International Journal of Forecasting
1985 - 2025
Current editor(s): R. J. Hyndman From Elsevier Bibliographic data for series maintained by Catherine Liu (). Access Statistics for this journal.
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Volume 41, issue 2, 2025
- Introduction to the Special Issue on Judgment in Forecasting pp. 419-423

- Robert Fildes, Fergus Bolger, Paul Goodwin, Nigel Harvey and Matthias Seifert
- An overview of the effects of algorithm use on judgmental biases affecting forecasting pp. 424-439

- Alvaro Chacon and Esther Kaufmann
- Light-touch forecasting: A novel method to combine human judgment with statistical algorithms pp. 440-451

- B.B.J.P.J. van der Staak, R.J.I. Basten, P.P.F.M. van de Calseyde, E. Demerouti and A.G. de Kok
- Investigating laypeople’s short- and long-term forecasts of COVID-19 infection cycles pp. 452-465

- Moon Su Koo, Yun Shin Lee and Matthias Seifert
- An extended logarithmic visualization improves forecasting accuracy for exponentially growing numbers, but residual difficulties remain pp. 466-474

- Ben H. Engler, Florian Hutzler and Stefan Hawelka
- Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence pp. 475-486

- Michael Pedersen
- How does training improve individual forecasts? Modeling differences in compensatory and non-compensatory biases in geopolitical forecasts pp. 487-498

- Vahid Karimi Motahhar and Thomas S. Gruca
- Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament pp. 499-516

- Ezra Karger, Josh Rosenberg, Zachary Jacobs, Molly Hickman and Phillip E. Tetlock
- Cognitive reflection, arithmetic ability and financial literacy independently predict both inflation expectations and forecast accuracy pp. 517-531

- David A. Comerford
- Factors affecting preferences between judgmental and algorithmic forecasts: Feedback, guidance and labeling effects pp. 532-553

- Nigel Harvey and Shari De Baets
- Service-level anchoring in demand forecasting: The moderating impact of retail promotions and product perishability pp. 554-570

- Ben Fahimnia, Tarkan Tan and Nail Tahirov
- Emotions and the status quo: The anti-incumbency bias in political prediction markets pp. 571-579

- Vahid Karimi Motahhar, Thomas S. Gruca and Mohammad Hosein Tavakoli
- Crowd prediction systems: Markets, polls, and elite forecasters pp. 580-595

- Pavel Atanasov, Jens Witkowski, Barbara Mellers and Philip Tetlock
- Measuring probabilistic coherence to identify superior forecasters pp. 596-612

- Emily H. Ho, David V. Budescu and Mark Himmelstein
- Robust recalibration of aggregate probability forecasts using meta-beliefs pp. 613-630

- Cem Peker and Tom Wilkening
- Humans vs. large language models: Judgmental forecasting in an era of advanced AI pp. 631-648

- Mahdi Abolghasemi, Odkhishig Ganbold and Kristian Rotaru
- Forecast value added in demand planning pp. 649-669

- Robert Fildes, Paul Goodwin and Shari De Baets
- Efficiency of poll-based multi-period forecasting systems for German state elections pp. 670-688

- Markus Fritsch, Harry Haupt and Joachim Schnurbus
- Improving out-of-population prediction: The complementary effects of model assistance and judgmental bootstrapping pp. 689-701

- Mathew D. Hardy, Sam Zhang, Jessica Hullman, Jake M. Hofman and Daniel Goldstein
- Partisan bias, attribute substitution, and the benefits of an indirect format for eliciting forecasts and judgments of trend pp. 702-715

- David A. Comerford and Jack B. Soll
- Guiding supervisors in artificial intelligence-enabled forecasting: Understanding the impacts of salience and detail on decision-making pp. 716-732

- Naghmeh Khosrowabadi, Kai Hoberg and Yun Shin Lee
- Adaptively aggregated forecast for exponential family panel model pp. 733-747

- Dalei Yu, Nian-Sheng Tang and Yang Shi
- Does economic uncertainty predict real activity in real time? pp. 748-762

- Bart Keijsers and Dick van Dijk
- Skew–Brownian processes for estimating the volatility of crude oil Brent pp. 763-780

- Michele Bufalo, Brunero Liseo and Giuseppe Orlando
- Sensitivity and uncertainty in the Lee–Carter mortality model pp. 781-797

- Wenyun Zuo, Anil Damle and Shripad Tuljapurkar
- Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks pp. 798-802

- Lawrence Clegg and John Cartlidge
- Forecasting soccer matches with betting odds: A tale of two markets pp. 803-820

