Search Results - subject_exact:"Prognoseverfahren"

Who shirks at work? : an application of machine learning to time use data

Gimenez-Nadal, José Ignacio; Molina, José Alberto; … - 2026

Worker productivity depends not only on hours worked, but also on how work time is actually used, and time-use evidence shows that non-work at work is non-trivial. This paper provides a data-driven characterization of shirking, and studies which observable characteristics best predict shirking...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015616882

Expertise and prediction accuracy

Grewenig, Elisabeth; Gründler, Klaus; Lergetporer, Philipp - 2026

Public support for policy interventions depends on citizens' beliefs about their likely effects. We examine how individuals form such beliefs by studying their predictions of experimental outcomes in a policy-relevant setting, and why their predictions differ from expert benchmarks. We elicit...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015617180

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Expertise and prediction accuracy

Grewenig, Elisabeth; Gründler, Klaus; Lergetporer, Philipp - 2026

Book / Working Paper

An analytical framework for causal decision-making in international trade

Vanegas-López, Juan Gabriel; Pérez-Aguirre, Carlos Andrés - 2026

In international trade, selecting an Incoterm is a critical decision impacting costs and risks. Previous quantitative studies relied on traditional econometric models imposing strict linearity, limiting causal interpretation. This study addresses this gap by applying a causal inference framework...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015654282

A data-assimilative approach to air quality analytics for policy and emergency planning

Poudel, Eeshwar Prasad; Pariyar, Shankar; Kafle, Jeevan; … - 2026

Air pollution remains a pressing environmental and public health concern, particularly in urban and industrial regions, underscoring the need for reliable dispersion modeling and effective emission control strategies. This study presents a unified framework for a two-dimensional...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015654291

A predictive analytics approach for forecasting global stock index returns using deep learning techniques

Hu, Liang; Shen, Yinru - 2026

Accurately predicting stock index returns remains a critical yet complex task due to the inherent volatility of financial markets and the intricate temporal dependencies within financial time series. This study presents a robust machine learning framework to forecast the relative returns of...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015654339

A cloud-enabled predictive analytics model for assessing health risks under climate variation

Rani, S. Sheeja; Aburukba, Raafat - 2026

The relationship between climatic conditions and disease spread is a crucial aspect of public health. Factors such as temperature, humidity, precipitation, seasonal changes, and air pollution directly and indirectly influence the transmission of infectious diseases, including respiratory...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015654340

A computational approach to cognitive architecture with adaptive networks and entropy-driven dynamics

Arbaoui, Billel - 2026

This study presents a computational approach to cognitive architecture that integrates adaptive networks with entropy-driven dynamics to model the evolution and stabilization of mental states. The framework combines temporal-causal network modeling with entropy-based mechanisms inspired by...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015654358

Monotonic polynomial GARCH models for conditional higher moments

Beiner, Rouven; Süssmuth, Bernd - 2026

Density expansions such as the Gram-Charlier (GC) expansion allow for the modeling of time-varying higher moments. However, they can suffer from spurious multimodality, negative densities, and asymptotically light tails if truncated. This paper introduces monotonic polynomial generalized...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015654688

A new model of trend inflation using disaggregates, survey expectations, and uncertainty

Tallman, Ellis W.; Zaman, Saeed - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015619060

Improving the sampling strategy for the community innovation survey using machine learning algorithms

Klingwort, Jonas; Berkel, Kees van; Brakel, Jan A. van den - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015619569

An in-depth assessment of the Central Bank of Malta's projections

Saliba, Maria Christine - 2026

This paper presents an in-depth analysis of the performance of the macroeconomic projections produced by Central Bank of Malta (CBM) staff. A real-time macroeconomic database published by the CBM is utilized, allowing for the computation of forecast errors based on the first official data...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015655280

Text as priors

Ge, Shuyi; Li, Shaoran; Linton, Oliver; Su, Wen - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015655582

Reliable prediction intervals for automated rental valuations

Besien, Maarten Van - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015608662

Understanding and predicting recidivism in Latin America : a machine learning approach

Anauati, María Victoria; Romero, María Noelia; … - 2026

Recidivism is a persistent challenge for criminal justice systems worldwide, yet evidence from Latin America remains scarce. This study addresses that gap through three contributions. First, it reviews the individual, institutional, and contextual determinants of recidivism, with special...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015608807

