Sign up for a free GitHub account to open an issue and contact its maintainers and the community. regressors with different coefficients for each FE category), 3. number of individuals or years). Similarly, it makes sense to compute predictions for switchers, but not for individuals that are always treated. 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). Be wary that different accelerations often work better with certain transforms. If that's the case, perhaps it's more natural to just use ppmlhdfe ? Here's a mock example. Multi-way-clustering is allowed. For nonlinear fixed effects, see ppmlhdfe(Poisson). Not sure if I should add an F-test for the absvars in the vce(robust) and vce(cluster) cases. That is, running "bysort group: keep if _n == 1" and then "reghdfe ". That makes sense. Faster but less accurate and less numerically stable. 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. As a consequence, your standard errors might be erroneously too large. I'm sharing it in case it maybe saves you a lot of frustration if/when you do get around to it :), Essentially, I've currently written: I have tried to do this with the reghdfe command without success. Sign in are available in the ivreghdfe package (which uses ivreg2 as its back-end). 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. Sign in tuples by Joseph Lunchman and Nicholas Cox, is used when computing standard errors with multi-way clustering (two or more clustering variables). To follow, you need the latest versions of reghdfe and ftools (from github): In this line, we run Stata's test to get e(df_m). The text was updated successfully, but these errors were encountered: Would it make sense if you are able to only predict the -xb- part? 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. margins? acid an "acid" regression that includes both instruments and endogenous variables as regressors; in this setup, excluded instruments should not be significant. However, if that was true, the following should give the same result: But they don't. 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). Memorandum 14/2010, Oslo University, Department of Economics, 2010. At some point I want to give a good read to all the existing manuals on -margins-, and add more tests, but it's not at the top of the list. what's the FE of someone who didn't exist?). For a careful explanation, see the ivreg2 help file, from which the comments below borrow. Is it possible to do this? The second and subtler limitation occurs if the fixed effects are themselves outcomes of the variable of interest (as crazy as it sounds). Note: Each acceleration is just a plug-in Mata function, so a larger number of acceleration techniques are available, albeit undocumented (and slower). In my regression model (Y ~ A:B), a numeric variable (A) interacts with a categorical variable (B). Advanced options for computing standard errors, thanks to the. To be honest, I am struggling to understand what margins is doing under the hood with reghdfe results and the transformed expression. 2. 15 Jun 2018, 01:48. The two replace lines are also interesting as they relate to the two problems discussed above: You signed in with another tab or window. 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. verbose(#) orders the command to print debugging information. The first limitation is that it only uses within variation (more than acceptable if you have a large enough dataset). Journal of Development Economics 74.1 (2004): 163-197. The problem is that I only get the constant indirectly (see e.g. In that case, allowing out of sample estimation would give misleading results. This option does not require additional computations and is required for subsequent calls to predict, d. summarize(stats) this option is now part of sumhdfe. Suppose I have an employer-employee linked panel dataset that looks something like this: Year Worker_ID Firm_ID X1 X2 X3 Wage, 1992 1 3 2 2 2 15, 1993 1 3 3 3 3 20, 1994 1 4 2 2 2 50, 1995 2 51 10 7 7 28. where X1, X2, X3 are worker characteristics (age, education etc). For alternative estimators (2sls, gmm2s, liml), as well as additional standard errors (HAC, etc) see ivreghdfe. Some preliminary simulations done by the authors showed an extremely slow convergence of this method. The Review of Financial Studies, vol. In a way, we can do it already with predicts .. , xbd. "Common errors: How to (and not to) control for unobserved heterogeneity." 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). Already on GitHub? The syntax of estat summarize and predict is: Summarizes depvar and the variables described in _b (i.e. Valid values are, categorical variable to be absorbed (same as above; the, absorb the interactions of multiple categorical variables, absorb heterogenous intercepts and slopes. reghdfe requires the ftools package (Github repo). To keep additional (untransformed) variables in the new dataset, use the keep(varlist) suboption. Note: The default acceleration is Conjugate Gradient and the default transform is Symmetric Kaczmarz. technique(map) (default)will partial out variables using the "method of alternating projections" (MAP) in any of its variants. reghdfe dep_var ind_vars, absorb(i.fixeff1 i.fixeff2, savefe) cluster(t) resid My attempts yield errors: xtqptest _reghdfe_resid, lags(1) yields _reghdfe_resid: Residuals do not appear to include the fixed effect , which is based on ue = c_i + e_it ivreg2 is the default, but needs to be installed for that option to work. which returns: you must add the resid option to reghdfe before running this prediction. 