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Eoghan Patrick O'Neill

Personal Details

First Name:Eoghan
Middle Name:Patrick
Last Name:O'Neill
Suffix:
RePEc Short-ID:pox8
[This author has chosen not to make the email address public]
https://eoghanoneill.com/
Terminal Degree:2020 Faculty of Economics; University of Cambridge (from RePEc Genealogy)

Affiliation

School of Economics
University College Dublin

Dublin, Ireland
http://www.ucd.ie/economics/
RePEc:edi:educdie (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Eoghan O'Neill, 2025. "Type 2 Tobit Sample Selection Models with Bayesian Additive Regression Trees," Papers 2502.03600, arXiv.org, revised Nov 2025.
  2. Zhou, W. & Moncaster, A. & O'Neill, E. & Reiner, D. & Wang, X. & Guthrie, P., 2022. "Modelling future trends of annual embodied energy of urban residential building stock in China," Cambridge Working Papers in Economics 2223, Faculty of Economics, University of Cambridge.
  3. Eoghan O'Neill, 2022. "Type I Tobit Bayesian Additive Regression Trees for Censored Outcome Regression," Papers 2211.07506, arXiv.org, revised Feb 2024.
  4. Wei Zhou & Eoghan O'Neill & Alice Moncaster & David M Reiner & Peter Guthrie, 2019. "Applying Bayesian Model Averaging to Characterise Urban Residential Stock Turnover Dynamics," Working Papers EPRG1933, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  5. Eoghan O'Neill & Melvyn Weeks, 2018. "Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes," Papers 1810.09179, arXiv.org, revised Oct 2019.

Articles

  1. Andrea A. Naghi & Eoghan O'Neill & Martina Danielova Zaharieva, 2024. "The benefits of forecasting inflation with machine learning: New evidence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1321-1331, November.
  2. Zhou, Wei & Moncaster, Alice & O'Neill, Eoghan & Reiner, David M. & Wang, Xinke & Guthrie, Peter, 2022. "Modelling future trends of annual embodied energy of urban residential building stock in China," Energy Policy, Elsevier, vol. 165(C).
  3. Xie, Bai-Chen & Ni, Kang-Kang & O'Neill, Eoghan & Li, Hong-Zhou, 2021. "The scale effect in China's power grid sector from the perspective of malmquist total factor productivity analysis," Utilities Policy, Elsevier, vol. 69(C).
  4. Zhou, Wei & O'Neill, Eoghan & Moncaster, Alice & Reiner, David M. & Guthrie, Peter, 2020. "Forecasting urban residential stock turnover dynamics using system dynamics and Bayesian model averaging," Applied Energy, Elsevier, vol. 275(C).
  5. She, Zhen-Yu & Meng, Gang & Xie, Bai-Chen & O'Neill, Eoghan, 2020. "The effectiveness of the unbundling reform in China’s power system from a dynamic efficiency perspective," Applied Energy, Elsevier, vol. 264(C).

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Zhou, W. & Moncaster, A. & O'Neill, E. & Reiner, D. & Wang, X. & Guthrie, P., 2022. "Modelling future trends of annual embodied energy of urban residential building stock in China," Cambridge Working Papers in Economics 2223, Faculty of Economics, University of Cambridge.

    Cited by:

    1. York Castillo Santiago & Daiane Busanello & Alexandre F. Santos & Osvaldo J. Venturini & Leandro A. Sphaier, 2024. "The Impact of Air Renewal with Heat-Recovery Technologies on Energy Consumption for Different Types of Environments in Brazilian Buildings," Energies, MDPI, vol. 17(16), pages 1-23, August.
    2. Yang, Sheng & Jin, Zhengpeng & Ji, Feng & Deng, Chengwei & Liu, Zhiqiang, 2023. "Proposal and analysis of a combined cooling, heating, and power system with humidity control based on solid oxide fuel cell," Energy, Elsevier, vol. 284(C).
    3. Ming Hu & Siavash Ghorbany, 2024. "Building Stock Models for Embodied Carbon Emissions—A Review of a Nascent Field," Sustainability, MDPI, vol. 16(5), pages 1-18, March.
    4. Zhang, Shufan & Zhou, Nan & Feng, Wei & Ma, Minda & Xiang, Xiwang & You, Kairui, 2023. "Pathway for decarbonizing residential building operations in the US and China beyond the mid-century," Applied Energy, Elsevier, vol. 342(C).

  2. Eoghan O'Neill & Melvyn Weeks, 2018. "Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes," Papers 1810.09179, arXiv.org, revised Oct 2019.