Forecasting Kazakhstan's GDP based on a dynamic factor model with regularization

Akhmet, Alisher - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015609234

Direct Gaussian process predictive regressions with mixed frequency data

Hauzenberger, Niko; Marcellino, Massimiliano; … - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015609527

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Direct gaussian process predictive regressions with mixed frequency data

Hauzenberger, Niko; Marcellino, Massimiliano; … - 2026

Book / Working Paper

Expectations versus reality in Business formation

Dinlersoz, Emin Murat; Ma, Yueyuan - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015609727

Establishment-level life cycle and analysts' forecasts

Basu, Sudipta; Dai, Xin; Lee, Caroline - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015609751

Can satellites predict oil demand?

Bricongne, Jean-Charles; Macalos, Joao; Meunier, Baptiste; … - 2026

We investigate whether satellite observations of nitrogen dioxide (NO₂) - a short-lived pollutant primarily emitted by fossil fuel combustion - can improve the forecasting of oil demand. After retrieving, cleaning, and aggregating daily satellite data, we integrate NO₂ into a range of...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015610289

A robust approach to tilting : parametric relative entropy

Montes-Galdón, Carlos; Paredes, Joan; Wolf, Elias - 2026

We introduce a novel methodology, "parametric tilting," for incorporating external information into econometric model-based density forecasts. Unlike traditional entropic tilting, which can generate unrealistic or unstable distributions under certain conditions, parametric tilting ensures more...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015610816

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A robust approach to tilting : parametric relative entropy

Montes-Galdón, Carlos; Paredes, Joan; Wolf, Elias - 2026

Book / Working Paper

Forecasting commodity prices using futures : the case of copper

Cortazar, Gonzalo; Enberg, Mariavictoria; Ortega, Hector - 2026

This paper analyzes three forecasting methods for commodity spot prices and applies them to copper prices. The first method uses futures prices from either LME or COMEX. The second method uses analysts' consensus expectations, reported by Bloomberg. The third method jointly uses futures and...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015611243

Evaluation and prediction of stock market crash risk in Mexico using log-periodic power-law modeling

Sunil, Suryansh; Goyal, Amit Kumar; Mahadeva, Rajesh; … - 2026

This study applies the Log-Periodic Power-Law (LPPL) framework to three major equity markets-Mexico (IPC), Brazil (IBOVESPA), and the United States (NYSE Composite)-using daily closes from 8 November 1991-30 January 2025 for IPC and NYSE, and 3 May 1993-30 January 2025 for IBOVESPA. Multi-window...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015611246

Enhancing predictive performance of LSTM-attention models for investment risk forecasting

Ladhari, Amina; Boubaker, Heni - 2026

For many decades, time-series forecasting has been applied to different problems by scientists and industries. Many models have been introduced for the purpose of forecasting. These advancements have significantly improved the accuracy and reliability of predictions, especially in complex...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015611300

Deep hybrid CNN-LSTM-GRU model for a financial risk early warning system

Muhammad Ali Chohan; Li, Teng; Abrar, Mohammad; … - 2026

Financial risk early warning systems are essential for proactive risk management in volatile markets, particularly for emerging economies such as China. This study develops a hybrid deep learning model integrating Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), and Gated...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015611314

A framework for interpreting machine learning models in bond default risk prediction using LIME and SHAP

Zhang, Yan; Chen, Lin; Tian, YiXiang - 2026

Interpretability analysis methods, such as LIME and SHAP, are widely employed to explain the predictions of artificial intelligence models; however, they primarily function as post hoc tools and do not directly quantify the intrinsic interpretability of the models. Although it is commonly...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015611531

Cognitive supply chain management and risk management in pharmaceuticals : the mediating roles of forecasting, synchronization, and transparency

Abushaikha, Ismail; AlQahtani, Munirah; Bwaliez, Omar M.; … - 2026

Background: This study examines the degree to which cognitive supply chain management (CSCM) indirectly enhances supply chain risk management (SCRM), addressing the lack of specific empirical research concerning the underlying mechanisms of this relationship. Specifically, this study tests the...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015611796

Bridging digitalization and sustainability in supply chain performance measurement : an MLP-based predictive model

