base_did

This data has been generated to illustrate the use of difference in difference functions in package fixest. This is a balanced panel of 104 individuals and 10 periods. About half the individuals are treated, the treatment having a positive effect on the dependent variable <code>y</code> after the 5th period. The effect of the treatment on <code>y</code> is gradual.

datasets

Fast and user-friendly estimation of econometric models with multiple fixed-effects. Includes ordinary least squares (OLS), generalized linear models (GLM) and the negative binomial.
The core of the package is based on optimized parallel C++ code, scaling especially well for large data sets. The method to obtain the fixed-effects coefficients is based on Berge (2018) <https://wwwen.uni.lu/content/download/110162/1299525/file/2018_13>.
Further provides tools to export and view the results of several estimations with intuitive design to cluster the standard-errors.

Laurent Berge

fixest

Fast Fixed-Effects Estimations

base_did function

<code>base_did</code> is a data frame with 1,040 observations and 6 variables named <code>y</code>, <code>x1</code>, <code>id</code>, <code>period</code>, <code>post</code> and <code>treat</code>.<ul>
<li>y: The dependent variable affected by the treatment.</li>
<li>x1: An explanatory variable.</li>
<li>id: Identifier of the individual.</li>
<li>period: From 1 to 10</li>
<li>post: Indicator taking value 1 if the period is strictly greater than 5, 0 otherwise.</li>
<li>treat: Indicator taking value 1 if the individual is treated, 0 otherwise.</li>
</ul>

base_did: Sample data for difference in difference

Description

Usage

Arguments

Format

See Also