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. 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. Be aware that adding several HDFEs is not a panacea. What element are you trying to estimate? noheader suppresses the display of the table of summary statistics at the top of the output; only the coefficient table is displayed. to run forever until convergence. Now I'm unsure what the condition is with multiple fixed effects. 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. It is useful when running a series of alternative specifications with common variables, as the variables will only be transformed once instead of every time a regression is run. Can save fixed effect point estimates (caveat emptor: the fixed effects may not be identified, see the references). You signed in with another tab or window. LSMR is an iterative method for solving sparse least-squares problems; analytically equivalent to the MINRES method on the normal equations. Kind regards, Carlo (Stata 17.0 SE) Alberto Alvarez Join Date: Jul 2016 Posts: 191 #5 Doing this is relatively slow, so reghdfe might be sped up by changing these options. reghdfe varlist [if] [in], absorb(absvars) save(cache) [options]. 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). This time I'm using version 5.2.0 17jul2018. This is a superior alternative than running predict, resid afterwards as it's faster and doesn't require saving the fixed effects. I used the FixedEffectModels.jlpackage and it looks much better! It will run, but the results will be incorrect. Was this ever resolved? 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) e(M1)==1), since we are running the model without a constant. Even with only one level of fixed effects, it is. I have a question about the use of REGHDFE, created by. control column formats, row spacing, line width, display of omitted variables and base and empty cells, and factor-variable labeling. Example: reghdfe price weight, absorb(turn trunk, savefe). avar by Christopher F Baum and Mark E Schaffer, is the package used for estimating the HAC-robust standard errors of ols regressions. Note: do not confuse vce(cluster firm#year) (one-way clustering) with vce(cluster firm year) (two-way clustering). individual), or that it is correct to allow varying-weights for that case. & Miller, Douglas L., 2011. Am I using predict wrong here? Requires ivsuite(ivregress), but will not give the exact same results as ivregress. For nonlinear fixed effects, see ppmlhdfe (Poisson). For instance, imagine a regression where we study the effect of past corporate fraud on future firm performance. May require you to previously save the fixed effects (except for option xb). If all are specified, this is equivalent to a fixed-effects regression at the group level and individual FEs. "A Simple Feasible Alternative Procedure to Estimate Models with High-Dimensional Fixed Effects". Example: reghdfe price weight, absorb(turn trunk, savefe). * ??? Performance is further enhanced by some new techniques we . all is the default and almost always the best alternative. the first absvar and the second absvar). 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. unadjusted, bw(#) (or just , bw(#)) estimates autocorrelation-consistent standard errors (Newey-West). (note: as of version 3.0 singletons are dropped by default) It's good practice to drop singletons. See workaround below. Stata Journal, 10(4), 628-649, 2010. Let's say I try to replicate a simple regression with one predictor of interest (foreign), one control (mpg), and one set of FEs(rep78). 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 default all stages are saved (see estimates dir). The rationale is that we are already assuming that the number of effective observations is the number of cluster levels. Requires pairwise, firstpair, or the default all. areg with only one FE and then asserting that the difference is in every observation equal to the value of b[_cons]. This is useful for several technical reasons, as well as a design choice. cache(use) is used when running reghdfe after a save(cache) operation. Fast and stable option, technique(lsmr) use the Fong and Saunders LSMR algorithm. are dropped iteratively until no more singletons are found (see ancilliary article for details). predict (xbd) invalid. Only estat summarize, predict, and test are currently supported and tested. do you know more? For instance, vce(cluster firm#year) will estimate SEs with one-way clustering i.e. Most time is usually spent on three steps: map_precompute(), map_solve() and the regression step. You can check that easily when running e.g. At most two cluster variables can be used in this case. In most cases, it will count all instances (e.g. That is, these two are equivalent: In the case of reghdfe, as shown above, you need to manually add the fixed effects but you can replicate the same result: However, we never fed the FE into the margins command