Mrad, Mariem; Belgaroui, Rym; Boujelbene, Younes; … - 2026

Background: The transition toward Industry 4.0 and Supply Chain 5.0 requires performance measurement frameworks that integrate efficiency, digitalization, and sustainability indicators. Although the SCOR® 4.0 model provides standardized metrics, it lacks predictive capabilities under complex...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015612219

Beating the "pros" with a semi-structural model of their own inflation forecasts

Alves, Sergio Afonso Lago; Areosa, Waldyr Dutra; … - 2026 - Last updated: March 10, 2026

Professional inflation forecasts contain valuable information but exhibit information frictions. We extract improved forecasts by explicitly modeling these frictions using the US Survey of Professional Forecasters data, and find that forecast rigidity increases systematically with horizon,...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015612295

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Beating the "pros" with a semi-structural model of their own inflation forecasts

Alves, Sergio Afonso Lago; Areosa, Waldyr Dutra; … - 2026

Book / Working Paper

A Novel Quarterly Macroeconomic Forecasting Framework : Illustration on the Case of Bosnia and Herzegovina

Hlédik, Tibor - 2026

This paper describes the Quarterly Macro Forecasting Framework (QMFF), which is a novel approach to macroeconomic policy analysis and forecasting. At the core of this framework is a Quarterly Projection Model, with main behavioral equations quantified as deviations of real variables from their...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015612585

Algeria Macroeconomic Projection Model (AMPM)

Abderrahim, Mustapha - 2026

The paper describes QMPM, the Quarterly Projection Model for the Bank of Algeria that underpins the Bank’s Forecasting and Policy Analysis System. The model is designed to capture the key features of the economy, including the importance of the hydrocarbon sector, sizable fiscal policy...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015612618

Ukraine : Technical Assistance Report-Strengthening Macroeconomic Modeling in Support of Forecasting and Policy Analysis System (FPAS) at the National Bank of Ukraine (NBU)

2026

This Technical Assistance followed a request by the National Bank of Ukraine for a review of their existing Quarterly Projection Model (QPM) and Forecasting and Policy Analysis System (FPAS). Although the NBU had an established FPAS, which benefited from previous IMF TA, the existing model-based...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015612632

Understanding and Forecasting Inflation in Timor-Leste

Asao, Kohei - 2026

This paper presents a comprehensive analysis of inflation in Timor-Leste—a post-conflict, low-income economy and small developing state that is fully dollarized. We find that Timorese inflation was high until about mid-2010 and was strongly influenced by swings in global food prices given its...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015612641

Tonga : Technical Assistance Report-Liquidity Management and Forecasting

2026

The IMF conducted a Technical Assistance (TA) mission to assist the National Reserve Bank of Tonga (NRBT) in determining an appropriate policy rate and in implementing an effective liquidity management and forecasting framework. This TA mission serves as a follow-up to previous IMF TA, which...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015612646

Satellite Data for Nowcasting : Estimating Cambodia’s GDP in Real Time Using Satellite Data in a Machine Learning Framework

Maduako, Iyke - 2026

Cambodia is not alone in facing capacity limitations in the production and timely release of key official statistics needed for data-driven policy decisions. This paper demonstrates that combining satellite-derived indicators (e.g., nighttime lights, NO₂ emissions, vegetation indices) with...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015612716

Introducing BISTRO: a foundational model for unconditional and conditional forecasting of macroeconomic time series

Koyuncu, Batuhan; Kwon, Byeungchun; Lombardi, Marco; … - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015613838

Toward a Standard for Landslide Data : Bridging Gaps in Landslide Susceptibility Modeling and Early Warning Systems

Niyokwiringirwa, Priscilla; Gall, Tjark; Jha, Abhas K. - 2026

Landslides claim more than 4,000 lives annually and lead to approximately US$20 billion in economic losses. However, landslide hazard, risk assessment, and early warning systems remain constrained by fragmented, inconsistent, and incomplete data. This study addresses the global data gap by...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015613912

Interpretable multi-model framework for early warning of SME loan delinquency

Akhmetova, Ardak; Shayakhmetova, Assem; Abdurakhmanov, … - 2026

The rapid expansion of small and medium enterprise (SME) lending has intensified the need for accurate and interpretable credit risk forecasting. Financial institutions must anticipate potential business loan delinquency to maintain portfolio stability and meet regulatory standards. This study...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015614113

