reghdfe predict xbd
display_options: noomitted, vsquish, noemptycells, baselevels, allbaselevels, nofvlabel, fvwrap(#), fvwrapon(style), cformat(%fmt), pformat(%fmt), sformat(%fmt), and nolstretch; see [R] estimation options. acid an "acid" regression that includes both instruments and endogenous variables as regressors; in this setup, excluded instruments should not be significant. privacy statement. Warning: it is not recommended to run clustered SEs if any of the clustering variables have too few different levels. Communications in Applied Numerical Methods 2.4 (1986): 385-392. With the reg and predict commands it is possible to make out-of-sample predictions, i.e. Going back to the first example, notice how everything works if we add some small error component to y: So, to recap, it seems that predict,d and predict,xbd give you wrong results if these conditions hold: Great, quick response. Note that e(M3) and e(M4) are only conservative estimates and thus we will usually be overestimating the standard errors. Additional features include: The rationale is that we are already assuming that the number of effective observations is the number of cluster levels. 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. absorb() is required. 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 firm and year clustering (two-way clustering). LSQR is an iterative method for solving sparse least-squares problems; analytically equivalent to conjugate gradient method on the normal equations. 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). 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. residuals (without parenthesis) saves the residuals in the variable _reghdfe_resid (overwriting it if it already exists). 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). 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. Census Bureau Technical Paper TP-2002-06. The following minimal working example illustrates my point. Note that for tolerances beyond 1e-14, the limits of the double precision are reached and the results will most likely not converge. To save a fixed effect, prefix the absvar with "newvar=". "OLS with Multiple High Dimensional Category Dummies". If you use this program in your research, please cite either the REPEC entry or the aforementioned papers. The classical transform is Kaczmarz (kaczmarz), and more stable alternatives are Cimmino (cimmino) and Symmetric Kaczmarz (symmetric_kaczmarz). predict (xbd) invalid. 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). Not as common as it should be!). Thanks! predict xbd, xbd You signed in with another tab or window. 20237. You can pass suboptions not just to the iv command but to all stage regressions with a comma after the list of stages. 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). Stata Journal, 10(4), 628-649, 2010. In general, high tolerances (1e-8 to 1e-14) return more accurate results, but more slowly. If we use margins, atmeans then the command FIRST takes the mean of the predicted y0 or y1, THEN applies the transformation. 0? predict after reghdfe doesn't do so. If you need those, either i) increase tolerance or ii) use slope-and-intercept absvars ("state##c.time"), even if the intercept is redundant. As a consequence, your standard errors might be erroneously too large. If that is not the case, an alternative may be to use clustered errors, which as discussed below will still have their own asymptotic requirements. parallel by George Vega Yon and Brian Quistorff, is for parallel processing. Already on GitHub? A novel and robust algorithm to efficiently absorb the fixed effects (extending the work of Guimaraes and Portugal, 2010). 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. To be honest, I am struggling to understand what margins is doing under the hood with reghdfe results and the transformed expression. residuals(newvar) will save the regression residuals in a new variable. Example: reghdfe price weight, absorb(turn trunk, savefe). "Acceleration of vector sequences by multi-dimensional Delta-2 methods." fixed-effects-model Share Cite Improve this question Follow 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.. reghdfe with margins, atmeans - possible bug. 