IDEAS home Printed from https://ideas.repec.org/f/c/pca273.html
   My authors  Follow this author

Jennifer L. Castle

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.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Jennifer Castle & David Hendry, 2007. "Forecasting UK Inflation: the Roles of Structural Breaks and Time Disaggregation," Economics Series Working Papers 309, University of Oxford, Department of Economics.

    Mentioned in:

    1. Money growth & inflation
      by chris dillow in Stumbling and Mumbling on 2009-03-26 19:31:34
  2. Jennifer Castle & David Hendry & Michael P. Clements, 2014. "Robust Approaches to Forecasting," Economics Series Working Papers 697, University of Oxford, Department of Economics.

    Mentioned in:

    1. In all probability, economic forecasts are probably wrong
      by David F Hendry, Director, Economic Modelling, The Institute for New Economic Thinking at the Oxford Martin School at University of Oxford in The Conversation on 2014-07-18 17:06:35

Working papers

  1. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2022. "The Historical Role of Energy in UK Inflation and Productivity and Implications for Price Inflation in 2022," Working Papers 2022-001, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2024. "Improving models and forecasts after equilibrium-mean shifts," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1085-1100.

  2. Jennifer L. Castle & David F. Hendry, 2021. "Can the UK achieve net-zero greenhouse gas emissions by 2050?," Economics Series Working Papers 953 JEL classification: C, University of Oxford, Department of Economics.

    Cited by:

    1. Thet Paing Tun & Oguzhan Ceylan & Ioana Pisica, 2025. "A Real-World Case Study Towards Net Zero: EV Charger and Heat Pump Integration in End-User Residential Distribution Networks," Energies, MDPI, vol. 18(10), pages 1-27, May.
    2. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2022. "The historical role of energy in UK inflation and productivity and implications for price inflation in 2022," Economics Series Working Papers 983, University of Oxford, Department of Economics.

  3. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2020. "Short-term forecasting of the Coronavirus Pandemic - 2020-04-27," Economics Papers 2020-W06, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    2. Petropoulos, Fotios & Makridakis, Spyros & Stylianou, Neophytos, 2022. "COVID-19: Forecasting confirmed cases and deaths with a simple time series model," International Journal of Forecasting, Elsevier, vol. 38(2), pages 439-452.
    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Principles from Experience with Forecasting Competitions," Forecasting, MDPI, vol. 3(1), pages 1-28, February.
    5. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Selecting a Model for Forecasting," Econometrics, MDPI, vol. 9(3), pages 1-35, June.
    6. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2023. "Robust Discovery of Regression Models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 31-51.
    7. Bozkir, Cem D.C. & Ozmemis, Cagri & Kurbanzade, Ali Kaan & Balcik, Burcu & Gunes, Evrim D. & Tuglular, Serhan, 2023. "Capacity planning for effective cohorting of hemodialysis patients during the coronavirus pandemic: A case study," European Journal of Operational Research, Elsevier, vol. 304(1), pages 276-291.

  4. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.

    Cited by:

    1. Nie, Yan & Zhang, Guoxing & Zhong, Luhao & Su, Bin & Xi, Xi, 2024. "Urban‒rural disparities in household energy and electricity consumption under the influence of electricity price reform policies," Energy Policy, Elsevier, vol. 184(C).
    2. Julia Eichholz & Thorsten Knauer & Sandra Winkelmann, 2023. "Digital Maturity of Forecasting and its Impact in Times of Crisis," Schmalenbach Journal of Business Research, Springer, vol. 75(4), pages 443-481, December.
    3. Afif Zuhri Muhammad Khodri Harahap & Mohd Kamarul Irwan Abdul Rahim & Noor Malinjasari & Suzila Mat Salleh & Rabiatul Adawiyah Ma'arof, 2025. "Enhancing the Inventory Management through Demand Forecasting," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(1), pages 2737-2744, January.
    4. Zin Mar Oo & Ching‐Yang Lin & Makoto Kakinaka, 2025. "Deciphering Long‐Term Economic Growth: An Exploration With Leading Machine Learning Techniques," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(4), pages 1531-1562, July.
    5. Marco Zanotti, 2025. "On the stability of global forecasting models," Working Papers 553, University of Milano-Bicocca, Department of Economics.
    6. Qi Zheng & Yunwei Cui & Rongning Wu, 2024. "On estimation of nonparametric regression models with autoregressive and moving average errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(2), pages 235-262, April.
    7. Karamolegkos, Spyridon & Koulouriotis, Dimitrios E., 2025. "Advancing short-term load forecasting with decomposed Fourier ARIMA: A case study on the Greek energy market," Energy, Elsevier, vol. 325(C).
    8. Simon Hirsch & Jonathan Berrisch & Florian Ziel, 2024. "Online Distributional Regression," Papers 2407.08750, arXiv.org, revised Aug 2025.
    9. Diego Zappa & Gian Paolo Clemente & Francesco Della Corte & Nino Savelli, 2023. "Editorial on the Special Issue on Insurance: complexity, risks and its connection with social sciences," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 125-130, December.
    10. Ca’ Zorzi, Michele & Rubaszek, Michał, 2023. "How many fundamentals should we include in the behavioral equilibrium exchange rate model?," Economic Modelling, Elsevier, vol. 118(C).
    11. Huang, Congzhi & Yang, Mengyuan, 2023. "Memory long and short term time series network for ultra-short-term photovoltaic power forecasting," Energy, Elsevier, vol. 279(C).
    12. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    13. Wesley Marcos Almeida & Claudimar Pereira Veiga, 2023. "Does demand forecasting matter to retailing?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 219-232, June.
    14. Marek Kwas & Alessia Paccagnini & Michal Rubaszek, 2020. "Common Factors and the Dynamics of Cereal Prices: A Forecasting Perspective," CAMA Working Papers 2020-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    16. Bernhard Tröster & Ulrich Gunter, 2023. "The Financialization of Coffee, Cocoa and Cotton Value Chains: The Role of Physical Actors," Development and Change, International Institute of Social Studies, vol. 54(6), pages 1550-1574, November.
    17. Tetiana Zatonatska & Olena Liashenko & Yana Fareniuk & Oleksandr Dluhopolskyi & Artur Dmowski & Marzena Cichorzewska, 2022. "The Migration Influence on the Forecasting of Health Care Budget Expenditures in the Direction of Sustainability: Case of Ukraine," Sustainability, MDPI, vol. 14(21), pages 1-17, November.
    18. Oscar Espinosa & Valeria Bejarano & Jeferson Ramos & Boris Martínez, 2023. "Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021," Health Economics Review, Springer, vol. 13(1), pages 1-20, December.
    19. Wang, Lu & Wang, Xing & Liang, Chao, 2024. "Natural gas volatility prediction via a novel combination of GARCH-MIDAS and one-class SVM," The Quarterly Review of Economics and Finance, Elsevier, vol. 98(C).
    20. Shanshan Wang & Shih‐Chih Chen & Mohd Helmi Ali & Ming‐Lang Tseng, 2024. "Nexus of environmental, social, and governance performance in China‐listed companies: Disclosure and green bond issuance," Business Strategy and the Environment, Wiley Blackwell, vol. 33(3), pages 1647-1660, March.
    21. Alroomi, Azzam & Karamatzanis, Georgios & Nikolopoulos, Konstantinos & Tilba, Anna & Xiao, Shujun, 2022. "Fathoming empirical forecasting competitions’ winners," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1519-1525.
    22. Fernández, Joaquín Delgado & Menci, Sergio Potenciano & Lee, Chul Min & Rieger, Alexander & Fridgen, Gilbert, 2022. "Privacy-preserving federated learning for residential short-term load forecasting," Applied Energy, Elsevier, vol. 326(C).
    23. Paul Ghelasi & Florian Ziel, 2023. "Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions," Papers 2305.16255, arXiv.org.
    24. Augusto Cerqua & Marco Letta & Gabriele Pinto, 2024. "On the (Mis)Use of Machine Learning with Panel Data," Papers 2411.09218, arXiv.org, revised May 2025.
    25. Heymann, Fabian & Milojevic, Tatjana & Covatariu, Andrei & Verma, Piyush, 2023. "Digitalization in decarbonizing electricity systems – Phenomena, regional aspects, stakeholders, use cases, challenges and policy options," Energy, Elsevier, vol. 262(PB).
    26. Spiliotis, Evangelos & Petropoulos, Fotios, 2024. "On the update frequency of univariate forecasting models," European Journal of Operational Research, Elsevier, vol. 314(1), pages 111-121.
    27. Ramos, Paulo Vitor B. & Villela, Saulo Moraes & Silva, Walquiria N. & Dias, Bruno H., 2023. "Residential energy consumption forecasting using deep learning models," Applied Energy, Elsevier, vol. 350(C).
    28. Ghelasi, Paul & Ziel, Florian, 2024. "Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions," International Journal of Forecasting, Elsevier, vol. 40(2), pages 581-596.
    29. Jacek Batóg & Barbara Batóg & Magdalena Mojsiewicz & Przemysław Pluskota, 2024. "Electrification of Public Urban Transport: Funding Opportunities, Bus Fleet, and Energy Use Forecasts for Poland," Energies, MDPI, vol. 17(23), pages 1-20, December.
    30. Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
    31. Katarzyna Maciejowska & Weronika Nitka, 2024. "Multiple split approach -- multidimensional probabilistic forecasting of electricity markets," Papers 2407.07795, arXiv.org.
    32. Divya Aggarwal & Sougata Banerjee, 2025. "Forecasting of S&P 500 ESG Index by Using CEEMDAN and LSTM Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 339-355, March.
    33. Nghia Chu & Binh Dao & Nga Pham & Huy Nguyen & Hien Tran, 2022. "Predicting Mutual Funds' Performance using Deep Learning and Ensemble Techniques," Papers 2209.09649, arXiv.org, revised Jul 2023.
    34. Pan Tang & Yuwei Zhang, 2024. "China's business cycle forecasting: a machine learning approach," Computational Economics, Springer;Society for Computational Economics, vol. 64(5), pages 2783-2811, November.
    35. Joanna Janczura & Andrzej Puć, 2023. "ARX-GARCH Probabilistic Price Forecasts for Diversification of Trade in Electricity Markets—Variance Stabilizing Transformation and Financial Risk-Minimizing Portfolio Allocation," Energies, MDPI, vol. 16(2), pages 1-28, January.
    36. David P. Brown & Daniel O. Cajueiro & Andrew Eckert & Douglas Silveira, 2024. "Evaluating the Role of Information Disclosure on Bidding Behavior in Wholesale Electricity Markets," Working Papers 2024-02, University of Alberta, Department of Economics.
    37. Theodorou, Evangelos & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2025. "Forecast accuracy and inventory performance: Insights on their relationship from the M5 competition data," European Journal of Operational Research, Elsevier, vol. 322(2), pages 414-426.
    38. Emanuela Raffinetti, 2023. "A Rank Graduation Accuracy measure to mitigate Artificial Intelligence risks," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 131-150, December.
    39. Marta Crispino & Vincenzo Mariani, 2025. "A Tool to Nowcast Tourist Overnight Stays with Payment Data and Complementary Indicators," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 11(1), pages 285-312, March.
    40. Conigliani, Caterina & Costantini, Valeria & Paglialunga, Elena & Tancredi, Andrea, 2024. "Forecasting the climate-conflict risk in Africa along climate-related scenarios and multiple socio-economic drivers," Economic Modelling, Elsevier, vol. 141(C).
    41. Wang, Xiaoqian & Kang, Yanfei & Hyndman, Rob J. & Li, Feng, 2023. "Distributed ARIMA models for ultra-long time series," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1163-1184.
    42. Katarzyna Chec & Bartosz Uniejewski & Rafal Weron, 2024. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," WORking papers in Management Science (WORMS) WORMS/24/04, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    43. Agakishiev, Ilyas & Härdle, Wolfgang Karl & Kopa, Milos & Kozmik, Karel & Petukhina, Alla, 2025. "Multivariate probabilistic forecasting of electricity prices with trading applications," Energy Economics, Elsevier, vol. 141(C).
    44. Silvia Golia & Luigi Grossi & Matteo Pelagatti, 2022. "Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices," Forecasting, MDPI, vol. 5(1), pages 1-21, December.
    45. Li, Xin & Xu, Yechi & Law, Rob & Wang, Shouyang, 2024. "Enhancing Tourism Demand Forecasting with a Transformer-based Framework," SocArXiv 5ezn3_v1, Center for Open Science.
    46. Fałdziński, Marcin & Fiszeder, Piotr & Molnár, Peter, 2024. "Improving volatility forecasts: Evidence from range-based models," The North American Journal of Economics and Finance, Elsevier, vol. 69(PB).
    47. Guo, Su & Zheng, Kun & He, Yi & Kurban, Aynur, 2023. "The artificial intelligence-assisted short-term optimal scheduling of a cascade hydro-photovoltaic complementary system with hybrid time steps," Renewable Energy, Elsevier, vol. 202(C), pages 1169-1189.
    48. Swaminathan, Kritika & Venkitasubramony, Rakesh, 2024. "Demand forecasting for fashion products: A systematic review," International Journal of Forecasting, Elsevier, vol. 40(1), pages 247-267.
    49. Said Rosli & Sulaimi Mardhiati & Majid Rohayu Ab & Aini Ainoriza Mohd & Olanrele Olusegun Olaopin & Akinsomi Omokolade, 2024. "Evaluating Market Attributes and Housing Affordability: Gaining Perspective on Future Value Trends," Real Estate Management and Valuation, Sciendo, vol. 32(3), pages 87-100.
    50. Martin McCarthy, Stephen Snudden, 2024. "Forecasts of Period-Average Exchange Rates: New Insights from Real-Time Daily Data," LCERPA Working Papers jc0148, Laurier Centre for Economic Research and Policy Analysis, revised Oct 2024.
    51. Raja, Aitazaz Ali & Pinson, Pierre & Kazempour, Jalal & Grammatico, Sergio, 2024. "A market for trading forecasts: A wagering mechanism," International Journal of Forecasting, Elsevier, vol. 40(1), pages 142-159.
    52. Amjad Almusaed & Ibrahim Yitmen & Asaad Almssad, 2023. "Enhancing Smart Home Design with AI Models: A Case Study of Living Spaces Implementation Review," Energies, MDPI, vol. 16(6), pages 1-23, March.
    53. Jozef Barunik & Lubos Hanus, 2023. "Learning the Probability Distributions of Day-Ahead Electricity Prices," Papers 2310.02867, arXiv.org, revised Jul 2025.
    54. Yi Ding & Peng Wu & Jie Zhao & Ligang Zhou, 2025. "Forecasting product sales using text mining: a case study in new energy vehicle," Electronic Commerce Research, Springer, vol. 25(1), pages 495-527, February.
    55. Ricardo Caetano & José Manuel Oliveira & Patrícia Ramos, 2025. "Transformer-Based Models for Probabilistic Time Series Forecasting with Explanatory Variables," Mathematics, MDPI, vol. 13(5), pages 1-29, February.
    56. Kafa, Nadine & Babai, M. Zied & Klibi, Walid, 2025. "Forecasting mail flow: A hierarchical approach for enhanced societal wellbeing," International Journal of Forecasting, Elsevier, vol. 41(1), pages 51-65.
    57. Racek, Daniel & Thurner, Paul W. & Davidson, Brittany I. & Zhu, Xiao Xiang & Kauermann, Göran, 2024. "Conflict forecasting using remote sensing data: An application to the Syrian civil war," International Journal of Forecasting, Elsevier, vol. 40(1), pages 373-391.
    58. Marco Zanotti, 2025. "Do global forecasting models require frequent retraining?," Working Papers 551, University of Milano-Bicocca, Department of Economics.
    59. Anna Sznajderska & Alfred A. Haug, 2023. "Bayesian VARs of the U.S. economy before and during the pandemic," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 211-236, June.
    60. Li, Xiaoyuan & Tian, Zhe & Wu, Xia & Feng, Wei & Niu, Jide, 2024. "Optimal planning for hybrid renewable energy systems under limited information based on uncertainty quantification," Renewable Energy, Elsevier, vol. 237(PD).
    61. Minghao Ran & Yingchao Wang & Qilu Qin & Jindi Huang & Jiading Jiang, 2025. "An Improved Grey Prediction Model Integrating Periodic Decomposition and Aggregation for Renewable Energy Forecasting: Case Studies of Solar and Wind Power," Sustainability, MDPI, vol. 17(11), pages 1-31, May.
    62. Jeroen Rombouts & Marie Ternes & Ines Wilms, 2024. "Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning," Papers 2402.09033, arXiv.org, revised May 2024.
    63. Jonathan Berrisch & Florian Ziel, 2022. "Distributional modeling and forecasting of natural gas prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1065-1086, September.
    64. Meisenbacher, Stefan & Phipps, Kaleb & Taubert, Oskar & Weiel, Marie & Götz, Markus & Mikut, Ralf & Hagenmeyer, Veit, 2025. "AutoPQ: Automating quantile estimation from point forecasts in the context of sustainability," Applied Energy, Elsevier, vol. 392(C).
    65. Rai, Amit & Shrivastava, Ashish & Jana, Kartick C., 2023. "Differential attention net: Multi-directed differential attention based hybrid deep learning model for solar power forecasting," Energy, Elsevier, vol. 263(PC).
    66. Marco Zanotti, 2025. "The cost of ensembling: is it always worth combining?," Working Papers 554, University of Milano-Bicocca, Department of Economics.
    67. Anita M. Bunea & Mariangela Guidolin & Piero Manfredi & Pompeo Della Posta, 2022. "Diffusion of Solar PV Energy in the UK: A Comparison of Sectoral Patterns," Forecasting, MDPI, vol. 4(2), pages 1-21, April.
    68. Zheng, Zhuang & Shafique, Muhammad & Luo, Xiaowei & Wang, Shengwei, 2024. "A systematic review towards integrative energy management of smart grids and urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    69. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    70. Li, Xin & Xu, Yechi & Law, Rob & Wang, Shouyang, 2024. "Enhancing tourism demand forecasting with a transformer-based framework," Annals of Tourism Research, Elsevier, vol. 107(C).
    71. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    72. Allen, Sam & Koh, Jonathan & Segers, Johan & Ziegel, Johanna, 2024. "Tail calibration of probabilistic forecasts," LIDAM Discussion Papers ISBA 2024018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    73. Janczura, Joanna & Wójcik, Edyta, 2022. "Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study," Energy Economics, Elsevier, vol. 110(C).
    74. Entezari, Negin & Fuinhas, José Alberto, 2024. "Measuring wholesale electricity price risk from climate change: Evidence from Portugal," Utilities Policy, Elsevier, vol. 91(C).
    75. Pedersen, Michael, 2025. "Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence," International Journal of Forecasting, Elsevier, vol. 41(2), pages 475-486.
    76. Caravaggio, Nicola & Resce, Giuliano & Vaquero-Piñeiro, Cristina, 2025. "Predicting policy funding allocation with Machine Learning," Socio-Economic Planning Sciences, Elsevier, vol. 98(C).
    77. Victoria A Bensel & Kelsey Corcoran & Anthony J Lisi, 2025. "Forecasting the use of chiropractic services within the Veterans Health Administration," PLOS ONE, Public Library of Science, vol. 20(1), pages 1-8, January.
    78. Bergsteinsson, Hjörleifur G. & Sørensen, Mikkel Lindstrøm & Møller, Jan Kloppenborg & Madsen, Henrik, 2023. "Heat load forecasting using adaptive spatial hierarchies," Applied Energy, Elsevier, vol. 350(C).
    79. Mutele, Litshedzani & Carranza, Emmanuel John M., 2024. "Statistical analysis of gold production in South Africa using ARIMA, VAR and ARNN modelling techniques: Extrapolating future gold production, Resources–Reserves depletion, and Implication on South Afr," Resources Policy, Elsevier, vol. 93(C).
    80. Takahashi, Carlos Kazunari & Figueiredo, Júlio César Bastos de & Scornavacca, Eusebio, 2024. "Investigating the diffusion of innovation: A comprehensive study of successive diffusion processes through analysis of search trends, patent records, and academic publications," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    81. Li, Xishu & Zuidwijk, Rob & de Koster, M.B.M, 2023. "Optimal competitive capacity strategies: Evidence from the container shipping market," Omega, Elsevier, vol. 115(C).
    82. Shi, Qi, 2025. "Technical indicators and aggregate stock returns: An updated look," Journal of Multinational Financial Management, Elsevier, vol. 77(C).
    83. Richard Bean, 2023. "Forecasting the Monash Microgrid for the IEEE-CIS Technical Challenge," Energies, MDPI, vol. 16(3), pages 1-23, January.
    84. Shafie Bahman & Hamidreza Zareipour, 2025. "Long-Term Multi-Resolution Probabilistic Load Forecasting Using Temporal Hierarchies," Energies, MDPI, vol. 18(11), pages 1-30, June.
    85. Emmanuel Senyo Fianu, 2022. "Analyzing and Forecasting Multi-Commodity Prices Using Variants of Mode Decomposition-Based Extreme Learning Machine Hybridization Approach," Forecasting, MDPI, vol. 4(2), pages 1-27, June.
    86. Cristiana Tudor & Robert Sova, 2025. "An automated adaptive trading system for enhanced performance of emerging market portfolios," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-39, December.
    87. Elalem, Yara Kayyali & Maier, Sebastian & Seifert, Ralf W., 2023. "A machine learning-based framework for forecasting sales of new products with short life cycles using deep neural networks," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1874-1894.
    88. Jun Meng & Jingfang Fan & Uma S. Bhatt & Jürgen Kurths, 2023. "Arctic weather variability and connectivity," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    89. Aitazaz Ali Raja & Pierre Pinson & Jalal Kazempour & Sergio Grammatico, 2022. "A Market for Trading Forecasts: A Wagering Mechanism," Papers 2205.02668, arXiv.org, revised Oct 2022.
    90. Katarzyna Chk{e}'c & Bartosz Uniejewski & Rafa{l} Weron, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Papers 2503.02518, arXiv.org.
    91. Robinson Kruse‐Becher, 2025. "Adaptive Now‐ and Forecasting of Global Temperatures Under Smooth Structural Changes," Environmetrics, John Wiley & Sons, Ltd., vol. 36(6), September.
    92. Paul Ghelasi & Florian Ziel, 2025. "A data-driven merit order: Learning a fundamental electricity price model," Papers 2501.02963, arXiv.org, revised Nov 2025.
    93. Niklas Valentin Lehmann, 2023. "Forecasting skill of a crowd-prediction platform: A comparison of exchange rate forecasts," Papers 2312.09081, arXiv.org, revised May 2025.
    94. Qi, Lingzhi & Li, Xixi & Wang, Qiang & Jia, Suling, 2023. "fETSmcs: Feature-based ETS model component selection," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1303-1317.
    95. Andrea Savio & Luigi De Giovanni & Mariangela Guidolin, 2022. "Modelling Energy Transition in Germany: An Analysis through Ordinary Differential Equations and System Dynamics," Forecasting, MDPI, vol. 4(2), pages 1-18, April.
    96. Radovan Šomplák & Veronika Smejkalová & Martin Rosecký & Lenka Szásziová & Vlastimír Nevrlý & Dušan Hrabec & Martin Pavlas, 2023. "Comprehensive Review on Waste Generation Modeling," Sustainability, MDPI, vol. 15(4), pages 1-29, February.
    97. Ye, Lili & Xie, Naiming & Boylan, John E. & Shang, Zhongju, 2024. "Forecasting seasonal demand for retail: A Fourier time-varying grey model," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1467-1485.