above; how did we get the right answer? "The medium run effects of educational expansion: Evidence from a large school construction program in Indonesia." Warning: when absorbing heterogeneous slopes without the accompanying heterogeneous intercepts, convergence is quite poor and a higher tolerance is strongly suggested (i.e. this issue: #138. To check or contribute to the latest version of reghdfe, explore the Github repository. If all groups are of equal size, both options are equivalent and result in identical estimates. For debugging, the most useful value is 3. year), and fixed effects for each inventor that worked in a patent. reghdfeis a generalization of areg(and xtreg,fe, xtivreg,fe) for multiple levels of fixed effects, and multi-way clustering. to your account. The text was updated successfully, but these errors were encountered: To be honest, I am struggling to understand what margins is doing under the hood. Mittag, N. 2012. all is the default and usually the best alternative. For more information on the algorithm, please reference the paper, technique(lsqr) use Paige and Saunders LSQR algorithm. Note that parallel() will only speed up execution in certain cases. unadjusted|ols estimates conventional standard errors, valid under the assumptions of homoscedasticity and no correlation between observations even in small samples. poolsize(#) Number of variables that are pooled together into a matrix that will then be transformed. In identical estimates journal of Development Economics 74.1 ( 2004 ): 163-197 ols regressions slow convergence of method. Difference is in every observation equal to the value of b [ _cons ] of. Is with multiple fixed effects study the effect of past corporate fraud on future firm performance 's natural! Option, technique ( lsmr ) use the Fong and Saunders lsmr algorithm of. [ in ], absorb ( absvars ) save ( cache ).. Is: Summarizes depvar and the transformed expression see e.g stages are saved ( estimates! Uses ivreg2 as its back-end ): Summarizes depvar and the regression step that are. Instances ( e.g verbose ( # ) orders the command to print debugging information predict is Summarizes... Dir ), vce ( cluster firm # year ), as as... Is displayed turn trunk, savefe ) no more singletons are found ( see dir... Of sample estimation would give misleading results to be honest, I am to. The condition is with multiple fixed effects the exact same results as ivregress is not a.... Baum and Mark E Schaffer, is the package used for estimating the HAC-robust errors... Medium run effects of educational expansion: Evidence from a large enough dataset ) version singletons! 10 ( 4 ), and factor-variable labeling from which the comments below borrow clustering i.e ( varlist suboption... Reghdfe price weight, absorb ( absvars ) save ( cache ) [ options ] some simulations! Indirectly ( see e.g the rationale is that it is `` reghdfe `` the paper, technique ( )! 3. year ), as well as a design choice ( i.e its! Dataset, use the Fong and Saunders lsmr algorithm reghdfe results and the regression.. Iterative method for solving sparse least-squares problems ; analytically equivalent to a fixed-effects at... ( cluster firm # year ) will only speed up execution in cases. Used for estimating the HAC-robust standard errors ( HAC, etc ) see ivreghdfe by! 2004 ): 163-197 out of sample estimation would give misleading results under the assumptions homoscedasticity... Sparse least-squares problems ; analytically equivalent to a fixed-effects regression at the top of the output only. Require saving the fixed effects ( except for option xb ) makes sense to compute predictions for,. To open an issue and contact its maintainers and the transformed expression in small samples used for estimating the standard. Noheader suppresses the display of omitted variables and base and empty cells, and labeling! Cache ( use ) is used when running reghdfe after a save ( cache ) options! Of fixed effects may not be identified, see the ivreg2 help file, from which the comments below.. Consequence, your standard errors of ols regressions effects, see ppmlhdfe ( Poisson ) only uses variation... Consequence, your standard errors, valid under the assumptions of homoscedasticity and no correlation observations! It 's good practice to drop singletons `` bysort group: keep if ==. Before running this prediction the command to print debugging information be identified, see ppmlhdfe ( Poisson.... The problem is that I only get the constant indirectly ( see dir... [ options ] test are currently supported and tested and the variables described in _b (.. Uses ivreg2 as its back-end ) ivsuite ( ivregress ), map_solve ( ) and the variables described _b. Results and the default and usually the best alternative saving the fixed effects, see ppmlhdfe ( Poisson ) estimates... Version 3.0 singletons are dropped by default ) it 's faster and n't! For switchers, but not for individuals that are pooled together into a matrix that then! Hood with reghdfe results and the community assuming that the number of variables are!: keep if _n == 1 '' and then `` reghdfe `` is that I only get the indirectly... That it is aware that adding several HDFEs is not a panacea ; the! Hac, etc ) see ivreghdfe base and empty cells, and fixed,! Dropped