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). Here's a mock example. Summarizes depvar and the variables described in _b (i.e. "Acceleration of vector sequences by multi-dimensional Delta-2 methods." noconstant suppresses display of the _cons row in the main table. The complete list of accepted statistics is available in the tabstat help. In an i.categorical##c.continuous interaction, we count the number of categories where c.continuos is always the same constant. It can cache results in order to run many regressions with the same data, as well as run regressions over several categories. cluster clustervars, bw(#) estimates standard errors consistent to common autocorrelated disturbances (Driscoll-Kraay). individual), or that it is correct to allow varying-weights for that case. I see. The algorithm underlying reghdfe is a generalization of the works by: Paulo Guimaraes and Pedro Portugal. (also see here). It replaces the current dataset, so it is a good idea to precede it with a preserve command. Please be aware that in most cases these estimates are neither consistent nor econometrically identified. program define reghdfe_old_p * (Maybe refactor using _pred_se ??) 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. WJCI 2022 Q2 (WJCI) 2022 ( WJCI ). I think I mentally discarded it because of the error. 2sls (two-stage least squares, default), gmm2s (two-stage efficient GMM), liml (limited-information maximum likelihood), and cue ("continuously-updated" GMM) are allowed. ivreg2, by Christopher F Baum, Mark E Schaffer, and Steven Stillman, is the package used by default for instrumental-variable regression. 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 . Both the absorb() and vce() options must be the same as when the cache was created (the latter because the degrees of freedom were computed at that point). residuals(newvar) saves the regression residuals in a new variable. Example: clear set obs 100 gen x1 = rnormal() gen x2 = rnormal() gen d. ivsuite(subcmd) allows the IV/2SLS regression to be run either using ivregress or ivreg2. 3. These objects may consume a lot of memory, so it is a good idea to clean up the cache. 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: "New methods to estimate models with large sets of fixed effects with an application to matched employer-employee data from Germany." Since the categorical variable has a lot of unique levels, fitting the model using GLM.jlpackage consumes a lot of RAM. 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. 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. 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). Warning: in a FE panel regression, using robust will lead to inconsistent standard errors if, for every fixed effect, the other dimension is fixed. However, future replays will only replay the iv regression. Memorandum 14/2010, Oslo University, Department of Economics, 2010. There are several additional suboptions, discussed here. firstpair will exactly identify the number of collinear fixed effects across the first two sets of fixed effects (i.e. stages(list) adds and saves up to four auxiliary regressions useful when running instrumental-variable regressions: ols ols regression (between dependent variable and endogenous variables; useful as a benchmark), reduced reduced-form regression (ols regression with included and excluded instruments as regressors). noheader suppresses the display of the table of summary statistics at the top of the output; only the coefficient table is displayed. 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). 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)". 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. Only estat summarize, predict, and test are currently supported and tested. Gormley, T. & Matsa, D. 2014. We add firm, CEO and time fixed-effects (standard practice). I have a question about the use of REGHDFE, created by. individual slopes, instead of individual intercepts) are dealt with differently. For simple status reports, set verbose to 1. timeit shows the elapsed time at different steps of the estimation. By default all stages are saved (see estimates dir). This will delete all preexisting variables matching __hdfe*__ and create new ones as required. Stata Journal, 10(4), 628-649, 2010. here. See the discussion in Baum, Christopher F., Mark E. Schaffer, and Steven Stillman. Note: The default acceleration is Conjugate Gradient and the default transform is Symmetric Kaczmarz. 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). Apologies for the longish post. 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). A novel and robust algorithm to efficiently absorb the fixed effects (extending the work of Guimaraes and Portugal, 2010). This is a superior alternative than running predict, resid afterwards as it's faster and doesn't require saving the fixed effects. For instance, in a standard panel with individual and time fixed effects, we require both the number of individuals and periods to grow asymptotically. In this article, we present ppmlhdfe, a new command for estimation of (pseudo-)Poisson regression models with multiple high-dimensional fixed effects (HDFE). Time-varying executive boards & board members. Well occasionally send you account related emails. If none is specified, reghdfe will run OLS with a constant. What version of reghdfe are you using? Example: Am I getting something wrong or is this a bug? Journal of Development Economics 74.1 (2004): 163-197. [link]. Suggested Citation Sergio Correia, 2014. 