Research classified by Journal of Economic Literature (JEL) codes

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Top JEL
/ C: Mathematical and Quantitative Methods
/ / C4: Econometric and Statistical Methods: Special Topics
/ / / C45: Neural Networks and Related Topics

2026

• Paulo Júlio, 2026, "Deep Learning Models in Central Bank Forecasting," Working Papers, Banco de Portugal, Economics and Research Department, number w202612.
• Steffen Jahn & Tobias Klinke & Daniel Guhl & Maja Murr, 2026, "Re-fielding Replicability of Silicon Sample-based Marketing Research," Rationality and Competition Discussion Paper Series, CRC TRR 190 Rationality and Competition, number 583, Aug.
• Joan Christine S. Allon-Pineda, 2026, "Inflation Unpacked: Breaking Down the Key Components Using a Neural Phillips Curve," Asian Journal of Applied Economics/ Applied Economics Journal, Kasetsart University, Faculty of Economics, Center for Applied Economic Research, volume 33, issue 2, July.
• Emek Aslı CİNEL & Ufuk YOLCU, 2026, "Türkiye’de İşsizlik ve İstihdam Oranlarının Ekonomik Büyüme Göstergeleriyle Öngörülmesi: İstatistiksel, Yapay Sinir Ağı ve Bulanık Modellerin Karşılaştırılması
  [Forecasting Unemployment and Employment Rates in Türkiye with Economic Growth Indicato," Business and Economics Research Journal, Bursa Uludag University, Faculty of Economics and Administrative Sciences, volume 17, issue 4, pages 587-618, October, DOI: 10.20409/berj.2026.513.
• Andre Mouton, 2026, "Measuring Task-Level Technological Exposure: A Language Model Approach," Working Papers, Wake Forest University, Economics Department, number 132, Feb.
• Elliot Beck & Franziska Eckert & Linus Kühne & Helge Liebert & Rina Rosenblatt-Wisch, 2026, "Measuring economic outlook in the news," Working Papers, Swiss National Bank, number 2026-04.
• Arvind Ashta, 2026, "Artificial Intelligence in Microfinance and Financial Inclusion: Applications, Issues, and Future Directions," Working Papers CEB, ULB -- Universite Libre de Bruxelles, number 26-008, Jun.
• Cosimo Magazzino & Benedetta Coluccia & Donatella Porrini & Tulia Gattone, 2026, "Agents of digitalization: gendered employment patterns and broadband access across Asian economies," The Annals of Regional Science, Springer;Western Regional Science Association, volume 75, issue 1, pages 1-28, March, DOI: 10.1007/s00168-025-01432-z.
• Sergio Scicchitano & Marco Biagetti & Tulia Gattone & Cosimo Magazzino, 2026, "Digital transformation and remote work: gender, family size, and education in shaping work-from-home perceptions during COVID-19," The Annals of Regional Science, Springer;Western Regional Science Association, volume 75, issue 3, pages 1-39, September, DOI: 10.1007/s00168-026-01469-8.
• Yuanfang Chen & Wee-Yeap Lau & Lim-Thye Goh, 2026, "Spatio-temporal heterogeneity effect of digital talent mobility on economic growth: evidence from urban agglomerations in China," Asia-Pacific Journal of Regional Science, Springer, volume 10, issue 2, pages 1-37, June, DOI: 10.1007/s41685-026-00430-z.
• Ayben Koy & Semra Demir & Andaç Batur Çolak, 2026, "Google trend index as an investor sentiment proxy in cryptomarket: nonlinear relationships with cryptomarket and predicting bitcoin returns with machine learning approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, volume 34, issue 2, pages 575-595, June, DOI: 10.1007/s10100-025-01012-8.
• Soheil Salahshour & Mehdi Salimi & Kian Tehranian & Niloufar Erfanibehrouz & Massimiliano Ferrara & Ali Ahmadian, 2026, "Deep prediction on financial market sequence for enhancing economic policies," Decisions in Economics and Finance, Springer;Associazione per la Matematica, volume 49, issue 1, pages 5-24, June, DOI: 10.1007/s10203-024-00488-4.
• Rita Pimentel & Morten Risstad & Sondre Rogde & Erlend S. Rygg & Jacob Vinje & Sjur Westgaard & Cassandra Wu, 2026, "Option pricing with deep learning: a long short-term memory approach," Decisions in Economics and Finance, Springer;Associazione per la Matematica, volume 49, issue 1, pages 155-186, June, DOI: 10.1007/s10203-025-00518-9.
• Vaibhav Gagneja & Mayank Gupta & Sanjay Batish & Poonam Saini & Sudesh Rani, 2026, "ES-LSTM: a hybrid model for accurate time series forecasting in financial markets," Digital Finance, Springer, volume 8, issue 1, pages 1-21, March, DOI: 10.1007/s42521-025-00173-0.
• Qizhao Chen & Hiroaki Kawashima, 2026, "Sentiment-aware stock price prediction with transformer and LLM-generated formulaic alpha," Digital Finance, Springer, volume 8, issue 2, pages 1-28, June, DOI: 10.1007/s42521-026-00176-5.
• Hoang Anh Nguyen & Nhat Hoang Bach, 2026, "QI-HRNN: a quantum-inspired hybrid framework for resilient currency forecasting under extreme market conditions," Digital Finance, Springer, volume 8, issue 2, pages 1-40, June, DOI: 10.1007/s42521-026-00189-0.
• Huyen Giang Thi Thu & Thang Viet Doan & Ha-Bang Ban & Tai Le Quy, 2026, "An experimental study on fairness-aware machine learning for credit scoring problems," Digital Finance, Springer, volume 8, issue 3, pages 1-26, September, DOI: 10.1007/s42521-026-00202-6.