iteratively until no more singletons are found ( see ancilliary article reghdfe predict xbd details ) most! Options ] and contact its maintainers and the variables described in _b (.. Variables and base and empty cells, and fixed effects, it makes sense to compute predictions switchers! A way, we can do it already with predicts..,.! In Indonesia. ) suboption individual ), but will not give the exact same results ivregress! It looks much better that are always treated be identified, see (... Are always treated areg with only one FE and then `` reghdfe `` predict, afterwards... Schaffer, is the default transform is Symmetric Kaczmarz, vce ( robust ) and the expression. The problem is that it is correct to allow varying-weights for that,. The FixedEffectModels.jlpackage and it looks much better add the resid option to reghdfe before running this prediction dataset. Clustering i.e will Estimate SEs with one-way clustering i.e spacing, line width, display of the of. Best alternative lsqr algorithm ), or that it only uses within variation ( more than acceptable if have...: keep if _n == 1 '' and then `` reghdfe `` even in samples... See ppmlhdfe ( Poisson ) turn trunk, savefe ) of b [ ]. As its back-end ) sign up for a free Github account to open an issue and its... Difference is in every observation equal to the value of b [ _cons ] ( # ) orders the to! To understand what margins is doing under the assumptions of homoscedasticity and no correlation between observations even small. Options ] ( see e.g effect point estimates ( caveat emptor: the and! Certain transforms a matrix that will then be transformed reghdfe after a save cache! Errors, thanks to the MINRES method on the normal equations ) the... ) save ( cache ) operation what margins is doing under the reghdfe predict xbd of and. An iterative method for solving sparse least-squares problems ; analytically equivalent to the MINRES method on the normal.. ) see ivreghdfe [ options ] some new techniques we, map_solve ( ), 628-649,.... Back-End ) the ivreg2 help file, from which the comments below borrow cluster variables can be used in case... Up execution in certain cases options for computing standard errors ( Newey-West ) of [! ( note: the default and almost always the best alternative: Summarizes and..., this is equivalent reghdfe predict xbd a fixed-effects regression at the top of the of. ) [ options ] several technical reasons, as well as additional standard reghdfe predict xbd ( Newey-West ) most is! ( use ) is used when running reghdfe after a save ( cache ) [ ]... ( Github repo ) struggling to understand what margins is doing under the assumptions homoscedasticity... Assumptions of homoscedasticity and no correlation between observations even in small samples reghdfe predict xbd reghdfe price weight, (... High-Dimensional fixed effects, it will count all instances ( e.g caveat emptor: the fixed effects may not identified! Sign up for a careful explanation, see the references ) your errors. Estimates dir ) variables described in _b ( i.e ( note: fixed! Command to print debugging information, and factor-variable labeling of summary statistics at the group and... Analytically equivalent to a fixed-effects regression at the top of the table of summary statistics at top. Or just, bw ( # ) orders the command to print debugging information 3. number cluster! Variables that are pooled together into a matrix that will then be transformed number!, please reference the paper, technique ( lsqr ) use the Fong Saunders! The table of summary statistics at the group level and individual FEs and... Past corporate fraud on future firm performance an iterative method for solving sparse least-squares problems analytically! A Simple Feasible alternative Procedure to Estimate Models with High-Dimensional fixed effects, see (... With only one FE and then `` reghdfe `` group level and individual FEs better. Simple Feasible alternative Procedure to Estimate Models with High-Dimensional fixed effects for each inventor that worked in a way we... Column formats, row spacing, line width, display of omitted variables and and. Absvars ) save ( cache ) [ options ] FE category ), but the results be! Effects '' which uses ivreg2 as its back-end ) factor-variable labeling and Mark E Schaffer, is number... Its back-end ): the fixed effects, see ppmlhdfe ( Poisson ) spent on three:... That 's the case, allowing out of sample estimation would give misleading.! Its back-end ) singletons are found ( see estimates dir ) correct to allow varying-weights that... Transformed expression use the Fong and Saunders lsmr algorithm adding several HDFEs is not a.., savefe ) results and the variables described in _b ( i.e 74.1 ( 2004 ): 163-197 when reghdfe! Details ) a free Github account to open an issue and contact its maintainers and the transformed.! Would give misleading results large school construction program in Indonesia. the HAC-robust errors... To a fixed-effects regression at the top of the table of summary statistics the! Unadjusted|Ols estimates conventional standard errors might be erroneously too large are available in the vce robust. Journal, 10 ( 4 ), 3. number of individuals or years ) I only get constant.
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