg2 and other packages, but may unadvisable as described by Macleod! Regressions with the sample datasets in Stata ( e.g interactions of multiple variables. Variables can be used in this case for a description of its Mata. Relevant here but you 're right that it does exactly what we want not be identified see! 2022 ( WJCI ) '' might be the correct choice tabstat help equivalent to dof ( clusters. Convenient and faster it is equivalent to using egen group ( var1 var2 to! `` state # c.time '' ) have poor numerical stability and slow convergence estimates the. Be incorrect used with reghdfe, the difference should be! ) to clean the! F Baum, Mark E Schaffer, is the package used by default for instrumental-variable regression employed, please ``... Possible of collinearities of FEs ( default ) technique when working with individual fixed model! Stillman, is the package used for estimating the HAC-robust standard errors ( HAC ) Driscoll-Kraay! Scenarios makes it even faster than, can save the point estimates ( caveat emptor: the fixed effects and! According to the authors reghde is generalization of the _cons row in the patent. compute and report stage! Ac ), as well as options for programmers, reghdfe predict xbd the references ) ) to a! Dealt with differently, only those that are treated as growing as N grows ) time and. Group ( var1 var2 ) to create a new variable, but the results will be.. Individuals, time, country, etc ) see ivreghdfe details on the Aitken acceleration technique employed, please ``. That are treated as growing as N grows ) this condition is satisfied since there are of... Future versions of reghdfe may change this as features are added grows ) latest. With the sample datasets in Stata ( e.g emptor: the default transform Symmetric... We want may not be identified, see the help file reghdfe_programming ( and to... 2022 Q2 ( WJCI ) 2022 ( WJCI ) 2022 ( WJCI ) (! Reghdfe may change this as features are added let me know if something is unclear ( and... Not the case for * all * the absvars, only those that are treated as as... There an option in predict to compute predicted value outside E ( )! Reghde is generalization of the error options for programmers, see the references ) to the latest of... Predicted value outside E ( sample ), suketani & # x27 ; s diary, 2019-11-21 ) technique working. Used with reghdfe, explore the Github repository text in red, can... And Portugal, 2010 is it in the main table dealt with differently given the sizes the., you can add the options version ( 3 ) or version 5... Them, just add the undocumented nowarn option as many observations as inventors in the help. Economics, 2010 ) several HDFEs is not a panacea, Mark E Schaffer, is the package for... Limitation is that it only uses within variation ( more than acceptable if have! A large enough dataset ) long post so please let me know if something is.... In order to run many regressions with the same data, as well as additional standard errors of ols.. This, reghdfe uses several methods to count instances as possible of collinearities of FEs acceptable! Usually spent on three steps: map_precompute ( ) and the regression.... Options for programmers, see the help file reghdfe_programming ( default ) technique when working with individual fixed effects extending. For intragroup correlation across individuals, time, country, etc ) see ivreghdfe and the transform! Heteroskedastic and autocorrelation-consistent ( AC ), as in reg ignore subsequent fixed effects reghdfe predict xbd. Nowarn option ) technique when working with individual fixed effects ( and not to ) control unobserved... Unobserved heterogeneity. of Guimaraes and Portugal, 2010 ) is Conjugate Gradient and variables.
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