• Alexandra Ioana Conda & Ștefan Găman & Raul Cristian Bâg & Miruna Mazurencu-Marinescu-Pele & Daniel Traian Pele & Wolfgang Karl Härdle, 2026, "BitMood: AI analysis of Bitcoin trends via Facebook emotions," Digital Finance, Springer, volume 8, issue 3, pages 1-25, September, DOI: 10.1007/s42521-026-00205-3.
• Andry Alamsyah & Ki Anisa Zahria Salsabila & Nora Amelda Rizal, 2026, "Who holds the power in DeFi? Insights from a transactional network analysis of risk and control," Digital Finance, Springer, volume 8, issue 4, pages 1-40, December, DOI: 10.1007/s42521-026-00222-2.
• Yuhang Li & Hyoung-Goo Kang & Myeongsu Choi, 2026, "Protocol liquidity, rule-based benchmarks, and USDT yield predictability in DeFi lending," Digital Finance, Springer, volume 8, issue 4, pages 1-26, December, DOI: 10.1007/s42521-026-00223-1.
• Jinwon Kim & Seongsoo Jang & Ulrike Gretzel & Chulmo Koo, 2026, "Special issue on “Smart tourism 2.0: Perspectives with geospatial data and AI”," Electronic Markets, Springer;IIM University of St. Gallen, volume 36, issue 1, pages 1-5, December, DOI: 10.1007/s12525-025-00866-9.
• Radmir Mishelevich Leushuis & Nicolai Petkov, 2026, "Advances in forecasting realized volatility: a review of methodologies," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 12, issue 1, pages 1-29, December, DOI: 10.1186/s40854-025-00809-5.
• Hugo Gobato Souto & Amir Moradi, 2026, "Enhancing financial risk management: a novel multivariate neural network approach for realized covariance matrix prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 12, issue 1, pages 1-26, December, DOI: 10.1186/s40854-025-00816-6.
• Heng Xiong & Yuxuan Guo & Ričardas Zitikis, 2026, "Beyond no-claims discount: a learning-embedded telematics-driven pricing system for dynamic premium adjustments," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 12, issue 1, pages 1-38, December, DOI: 10.1186/s40854-026-00928-7.
• Boyu Wang & Xuefeng Gao & Lingfei Li, 2026, "Reinforcement learning for continuous-time optimal execution: actor–critic algorithm and error analysis," Finance and Stochastics, Springer, volume 30, issue 2, pages 597-655, April, DOI: 10.1007/s00780-026-00589-5.
• Hien Thu Bui & Thu Anh Trinh & Nhung Ha Phuong Vu & Linh Thi Thuy Pham & Hang Nguyet Trieu, 2026, "ESG, firm systematic risk, and economic policy uncertainty: analysis using deep learning-based ESG scores," Future Business Journal, Springer, volume 12, issue 1, pages 1-15, December, DOI: 10.1186/s43093-026-00830-9.
• Baffour Osei & Abigail Boatemaa & Isaac Nyame & Gabriel Osei Forkuo, 2026, "Evaluating machine learning and econometric models for inflation forecasting: evidence from a Sub-Saharan African panel," Future Business Journal, Springer, volume 12, issue 1, pages 1-21, December, DOI: 10.1186/s43093-026-01003-4.
• Amit Kumar Singh & Monomita Nandy & Suman Lodh & Shivani Kalra, 2026, "Sector signals: machine learning insights into IPO pricing dynamics," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, volume 17, issue 11, pages 3245-3263, November, DOI: 10.1007/s13198-026-03155-6.
• Tetsuya Kaji & Elena Manresa, 2026, "Why do the elderly save? using health shocks to uncover bequest motives," The Japanese Economic Review, Springer, volume 77, issue 2, pages 355-378, April, DOI: 10.1007/s42973-026-00249-5.
• Emiliano Alvarez & Juan Gabriel Brida & Roberto Gabriele, 2026, "The inflation process and the evolution of the price system: A complex systems approach," Journal of Evolutionary Economics, Springer, volume 36, issue 3, pages 1-32, December, DOI: 10.1007/s00191-026-00989-y.
• Élvio Camacho, 2026, "Multilingual Sentiment Analysis on Natural Trails Using Deep Learning: A Case Study from Pico do Areeiro, Madeira," Springer Proceedings in Business and Economics, Springer, in: Vicky Katsoni, "Synergizing Management, Culture, and Arts for Tourism Development - Vol. 2", DOI: 10.1007/978-3-032-17534-2_12.
• Evgenia Gkintoni & Georgios Telonis & Constantinos Halkiopoulos & Basilis Boutsinas, 2026, "Eye-Tracking and EEG in Neuro-Tourism: A Systematic Review of Machine Learning Approaches for Visual Attention and Cognitive Load Modeling," Springer Proceedings in Business and Economics, Springer, in: Vicky Katsoni, "Synergizing Management, Culture, and Arts for Tourism Development - Vol. 2", DOI: 10.1007/978-3-032-17534-2_7.
• Evgenia Gkintoni & Georgios Telonis & Constantinos Halkiopoulos & Basilis Boutsinas, 2026, "GSR and EEG-Based Arousal Analytics in Neuro-Tourism: A Systematic Review of Data Mining and Ethical Personalization Strategies," Springer Proceedings in Business and Economics, Springer, in: Vicky Katsoni, "Synergizing Management, Culture, and Arts for Tourism Development - Vol. 2", DOI: 10.1007/978-3-032-17534-2_8.
• Konstantinos Gkillas & Constantinos Halkiopoulos, 2026, "AI-Driven Smart Tourism: Leveraging Deep Learning and Financial Econometrics for Predictive Risk Management and Dynamic Destination Optimization," Springer Proceedings in Business and Economics, Springer, in: Vicky Katsoni, "Synergizing Management, Culture, and Arts for Tourism Development - Vol. 1", DOI: 10.1007/978-3-032-17545-8_17.