  5. Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2020. "Smooth Robust Multi-Horizon Forecasts," Working Papers 2020-009, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    2. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2024. "Improving models and forecasts after equilibrium-mean shifts," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1085-1100.
    4. Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, The Center for Economic Research.

  6. Jennifer Castle & David Hendry, 2020. "Identifying the Causal Role of CO2 during the Ice Ages," Economics Series Working Papers 898, University of Oxford, Department of Economics.

    Cited by:

    1. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    2. Neil R. Ericsson & Mohammed H. I. Dore & Hassan Butt, 2022. "Detecting and Quantifying Structural Breaks in Climate," Econometrics, MDPI, vol. 10(4), pages 1-27, November.
    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.

  7. Jennifer Castle & Jurgen Doornik & David Hendry, 2020. "Modelling Non-stationary 'Big Data'," Economics Series Working Papers 905, University of Oxford, Department of Economics.

    Cited by:

    1. Varga, Katalin & Szendrei, Tibor, 2025. "Non-stationary financial risk factors and macroeconomic vulnerability for the UK," International Review of Financial Analysis, Elsevier, vol. 97(C).
    2. Escribano, Alvaro & Peña, Daniel & Ruiz, Esther, 2021. "30 years of cointegration and dynamic factor models forecasting and its future with big data: Editorial," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1333-1337.
    3. Hasnain Iftikhar & Faridoon Khan & Paulo Canas Rodrigues & Abdulmajeed Atiah Alharbi & Jeza Allohibi, 2025. "Forecasting of Inflation Based on Univariate and Multivariate Time Series Models: An Empirical Application," Mathematics, MDPI, vol. 13(7), pages 1-18, March.

  8. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2020. "Robust Discovery of Regression Models," Economics Papers 2020-W04, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Emmanuel Flachaire & Sullivan Hué & Sébastien Laurent & Gilles Hacheme, 2024. "Interpretable Machine Learning Using Partial Linear Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 519-540, June.
    3. Aron, Janine & Muellbauer, John, 2021. "Excess mortality versus COVID-19 death rates: a spatial analysis of socioeconomic disparities and political allegiance across US states," INET Oxford Working Papers 2021-24, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    4. Khan, Faridoon & Muhammadullah, Sara & Sharif, Arshian & Lee, Chien-Chiang, 2024. "The role of green energy stock market in forecasting China's crude oil market: An application of IIS approach and sparse regression models," Energy Economics, Elsevier, vol. 130(C).
    5. Andrew B. Martinez, 2025. "Real-time Hurricane Damage Nowcasts," Working Papers 2025-006, The George Washington University, The Center for Economic Research.
    6. Aurelia Rybak & Aleksandra Rybak & Jarosław Joostberens & Spas D. Kolev, 2024. "Key SDG7 Factors Shaping the Future of Clean Coal Technologies: Analysis of Trends and Prospects in Poland," Energies, MDPI, vol. 17(16), pages 1-15, August.
    7. Antoni Espasa & Guillermo Carlomagno, 2024. "Modelling high frequency non-financial big time series with an application to jobless claims in Chile," Working Papers Central Bank of Chile 1023, Central Bank of Chile.

  9. Jennifer L. Castle & Jurgen A. Doornik & David Hendry, 2019. "Some forecasting principles from the M4 competition," Economics Papers 2019-W01, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F., 2022. "Short-term forecasting of the coronavirus pandemic," International Journal of Forecasting, Elsevier, vol. 38(2), pages 453-466.
    2. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2020. "Short-term forecasting of the Coronavirus Pandemic - 2020-04-27," Economics Papers 2020-W06, Economics Group, Nuffield College, University of Oxford.
    3. Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F., 2020. "Card forecasts for M4," International Journal of Forecasting, Elsevier, vol. 36(1), pages 129-134.

  10. Jennifer Castle & Jurgen Doornik & David Hendry, 2018. "Selecting a Model for Forecasting," Economics Series Working Papers 861, University of Oxford, Department of Economics.

    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Jia, Jian & Kang, Sang Baum, 2022. "Do the basis and other predictors of futures return also predict spot return with the same signs and magnitudes? Evidence from the LME," Journal of Commodity Markets, Elsevier, vol. 25(C).
    3. Chad Fulton & Kirstin Hubrich, 2021. "Forecasting US Inflation in Real Time," Finance and Economics Discussion Series 2021-014, Board of Governors of the Federal Reserve System (U.S.).

  11. Jennifer Castle & David Hendry, 2016. "Policy Analysis, Forediction, and Forecast Failure," Economics Series Working Papers 809, University of Oxford, Department of Economics.

    Cited by:

    1. Marcela De Castro-Valderrama & Santiago Forero-Alvarado & Nicolás Moreno-Arias & Sara Naranjo-Saldarriaga, 2021. "Unraveling the Exogenous Forces Behind Analysts’ Macroeconomic Forecasts," Borradores de Economia 1184, Banco de la Republica de Colombia.

  12. Jennifer Castle & David Hendry & Michael P. Clements, 2016. "An Overview of Forecasting Facing Breaks," Economics Series Working Papers 779, University of Oxford, Department of Economics.

    Cited by:

    1. Marta Boczon, 2018. "Balanced Growth Approach to Forecasting Recessions," Working Paper 6487, Department of Economics, University of Pittsburgh.
    2. Nikita Fokin, 2021. "The importance of modeling structural breaks in forecasting Russian GDP," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 5-29.
    3. Jeronymo Marcondes Pinto & Emerson Fernandes Marçal, 2023. "An artificial intelligence approach to forecasting when there are structural breaks: a reinforcement learning-based framework for fast switching," Empirical Economics, Springer, vol. 65(4), pages 1729-1759, October.
    4. Döpke, Jörg & Fritsche, Ulrich & Müller, Karsten, 2019. "Has macroeconomic forecasting changed after the Great Recession? Panel-based evidence on forecast accuracy and forecaster behavior from Germany," Journal of Macroeconomics, Elsevier, vol. 62(C).
    5. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2022. "The historical role of energy in UK inflation and productivity and implications for price inflation in 2022," Economics Series Working Papers 983, University of Oxford, Department of Economics.
    6. Muhammad Jahanzeb Malik & Muhammad Nadim Hanif, 2019. "Learning from Errors While Forecasting Inflation: A Case for Intercept Correction," International Econometric Review (IER), Econometric Research Association, vol. 11(1), pages 24-38, April.
    7. Talis Tebecis, 2023. "Have climate policies been effective in Austria? A reverse causal analysis," Department of Economics Working Papers wuwp346, Vienna University of Economics and Business, Department of Economics.
    8. Celia Rangel-Pérez & Belen López & Manuel Fernández, 2024. "A strategic sustainability model for global luxury companies in the management of CO2 emissions," International Entrepreneurship and Management Journal, Springer, vol. 20(3), pages 1597-1615, September.
    9. William D. Larson & Tara M. Sinclair, 2020. "Nowcasting Unemployment Insurance Claims in the Time of COVID-19," Working Papers 2020-004, The George Washington University, The Center for Economic Research, revised Aug 2020.
    10. Marta Boczoń & Jean-François Richard, 2020. "Balanced Growth Approach to Tracking Recessions," Econometrics, MDPI, vol. 8(2), pages 1-35, April.
    11. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    12. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2021. "Modelling non-stationary ‘Big Data’," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1556-1575.
    13. Luca Nocciola, "undated". "Finite sample forecast properties and window length under breaks in cointegrated systems," Discussion Papers 19/07, University of Nottingham, Granger Centre for Time Series Econometrics.
    14. Xin, Daleng & Ahmad, Manzoor & Lei, Hong & Khattak, Shoukat Iqbal, 2021. "Do innovation in environmental-related technologies asymmetrically affect carbon dioxide emissions in the United States?," Technology in Society, Elsevier, vol. 67(C).
    15. Castle, Jennifer L. & Hendry, David F. & Martinez, Andrew B., 2023. "The historical role of energy in UK inflation and productivity with implications for price inflation," Energy Economics, Elsevier, vol. 126(C).
    16. Jörg Döpke & Ulrich Fritsche & Karsten Müller, 2018. "Has Macroeconomic Forecasting changed after the Great Recession? - Panel-based Evidence on Accuracy and Forecaster Behaviour from Germany," Macroeconomics and Finance Series 201803, University of Hamburg, Department of Socioeconomics.
    17. igescu, iulia, 2020. "Describing Location Shifts with One Class Support Vector Machines," MPRA Paper 100984, University Library of Munich, Germany.
    18. Jeronymo Marcondes Pinto & Jennifer L. Castle, 2022. "Machine Learning Dynamic Switching Approach to Forecasting in the Presence of Structural Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(2), pages 129-157, July.
    19. Tebecis, Talis, 2023. "Have climate policies been effective in Austria? A reverse causal analysis," Department of Economics Working Paper Series 346, WU Vienna University of Economics and Business.

  13. Jennifer Castle & David Hendry & Michael P. Clements, 2014. "Robust Approaches to Forecasting," Economics Series Working Papers 697, University of Oxford, Department of Economics.

    Cited by:

    1. Pinto, Jeronymo Marcondes & Marçal, Emerson Fernandes, 2019. "Cross-validation based forecasting method: a machine learning approach," Textos para discussão 498, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    2. Neil R. Ericsson, 2015. "Eliciting GDP Forecasts from the FOMC’s Minutes Around the Financial Crisis," International Finance Discussion Papers 1152, Board of Governors of the Federal Reserve System (U.S.).
    3. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
    4. Emerson Fernandes Marçal & Eli Hadad Junior, 2016. "Is It Possible to Beat the Random Walk Model in Exchange Rate Forecasting? More Evidence for Brazilian Case," Brazilian Review of Finance, Brazilian Society of Finance, vol. 14(1), pages 65-88.
    5. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    6. Jennifer Castle & Takamitsu Kurita, 2019. "Modelling and forecasting the dollar-pound exchange rate in the presence of structural breaks," Economics Series Working Papers 866, University of Oxford, Department of Economics.
    7. John B. Guerard, 2024. "Sir David Hendry: An Appreciation from Wall Street and What Macroeconomics Got Right," Working Papers 2024-001, The George Washington University, The Center for Economic Research, revised Feb 2024.
    8. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    9. Jeronymo Marcondes Pinto & Emerson Fernandes Marçal, 2023. "An artificial intelligence approach to forecasting when there are structural breaks: a reinforcement learning-based framework for fast switching," Empirical Economics, Springer, vol. 65(4), pages 1729-1759, October.
    10. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," Working Papers 2017-001, The George Washington University, The Center for Economic Research.
    11. Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F., 2022. "Short-term forecasting of the coronavirus pandemic," International Journal of Forecasting, Elsevier, vol. 38(2), pages 453-466.
    12. Lin, Jilei & Eck, Daniel J., 2021. "Minimizing post-shock forecasting error through aggregation of outside information," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1710-1727.
    13. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    14. David F Hendry & John N J Muellbauer, 2018. "The future of macroeconomics: macro theory and models at the Bank of England," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 34(1-2), pages 287-328.
    15. Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2020. "Smooth Robust Multi-Horizon Forecasts," Working Papers 2020-009, The George Washington University, The Center for Economic Research.
    16. William D. Larson & Tara M. Sinclair, 2020. "Nowcasting Unemployment Insurance Claims in the Time of COVID-19," Working Papers 2020-004, The George Washington University, The Center for Economic Research, revised Aug 2020.
    17. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2024. "Improving models and forecasts after equilibrium-mean shifts," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1085-1100.
    18. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2020. "Short-term forecasting of the Coronavirus Pandemic - 2020-04-27," Economics Papers 2020-W06, Economics Group, Nuffield College, University of Oxford.
    19. David F. Hendry, 2020. "A Short History of Macro-econometric Modelling," Economics Papers 2020-W01, Economics Group, Nuffield College, University of Oxford.
    20. Clements, Michael P., 2016. "Real-time factor model forecasting and the effects of instability," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 661-675.
    21. David Hendry, 2016. "Deciding Between Alternative Approaches In Macroeconomics," Economics Series Working Papers 778, University of Oxford, Department of Economics.
    22. Spiliotis, Evangelos & Nikolopoulos, Konstantinos & Assimakopoulos, Vassilios, 2019. "Tales from tails: On the empirical distributions of forecasting errors and their implication to risk," International Journal of Forecasting, Elsevier, vol. 35(2), pages 687-698.
    23. Castle, Jennifer L. & Kurita, Takamitsu, 2021. "A dynamic econometric analysis of the dollar-pound exchange rate in an era of structural breaks and policy regime shifts," Journal of Economic Dynamics and Control, Elsevier, vol. 128(C).
    24. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Selecting a Model for Forecasting," Econometrics, MDPI, vol. 9(3), pages 1-35, June.
    25. Luke P. Jackson & Katarina Juselius & Andrew B. Martinez & Felix Pretis, 2025. "Modelling the dependence between recent changes in polar ice sheets: Implications for global sea-level projections," Working Papers 2025-002, The George Washington University, The Center for Economic Research.
    26. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2024. "Forecasting the UK top 1% income share in a shifting world," Economica, London School of Economics and Political Science, vol. 91(363), pages 1047-1074, July.
    27. Jeronymo Marcondes Pinto & Jennifer L. Castle, 2022. "Machine Learning Dynamic Switching Approach to Forecasting in the Presence of Structural Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(2), pages 129-157, July.
    28. Robinson Kruse‐Becher, 2025. "Adaptive Now‐ and Forecasting of Global Temperatures Under Smooth Structural Changes," Environmetrics, John Wiley & Sons, Ltd., vol. 36(6), September.
    29. Papailias, Fotis & Thomakos, Dimitrios, 2017. "EXSSA: SSA-based reconstruction of time series via exponential smoothing of covariance eigenvalues," International Journal of Forecasting, Elsevier, vol. 33(1), pages 214-229.
    30. Kyriazi, Foteini & Thomakos, Dimitrios D. & Guerard, John B., 2019. "Adaptive learning forecasting, with applications in forecasting agricultural prices," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1356-1369.

  14. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.

    Cited by:

    1. Rocha, Jordano Vieira & Pereira, Pedro L. Valls, 2015. "Forecast comparison with nonlinear methods for Brazilian industrial production," Textos para discussão 397, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).

  15. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.

    Cited by:

    1. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    2. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," Working Papers 2017-001, The George Washington University, The Center for Economic Research.
    3. Emilian DOBRESCU, 2020. "Self-fulfillment degree of economic expectations within an integrated space: The European Union case study," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-32, December.
    4. Bonino-Gayoso, Nicolás & García-Hiernaux, Alfredo, 2019. "TF-MIDAS: a new mixed-frequency model to forecast macroeconomic variables," MPRA Paper 93366, University Library of Munich, Germany.
    5. Manu Sharma & Vinish Kathuria, 2025. "Macroeconomic Nowcasting: What can Central Banks Learn from a Structured Literature Review?," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 23(2), pages 333-388, June.
    6. David Hendry, 2016. "Deciding Between Alternative Approaches In Macroeconomics," Economics Series Working Papers 778, University of Oxford, Department of Economics.
    7. Balcombe, Kelvin & Fraser, Iain, 2017. "Do bubbles have an explosive signature in markov switching models?," Economic Modelling, Elsevier, vol. 66(C), pages 81-100.

  16. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Ragnar Nymoen, 2012. "Mis-specification Testing: Non-Invariance of Expectations Models of Inflation," Working Paper series 50_12, Rimini Centre for Economic Analysis.

    Cited by:

    1. Mariano Kulish & Adrian Pagan, 2016. "Issues in Estimating New Keynesian Phillips Curves in the Presence of Unknown Structural Change," Econometric Reviews, Taylor & Francis Journals, vol. 35(7), pages 1251-1270, August.
    2. Philip Hans Franses, 2019. "Model‐based forecast adjustment: With an illustration to inflation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(2), pages 73-80, March.
    3. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2022. "The historical role of energy in UK inflation and productivity and implications for price inflation in 2022," Economics Series Working Papers 983, University of Oxford, Department of Economics.
    4. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.
    5. David F. Hendry, 2020. "A Short History of Macro-econometric Modelling," Economics Papers 2020-W01, Economics Group, Nuffield College, University of Oxford.
    6. Kristine Wika Haraldsen & Ragnar Nymoen & Victoria Sparrman, 2019. "Labour market institutions, shocks and the employment rate," Discussion Papers 901, Statistics Norway, Research Department.
    7. David Hendry, 2016. "Deciding Between Alternative Approaches In Macroeconomics," Economics Series Working Papers 778, University of Oxford, Department of Economics.
    8. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2023. "Robust Discovery of Regression Models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 31-51.
    9. Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, The Center for Economic Research.
    10. Haraldsen, Kristine Wika & Ragnar, Nymoen & Sparrman, Victoria, 2019. "Labour market institutions, shocks and the employment rate," Memorandum 6/2019, Oslo University, Department of Economics.
    11. Melnick, Rafi & Strohsal, Till, 2017. "Disinflation in steps and the Phillips curve: Israel 1986–2015," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 145-161.

  17. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.

    Cited by:

    1. Neil R. Ericsson & Mohammed H. I. Dore & Hassan Butt, 2022. "Detecting and Quantifying Structural Breaks in Climate," Econometrics, MDPI, vol. 10(4), pages 1-27, November.
    2. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2013. "Model Selection in Equations with Many ‘Small’ Effects," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(1), pages 6-22, February.
    3. Valentina Corradi & Norman Swanson, 2013. "Testing for Structural Stability of Factor Augmented Forecasting Models," Departmental Working Papers 201314, Rutgers University, Department of Economics.
    4. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.

  18. Jennifer Castle & David Hendry & Nicholas W.P. Fawcett, 2011. "Forecasting breaks and forecasting during breaks," Economics Series Working Papers 535, University of Oxford, Department of Economics.

    Cited by:

    1. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
    2. Neil R. Ericsson, 2016. "Economic Forecasting in Theory and Practice : An Interview with David F. Hendry," International Finance Discussion Papers 1184, Board of Governors of the Federal Reserve System (U.S.).
    3. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
    4. Clements, Michael P. & Reade, J. James, 2020. "Forecasting and forecast narratives: The Bank of England Inflation Reports," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1488-1500.
    5. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
    6. David Hendry & Grayham E. Mizon, 2016. "Improving the Teaching of Econometrics," Economics Series Working Papers 785, University of Oxford, Department of Economics.
    7. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    8. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.
    9. Liudas Giraitis & George Kapetanios & Simon Price, 2012. "Adaptive Forecasting in the Presence of Recent and Ongoing Structural Change," Working Papers 691, Queen Mary University of London, School of Economics and Finance.
    10. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Facing Economic Shifts, Climate Change and Evolving Pandemics," Econometrics, MDPI, vol. 10(1), pages 1-21, December.
    11. Muellbauer, John, 2018. "The Future of Macroeconomics," INET Oxford Working Papers 2018-10, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    12. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, vol. 177(2), pages 305-319.
    13. William D. Larson & Tara M. Sinclair, 2020. "Nowcasting Unemployment Insurance Claims in the Time of COVID-19," Working Papers 2020-004, The George Washington University, The Center for Economic Research, revised Aug 2020.
    14. Wickens, Michael R., 2012. "How Useful are DSGE Macroeconomic Models for Forecasting?," CEPR Discussion Papers 9049, C.E.P.R. Discussion Papers.
    15. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    16. Qin, Duo & He, Xinhua, 2012. "Modelling the impact of aggregate financial shocks external to the Chinese economy," BOFIT Discussion Papers 25/2012, Bank of Finland Institute for Emerging Economies (BOFIT).
    17. Jennifer Castle & David Hendry & Michael P. Clements, 2014. "Robust Approaches to Forecasting," Economics Series Working Papers 697, University of Oxford, Department of Economics.
    18. David Hendry & Grayham E. Mizon, 2012. "Forecasting from Structural Econometric Models," Economics Series Working Papers 597, University of Oxford, Department of Economics.
    19. Rocha, Jordano Vieira & Pereira, Pedro L. Valls, 2015. "Forecast comparison with nonlinear methods for Brazilian industrial production," Textos para discussão 397, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    20. Fardoust, Shahrokh & Dhareshwar, Ashok, 2013. "Some thoughts on making long-term forecasts for the world economy," Policy Research Working Paper Series 6705, The World Bank.
    21. William Larson, 2015. "Forecasting an Aggregate in the Presence of Structural Breaks in the Disaggregates," Working Papers 2015-002, The George Washington University, The Center for Economic Research.