Adaptive LASSO-MGARCH for multivariate volatility forecasting

Xu, Yongdeng; Lyu, Juyi; Lu, Wenna - 2026

This paper evaluates an Adaptive LASSO-MGARCH model for multivariate volatility forecasting, with an application to green and conventional bonds, equities, energy commodities, and EU carbon allowances. By introducing coefficient-specific adaptive penalisation directly into the multivariate GARCH...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015614300

Bayesian causal inference for credit default risk

Pitso, Sello Dalton; Michael, Taryn - 2026

Banks often assume that higher credit limits increase customer default risk because greater exposure appears to imply greater vulnerability. This reasoning, however, conflates correlation with causation. Whether increasing a customer's credit limit truly raises the likelihood of default remains...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015614384

On the predictability of the effects of data centers electricity demand shocks

Crampes, Claude; Estache, Antonio - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015614427

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On the predictability of the effects of data centers electricity demand shocks

Crampes, Claude; Estache, Antonio - 2026

Book / Working Paper

The credit gap as a real-time early warning indicator of financial imbalances : a South African perspective

Msiska, Wongani; Sikhosana, Ayanda; Vermeulen, Cobus - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015615329

Measuring economic outlook in the news

Beck, Elliot; Eckert, Franziska; Kühne, Linus; … - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015615555

Forecasting stock market behavior in BRICS economies using artificial neural machine learning models

Panigrahi, Shrikant; Kukreja, Gagan; Kumaraswamy, Sumathi - 2026

Purpose - This study aims to forecast the stock market behavior of BRICS nations (Brazil, Russia, India, China and South Africa) using advanced machine learning models. The focus is on identifying market trends, predicting future index prices and analyzing returns. Design/methodology/approach -...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015592502

Outlier-robust evaluation of fixed-event macroeconomic survey expectations

Delis, Panagiotis; Kontogeorgos, Georgios - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015593667

Merger and acquisition prediction based on deep learning with attention mechanism

Wan, Liangyong; Zheng, Yongjia; Xu, Xiaoying; Wang, Rui - 2026

This study proposes a novel attention-based deep neural network (AttDNN) model specifically designed for predicting mergers and acquisitions (M&A). The model extends existing deep learning frameworks by incorporating M&A-specific features, regularization layers, and an attention mechanism that...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015596393

Hybrid modelling using simulation and machine learning in healthcare

Ahmadi, Ali; Fakhimi, Masoud; Magnusson, Carin - 2026

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015552381

A rotated dynamic factor model for the yield curve : squeezing out information when it matters

Casoli, Chiara; Lucchetti, Riccardo - 2026

The yield curve is widely regarded as a powerful descriptor of the economy and market expectations. A common approach to its statistical representation relies on a small number of factors summarizing the curve, which can then be used to forecast real economic activity. We argue that optimal...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015588201

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A rotated dynamic factor model for the yield curve : squeezing out information when it matters

Casoli, Chiara; Lucchetti, Riccardo - 2026

Book / Working Paper

Extrapolators and contrarians : forecast bias and individual investor stock trading

Andersen, Steffen; Dimmock, Stephen G.; Nielsen, Kasper M. - 2026

We test whether forecast bias affects individual investors' stock trading by combining bias measures from laboratory experiments with administrative trade data. Forecast bias is positively associated with past excess returns of purchased stocks: Compared to contrarians, extrapolators purchase...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015588367

Real-time nowcasting of Kyiv's regional GRP using Google trends and mixed-frequency data

Drin, Svitlana; Zhuravlova, Anastasiia - 2026

imely assessment of regional economic activity in Ukraine is severely constrained by institutional and data-related limitations. Official regional gross regional product (GRP) statistics are available only at low frequency, are published with substantial delays, and, in the post-2022 period, are...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015589819

Forecasting mutual fund performance : combining return-based with portfolio holdings-based predictors

Müller, Sebastian; Pugachyov, Nikolay; Weigert, Florian - 2026

We introduce a simple yet powerful method for enhancing mutual fund performance prediction by combining individual predictors into a composite predictor. This composite approach integrates information from 19 well-established return-based and portfolio holdings-based predictors from the...

Persistent link: https://www.econbiz.de, ebvufind01.dmz1.zbw.eu/10015591032