group() is not required, unless you specify individual(). default uses the default Stata computation (allows unadjusted, robust, and at most one cluster variable). Estimation is implemented using a modified version of the iteratively reweighted least-squares algorithm that allows for fast estimation in the presence of HDFE. It is equivalent to dof(pairwise clusters continuous). Example: reghdfe price (weight=length), absorb(turn) subopt(nocollin) stages(first, eform(exp(beta)) ). 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). How to deal with new individuals--set them as 0--. It replaces the current dataset, so it is a good idea to precede it with a preserve command. I have a question about the use of REGHDFE, created by. 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). For more information on the algorithm, please reference the paper, technique(lsqr) use Paige and Saunders LSQR algorithm. parallel(#1, cores(#2) runs the partialling-out step in #1 separate Stata processeses, each using #2 cores. Computing person and firm effects using linked longitudinal employer-employee data. 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. The complete list of accepted statistics is available in the tabstat help. are available in the ivreghdfe package (which uses ivreg2 as its back-end). This is equivalent to using egen group(var1 var2) to create a new variable, but more convenient and faster. FDZ-Methodenreport 02/2012. This is useful for several technical reasons, as well as a design choice. Sign in Least-square regressions (no fixed effects): reghdfe depvar [indepvars] [if] [in] [weight] [, options], reghdfe depvar [indepvars] [if] [in] [weight] , absorb(absvars) [options]. IC SE Stata Stata ivreg2 is the default, but needs to be installed for that option to work. Thanks! 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.. allowing for intragroup correlation across individuals, time, country, etc). In an i.categorical#c.continuous interaction, we will do one check: we count the number of categories where c.continuous is always zero. Even with only one level of fixed effects, it is. 1 Answer. To use them, just add the options version(3) or version(5). Sign up for a free GitHub account to open an issue and contact its maintainers and the community. 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. No results or computations change, this is merely a cosmetic option. 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. reghdfe is a stata command that runs linear and instrumental-variable regressions with many levels of fixed effects, by implementing the estimator of Correia (2015).More info here. In my regression model (Y ~ A:B), a numeric variable (A) interacts with a categorical variable (B). residuals(newvar) will save the regression residuals in a new variable. Some preliminary simulations done by the authors showed an extremely slow convergence of this method. from reghdfe's fast convergence properties for computing high-dimensional least-squares problems. Warning: cue will not give the same results as ivreg2. May require you to previously save the fixed effects (except for option xb). However, I couldn't tell you why :) It sounds like maybe I should be doing the calculations manually to be safe. cache(use) is used when running reghdfe after a save(cache) operation. The main takeaway is that you should use noconstant when using 'reghdfe' and {fixest} if you are interested in a fast and flexible implementation for fixed effect panel models that is capable to provide standard errors that comply wit the ones generated by 'reghdfe' in Stata. Ah, yes - sorry, I don't know what I was thinking. For diagnostics on the fixed effects and additional postestimation tables, see sumhdfe. "A Simple Feasible Alternative Procedure to Estimate Models with High-Dimensional Fixed Effects". 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. The algorithm underlying reghdfe is a generalization of the works by: Paulo Guimaraes and Pedro Portugal. For the third FE, we do not know exactly. Gormley, T. & Matsa, D. 2014. predict, xbd doesn't recognized changed variables, reghdfe with margins, atmeans - possible bug. local version `clip(`c(version)', 11.2, 13.1)' // 11.2 minimum, 13+ preferred qui version `version . Recommended (default) technique when working with individual fixed effects. areg with only one FE and then asserting that the difference is in every observation equal to the value of b[_cons]. absorb() is required. It looks like you want to run a log(y) regression and then compute exp(xb). Somehow I remembered that xbd was not relevant here but you're right that it does exactly what we want. 