  19. Jennifer Castle & David Hendry, 2011. "On Not Evaluating Economic Models by Forecast Outcomes," Economics Series Working Papers 538, University of Oxford, Department of Economics.

    Cited by:

    1. Jennifer Castle & Takamitsu Kurita, 2019. "Modelling and forecasting the dollar-pound exchange rate in the presence of structural breaks," Economics Series Working Papers 866, University of Oxford, Department of Economics.
    2. Jennifer Castle & David Hendry, 2016. "Policy Analysis, Forediction, and Forecast Failure," Economics Series Working Papers 809, University of Oxford, Department of Economics.
    3. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2017. "Evaluating Forecasts, Narratives and Policy Using a Test of Invariance," Econometrics, MDPI, vol. 5(3), pages 1-27, September.
    4. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2024. "Forecasting the UK top 1% income share in a shifting world," Economica, London School of Economics and Political Science, vol. 91(363), pages 1047-1074, July.

  20. Jennifer Castle & David Hendry, 2011. "Model Selection in Equations with Many 'Small' Effects," Economics Series Working Papers 528, University of Oxford, Department of Economics.

    Cited by:

    1. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
    2. David Hendry & Felix Pretis, 2011. "Anthropogenic Influences on Atmospheric CO2," Economics Series Working Papers 584, University of Oxford, Department of Economics.
    3. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, vol. 177(2), pages 305-319.
    4. Yuxuan Huang, 2016. "Forecasting the USD/CNY Exchange Rate under Different Policy Regimes," Working Papers 2016-001, The George Washington University, The Center for Economic Research.
    5. Rahul Verma & Rajesh Mohnot, 2023. "Relative Impact of the U.S. Energy Market Sentiments on Stocks and ESG Index Returns: Evidence from GCC Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 290-300, March.
    6. Jurgen A. Doornik & David F. Hendry & Steve Cook, 2015. "Statistical model selection with “Big Data”," Cogent Economics & Finance, Taylor & Francis Journals, vol. 3(1), pages 1045216-104, December.

  21. Jennifer Castle & Xiaochuan Qin & W. Robert Reed, 2011. "Using Model Selection Algorthims to Obtain Reliable Coefficient Estimates," Working Papers in Economics 11/03, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Cunha, Ronan & Pereira, Pedro L. Valls, 2015. "Automatic model selection for forecasting Brazilian stock returns," Textos para discussão 398, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    2. W. Robert Reed, 2018. "A Primer on the ‘Reproducibility Crisis’ and Ways to Fix It," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 51(2), pages 286-300, June.
    3. Durevall, Dick & Loening, Josef L. & Birru, Yohannes A., 2010. "Inflation Dynamics and Food Prices in Ethiopia," Working Papers in Economics 478, University of Gothenburg, Department of Economics, revised 03 Jun 2013.
    4. Nymoen, Ragnar & Pedersen, Kari & Sjåberg, Jon Ivar, 2018. "Estimation of effects of recent macroprudential policies in a sample of advanced open economies," Memorandum 5/2018, Oslo University, Department of Economics.
    5. David Hendry, 2016. "Deciding Between Alternative Approaches In Macroeconomics," Economics Series Working Papers 778, University of Oxford, Department of Economics.
    6. Ragnar Nymoen & Kari Pedersen & Jon Ivar Sjåberg, 2019. "Estimation of Effects of Recent Macroprudential Policies in a Sample of Advanced Open Economies," IJFS, MDPI, vol. 7(2), pages 1-20, May.
    7. Kevin S. Nell, 2018. "Conditional Divergence in the Post-1989 Globalisation Period," CEF.UP Working Papers 1806, Universidade do Porto, Faculdade de Economia do Porto.
    8. Ericsson Neil R., 2016. "Testing for and estimating structural breaks and other nonlinearities in a dynamic monetary sector," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 377-398, September.

  22. Jennifer Castle & David Hendry, 2010. "Automatic Selection for Non-linear Models," Economics Series Working Papers 473, University of Oxford, Department of Economics.

    Cited by:

    1. Gunnar Bårdsen & Stan Hurn & Zoë McHugh, 2010. "Asymmetric unemployment rate dynamics in Australia," CREATES Research Papers 2010-02, Department of Economics and Business Economics, Aarhus University.
    2. Jennifer Castle & David Hendry & Jurgen A. Doornik, 2010. "Evaluating Automatic Model Selection," Economics Series Working Papers 474, University of Oxford, Department of Economics.
    3. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
    4. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2013. "Model Selection in Equations with Many ‘Small’ Effects," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(1), pages 6-22, February.
    5. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.
    6. David Hendry & Felix Pretis, 2011. "Anthropogenic Influences on Atmospheric CO2," Economics Series Working Papers 584, University of Oxford, Department of Economics.
    7. Jennifer Castle & David Hendry, 2008. "The Long-Run Determinants of UK Wages, 1860-2004," Economics Series Working Papers 409, University of Oxford, Department of Economics.
    8. James Reade, 2014. "Detecting corruption in football," Chapters, in: John Goddard & Peter Sloane (ed.), Handbook on the Economics of Professional Football, chapter 25, pages 419-446, Edward Elgar Publishing.
    9. John Goddard & Peter Sloane (ed.), 2014. "Handbook on the Economics of Professional Football," Books, Edward Elgar Publishing, number 14821, June.

  23. Jennifer Castle & David Hendry & Jurgen A. Doornik, 2010. "Evaluating Automatic Model Selection," Economics Series Working Papers 474, University of Oxford, Department of Economics.

    Cited by:

    1. Carlomagno, Guillermo & Espasa, Antoni, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Tasneem, Dina & Engle-Warnick, Jim & Benchekroun, Hassan, 2017. "An experimental study of a common property renewable resource game in continuous time," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 91-119.
    3. Driver, Ciaran & Trapani, Lorenzo & Urga, Giovanni, 2013. "On the use of cross-sectional measures of forecast uncertainty," International Journal of Forecasting, Elsevier, vol. 29(3), pages 367-377.
    4. Sophia Voulgaropoulou & Nikolaos Samaras & Nikolaos Ploskas, 2022. "Predicting the Execution Time of the Primal and Dual Simplex Algorithms Using Artificial Neural Networks," Mathematics, MDPI, vol. 10(7), pages 1-21, March.
    5. Thomas Chuffart & Emma Hooper, 2019. "An investigation of oil prices impact on sovereign credit default swaps in Russia and Venezuela," Post-Print hal-02194152, HAL.
    6. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
    7. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Felix Pretis, 2015. "Detecting Location Shifts during Model Selection by Step-Indicator Saturation," Econometrics, MDPI, vol. 3(2), pages 1-25, April.
    8. Bisio, Laura & Moauro, Filippo, 2017. "Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts," MPRA Paper 80211, University Library of Munich, Germany, revised 14 Jul 2017.
    9. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
    10. David Hendry & Grayham E. Mizon, 2016. "Improving the Teaching of Econometrics," Economics Series Working Papers 785, University of Oxford, Department of Economics.
    11. Cunha, Ronan & Pereira, Pedro L. Valls, 2015. "Automatic model selection for forecasting Brazilian stock returns," Textos para discussão 398, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    12. Emmanuel Flachaire & Sullivan Hué & Sébastien Laurent & Gilles Hacheme, 2024. "Interpretable Machine Learning Using Partial Linear Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 519-540, June.
    13. Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2017. "Mixed-frequency models for tracking short-term economic developments in Switzerland," Working Papers 2017-02, Swiss National Bank.
    14. Camila Epprecht & Dominique Guegan & Álvaro Veiga, 2013. "Comparing variable selection techniques for linear regression: LASSO and Autometrics," Documents de travail du Centre d'Economie de la Sorbonne 13080, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    15. Søren Johansen & Bent Nielsen, 2014. "Outlier detection algorithms for least squares time series regression," CREATES Research Papers 2014-39, Department of Economics and Business Economics, Aarhus University.
    16. André K. Anundsen, 2019. "Detecting Imbalances in House Prices: What Goes Up Must Come Down?," Scandinavian Journal of Economics, Wiley Blackwell, vol. 121(4), pages 1587-1619, October.
    17. Sullivan Hué, 2022. "GAM(L)A: An econometric model for interpretable machine learning," French Stata Users' Group Meetings 2022 19, Stata Users Group.
    18. Jennifer Castle & Xiaochuan Qin & W. Robert Reed, 2011. "Using Model Selection Algorthims to Obtain Reliable Coefficient Estimates," Working Papers in Economics 11/03, University of Canterbury, Department of Economics and Finance.
    19. Tomáš Plíhal, 2021. "Scheduled macroeconomic news announcements and Forex volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1379-1397, December.
    20. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2013. "Model Selection in Equations with Many ‘Small’ Effects," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(1), pages 6-22, February.
    21. Lukasz Gatarek & Søren Johansen, 2014. "Optimal hedging with the cointegrated vector autoregressive model," Discussion Papers 14-22, University of Copenhagen. Department of Economics.
    22. Fakhri J. Hasanov & Muhammad Javid & Frederick L. Joutz, 2022. "Saudi Non-Oil Exports before and after COVID-19: Historical Impacts of Determinants and Scenario Analysis," Sustainability, MDPI, vol. 14(4), pages 1-38, February.
    23. Loann David Denis Desboulets, 2018. "A Review on Variable Selection in Regression Analysis," Econometrics, MDPI, vol. 6(4), pages 1-27, November.
    24. Carlomagno Real, Guillermo & Espasa, Antoni, 2017. "Discovering pervasive and non-pervasive common cycles," DES - Working Papers. Statistics and Econometrics. WS 25392, Universidad Carlos III de Madrid. Departamento de Estadística.
    25. Jennifer Castle & David Hendry & Jurgen A. Doornik, 2008. "Model Selection when there are Multiple Breaks," Economics Series Working Papers 407, University of Oxford, Department of Economics.
    26. Robert A. Buckle & John Creedy, 2022. "Methods to evaluate institutional responses to performance‐based research funding systems," Australian Economic Papers, Wiley Blackwell, vol. 61(3), pages 615-634, September.
    27. David Hendry & Jennifer L. Castle, 2010. "Model Selection in Under-specified Equations Facing Breaks," Economics Series Working Papers 509, University of Oxford, Department of Economics.
    28. Brian Chi-ang Lin & Siqi Zheng & Felix Pretis & Lea Schneider & Jason E. Smerdon & David F. Hendry, 2016. "Detecting Volcanic Eruptions In Temperature Reconstructions By Designed Break-Indicator Saturation," Journal of Economic Surveys, Wiley Blackwell, vol. 30(3), pages 403-429, July.
    29. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.
    30. Kornstad, Tom & Nymoen, Ragnar & Skjerpen, Terje, 2013. "Macroeconomic shocks and the probability of being employed," Economic Modelling, Elsevier, vol. 33(C), pages 572-587.
    31. Andrew B. Martinez & Neil R. Ericsson, 2025. "Improving empirical models and forecasts with saturation-based machine learning," Annals of Operations Research, Springer, vol. 346(1), pages 447-487, March.
    32. Benedictow, Andreas & Hammersland, Roger, 2023. "Transition risk of a petroleum currency," Economic Modelling, Elsevier, vol. 128(C).
    33. David Hendry & Felix Pretis, 2011. "Anthropogenic Influences on Atmospheric CO2," Economics Series Working Papers 584, University of Oxford, Department of Economics.
    34. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Ragnar Nymoen, 2012. "Mis-specification Testing: Non-Invariance of Expectations Models of Inflation," Working Paper series 50_12, Rimini Centre for Economic Analysis.
    35. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, vol. 177(2), pages 305-319.
    36. Buckle, Robert A. & Creedy, John & Gemmell, Norman, 2019. "Is External Research Assessment Associated with Convergence or Divergence of Research Quality Across Universities and Disciplines? Evidence from the PBRF Process in New Zealand," Working Paper Series 20931, Victoria University of Wellington, Chair in Public Finance.
    37. David F. Hendry & Søren Johansen, 2011. "The Properties of Model Selection when Retaining Theory Variables," Discussion Papers 11-25, University of Copenhagen. Department of Economics.
    38. Camila Epprecht & Dominique Guegan & Álvaro Veiga & Joel Correa da Rosa, 2017. "Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00917797, HAL.
    39. Guillermo Carlomagno & Antoni Espasa, 2021. "Discovering Specific Common Trends in a Large Set of Disaggregates: Statistical Procedures, their Properties and an Empirical Application," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 641-662, June.
    40. Jennifer Castle & David Hendry, 2010. "Automatic Selection for Non-linear Models," Economics Series Working Papers 473, University of Oxford, Department of Economics.
    41. Søren Johansen & Bent Nielsen, 2016. "Asymptotic Theory of Outlier Detection Algorithms for Linear Time Series Regression Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 321-348, June.
    42. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    43. David Hendry, 2016. "Deciding Between Alternative Approaches In Macroeconomics," Economics Series Working Papers 778, University of Oxford, Department of Economics.
    44. Mukhtarov, Shahriyar & Mikayilov, Jeyhun I., 2023. "Could financial development eliminate energy poverty through renewable energy in Poland?," Energy Policy, Elsevier, vol. 182(C).
    45. Anundsen, André Kallåk, 2013. "Economic Regime Shifts and the US Subprime Bubble," Memorandum 05/2013, Oslo University, Department of Economics.
    46. Fakhri J. Hasanov & Elchin Suleymanov & Heyran Aliyeva & Hezi Eynalov & Sa'd Shannak, 2022. "What Drives the Agricultural Growth in Azerbaijan? Insights from Autometrics with Super Saturation," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 70(3), pages 147-174.
    47. Emmanuel Flachaire & Gilles Hacheme & Sullivan Hu'e & S'ebastien Laurent, 2022. "GAM(L)A: An econometric model for interpretable Machine Learning," Papers 2203.11691, arXiv.org.
    48. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damages," Working Papers 2020-003, The George Washington University, The Center for Economic Research.
    49. David Hendry & Grayham E. Mizon, 2012. "Forecasting from Structural Econometric Models," Economics Series Working Papers 597, University of Oxford, Department of Economics.
    50. Pellini, Elisabetta, 2021. "Estimating income and price elasticities of residential electricity demand with Autometrics," Energy Economics, Elsevier, vol. 101(C).
    51. Asad Zaman, 2017. "Lessons in Econometric Methodology: The Axiom of Correct Specification," International Econometric Review (IER), Econometric Research Association, vol. 9(2), pages 50-68, September.
    52. Daniel O. Beltran & Valentin Bolotnyy & Elizabeth C. Klee, 2015. "Un-Networking: The Evolution of Networks in the Federal Funds Market," Finance and Economics Discussion Series 2015-55, Board of Governors of the Federal Reserve System (U.S.).
    53. Deng, Yongheng & Girardin, Eric & Joyeux, Roselyne, 2018. "Fundamentals and the volatility of real estate prices in China: A sequential modelling strategy," China Economic Review, Elsevier, vol. 48(C), pages 205-222.
    54. David Hendry & Jurgen A. Doornik & Felix Pretis, 2013. "Step-indicator Saturation," Economics Series Working Papers 658, University of Oxford, Department of Economics.
    55. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2023. "Robust Discovery of Regression Models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 31-51.
    56. Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
    57. Carlomagno, Guillermo & Espasa, Antoni, 2015. "Forecasting a large set of disaggregates with common trends and outliers," DES - Working Papers. Statistics and Econometrics. WS ws1518, Universidad Carlos III de Madrid. Departamento de Estadística.
    58. Nymoen, Ragnar & Sparrman, Victoria, 2012. "Panel Data Evidence on the Role of Institutions and Shocks for Unemployment Dynamics and Equilibrium," Memorandum 20/2012, Oslo University, Department of Economics.
    59. Hendry, David F. & Johansen, Søren, 2015. "Model Discovery And Trygve Haavelmo’S Legacy," Econometric Theory, Cambridge University Press, vol. 31(1), pages 93-114, February.
    60. Waqar Badshah & Mehmet Bulut, 2020. "Model Selection Procedures in Bounds Test of Cointegration: Theoretical Comparison and Empirical Evidence," Economies, MDPI, vol. 8(2), pages 1-23, June.
    61. Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, The Center for Economic Research.
    62. Steven L. Scott & Hal R. Varian, 2015. "Bayesian Variable Selection for Nowcasting Economic Time Series," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 119-135, National Bureau of Economic Research, Inc.
    63. Jurgen A. Doornik & David F. Hendry & Steve Cook, 2015. "Statistical model selection with “Big Data”," Cogent Economics & Finance, Taylor & Francis Journals, vol. 3(1), pages 1045216-104, December.
    64. David H. Bernstein & Andrew B. Martinez, 2021. "Jointly Modeling Male and Female Labor Participation and Unemployment," Working Papers 2021-006, The George Washington University, The Center for Economic Research.
    65. Aris Spanos, 2011. "Foundational Issues in Statistical Modeling: Statistical Model Specification and Validation," Rationality, Markets and Morals, Frankfurt School Verlag, Frankfurt School of Finance & Management, vol. 2(47), October.
    66. Robert A. Buckle & John Creedy & Norman Gemmell, 2022. "Sources of convergence and divergence in university research quality: evidence from the performance-based research funding system in New Zealand," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3021-3047, June.
    67. Bent Jesper Christensen & Nabanita Datta Gupta & Paolo Santucci de Magistris, 2021. "Measuring the impact of clean energy production on CO2 abatement in Denmark: Upper bound estimation and forecasting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 118-149, January.
    68. Carlomagno, Guillermo & Espasa, Antoni, 2016. "Discovering common trends in a large set of disaggregates: statistical procedures and their properties," DES - Working Papers. Statistics and Econometrics. WS ws1519, Universidad Carlos III de Madrid. Departamento de Estadística.

  24. Nymoen, Ragnar & L. Castle, Jennifer & A. Doornik, Jurgen & F. Hendry, David, 2010. "Testing the Invariance of Expectations Models of Inflation," Memorandum 21/2010, Oslo University, Department of Economics.

    Cited by:

    1. Sophocles Mavroeidis & Mikkel Plagborg-M?ller & James H. Stock, 2014. "Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 52(1), pages 124-188, March.
    2. Mariano Kulish & Adrian Pagan, 2016. "Issues in Estimating New Keynesian Phillips Curves in the Presence of Unknown Structural Change," Econometric Reviews, Taylor & Francis Journals, vol. 35(7), pages 1251-1270, August.
    3. Russell, Bill & Chowdhury, Rosen Azad, 2013. "Estimating United States Phillips curves with expectations consistent with the statistical process of inflation," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 24-38.
    4. J. James Reade & Ulrich Volz, 2011. "From the General to the Specific," Discussion Papers 11-18, Department of Economics, University of Birmingham.
    5. Abbas, Syed K. & Bhattacharya, Prasad Sankar & Sgro, Pasquale, 2016. "The new Keynesian Phillips curve: An update on recent empirical advances," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 378-403.
    6. Syed Kanwar Abbas & Prasad Sankar Bhattacharya & Debdulal Mallick & Pasquale Sgro, 2016. "The New Keynesian Phillips Curve in a Small Open Economy: Empirical Evidence from Australia," The Economic Record, The Economic Society of Australia, vol. 92(298), pages 409-434, September.
    7. Nymoen, Ragnar & Swensen, Anders Rygh & Tveter, Eivind, 2012. "Interpreting the evidence for New Keynesian models of inflation dynamics," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 253-263.
    8. De Grauwe, Paul & Macchiarelli, Corrado, 2015. "Animal spirits and credit cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 59(C), pages 95-117.
    9. Adriana Cornea & Cars Hommes & Domenico Massaro, 2013. "Behavioral Heterogeneity in U.S. Inflation Dynamics," Tinbergen Institute Discussion Papers 13-015/II, Tinbergen Institute.
    10. Hendry, David F., 2011. "On adding over-identifying instrumental variables to simultaneous equations," Economics Letters, Elsevier, vol. 111(1), pages 68-70, April.
    11. Bill Russell & Anindya Banerjee & Issam Malki & Natalia Ponomareva, 2011. "A Multiple Break Panel Approach To Estimating United States Phillips Curves," Dundee Discussion Papers in Economics 252, Economic Studies, University of Dundee.

  25. David Hendry & Jennifer L. Castle, 2010. "Model Selection in Under-specified Equations Facing Breaks," Economics Series Working Papers 509, University of Oxford, Department of Economics.

