International Journal of Forecasting最新文献_第10页

Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament 存在风险的主观概率预测：混合劝说-预测比赛的初步结果

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2025-04-01 Epub Date: 2025-01-17 DOI: 10.1016/j.ijforecast.2024.11.008

Ezra Karger , Josh Rosenberg , Zachary Jacobs , Molly Hickman , Phillip E. Tetlock

{"title":"Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament","authors":"Ezra Karger , Josh Rosenberg , Zachary Jacobs , Molly Hickman , Phillip E. Tetlock","doi":"10.1016/j.ijforecast.2024.11.008","DOIUrl":"10.1016/j.ijforecast.2024.11.008","url":null,"abstract":"<div><div>A multi-stage persuasion-forecasting tournament asked specialists and generalists (“superforecasters”) to explain their probability judgments of short- and long-run existential threats to humanity. Specialists were more pessimistic, especially on long-run threats posed by artificial intelligence (AI). Despite incentives to share their best arguments during four months of discussion, neither side materially moved the other’s views. This would be puzzling if participants were Bayesian agents methodically sifting through elusive clues about distant futures but it is less puzzling if participants were boundedly rational agents searching for confirmatory evidence as the risks of embarrassing accuracy feedback receded. Consistent with the latter mechanism, strong AI-risk proponents made particularly extreme long- but not short-range forecasts and over-estimated the long-range AI-risk forecasts of others. We stress the potential of these methods to inform high-stakes debates, but we acknowledge limits on what even skilled forecasters can achieve in anticipating rare or unprecedented events.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 499-516"},"PeriodicalIF":6.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A framework for timely and accessible long-term forecasting of shale gas production based on time series pattern matching 基于时间序列模式匹配的页岩气产量长期及时预测框架

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2025-04-01 Epub Date: 2024-08-24 DOI: 10.1016/j.ijforecast.2024.07.009

Yilun Dong, Youzhi Hao, Detang Lu

{"title":"A framework for timely and accessible long-term forecasting of shale gas production based on time series pattern matching","authors":"Yilun Dong, Youzhi Hao, Detang Lu","doi":"10.1016/j.ijforecast.2024.07.009","DOIUrl":"10.1016/j.ijforecast.2024.07.009","url":null,"abstract":"<div><div>Shale gas production forecasting is an important research topic in the gas industry. A common shale gas block includes dozens or even thousands of wells and therefore has a great number of historical production series. However, most existing methods apply single-well modelling. This cannot exploit data from other wells and requires a long production history from the target well, so the forecasting timeliness is compromised. Moreover, the parameters required by many of the existing methods are difficult to collect in practice, so the forecasting accessibility is compromised. Therefore, this study presents a shale gas production forecasting framework with improved timeliness and accessibility. To ensure timeliness, the proposed approach utilises historical data from existing wells and only requires a short production history from the target well. To ensure accessibility, the proposed approach only requires past daily production time and gas yield. The performance of the proposed method is demonstrated through a comparison with baseline methods. The results regarding cumulative gas production forecasting indicate that the proposed method has an average overall mean absolute percentage error (OMAPE) of 0.210, outperforming an artificial neural network with an average OMAPE of 0.241 and ARIMA with an average OMAPE of more than 2.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 821-843"},"PeriodicalIF":6.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On memory-augmented gated recurrent unit network 关于记忆增强型门控递归单元网络

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2025-04-01 Epub Date: 2024-08-31 DOI: 10.1016/j.ijforecast.2024.07.008

Maolin Yang , Muyi Li , Guodong Li

引用次数: 0

Crowd prediction systems: Markets, polls, and elite forecasters 人群预测系统：市场、民意调查和精英预测者

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2025-04-01 Epub Date: 2024-01-22 DOI: 10.1016/j.ijforecast.2023.12.009

Pavel Atanasov , Jens Witkowski , Barbara Mellers , Philip Tetlock

{"title":"Crowd prediction systems: Markets, polls, and elite forecasters","authors":"Pavel Atanasov , Jens Witkowski , Barbara Mellers , Philip Tetlock","doi":"10.1016/j.ijforecast.2023.12.009","DOIUrl":"10.1016/j.ijforecast.2023.12.009","url":null,"abstract":"<div><div>What systems should we use to elicit and aggregate judgmental forecasts? Who should be asked to make such forecasts? We address these questions by assessing two widely used crowd prediction systems: prediction markets and prediction polls. Our main test compares a prediction market against team-based prediction polls, using data from a large, multi-year forecasting competition. Each of these two systems uses inputs from either a large, sub-elite or a small, elite crowd. We find that small, elite crowds outperform larger ones, whereas the two systems are statistically tied. In addition to this main research question, we examine two complementary questions. First, we compare two market structures—continuous double auction (CDA) markets and logarithmic market scoring rule (LMSR) markets—and find that the LMSR market produces more accurate forecasts than the CDA market, especially on low-activity questions. Second, given the importance of elite forecasters, we compare the talent-spotting properties of the two systems and find that markets and polls are equally effective at identifying elite forecasters. Overall, the performance benefits of “superforecasting” hold across systems. Managers should move towards identifying and deploying small, select crowds to maximize forecasting performance.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 580-595"},"PeriodicalIF":6.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139587673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Does economic uncertainty predict real activity in real time? 经济的不确定性能实时预测实际活动吗？

