Econometrics with Machine Learning

László Mátyás is a University Professor at the Department of Economics and Business at the Central European University (CEU – Budapest, Hungary and Vienna, Austria). He (co)authored and (co)edited several high impact publications in econometrics, mostly in the field of panel data. Earlier, among others, he worked as Senior Lecturer at Monash University (Melbourne, Australia), was the founding Director of the Institute for Economic Analysis (Budapest, Hungary), and also served as Provost of CEU. Matyas serves as a co-editor of the Springer book series "Advanced Studies in Theoretical and Applied Econometrics".Felix Chan is an Associate Professor at Curtin University and an elected Fellow of the Modelling and Simulation Society of Australia and New Zealand (MSSANZ). He serves as the Deputy Head, School of Accounting, Economics and Finance and was the Director of Centre for Research in Applied Economics (CRAE) between 2017 and 2022.Associate Professor Chan had also served as an external consultant to the Commonwealth Grant Commission (CGC), Department of Treasury Western Australia and Chamber of Commerce and Industry (WA) on issues surrounding forecasting, data analytics and mathematical modelling.

• Linear Econometric Models with Machine Learning.- Nonlinear Econometric Models with Machine Learning.- The Use of Machine Learning in Treatment Effect Estimation.-Forecasting with Machine Learning Methods.-Causal Estimation of Treatment Effects From Observational Health Care Data Using Machine Learning Methods.- Econometrics of Networks with Machine Learning.- Fairness in Machine Learning and Econometrics.- Graphical Models and their Interactions with Machine Learning in the Context of Economics and Finance.- Poverty, Inequality and Development Studies with Machine Learning.- Machine Learning for Asset Pricing.