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Andrew B. Martinez

Personal Details

First Name:Andrew
Middle Name:B.
Last Name:Martinez
Suffix:
RePEc Short-ID:pma1768
[This author has chosen not to make the email address public]
https://sites.google.com/view/andrewbmartinez/
Mastodon: @andrewbmartinez@econtwitter.net
Bluesky: @andrewbmartinez.bsky.social
Terminal Degree:2019 Department of Economics; Oxford University (from RePEc Genealogy)

Affiliation

(1%) Economic Research
Federal Reserve Bank of Cleveland

Cleveland, Ohio (United States)
https://www.clevelandfed.org/our-research/
RePEc:edi:efrbcus (more details at EDIRC)

(5%) Department of Economics
Oxford University

Oxford, United Kingdom
http://www.economics.ox.ac.uk/
RePEc:edi:sfeixuk (more details at EDIRC)

(89%) Department of the Treasury
Government of the United States

Washington, District of Columbia (United States)
http://www.treasury.gov/
RePEc:edi:tregvus (more details at EDIRC)

(5%) H.O. Stekler Research Program on Forecasting
Center for Economic Research
Department of Economics
George Washington University

Washington, District of Columbia (United States)
https://cer.columbian.gwu.edu/ho-stekler-research-program-forecasting
RePEc:edi:pfgwuus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. 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, Department of Economics, H. O. Stekler Research Program on Forecasting.
  2. Andrew B. Martinez, 2025. "How do Macroeconomic Expectations React to Extreme Weather Shocks?," Working Papers 2025-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  3. William D. Larson & Andrew B. Martinez, 2024. "House Prices, Debt Burdens, and the Heterogeneous Effects of Mortgage Rate Shocks," Working Papers 2024-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  4. 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, Department of Economics, H. O. Stekler Research Program on Forecasting.
  5. David H. Bernstein & Andrew B. Martinez, 2021. "Jointly Modeling Male and Female Labor Participation and Unemployment," Working Papers 2021-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  6. Martinez, Andrew & Schibuola, Alex, 2021. "The Expectations Gap: An Alternative Measure of Economic Slack," Working Papers 11284, George Mason University, Mercatus Center.
  7. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damages," Working Papers 2020-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  8. 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. Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2020. "Smooth Robust Multi-Horizon Forecasts," Working Papers 2020-009, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  10. Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  11. Andrew Martinez, 2017. "Testing for Differences in Path Forecast Accuracy: Forecast-Error Dynamics Matter," Working Papers (Old Series) 1717, Federal Reserve Bank of Cleveland.
  12. 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.
  13. Jennifer Castle & David Hendry, 2016. "Policy Analysis, Forediction, and Forecast Failure," Economics Series Working Papers 809, University of Oxford, Department of Economics.
  14. Andrew Martinez, 2014. "How Good Are U.S. Government Forecasts of the Federal Debt?," Economics Series Working Papers 727, University of Oxford, Department of Economics.
  15. Andrew B. Martinez, 2011. "Comparing Government Forecasts of the United States’ Gross Federal Debt," Working Papers 2011-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.

Articles

  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. 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).
  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. David H. Bernstein & Andrew B. Martinez, 2021. "Jointly Modeling Male and Female Labor Participation and Unemployment," Econometrics, MDPI, vol. 9(4), pages 1-14, December.
  5. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damage," Econometrics, MDPI, vol. 8(2), pages 1-24, May.
  6. Andrew B. Martinez, 2020. "Improving normalized hurricane damages," Nature Sustainability, Nature, vol. 3(7), pages 517-518, July.
  7. 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.
  8. Hendry, David F. & Martinez, Andrew B., 2017. "Evaluating multi-step system forecasts with relatively few forecast-error observations," International Journal of Forecasting, Elsevier, vol. 33(2), pages 359-372.
  9. Martinez, Andrew B., 2015. "How good are US government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 31(2), pages 312-324.

Chapters

  1. Andrew B. Martinez & Andrew J. Wilson, 2024. "Forecasting the macroeconomic effects of physical climate risk," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 15, pages 396-424, Edward Elgar Publishing.
  2. 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.

Citations

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

Working papers

  1. William D. Larson & Andrew B. Martinez, 2024. "House Prices, Debt Burdens, and the Heterogeneous Effects of Mortgage Rate Shocks," Working Papers 2024-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.

    Cited by:

    1. Aditya Aladangady & Jacob Krimmel & Tess C. Scharlemann, 2024. "Locked In: Rate Hikes, Housing Markets, and Mobility," Finance and Economics Discussion Series 2024-088, Board of Governors of the Federal Reserve System (U.S.).

