*! version 1.0.0 19July2022
help pariv

Title

pariv -- Nearly collinear robust instrumental-variables regression

Syntax

pariv depvar (endovars = excludedinst) [includedinst] [if] [in] [weight] [, options]

Options

noconstant suppress constant term
absorb(varname) fixed effects for varname
small Stata's finite sample adjustment of standard errors and degrees of freedom adjustments of p-values
robust heteroskedasticity robust conventional standard errors
cluster(varname) clustered conventional standard errors
reps(#) number of permutations of data and variable order; default is 0
seed(#) set random-number seed to #, default is 1

Description

pariv fits a partitioned 2SLS regression of depvar on endovars, includedinst and (if specified) fixed effects for
varname using excludedinst (as well as includedinst and any fixed effects) as instruments for endovars.
The partitioned regression is more robust to near collinearity among the instruments than the procedures used by Stata commands such as ivregress. For details, see:

Young, Alwyn.
Nearly Collinear Robust Procedures for 2SLS Estimation.

pariv reports the maximum R2 found in regressing any one instrument on the others. In Stata's built-in 2SLS commands ivregress and xtivreg,
maximum R2 values in excess of .99999 may generate substantive sensitivity to econometrically irrelevant procedures such as the reordering of the data and variables.
pariv is much less sensitive to near collinearity, but to check that reported results are robust to this issue, the user can call for reps(#) > 0 random
permutations of data and variable order. pariv will report the min to max range of the coefficient and standard errors estimates of the partitioned
2SLS regression across these permutations. If the minimum and maximum are the same, the user can be confident that the reported results are not sensitive to near collinearity.
If the user does not provide a random number seed, the seed is set to 1. Regardless, the seed is restored to its pre-program value on termination.

Stored results

pariv stores the following matrices in e():

e(Res) Results table in matrix form.
e(ResB) Coefficient estimates for each random permutation of data and variable order.
e(ResSE) Standard error estimates for each random permutation of data and variable order.
e(R2max) Maximum R2 found in regressing one instrument on the others.

Author

Alwyn Young, London School of Economics, a.young@lse.ac.uk.