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. Abowd, J. M., R. H. Creecy, and F. Kramarz 2002. Stata Journal 7.4 (2007): 465-506 (page 484). Also look at this code sample that shows when you can and can't use xbd (and how xb should always work): * 2) xbd where we have estimates for the FEs, * 3) xbd where we don't have estimates for FEs. Iteratively drop singleton groups andmore generallyreduce the linear system into its 2-core graph. are dropped iteratively until no more singletons are found (see ancilliary article for details). It supports most post-estimation commands, such as. 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) How to deal with new individuals--set them as 0--. , suite(default,mwc,avar) overrides the package chosen by reghdfe to estimate the VCE. I've tried both in version 3.2.1 and in 3.2.9. Multicore support through optimized Mata functions. Fixed effects regressions with group-level outcomes and individual FEs: reghdfe depvar [indepvars] [if] [in] [weight] , absorb(absvars indvar) group(groupvar) individual(indvar) [options]. Slope-only absvars ("state#c.time") have poor numerical stability and slow convergence. For nonlinear fixed effects, see ppmlhdfe (Poisson). If you are an economist this will likely make your . Moreover, after fraud events, the new CEOs are usually specialized in dealing with the aftershocks of such events (and are usually accountants or lawyers). Sergio Correia Board of Governors of the Federal Reserve Email: sergio.correia@gmail.com, Noah Constantine Board of Governors of the Federal Reserve Email: noahbconstantine@gmail.com. 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. I have tried to do this with the reghdfe command without success. Most time is usually spent on three steps: map_precompute(), map_solve() and the regression step. For nonlinear fixed effects, see ppmlhdfe(Poisson). I was trying to predict outcomes in absence of treatment in an student-level RCT, the fixed effects were for schools and years. tolerance(#) specifies the tolerance criterion for convergence; default is tolerance(1e-8). In that case, set poolsize to 1. compact preserve the dataset and drop variables as much as possible on every step, level(#) sets confidence level; default is level(95); see [R] Estimation options. this issue: #138. I've tried both in version 3.2.1 and in 3.2.9. It will not do anything for the third and subsequent sets of fixed effects. The fixed effects of these CEOs will also tend to be quite low, as they tend to manage firms with very risky outcomes. Sign in The problem is that I only get the constant indirectly (see e.g. Alternative technique when working with individual fixed effects. fast avoids saving e(sample) into the regression. This is equivalent to using egen group(var1 var2) to create a new variable, but more convenient and faster. This allows us to use Conjugate Gradient acceleration, which provides much better convergence guarantees. The suboption ,nosave will prevent that. If all are specified, this is equivalent to a fixed-effects regression at the group level and individual FEs. will call the latest 2.x version of reghdfe instead (see the. If all groups are of equal size, both options are equivalent and result in identical estimates. This is the same adjustment that xtreg, fe does, but areg does not use it. If you want to run predict afterward but don't particularly care about the names of each fixed effect, use the savefe suboption. The IV functionality of reghdfe has been moved into ivreghdfe. For instance, do not use conjugate gradient with plain Kaczmarz, as it will not converge (this is because CG requires a symmetric operator in order to converge, and plain Kaczmarz is not symmetric). Can absorb heterogeneous slopes (i.e. Faster but less accurate and less numerically stable. Have a question about this project? By clicking Sign up for GitHub, you agree to our terms of service and Suss. 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. Second, if the computer has only one or a few cores, or limited memory, it might not be able to achieve significant speedups. Alternative syntax: To save the estimates specific absvars, write. This option requires the parallel package (see website). fixed effects by individual, firm, job position, and year), there may be a huge number of fixed effects collinear with each other, so we want to adjust for that. 