    Cited by:

    1. Liqian Cai & Arnab Bhattacharjee & Roger Calantone & Taps Maiti, 2019. "Variable Selection with Spatially Autoregressive Errors: A Generalized Moments LASSO Estimator," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 146-200, September.
    2. Calvert Jump, Robert & Kohler, Karsten, 2022. "A history of aggregate demand and supply shocks for the United Kingdom, 1900 to 2016," Explorations in Economic History, Elsevier, vol. 85(C).
    3. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Hasan Dinçer & Serhat Yüksel & Rıdvan Aydın, 2020. "Elasticity Analysis of Fossil Energy Sources for Sustainable Economies: A Case of Gasoline Consumption in Turkey," Energies, MDPI, vol. 13(3), pages 1-15, February.
    4. James J. Forest & Ben S. Branch & Brian T. Berry, 2024. "Trading Activity in the Corporate Bond Market: A SAD Tale of Macro-Announcements and Behavioral Seasonality?," Risks, MDPI, vol. 12(5), pages 1-25, May.
    5. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Felix Pretis, 2015. "Detecting Location Shifts during Model Selection by Step-Indicator Saturation," Econometrics, MDPI, vol. 3(2), pages 1-25, April.
    6. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
    7. David Hendry & Grayham E. Mizon, 2016. "Improving the Teaching of Econometrics," Economics Series Working Papers 785, University of Oxford, Department of Economics.
    8. Marçal, Emerson Fernandes, 2024. "Testing rational expectations in a cointegrated VAR with structural change," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    9. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2013. "Model Selection in Equations with Many ‘Small’ Effects," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(1), pages 6-22, February.
    10. Hendry, David F. & Pretis, Felix, 2023. "Analysing differences between scenarios," International Journal of Forecasting, Elsevier, vol. 39(2), pages 754-771.
    11. David F. Hendry, 2020. "First in, First out: Econometric Modelling of UK Annual CO_2 Emissions, 1860–2017," Economics Papers 2020-W02, Economics Group, Nuffield College, University of Oxford.
    12. David Hendry, 2016. "Deciding Between Alternative Approaches In Macroeconomics," Economics Series Working Papers 778, University of Oxford, Department of Economics.
    13. Jennifer Castle & David Hendry & Michael P. Clements, 2014. "Robust Approaches to Forecasting," Economics Series Working Papers 697, University of Oxford, Department of Economics.
    14. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2023. "Robust Discovery of Regression Models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 31-51.

  26. Jennifer Castle & David Hendry, 2010. "A Low-Dimension Portmanteau Test for Non-linearity," Economics Series Working Papers 471, University of Oxford, Department of Economics.

    Cited by:

    1. David F. Hendry, 2011. "Empirical Economic Model Discovery and Theory Evaluation," Rationality, Markets and Morals, Frankfurt School Verlag, Frankfurt School of Finance & Management, vol. 2(46), October.
    2. Jennifer Castle & David Hendry & Jurgen A. Doornik, 2010. "Evaluating Automatic Model Selection," Economics Series Working Papers 474, University of Oxford, Department of Economics.
    3. Anne Péguin-Feissolle & Bilel Sanhaji, 2015. "Testing the Constancy of Conditional Correlations in Multivariate GARCH-type Models (Extended Version with Appendix)," AMSE Working Papers 1516, Aix-Marseille School of Economics, France.
    4. David Hendry & Grayham E. Mizon, 2016. "Improving the Teaching of Econometrics," Economics Series Working Papers 785, University of Oxford, Department of Economics.
    5. Frank Asche & Atle Oglend & Petter Osmundsen, 2015. "Modeling UK Natural Gas Prices when Gas Prices Periodically Decouple from the Oil Price," CESifo Working Paper Series 5232, CESifo.
    6. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2022. "The historical role of energy in UK inflation and productivity and implications for price inflation in 2022," Economics Series Working Papers 983, University of Oxford, Department of Economics.
    7. Sullivan Hué, 2022. "GAM(L)A: An econometric model for interpretable machine learning," French Stata Users' Group Meetings 2022 19, Stata Users Group.
    8. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2013. "Model Selection in Equations with Many ‘Small’ Effects," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(1), pages 6-22, February.
    9. Mosab I. Tabash & Ezekiel Oseni & Adel Ahmed & Yasmeen Elsantil & Linda Nalini Daniel & Adedoyin Isola Lawal, 2024. "Pathway to a Sustainable Energy Economy: Determinants of Electricity Infrastructure in Nigeria," Sustainability, MDPI, vol. 16(7), pages 1-25, April.
    10. Loann David Denis Desboulets, 2018. "A Review on Variable Selection in Regression Analysis," Econometrics, MDPI, vol. 6(4), pages 1-27, November.
    11. Stillwagon, Josh R., 2016. "Non-linear exchange rate relationships: An automated model selection approach with indicator saturation," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 84-109.
    12. Mendonça, Diogo de Prince & Marçal, Emerson Fernandes & Brito, Márcio Holland de, 2016. "Is fiscal policy effective in Brazil? An empirical analysis," Textos para discussão 433, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    13. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.
    14. David F. Hendry, 2020. "First in, First out: Econometric Modelling of UK Annual CO_2 Emissions, 1860–2017," Economics Papers 2020-W02, Economics Group, Nuffield College, University of Oxford.
    15. Josh R. Stillwagon, 2015. "TIPS and the VIX: Non-linear Spillovers from Financial Panic to Breakeven Inflation," Working Papers 1502, Trinity College, Department of Economics.
    16. Anders Bredahl Kock & Timo Teräsvirta, 2010. "Forecasting with nonlinear time series models," CREATES Research Papers 2010-01, Department of Economics and Business Economics, Aarhus University.
    17. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Facing Economic Shifts, Climate Change and Evolving Pandemics," Econometrics, MDPI, vol. 10(1), pages 1-21, December.
    18. Mukhtarov, Shahriyar & Mikayilov, Jeyhun I. & Maharramov, Shahin & Aliyev, Javid & Suleymanov, Elchin, 2022. "Higher oil prices, are they good or bad for renewable energy consumption: The case of Iran?," Renewable Energy, Elsevier, vol. 186(C), pages 411-419.
    19. Barry Harrison & Winston Moore, 2012. "Stock Market Efficiency, Non-Linearity, Thin Trading and Asymmetric Information in MENA Stock Markets," Economic Issues Journal Articles, Economic Issues, vol. 17(1), pages 77-93, March.
    20. Jennifer Castle & David Hendry, 2010. "Automatic Selection for Non-linear Models," Economics Series Working Papers 473, University of Oxford, Department of Economics.
    21. Bendik P. Andersen & Petter E. de Lange, 2021. "Efficiency in the Atlantic salmon futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 949-984, June.
    22. David Hendry, 2016. "Deciding Between Alternative Approaches In Macroeconomics," Economics Series Working Papers 778, University of Oxford, Department of Economics.
    23. Şule Akkoyunlu, 2024. "Testing Okun’s Law for Turkey (1923-2019)," Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 48(2), pages 113-132, April.
    24. Jahyun Koo & Ivan Paya & David A. Peel, 2012. "The Bank of Korea's nonlinear monetary policy rule," Applied Economics Letters, Taylor & Francis Journals, vol. 19(12), pages 1193-1202, August.
    25. Emmanuel Flachaire & Gilles Hacheme & Sullivan Hu'e & S'ebastien Laurent, 2022. "GAM(L)A: An econometric model for interpretable Machine Learning," Papers 2203.11691, arXiv.org.
    26. Francisco Salas-Molina & Juan A. Rodr'iguez-Aguilar & Joan Serr`a & Montserrat Guillen & Francisco J. Martin, 2016. "Empirical analysis of daily cash flow time series and its implications for forecasting," Papers 1611.04941, arXiv.org, revised Jun 2017.
    27. Castle, Jennifer L. & Hendry, David F. & Martinez, Andrew B., 2023. "The historical role of energy in UK inflation and productivity with implications for price inflation," Energy Economics, Elsevier, vol. 126(C).
    28. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2023. "Robust Discovery of Regression Models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 31-51.
    29. Jurgen A. Doornik & David F. Hendry & Steve Cook, 2015. "Statistical model selection with “Big Data”," Cogent Economics & Finance, Taylor & Francis Journals, vol. 3(1), pages 1045216-104, December.
    30. Jurgen A. Doornik, 2016. "An Example of Instability: Discussion of the Paper by Søren Johansen and Bent Nielsen," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 357-359, June.
    31. Mahalia Jackman & Roland Craigwell & Michelle Doyle-Lowe, 2013. "Nonlinearity in the reaction of the foreign exchange market to interest rate differentials: evidence from a small open economy with a long-term peg," Applied Financial Economics, Taylor & Francis Journals, vol. 23(4), pages 287-296, February.
    32. Tucker S. McElroy & Dhrubajyoti Ghosh & Soumendra Lahiri, 2024. "Quadratic Prediction of Time Series via Auto-Cumulants," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 86(1), pages 431-463, February.
    33. Shahid IQBAL & Maqbool H. SIAL, 2016. "Projections of Inflation Dynamics for Pakistan: GMDH Approach," Journal of Economics and Political Economy, KSP Journals, vol. 3(3), pages 536-559, September.
    34. Ericsson Neil R., 2016. "Testing for and estimating structural breaks and other nonlinearities in a dynamic monetary sector," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 377-398, September.

  27. Jennifer L. Castle & Xiaochuan Qin & W. Robert Reed, 2009. "How To Pick The Best Regression Equation: A Review And Comparison Of Model Selection Algorithms," Working Papers in Economics 09/13, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Jennifer Castle & David Hendry & Jurgen A. Doornik, 2010. "Evaluating Automatic Model Selection," Economics Series Working Papers 474, University of Oxford, Department of Economics.
    2. Thomas Pave Sohnesen & Niels Stender, 2017. "Is Random Forest a Superior Methodology for Predicting Poverty? An Empirical Assessment," Poverty & Public Policy, John Wiley & Sons, vol. 9(1), pages 118-133, March.
    3. Jennifer Castle & David Hendry & Jurgen A. Doornik, 2008. "Model Selection when there are Multiple Breaks," Economics Series Working Papers 407, University of Oxford, Department of Economics.
    4. Lu, Quanying & Li, Yuze & Chai, Jian & Wang, Shouyang, 2020. "Crude oil price analysis and forecasting: A perspective of “new triangle”," Energy Economics, Elsevier, vol. 87(C).
    5. Graham Bird & Alex Mandilaras & Helen Popper, 2012. "Explaining Shifts in Exchange Rate Regimes," School of Economics Discussion Papers 1312, School of Economics, University of Surrey.
    6. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    7. Steven L. Scott & Hal R. Varian, 2015. "Bayesian Variable Selection for Nowcasting Economic Time Series," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 119-135, National Bureau of Economic Research, Inc.

  28. Jennifer Castle & David Hendry & Jurgen A. Doornik, 2008. "Model Selection when there are Multiple Breaks," Economics Series Working Papers 407, University of Oxford, Department of Economics.

    Cited by:

    1. Hecq, Alain & Jacobs, Jan P.A.M. & Stamatogiannis, Michalis P., 2019. "Testing for news and noise in non-stationary time series subject to multiple historical revisions," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 396-407.
    2. Calvert Jump, Robert & Kohler, Karsten, 2022. "A history of aggregate demand and supply shocks for the United Kingdom, 1900 to 2016," Explorations in Economic History, Elsevier, vol. 85(C).
    3. Carlomagno, Guillermo & Espasa, Antoni, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
    5. Janine Aron & Ronald Macdonald & John Muellbauer, 2014. "Exchange Rate Pass-Through in Developing and Emerging Markets: A Survey of Conceptual, Methodological and Policy Issues, and Selected Empirical Findings," Journal of Development Studies, Taylor & Francis Journals, vol. 50(1), pages 101-143, January.
    6. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    7. David F. Hendry, 2011. "Empirical Economic Model Discovery and Theory Evaluation," Rationality, Markets and Morals, Frankfurt School Verlag, Frankfurt School of Finance & Management, vol. 2(46), October.
    8. Jennifer Castle & David Hendry & Jurgen A. Doornik, 2010. "Evaluating Automatic Model Selection," Economics Series Working Papers 474, University of Oxford, Department of Economics.
    9. Marczak, Martyna & Proietti, Tommaso, 2015. "Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113137, Verein für Socialpolitik / German Economic Association.
    10. Bernd Hayo & Kentaro Iwatsubo, 2019. "Who Is Successful in Foreign Exchange Margin Trading? New Survey Evidence from Japan," MAGKS Papers on Economics 201917, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    11. Neil R. Ericsson, 2016. "Economic Forecasting in Theory and Practice : An Interview with David F. Hendry," International Finance Discussion Papers 1184, Board of Governors of the Federal Reserve System (U.S.).
    12. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
    13. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Felix Pretis, 2015. "Detecting Location Shifts during Model Selection by Step-Indicator Saturation," Econometrics, MDPI, vol. 3(2), pages 1-25, April.
    14. Guillaume Chevillon & Takamitsu Kurita, 2023. "What Does it Take to Control Global Temperatures? A toolbox for testing and estimating the impact of economic policies on climate," Papers 2307.05818, arXiv.org, revised Jul 2024.
    15. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
    16. Apergis, Nicholas & Pan, Wei-Fong & Reade, James & Wang, Shixuan, 2023. "Modelling Australian electricity prices using indicator saturation," Energy Economics, Elsevier, vol. 120(C).
    17. Camila Epprecht & Dominique Guegan & Álvaro Veiga, 2013. "Comparing variable selection techniques for linear regression: LASSO and Autometrics," Documents de travail du Centre d'Economie de la Sorbonne 13080, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    18. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," Working Papers 2017-001, The George Washington University, The Center for Economic Research.
    19. Panday, Anjan, 2015. "Impact of monetary policy on exchange market pressure: The case of Nepal," Journal of Asian Economics, Elsevier, vol. 37(C), pages 59-71.
    20. Anundsen, Andre K. & Nymoen, Ragnar, 2015. "Did US consumers `save for a rainy day' before the Great Recession?," Memorandum 11/2015, Oslo University, Department of Economics.
    21. Marçal, Emerson Fernandes, 2024. "Testing rational expectations in a cointegrated VAR with structural change," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    22. Marcin Błażejowski & Jacek Kwiatkowski & Paweł Kufel, 2020. "BACE and BMA Variable Selection and Forecasting for UK Money Demand and Inflation with Gretl," Econometrics, MDPI, vol. 8(2), pages 1-29, May.
    23. Bjørnar Karlsen Kivedal, 2023. "Long run non-linearity in CO2 emissions: the I(2) cointegration model and the environmental Kuznets curve," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 50(4), pages 899-931, November.
    24. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2013. "Model Selection in Equations with Many ‘Small’ Effects," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(1), pages 6-22, February.
    25. Fakhri J. Hasanov & Muhammad Javid & Frederick L. Joutz, 2022. "Saudi Non-Oil Exports before and after COVID-19: Historical Impacts of Determinants and Scenario Analysis," Sustainability, MDPI, vol. 14(4), pages 1-38, February.
    26. J. James Reade & Ulrich Volz, 2011. "From the General to the Specific," Discussion Papers 11-18, Department of Economics, University of Birmingham.
    27. Valentina Corradi & Norman Swanson, 2013. "Testing for Structural Stability of Factor Augmented Forecasting Models," Departmental Working Papers 201314, Rutgers University, Department of Economics.
    28. David Hendry & Jennifer L. Castle, 2010. "Model Selection in Under-specified Equations Facing Breaks," Economics Series Working Papers 509, University of Oxford, Department of Economics.
    29. David Hendry & Andrew B. Martinez, 2016. "Evaluating Multi-Step System Forecasts with Relatively Few Forecast-Error Observations," Economics Series Working Papers 784, University of Oxford, Department of Economics.
    30. Sara Muhammadullah & Amena Urooj & Faridoon Khan, 2021. "A revisit of the unemployment rate, interest rate, GDP growth and Inflation of Pakistan: Whether Structural break or unit root?," iRASD Journal of Economics, International Research Alliance for Sustainable Development (iRASD), vol. 3(2), pages 80-92, September.
    31. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.
    32. Dai, Hongyan & Xiao, Qin & Chen, Songlin & Zhou, Weihua, 2023. "Data-driven demand forecast for O2O operations: An adaptive hierarchical incremental approach," International Journal of Production Economics, Elsevier, vol. 259(C).
    33. Igor Pelipas, 2012. "Multiple Structural Breaks and Inflation Persistance in Belarus," BEROC Working Paper Series 21, Belarusian Economic Research and Outreach Center (BEROC).
    34. Pollack, Adam B. & Kaufmann, Robert K., 2022. "Increasing storm risk, structural defense, and house prices in the Florida Keys," Ecological Economics, Elsevier, vol. 194(C).
    35. David Hendry & Felix Pretis, 2011. "Anthropogenic Influences on Atmospheric CO2," Economics Series Working Papers 584, University of Oxford, Department of Economics.
    36. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Ragnar Nymoen, 2012. "Mis-specification Testing: Non-Invariance of Expectations Models of Inflation," Working Paper series 50_12, Rimini Centre for Economic Analysis.
    37. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, vol. 177(2), pages 305-319.
    38. Haug, Alfred A. & King, Ian, 2014. "In the long run, US unemployment follows inflation like a faithful dog," Journal of Macroeconomics, Elsevier, vol. 41(C), pages 42-52.
    39. Camila Epprecht & Dominique Guegan & Álvaro Veiga & Joel Correa da Rosa, 2017. "Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00917797, HAL.
    40. Guillermo Carlomagno & Antoni Espasa, 2021. "Discovering Specific Common Trends in a Large Set of Disaggregates: Statistical Procedures, their Properties and an Empirical Application," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 641-662, June.
    41. Jennifer Castle & David Hendry, 2010. "Automatic Selection for Non-linear Models," Economics Series Working Papers 473, University of Oxford, Department of Economics.
    42. Kristine Wika Haraldsen & Ragnar Nymoen & Victoria Sparrman, 2019. "Labour market institutions, shocks and the employment rate," Discussion Papers 901, Statistics Norway, Research Department.
    43. Ryan-Collins, Josh & Werner, Richard A. & Castle, Jennifer, 2016. "A half-century diversion of monetary policy? An empirical horse-race to identify the UK variable most likely to deliver the desired nominal GDP growth rate," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 158-176.
    44. Jennifer Castle & David Hendry & Michael P. Clements, 2014. "Robust Approaches to Forecasting," Economics Series Working Papers 697, University of Oxford, Department of Economics.
    45. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damages," Working Papers 2020-003, The George Washington University, The Center for Economic Research.
    46. Bucacos, Elizabeth, 2017. "Financial Conditions and Monetary Policy in Uruguay: An MS-VAR Approach," IDB Publications (Working Papers) 8275, Inter-American Development Bank.
    47. Ericsson, Neil R., 2017. "Interpreting estimates of forecast bias," International Journal of Forecasting, Elsevier, vol. 33(2), pages 563-568.
    48. M. Mogliani & Thomas Ferrière, 2016. "Rationality of announcements, business cycle asymmetry, and predictability of revisions. The case of French GDP," Working papers 600, Banque de France.
    49. David Hendry & Grayham E. Mizon, 2012. "Forecasting from Structural Econometric Models," Economics Series Working Papers 597, University of Oxford, Department of Economics.
    50. Pellini, Elisabetta, 2021. "Estimating income and price elasticities of residential electricity demand with Autometrics," Energy Economics, Elsevier, vol. 101(C).
    51. Pedro Garcia-del-Barrio & J. James Reade, 2022. "Does certainty on the winner diminish the interest in sport competitions? The case of formula one," Empirical Economics, Springer, vol. 63(2), pages 1059-1079, August.
    52. Dooruj Rambaccussing & Andrzej Kwiatkowski, 2024. "The nexus between national and regional reporting of economic news: Evidence from the United Kingdom and Scotland," Bulletin of Economic Research, Wiley Blackwell, vol. 76(2), pages 371-393, April.
    53. Roman Frydman & Soren Johansen & Anders Rahbek & Morten Nyboe Tabor, 2021. "Asset Prices Under Knightian Uncertainty," Working Papers Series inetwp172, Institute for New Economic Thinking.
    54. David Hendry & Jurgen A. Doornik & Felix Pretis, 2013. "Step-indicator Saturation," Economics Series Working Papers 658, University of Oxford, Department of Economics.
    55. Irfan Akbar Kazi & Mohamed Mehanaoui & Farhan Akbar, 2014. "The shift-contagion effect of global financial crisis and the European debt crisis on OECD Countries," Working Papers 2014-128, Department of Research, Ipag Business School.
    56. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Selecting a Model for Forecasting," Econometrics, MDPI, vol. 9(3), pages 1-35, June.
    57. Carlomagno, Guillermo & Espasa, Antoni, 2015. "Forecasting a large set of disaggregates with common trends and outliers," DES - Working Papers. Statistics and Econometrics. WS ws1518, Universidad Carlos III de Madrid. Departamento de Estadística.
    58. Anh Dinh Minh Nguyen, 2017. "U.K. Monetary Policy under Inflation Targeting," Bank of Lithuania Working Paper Series 41, Bank of Lithuania.
    59. Hendry, David F. & Johansen, Søren, 2015. "Model Discovery And Trygve Haavelmo’S Legacy," Econometric Theory, Cambridge University Press, vol. 31(1), pages 93-114, February.
    60. David F. Hendry, 2024. "A Brief History of General‐to‐specific Modelling," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(1), pages 1-20, February.
    61. Roman Frydman & Morten Nyboe Tabor, 2022. "Muth's Hypothesis Under Knightian Uncertainty: A Novel Account of Inflation Forecasts," Working Papers Series inetwp194, Institute for New Economic Thinking.
    62. Alexander HARIN, 2014. "Partially Unforeseen Events. Corrections and Correcting Formulae for Forecasts," Expert Journal of Economics, Sprint Investify, vol. 2(2), pages 69-79.
    63. Jurgen A. Doornik & David F. Hendry & Steve Cook, 2015. "Statistical model selection with “Big Data”," Cogent Economics & Finance, Taylor & Francis Journals, vol. 3(1), pages 1045216-104, December.
    64. Rocha, Jordano Vieira & Pereira, Pedro L. Valls, 2015. "Forecast comparison with nonlinear methods for Brazilian industrial production," Textos para discussão 397, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    65. Igor Pelipas, 2011. "Structural Breaks and Dynamic Characteristics of Inflation and Growth Rates of Monetary Aggregates," BEROC Working Paper Series 15, Belarusian Economic Research and Outreach Center (BEROC).
    66. László Kónya & Bekzod Abdullaev, 2015. "Does Ricardian equivalence hold in Australia? A revision based on testing super exogeneity with impulse-indicator saturation," Empirical Economics, Springer, vol. 49(2), pages 423-448, September.
    67. Haraldsen, Kristine Wika & Ragnar, Nymoen & Sparrman, Victoria, 2019. "Labour market institutions, shocks and the employment rate," Memorandum 6/2019, Oslo University, Department of Economics.
    68. Huang, Tao & Fildes, Robert & Soopramanien, Didier, 2014. "The value of competitive information in forecasting FMCG retail product sales and the variable selection problem," European Journal of Operational Research, Elsevier, vol. 237(2), pages 738-748.
    69. Huang, Tao & Fildes, Robert & Soopramanien, Didier, 2019. "Forecasting retailer product sales in the presence of structural change," European Journal of Operational Research, Elsevier, vol. 279(2), pages 459-470.
    70. Ericsson Neil R., 2016. "Testing for and estimating structural breaks and other nonlinearities in a dynamic monetary sector," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 377-398, September.
    71. William Larson, 2015. "Forecasting an Aggregate in the Presence of Structural Breaks in the Disaggregates," Working Papers 2015-002, The George Washington University, The Center for Economic Research.
    72. Harin, Alexander, 2014. "General correcting formulae for forecasts," MPRA Paper 55283, University Library of Munich, Germany.

