Research

Working Papers

Type II Tobit Bayesian Additive Regression Trees. https://arxiv.org/abs/2502.03600 https://github.com/EoghanONeill/TobitBART

Spatial Effects on the Performance of Solar Plants: Evidence from a Meta-Frontier Analysis of Qinghai, China (with Bai-Chen Xie and Xian-Peng Chen). https://dx.doi.org/10.2139/ssrn.4852346

Work in Progress
General Autoregressive Bayesian Additive Regression Tree Models for Limited Dependent Variables (with Matteo Iacopini and Luca Rossini). https://github.com/EoghanONeill/ARBART

Smooth Bayesian Additive Regression Trees with Model Trees (with Abdelmounaim el Yaakoubi). https://github.com/EoghanONeill/SMOTRbart

Time Varying Parameter Bayesian Additive Regression Trees.
Attention Weighted Bayesian Additive Regression Trees (with Jan Heijmans). https://github.com/EoghanONeill/AttBART

Publications
Static and Dynamic BART for Rank-Order Data. Journal of Business & Economic Statistics, forthcoming (2026) (with Matteo Iacopini and Luca Rossini) https://doi.org/10.1080/07350015.2025.2604128

Type I Tobit Bayesian Additive Regression Trees for Censored Outcome Regression. Statistics and Computing, 34.4 (2024): 1-19. https://doi.org/10.1007/s11222-024-10434-4

The Benefits of Forecasting Inflation with Machine Learning: New Evidence. Journal of Applied Econometrics, 39(7), 1321-1331. (with Andrea Naghi and Martina Zaharieva). https://doi.org/10.1002/jae.3088

Modelling future trends of annual embodied energy of urban residential building stock in China. Energy Policy, 165, 112932 (2022) (with Zhou, W., Moncaster, A., Reiner, D. M., Wang, X., and Guthrie, P.).

Modelling Chinese Urban Residential Stock Turnover Uncertainties Using System Dynamics and Bayesian Statistical Inference. In Urban Infrastructuring (pp. 221-240). Springer, Singapore (2022). (with Zhou, W., Moncaster, A., Reiner, D. M., and Guthrie, P.).

Study on the scale effect of China’s power grid sector from the perspective of dynamic performance. Utilities Policy, 69, 101187 (2021) (with Kang-Kang Ni, Bai-Chen Xie, and Hong-Zhou Li).

Forecasting Urban Residential Stock Turnover Dynamics using System Dynamics and Bayesian Model Averaging. Applied Energy (2020) (with Wei Zhou, Alice Moncaster, David Reiner, and Peter Guthrie).

The effectiveness of the unbundling reform in China’s power system from a dynamic efficiency perspective. Applied Energy, 264, 114717 (2020) (with Zhen-Yu She, Gang Meng, and Bai-Chen Xie)

Link to PhD Thesis: https://doi.org/10.17863/CAM.62828