- Tadgh Hegarty and Karl Whelan
- A framework for timely and accessible long-term forecasting of shale gas production based on time series pattern matching pp. 821-843

- Yilun Dong, Youzhi Hao and Detang Lu
- On memory-augmented gated recurrent unit network pp. 844-858

- Maolin Yang, Muyi Li and Guodong Li
Volume 41, issue 1, 2025
- Guest editorial: Forecasting for social good pp. 1-2

- Bahman Rostami-Tabar, Pierre Pinson and Michael D. Porter
- Machine learning for satisficing operational decision making: A case study in blood supply chain pp. 3-19

- Mahdi Abolghasemi, Babak Abbasi and Zahra HosseiniFard
- Nowcasting U.S. state-level CO2 emissions and energy consumption pp. 20-30

- Jack Fosten and Shaoni Nandi
- Predicting and optimizing the fair allocation of donations in hunger relief supply chains pp. 31-50

- Nowshin Sharmile, Isaac A. Nuamah, Lauren Davis, Funda Samanlioglu, Steven Jiang and Carter Crain
- Forecasting mail flow: A hierarchical approach for enhanced societal wellbeing pp. 51-65

- Nadine Kafa, M. Zied Babai and Walid Klibi
- Forecasting presidential elections: Accuracy of ANES voter intentions pp. 66-75

- Hyein Ko, Natalie Jackson, Tracy Osborn and Michael S. Lewis-Beck
- Forecasting adversarial actions using judgment decomposition-recomposition pp. 76-91

- Yolanda Gomez, Jesus Rios, David Rios Insua and Jose Vila
- Return predictability, dividend growth, and the persistence of the price–dividend ratio pp. 92-110

- Adam Goliński, Joao Madeira and Dooruj Rambaccussing
- Local and global trend Bayesian exponential smoothing models pp. 111-127

- Slawek Smyl, Christoph Bergmeir, Alexander Dokumentov, Xueying Long, Erwin Wibowo and Daniel Schmidt
- Coupling LSTM neural networks and state-space models through analytically tractable inference pp. 128-140

- Van-Dai Vuong, Luong-Ha Nguyen and James-A. Goulet
- Do oil price forecast disagreement of survey of professional forecasters predict crude oil return volatility? pp. 141-152

- Anton Hasselgren, Ai Jun Hou, Sandy Suardi, Caihong Xu and Xiaoxia Ye
- Forecasting interest rates with shifting endpoints: The role of the functional demographic age distribution pp. 153-174

- Jiazi Chen, Zhiwu Hong and Linlin Niu
- The time-varying Multivariate Autoregressive Index model pp. 175-190

- Gianluca Cubadda, Stefano Grassi and Barbara Guardabascio
- Boosting domain-specific models with shrinkage: An application in mortality forecasting pp. 191-207

- Li Li, Han Li and Anastasios Panagiotelis
- Predicting the equity premium around the globe: Comprehensive evidence from a large sample pp. 208-228

- Fabian Hollstein, Marcel Prokopczuk, Björn Tharann and Chardin Wese Simen
- Asymmetric uncertainty: Nowcasting using skewness in real-time data pp. 229-250

- Paul Labonne
- Dynamic time series modelling and forecasting of COVID-19 in Norway pp. 251-269

- Gunnar Bårdsen and Ragnar Nymoen
- ABC-based forecasting in misspecified state space models pp. 270-289

- Chaya Weerasinghe, Rubén Loaiza-Maya, Gael M. Martin and David T. Frazier
- Multi-view locally weighted regression for loss given default forecasting pp. 290-306

- Hui Cheng, Cuiqing Jiang, Zhao Wang and Xiaoya Ni
- Forecasting macroeconomic tail risk in real time: Do textual data add value? pp. 307-320

- Philipp Adämmer, Jan Prüser and Rainer A. Schüssler
- Cross-temporal forecast reconciliation at digital platforms with machine learning pp. 321-344

- Jeroen Rombouts, Marie Ternes and Ines Wilms
- A modified VAR-deGARCH model for asynchronous multivariate financial time series via variational Bayesian inference pp. 345-360

- Wei-Ting Lai, Ray-Bing Chen and Shih-Feng Huang
- Sparse time-varying parameter VECMs with an application to modeling electricity prices pp. 361-376

- Niko Hauzenberger, Michael Pfarrhofer and Luca Rossini
- Forecasting realized volatility with spillover effects: Perspectives from graph neural networks pp. 377-397

- Chao Zhang, Xingyue Pu, Mihai Cucuringu and Xiaowen Dong
- Forecasting house price growth rates with factor models and spatio-temporal clustering pp. 398-417

- Raffaele Mattera and Philip Hans Franses
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