  29. Jennifer Castle & David Hendry & Nicholas W.P. Fawcett, 2008. "Forecasting with Equilibrium-correction Models during Structural Breaks," Economics Series Working Papers 408, University of Oxford, Department of Economics.

    Cited by:

    1. Neil R. Ericsson, 2015. "Eliciting GDP Forecasts from the FOMC’s Minutes Around the Financial Crisis," International Finance Discussion Papers 1152, Board of Governors of the Federal Reserve System (U.S.).
    2. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
    3. David F. Hendry, 2011. "Empirical Economic Model Discovery and Theory Evaluation," Rationality, Markets and Morals, Frankfurt School Verlag, Frankfurt School of Finance & Management, vol. 2(46), October.
    4. Chihwa Kao & Lorenzo Trapani & Giovanni Urga, 2016. "Testing for Instability in Covariance Structures," Working papers 2016-33, University of Connecticut, Department of Economics.
    5. Neil R. Ericsson, 2016. "Economic Forecasting in Theory and Practice : An Interview with David F. Hendry," International Finance Discussion Papers 1184, Board of Governors of the Federal Reserve System (U.S.).
    6. Neil R. Ericsson & Mohammed H. I. Dore & Hassan Butt, 2022. "Detecting and Quantifying Structural Breaks in Climate," Econometrics, MDPI, vol. 10(4), pages 1-27, November.
    7. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    8. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
    9. Jeronymo Marcondes Pinto & Emerson Fernandes Marçal, 2023. "An artificial intelligence approach to forecasting when there are structural breaks: a reinforcement learning-based framework for fast switching," Empirical Economics, Springer, vol. 65(4), pages 1729-1759, October.
    10. David Hendry & Grayham E. Mizon, 2016. "Improving the Teaching of Econometrics," Economics Series Working Papers 785, University of Oxford, Department of Economics.
    11. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," Working Papers 2017-001, The George Washington University, The Center for Economic Research.
    12. David F. Hendry, 2020. "First in, First out: Econometric Modelling of UK Annual CO_2 Emissions, 1860–2017," Economics Papers 2020-W02, Economics Group, Nuffield College, University of Oxford.
    13. Andrew B. Martinez & Neil R. Ericsson, 2025. "Improving empirical models and forecasts with saturation-based machine learning," Annals of Operations Research, Springer, vol. 346(1), pages 447-487, March.
    14. Allanson, Paul & Petrie, Dennis, 2013. "Longitudinal methods to investigate the role of health determinants in the dynamics of income-related health inequality," Journal of Health Economics, Elsevier, vol. 32(5), pages 922-937.
    15. William D. Larson & Tara M. Sinclair, 2020. "Nowcasting Unemployment Insurance Claims in the Time of COVID-19," Working Papers 2020-004, The George Washington University, The Center for Economic Research, revised Aug 2020.
    16. Marta Boczoń & Jean-François Richard, 2020. "Balanced Growth Approach to Tracking Recessions," Econometrics, MDPI, vol. 8(2), pages 1-35, April.
    17. Wickens, Michael R., 2012. "How Useful are DSGE Macroeconomic Models for Forecasting?," CEPR Discussion Papers 9049, C.E.P.R. Discussion Papers.
    18. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    19. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Principles from Experience with Forecasting Competitions," Forecasting, MDPI, vol. 3(1), pages 1-28, February.
    20. Jennifer Castle & David Hendry & Michael P. Clements, 2014. "Robust Approaches to Forecasting," Economics Series Working Papers 697, University of Oxford, Department of Economics.
    21. David Hendry & Grayham E. Mizon, 2012. "Forecasting from Structural Econometric Models," Economics Series Working Papers 597, University of Oxford, Department of Economics.
    22. Ahumada, H. & Cornejo, M., 2016. "Forecasting food prices: The case of corn, soybeans and wheat," International Journal of Forecasting, Elsevier, vol. 32(3), pages 838-848.
    23. David Hendry & Carlos Santos, 2010. "An Automatic Test of Super Exogeneity," Economics Series Working Papers 476, University of Oxford, Department of Economics.
    24. Hendry, David F. & Johansen, Søren, 2015. "Model Discovery And Trygve Haavelmo’S Legacy," Econometric Theory, Cambridge University Press, vol. 31(1), pages 93-114, February.
    25. Rocha, Jordano Vieira & Pereira, Pedro L. Valls, 2015. "Forecast comparison with nonlinear methods for Brazilian industrial production," Textos para discussão 397, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    26. Jitendra Sharma & Subrata Kumar Mitra, 2021. "Asymmetric relationship between tourist arrivals and employment," Tourism Economics, , vol. 27(5), pages 952-970, August.
    27. David Hendry & Michael P. Clements, 2010. "Forecasting from Mis-specified Models in the Presence of Unanticipated Location Shifts," Economics Series Working Papers 484, University of Oxford, Department of Economics.
    28. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2024. "Forecasting the UK top 1% income share in a shifting world," Economica, London School of Economics and Political Science, vol. 91(363), pages 1047-1074, July.

  30. Jennifer Castle & David Hendry, 2008. "The Long-Run Determinants of UK Wages, 1860-2004," Economics Series Working Papers 409, University of Oxford, Department of Economics.

    Cited by:

    1. Nicholas Barr & Alison Johnston, 2010. "Interest Subsidies on Student Loans: A Better Class of Drain," CEE Discussion Papers 0114, Centre for the Economics of Education, LSE.
    2. Calvert Jump, Robert & Kohler, Karsten, 2022. "A history of aggregate demand and supply shocks for the United Kingdom, 1900 to 2016," Explorations in Economic History, Elsevier, vol. 85(C).
    3. Loening, Josef L. & Durevall, Dick & Birru, Yohannes A., 2009. "Inflation dynamics and food prices in an agricultural economy : the case of Ethiopia," Policy Research Working Paper Series 4969, The World Bank.
    4. Durevall, Dick & Loening, Josef L. & Birru, Yohannes A., 2010. "Inflation Dynamics and Food Prices in Ethiopia," Working Papers in Economics 478, University of Gothenburg, Department of Economics, revised 03 Jun 2013.
    5. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2022. "The historical role of energy in UK inflation and productivity and implications for price inflation in 2022," Economics Series Working Papers 983, University of Oxford, Department of Economics.
    6. David M. Williams, 2021. "Pay and Productivity in Canada: Growing Together, Only Slower than Ever," International Productivity Monitor, Centre for the Study of Living Standards, vol. 40, pages 3-26, Spring.
    7. Stillwagon, Josh R., 2016. "Non-linear exchange rate relationships: An automated model selection approach with indicator saturation," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 84-109.
    8. Neil Shephard, 2010. "Deferred fees for universities," Economics Papers 2010-W03, Economics Group, Nuffield College, University of Oxford.
    9. Jiao, Xiyu & Pretis, Felix & Schwarz, Moritz, 2024. "Testing for coefficient distortion due to outliers with an application to the economic impacts of climate change," Journal of Econometrics, Elsevier, vol. 239(1).
    10. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.
    11. Josh R. Stillwagon, 2015. "TIPS and the VIX: Non-linear Spillovers from Financial Panic to Breakeven Inflation," Working Papers 1502, Trinity College, Department of Economics.
    12. Baffigi, Alberto & Bontempi, Maria Elena & Felice, Emanuele & Golinelli, Roberto, 2015. "The changing relationship between inflation and the economic cycle in Italy: 1861–2012," Explorations in Economic History, Elsevier, vol. 56(C), pages 53-70.
    13. Durevall, Dick & Henrekson, Magnus, 2011. "The futile quest for a grand explanation of long-run government expenditure," Journal of Public Economics, Elsevier, vol. 95(7), pages 708-722.
    14. Muellbauer, John, 2018. "The Future of Macroeconomics," INET Oxford Working Papers 2018-10, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    15. Robert G. King, 2008. "The Phillips curve and U.S. macroeconomic policy : snapshots, 1958-1996," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 94(Fall), pages 311-359.
    16. Sohrab Rafiq, 2014. "What Do Energy Prices Tell Us About UK Inflation?," Economica, London School of Economics and Political Science, vol. 81(322), pages 293-310, April.
    17. Castle, Jennifer L. & Hendry, David F. & Martinez, Andrew B., 2023. "The historical role of energy in UK inflation and productivity with implications for price inflation," Energy Economics, Elsevier, vol. 126(C).
    18. David Leblang & Michael D. Smith & Dennis Wesselbaum, 2025. "Does inflation affect well-being?," Empirical Economics, Springer, vol. 69(3), pages 1527-1549, September.
    19. Barr, Nicholas & Johnston, Alison, 2010. "Interest subsidies on student loans: a better class of drain," LSE Research Online Documents on Economics 28287, London School of Economics and Political Science, LSE Library.
    20. Nasir, Muhammad Ali & Wu, Junjie & Howes, Cameron & Ripley, Helen, 2022. "Asymmetric nexus between wages and productivity in the context of the global financial crisis," Journal of Economic Behavior & Organization, Elsevier, vol. 198(C), pages 164-175.
    21. Ragnar Nymoen, 2017. "Between Institutions and Global Forces: Norwegian Wage Formation Since Industrialisation," Econometrics, MDPI, vol. 5(1), pages 1-54, January.

  31. Jennifer Castle & David Hendry, 2007. "Forecasting UK Inflation: the Roles of Structural Breaks and Time Disaggregation," Economics Series Working Papers 309, University of Oxford, Department of Economics.

    Cited by:

    1. Costas Milas, 2009. "Does high M4 money growth trigger large increases in UK inflation? Evidence from a regime-switching model," Oxford Economic Papers, Oxford University Press, vol. 61(1), pages 168-182, January.
    2. Thiago Carlomagno Carlo & Emerson Fernandes Marçal, 2016. "Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon," Applied Economics, Taylor & Francis Journals, vol. 48(50), pages 4846-4860, October.
    3. David Hendry & Andrew B. Martinez, 2016. "Evaluating Multi-Step System Forecasts with Relatively Few Forecast-Error Observations," Economics Series Working Papers 784, University of Oxford, Department of Economics.
    4. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    5. Garcés Díaz Daniel, 2020. "On the Drivers of Inflation in Different Monetary Regimes," Working Papers 2020-16, Banco de México.
    6. Jan P.A.M. Jacobs & Kenneth F. Wallis, 2007. "Cointegration, Long-Run Structural Modelling And Weak Exogeneity: Two Models Of The Uk Economy," CAMA Working Papers 2007-12, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Torre Cepeda Leonardo E. & Flores Segovia Miguel A., 2020. "Private Banking Credit and Economic Growth in Mexico: A State Level Panel Data Analysis 2005-2018," Working Papers 2020-17, Banco de México.

  32. Jennifer L. Castle & David F. Hendry, 2007. "A Low-Dimension Collinearity-Robust Test for Non-linearity," Economics Series Working Papers 326, University of Oxford, Department of Economics.

    Cited by:

    1. Jennifer Castle & David Hendry, 2008. "The Long-Run Determinants of UK Wages, 1860-2004," Economics Series Working Papers 409, University of Oxford, Department of Economics.

Articles

  1. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2024. "Forecasting the UK top 1% income share in a shifting world," Economica, London School of Economics and Political Science, vol. 91(363), pages 1047-1074, July.

    Cited by:

    1. Andrew B. Martinez & Neil R. Ericsson, 2025. "Improving empirical models and forecasts with saturation-based machine learning," Annals of Operations Research, Springer, vol. 346(1), pages 447-487, March.
    2. Gary Cornwall & Marina Gindelsky, 2025. "Nowcasting Distributional National Accounts for the United States: A Machine Learning Approach," AEA Papers and Proceedings, American Economic Association, vol. 115, pages 79-84, May.

  2. Castle, Jennifer L. & Hendry, David F., 2024. "Five sensitive intervention points to achieve climate neutrality by 2050, illustrated by the UK," Renewable Energy, Elsevier, vol. 226(C).

    Cited by:

    1. Roshani, Amir Salek & Assareh, Ehsanolah & Ershadi, Ali & Carvalho, Monica, 2024. "Optimization of a hybrid renewable energy system for off-grid residential communities using numerical simulation, response surface methodology, and life cycle assessment," Renewable Energy, Elsevier, vol. 236(C).
    2. Guo, Shiliang & He, Jianqi & Ma, Kai & Yang, Jie & Wang, Yaochen & Li, Pengpeng, 2025. "Robust economic dispatch for industrial microgrids with electric vehicle demand response," Renewable Energy, Elsevier, vol. 240(C).

  3. Castle, Jennifer L. & Kurita, Takamitsu, 2024. "Stability between cryptocurrency prices and the term structure," Journal of Economic Dynamics and Control, Elsevier, vol. 165(C).

    Cited by:

    1. Fayssal Jamhamed & Franck Martin & Fabien Rondeau & Josué Thélissaint & Stéphane Tufféry, 2024. "Regime-Specific Dynamics and Informational Efficiency in Cryptomarkets: Evidence from Gaussian Mixture Models," Economics Working Paper Archive (University of Rennes & University of Caen) 2024-13, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
    2. Josué Thélissaint, 2024. "Assessing Cryptomarket Risks: Macroeconomic Forces, Market Shocks and Behavioural Dynamics," Economics Working Paper Archive (University of Rennes & University of Caen) 2024-14, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.

  4. Castle, Jennifer L. & Hendry, David F. & Martinez, Andrew B., 2023. "The historical role of energy in UK inflation and productivity with implications for price inflation," Energy Economics, Elsevier, vol. 126(C).

    Cited by:

    1. Zhang, Long & Padhan, Hemachandra & Singh, Sanjay Kumar & Gupta, Monika, 2024. "The impact of renewable energy on inflation in G7 economies: Evidence from artificial neural networks and machine learning methods," Energy Economics, Elsevier, vol. 136(C).
    2. Jennifer L. Castle & David F. Hendry, 2024. "What a Puzzle! Unravelling Why UK Phillips Curves were Unstable," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(4), pages 743-760, August.
    3. Michael D. Bordo & Oliver Bush & Bank of England, 2025. ""Muddling Through or Tunnelling Through?" UK Monetary and Fiscal Exceptionalism and The Great Inflation," Working Papers 347, Princeton University, Department of Economics, Center for Economic Policy Studies..

  5. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2023. "Robust Discovery of Regression Models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 31-51.
    See citations under working paper version above.
  6. Castle, Jennifer L. & Hendry, David F., 2023. "Can The Uk Achieve Net Zero Greenhouse Gas Emissions By 2050?," National Institute Economic Review, National Institute of Economic and Social Research, vol. 266, pages 11-21, November.
    See citations under working paper version above.
  7. Jeronymo Marcondes Pinto & Jennifer L. Castle, 2022. "Machine Learning Dynamic Switching Approach to Forecasting in the Presence of Structural Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(2), pages 129-157, July.

    Cited by:

    1. Jeronymo Marcondes Pinto & Emerson Fernandes Marçal, 2023. "An artificial intelligence approach to forecasting when there are structural breaks: a reinforcement learning-based framework for fast switching," Empirical Economics, Springer, vol. 65(4), pages 1729-1759, October.
    2. Marcelo C. Medeiros & Jeronymo M. Pinro, 2025. "Time Series Embedding and Combination of Forecasts: A Reinforcement Learning Approach," Papers 2508.20795, arXiv.org.
    3. Andrew B. Martinez & Neil R. Ericsson, 2025. "Improving empirical models and forecasts with saturation-based machine learning," Annals of Operations Research, Springer, vol. 346(1), pages 447-487, March.

  8. Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F., 2022. "Short-term forecasting of the coronavirus pandemic," International Journal of Forecasting, Elsevier, vol. 38(2), pages 453-466.

    Cited by:

    1. Marcelo Medeiros & Alexandre Street & Davi Vallad~ao & Gabriel Vasconcelos & Eduardo Zilberman, 2020. "Short-Term Covid-19 Forecast for Latecomers," Papers 2004.07977, arXiv.org, revised Sep 2021.
    2. Bårdsen, Gunnar & Nymoen, Ragnar, 2025. "Dynamic time series modelling and forecasting of COVID-19 in Norway," International Journal of Forecasting, Elsevier, vol. 41(1), pages 251-269.
    3. Aljuneidi, Tariq & Punia, Sushil & Jebali, Aida & Nikolopoulos, Konstantinos, 2024. "Forecasting and planning for a critical infrastructure sector during a pandemic: Empirical evidence from a food supply chain," European Journal of Operational Research, Elsevier, vol. 317(3), pages 936-952.
    4. Gunnar BÃ¥rdsen & Ragnar Nymoen, 2023. "Dynamic time series modelling and forecasting of COVID-19 in Norway," Working Paper Series 19623, Department of Economics, Norwegian University of Science and Technology.
    5. Sen, Anindya & Baker, John David & Zhang, Qihuang & Agarwal, Rishav Raj & Lam, Jean-Paul, 2023. "Do more stringent policies reduce daily COVID-19 case counts? Evidence from Canadian provinces," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 225-242.
    6. Choudhury, Nishat Alam & Ramkumar, M. & Schoenherr, Tobias & Singh, Shalabh, 2023. "The role of operations and supply chain management during epidemics and pandemics: Potential and future research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    7. Bårdsen, Gunnar & Nymoen, Ragnar, 2023. "Dynamic time series modelling and forecasting of COVID-19 in Norway," Memorandum 3/2023, Oslo University, Department of Economics.
    8. Evangelos Spiliotis & Fotios Petropoulos & Vassilios Assimakopoulos, 2023. "On the Disagreement of Forecasting Model Selection Criteria," Forecasting, MDPI, vol. 5(2), pages 1-12, June.
    9. Paul Haimerl & Tobias Hartl, 2023. "Modeling COVID-19 Infection Rates by Regime-Switching Unobserved Components Models," Econometrics, MDPI, vol. 11(2), pages 1-15, April.

  9. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    See citations under working paper version above.
  10. Castle, Jennifer L. & Kurita, Takamitsu, 2021. "A dynamic econometric analysis of the dollar-pound exchange rate in an era of structural breaks and policy regime shifts," Journal of Economic Dynamics and Control, Elsevier, vol. 128(C).

    Cited by:

    1. Takamitsu Kurita & Patrick James, 2022. "The Canadian–US dollar exchange rate over the four decades of the post‐Bretton Woods float: An econometric study allowing for structural breaks," Metroeconomica, Wiley Blackwell, vol. 73(3), pages 856-883, July.
    2. Angela Ifeanyi Ujunwa & Augustine Ujunwa & Emmanuel Onah & Nnenna Georgina Nwonye & Onyedikachi David Chukwunwike, 2021. "Extending the determinants of currency substitution in Nigeria: Any role for financial innovation?," South African Journal of Economics, Economic Society of South Africa, vol. 89(4), pages 590-607, December.
    3. Luke P. Jackson & Katarina Juselius & Andrew B. Martinez & Felix Pretis, 2025. "Modelling the dependence between recent changes in polar ice sheets: Implications for global sea-level projections," Working Papers 2025-002, The George Washington University, The Center for Economic Research.
    4. Tang, Xinmeng & Zhou, Xiaoguang, 2023. "Impact of green finance on renewable energy development: A spatiotemporal consistency perspective," Renewable Energy, Elsevier, vol. 204(C), pages 320-337.

  11. Jurgen A. Doornik & Jennifer L. Castle & David F. Hendry, 2021. "Modeling and forecasting the COVID‐19 pandemic time‐series data," Social Science Quarterly, Southwestern Social Science Association, vol. 102(5), pages 2070-2087, September.

