A Robust Approach using M-Estimation for Dynamic Panel Autoregressive Model

Year 2025, Volume: 37 Issue: UYIK 2024 Special Issue, 7 - 20

Beste Hamiye Beyaztaş

https://doi.org/10.7240/jeps.1506329

Abstract

This paper presents a robust M-estimation approach for first-order panel autoregressive models, addressing the challenges posed by high persistence levels of the autoregressive parameter and individual heterogeneity. Generalized method of moments estimators widely used in dynamic panel models exhibit substantial finite sample biases and are sensitive to weak instruments, particularly as the autoregressive parameter gets close to unity. Our proposed weighted M-estimator, which uses a power function for the scale parameter in Huber’s loss function, offers a robust alternative. By minimizing the variance of model parameters through an optimal tuning parameter, our method enhances the efficiency and robustness of parameter estimates. We demonstrate the superiority of the proposed approach through several Monte-Carlo simulations and an application to hydro-electric power output data, providing comprehensive comparisons with existing generalized method of moments estimators.

Keywords

Panel autoregressive models, Robust estimation, M-estimation, Generalized method of moments

Dinamik Panel Otoregresif Model için M-Tahmini Kullanan Dayanıklı Bir Yaklaşım

Abstract

Bu makale, otoregresif parametrenin yüksek süreklilik seviyeleri ve bireysel heterojenlik tarafından ortaya çıkan zorlukları ele alarak, birinci dereceden panel otoregresif modeller için dayanıklı bir M-tahmini yaklaşımını sunmaktadır. Dinamik panel modellerinde yaygın olarak kullanılan genelleştirilmiş momentler yöntemi tahmin edicileri, özellikle otoregresif parametre bire yaklaştıkça, zayıf araçlara karşı hassasiyet gösterir ve önemli miktarda sonlu örneklem yanlılıkları sergiler. Önerdiğimiz ağırlıklı M-tahmin edicisi, Huber’in kayıp fonksiyonundaki ölçek parametresi için bir kuvvet fonksiyonu kullanarak dayanıklı bir alternatif sunar. Optimal ayar parametresi aracılığıyla model parametrelerinin varyansını en aza indirerek, yöntemimiz parametre tahminlerinin etkinliğini ve dayanıklılığını artırır. Önerilen yaklaşımın üstünlüğünü, çeşitli Monte-Carlo simülasyonları ve hidroelektrik enerji üretim verilerine uygulama yoluyla göstererek, mevcut genelleştirilmiş momentler yöntemi tahmin edicileri ile kapsamlı karşılaştırmalar sunmaktayız.

Keywords

Panel otoregresif modeller, Dayanıklı tahmin, M-tahmini, Genelleştirilmiş momentler yöntemi

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