simGLM

Constructs an artificial data set with $n$ cross-sectional units observed for $t$ time
periods for logit, poisson, or gamma models. The &#8220;true&#8221; linear predictor
($\boldsymbol{\eta}$) is generated as follows:
$$\eta_{it} = \mathbf{x}_{it}^{\prime} \boldsymbol{\beta} +
 \alpha_{i} + \gamma_{t} \, ,$$
where $\mathbf{X}$ consists of three independent standard normally distributed regressors.
Both parameter referring to the unobserved heterogeneity ($\alpha_{i}$ and 
$\gamma_{t}$) are generated as iid. standard normal and the structural parameters are
set to $\boldsymbol{\beta} = [1, - 1, 1]^{\prime}$.
Note: The poisson and gamma model are based on the logarithmic link function.

Provides a routine to partial out factors with many levels during the optimization of the log-likelihood function of the corresponding generalized linear model (glm). The package is based on the algorithm described in Stammann (2018) <arXiv:1707.01815> and is restricted to glm's that are based on maximum likelihood estimation and nonlinear. It also offers an efficient algorithm to recover estimates of the fixed effects in a post-estimation routine and includes robust and multi-way clustered standard errors. Further the package provides analytical bias corrections for binary choice models derived by Fernandez-Val and Weidner (2016) <doi:10.1016/j.jeconom.2015.12.014> and Hinz, Stammann, and Wanner (2020) <arXiv:2004.12655>.

Amrei Stammann

alpaca

Fit GLM's with High-Dimensional k-Way Fixed Effects

Daniel Czarnowske

simGLM function

<dl><dt>n</dt>
<dd>a strictly positive integer equal to the number of cross-sectional units.</dd>
<dt>t</dt>
<dd>a strictly positive integer equal to the number of time periods.</dd>
<dt>seed</dt>
<dd>a seed to ensure reproducibility.</dd>
<dt>model</dt>
<dd>a string equal to <code>"logit"</code>, <code>"poisson"</code>, or <code>"gamma"</code>. Default is 
<code>"logit"</code>.</dd></dl>

Arguments

Generate an artificial data set for some GLM's with two-way fixed effects — simGLM

<dl>

<dt>n</dt>
<dd>a strictly positive integer equal to the number of cross-sectional units.</dd>


<dt>t</dt>
<dd>a strictly positive integer equal to the number of time periods.</dd>


<dt>seed</dt>
<dd>a seed to ensure reproducibility.</dd>


<dt>model</dt>
<dd>a string equal to <code>"logit"</code>, <code>"poisson"</code>, or <code>"gamma"</code>. Default is 
<code>"logit"</code>.</dd>

</dl>

simGLM: Generate an artificial data set for some GLM's with two-way fixed effects

Description

Usage

Value

Arguments

See Also