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help for reg2hdfe                                                            ()
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Title

reg2hdfe - Estimates a Linear Regression Model with two High Dimensional Fixed 
> Effects.

Syntax

        reg2hdfe depvar [indepvar] [if] [in] , id1(varname) id2(varname)
               [options]


Description

This command implements the algorithm of Guimaraes & Portugal for estimation of
a linear regression model with two high dimensional fixed effects. The command
is particularly suited for use with large data sets because in a first step you
can remove the high dimensional fixed effects from the data and then use the
transformed regression variables to try alternative specifications of the
model.

Options

fe1(new varname) fe2(new varname):  Stores the estimates of the two fixed
    effects.

cluster(varname) Computes clustered standard errors.

groupid (new varname) Creates a new variable containing a unique identifier for
    the mobility groups.

outdata(string) Saves the transformed regression variables.

indata(string) To be used after outdata(string). Performs the regression with
    previously transformed variables. This is the fastest way to implement
    regressions.

improve(string) To be used after outdata(string). Improves convergence for a
    single variable.

tol(float) Specify the convergence criterion for the iteration method. Default
    is 1.000e-06.

simple Disables acceleration of convergence for the algorithm.

op1(integer) Iteration number after which convergence is accelerated. Default
    is 3.

op2(integer) Parameter that defines the rate of acceleration at every iteration
    of the algorithm.  Default is 1. The parameter is adjusted as the algorithm
    evolves. If convergence is monotonous the parameter is increased and if the
    algorithm starts diverging the parameter goes back to its default value.

op3(integer) Parameter that defines a periodic attempt to accelerate
    convergence. Default is 10.  This means that every 10 iterations the
    algorithm tries an additional correction to improve convergence.

op4(integer) Parameter that defines the rate of acceleration for the periodic
    correction.  Default is 1000.

op5(integer) Periodic corrections are only applied if estimated values in two
    consecutived periodic corrections differ by less than this parameter. The
    default is 0.001.

autoff(integer) Parameter OP2 remains at its base level.

check Checks for convergence by computing additional regressions that use the
    fixed effects estimates as regressors. With successful convergence the
    coefficients for the fixed effects should equal one.  To check convergence
    of the final regression you must store the two fixed effects (use options
    fe1() and fe2()).

maxiter(integer) Specify a maximum number of iterations.

nodots Suppress dots indicating the progress of the iteration algorithm.

noregress Transforms the variables but does not estimate the regression.

param1 The estimates of the fixed effects for id1() sum to zero within each
    group.

param2 The estimates of the fixed effects for id2() sum to zero within each
    group.

verbose Gives more information during estimation.

Examples

Example 1:
Estimates a model with two high dimensional fixed effects

        . reg2hdfe y x1 x2 x3, id1(i) id2(j)

Example2:

Estimate a model saving the transformed variables

        . reg2hdfe y x1 x2 x3, id1(i) id2(j) outdata(data1)

and then run a (much faster) alternative specification.

        . reg2hdfe y x1 x2, id1(i) id2(j) indata(data1)
 
Example 3:

For faster results estimate a model with a low tolerance level.

        . reg2hdfe y x1 x2 x3, id1(i) id2(j) outdata(data1) check tol(0.001)
 

The "check" option gives an idea how well the model converged. Next we improve
convergence for a single variable, say x1,  

        . reg2hdfe x1, id1(i) id2(j) improve(data1) check tol(0.000001)
 

and then reestimate the model.

        . reg2hdfe y x1 x2, id1(i) id2(j) indata(data1) check
 

Author

Paulo Guimaraes, Universidade do Porto, Portugal

Email: pguimaraes@fep.up.pt

Comments welcome!

Acknowledgements
This program makes use of Amine Quazad's a2group Stata algorithm to compute the
>  connected groups.

Reference

If you use this program in your research cite:

Paulo Guimaraes and Pedro Portugal. "A Simple Feasible Alternative Procedure to
>  Estimate Models with 
High-Dimensional Fixed Effects", Stata Journal, 10(4), 628-649, 2010.

Also see

gpreg (if installed), a2reg (if installed), a2group (if installed), felsdvreg
                     (if installed).