• Nikolina Christou & Vassiliki Karioti, 2026, "Forecasting Tourist Indicators in Greece: A Comparative Evaluation of Statistical and Deep Learning Models," Springer Proceedings in Business and Economics, Springer, in: Vicky Katsoni, "Synergizing Management, Culture, and Arts for Tourism Development - Vol. 1", DOI: 10.1007/978-3-032-17545-8_22.
• Gideon Mazuruse & Brighton Nyagadza, 2026, "Barriers to adopting climate change awareness and education in Zimbabwe: a hybrid structural equation modelling and extreme gradient boosting approach," Quality & Quantity: International Journal of Methodology, Springer, volume 60, issue 1, pages 2883-2912, February, DOI: 10.1007/s11135-025-02384-4.
• Sadik Aden Dirir, 2026, "Predictive modeling of electric vehicle adoption in OECD nations: an empirical assessment," Quality & Quantity: International Journal of Methodology, Springer, volume 60, issue 5, pages 15855-15883, October, DOI: 10.1007/s11135-026-02805-y.
• Aditya Ananda & Mohammad Ghani, 2026, "Modeling risk-based capital for life insurance companies in Indonesia: a comparative study of panel data regression and Gaussian Process Boosting," Quality & Quantity: International Journal of Methodology, Springer, volume 60, issue 5, pages 19025-19064, October, DOI: 10.1007/s11135-026-02923-7.
• Linjing Yang, 2026, "Uncovering cross-organizational risk patterns: a machine learning approach to predicting financial fraud via chain leader attributes," Review of Managerial Science, Springer, volume 20, issue 12, pages 4401-4441, December, DOI: 10.1007/s11846-026-01015-y.
• Changmin Oh, 2026, "ARDL-based feature engineering for corporate tax revenue forecasting under short samples: a machine-learning evaluation framework," SN Business & Economics, Springer, volume 6, issue 11, pages 1-23, November, DOI: 10.1007/s43546-026-01480-3.
• Mohd Redzuan Ahmad & Mohd Herwan Sulaiman, 2026, "Machine learning-based gold price forecasting: a bibliometric review of trends, methods, and future directions," SN Business & Economics, Springer, volume 6, issue 8, pages 1-38, August, DOI: 10.1007/s43546-026-01299-y.
• Elliott Ash & Stephen Hansen & Yabra Muvdi & Claudia Marangon, 2026, "Large Language Models in Economics," Springer Books, Springer, chapter 0, in: Shlomo Weber & Victor Ginsburgh, "The Palgrave Handbook of Economics and Language", DOI: 10.1007/978-3-031-88240-1_8.
• Ian Staley, 2026, "Quantum-Inspired Counterfactual Explainable AI with Blockchain-Based Provenance for Governed Automated Decision-Making: An Empirical Evaluation on Credit Underwriting," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 16, issue 3, pages 1-5.
• Rakshay Pawar, 2026, "Regime-Gated Tail Transfer: Reliable Cross-Industry Machine Learning for Value-at-Risk and Expected Shortfall," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 16, issue 6, pages 1-3.
• Alexa Kaminski & Alistair Macaulay & Wenting Song, 2026, "Monetary Policy Narratives and the Transmission of Monetary Policy," School of Economics Discussion Papers, School of Economics, University of Surrey, number 0126, Jan.
• Johan Fourie & Calumet Links, 2026, "Demographic Pressure, Emancipation and Selection into the Great Trek," Working Papers, Stellenbosch University, Department of Economics, number 06/2026.
• Zongwu Cai & Xiyuan Liu & Liangjun Su, 2026, "A Functional-Coefficient VAR Model for Dynamic Quantiles and Its Application to Constructing Nonparametric Financial Network," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 44, issue 1, pages 162-176, January, DOI: 10.1080/07350015.2025.2511960.
• Sicco Kooiker & Janneke van Brummelen & Julia Schaumburg & Marcin Zamojski, 2026, "Self-driving neural networks for term structure modeling," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 26-007/III, Feb.
• Francisco Blasques & Nepomuk Dunz & Erik Feyen & Charl Jooste & Jose Marzluf & Gabriele Mingoli, 2026, "New Early-Warning Indicators of Macro-Financial Risk: A Mixture-of-Experts Approach," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 26-074/III, Sep.
• Nicholas Lacoste & Zehra Farooq, 2026, "Optimal Audit Targeting with Machine Learning: Evidence from Pakistan," Working Papers, Tulane University, Department of Economics, number 2603, Feb.
• Santiago Picasso, 2026, "Measuring Services Complexity: A Novel Machine Learning Approach Using U.S. Input–Output Data," Documentos de Trabajo (working papers), Department of Economics - dECON, number 0126, Feb.
• Rony, Sidharth, 2026, "LLM Meets Job Advertisements: Unmasking Skill Premia in the UK," MERIT Working Papers, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT), number 010, Aug, DOI: 10.53330/QGGU3545.
• Oleksandr Castello & Marco Corazza, 2026, "Machine Learning techniques for synthetic data generation in Energy and Financial Markets," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2026: 11.
• Antonella Basso & Marco Corazza & Lorenzo Tonon, 2026, "Recurrent Neural Networks for real estate evaluation in the Italian market," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2026: 22.
• Adriano Amati & Monica Billio & Marco Di Cataldo & Giovanni Mastrobuoni, 2026, "Mafia Connections: Infiltration in Corporate Ownership," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2026: 24.
• Yachou Najlae & Abahman Omar & Hakimi Khalid, 2026, "Designing an LSTM-Based Model for Financial Asset Forecasting Using Machine Learning," Central European Economic Journal, Paradigm, volume 13, issue 60, pages 1-23, DOI: 10.2478/ceej-2026-0001.
