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Neural Network Models for Inflation Forecasting: An Appraisal

Citations

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Cited by:

  1. Naijing Huang & Yuqing Qi & Jie Xia, 2025. "China’s inflation forecasting in a data-rich environment: based on machine learning algorithms," Applied Economics, Taylor & Francis Journals, vol. 57(17), pages 1995-2020, April.
  2. Oscar Claveria & Enric Monte & Salvador Torra, 2014. "“A multivariate neural network approach to tourism demand forecasting”," IREA Working Papers 201417, University of Barcelona, Research Institute of Applied Economics, revised May 2014.
  3. Raquel M. Gaspar & Sara D. Lopes & Bernardo Sequeira, 2020. "Neural Network Pricing of American Put Options," Risks, MDPI, vol. 8(3), pages 1-24, July.
  4. Shovon Sengupta & Tanujit Chakraborty & Sunny Kumar Singh, 2024. "Forecasting CPI inflation under economic policy and geopolitical uncertainties," Post-Print hal-05056934, HAL.
  5. Barkan, Oren & Benchimol, Jonathan & Caspi, Itamar & Cohen, Eliya & Hammer, Allon & Koenigstein, Noam, 2023. "Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 39(3), pages 1145-1162.
  6. Marcos Vizcaíno-González & Juan Pineiro-Chousa & Jorge Sáinz-González, 2017. "Selecting explanatory factors of voting decisions by means of fsQCA and ANN," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2049-2061, September.
  7. Tea Šestanović & Josip Arnerić, 2021. "Can Recurrent Neural Networks Predict Inflation in Euro Zone as Good as Professional Forecasters?," Mathematics, MDPI, vol. 9(19), pages 1-13, October.
  8. Denis Shibitov & Mariam Mamedli, 2021. "Forecasting Russian Cpi With Data Vintages And Machine Learning Techniques," Bank of Russia Working Paper Series wps70, Bank of Russia.
  9. Soňa Benecká, 2026. "Forecasting Disaggregated Producer Prices: A Fusion of Machine Learning and Econometric Techniques," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(5), pages 2458-2501, August.
  10. E. Balatskiy V. & M. Yurevich A. & Е. Балацкий В. & М. Юревич А., 2018. "Прогнозирование инфляции: практика использования синтетических процедур // Inflation Forecasting: The Practice of Using Synthetic Procedures," Мир новой экономики // The world of new economy, Финансовый университет при Правительстве Российской Федерации // Financial University under The Governtment оf The Russian Federation, vol. 12(4), pages 20-31.
  11. Sengupta, Shovon & Chakraborty, Tanujit & Singh, Sunny Kumar, 2025. "Forecasting CPI inflation under economic policy and geopolitical uncertainties," International Journal of Forecasting, Elsevier, vol. 41(3), pages 953-981.
  12. Dmytro Krukovets, 2020. "Data Science Opportunities at Central Banks: Overview," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 249, pages 13-24.
  13. Tea Šestanović & Josip Arnerić, 2021. "Neural network structure identification in inflation forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 62-79, January.
  14. Lisa-Cheree Martin, 2019. "Machine Learning vs Traditional Forecasting Methods: An Application to South African GDP," Working Papers 12/2019, Stellenbosch University, Department of Economics.
  15. Mihaela Simionescu, 2025. "Machine Learning vs. Econometric Models to Forecast Inflation Rate in Romania? The Role of Sentiment Analysis," Mathematics, MDPI, vol. 13(1), pages 1-18, January.
  16. Muhammad Nadim Hanif & Khurrum S. Mughal & Javed Iqbal, 2018. "A Thick ANN Model for Forecasting Inflation," SBP Working Paper Series 99, State Bank of Pakistan, Research Department.
  17. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
  18. Jena, Pradyot Ranjan & Majhi, Ritanjali & Kalli, Rajesh & Managi, Shunsuke & Majhi, Babita, 2021. "Impact of COVID-19 on GDP of major economies: Application of the artificial neural network forecaster," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 324-339.
  19. Hasan ŞENGÜLER & Berat KARA, 2025. "Forecasting the Inflation for Budget Forecasters: An Analysis of ANN Model Performance in Türkiye," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 10(1), pages 58-91.
  20. Hyeongjun Kim & Hoon Cho & Doojin Ryu, 2022. "Corporate Bankruptcy Prediction Using Machine Learning Methodologies with a Focus on Sequential Data," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1231-1249, March.
  21. Arnerić Josip & Poklepović Tea & Teai Juin Wen, 2018. "Neural Network Approach in Forecasting Realized Variance Using High-Frequency Data," Business Systems Research, Paradigm, vol. 9(2), pages 18-34, July.
  22. Claveria, Oscar & Torra, Salvador, 2014. "Forecasting tourism demand to Catalonia: Neural networks vs. time series models," Economic Modelling, Elsevier, vol. 36(C), pages 220-228.
  23. Gilberto Boaretto & Marcelo C. Medeiros, 2023. "Forecasting inflation using disaggregates and machine learning," Papers 2308.11173, arXiv.org.
  24. Enja Erker, 2024. "Forecasting medical inflation in the European Union using the ARIMA model," Public Sector Economics, Institute of Public Finance, vol. 48(1), pages 39-56.
  25. Marcos Álvarez-Díaz & Rangan Gupta, 2015. "Forecasting the US CPI: Does Nonlinearity Matter?," Working Papers 201512, University of Pretoria, Department of Economics.
  26. Shovon Sengupta & Tanujit Chakraborty & Sunny Kumar Singh, 2023. "Forecasting CPI inflation under economic policy and geopolitical uncertainties," Papers 2401.00249, arXiv.org, revised Jul 2024.
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