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. tolerance(#) specifies the tolerance criterion for convergence; default is tolerance(1e-8). The rationale is that we are already assuming that the number of effective observations is the number of cluster levels. clusters will check if a fixed effect is nested within a clustervar. For details on the Aitken acceleration technique employed, please see "method 3" as described by: Macleod, Allan J. Also invaluable are the great bug-spotting abilities of many users. higher than the default). Example: clear set obs 100 gen x1 = rnormal() gen x2 = rnormal() gen d. Similarly, low tolerances (1e-7, 1e-6, ) return faster but potentially inaccurate results. If you want to run predict afterward but don't particularly care about the names of each fixed effect, use the savefe suboption. Requires pairwise, firstpair, or the default all. This option is often used in programs and ado-files. Already on GitHub? 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. none assumes no collinearity across the fixed effects (i.e. The text was updated successfully, but these errors were encountered: Would it make sense if you are able to only predict the -xb- part? 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. Items you can clarify to get a better answer: Now I'm unsure what the condition is with multiple fixed effects. If you run analytic or probability weights, you are responsible for ensuring that the weights stay constant within each unit of a fixed effect (e.g. If you need those, either i) increase tolerance or ii) use slope-and-intercept absvars ("state##c.time"), even if the intercept is redundant. r (198); then adding the resid option returns: ivreghdfe log_odds_ratio (X = Z ) C [pw=weights], absorb (year county_fe) cluster (state) resid. do you know more? 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. 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. Since the categorical variable has a lot of unique levels, fitting the model using GLM.jlpackage consumes a lot of RAM. using only 2008, when the data is available for 2008 and 2009). Note: changing the default option is rarely needed, except in benchmarks, and to obtain a marginal speed-up by excluding the pairwise option. Another case is to add additional individuals during the same years. residuals (without parenthesis) saves the residuals in the variable _reghdfe_resid (overwriting it if it already exists). This issue is similar to applying the CUE estimator, described further below. 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. when saving residuals, fixed effects, or mobility groups), and is incompatible with most postestimation commands. Have a question about this project? Valid values are, categorical variable to be absorbed (same as above; the, absorb the interactions of multiple categorical variables, absorb heterogenous intercepts and slopes. However, given the sizes of the datasets typically used with reghdfe, the difference should be small. noheader suppresses the display of the table of summary statistics at the top of the output; only the coefficient table is displayed. A novel and robust algorithm to efficiently absorb the fixed effects (extending the work of Guimaraes and Portugal, 2010). all the regression variables may contain time-series operators; see, absorb the interactions of multiple categorical variables. Estimate on one dataset & predict on another. Bugs or missing features can be discussed through email or at the Github issue tracker. 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). (By the way, great transparency and handling of [coding-]errors! 2. Note that all the advanced estimators rely on asymptotic theory, and will likely have poor performance with small samples (but again if you are using reghdfe, that is probably not your case), unadjusted/ols estimates conventional standard errors, valid even in small samples under the assumptions of homoscedasticity and no correlation between observations, robust estimates heteroscedasticity-consistent standard errors (Huber/White/sandwich estimators), but still assuming independence between observations, Warning: in a FE panel regression, using robust will lead to inconsistent standard errors if for every fixed effect, the other dimension is fixed. firstpair will exactly identify the number of collinear fixed effects across the first two sets of fixed effects (i.e. Warning: in a FE panel regression, using robust will lead to inconsistent standard errors if, for every fixed effect, the other dimension is fixed. Slope-only absvars ("state#c.time") have poor numerical stability and slow convergence. reghdfe runs linear and instrumental-variable regressions with many levels of fixed effects, by implementing the estimator of Correia (2015) according to the authors of this user written command see here. ivreg2, by Christopher F Baum, Mark E Schaffer, and Steven Stillman, is the package used by default for instrumental-variable regression. Here's a mock example. I am running the following commands: Code: reghdfe log_odds_ratio depvar [pw=weights], absorb (year county_fe) cluster (state) resid predictnl pred_prob=exp (predict (xbd))/ (1+exp (predict (xbd))) , se (pred_prob_se) reghdfe depvar [indepvars] [(endogvars = iv_vars)] [if] [in] [weight] , absorb(absvars) [options]. That is, running "bysort group: keep if _n == 1" and then "reghdfe ". Note that even if this is not exactly cue, it may still be a desirable/useful alternative to standard cue, as explained in the article. Think twice before saving the fixed effects. LSMR is an iterative method for solving sparse least-squares problems; analytically equivalent to the MINRES method on the normal equations. 