    Cited by:

    1. Jarvis, Stephen & Deschenes, Olivier & Jha, Akshaya, 2022. "The private and external costs of Germany’s nuclear phase-out," LSE Research Online Documents on Economics 113634, London School of Economics and Political Science, LSE Library.
    2. Merlin Stein, 2022. "When are large female-led firms more resilient against shocks? Learnings from Indian enterprises during COVID-19 with diff-in-diff and causal forests," CSAE Working Paper Series 2022-01, Centre for the Study of African Economies, University of Oxford.
    3. Kayo MURAKAMI & Hideki SHIMADA & Yoshiaki USHIFUSA & Takanori IDA, 2020. "Heterogeneous Treatment Effects of Nudge and Rebate:Causal Machine Learning in a Field Experiment on Electricity Conservation," Discussion papers e-20-003, Graduate School of Economics , Kyoto University.
    4. Patrick Rehill & Nicholas Biddle, 2023. "Transparency challenges in policy evaluation with causal machine learning -- improving usability and accountability," Papers 2310.13240, arXiv.org, revised Mar 2024.
    5. Jau-er Chen & Chen-Wei Hsiang, 2019. "Causal Random Forests Model Using Instrumental Variable Quantile Regression," Econometrics, MDPI, vol. 7(4), pages 1-22, December.
    6. Pons Rotger, Gabriel & Rosholm, Michael, 2020. "The Role of Beliefs in Long Sickness Absence: Experimental Evidence from a Psychological Intervention," IZA Discussion Papers 13582, Institute of Labor Economics (IZA).
    7. Axenbeck, Janna & Berner, Anne & Kneib, Thomas, 2022. "What drives the relationship between digitalization and industrial energy demand? Exploring firm-level heterogeneity," ZEW Discussion Papers 22-059, ZEW - Leibniz Centre for European Economic Research.
    8. Xie, Yutao & Xiao, Jiang-Wen & Wang, Yan-Wu & Dong, Jiale, 2024. "A new customer selection framework for time-based pricing program," Energy, Elsevier, vol. 290(C).
    9. Kiguchi, Y. & Weeks, M. & Arakawa, R., 2021. "Predicting winners and losers under time-of-use tariffs using smart meter data," Energy, Elsevier, vol. 236(C).
    10. Tomomi Tanaka, 2019. "Human Capital Development in Ghana," World Bank Publications - Reports 34181, The World Bank Group.
    11. Vishalie Shah & Julia Hatamyar & Taufik Hidayat & Noemi Kreif, 2025. "Exploring the heterogeneous impacts of Indonesia's conditional cash transfer scheme (PKH) on maternal health care utilisation using instrumental causal forests," Papers 2501.12803, arXiv.org.
    12. Rana, Pushpendra & Fleischman, Forrest & Ramprasad, Vijay & Lee, Kangjae, 2022. "Predicting wasteful spending in tree planting programs in Indian Himalaya," World Development, Elsevier, vol. 154(C).
    13. Guo, Bowei & Weeks, Melvyn, 2022. "Dynamic tariffs, demand response, and regulation in retail electricity markets," Energy Economics, Elsevier, vol. 106(C).

Articles

  1. Andrea A. Naghi & Eoghan O'Neill & Martina Danielova Zaharieva, 2024. "The benefits of forecasting inflation with machine learning: New evidence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1321-1331, November.

    Cited by:

    1. Faria, Gonçalo & Verona, Fabio, 2024. "Enhancing forecast accuracy through frequencydomain combination: Applications to financial and economic indicators," Bank of Finland Research Discussion Papers 14/2024, Bank of Finland.
    2. Robert-Paul Berben & Rajni Rasiawan & Jasper de Winter, 2025. "Forecasting Dutch inflation using machine learning methods," Working Papers 828, DNB.
    3. Paponpat Taveeapiradeecharoen & Nattapol Aunsri, 2025. "Forecasting in small open emerging economies Evidence from Thailand," Papers 2509.14805, arXiv.org.

  2. Zhou, Wei & Moncaster, Alice & O'Neill, Eoghan & Reiner, David M. & Wang, Xinke & Guthrie, Peter, 2022. "Modelling future trends of annual embodied energy of urban residential building stock in China," Energy Policy, Elsevier, vol. 165(C).
    See citations under working paper version above.
  3. Xie, Bai-Chen & Ni, Kang-Kang & O'Neill, Eoghan & Li, Hong-Zhou, 2021. "The scale effect in China's power grid sector from the perspective of malmquist total factor productivity analysis," Utilities Policy, Elsevier, vol. 69(C).

    Cited by:

    1. Dong, Jingrong & Zhang, Wenqing & Chen, Yuke & Li, Tingting, 2024. "Does technological progress mode affect just energy transition? A seemingly unrelated regression analysis based on Chinese provincial panel data," Energy, Elsevier, vol. 313(C).
    2. Li, Biao & Xie, Bai-Chen & Yu, Xiao-Chen & She, Zhen-Yu & Hu, Wenhao, 2025. "Does the incentive policy for renewable energy grid connection affect the technical efficiency of power grid companies? Empirical analysis based on China and Japan," Economic Analysis and Policy, Elsevier, vol. 85(C), pages 28-47.
    3. Yongrok Choi & Yunning Ma & Yu Zhao & Hyoungsuk Lee, 2023. "Inequality in Fossil Fuel Power Plants in China: A Perspective of Efficiency and Abatement Cost," Sustainability, MDPI, vol. 15(5), pages 1-15, March.

