mixedREndo-class

defines the slots of class mixedREndo.

internal

Fits linear models with endogenous regressor using latent
instrumental variable approaches. The methods included in the package
are Lewbel's (1997) <doi:10.2307/2171884> higher moments approach as well as Lewbel's (2012) <doi:10.1080/07350015.2012.643126>
heteroskedasticity approach, Park and Gupta's (2012) <doi:10.1287/mksc.1120.0718>joint estimation method
that uses Gaussian copula and Kim and Frees's (2007) <doi:10.1007/s11336-007-9008-1> multilevel generalized
method of moment approach that deals with endogeneity in a multilevel setting.
These are statistical techniques to address the endogeneity problem where no
external instrumental variables are needed.
This version:
- includes an omitted variable test in the multilevel estimation. It is reported in the summary() function of the
multilevelIV() function.
- resolves the error "Error in listIDs[, 1] : incorrect number of dimensions" when using the multilevelIV() function.
- a new simulated dataset is provided, dataMultilevelIV, on which to exemplify the multilevelIV() function.

Raluca Gui

REndo

Fitting Linear Models with Endogenous Regressors using Latent
Instrumental Variables

mixedREndo-class function

<dl class="dl-horizontal">
<dt><code>coefficients</code></dt><dd>- the estimated coefficients.</dd></dl><dt><code>coefSdErr</code></dt><dd>- standard errors of the estimates.</dd><dt><code>mixedCall</code></dt><dd>- function call.</dd><dt><code>vcovMat</code></dt><dd>- variance-covariance matrix.</dd><dt><code>weightMat</code></dt><dd>- the weight matrix used for estimation.</dd><dt><code>omittedVarTest</code></dt><dd>- Omitted Variable Test statistic and p-value.</dd>

mixedREndo-class: mixedREndo S4 Object

Description

Arguments

Slots

Examples