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About Hsein
Dr. Hsein Kew is a Senior Lecturer in the Department of Econometrics and Business Statistics at Monash Business School, Monash University. He obtained his PhD from the Department of Economics at the University of Melbourne. Prior to joining Monash University, Kew worked as a researcher at the Melbourne Institute of Applied Economic and Social Research, contributing to empirical research projects that examined the interaction between social security benefits and labour market outcomes. In his teaching role, he delivers courses on Financial Econometrics and Data Analysis in Business, equipping students with essential skills in econometric analysis and application.
Kew's research specializations include time series analysis, heteroskedastic models, and non-parametric methods, with associated keywords encompassing time-series analysis, econometric theory and practice, and econometrics/forecasting. His contributions to the field are evidenced by publications in prominent econometric journals. Key works include 'Semi-parametric single-index predictive regression models with cointegrated regressors' (2024), 'Non-stationary parametric single-index predictive models: simulation and empirical studies' (2023), 'Level shift estimation in the presence of non-stationary volatility with an application to the unit root testing problem' (2020), 'Adaptive long memory testing under heteroskedasticity' (2017), 'Portmanteau autocorrelation tests under q-dependence and heteroskedasticity' (2014), and 'Heteroskedasticity-robust testing for a fractional unit root' (2008). Kew has supervised doctoral theses such as 'Estimation for Nonlinear Time Series Models with Stationary and Non-stationary Regressors' (2022) and 'A System of Time-Varying Models for Predictive Regressions: Theory and Application' (2021). His scholarship has received over 290 citations on Google Scholar, highlighting his impact on econometric methodologies for handling complex time series data and volatility.