  4. Zhou, Wei & O'Neill, Eoghan & Moncaster, Alice & Reiner, David M. & Guthrie, Peter, 2020. "Forecasting urban residential stock turnover dynamics using system dynamics and Bayesian model averaging," Applied Energy, Elsevier, vol. 275(C).

    Cited by:

    1. Zhou, W. & Moncaster, A. & O'Neill, E. & Reiner, D. & Wang, X. & Guthrie, P., 2022. "Modelling future trends of annual embodied energy of urban residential building stock in China," Cambridge Working Papers in Economics 2223, Faculty of Economics, University of Cambridge.
    2. Mohammed Alkahtani, 2022. "Supply Chain Management Optimization and Prediction Model Based on Projected Stochastic Gradient," Sustainability, MDPI, vol. 14(6), pages 1-14, March.
    3. Danyang Cheng & David M. Reiner & Fan Yang & Can Cui & Jing Meng & Yuli Shan & Yunhui Liu & Shu Tao & Dabo Guan, 2023. "Projecting future carbon emissions from cement production in developing countries," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    4. Zhu, Chen & Li, Xiaodong & Zhu, Weina & Gong, Wei, 2022. "Embodied carbon emissions and mitigation potential in China's building sector: An outlook to 2060," Energy Policy, Elsevier, vol. 170(C).

  5. She, Zhen-Yu & Meng, Gang & Xie, Bai-Chen & O'Neill, Eoghan, 2020. "The effectiveness of the unbundling reform in China’s power system from a dynamic efficiency perspective," Applied Energy, Elsevier, vol. 264(C).

    Cited by:

    1. Cheng, Xiaobin & Liu, Pengfei & Zhu, Lei, 2024. "The impact of electricity market reform on renewable energy production," Energy Policy, Elsevier, vol. 194(C).
    2. Li, Biao & Xie, Bai-Chen & Yu, Xiao-Chen & She, Zhen-Yu & Hu, Wenhao, 2025. "Does the incentive policy for renewable energy grid connection affect the technical efficiency of power grid companies? Empirical analysis based on China and Japan," Economic Analysis and Policy, Elsevier, vol. 85(C), pages 28-47.
    3. Xiaohua Song & Caiping Zhao & Jingjing Han & Qi Zhang & Jinpeng Liu & Yuanying Chi, 2020. "Measurement and Influencing Factors Research of the Energy and Power Efficiency in China: Based on the Supply-Side Structural Reform Perspective," Sustainability, MDPI, vol. 12(9), pages 1-23, May.
    4. Jiang, Xin & Jin, Yang & Zheng, Xueyuan & Hu, Guobao & Zeng, Qingshan, 2020. "Optimal configuration of grid-side battery energy storage system under power marketization," Applied Energy, Elsevier, vol. 272(C).
    5. Tianyu Li & Ciwei Gao & Michael G. Pollitt & Tao Chen & Hao Ming, 2025. "Measuring the Effects of Power System Reform in Jiangsu Province, China from the Perspective of Social Cost Benefit Analysis," The Energy Journal, , vol. 46(2), pages 1-33, March.
    6. Meng, Ming & Pang, Tingting, 2022. "Operational efficiency analysis of China's electric power industry using a dynamic network slack-based measure model," Energy, Elsevier, vol. 251(C).
    7. Ju, Liwei & Wu, Jing & Lin, Hongyu & Tan, Qinliang & Li, Gen & Tan, Zhongfu & Li, Jiayu, 2020. "Robust purchase and sale transactions optimization strategy for electricity retailers with energy storage system considering two-stage demand response," Applied Energy, Elsevier, vol. 271(C).
    8. Hongliang Tian & Liang Zhao & Sen Guo, 2023. "Comprehensive Benefit Evaluation of Power Grid Investment Considering Renewable Energy Development from the Perspective of Sustainability," Sustainability, MDPI, vol. 15(10), pages 1-17, May.
    9. Dong, Hanjiang & Wang, Xiuyuan & Cui, Ziyu & Zhu, Jizhong & Li, Shenglin & Yu, Changyuan, 2025. "Machine learning-enhanced Data Envelopment Analysis via multi-objective variable selection for benchmarking combined electricity distribution performance," Energy Economics, Elsevier, vol. 143(C).
    10. Zhang, Tao & Li, Hong-Zhou & Xie, Bai-Chen, 2022. "Have renewables and market-oriented reforms constrained the technical efficiency improvement of China's electric grid utilities?," Energy Economics, Elsevier, vol. 114(C).

More information

Research fields, statistics, top rankings, if available.

Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 6 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ENE: Energy Economics (3) 2018-11-26 2019-03-25 2022-04-25. Author is listed
  2. NEP-ECM: Econometrics (2) 2022-12-19 2025-03-03. Author is listed
  3. NEP-REG: Regulation (2) 2018-11-26 2019-03-25. Author is listed
  4. NEP-CNA: China (1) 2022-04-25
  5. NEP-ENV: Environmental Economics (1) 2022-04-25
  6. NEP-ORE: Operations Research (1) 2020-07-20

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