Didier Nibbering
I am a Lecturer (Assistant Professor) at the Department of Econometrics and Business Statistics at Monash University.
My research interests are high-dimensional inference, forecasting, and semi-parametric Bayesian inference.
Contact Information:
didier.nibbering[at]monash.edu
Department of Econometrics and Business Statistics
Level 8, Menzies Building, Clayton Campus
20 Chancellors Walk, Melbourne, VIC 3800, Australia
Working papers
Clustered local average treatment effects: fields of study and academic student progress, with Matthijs Oosterveen and Pedro Luis Silva
Fast variational inference for multinomial probit models, with Ruben Loaiza-Maya
The Tale of the Tail: Inference for Customer Purchase Behavior in the Long Tail, with Bruno Jacobs
Panel Forecasting with Asymmetric Grouping, with Richard Paap
Scalable simultaneous inference in high-dimensional linear regression models, with Tom Boot
A Bayesian Infinite Hidden Markov Vector Autoregressive Model, with Richard Paap and Michel van der Wel
Publications
Multiclass-penalized logistic regression, with Trevor Hastie, forthcoming in Computational Statistics and Data Analysis
Scalable Bayesian estimation in the multinomial probit model, with Ruben Loaiza-Maya, forthcoming in Journal of Business and Economic Statistics.
Forecasting using Random Subspace Methods, with Tom Boot, Journal of Econometrics, Volume 209, Issue 2, April 2019, Pages 391-406.
Subspace methods, with Tom Boot, In P. Fuleky (Ed.), 2020 Macroeconomic Forecasting in the Era of Big Data: Theory and Practice (pp. 269-291). (Advanced Studies in Theoretical and Applied Econometrics; Vol. 52). Cham: Springer.
What do Professional Forecasters actually predict? with Richard Paap and Michel van der Wel, International Journal of Forecasting, Volume 34, Issue 2, April–June 2018, Pages 288-311.