• Mishra Somanath Kumar & Patri Prasanta, 2026, "Flood Forecasting Using Artificial Intelligence (AI): A Prisma – Guided Systematic Review," Economic and Regional Studies / Studia Ekonomiczne i Regionalne, Paradigm, volume 19, issue 2, pages 345-366, DOI: 10.2478/ers-2026-0020.
• Cafieri Simona & Borrata Gianmarco, 2026, "AI Techniques for Survey Data Quality: Transformers and GANs," Journal of Social and Economic Statistics, Paradigm, volume 15, issue 1, pages 57-68, DOI: 10.2478/jses-2026-0005.
• Węgrzyn Joanna, 2026, "Mining Real Estate Data: A Systematic Review of Text-Based Approaches," Real Estate Management and Valuation, Paradigm, volume 34, issue 1, pages 1-15, DOI: 10.2478/remav-2026-0001.
• Pham Thuy Tu, 2026, "Global Information Uncertainty and Real Estate Stock Valuation in Emerging Markets: an Integrated Behavioral - Theoretical and Machine Learning Framework," Real Estate Management and Valuation, Paradigm, volume 34, issue 1, pages 63-83, DOI: 10.2478/remav-2026-0006.
• Thanh Hang Hoang Thi & Pham Thuy Tu, 2026, "Bridging Predictive Power and Interpretability: A Hybrid Deep Learning Framework for Real Estate Performance Under Systemic Uncertainty," Real Estate Management and Valuation, Paradigm, volume 34, issue 3, pages 62-76, DOI: 10.2478/remav-2026-0025.
• Horák Jakub & Kučera Jiří, 2026, "Trends, Shocks and Predictions in the Price Development of Food-Grade Wheat," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Paradigm, volume 36, issue 3, pages 128-165, DOI: 10.2478/sues-2026-0015.
• Kostiantyn Okhrimenko, 2026, "Painting Price: A Machine Learning Approach to Art Valuation. Proof of Concept and Market Structure Diagnosis," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2026-18.
• Jabeur Salhi & Ichrak Dridi & Oussama Gafrej, 2026, "Unlocking success in tech reward crowdfunding: A hybrid probit-machine learning approach with SHAP-driven feature analysis," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., volume 13, issue 01, pages 1-43, March, DOI: 10.1142/S2424786326500027.
• Sabbor Hussain & Jo-Hui Chen & Dramane Thiombiano, 2026, "The impact of macroeconomic indicators on ETF: A grey relational analysis-machine learning approach," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., volume 13, issue 03, pages 1-30, September, DOI: 10.1142/S2424786326500234.
• Anshul Agrawal & Sanjeev Kadam & Mohd Afjal, 2026, "Evaluating Predictive Robustness of Machine Learning Models During Black Swan Crises: Insights from Bitcoin Price Forecasting," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., volume 17, issue 02, pages 1-22, June, DOI: 10.1142/S1793993325500267.
• Tuyen Le Nam & Tam Phan Huy, 2026, "Corporate Financial Distress Prediction in Vietnam Using Calibrated and Explainable Machine Learning," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., volume 17, issue 03, pages 1-31, October, DOI: 10.1142/S1793993326500195.
• Qingqing Ren & Hualing Liu, 2026, "Fraud Detection and Risk Management in Internet Finance," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 14457, ISBN: ARRAY(0x7c9c8090), March.
• Krishan Arora & Himanshu Sharma (ed.), 2026, "AI in Finance:Shaping the Future of Intelligent Automation and Financial Services," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number q0542, ISBN: ARRAY(0x7cc26ba8), March.
• Brijlal Mallik & Shivangi Kashyap & Robert Ślepaczuk & Manish Kumar & Dev Kumar Mandal, 2026, "AI-Driven Automation: Revolutionizing Financial Operations and Efficiency," World Scientific Book Chapters, World Scientific Publishing Co. Pte. Ltd., chapter 1, in: Krishan Arora & Himanshu Sharma, "AI in Finance Shaping the Future of Intelligent Automation and Financial Services".
• Shikha Tuteja & Ravinder Tonk & Moushumi Das & Vishal Jagota & Rajan Vohra, 2026, "Integrating AI with Traditional Financial Systems," World Scientific Book Chapters, World Scientific Publishing Co. Pte. Ltd., chapter 2, in: Krishan Arora & Himanshu Sharma, "AI in Finance Shaping the Future of Intelligent Automation and Financial Services".
• S. Babu Reddy & R. Ganesh & Nirmalya Pal & Sammarth Choudhury & Riya Sil, 2026, "Securing the Cloud: Mitigating Data Security and Privacy Challenges in Cloud Computing," World Scientific Book Chapters, World Scientific Publishing Co. Pte. Ltd., chapter 3, in: Krishan Arora & Himanshu Sharma, "AI in Finance Shaping the Future of Intelligent Automation and Financial Services".
• Manik Rakhra & Tiyas Sarkar, 2026, "Transforming Investment Management Strategies: The Impact of Intelligent Systems on Modern Financial Planning Utilizing Robo-Advisors," World Scientific Book Chapters, World Scientific Publishing Co. Pte. Ltd., chapter 4, in: Krishan Arora & Himanshu Sharma, "AI in Finance Shaping the Future of Intelligent Automation and Financial Services".
• Shivangi Kashyap, 2026, "AI or Bye: Tackling Ethical Dilemmas in Financial Automation," World Scientific Book Chapters, World Scientific Publishing Co. Pte. Ltd., chapter 5, in: Krishan Arora & Himanshu Sharma, "AI in Finance Shaping the Future of Intelligent Automation and Financial Services".