    Cited by:

    1. Gilles Dufrénot & Ewen Gallic & Pierre Michel & Norgile Midopkè Bonou & Ségui Gnaba & Iness Slaoui, 2024. "Impact of socioeconomic determinants on the speed of epidemic diseases: a comparative analysis," Oxford Economic Papers, Oxford University Press, vol. 76(4), pages 1089-1107.
    2. Friedrich, Marina & Lin, Yicong, 2024. "Sieve bootstrap inference for linear time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 239(1).

  12. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Principles from Experience with Forecasting Competitions," Forecasting, MDPI, vol. 3(1), pages 1-28, February.

    Cited by:

    1. Bårdsen, Gunnar & Nymoen, Ragnar, 2025. "Dynamic time series modelling and forecasting of COVID-19 in Norway," International Journal of Forecasting, Elsevier, vol. 41(1), pages 251-269.
    2. Jennifer Castle & Takamitsu Kurita, 2022. "Structural relationships between cryptocurrency prices and monetary policy indicators," Economics Series Working Papers 972, University of Oxford, Department of Economics.
    3. Voyant, Cyril & Notton, Gilles & Duchaud, Jean-Laurent & Gutiérrez, Luis Antonio García & Bright, Jamie M. & Yang, Dazhi, 2022. "Benchmarks for solar radiation time series forecasting," Renewable Energy, Elsevier, vol. 191(C), pages 747-762.
    4. Sbrana, Giacomo & Silvestrini, Andrea, 2025. "The structural Theta method and its predictive performance in the M4-Competition," International Journal of Forecasting, Elsevier, vol. 41(3), pages 940-952.
    5. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Facing Economic Shifts, Climate Change and Evolving Pandemics," Econometrics, MDPI, vol. 10(1), pages 1-21, December.
    6. Alessia Paccagnini, 2021. "Editorial for Special Issue “New Frontiers in Forecasting the Business Cycle and Financial Markets”," Forecasting, MDPI, vol. 3(3), pages 1-3, July.
    7. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2024. "Improving models and forecasts after equilibrium-mean shifts," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1085-1100.
    8. Jurgen A. Doornik & Jennifer L. Castle & David F. Hendry, 2021. "Modeling and forecasting the COVID‐19 pandemic time‐series data," Social Science Quarterly, Southwestern Social Science Association, vol. 102(5), pages 2070-2087, September.
    9. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Selecting a Model for Forecasting," Econometrics, MDPI, vol. 9(3), pages 1-35, June.
    10. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2024. "Forecasting the UK top 1% income share in a shifting world," Economica, London School of Economics and Political Science, vol. 91(363), pages 1047-1074, July.

  13. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2021. "Modelling non-stationary ‘Big Data’," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1556-1575.
    See citations under working paper version above.
  14. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2021. "The Value Of Robust Statistical Forecasts In The Covid-19 Pandemic," National Institute Economic Review, National Institute of Economic and Social Research, vol. 256, pages 19-43, April.

    Cited by:

    1. Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," ERSA Working Paper Series, Economic Research Southern Africa, vol. 0.
    2. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Bårdsen, Gunnar & Nymoen, Ragnar, 2025. "Dynamic time series modelling and forecasting of COVID-19 in Norway," International Journal of Forecasting, Elsevier, vol. 41(1), pages 251-269.
    4. John M Drake & Andreas Handel & Éric Marty & Eamon B O’Dea & Tierney O’Sullivan & Giovanni Righi & Andrew T Tredennick, 2023. "A data-driven semi-parametric model of SARS-CoV-2 transmission in the United States," PLOS Computational Biology, Public Library of Science, vol. 19(11), pages 1-17, November.
    5. Hendry, David F. & Pretis, Felix, 2023. "Analysing differences between scenarios," International Journal of Forecasting, Elsevier, vol. 39(2), pages 754-771.
    6. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Facing Economic Shifts, Climate Change and Evolving Pandemics," Econometrics, MDPI, vol. 10(1), pages 1-21, December.
    7. Castle, Jennifer L. & Hendry, David F. & Martinez, Andrew B., 2023. "The historical role of energy in UK inflation and productivity with implications for price inflation," Energy Economics, Elsevier, vol. 126(C).

  15. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Selecting a Model for Forecasting," Econometrics, MDPI, vol. 9(3), pages 1-35, June.
    See citations under working paper version above.
  16. Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F., 2020. "Card forecasts for M4," International Journal of Forecasting, Elsevier, vol. 36(1), pages 129-134.

    Cited by:

    1. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    2. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F., 2022. "Short-term forecasting of the coronavirus pandemic," International Journal of Forecasting, Elsevier, vol. 38(2), pages 453-466.
    4. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2024. "Improving models and forecasts after equilibrium-mean shifts," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1085-1100.
    5. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2020. "Short-term forecasting of the Coronavirus Pandemic - 2020-04-27," Economics Papers 2020-W06, Economics Group, Nuffield College, University of Oxford.
    6. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Principles from Experience with Forecasting Competitions," Forecasting, MDPI, vol. 3(1), pages 1-28, February.
    7. Pantelis Agathangelou & Demetris Trihinas & Ioannis Katakis, 2020. "A Multi-Factor Analysis of Forecasting Methods: A Study on the M4 Competition," Data, MDPI, vol. 5(2), pages 1-24, April.
    8. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2021. "Modelling non-stationary ‘Big Data’," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1556-1575.
    9. Castle, Jennifer L. & Hendry, David F. & Martinez, Andrew B., 2023. "The historical role of energy in UK inflation and productivity with implications for price inflation," Energy Economics, Elsevier, vol. 126(C).
    10. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Selecting a Model for Forecasting," Econometrics, MDPI, vol. 9(3), pages 1-35, June.
    11. Ruben Loaiza-Maya & Gael M Martin & David T. Frazier, 2020. "Focused Bayesian Prediction," Monash Econometrics and Business Statistics Working Papers 1/20, Monash University, Department of Econometrics and Business Statistics.
    12. Diogo de Prince & Emerson Fernandes Marçal & Pedro L. Valls Pereira, 2022. "Forecasting Industrial Production Using Its Aggregated and Disaggregated Series or a Combination of Both: Evidence from One Emerging Market Economy," Econometrics, MDPI, vol. 10(2), pages 1-34, June.
    13. Wilson, Tom & Grossman, Irina & Temple, Jeromey, 2023. "Evaluation of the best M4 competition methods for small area population forecasting," International Journal of Forecasting, Elsevier, vol. 39(1), pages 110-122.
    14. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2024. "Forecasting the UK top 1% income share in a shifting world," Economica, London School of Economics and Political Science, vol. 91(363), pages 1047-1074, July.
    15. Jennifer L. Castle & Jurgen A. Doornik & David Hendry, 2019. "Some forecasting principles from the M4 competition," Economics Papers 2019-W01, Economics Group, Nuffield College, University of Oxford.

  17. Castle, Jennifer L. & Hendry, David F., 2020. "Climate Econometrics: An Overview," Foundations and Trends(R) in Econometrics, now publishers, vol. 10(3-4), pages 145-322, August.

    Cited by:

    1. Blazsek, Szabolcs & Escribano, Álvaro, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Chen, Liang & Dolado, Juan José & Gonzalo, Jesús & Ramos Ramírez, Andrey David, 2023. "Heterogeneous Predictive Association of CO2 with Global Warming," UC3M Working papers. Economics 36451, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    4. Blazsek, Szabolcs & Escribano, Álvaro & Kristof, Erzsebet, 2024. "Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models," UC3M Working papers. Economics 39546, Universidad Carlos III de Madrid. Departamento de Economía.
    5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Castle, Jennifer L. & Hendry, David F., 2024. "Five sensitive intervention points to achieve climate neutrality by 2050, illustrated by the UK," Renewable Energy, Elsevier, vol. 226(C).
    7. Guglielmo Maria Caporale & Maria Fatima Romero-Rojo & Luis Alberiko Gil-Alana, 2024. "Trends in the Sea Ice and Snow Cover Extent: A Fractional Integration Analysis," CESifo Working Paper Series 11475, CESifo.
    8. Jennifer L. Castle & David F. Hendry, 2024. "What a Puzzle! Unravelling Why UK Phillips Curves were Unstable," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(4), pages 743-760, August.
    9. Ar'anzazu de Juan & Pilar Poncela & Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2022. "Economic activity and climate change," Papers 2206.03187, arXiv.org, revised Jun 2022.
    10. Marra, Alessandro & Colantonio, Emiliano & Cucculelli, Marco & Nissi, Eugenia, 2024. "The ‘complex’ transition: Energy intensity and CO2 emissions amidst technological and structural shifts. Evidence from OECD countries," Energy Economics, Elsevier, vol. 136(C).
    11. Federico Maddanu, 2022. "A harmonically weighted filter for cyclical long memory processes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(1), pages 49-78, March.
    12. K. Mukherjee & B. Ouattara, 2021. "Climate and monetary policy: do temperature shocks lead to inflationary pressures?," Climatic Change, Springer, vol. 167(3), pages 1-21, August.
    13. del Barrio Castro, Tomas & Escribano, Alvaro & Sibbertsen, Philipp, 2024. "Modeling and Forecasting the Long Memory of Cyclical Trends in Paleoclimate Data," Hannover Economic Papers (HEP) dp-722, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    14. Vasco J.Gabriel & Luis F. Martins & Anthoulla Phella, 2021. "Modelling Low-Frequency Covariability of Paleoclimatic Data," Working Papers 2022_17, Business School - Economics, University of Glasgow.
    15. Tommaso Proietti & Federico Maddanu, 2021. "Modelling Cycles in Climate Series: the Fractional Sinusoidal Waveform Process," CEIS Research Paper 518, Tor Vergata University, CEIS, revised 19 Oct 2021.

  18. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2017. "Evaluating Forecasts, Narratives and Policy Using a Test of Invariance," Econometrics, MDPI, vol. 5(3), pages 1-27, September.

    Cited by:

    1. Darandary, Abdulelah & Mikayilov, Jeyhun I. & Soummane, Salaheddine, 2024. "Impacts of electricity price reform on Saudi regional fuel consumption and CO2 emissions," Energy Economics, Elsevier, vol. 131(C).
    2. Clements, Michael P. & Reade, J. James, 2020. "Forecasting and forecast narratives: The Bank of England Inflation Reports," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1488-1500.
    3. Guillaume Chevillon & Takamitsu Kurita, 2023. "What Does it Take to Control Global Temperatures? A toolbox for testing and estimating the impact of economic policies on climate," Papers 2307.05818, arXiv.org, revised Jul 2024.
    4. S. Yanki Kalfa & Jaime Marquez, 2021. "Forecasting FOMC Forecasts," Econometrics, MDPI, vol. 9(3), pages 1-21, September.
    5. Hendry, David F. & Pretis, Felix, 2023. "Analysing differences between scenarios," International Journal of Forecasting, Elsevier, vol. 39(2), pages 754-771.
    6. Rocco Mosconi & Paolo Paruolo, 2022. "Celebrated Econometricians: Katarina Juselius and Søren Johansen," Econometrics, MDPI, vol. 10(2), pages 1-4, May.
    7. Andrew B. Martinez & Neil R. Ericsson, 2025. "Improving empirical models and forecasts with saturation-based machine learning," Annals of Operations Research, Springer, vol. 346(1), pages 447-487, March.
    8. David F. Hendry, 2020. "A Short History of Macro-econometric Modelling," Economics Papers 2020-W01, Economics Group, Nuffield College, University of Oxford.
    9. Pretis, Felix, 2021. "Exogeneity in climate econometrics," Energy Economics, Elsevier, vol. 96(C).
    10. David Hendry, 2016. "Deciding Between Alternative Approaches In Macroeconomics," Economics Series Working Papers 778, University of Oxford, Department of Economics.
    11. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Jeyhun Mammadov, 2020. "Gasoline Demand Elasticities at the Backdrop of Lower Oil Prices: Fuel-Subsidizing Country Case," Energies, MDPI, vol. 13(24), pages 1-18, December.
    12. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damages," Working Papers 2020-003, The George Washington University, The Center for Economic Research.
    13. Simionescu, Mihaela, 2022. "Econometrics of sentiments- sentometrics and machine learning: The improvement of inflation predictions in Romania using sentiment analysis," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    14. Castle, Jennifer L. & Hendry, David F. & Martinez, Andrew B., 2023. "The historical role of energy in UK inflation and productivity with implications for price inflation," Energy Economics, Elsevier, vol. 126(C).
    15. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2023. "Robust Discovery of Regression Models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 31-51.

  19. Ryan-Collins, Josh & Werner, Richard A. & Castle, Jennifer, 2016. "A half-century diversion of monetary policy? An empirical horse-race to identify the UK variable most likely to deliver the desired nominal GDP growth rate," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 158-176.

    Cited by:

    1. Hillary Chijindu Ezeaku & Imo Godwin Ibe & Uche Boniface Ugwuanyi & N. J. Modebe & Emmanuel Kalu Agbaeze, 2018. "Monetary Policy Transmission and Industrial Sector Growth: Empirical Evidence From Nigeria," SAGE Open, , vol. 8(2), pages 21582440187, April.
    2. Wang, Ling, 2022. "The dynamics of money supply determination under asset purchase programs: A market-based versus a bank-based financial system," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    3. Ponomarenko, Alexey, 2019. "Do sterilized foreign exchange interventions create money?," Journal of Asian Economics, Elsevier, vol. 62(C), pages 1-16.
    4. Setareh Katircioglu & Salih Katircioglu & Farid Irani, 2023. "Links between growth, trade and financial openness in South Africa: An empirical investigation," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4324-4330, October.
    5. David F. Hendry, 2020. "A Short History of Macro-econometric Modelling," Economics Papers 2020-W01, Economics Group, Nuffield College, University of Oxford.
    6. Pawe³ Œliwiñski, 2023. "Endogenous money supply, global liquidity and financial transactions: Panel evidence from OECD countries," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 18(1), pages 121-152, March.
    7. Clavero, Borja, 2017. "A contribution to the Quantity Theory of Disaggregated Credit," MPRA Paper 76657, University Library of Munich, Germany.
    8. Lee, Kang-Soek & Werner, Richard A., 2018. "Reconsidering Monetary Policy: An Empirical Examination of the Relationship Between Interest Rates and Nominal GDP Growth in the U.S., U.K., Germany and Japan," Ecological Economics, Elsevier, vol. 146(C), pages 26-34.
    9. Bahaa Aly, Tarek, 2025. "Nonlinear Macroeconomic Granger Causality: An ANN Input Occlusion Approach on MSSA-Denoised Data," MPRA Paper 125453, University Library of Munich, Germany.

  20. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
    See citations under working paper version above.
  21. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2015. "Robust approaches to forecasting," International Journal of Forecasting, Elsevier, vol. 31(1), pages 99-112.
    See citations under working paper version above.
  22. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Felix Pretis, 2015. "Detecting Location Shifts during Model Selection by Step-Indicator Saturation," Econometrics, MDPI, vol. 3(2), pages 1-25, April.

    Cited by:

