ivgets {ivgets}

General-to-specific modeling for 2SLS models

Description

General-to-specific modeling for 2SLS models

Usage

ivgets(
  formula,
  data,
  gum.result = NULL,
  t.pval = 0.05,
  wald.pval = t.pval,
  do.pet = TRUE,
  ar.LjungB = NULL,
  arch.LjungB = NULL,
  normality.JarqueB = NULL,
  include.gum = FALSE,
  include.1cut = FALSE,
  include.empty = FALSE,
  max.paths = NULL,
  turbo = FALSE,
  tol = 1e-07,
  max.regs = NULL,
  print.searchinfo = TRUE,
  alarm = FALSE,
  keep_exog = NULL,
  overid = NULL,
  weak = NULL
)

Arguments

formula

A formula in the format y ~ x1 + x2 | z1 + z2.

data

A data frame with all necessary variables y, x, and z.

gum.result

a list with the estimation results of the General Unrestricted Model (GUM), or NULL (default). If the estimation results of the GUM are already available, then re-estimation of the GUM is skipped if the estimation results are provided via this argument

t.pval

numeric value between 0 and 1. The significance level used for the two-sided regressor significance t-tests

wald.pval

numeric value between 0 and 1. The significance level used for the Parsimonious Encompassing Tests (PETs)

do.pet

logical. If TRUE (default), then a Parsimonious Encompassing Test (PET) against the GUM is undertaken at each regressor removal for the joint significance of all the deleted regressors along the current path. If FALSE, then a PET is not undertaken at each regressor removal

ar.LjungB

a two element vector or NULL (default). In the former case, the first element contains the AR-order, the second element the significance level. If NULL, then a test for autocorrelation is not conducted

arch.LjungB

a two element vector or NULL (default). In the former case, the first element contains the ARCH-order, the second element the significance level. If NULL, then a test for ARCH is not conducted

normality.JarqueB

NULL or a numeric value between 0 and 1. In the latter case, a test for non-normality is conducted using a significance level equal to normality.JarqueB. If NULL, then no test for non-normality is conducted

include.gum

logical. If TRUE, then the GUM (i.e. the starting model) is included among the terminal models. If FALSE (default), then the GUM is not included

include.1cut

logical. If TRUE, then the 1-cut model is added to the list of terminal models. If FALSE (default), then the 1-cut is not added, unless it is a terminal model in one of the paths

include.empty

logical. If TRUE, then the empty model is added to the list of terminal models. If FALSE (default), then the empty model is not added, unless it is a terminal model in one of the paths

max.paths

NULL (default) or an integer equal to or greater than 0. If NULL, then there is no limit to the number of paths. If an integer, for example 1, then this integer constitutes the maximum number of paths searched

turbo

logical. If TRUE, then (parts of) paths are not searched twice (or more) unnecessarily, thus yielding a significant potential for speed-gain. However, the checking of whether the search has arrived at a point it has already been comes with a slight computational overhead. Accordingly, if turbo=TRUE, then the total search time might in fact be higher than if turbo=FALSE. This happens if estimation is very fast, say, less than quarter of a second. Hence the default is FALSE

tol

numeric value (default = 1e-07). The tolerance for detecting linear dependencies in the columns of the variance-covariance matrix when computing the Wald-statistic used in the Parsimonious Encompassing Tests (PETs), see the qr.solve function

max.regs

integer. The maximum number of regressions along a deletion path. Do not alter unless you know what you are doing!

print.searchinfo

logical. If TRUE (default), then a print is returned whenever simiplification along a new path is started

alarm

logical. If TRUE, then a sound or beep is emitted (in order to alert the user) when the model selection ends

keep_exog

A numeric vector of indices or a character vector of names corresponding to the exogenous regressors in the data that should not be selected over. Default NULL means that selection is over all exogenous regressors. If an intercept has been specified in the formula but is not already included in the data, then it can be kept by either including the index 0 or the character "Intercept", respectively, as an element in keep_exog.

overid

NULL if no Sargan test of overidentifying restrictions should be used as a diagnostic check for model selection or a numeric value between 0 and 1. In the latter case, the test is conducted using this value as the significance level.

weak

NULL if no weak instrument F-test on the first stage should be used as a diagnostic check for model selection or a numeric value between 0 and 1. In the latter case, the test is conducted using this value as the significance level.

Value

Returns a list of class "ivgets" with three named elements. $selection stores the selection results from getsFun (including paths, terminal models, and best specification). $final stores the ivreg model object of the best specification or NULL if the GUM does not pass all diagnostics. $keep stores the names of the regressors that were not selected over, including the endogenous regressors, which are always kept.