Conduct Parameter Estimation in Homogeneous Goods Markets with Equilibrium Existence and Uniqueness Conditions: The Case of Log-linear Specification

TL;DR

This paper introduces a GMM estimator with equilibrium conditions for accurately estimating conduct parameters in homogeneous goods markets, addressing numerical issues present in previous methods.

Contribution

It proposes a novel GMM estimation approach incorporating equilibrium uniqueness conditions to improve accuracy and numerical stability in conduct parameter estimation.

Findings

Adding equilibrium uniqueness conditions improves estimation accuracy.

The proposed GMM method resolves numerical issues in parameter estimation.

Monte Carlo simulations validate the effectiveness of the new approach.

Abstract

We propose a constrained generalized method of moments (GMM) estimator with some equilibrium uniqueness conditions for estimating the conduct parameter in a log-linear model with homogeneous goods markets. Monte Carlo simulations demonstrate that merely imposing parameter restrictions leads to not just inaccurate estimations but also some numerical issues, and adding the equilibrium uniqueness conditions resolves them. We also suggest a formulation of the GMM estimation to further avoid the numerical issues.