Dyadic Regression

TL;DR

This paper reviews methods for dyadic regression analysis, addressing the unique dependence structures in pairwise interaction data common in social sciences, and provides practical guidelines for researchers.

Contribution

It offers a comprehensive review of current parametric dyadic regression methods and practical guidelines for empirical application.

Findings

Summarizes existing dyadic regression techniques

Highlights estimation and inference challenges

Provides practical guidelines for researchers

Abstract

Dyadic data, where outcomes reflecting pairwise interaction among sampled units are of primary interest, arise frequently in social science research. Regression analyses with such data feature prominently in many research literatures (e.g., gravity models of trade). The dependence structure associated with dyadic data raises special estimation and, especially, inference issues. This chapter reviews currently available methods for (parametric) dyadic regression analysis and presents guidelines for empirical researchers.