• Chirra Baburao & Sakha Gangadhara Rama Rao & Lova Baliji & Firdous Ahmad Malik & Krishan Arora, 2026, "Artificial Intelligence in Portfolio Management: Transforming Financial Decision-Making and Optimizing Risk Management," World Scientific Book Chapters, World Scientific Publishing Co. Pte. Ltd., chapter 6, in: Krishan Arora & Himanshu Sharma, "AI in Finance Shaping the Future of Intelligent Automation and Financial Services".
• Tiyas Sarkar & Manik Rakhra, 2026, "Transforming Indian Banking: The Impact of Intelligent Systems and Process Automation on Financial Innovation," World Scientific Book Chapters, World Scientific Publishing Co. Pte. Ltd., chapter 7, in: Krishan Arora & Himanshu Sharma, "AI in Finance Shaping the Future of Intelligent Automation and Financial Services".
• Pankhuri Kapoor & Tushinder Preet Kaur, 2026, "AI, Finance, and the Future of Healthcare and Medical Tourism in Delhi," World Scientific Book Chapters, World Scientific Publishing Co. Pte. Ltd., chapter 8, in: Krishan Arora & Himanshu Sharma, "AI in Finance Shaping the Future of Intelligent Automation and Financial Services".
• Prabhjeet Kaur & Amandeep Kaur & Ramandeep Sandhu & Deepika Ghai & Veer P. Gangwar & Lokesh Jasrai, 2026, "Role of Artificial Intelligence in Cybersecurity: Innovations and Challenges," World Scientific Book Chapters, World Scientific Publishing Co. Pte. Ltd., chapter 9, in: Krishan Arora & Himanshu Sharma, "AI in Finance Shaping the Future of Intelligent Automation and Financial Services".
• Rajesh Singh & Anita Gehlot & Shaik Vaseem Akram & Mohammed Ismail Iqbal & Praveen Kumar Malik, 2026, "Role of Industry 5.0 in Enabling Technologies for Manufacturing Systems: A Sustainability and Intelligence Perspective," World Scientific Book Chapters, World Scientific Publishing Co. Pte. Ltd., chapter 10, in: Krishan Arora & Himanshu Sharma, "AI in Finance Shaping the Future of Intelligent Automation and Financial Services".
• Nahita Pathania & Balraj Singh & Isha Batra, 2026, "AI-Based Real-Time Problem-Solving Using Smart Technologies," World Scientific Book Chapters, World Scientific Publishing Co. Pte. Ltd., chapter 11, in: Krishan Arora & Himanshu Sharma, "AI in Finance Shaping the Future of Intelligent Automation and Financial Services".
• Boughabi, Houssam, 2026, "Fiscal and labour-market conditions and wage-income dynamics in Morocco: A Kaleckian-inspired reduced-form analysis," ZÖSS-Discussion Papers, University of Hamburg, Centre for Economic and Sociological Studies (CESS/ZÖSS), number 131.
• Fausch, Jürg & Frigg, Moreno & Ruenzi, Stefan & Weigert, Florian, 2026, "Machine learning mutual fund flows," CFR Working Papers, University of Cologne, Centre for Financial Research (CFR), number 26-03.
• Weibels, Sebastian, 2026, "Hard to process: Atypical firms and the cross-section of expected stock returns," CFR Working Papers, University of Cologne, Centre for Financial Research (CFR), number 26-05.
• Gondauri, Davit, 2026, "Millennium Economics: Seven Mathematical Architectures for Measuring Global Economic Complexity," EconStor Books, ZBW - Leibniz Information Centre for Economics, number 342001, June.
• Gondauri, Davit, 2026, "Global Hodge-Econometric Modeling of the World Economy: A Regional Benchmark Prototype for Topological Flow Decomposition, Systemic Circulation, Shock Transmission, and Macroeconomic Resilience," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 341543.
• Gondauri, Davit, 2026, "Economic Yang–Mills Mass Gap in Global and Corridor Flow Networks: A Finite-Network Gauge-Econometric Framework for Measuring Systemic Shock Thresholds," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 341544.
• Greyling, Talita & Rossouw, Stephanie, 2026, "Different Evaluative Well-being Measures, Different Conclusions? Evidence across Regions," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1825.
• Rossouw, Stephanie & Greyling, Talita, 2026, "Social Capital, Economic Conditions and Evaluative Well-Being: Comparing Life Satisfaction and the Cantril Ladder Across the West and the Global South," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1833.
• Plüghan, Oliver & Rehfeld, Katharina-Maria, 2026, "Assessing wage inequality with machine learning: Approaches for measuring the adjusted gender pay gap," IU Discussion Papers - Human Resources, IU International University of Applied Sciences, number 4 (März 2026), DOI: 10.56250/4118.
• Werner, Sven & Trotter, Philipp, 2026, "When development finance spurs entrepreneurship: New evidence from 5 million projects using a machine learning classifier," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 1205, DOI: 10.4419/96973390.

2025

• Angel Anchev & Borislav Stoyanov & Milka Atanasova & Yaroslav Argirov & Boris Petkov, 2025, "Improving in microhardness of C45 steel obtained via electron beam hardening using a one-factor-at-a-time technique," International Journal of Innovative Research and Scientific Studies, Innovative Research Publishing, volume 8, issue 5, pages 1255-1270.
• Habib ZOUAOUI & Meryem-Nadjat NAAS, 2025, "Portfolio Optimization Based on MPT-LSTM Neural Networks: A case study of Cryptocurrency Markets," Finance, Accounting and Business Analysis, Academic Publishing UNWE, volume 7, issue 1, pages 82-98, June.
• Adedeji Gbadebo, 2025, "Stock Price Forecasting Using a Time-Series Long Short-Term Memory Model," Finance, Accounting and Business Analysis, Academic Publishing UNWE, volume 7, issue 2, pages 304-322, December.
