Relevant bibliographies by topics / