ExtremeBounds: Extreme Bounds Analysis in R

  • Hlavac M
N/ACitations
Citations of this article
34Readers
Mendeley users who have this article in their library.

Abstract

This article introduces the R package ExtremeBounds to perform extreme bounds analysis (EBA), a sensitivity test that examines how robustly the dependent variable of a regression model is related to a variety of possible determinants. ExtremeBounds supports Leamer's EBA that focuses on the upper and lower extreme bounds of regression coefficients, as well as Sala-i-Martin's EBA which considers their entire distribution. In contrast to existing alternatives, it can estimate models of any size, use regression models other than Ordinary Least Squares, incorporate non-linearities in the model specification, and apply custom weights and standard errors. To alleviate concerns about the multicollinearity and conceptual overlap of examined variables, ExtremeBounds allows users to specify sets of mutually exclusive variables, and can restrict the analysis to coefficients from regression models that yield a variance inflation factor (VIF) within a pre-specified limit.

Cite

CITATION STYLE

APA

Hlavac, M. (2014). ExtremeBounds: Extreme Bounds Analysis in R. SSRN. https://doi.org/10.2139/ssrn.2393113

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free