Sean Telg (J.M.A.)
Welcome to my personal page!
My main research interest is the statistical analysis of time series data. Within this field, I am particularly interested in noncausal autoregressions, which consider dependence on future values (rather than only the past). Due to this characteristic, these models are closely related to concepts like non-fundamentalness, time-reversibility, non-invertibility and important building blocks in economic theory.
Check out our R package "MARX" constructed to simulate, estimate and select mixed causal-noncausal models: https://CRAN.R-project.org/package=MARX
- Time series econometrics
- Mixed causal-noncausal models
- Modeling speculative bubbles
Professional career history
9/2014 – present
PhD candidate, Maastricht University, Project “Estimation and Inference on Mixed Causal-Noncausal Time Series”, under the supervision of prof. dr. Jean-Pierre Urbain, dr. Alain Hecq and dr. Lenard Lieb.
9/2013 – 7/2014
Research Assistant, Maastricht University.
9/2012 – 7/2014
Economic and Financial Research, Econometrics, Maastricht University. Master of Science, Research Master in Econometrics.
9/2009 – 7/2012
Econometrics and Operations Research, Maastricht University. Bachelor of Science, Econometrics and Operations Research.
9/2011 – 2/2012
Erasmus Exchange Program, Universidade Nova de Lisboa. Part of the bachelor Econometrics and Operations Research.
9/2003 – 7/2009
Gymnasium (VWO), Bonnefanten College, Maastricht. Profile: Economie & Maatschappij. Extra courses: French, Mathematics B1,2, Latin, Greek, M&O.