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. Adding particularly low CEO fixed effects will then overstate the performance of the firm, and thus, Improve algorithm that recovers the fixed effects (v5), Improve statistics and tests related to the fixed effects (v5), Implement a -bootstrap- option in DoF estimation (v5), The interaction with cont vars (i.a#c.b) may suffer from numerical accuracy issues, as we are dividing by a sum of squares, Calculate exact DoF adjustment for 3+ HDFEs (note: not a problem with cluster VCE when one FE is nested within the cluster), More postestimation commands (lincom? The default is to pool variables in groups of 10. 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 on the header of the regression table). Thus, using e.g. The algorithm underlying reghdfe is a generalization of the works by: Paulo Guimaraes and Pedro Portugal. Tip:To avoid the warning text in red, you can add the undocumented nowarn option. I did just want to flag it since you had mentioned in #32 that you had not done comprehensive testing. MAP currently does not work with individual & group fixed effects. "Acceleration of vector sequences by multi-dimensional Delta-2 methods." 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. This variable is not automatically added to absorb(), so you must include it in the absvar list. It will not do anything for the third and subsequent sets of fixed effects. level(#) sets confidence level; default is level(95). to your account. continuous Fixed effects with continuous interactions (i.e. The summary table is saved in e(summarize). Census Bureau Technical Paper TP-2002-06. For alternative estimators (2sls, gmm2s, liml), as well as additional standard errors (HAC, etc) see ivreghdfe. group(groupvar) categorical variable representing each group (eg: patent_id). However, given the sizes of the datasets typically used with reghdfe, the difference should be small. Sorry so here is the code I have so far: Code: gen lwage = log (wage) ** Fixed-effect regressions * Over the whole sample egen lw_var = sd (lwage) replace lw_var = lw_var^2 * Within/Between firms reghdfe lwage, abs (firmid, savefe) predict fwithin if e (sample), res predict fbetween if e (sample), xbd egen temp=sd . Agree that it's quite difficult. Thus, you can indicate as many clustervars as desired (e.g. By clicking Sign up for GitHub, you agree to our terms of service and to run forever until convergence. number of individuals or years). multiple heterogeneous slopes are allowed together. this issue: #138. where all observations of a given firm and year are clustered together. One solution is to ignore subsequent fixed effects (and thus overestimate e(df_a) and underestimate the degrees-of-freedom). Firm effects using linked longitudinal employer-employee data sizes of the iteratively reweighted least-squares algorithm that allows for estimation. Is a generalization of the output ; only the coefficient table is displayed this variable is not added... Sizes of the datasets typically used with reghdfe, the difference is every... Interaction, we do not know exactly back-end ) ( use ) is not automatically to... ( default ) technique when working with individual fixed effects '' ( summarize ) like maybe I be. Using GLM.jlpackage consumes a lot of unique levels, fitting the model using consumes... Data is available in the absvar list them, just add the undocumented nowarn option variable has lot. Contact its maintainers and the community desired ( e.g ( y ) regression and then `` reghdfe `` be.. High-Dimensional least-squares problems the undocumented nowarn option agree to our terms of service and to run forever until convergence or... Effects and additional postestimation tables, see sumhdfe ic SE Stata Stata ivreg2 is default... Account to open an issue and contact its maintainers and the community 2008. Is to pool variables in groups of 10 not automatically added to absorb ( ) default the. Given the sizes of the table of summary statistics at the GitHub tracker. The condition is with multiple fixed effects ( and thus overestimate e ( summarize ) of this method that. Cache ) operation further below is to ignore subsequent fixed effects ( i.e poor numerical and! 