  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," Working Papers 2022-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.

    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.

  3. David H. Bernstein & Andrew B. Martinez, 2021. "Jointly Modeling Male and Female Labor Participation and Unemployment," Working Papers 2021-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.

    Cited by:

    1. Jamie Emerson, 2023. "Education, employment, and labor force participation in the United States," Economics Bulletin, AccessEcon, vol. 43(3), pages 1377-1388.
    2. 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).
    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. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damages," Working Papers 2020-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.

    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. Andrew B. Martinez, 2025. "How do Macroeconomic Expectations React to Extreme Weather Shocks?," Working Papers 2025-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    3. 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.
    4. J. James Reade & Carl Singleton & Alasdair Brown, 2019. "Evaluating Strange Forecasts: The Curious Case of Football Match Scorelines," Economics Discussion Papers em-dp2019-18, Department of Economics, University of Reading, revised 01 Aug 2020.
    5. Song, Yuqi, 2024. "The value of weather forecasts: Evidence from labor responses to accurate versus inaccurate temperature forecasts in China," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    6. Renato Molina & Ivan Rudik, 2022. "The Social Value of Predicting Hurricanes," CESifo Working Paper Series 10049, CESifo.
    7. 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).
    8. 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).
    9. Anand, Vaibhav, 2022. "The Value of Forecast Improvements: Evidence from Advisory Lead Times and Vehicle Crashes," MPRA Paper 114491, University Library of Munich, Germany.

  5. 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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Simon Hirsch & Jonathan Berrisch & Florian Ziel, 2024. "Online Distributional Regression," Papers 2407.08750, arXiv.org, revised Aug 2024.
    9. 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.
    10. Jozef Barunik & Lubos Hanus, 2023. "Learning Probability Distributions of Day-Ahead Electricity Prices," Papers 2310.02867, arXiv.org, revised Oct 2023.
    11. Xiaoqian Wang & Yanfei Kang & Rob J Hyndman & Feng Li, 2020. "Distributed ARIMA Models for Ultra-long Time Series," Monash Econometrics and Business Statistics Working Papers 29/20, Monash University, Department of Econometrics and Business Statistics.
    12. 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.
    13. 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.
    14. 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.
    15. 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).
    16. 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.
    17. 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).
    18. 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).
    19. 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.
    20. 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.
    21. 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.
    22. 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).
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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).
    32. 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.
    33. 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).
    34. 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).
    35. 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.
    36. 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).
    37. Paul Ghelasi & Florian Ziel, 2023. "Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions," Papers 2305.16255, arXiv.org.
    38. 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.
    39. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    40. 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).
    41. 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).
    42. 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).
    43. 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.
    44. Entezari, Negin & Fuinhas, José Alberto, 2024. "Measuring wholesale electricity price risk from climate change: Evidence from Portugal," Utilities Policy, Elsevier, vol. 91(C).
    45. 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).
    46. 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.
    47. Pedersen, Michael, 2025. "Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence," International Journal of Forecasting, Elsevier, vol. 41(2), pages 475-486.
    48. 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.
    49. 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.
    50. Katarzyna Maciejowska & Weronika Nitka, 2024. "Multiple split approach -- multidimensional probabilistic forecasting of electricity markets," Papers 2407.07795, arXiv.org.
    51. 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.
    52. 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).
    53. 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.
    54. 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).
    55. 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).
    56. 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).
    57. 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.
    58. Richard Bean, 2023. "Forecasting the Monash Microgrid for the IEEE-CIS Technical Challenge," Energies, MDPI, vol. 16(3), pages 1-23, January.
    59. 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.
    60. 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.
    61. 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.
    62. 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.
    63. 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.
    64. 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.
    65. 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.
    66. 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).
    67. 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.
    68. Paul Ghelasi & Florian Ziel, 2025. "A data-driven merit order: Learning a fundamental electricity price model," Papers 2501.02963, arXiv.org.
    69. Niklas Valentin Lehmann, 2023. "Forecasting skill of a crowd-prediction platform: A comparison of exchange rate forecasts," Papers 2312.09081, arXiv.org.
    70. 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.
    71. 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.
    72. 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).
    73. 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.
    74. 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.
    75. Swaminathan, Kritika & Venkitasubramony, Rakesh, 2024. "Demand forecasting for fashion products: A systematic review," International Journal of Forecasting, Elsevier, vol. 40(1), pages 247-267.
    76. 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.
    77. 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.
    78. 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.

