Recursive Score and Hessian Computation in Regime-Switching Models

TL;DR

This paper introduces a recursive algorithm for efficiently computing the score and Hessian in regime-switching models, demonstrating that the outer product of the score provides better variance estimates.

Contribution

It presents a novel recursive method for calculating score and Hessian matrices in regime-switching models, simplifying implementation.

Findings

Outer product of the score yields more accurate variance estimates.

Recursive algorithm is easy to implement.

Simulation results support the proposed method.

Abstract

This study proposes a recursive and easy-to-implement algorithm to compute the score and Hessian matrix in general regime-switching models. We use simulation to compare the asymptotic variance estimates constructed from the Hessian matrix and the outer product of the score. The results favor the latter.