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2025-04-01 Epub Date: 2024-07-20 DOI: 10.1016/j.ijforecast.2024.06.008

Bart Keijsers , Dick van Dijk

{"title":"Does economic uncertainty predict real activity in real time?","authors":"Bart Keijsers , Dick van Dijk","doi":"10.1016/j.ijforecast.2024.06.008","DOIUrl":"10.1016/j.ijforecast.2024.06.008","url":null,"abstract":"<div><div>We assess the predictive ability of 15 economic uncertainty measures in a real-time out-of-sample forecasting exercise for The Conference Board’s coincident economic index and its components (industrial production, employment, personal income, and manufacturing and trade sales). The results show that the measures hold (real-time) predictive power for quantiles in the left tail. Because uncertainty measures are all proxies of an unobserved entity, we combine their information using principal component analysis. A large fraction of the variance of the uncertainty measures can be explained by two factors: a general economic uncertainty factor with a slight tilt toward financial conditions, and a consumer/media confidence index which remains elevated after recessions. Using a predictive regression model with the factors from the set of uncertainty measures yields more consistent gains compared to a model with an individual uncertainty measure. Further, although accurate forecasts are obtained using the National Financial Conditions Index (NFCI), the uncertainty factor models are better when forecasting employment, and in general, the uncertainty factors have predictive content that is complementary to the NFCI.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 748-762"},"PeriodicalIF":6.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cognitive reflection, arithmetic ability and financial literacy independently predict both inflation expectations and forecast accuracy 认知反思、算术能力和金融素养分别独立预测通胀预期和预测准确性

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2025-04-01 Epub Date: 2024-09-20 DOI: 10.1016/j.ijforecast.2024.06.011

David A. Comerford

引用次数: 0

Investigating laypeople’s short- and long-term forecasts of COVID-19 infection cycles 调查非专业人士对 COVID-19 感染周期的短期和长期预测

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2025-04-01 Epub Date: 2023-12-15 DOI: 10.1016/j.ijforecast.2023.11.008

Moon Su Koo , Yun Shin Lee , Matthias Seifert

{"title":"Investigating laypeople’s short- and long-term forecasts of COVID-19 infection cycles","authors":"Moon Su Koo , Yun Shin Lee , Matthias Seifert","doi":"10.1016/j.ijforecast.2023.11.008","DOIUrl":"10.1016/j.ijforecast.2023.11.008","url":null,"abstract":"<div><div>How do laypeople anticipate the severity of the COVID-19 pandemic in the short and long term? The evolution of COVID-19 infection cases is characterized by wave-shaped cycles, and we examine how individuals make forecasts for this type of time series<span><span>. Over 42 weeks, we ran forecasting experiments and elicited weekly judgments from the general public to analyze their forecasting behavior<span> (Study 1). We find that laypeople often tend to dampen trends when generating judgmental forecasts, but the degree to which this happens depends on the evolution of the cyclic time series data. The observed forecasting behavior reveals evidence of an </span></span>optimism bias in that people do not expect the number of infection cases to grow at the observed rate while believing that infection rates would drop at an even faster rate than they are. Also, our results suggest that laypeople’s forecasting judgments are affected by the magnitude of the present wave relative to the previously observed ones. Further, we provide evidence that laypeople rely on a cognitive heuristic for generating long-term forecasts. People tend to rely on a linear discounting rule in that they lower their long-term forecasts proportionally to the interval of the forecast horizon, i.e., from tomorrow to 6 months and from 6 months to 1 year. We also find that this linear discounting rule can change to an exponential one in reaction to externally generated optimistic information signals such as vaccine approval. Furthermore, we replicated the major findings of Study 1 in a more controlled setting with a hypothetical pandemic scenario and artificially generated time series (Study 2). Overall, the current research contributes to the judgmental forecasting literature and provides practical implications for decision-makers in the pandemic.</span></div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 452-465"},"PeriodicalIF":6.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138682565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 7.1 2区经济学

International Journal of Forecasting Pub Date : 2025-02-26 DOI: 10.1016/j.ijforecast.2025.02.005

Giorgio Corani

引用次数: 0

The time-varying Multivariate Autoregressive Index model 时变多元自回归指数模型

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2025-01-01 Epub Date: 2024-05-15 DOI: 10.1016/j.ijforecast.2024.04.007

Gianluca Cubadda , Stefano Grassi , Barbara Guardabascio

引用次数: 0

Sparse time-varying parameter VECMs with an application to modeling electricity prices 稀疏时变参数 VECMs 在电价建模中的应用

IF 6.9 2区经济学