Added-Variable Plots for Panel-Data Estimation

Authors

John Luke Gallup, Portland State UniversityFollow

Published In

The Stata Journal

Document Type

Citation

Publication Date

3-2020

Abstract

In this article, I extend the theory of added-variable plots to three panel-data estimation methods: fixed effects, between effects, and random effects. An added-variable plot is an effective way to show the correlation between an independent variable and a dependent variable conditional on other independent variables. In a multivariate context, a simple scatterplot showing x versus y is not adequate to show the relationship of x with y, because it ignores the impact of the other covariates. Added-variable plots are also useful for spotting influential outliers in the data that affect the estimated regression parameters. Stata can display added-variable plots with the command avplot, but it can be used only after regress. My new command, xtavplot, is a postestimation command that creates added-variable plots after xtreg estimates. Unlike avplot, xtavplot can display a confidence interval around the fitted regression line.

Description

Copyright © 2020 by StataCorp LLC. All rights reserved

Locate the Document

https://doi.org/10.1177/1536867X20909689

DOI

10.1177/1536867X20909689

Persistent Identifier

https://archives.pdx.edu/ds/psu/32825

Citation Details

Gallup, J. L. (2020). Added-variable plots for panel-data estimation. The Stata Journal, 20(1), 30-50.