• Daria Dzyabura & Renana Peres & Irina Linevich, 2025, "Color Analytics for Data-Driven Brand Communications," Working Papers, New Economic School (NES), number w0292, Dec.
• Alejandro Adame-Castaneda & Ivan Alejandro Salas-Durazo, 2025, "Politicas publicas para el desarrollo rural integral en Mexico una aproximacion multidimensional al ODS 2 Hambre Cero," Scientia et PRAXIS, AMIDI Editorial, volume 5, issue 10, pages 34-63.
• Ahmet Akusta, 2025, "Predicting Market Sensitivity: The Role of Board Structure in the Beta Coefficient of Software Companies on the Nasdaq Global Select Market," Journal of Finance Letters (Maliye ve Finans Yazıları), Maliye ve Finans Yazıları Yayıncılık Ltd. Şti., volume 40, issue 123, pages 14-34, April, DOI: https://doi.org/10.33203/mfy.159699.
• Johannes Haushofer & Paul Niehaus & Carlos Paramo & Edward Miguel & Michael Walker, 2025, "Targeting Impact versus Deprivation," American Economic Review, American Economic Association, volume 115, issue 6, pages 1936-1974, June, DOI: 10.1257/aer.20221650.
• Marlène Koffi, 2025, "Innovative Ideas and Gender (In)equality," American Economic Review, American Economic Association, volume 115, issue 7, pages 2207-2236, July, DOI: 10.1257/aer.20211811.
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• Elliott Ash & Sergio Galletta & Tommaso Giommoni, 2025, "A Machine Learning Approach to Analyze and Support Anticorruption Policy," American Economic Journal: Economic Policy, American Economic Association, volume 17, issue 2, pages 162-193, May, DOI: 10.1257/pol.20210618.
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• Abi Adams & Mathias Fjællegaard Jensen & Barbara Petrongolo, 2025, "The Contribution of Employee-Led and Employer-Led Work Flexibility to the Motherhood Wage Gap," AEA Papers and Proceedings, American Economic Association, volume 115, pages 243-247, May, DOI: 10.1257/pandp.20251015.
• Lefteris Andreadis & Eleni Kalotychou & Manolis Chatzikonstantinou & Christodoulos Louca & Christos A. Makridis, 2025, "Local Heterogeneity in Artificial Intelligence Jobs over Time and Space," AEA Papers and Proceedings, American Economic Association, volume 115, pages 29-34, May, DOI: 10.1257/pandp.20251001.
• Tania Babina & Anastassia Fedyk & Alex He & James Hodson, 2025, "Artificial Intelligence Makes Firm Operating Performance Less Volatile," AEA Papers and Proceedings, American Economic Association, volume 115, pages 35-39, May, DOI: 10.1257/pandp.20251002.
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• Stefania Albanesi & António Dias da Silva & Juan F. Jimeno & Ana Lamo & Alena Wabitsch, 2025, "AI and Women's Employment in Europe," AEA Papers and Proceedings, American Economic Association, volume 115, pages 46-50, May, DOI: 10.1257/pandp.20251044.
• Benjamin Labaschin & Tyna Eloundou & Sam Manning & Pamela Mishkin & Daniel Rock, 2025, "Extending "GPTs Are GPTs" to Firms," AEA Papers and Proceedings, American Economic Association, volume 115, pages 51-55, May, DOI: 10.1257/pandp.20251045.
• Mauro Cazzaniga & Augustus Panton & Longji Li & Carlo Pizzinelli & Marina M. Tavares, 2025, "A Gender Lens on Labor Market Exposure to AI," AEA Papers and Proceedings, American Economic Association, volume 115, pages 56-61, May, DOI: 10.1257/pandp.20251046.
• Philippe Aghion & Simon Bunel & Xavier Jaravel & Thomas Mikaelsen & Alexandra Roulet & Jakob Søgaard, 2025, "How Different Uses of AI Shape Labor Demand: Evidence from France," AEA Papers and Proceedings, American Economic Association, volume 115, pages 62-67, May, DOI: 10.1257/pandp.20251047.
• Abe Dunn & Eric English & Kyle Hood & Lowell Mason & Brian Quistorff, 2025, "Economic Measurement Lost in a Random Forest? A Case Study of Employment Data," AEA Papers and Proceedings, American Economic Association, volume 115, pages 68-72, May, DOI: 10.1257/pandp.20251103.
• Tatjana Dahlhaus & Reinhard Ellwanger & Gabriela Galassi & Pierre-Yves Yanni, 2025, "From Online Job Postings to Economic Insights: A Machine Learning Approach to Structuring Naturally Occurring Data," AEA Papers and Proceedings, American Economic Association, volume 115, pages 73-78, May, DOI: 10.1257/pandp.20251104.
• Gary Cornwall & Marina Gindelsky, 2025, "Nowcasting Distributional National Accounts for the United States: A Machine Learning Approach," AEA Papers and Proceedings, American Economic Association, volume 115, pages 79-84, May, DOI: 10.1257/pandp.20251105.
• Andrew Caplin, 2025, "Data Engineering for Cognitive Economics," Journal of Economic Literature, American Economic Association, volume 63, issue 1, pages 164-196, March, DOI: 10.1257/jel.20241351.
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• Quintana Pablo & Herrera-Gomez Marcos, 2025, "Redefining Regions in Space and Time: A Deep Learning Method for Spatio-Temporal Clustering," Asociación Argentina de Economía Política: Working Papers, Asociación Argentina de Economía Política, number 4831, Dec.
• Kutlu ERGÃœN, 2025, "From Man to Man with AI Navigation: An Essay on the Homo Economicus Strengthened and Weakened by AI," Journal of Emerging Trends in Marketing and Management, The Bucharest University of Economic Studies, volume 1, issue 3, pages 31-42, September.
• Katleho Makatjane & Claris Shoko, 2025, "Explainable Deep Learning for Financial Risk: Joint VaR and ES Forecasting Using ESRNN in the Bitcoin Market," The African Finance Journal, Africagrowth Institute, volume 27, issue 1, pages 53-69.
• Jieyu Chen & Sebastian Lerch & Melanie Schienle & Tomasz Serafin & Rafal Weron, 2025, "Probabilistic intraday electricity price forecasting using generative machine learning," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/25/05.
• Arkadiusz Lipiecki & Kaja Bilinska & Nikolaos Kourentzes & Rafal Weron, 2025, "Stealing accuracy: Predicting day-ahead electricity prices with Temporal Hierarchy Forecasting (THieF)," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/25/06.
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• Yunus Emre Akdoğan, 2025, "The Role of Financial Indicators in the Prediction of Voluntary Carbon Disclosure: A Comparative Analysis with Machine Learning Methods," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 10, issue 3, pages 949-970, DOI: 10.30784/epfad.1651693.
• Çiğdem Yerli, 2025, "Evaluating the Impact of ESG and Decarbonization Metrics on Stock Price Prediction," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 10, issue SI, pages 252-274, DOI: 10.30784/epfad.1669184.
• Yunus Emre Gür & Ahmet İhsan Şimşek & Emre Bulut, 2025, "Artificial Intelligence-Assisted Machine Learning Methods For Forecasting Green Bond Index: A Comparative Analysis," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 9, issue 4, pages 628-655, DOI: https://doi.org/10.30784/epfad.1495.
• Lev A. Bulanov & Alexei V. Kalina & Vadim V. Krivorotov, 2025, "Clustering of Russian Manufacturing Companies by Indicators of Their Financial Condition Using Machine Learning Technologies," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, volume 24, issue 2, pages 584-621, DOI: https://doi.org/10.15826/vestnik.20.
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• Mona MAHYAOUI & Malak LAZRAK & Rachid KRAMI, 2025, "Modeling volatility with multivariate GARCH models through the integration of deep Learning: A literature review," International Journal of Accounting, Finance, Auditing, Management and Economics, Faculté d'Économie et de Gestion, Université Ibn Tofaïl de Kénitra, volume 6, issue 11, pages 765-778.
• Anas JABOURI & Abdelali EZZIADI, 2025, "Capacité prédictive des technologies émergentes pour le contrôle de gestion de la construction : Une analyse bibliométrique," International Journal of Accounting, Finance, Auditing, Management and Economics, Faculté d'Économie et de Gestion, Université Ibn Tofaïl de Kénitra, volume 6, issue 12, pages 53-74.
• Chaymae SAHRAOUI & Tarek ZARI, 2025, "Targeting Social Assistance Beneficiaries Using Machine Learning: A Poverty Probability-Based Approach," International Journal of Accounting, Finance, Auditing, Management and Economics, Faculté d'Économie et de Gestion, Université Ibn Tofaïl de Kénitra, volume 6, issue 9, pages 303-318.
• Pablo Quintana & Marcos Herrera-Gómez, 2025, "Redefining Regions in Space and Time: A Deep Learning Method for Spatio-Temporal Clustering," Working Papers, Red Nacional de Investigadores en Economía (RedNIE), number 368, Aug.
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• Arkadiusz Lipiecki & Kaja Bilinska & Nicolaos Kourentzes & Rafal Weron, 2025, "Stealing Accuracy: Predicting Day-ahead Electricity Prices with Temporal Hierarchy Forecasting (THieF)," Papers, arXiv.org, number 2508.11372, Aug, revised Mar 2026.
• Tatsuru Kikuchi, 2025, "Network Contagion Dynamics in European Banking: A Navier-Stokes Framework for Systemic Risk Assessment," Papers, arXiv.org, number 2510.19630, Oct, revised Oct 2025.
• Elliot Beck & Franziska Eckert & Linus Kuhne & Helge Liebert & Rina Rosenblatt-Wisch, 2025, "Measuring economic outlook in the news," Papers, arXiv.org, number 2511.04299, Nov, revised Feb 2026.
• Rubén Fernández-Fuertes, 2025, "Monetary Policy Shocks: A New Hope. Large Language Models and Central Bank Communication," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 25257.
• Kamelia Ahmadkhan & Abdolreza Yazdani-Chamzini & Alireza Bakhshizadeh & Jonas Šaparauskas & Zenonas Turskis & Niousha Zeidyahyaee, 2025, "Promoting reverse logistics decisions using a new hybrid model based on deep learning and failure mode and effects analysis approaches," E&M Economics and Management, Technical University of Liberec, Faculty of Economics, volume 28, issue 4, pages 79-98, December, DOI: 10.15240/tul/001/2025-4-006.
• Julien Pascal, 2025, "Solving economic models with neural networks without backpropagation," BCL working papers, Central Bank of Luxembourg, number 196, Apr.
• Firdevs Nur UYKUN & Busra Zeynep TEMOCIN, 2025, "A Machine Learning Integrated Portfolio Rebalance Framework with Risk Aversion Adjustment," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, volume 19, issue 2, pages 173-197.
• Pilar García & Diego Torres, 2025, "Perceiving central bank communications through press coverage," Working Papers, Banco de España, number 2505, Jan, DOI: https://doi.org/10.53479/38922.
• Canio Benedetto & Sara Crestini & Alessandro de Gregorio & Marco de Leonardis & Andrea del Monaco & Daniele Gulino & Paolo Massaro & Francesca Monacelli & Lorenzo Rubeo, 2025, "Applying artificial intelligence to support regulatory reporting management: the experience at Banca d'Italia," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 927, Apr.