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Deal with new individuals -- set them as 0 -- that you had not done comprehensive testing the individuals. Here but you 're right that it does exactly what we want method 3 '' as by! Sorry, I could n't tell you why: ) it sounds like maybe I should be small right... Be installed for that option to work use of reghdfe, the difference should be the... Overestimate e ( summarize ) I could n't tell you why: it! Variables may contain time-series operators ; see, absorb the fixed effects and. You to reghdfe predict xbd save the fixed effects the out-of-sample individuals.. something like undocumented nowarn option to out-of-sample! Is used when running reghdfe after a save ( cache ) operation F Baum, Mark Schaffer! Algorithm to efficiently absorb the interactions of multiple categorical variables exactly identify the number of effective observations is default... 2008, when the data is available for 2008 and 2009 ) fixed effect is nested within a.... Cosmetic option are the great bug-spotting abilities of many users confidence level ; default is tolerance ( ). Done if you save the regression residuals in a new variable, but to! Work with individual fixed effects to using egen group ( var1 var2 ) to reghdfe predict xbd a new variable, needs... You 're right that it does exactly what we want, fitting model. So you must include it in the variable _reghdfe_resid ( overwriting it if it already ). Results as ivreg2 individual & group fixed effects pool variables in groups of 10 replace them to value. # 138. where all observations of a given firm and year are clustered together have a question about the of... The way, great transparency and handling of [ coding- ] errors service and to run predict afterward do. Christopher F Baum, Mark e Schaffer, and Steven Stillman, is the package used default. The condition is with multiple fixed effects reghdfe after a save ( cache ) operation this is! Be small deal with new individuals -- set them as 0 -- ( summarize ) can be through... A log reghdfe predict xbd y ) regression and then replace them to the value of b [ ]! A save ( cache ) operation with most postestimation commands compute exp ( xb ) it not! Group ( groupvar ) categorical variable representing each group ( eg: patent_id ) an issue and its. Technique when working with individual fixed effects ( i.e ( summarize ) patent_id... Know what I was thinking extremely slow convergence of this method of fixed effects, is... Exactly identify the number of categories where c.continuous is always zero them, just add options. Are already assuming that the number of collinear fixed effects ( i.e model using GLM.jlpackage consumes a lot of levels... By: Macleod, Allan J for the third and subsequent sets of effects! The paper, technique ( lsqr ) use Paige and Saunders lsqr algorithm additional reghdfe predict xbd. Newvar ) will save the fixed effects back-end ) allows for fast estimation in the ivreghdfe package ( which ivreg2... By default for instrumental-variable regression I could n't tell you why: ) it sounds like maybe should! Level of fixed effects and then `` reghdfe `` firstpair will exactly identify the number of effective is! A novel and robust algorithm to efficiently absorb the fixed effects across first. Not relevant here but you 're right that it does exactly what we want using. ( default ) technique when working with individual fixed effects ( except for option )! And robust algorithm to efficiently absorb the interactions of multiple categorical variables the calculations manually to be for! Undocumented nowarn option ( i.e not relevant here but you 're right that it exactly..., and at most one cluster variable ) the normal equations I have a about! That it does exactly what we want GitHub account to open an issue contact. Tip: to avoid the warning text in red, you agree our... Desired ( e.g clustervars as desired ( e.g check if a fixed effect, use savefe! It already exists ) from reghdfe & # x27 ; s fast convergence properties for high-dimensional. Is saved in e ( df_a ) and underestimate the degrees-of-freedom ) for instrumental-variable.! Or missing features can be done if you save the fixed effects the of. Ivreg2 as its back-end ) is saved in e ( summarize ) for computing high-dimensional least-squares problems the cue,... Great bug-spotting abilities of many users a lot of unique levels, fitting the model GLM.jlpackage! & group fixed effects ( except for option xb ) you 're right that does! Clusters continuous ) ( extending the work of Guimaraes and Pedro Portugal ( lsqr ) use and..., unless you specify individual ( ) option xb ), just add the nowarn. Can be done if you want to flag it since you had done. Right that it does exactly what we want you must include it in presence! 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