  6. Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2020. "Smooth Robust Multi-Horizon Forecasts," Working Papers 2020-009, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.

    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. Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    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.

  7. Andrew Martinez, 2017. "Testing for Differences in Path Forecast Accuracy: Forecast-Error Dynamics Matter," Working Papers (Old Series) 1717, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Ivan Svetunkov & Nikolaos Kourentzes & Rebecca Killick, 2024. "Multi-step estimators and shrinkage effect in time series models," Computational Statistics, Springer, vol. 39(3), pages 1203-1239, May.
    2. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    3. Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.

  8. 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.

    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. Michael P. Clements, 2022. "Forecaster Efficiency, Accuracy, and Disagreement: Evidence Using Individual‐Level Survey Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(2-3), pages 537-568, March.
    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. 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.
    5. Andrew Martinez, 2017. "Testing for Differences in Path Forecast Accuracy: Forecast-Error Dynamics Matter," Working Papers (Old Series) 1717, Federal Reserve Bank of Cleveland.
    6. 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.).
    7. 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).
    8. Michael Clements, 2016. "Are Macro-Forecasters Essentially The Same? An Analysis of Disagreement, Accuracy and Efficiency," ICMA Centre Discussion Papers in Finance icma-dp2016-08, Henley Business School, University of Reading.
    9. Budnik, Katarzyna & Ponte Marques, Aurea & Giglio, Carla & Grassi, Alberto & Durrani, Agha & Figueres, Juan Manuel & Konietschke, Paul & Le Grand, Catherine & Metzler, Julian & Población García, Franc, 2024. "Advancements in stress-testing methodologies for financial stability applications," Occasional Paper Series 348, European Central Bank.
    10. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    11. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
    12. Håvard Hungnes, 2020. "Predicting the exchange rate path. The importance of using up-to-date observations in the forecasts," Discussion Papers 934, Statistics Norway, Research Department.
    13. Chevillon, Guillaume, 2017. "Robustness of Multistep Forecasts and Predictive Regressions at Intermediate and Long Horizons," ESSEC Working Papers WP1710, ESSEC Research Center, ESSEC Business School.
    14. Michael P. Clements, 2020. "Are Some Forecasters’ Probability Assessments of Macro Variables Better Than Those of Others?," Econometrics, MDPI, vol. 8(2), pages 1-16, May.
    15. Håvard Hungnes, 2018. "Encompassing tests for evaluating multi-step system forecasts invariant to linear transformations," Discussion Papers 871, Statistics Norway, Research Department.

  9. 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.

  10. Andrew Martinez, 2014. "How Good Are U.S. Government Forecasts of the Federal Debt?," Economics Series Working Papers 727, University of Oxford, Department of Economics.

    Cited by:

    1. Hendry, David F. & Martinez, Andrew B., 2017. "Evaluating multi-step system forecasts with relatively few forecast-error observations," International Journal of Forecasting, Elsevier, vol. 33(2), pages 359-372.
    2. Andrew Martinez, 2017. "Testing for Differences in Path Forecast Accuracy: Forecast-Error Dynamics Matter," Working Papers (Old Series) 1717, Federal Reserve Bank of Cleveland.
    3. Tsuchiya, Yoichi, 2016. "Directional analysis of fiscal sustainability: Revisiting Domar's debt sustainability condition," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 189-201.
    4. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," Working Papers 2017-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    5. Bachleitner, Alena & Prammer, Doris, 2024. "Don’t blame the government!? An assessment of debt forecast errors with a view to the EU Economic Governance Review," European Journal of Political Economy, Elsevier, vol. 82(C).
    6. Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    7. Arai, Natsuki & Iizuka, Nobuo & Yamamoto, Yohei, 2022. "The Efficiency of the Government’s Revenue Projections," Discussion paper series HIAS-E-122, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    8. Steinbuks, Jevgenijs, 2019. "Assessing the accuracy of electricity production forecasts in developing countries," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1175-1185.
    9. Arai, Natsuki & Iizuka, Nobuo & Yamamoto, Yohei, 2024. "The efficiency of the Japanese government’s revenue projections," Economics Letters, Elsevier, vol. 244(C).
    10. Arai, Natsuki, 2020. "Investigating the inefficiency of the CBO’s budgetary projections," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1290-1300.

  11. Andrew B. Martinez, 2011. "Comparing Government Forecasts of the United States’ Gross Federal Debt," Working Papers 2011-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.

