copulaREndo-class

This class is used to store and further analyze the results of the copulaCorrection function when method=1 is applied

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

copulaREndo-class function

<dl class="dl-horizontal">
<dt><code>copCall</code></dt><dd>- call fo the copulaCorrection function.</dd></dl><dt><code>coefficients</code></dt><dd>- estimated coefficients.</dd><dt><code>coefEndoVar</code></dt><dd>- estimated coefficients of the variables considered endogenous.</dd><dt><code>coefExoVar</code></dt><dd>- estimated coefficients of the variables considered exogenous.</dd><dt><code>coefPStar</code></dt><dd>- estimated coefficient of the additional variable, p*.</dd><dt><code>seCoefficients</code></dt><dd>- standard errors of the coefficients.</dd><dt><code>residuals</code></dt><dd>- the residuals.</dd><dt><code>fitted.values</code></dt><dd>- fitted values.</dd><dt><code>stats</code></dt><dd>- model fit statistics such as R2, Adj-R2, Fstatistic.</dd><dt><code>rho</code></dt><dd>- the estimate of the correlation between the endogenous variable and the error.</dd><dt><code>sigma</code></dt><dd>- standard deviation of the error.</dd><dt><code>logLik</code></dt><dd>- value of the maximum likelihood.</dd><dt><code>param</code></dt><dd>- initial values of the parameter. THese are either chosen by the user or are the OLS estimates, with value 0.5 for rho and 0.9 for sigma.</dd><dt><code>AIC</code></dt><dd>- Akaike Information Criterion.</dd><dt><code>BIC</code></dt><dd>- Bayesian Information Criterion.</dd><dt><code>convCode</code></dt><dd>- the convergence code. If is equal to zero, the model converged.</dd><dt><code>regressors</code></dt><dd>- returns the regressors matrix.</dd><dt><code>confint</code></dt><dd>- returns the lower and upper limits of the 95% confidence interval for the estimates.</dd>

copulaREndo-class: generics for copulaREndo-class

Description

Arguments

Slots

Examples