    1. Liqian Cai & Arnab Bhattacharjee & Roger Calantone & Taps Maiti, 2019. "Variable Selection with Spatially Autoregressive Errors: A Generalized Moments LASSO Estimator," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 146-200, September.
    2. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Hasan Dinçer & Serhat Yüksel & Rıdvan Aydın, 2020. "Elasticity Analysis of Fossil Energy Sources for Sustainable Economies: A Case of Gasoline Consumption in Turkey," Energies, MDPI, vol. 13(3), pages 1-15, February.
    3. Neil R. Ericsson, 2015. "Eliciting GDP Forecasts from the FOMC’s Minutes Around the Financial Crisis," International Finance Discussion Papers 1152, Board of Governors of the Federal Reserve System (U.S.).
    4. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
    5. Jennifer Castle & Takamitsu Kurita, 2019. "Modelling and forecasting the dollar-pound exchange rate in the presence of structural breaks," Economics Series Working Papers 866, University of Oxford, Department of Economics.
    6. John Muellbauer, 2016. "Macroeconomics and Consumption," Economics Series Working Papers Paper-811, University of Oxford, Department of Economics.
    7. Dima, Bogdan & Dima, Ştefana Maria & Ioan, Roxana, 2025. "The short-run impact of investor expectations’ past volatility on current predictions: The case of VIX," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 98(C).
    8. Pretis, Felix, 2020. "Econometric modelling of climate systems: The equivalence of energy balance models and cointegrated vector autoregressions," Journal of Econometrics, Elsevier, vol. 214(1), pages 256-273.
    9. Thomas Chuffart & Emma Hooper, 2019. "An investigation of oil prices impact on sovereign credit default swaps in Russia and Venezuela," Post-Print hal-02194152, HAL.
    10. Felix Pretis & Michael Mann & Robert Kaufmann, 2015. "Testing competing models of the temperature hiatus: assessing the effects of conditioning variables and temporal uncertainties through sample-wide break detection," Climatic Change, Springer, vol. 131(4), pages 705-718, August.
    11. Neil R. Ericsson, 2016. "Economic Forecasting in Theory and Practice : An Interview with David F. Hendry," International Finance Discussion Papers 1184, Board of Governors of the Federal Reserve System (U.S.).
    12. Takamitsu Kurita & Patrick James, 2022. "The Canadian–US dollar exchange rate over the four decades of the post‐Bretton Woods float: An econometric study allowing for structural breaks," Metroeconomica, Wiley Blackwell, vol. 73(3), pages 856-883, July.
    13. Neil R. Ericsson & Mohammed H. I. Dore & Hassan Butt, 2022. "Detecting and Quantifying Structural Breaks in Climate," Econometrics, MDPI, vol. 10(4), pages 1-27, November.
    14. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    15. Karsten Kohler & Engelbert Stockhammer, 2022. "Flexible exchange rates in emerging markets: shock absorbers or drivers of endogenous cycles?," Working Papers PKWP2205, Post Keynesian Economics Society (PKES).
    16. Rafael Wildauer & Stuart Leitch & Jakob Kapeller, 2021. "Is a €10 trillion European climate investment initiative fiscally sustainable?," Working Papers PKWP2121, Post Keynesian Economics Society (PKES).
    17. David Hendry & Grayham E. Mizon, 2016. "Improving the Teaching of Econometrics," Economics Series Working Papers 785, University of Oxford, Department of Economics.
    18. Apergis, Nicholas & Pan, Wei-Fong & Reade, James & Wang, Shixuan, 2023. "Modelling Australian electricity prices using indicator saturation," Energy Economics, Elsevier, vol. 120(C).
    19. Kenneth G. Stewart, 2023. "The Simple Macroeconometrics of the Quantity Theory And the Welfare Cost of Inflation," Department Discussion Papers 2301, Department of Economics, University of Victoria.
    20. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," Working Papers 2017-001, The George Washington University, The Center for Economic Research.
    21. Mukanjari, Samson & Sterner, Thomas, 2018. "Do Markets Trump Politics? Evidence from Fossil Market Reactions to the Paris Agreement and the U.S. Election," Working Papers in Economics 728, University of Gothenburg, Department of Economics.
    22. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2022. "The historical role of energy in UK inflation and productivity and implications for price inflation in 2022," Economics Series Working Papers 983, University of Oxford, Department of Economics.
    23. Marçal, Emerson Fernandes, 2024. "Testing rational expectations in a cointegrated VAR with structural change," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    24. Jorge Marques & Carlos Santos & Maria Alberta Oliveira, 2025. "A Quest for Innovation Drivers with Autometrics: Do These Differ Before and After the COVID-19 Pandemic for European Economies?," Economies, MDPI, vol. 13(4), pages 1-41, April.
    25. Bjerregaard, Casper & Møller, Niels Framroze, 2022. "The influence of electricity prices on saving electricity in production: Automated multivariate time-series analyses for 99 Danish trades and industries," Energy Economics, Elsevier, vol. 107(C).
    26. Frydman, Roman & Stillwagon, Joshua R., 2018. "Fundamental factors and extrapolation in stock-market expectations: The central role of structural change," Journal of Economic Behavior & Organization, Elsevier, vol. 148(C), pages 189-198.
    27. James Reade & Genaro Sucarrat, 2016. "General-to-Specific (GETS) Modelling And Indicator Saturation With The R Package Gets," Economics Series Working Papers 794, University of Oxford, Department of Economics.
    28. Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F., 2022. "Short-term forecasting of the coronavirus pandemic," International Journal of Forecasting, Elsevier, vol. 38(2), pages 453-466.
    29. Stillwagon, Josh R., 2016. "Non-linear exchange rate relationships: An automated model selection approach with indicator saturation," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 84-109.
    30. James A. Duffy & David F. Hendry, 2017. "The impact of integrated measurement errors on modeling long-run macroeconomic time series," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 568-587, October.
    31. Sara Muhammadullah & Amena Urooj & Faridoon Khan, 2021. "A revisit of the unemployment rate, interest rate, GDP growth and Inflation of Pakistan: Whether Structural break or unit root?," iRASD Journal of Economics, International Research Alliance for Sustainable Development (iRASD), vol. 3(2), pages 80-92, September.
    32. Brian Chi-ang Lin & Siqi Zheng & Felix Pretis & Lea Schneider & Jason E. Smerdon & David F. Hendry, 2016. "Detecting Volcanic Eruptions In Temperature Reconstructions By Designed Break-Indicator Saturation," Journal of Economic Surveys, Wiley Blackwell, vol. 30(3), pages 403-429, July.
    33. Hendry, David F. & Pretis, Felix, 2023. "Analysing differences between scenarios," International Journal of Forecasting, Elsevier, vol. 39(2), pages 754-771.
    34. Jennifer Castle & David Hendry, 2016. "Policy Analysis, Forediction, and Forecast Failure," Economics Series Working Papers 809, University of Oxford, Department of Economics.
    35. Andrew B. Martinez & Neil R. Ericsson, 2025. "Improving empirical models and forecasts with saturation-based machine learning," Annals of Operations Research, Springer, vol. 346(1), pages 447-487, March.
    36. Scheer, Antonina & Schwarz, Moritz & Hopkins, Debbie & Caldecott, Ben, 2022. "Whose jobs face transition risk in Alberta? Understanding sectoral employment precarity in an oil-rich Canadian province," LSE Research Online Documents on Economics 115358, London School of Economics and Political Science, LSE Library.
    37. Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2020. "Smooth Robust Multi-Horizon Forecasts," Working Papers 2020-009, The George Washington University, The Center for Economic Research.
    38. Jurgen A. Doornik & David F. Hendry, 2016. "Outliers and Model Selection: Discussion of the Paper by Søren Johansen and Bent Nielsen," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 360-365, June.
    39. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2024. "Improving models and forecasts after equilibrium-mean shifts," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1085-1100.
    40. Felix Pretis, 2022. "Does a Carbon Tax Reduce CO2 Emissions? Evidence from British Columbia," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(1), pages 115-144, September.
    41. Espasa, Antoni & Senra, Eva, 2017. "22 Years of inflation assessment and forecasting experience at the bulletin of EU & US inflation and macroeconomic analysis," DES - Working Papers. Statistics and Econometrics. WS 24678, Universidad Carlos III de Madrid. Departamento de Estadística.
    42. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2020. "Short-term forecasting of the Coronavirus Pandemic - 2020-04-27," Economics Papers 2020-W06, Economics Group, Nuffield College, University of Oxford.
    43. David F. Hendry, 2020. "A Short History of Macro-econometric Modelling," Economics Papers 2020-W01, Economics Group, Nuffield College, University of Oxford.
    44. Jennifer L. Castle & David F. Hendry, 2024. "What a Puzzle! Unravelling Why UK Phillips Curves were Unstable," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(4), pages 743-760, August.
    45. Niels Framroze Møller & Laura Mørch Andersen & Lars Gårn Hansen & Carsten Lynge Jensen, 2018. "Can pecuniary and environmental incentives via SMS messaging make households adjust their intra-day electricity demand to a fluctuating production?," IFRO Working Paper 2018/06, University of Copenhagen, Department of Food and Resource Economics.
    46. Dalano DaSouza & Mahalia Jackman, 2024. "Estimating the Impact of Education on Growth in a Small Data-Poor Country: the Case of Saint Vincent and the Grenadines," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 13449-13469, September.
    47. Mikayilov, Jeyhun I. & Darandary, Abdulelah & Alyamani, Ryan & Hasanov, Fakhri J. & Alatawi, Hatem, 2020. "Regional heterogeneous drivers of electricity demand in Saudi Arabia: Modeling regional residential electricity demand," Energy Policy, Elsevier, vol. 146(C).
    48. David Hendry, 2016. "Deciding Between Alternative Approaches In Macroeconomics," Economics Series Working Papers 778, University of Oxford, Department of Economics.
    49. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Nov 2024.
    50. Ryan-Collins, Josh & Werner, Richard A. & Castle, Jennifer, 2016. "A half-century diversion of monetary policy? An empirical horse-race to identify the UK variable most likely to deliver the desired nominal GDP growth rate," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 158-176.
    51. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2021. "Modelling non-stationary ‘Big Data’," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1556-1575.
    52. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damages," Working Papers 2020-003, The George Washington University, The Center for Economic Research.
    53. Kaufmann, Robert K. & Schroer, Colter, 2023. "Social and environmental events disrupt the relation between motor gasoline prices and market fundamentals," Energy Economics, Elsevier, vol. 126(C).
    54. Ericsson, Neil R., 2017. "Interpreting estimates of forecast bias," International Journal of Forecasting, Elsevier, vol. 33(2), pages 563-568.
    55. Møller, Niels Framroze & Andersen, Laura Mørch & Hansen, Lars Gårn & Jensen, Carsten Lynge, 2019. "Can pecuniary and environmental incentives via SMS messaging make households adjust their electricity demand to a fluctuating production?," Energy Economics, Elsevier, vol. 80(C), pages 1050-1058.
    56. Castle, Jennifer L. & Kurita, Takamitsu, 2024. "Stability between cryptocurrency prices and the term structure," Journal of Economic Dynamics and Control, Elsevier, vol. 165(C).
    57. Shahriyar Mukhtarov & Jeyhun I. Mikayilov & Sugra Humbatova & Vugar Muradov, 2020. "Do High Oil Prices Obstruct the Transition to Renewable Energy Consumption?," Sustainability, MDPI, vol. 12(11), pages 1-16, June.
    58. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2017. "Evaluating Forecasts, Narratives and Policy Using a Test of Invariance," Econometrics, MDPI, vol. 5(3), pages 1-27, September.
    59. Ahumada, H. & Cornejo, M., 2016. "Forecasting food prices: The case of corn, soybeans and wheat," International Journal of Forecasting, Elsevier, vol. 32(3), pages 838-848.
    60. Castle, Jennifer L. & Kurita, Takamitsu, 2021. "A dynamic econometric analysis of the dollar-pound exchange rate in an era of structural breaks and policy regime shifts," Journal of Economic Dynamics and Control, Elsevier, vol. 128(C).
    61. Pellini, Elisabetta, 2021. "Estimating income and price elasticities of residential electricity demand with Autometrics," Energy Economics, Elsevier, vol. 101(C).
    62. Hildegart Ahumada & Magdalena Cornejo, 2021. "Are Soybean Yields Getting a Free Ride from Climate Change? Evidence from Argentine Time Series Data," Econometrics, MDPI, vol. 9(2), pages 1-14, June.
    63. Castle, Jennifer L. & Hendry, David F. & Martinez, Andrew B., 2023. "The historical role of energy in UK inflation and productivity with implications for price inflation," Energy Economics, Elsevier, vol. 126(C).
    64. Roman Frydman & Soren Johansen & Anders Rahbek & Morten Nyboe Tabor, 2021. "Asset Prices Under Knightian Uncertainty," Working Papers Series inetwp172, Institute for New Economic Thinking.
    65. Sucarrat, Genaro, 2019. "User-Specified General-to-Specific and Indicator Saturation Methods," MPRA Paper 96148, University Library of Munich, Germany.
    66. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Selecting a Model for Forecasting," Econometrics, MDPI, vol. 9(3), pages 1-35, June.
    67. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2023. "Robust Discovery of Regression Models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 31-51.
    68. David F. Hendry, 2024. "A Brief History of General‐to‐specific Modelling," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(1), pages 1-20, February.
    69. Roman Frydman & Morten Nyboe Tabor, 2022. "Muth's Hypothesis Under Knightian Uncertainty: A Novel Account of Inflation Forecasts," Working Papers Series inetwp194, Institute for New Economic Thinking.
    70. David H. Bernstein & Andrew B. Martinez, 2021. "Jointly Modeling Male and Female Labor Participation and Unemployment," Working Papers 2021-006, The George Washington University, The Center for Economic Research.
    71. Felix Pretis, 2015. "Econometric Models of Climate Systems: The Equivalence of Two-Component Energy Balance Models and Cointegrated VARs," Economics Series Working Papers 750, University of Oxford, Department of Economics.
    72. Leighton Vaughan Williams & J. James Reade, 2016. "Prediction Markets, Social Media and Information Efficiency," Kyklos, Wiley Blackwell, vol. 69(3), pages 518-556, August.
    73. Samson Mukanjari & Thomas Sterner, 2024. "Do markets Trump politics? Fossil and renewable market reactions to major political events," Economic Inquiry, Western Economic Association International, vol. 62(2), pages 805-836, April.
    74. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2024. "Forecasting the UK top 1% income share in a shifting world," Economica, London School of Economics and Political Science, vol. 91(363), pages 1047-1074, July.
    75. Jeronymo Marcondes Pinto & Jennifer L. Castle, 2022. "Machine Learning Dynamic Switching Approach to Forecasting in the Presence of Structural Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(2), pages 129-157, July.
    76. Roman Frydman & Joshua R. Stillwagon, 2016. "Stock-Market Expectations: Econometric Evidence that both REH and Behavioral Insights Matter," Working Papers Series 44, Institute for New Economic Thinking.
    77. de Castro Matias, Marcos & Tabak, Benjamin Miranda, 2025. "Comparison of indicator saturation and Markov regime-switching models for Brazilian electricity prices," Energy Economics, Elsevier, vol. 144(C).
    78. Kaufmann, Robert K., 2023. "Energy price volatility affects decisions to purchase energy using capital: Motor vehicles," Energy Economics, Elsevier, vol. 126(C).
    79. Antoni Espasa & Eva Senra, 2017. "Twenty-Two Years of Inflation Assessment and Forecasting Experience at the Bulletin of EU & US Inflation and Macroeconomic Analysis," Econometrics, MDPI, vol. 5(4), pages 1-28, October.
    80. Ericsson Neil R., 2016. "Testing for and estimating structural breaks and other nonlinearities in a dynamic monetary sector," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 377-398, September.

  23. Castle, Jennifer L. & Hendry, David F., 2014. "Model selection in under-specified equations facing breaks," Journal of Econometrics, Elsevier, vol. 178(P2), pages 286-293.
    See citations under working paper version above.
  24. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Ragnar Nymoen, 2014. "Misspecification Testing: Non-Invariance of Expectations Models of Inflation," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 553-574, August.
    See citations under working paper version above.
  25. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2013. "Model Selection in Equations with Many ‘Small’ Effects," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(1), pages 6-22, February.
    See citations under working paper version above.
  26. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, vol. 177(2), pages 305-319.

    Cited by:

    1. Pinto, Jeronymo Marcondes & Marçal, Emerson Fernandes, 2019. "Cross-validation based forecasting method: a machine learning approach," Textos para discussão 498, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    2. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
    3. Thiago Carlomagno Carlo & Emerson Fernandes Marçal, 2016. "Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon," Applied Economics, Taylor & Francis Journals, vol. 48(50), pages 4846-4860, October.
    4. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    5. Neil R. Ericsson, 2016. "Economic Forecasting in Theory and Practice : An Interview with David F. Hendry," International Finance Discussion Papers 1184, Board of Governors of the Federal Reserve System (U.S.).
    6. Neil R. Ericsson & Mohammed H. I. Dore & Hassan Butt, 2022. "Detecting and Quantifying Structural Breaks in Climate," Econometrics, MDPI, vol. 10(4), pages 1-27, November.
    7. Domenic Franjic & Karsten Schweikert, 2025. "Predictor Preselection for Mixed‐Frequency Dynamic Factor Models: A Simulation Study With an Empirical Application to GDP Nowcasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 255-269, March.
    8. Emmanuel Flachaire & Sullivan Hué & Sébastien Laurent & Gilles Hacheme, 2024. "Interpretable Machine Learning Using Partial Linear Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 519-540, June.
    9. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," Working Papers 2017-001, The George Washington University, The Center for Economic Research.
    10. Sullivan Hué, 2022. "GAM(L)A: An econometric model for interpretable machine learning," French Stata Users' Group Meetings 2022 19, Stata Users Group.
    11. Michael S. Lee-Browne, 2019. "Estimating monetary policy rules in small open economies," Working Papers 2019-002, The George Washington University, The Center for Economic Research.
    12. Valentina Corradi & Norman Swanson, 2013. "Testing for Structural Stability of Factor Augmented Forecasting Models," Departmental Working Papers 201314, Rutgers University, Department of Economics.
    13. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    14. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
    15. Andrew B. Martinez & Neil R. Ericsson, 2025. "Improving empirical models and forecasts with saturation-based machine learning," Annals of Operations Research, Springer, vol. 346(1), pages 447-487, March.
    16. Clements, Michael P., 2016. "Real-time factor model forecasting and the effects of instability," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 661-675.
    17. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    18. Jack Fosten, 2016. "Forecast evaluation with factor-augmented models," University of East Anglia School of Economics Working Paper Series 2016-05, School of Economics, University of East Anglia, Norwich, UK..
    19. Yuxuan Huang, 2016. "Forecasting the USD/CNY Exchange Rate under Different Policy Regimes," Working Papers 2016-001, The George Washington University, The Center for Economic Research.
    20. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2021. "Modelling non-stationary ‘Big Data’," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1556-1575.
    21. Jennifer Castle & David Hendry & Michael P. Clements, 2014. "Robust Approaches to Forecasting," Economics Series Working Papers 697, University of Oxford, Department of Economics.
    22. Emmanuel Flachaire & Gilles Hacheme & Sullivan Hu'e & S'ebastien Laurent, 2022. "GAM(L)A: An econometric model for interpretable Machine Learning," Papers 2203.11691, arXiv.org.
    23. Dellas, Harris & Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2018. "The macroeconomic and fiscal implications of inflation forecast errors," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 203-217.
    24. Anh Dinh Minh Nguyen, 2017. "U.K. Monetary Policy under Inflation Targeting," Bank of Lithuania Working Paper Series 41, Bank of Lithuania.
    25. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    26. Hasnain Iftikhar & Faridoon Khan & Paulo Canas Rodrigues & Abdulmajeed Atiah Alharbi & Jeza Allohibi, 2025. "Forecasting of Inflation Based on Univariate and Multivariate Time Series Models: An Empirical Application," Mathematics, MDPI, vol. 13(7), pages 1-18, March.
    27. Jack Fosten, 2016. "Model selection with factors and variables," University of East Anglia School of Economics Working Paper Series 2016-07, School of Economics, University of East Anglia, Norwich, UK..
    28. Kitlinski, Tobias, 2015. "With or without you: Do financial data help to forecast industrial production?," Ruhr Economic Papers 558, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

  27. Jennifer L. Castle & Xiaochuan Qin & W. Robert Reed, 2013. "Using Model Selection Algorithms To Obtain Reliable Coefficient Estimates," Journal of Economic Surveys, Wiley Blackwell, vol. 27(2), pages 269-296, April.
    See citations under working paper version above.
  28. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2012. "Model selection when there are multiple breaks," Journal of Econometrics, Elsevier, vol. 169(2), pages 239-246.
    See citations under working paper version above.
  29. Castle Jennifer L. & Doornik Jurgen A & Hendry David F., 2011. "Evaluating Automatic Model Selection," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-33, February.
    See citations under working paper version above.
  30. Castle, Jennifer L. & Fawcett, Nicholas W.P. & Hendry, David F., 2010. "Forecasting with equilibrium-correction models during structural breaks," Journal of Econometrics, Elsevier, vol. 158(1), pages 25-36, September.
    See citations under working paper version above.
  31. Castle, Jennifer L. & Hendry, David F., 2010. "A low-dimension portmanteau test for non-linearity," Journal of Econometrics, Elsevier, vol. 158(2), pages 231-245, October.
    See citations under working paper version above.
  32. Jennifer L. Castle & David F. Hendry, 2010. "Nowcasting from disaggregates in the face of location shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 200-214.

    Cited by:

    1. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
    2. Neil R. Ericsson & Erica L. Reisman, 2012. "Evaluating a Global Vector Autoregression for Forecasting," Working Papers 2012-006, The George Washington University, The Center for Economic Research.
    3. Ralf Brüggemann & Helmut Lütkepohl, 2011. "Forecasting Contemporaneous Aggregates with Stochastic Aggregation Weights," Working Paper Series of the Department of Economics, University of Konstanz 2011-23, Department of Economics, University of Konstanz.
    4. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
    5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Carlomagno Real, Guillermo & Espasa, Antoni, 2017. "Discovering pervasive and non-pervasive common cycles," DES - Working Papers. Statistics and Econometrics. WS 25392, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Alina Stundziene & Vaida Pilinkiene & Jurgita Bruneckiene & Andrius Grybauskas & Mantas Lukauskas & Irena Pekarskiene, 2024. "Future directions in nowcasting economic activity: A systematic literature review," Journal of Economic Surveys, Wiley Blackwell, vol. 38(4), pages 1199-1233, September.
    8. William D. Larson & Tara M. Sinclair, 2020. "Nowcasting Unemployment Insurance Claims in the Time of COVID-19," Working Papers 2020-004, The George Washington University, The Center for Economic Research, revised Aug 2020.
    9. Guillermo Carlomagno & Antoni Espasa, 2021. "Discovering Specific Common Trends in a Large Set of Disaggregates: Statistical Procedures, their Properties and an Empirical Application," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 641-662, June.
    10. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    11. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    12. Pablo Duarte & Bernd Süssmuth, 2014. "Robust Implementation of a Parsimonious Dynamic Factor Model to Nowcast GDP," CESifo Working Paper Series 4574, CESifo.
    13. Carlomagno, Guillermo & Espasa, Antoni, 2015. "Forecasting a large set of disaggregates with common trends and outliers," DES - Working Papers. Statistics and Econometrics. WS ws1518, Universidad Carlos III de Madrid. Departamento de Estadística.
    14. David Hendry & Michael P. Clements, 2010. "Forecasting from Mis-specified Models in the Presence of Unanticipated Location Shifts," Economics Series Working Papers 484, University of Oxford, Department of Economics.
    15. Cai, Charlie X. & Kyaw, Khine & Zhang, Qi, 2012. "Stock index return forecasting: The information of the constituents," Economics Letters, Elsevier, vol. 116(1), pages 72-74.
    16. Carlomagno, Guillermo & Espasa, Antoni, 2016. "Discovering common trends in a large set of disaggregates: statistical procedures and their properties," DES - Working Papers. Statistics and Econometrics. WS ws1519, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Roberto Cerina & Raymond Duch, 2021. "Polling India via regression and post-stratification of non-probability online samples," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-34, November.
    18. William Larson, 2015. "Forecasting an Aggregate in the Presence of Structural Breaks in the Disaggregates," Working Papers 2015-002, The George Washington University, The Center for Economic Research.

  33. Castle, Jennifer L. & Fawcett, Nicholas W.P. & Hendry, David F., 2009. "Nowcasting is not Just Contemporaneous Forecasting," National Institute Economic Review, National Institute of Economic and Social Research, vol. 210, pages 71-89, October.

    Cited by:

    1. POPESCU Mioara, 2015. "Construction Of Economic Indicators Using Internet Searches," Annals of Spiru Haret University, Economic Series, Universitatea Spiru Haret, vol. 6(1), pages 25-31.
    2. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
    3. Neil R. Ericsson & Erica L. Reisman, 2012. "Evaluating a Global Vector Autoregression for Forecasting," Working Papers 2012-006, The George Washington University, The Center for Economic Research.
    4. Giacomo Caterini, 2018. "Classifying Firms with Text Mining," DEM Working Papers 2018/09, Department of Economics and Management.
    5. Chauvet, Marcelle & Gabriel, Stuart & Lutz, Chandler, 2016. "Mortgage default risk: New evidence from internet search queries," Journal of Urban Economics, Elsevier, vol. 96(C), pages 91-111.
    6. David F. Hendry, 2011. "Empirical Economic Model Discovery and Theory Evaluation," Rationality, Markets and Morals, Frankfurt School Verlag, Frankfurt School of Finance & Management, vol. 2(46), October.
    7. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
    8. Duarte, Pablo & Süßmuth, Bernd, 2018. "Implementing an approximate dynamic factor model to nowcast GDP using sensitivity analysis," Working Papers 152, University of Leipzig, Faculty of Economics and Management Science.
    9. Damien Challet & Ahmed Bel Hadj Ayed, 2015. "Do Google Trend data contain more predictability than price returns?," Post-Print hal-00960875, HAL.
    10. Maaß, Christina Heike, 2021. "Nowcast als Forecast: Neue Verfahren der BIP-Prognose in Echtzeit," Edition HWWI: Chapters, in: Straubhaar, Thomas (ed.), Neuvermessung der Datenökonomie, volume 6, pages 101-127, Hamburg Institute of International Economics (HWWI).
    11. Peter A.G. van Bergeijk, 2021. "Pandemic Economics," Books, Edward Elgar Publishing, number 20401, June.
    12. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
    13. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    14. David Hendry, 2016. "Deciding Between Alternative Approaches In Macroeconomics," Economics Series Working Papers 778, University of Oxford, Department of Economics.
    15. Grzegorz Michal Bulczak, 2021. "Use of Google Trends to Predict the Real Estate Market: Evidence from the United Kingdom," International Real Estate Review, Global Social Science Institute, vol. 24(4), pages 613-631.
    16. Amstad, Marlene & Fischer, Andreas M., 2010. "Monthly pass-through ratios," Journal of Economic Dynamics and Control, Elsevier, vol. 34(7), pages 1202-1213, July.
    17. Pablo Duarte & Bernd Süssmuth, 2014. "Robust Implementation of a Parsimonious Dynamic Factor Model to Nowcast GDP," CESifo Working Paper Series 4574, CESifo.
    18. Jennifer L. Castle & David F. Hendry, 2010. "Nowcasting from disaggregates in the face of location shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 200-214.
    19. Han Liu & Yongjing Wang & Haiyan Song & Ying Liu, 2023. "Measuring tourism demand nowcasting performance using a monotonicity test," Tourism Economics, , vol. 29(5), pages 1302-1327, August.
    20. Popescu Mioara, 2017. "Modelling prediction of unemployment statistics using web technologies," HOLISTICA – Journal of Business and Public Administration, Sciendo, vol. 8(3), pages 55-60, December.
    21. Christopher Adam & David Cobham, 2009. "Using Real-Time Output Gaps To Examine Past And Future Policy Choices," National Institute Economic Review, National Institute of Economic and Social Research, vol. 210(1), pages 98-110, October.
    22. Anh Dinh Minh Nguyen, 2017. "U.K. Monetary Policy under Inflation Targeting," Bank of Lithuania Working Paper Series 41, Bank of Lithuania.
    23. Livio Fenga, 2020. "Filtering and prediction of noisy and unstable signals: The case of Google Trends data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 281-295, March.
    24. Ene Andreea Bianca, 2018. "Distance Education in Romanian Higher Education," HOLISTICA – Journal of Business and Public Administration, Sciendo, vol. 9(1), pages 65-70, May.
    25. Boone, Tonya & Ganeshan, Ram & Jain, Aditya & Sanders, Nada R., 2019. "Forecasting sales in the supply chain: Consumer analytics in the big data era," International Journal of Forecasting, Elsevier, vol. 35(1), pages 170-180.
    26. Andrea Monaco & Adamaria Perrotta & Joseph Mulligan, 2024. "Selecting sensitive web info via conditional probabilities to model economics and financial variables," Empirical Economics, Springer, vol. 66(1), pages 467-481, January.
    27. Sayag, Doron & Ben-hur, Dano & Pfeffermann, Danny, 2022. "Reducing revisions in hedonic house price indices by the use of nowcasts," International Journal of Forecasting, Elsevier, vol. 38(1), pages 253-266.
    28. Boriss Siliverstovs, 2017. "Short-term forecasting with mixed-frequency data: a MIDASSO approach," Applied Economics, Taylor & Francis Journals, vol. 49(13), pages 1326-1343, March.
    29. David Hendry & Michael P. Clements, 2010. "Forecasting from Mis-specified Models in the Presence of Unanticipated Location Shifts," Economics Series Working Papers 484, University of Oxford, Department of Economics.
    30. Ulrich Gunter & Irem Önder & Stefan Gindl, 2019. "Exploring the predictive ability of LIKES of posts on the Facebook pages of four major city DMOs in Austria," Tourism Economics, , vol. 25(3), pages 375-401, May.
    31. William Larson, 2015. "Forecasting an Aggregate in the Presence of Structural Breaks in the Disaggregates," Working Papers 2015-002, The George Washington University, The Center for Economic Research.