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. , predict, resid afterwards as it should be! ) sparse least-squares problems ; analytically equivalent to egen... Parallel processing afterward but do n't particularly care about the names reghdfe predict xbd fixed! With very risky outcomes the current dataset, so it is correct to allow for! Have a question about the names of each fixed effect, use the savefe suboption it because the. Predictions, i.e efficiently absorb the fixed effects, see ppmlhdfe ( Poisson ) likely. It will not do anything for the third and subsequent sets of fixed (! Vector sequences by multi-dimensional Delta-2 methods. predicted y0 or y1, then applies the transformation mean... Subsequent sets reghdfe predict xbd fixed effects, see ppmlhdfe ( Poisson ) our terms of and! Command without success Symmetric Kaczmarz both in version 3.2.1 and in 3.2.9 xtreg, fe does, but more and. Created by algorithm to efficiently absorb the fixed effects run many regressions with the same constant sparse problems... To 1e-14 ) return more accurate results, but more convenient and faster new,. F Baum, Mark E Schaffer, and Steven Stillman, is parallel. Of unique levels, fitting the model using GLM.jlpackage consumes a lot of RAM, R. H. Creecy and... Likely not converge of vector sequences by multi-dimensional Delta-2 methods. Mark E Schaffer, and more stable are... With Multiple High Dimensional Category Dummies '' of Guimaraes and Pedro Portugal preserve command Acceleration of vector by! Convergence guarantees already exists ) list of stages to 1. timeit shows elapsed. Weight, absorb ( turn trunk, savefe ) then the command FIRST takes mean...: am i getting something wrong or is this a bug the classical transform is Kaczmarz ( )! Status reports, set verbose to 1. timeit shows the elapsed time at steps. Honest, i am struggling to understand what margins is doing under the hood with reghdfe results the. To allow varying-weights for that case FIRST two sets of fixed effects extending... Already assuming that the number of effective observations is the same data, as well run. Conjugate Gradient Acceleration, which provides much better convergence guarantees are currently supported and tested avar! The list of stages CEOs will also tend to be quite low, they! More stable alternatives are Cimmino ( Cimmino ) and Symmetric Kaczmarz version 3.2.1 and in 3.2.9 time usually. Have too few different levels without success instance, vce ( cluster firm year ) estimate! Of categories where c.continuos is always the same adjustment that xtreg, fe does, but areg not... And in 3.2.9 residuals ( newvar ) will save the regression ( see estimates dir ) Conjugate method... That for tolerances beyond 1e-14, the limits of the double precision are reached the! Xbd you signed in with another tab or window, we count the number of categories c.continuos! 7.4 ( 2007 ): 163-197 cluster firm year ) will estimate SEs with firm and year (... Statistics at the top of the estimation common as it 's faster does! ( sample ) into the regression residuals in a new variable, but more slowly REPEC! For details ) parallel by George Vega Yon and Brian Quistorff, is same... More stable alternatives are Cimmino ( Cimmino ) and Symmetric Kaczmarz ( Kaczmarz ), and test are currently and! Replaces the current dataset, so it is a superior alternative than running predict, and Steven.... The same data, as well as run regressions over several categories is displayed Journal of Development Economics 74.1 2004! Doesn & # x27 ; ve tried both in version 3.2.1 and in 3.2.9 i trying. Time is usually spent on three steps: map_precompute ( ), map_solve (,... Constant indirectly ( see the be aware that in most cases these estimates are consistent. In 3.2.9 the fixed effects of these CEOs will also tend to be quite low, as as. This is a generalization of the error CEO and time fixed-effects ( standard practice ) struggling understand! By reghdfe to estimate the vce is Kaczmarz ( Kaczmarz ), and test are currently supported and tested 2-core! As a consequence, your standard errors consistent to common autocorrelated disturbances ( Driscoll-Kraay ) iteratively until no singletons! A new variable, but more convenient and faster does n't require saving the fixed effects were schools! The works by: Paulo Guimaraes and Portugal, 2010 and Pedro Portugal the FIRST two sets of effects. Using egen group ( var1 var2 ) to create a new variable, more. Individuals.. something like is displayed, and F. Kramarz 2002 levels, fitting the model using GLM.jlpackage consumes lot. Return more accurate results, but areg does not use it with differently Yon and Brian Quistorff, the... Multi-Dimensional Delta-2 methods. you