    Cited by:

    1. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," Working Papers 2017-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    2. Martinez, Andrew B., 2015. "How good are US government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 31(2), pages 312-324.
    3. Gamber, Edward N. & Liebner, Jeffrey P., 2017. "Comment on “How Biased are US Government Forecasts of the Federal Debt?”," International Journal of Forecasting, Elsevier, vol. 33(2), pages 560-562.
    4. Arai, Natsuki, 2020. "Investigating the inefficiency of the CBO’s budgetary projections," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1290-1300.

Articles

  1. 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.

  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.
    See citations under working paper version above.
  3. David H. Bernstein & Andrew B. Martinez, 2021. "Jointly Modeling Male and Female Labor Participation and Unemployment," Econometrics, MDPI, vol. 9(4), pages 1-14, December.
    See citations under working paper version above.
  4. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damage," Econometrics, MDPI, vol. 8(2), pages 1-24, May.
    See citations under working paper version above.
  5. Andrew B. Martinez, 2020. "Improving normalized hurricane damages," Nature Sustainability, Nature, vol. 3(7), pages 517-518, July.

    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. Andrew B. Martinez, 2025. "How do Macroeconomic Expectations React to Extreme Weather Shocks?," Working Papers 2025-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    3. Pielke, Roger Jr, 2024. "Do Not Use the ICAT Hurricane Loss “Dataset”: An Opportunity for Course Correction in Climate Science," OSF Preprints x2dgy, Center for Open Science.

  6. 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. 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.
    2. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damages," Working Papers 2020-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    3. Hendry, David F., 2018. "Deciding between alternative approaches in macroeconomics," International Journal of Forecasting, Elsevier, vol. 34(1), pages 119-135.
    4. 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).
    5. 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).
    6. David F. Hendry & Felix Pretis, 2020. "Analyzing Differences between Scenarios," Economics Papers 2020-W05, Economics Group, Nuffield College, University of Oxford.
    7. 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.
    8. 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.
    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. S. Yanki Kalfa & Jaime Marquez, 2021. "Forecasting FOMC Forecasts," Econometrics, MDPI, vol. 9(3), pages 1-21, September.
      • S. Yanki Kalfa & Jaime Marquez, 2018. "Forecasting FOMC Forecasts," Working Papers 2018-007, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    11. 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.
    12. Rocco Mosconi & Paolo Paruolo, 2022. "Celebrated Econometricians: Katarina Juselius and Søren Johansen," Econometrics, MDPI, vol. 10(2), pages 1-4, May.
    13. David F. Hendry, 2020. "A Short History of Macro-econometric Modelling," Economics Papers 2020-W01, Economics Group, Nuffield College, University of Oxford.
    14. Pretis, Felix, 2021. "Exogeneity in climate econometrics," Energy Economics, Elsevier, vol. 96(C).

  7. Hendry, David F. & Martinez, Andrew B., 2017. "Evaluating multi-step system forecasts with relatively few forecast-error observations," International Journal of Forecasting, Elsevier, vol. 33(2), pages 359-372.
    See citations under working paper version above.
  8. Martinez, Andrew B., 2015. "How good are US government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 31(2), pages 312-324.
    See citations under working paper version above.

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.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 14 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-FOR: Forecasting (6) 2015-08-19 2016-04-16 2017-11-12 2021-01-18 2021-03-08 2022-03-21. Author is listed
  2. NEP-ECM: Econometrics (4) 2016-04-16 2016-11-20 2017-11-12 2021-01-18
  3. NEP-MON: Monetary Economics (3) 2020-11-16 2022-09-19 2022-11-28
  4. NEP-BIG: Big Data (2) 2020-07-20 2020-11-16
  5. NEP-ENE: Energy Economics (2) 2022-09-19 2022-11-28
  6. NEP-ENV: Environmental Economics (2) 2020-07-20 2025-02-03
  7. NEP-HIS: Business, Economic and Financial History (2) 2022-09-19 2022-11-28
  8. NEP-MAC: Macroeconomics (2) 2020-11-16 2021-12-06
  9. NEP-ORE: Operations Research (2) 2016-04-16 2021-12-06
  10. NEP-URE: Urban and Real Estate Economics (2) 2020-07-20 2024-08-26
  11. NEP-BAN: Banking (1) 2022-03-21
  12. NEP-CBA: Central Banking (1) 2024-08-26
  13. NEP-CWA: Central and Western Asia (1) 2022-03-21
  14. NEP-ETS: Econometric Time Series (1) 2021-01-18
  15. NEP-GEN: Gender (1) 2021-12-06
  16. NEP-LAB: Labour Economics (1) 2021-12-06
  17. NEP-UPT: Utility Models and Prospect Theory (1) 2022-03-21

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