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• Milovan Rankov, 2025, "Komparativna Analiza Modela Kreditnog Skoringa: Konvencijalni Vs Modeli Bazirani Na Mašinskom I Dubokom Učenju," Ekonomske ideje i praksa, Faculty of Economics and Business, University of Belgrade, issue 57, pages 29-45, June.
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• Oleg Kryzhanovskiy & Anastasia Mogilat & Zhanna Shuvalova & Dmitry Gvozdev, 2025, "Using LSTM Neural Networks for Nowcasting and Forecasting GVA of Industrial Sectors," Russian Journal of Money and Finance, Bank of Russia, volume 84, issue 1, pages 93-104, March.
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• Goulet Coulombe Philippe, 2025, "To Bag is to Prune," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 29, issue 6, pages 669-697, DOI: 10.1515/snde-2023-0030.
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• Alvaro Riascos Villegas, 2025, "El Potencial Impacto del Aprendizaje de M√°quinas en el Dise√±o de las Pol√≠ticas P√∫blicas en Colombia: Una d√©cada de experiencias," Documentos CEDE, Universidad de los Andes, Facultad de Economía, CEDE, number 21340, Feb.
• Juan Jos√© Rinc√≥n Brice√±o, 2025, "Colombian economic activity nowcasting: addressing nonlinearities and high dimensionality through machine-learning," Documentos CEDE, Universidad de los Andes, Facultad de Economía, CEDE, number 21388, Jun.
• Carlos Castro-Iragorri & Manuel Parra-Diaz, 2025, "Stability focused end to end frameworks for risk budgeting portfolios," Documentos de Trabajo, Universidad del Rosario, number 21367, Mar.
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• Christopher Mwololo Fred, 2025, "Comparative Analysis of Machine Learning Algorithms for Enhancing Social Media Marketing and Decision-Making in Kenyan SMEs," African Journal of Commercial Studies, African Journal of Commercial Studies, volume 6, issue 1, DOI: 10.59413/ajocs/v6.i.1.4.
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• Echevin, Damien & Fotso, Guy & Bouroubi, Yacine & Coulombe, Harold & Li, Qing, 2025, "Combining survey and census data for improved poverty prediction using semi-supervised deep learning," Journal of Development Economics, Elsevier, volume 172, issue C, DOI: 10.1016/j.jdeveco.2024.103385.
• Aridor, Guy & Azeredo da Silveira, Rava & Woodford, Michael, 2025, "Information-constrained coordination of economic behavior," Journal of Economic Dynamics and Control, Elsevier, volume 172, issue C, DOI: 10.1016/j.jedc.2024.104985.
• Ma, Dan & Zhu, Yanjin & Lee, Chien-Chiang, 2025, "The impact of new energy pilot city policies on urban green innovation: Evidence from China’s city level," Economic Analysis and Policy, Elsevier, volume 87, issue C, pages 585-604, DOI: 10.1016/j.eap.2025.06.029.
• Peng, Michael & Stern, Elisheva R. & Hu, Hanwen, 2025, "Forecasting China bond default with severe class-imbalanced data: A simple learning model with causal inference," Economic Modelling, Elsevier, volume 144, issue C, DOI: 10.1016/j.econmod.2024.106985.
• Limosani, Michele & Millemaci, Emanuele & Mustica, Paolo, 2025, "Do green policies enhance short-term economic growth? Assessing EU Recovery and Resilience Plans through the lens of Sustainable Development Goals," Economic Modelling, Elsevier, volume 147, issue C, DOI: 10.1016/j.econmod.2025.107044.
• Zhang, Heng-Guo & Wang, Shihong & Xie, Yuchi, 2025, "How does news-driven monetary policy frictions affect nonperforming loans?--Taking Chinese commercial banks as an example," The North American Journal of Economics and Finance, Elsevier, volume 76, issue C, DOI: 10.1016/j.najef.2024.102353.
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• Ahrens, Maximilian & Erdemlioglu, Deniz & McMahon, Michael & Neely, Christopher J. & Yang, Xiye, 2025, "Mind your language: Market responses to central bank speeches," Journal of Econometrics, Elsevier, volume 249, issue PC, DOI: 10.1016/j.jeconom.2024.105921.
• Haghighi, Maryam & Joseph, Andreas & Kapetanios, George & Kurz, Christopher & Lenza, Michele & Marcucci, Juri, 2025, "Machine Learning for Economic Policy," Journal of Econometrics, Elsevier, volume 249, issue PC, DOI: 10.1016/j.jeconom.2025.105970.
• Caner, Mehmet & Daniele, Maurizio, 2025, "Deep learning based residuals in non-linear factor models: Precision matrix estimation of returns with low signal-to-noise ratio," Journal of Econometrics, Elsevier, volume 251, issue C, DOI: 10.1016/j.jeconom.2025.106083.
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• Tsionas, Mike & Zelenyuk, Valentin & Zhang, Xibin, 2025, "Goodness-of-fit in production models: A Bayesian perspective," European Journal of Operational Research, Elsevier, volume 324, issue 2, pages 644-653, DOI: 10.1016/j.ejor.2025.01.030.
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• Agakishiev, Ilyas & Härdle, Wolfgang Karl & Kopa, Milos & Kozmik, Karel & Petukhina, Alla, 2025, "Multivariate probabilistic forecasting of electricity prices with trading applications," Energy Economics, Elsevier, volume 141, issue C, DOI: 10.1016/j.eneco.2024.108008.
• Albani, V.V.L. & Marcavillaca, R.T. & Moreira, P.S.E. & Avila, S.L. & Geremia, M. & Piovezan, R.P.B. & Sica, E.T. & Santos, E., 2025, "Short-term forecasting of forward prices in the Brazilian electricity market with a hybrid stochastic-neural network model," Energy Economics, Elsevier, volume 148, issue C, DOI: 10.1016/j.eneco.2025.108651.
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