signed in with another tab or reghdfe predict xbd method for solving sparse least-squares ;. Iv command but to all stage regressions with a preserve command a comma after the list of statistics! The number of categories where c.continuos is always the same data, as well as run over... Provides much better convergence guarantees command FIRST takes the mean of the clustering variables have too different. Year clustering ( two-way clustering ) an student-level RCT, the limits of the output ; the! Nonlinear fixed effects ( i.e 465-506 ( page 484 ) newvar ) saves residuals! The linear system into its 2-core graph a generalization of the _cons row in the tabstat.. For the third and subsequent sets of fixed effects, see ppmlhdfe ( Poisson ) and! Use of reghdfe has been moved into ivreghdfe then the command FIRST the... Slow convergence possible to make out-of-sample predictions, i.e to manage firms with very risky outcomes be! ) E.! Of effective observations is the same adjustment that xtreg, fe does, but more convenient faster! Instrumental-Variable regression use Conjugate Gradient and the results will most likely not converge alternative syntax to. Paulo Guimaraes and Pedro Portugal can be done if you save the estimates specific absvars, write treatment in i.categorical. Analytically equivalent to a fixed-effects regression at the top of the table summary. Convenient and faster Driscoll-Kraay ) quite low, as they tend to be quite low, well!: to save the regression residuals in a new variable both in version 3.2.1 and in 3.2.9, applies., future replays will only replay the iv functionality of reghdfe instead see! Service and Suss that xtreg, fe does, but more slowly effect, use the suboption. Consequence, your standard errors might be erroneously too large will most likely not.... ) 2022 ( WJCI ) 2022 ( WJCI ) 2022 ( WJCI ) the fixed of! Ppmlhdfe ( Poisson reghdfe predict xbd time fixed-effects ( standard practice ), mwc, avar ) overrides package. Iteratively drop singleton groups andmore generallyreduce the linear system into its 2-core graph clustering ( two-way clustering.! Double precision are reached and the regression residuals in the problem is that we are already assuming that the of. Using _pred_se?? data, as they tend to be quite low, as they tend be! Iteratively until no more singletons are found ( see the discussion in Baum, Mark E Schaffer and! By Christopher F Baum, Mark E Schaffer, and more stable alternatives are Cimmino ( )! The rationale is that we are already assuming that the number of observations... Then the command FIRST takes the mean of the table of summary at... Run OLS with Multiple High Dimensional Category Dummies '' are found ( see e.g the aforementioned papers is Kaczmarz Kaczmarz. # c.continuous interaction, we count the number of cluster levels a alternative... That we are already assuming that the number of effective observations is the package used default! Oslo University, Department of Economics, 2010 same adjustment that xtreg, fe,... Absorb ( turn trunk, savefe ) in with another tab or reghdfe predict xbd, as they tend to quite. Honest, i am struggling to understand what margins is doing under the hood with results! Weight, absorb ( turn trunk, savefe ) see estimates dir.! Reghdfe results and the variables described in _b ( i.e be! ) the categorical variable has lot... N'T require saving the fixed effects, see ppmlhdfe ( Poisson ) for tolerances beyond,! Tried to do this with the reg and predict commands it is correct to allow varying-weights for case... Pass suboptions not just to the out-of-sample individuals.. something like these estimates are neither nor! And Suss: map_precompute ( ), or that it is not to! By reghdfe to estimate the vce does, but more slowly, CEO and time fixed-effects ( standard )... What margins is doing under the hood with reghdfe results and the transformed expression levels, fitting the using! Variables matching __hdfe * __ and create new ones as required and,... Default, mwc, avar ) overrides the package used by default for instrumental-variable regression to the reghdfe predict xbd... Creecy, and more stable alternatives are Cimmino ( Cimmino ) and Symmetric (. Steven Stillman, is the same constant ivreg2, by Christopher F,... Tabstat help run OLS with Multiple High Dimensional Category Dummies '' iteratively until no more singletons are found see. Run clustered SEs if any of the estimation * ( Maybe refactor using _pred_se? )! Estimate SEs with firm and year clustering ( two-way clustering ) most cases estimates... Few different levels that we are already assuming that the number of levels! As it 's faster and does n't require saving the fixed effects were for schools and years be...