  34. Castle, Jennifer L. & Hendry, David F., 2009. "The long-run determinants of UK wages, 1860-2004," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 5-28, March.
    See citations under working paper version above.
  35. Jennifer L. Castle, 2005. "Evaluating PcGets and RETINA as Automatic Model Selection Algorithms," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 837-880, December.

    Cited by:

    1. Amélie Charles & Olivier Darné, 2022. "Backcasting world trade growth using data reduction methods," The World Economy, Wiley Blackwell, vol. 45(10), pages 3169-3191, October.
    2. Camila Epprecht & Dominique Guegan & Álvaro Veiga, 2013. "Comparing variable selection techniques for linear regression: LASSO and Autometrics," Documents de travail du Centre d'Economie de la Sorbonne 13080, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    3. David F. Hendry & Hans-Martin Krolzig, 2004. "We Ran One Regression," Economics Papers 2004-W17, Economics Group, Nuffield College, University of Oxford.
    4. Amélie Charles & Olivier Darné, 2022. "Backcasting world trade growth using data reduction methods," Post-Print hal-04027843, HAL.
    5. Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting the French index of industrial production: A comparison from bridge and factor models," Economic Modelling, Elsevier, vol. 29(6), pages 2174-2182.
    6. Pamfili Antipa & Karim Barhoumi & Véronique Brunhes-Lesage & Olivier Darn, 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Working papers 401, Banque de France.
    7. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.
    8. Olivier Darné & Amelie Charles, 2020. "Nowcasting GDP growth using data reduction methods: Evidence for the French economy," Post-Print hal-02948802, HAL.
    9. Camila Epprecht & Dominique Guegan & Álvaro Veiga & Joel Correa da Rosa, 2017. "Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00917797, HAL.
    10. Jennifer Castle & David Hendry, 2010. "Automatic Selection for Non-linear Models," Economics Series Working Papers 473, University of Oxford, Department of Economics.
    11. Karim Barhoumi & V ronique Brunhes-Lesage & Olivier Darn & Laurent Ferrara & Bertrand Pluyaud & Rouvreau, B., 2008. "Monthly forecasting of French GDP: A revised version of the OPTIM model," Working papers 222, Banque de France.
    12. Olivier Darn & V ronique Brunhes-Lesage, 2007. "L Indicateur Synth tique Mensuel d Activit (ISMA) : une r vision," Working papers 171, Banque de France.
    13. Santos, Carlos, 2008. "Impulse saturation break tests," Economics Letters, Elsevier, vol. 98(2), pages 136-143, February.
    14. Golinelli, Roberto & Parigi, Giuseppe, 2008. "Real-time squared: A real-time data set for real-time GDP forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 368-385.

Chapters

  1. Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2022. "Smooth Robust Multi-Horizon Forecasts," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling, volume 43, pages 143-165, Emerald Group Publishing Limited.
    See citations under working paper version above.Sorry, no citations of chapters recorded.

Books

  1. Castle, Jennifer & Shephard, Neil (ed.), 2009. "The Methodology and Practice of Econometrics: A Festschrift in Honour of David F. Hendry," OUP Catalogue, Oxford University Press, number 9780199237197.

    Cited by:

    1. Yukai Yang & Luc Bauwens, 2018. "State-Space Models on the Stiefel Manifold with a New Approach to Nonlinear Filtering," Econometrics, MDPI, vol. 6(4), pages 1-22, December.
    2. Hecq, Alain & Jacobs, Jan P.A.M. & Stamatogiannis, Michalis P., 2019. "Testing for news and noise in non-stationary time series subject to multiple historical revisions," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 396-407.
    3. Carlomagno, Guillermo & Espasa, Antoni, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Josh Ryan-Collins, 2015. "Is Monetary Financing Inflationary? A Case Study of the Canadian Economy, 1935-75," Economics Working Paper Archive wp_848, Levy Economics Institute.
    5. Laurent Callot & Johannes Tang Kristensen, 2015. "Regularized Estimation of Structural Instability in Factor Models: The US Macroeconomy and the Great Moderation," CREATES Research Papers 2015-29, Department of Economics and Business Economics, Aarhus University.
    6. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    7. Jennifer Castle & Takamitsu Kurita, 2019. "Modelling and forecasting the dollar-pound exchange rate in the presence of structural breaks," Economics Series Working Papers 866, University of Oxford, Department of Economics.
    8. Anders Bredahl Kock & Timo Teräsvirta, 2011. "Forecasting performance of three automated modelling techniques during the economic crisis 2007-2009," CREATES Research Papers 2011-28, Department of Economics and Business Economics, Aarhus University.
    9. Morana, Claudio, 2019. "Regularized semiparametric estimation of high dimensional dynamic conditional covariance matrices," Econometrics and Statistics, Elsevier, vol. 12(C), pages 42-65.
    10. Baiardi, Donatella & Morana, Claudio, 2021. "Climate change awareness: Empirical evidence for the European Union," Energy Economics, Elsevier, vol. 96(C).
    11. Hartigan, Luke & Morley, James, 2019. "A Factor Model Analysis of the Australian Economy and the Effects of Inflation Targeting," Working Papers 2019-10, University of Sydney, School of Economics, revised Nov 2019.
    12. Marczak, Martyna & Proietti, Tommaso, 2015. "Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113137, Verein für Socialpolitik / German Economic Association.
    13. Adam Gersl & Petr Jakubik & Tomas Konecny & Jakub Seidler, 2013. "Dynamic Stress Testing: The Framework for Assessing the Resilience of the Banking Sector Used by the Czech National Bank," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(6), pages 505-536, December.
    14. Marcin Błażejowski & Paweł Kufel & Jacek Kwiatkowski, 2020. "Model simplification and variable selection: A replication of the UK inflation model by Hendry (2001)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 645-652, August.
    15. Vanessa Berenguer-Rico & Søren Johansen & Bent Nielsen, 2019. "The analysis of marked and weighted empirical processes of estimated residuals," CREATES Research Papers 2019-06, Department of Economics and Business Economics, Aarhus University.
    16. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
    17. Cunha, Ronan & Pereira, Pedro L. Valls, 2015. "Automatic model selection for forecasting Brazilian stock returns," Textos para discussão 398, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    18. Hildegart Ahumada & Magdalena Cornejo, 2015. "Explaining commodity prices by a cointegrated time series-cross section model," Empirical Economics, Springer, vol. 48(4), pages 1667-1690, June.
    19. Bystrov, Victor & di Salvatore, Antonietta, 2012. "Martingale approximation for common factor representation," MPRA Paper 37669, University Library of Munich, Germany.
    20. Søren Johansen & Bent Nielsen, 2014. "Outlier detection algorithms for least squares time series regression," CREATES Research Papers 2014-39, Department of Economics and Business Economics, Aarhus University.
    21. Aslanidis, Nektarios & Hartigan, Luke, 2016. "Is the Assumption of Linearity in Factor Models too Strong in Practice?," Working Papers 2072/261531, Universitat Rovira i Virgili, Department of Economics.
    22. Durevall, Dick & Loening, Josef L. & Birru, Yohannes A., 2010. "Inflation Dynamics and Food Prices in Ethiopia," Working Papers in Economics 478, University of Gothenburg, Department of Economics, revised 03 Jun 2013.
    23. Janine Aron & John Muellbauer & Rachel Sebudde, 2015. "Inflation forecasting models for Uganda: is mobile money relevant?," CSAE Working Paper Series 2015-17, Centre for the Study of African Economies, University of Oxford.
    24. Hoerova, Marie & Bekaert, Geert, 2014. "The VIX, the variance premium and stock market volatility," Working Paper Series 1675, European Central Bank.
    25. Lukasz Gatarek & Søren Johansen, 2014. "Optimal hedging with the cointegrated vector autoregressive model," Discussion Papers 14-22, University of Copenhagen. Department of Economics.
    26. Frydman, Roman & Stillwagon, Joshua R., 2018. "Fundamental factors and extrapolation in stock-market expectations: The central role of structural change," Journal of Economic Behavior & Organization, Elsevier, vol. 148(C), pages 189-198.
    27. James Reade & Genaro Sucarrat, 2016. "General-to-Specific (GETS) Modelling And Indicator Saturation With The R Package Gets," Economics Series Working Papers 794, University of Oxford, Department of Economics.
    28. Stillwagon, Josh R., 2016. "Non-linear exchange rate relationships: An automated model selection approach with indicator saturation," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 84-109.
    29. Johannes Tang Kristensen, 2012. "Factor-Based Forecasting in the Presence of Outliers: Are Factors Better Selected and Estimated by the Median than by The Mean?," CREATES Research Papers 2012-28, Department of Economics and Business Economics, Aarhus University.
    30. Kornstad, Tom & Nymoen, Ragnar & Skjerpen, Terje, 2013. "Macroeconomic shocks and the probability of being employed," Economic Modelling, Elsevier, vol. 33(C), pages 572-587.
    31. Josh R. Stillwagon, 2015. "TIPS and the VIX: Non-linear Spillovers from Financial Panic to Breakeven Inflation," Working Papers 1502, Trinity College, Department of Economics.
    32. Andrew B. Martinez & Neil R. Ericsson, 2025. "Improving empirical models and forecasts with saturation-based machine learning," Annals of Operations Research, Springer, vol. 346(1), pages 447-487, March.
    33. Søren Johansen & Bent Nielsen, 2011. "Asymptotic theory for iterated one-step Huber-skip estimators," CREATES Research Papers 2011-40, Department of Economics and Business Economics, Aarhus University.
    34. Bennedsen, Mikkel & Hillebrand, Eric & Koopman, Siem Jan, 2021. "Modeling, forecasting, and nowcasting U.S. CO2 emissions using many macroeconomic predictors," Energy Economics, Elsevier, vol. 96(C).
    35. Marçal, Emerson Fernandes & Zimmermann, Beatrice Aline & Mendonça, Diogo de Prince & Merlin, Giovanni Tondin, 2015. "Assessing interdependence among countries' fundamentals and its implications for exchange rate misalignment estimates: An empirical exercise based on GVAR," Textos para discussão 384, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    36. Jan Morten Dyrstad, 2015. "Resource curse avoidance: Governmental intervention and wage formation in the Norwegian petroleum sector," Working Paper Series 16715, Department of Economics, Norwegian University of Science and Technology.
    37. Olivier Darné & Amelie Charles, 2020. "Nowcasting GDP growth using data reduction methods: Evidence for the French economy," Post-Print hal-02948802, HAL.
    38. Alvaro Escribano & Genaro Sucarrat, 2011. "Automated model selection in finance: General-to-speci c modelling of the mean and volatility speci cations," Working Papers 2011-09, Instituto Madrileño de Estudios Avanzados (IMDEA) Ciencias Sociales.
    39. Dellaportas, Petros & Tsionas, Mike G., 2019. "Importance sampling from posterior distributions using copula-like approximations," Journal of Econometrics, Elsevier, vol. 210(1), pages 45-57.
    40. Jurgen A. Doornik & Jennifer L. Castle & David F. Hendry, 2021. "Modeling and forecasting the COVID‐19 pandemic time‐series data," Social Science Quarterly, Southwestern Social Science Association, vol. 102(5), pages 2070-2087, September.
    41. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2020. "Short-term forecasting of the Coronavirus Pandemic - 2020-04-27," Economics Papers 2020-W06, Economics Group, Nuffield College, University of Oxford.
    42. Bates, Brandon J. & Plagborg-Møller, Mikkel & Stock, James H. & Watson, Mark W., 2013. "Consistent factor estimation in dynamic factor models with structural instability," Journal of Econometrics, Elsevier, vol. 177(2), pages 289-304.
    43. Pavel Řežábek, 2015. "Poptávka po hotovosti v oběhu v České republice v období let 2002-2014 a její změny v průběhu finanční krize [Demand For Cash in Circulation in the Czech Republic In 2002-2014 and Its Changes Durin," Politická ekonomie, Prague University of Economics and Business, vol. 2015(4), pages 436-455.
    44. Noriega Antonio E. & Ramos Francia Manuel & Rodríguez-Pérez Cid Alonso, 2015. "Money Demand Estimations in Mexico and of its Stability 1986-2010, as well as Some Examples of its Uses," Working Papers 2015-13, Banco de México.
    45. Ryan-Collins, Josh & Werner, Richard A. & Castle, Jennifer, 2016. "A half-century diversion of monetary policy? An empirical horse-race to identify the UK variable most likely to deliver the desired nominal GDP growth rate," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 158-176.
    46. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damages," Working Papers 2020-003, The George Washington University, The Center for Economic Research.
    47. David Zimmer, 2015. "Asymmetric dependence in house prices: evidence from USA and international data," Empirical Economics, Springer, vol. 49(1), pages 161-183, August.
    48. Hendry David F & Mizon Grayham E, 2011. "Econometric Modelling of Time Series with Outlying Observations," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-26, February.
    49. Ramos Francia Manuel & Noriega Antonio E. & Rodríguez-Pérez Cid Alonso, 2015. "The Use of Monetary Aggregates as Indicators of the Future Evolution of Consumer Prices: Monetary Growth and Inflation Target," Working Papers 2015-14, Banco de México.
    50. Rita Duarte, 2009. "The dynamic effects of shocks to wages and prices in the United States and the Euro Area," Working Papers w200915, Banco de Portugal, Economics and Research Department.
    51. M. Mogliani & Thomas Ferrière, 2016. "Rationality of announcements, business cycle asymmetry, and predictability of revisions. The case of French GDP," Working papers 600, Banque de France.
    52. Ahumada, H. & Cornejo, M., 2016. "Forecasting food prices: The case of corn, soybeans and wheat," International Journal of Forecasting, Elsevier, vol. 32(3), pages 838-848.
    53. Michael P. Clements, 2014. "Forecast Uncertainty- Ex Ante and Ex Post : U.S. Inflation and Output Growth," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 206-216, April.
    54. Kevin S. Nell, 2018. "Conditional Divergence in the Post-1989 Globalisation Period," CEF.UP Working Papers 1806, Universidade do Porto, Faculdade de Economia do Porto.
    55. Carlomagno, Guillermo & Espasa, Antoni, 2015. "Forecasting a large set of disaggregates with common trends and outliers," DES - Working Papers. Statistics and Econometrics. WS ws1518, Universidad Carlos III de Madrid. Departamento de Estadística.
    56. Haldrup, Niels & Vera Valdés, J. Eduardo, 2017. "Long memory, fractional integration, and cross-sectional aggregation," Journal of Econometrics, Elsevier, vol. 199(1), pages 1-11.
    57. Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, The Center for Economic Research.
    58. Adam Gersl & Petr Jakubik & Tomas Konecny & Jakub Seidler, 2012. "Dynamic Stress Testing: The Framework for Testing Banking Sector Resilience Used by the Czech National Bank," Working Papers 2012/11, Czech National Bank, Research and Statistics Department.
    59. Nauro F Campos & Corrado Macchiarelli, 2020. "The United Kingdom and the stability of the Euro area: From Maastricht to Brexit," The World Economy, Wiley Blackwell, vol. 43(7), pages 1792-1808, July.
    60. Frédérique Bec & Matteo Mogliani, 2013. "Nowcasting French GDP in Real-Time from Survey Opinions : Information or Forecast Combinations ?," Working Papers 2013-21, Center for Research in Economics and Statistics.
    61. Søren Johansen & Bent Nielsen, 2013. "Asymptotic analysis of the Forward Search," CREATES Research Papers 2013-05, Department of Economics and Business Economics, Aarhus University.
    62. Ahumada, Hildegart & Cavallo, Eduardo A. & Espina-Mairal, Santos & Navajas, Fernando, 2021. "Sectoral Productivity Growth, COVID-19 Shocks, and Infrastructure," IDB Publications (Working Papers) 11404, Inter-American Development Bank.
    63. Riccardo Borghi & Eric Hillebrand & Jakob Mikkelsen & Giovanni Urga, 2018. "The dynamics of factor loadings in the cross-section of returns," CREATES Research Papers 2018-38, Department of Economics and Business Economics, Aarhus University.
    64. Lu, Xun & White, Halbert, 2014. "Robustness checks and robustness tests in applied economics," Journal of Econometrics, Elsevier, vol. 178(P1), pages 194-206.
    65. David H. Bernstein & Andrew B. Martinez, 2021. "Jointly Modeling Male and Female Labor Participation and Unemployment," Working Papers 2021-006, The George Washington University, The Center for Economic Research.
    66. Papailias, Fotis & Fruet Dias, Gustavo, 2015. "Forecasting long memory series subject to structural change: A two-stage approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1056-1066.
    67. Luke P. Jackson & Katarina Juselius & Andrew B. Martinez & Felix Pretis, 2025. "Modelling the dependence between recent changes in polar ice sheets: Implications for global sea-level projections," Working Papers 2025-002, The George Washington University, The Center for Economic Research.
    68. Luke Hartigan, 2015. "Changes in the Factor Structure of the U.S. Economy: Permanent Breaks or Business Cycle Regimes?," Discussion Papers 2015-17, School of Economics, The University of New South Wales.
    69. James Reade, 2014. "Detecting corruption in football," Chapters, in: John Goddard & Peter Sloane (ed.), Handbook on the Economics of Professional Football, chapter 25, pages 419-446, Edward Elgar Publishing.
    70. Reinhold Heinlein & Hans-Martin Krolzig, 2011. "Effects of monetary policy on the $/£ exchange rate. Is there a 'delayed overshooting puzzle'?," Studies in Economics 1124, School of Economics, University of Kent.
    71. Jin Xisong & Lehnert Thorsten, 2018. "Large portfolio risk management and optimal portfolio allocation with dynamic elliptical copulas," Dependence Modeling, De Gruyter, vol. 6(1), pages 19-46, February.
    72. David Hendry & Michael P. Clements, 2010. "Forecasting from Mis-specified Models in the Presence of Unanticipated Location Shifts," Economics Series Working Papers 484, University of Oxford, Department of Economics.
    73. Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2020. "A statistical model of the global carbon budget," CREATES Research Papers 2020-18, Department of Economics and Business Economics, Aarhus University.
    74. Roman Frydman & Joshua R. Stillwagon, 2016. "Stock-Market Expectations: Econometric Evidence that both REH and Behavioral Insights Matter," Working Papers Series 44, Institute for New Economic Thinking.
    75. Genaro Sucarrat & Alvaro Escribano, 2012. "Automated Model Selection in Finance: General-to-Specific Modelling of the Mean and Volatility Specifications," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(5), pages 716-735, October.
    76. Carlomagno, Guillermo & Espasa, Antoni, 2016. "Discovering common trends in a large set of disaggregates: statistical procedures and their properties," DES - Working Papers. Statistics and Econometrics. WS ws1519, Universidad Carlos III de Madrid. Departamento de Estadística.
    77. Jinan Liu & Apostolos Serletis, 2022. "World Commodity Prices and Economic Activity in Advanced and Emerging Economies," Open Economies Review, Springer, vol. 33(2), pages 347-374, April.
    78. John Goddard & Peter Sloane (ed.), 2014. "Handbook on the Economics of Professional Football," Books, Edward Elgar Publishing, number 14821, June.
    79. Konstantin Belyaev & Aelita Belyaeva & Tomas Konecny & Jakub Seidler & Martin Vojtek, 2012. "Macroeconomic Factors as Drivers of LGD Prediction: Empirical Evidence from the Czech Republic," Working Papers 2012/12, Czech National Bank, Research and Statistics Department.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.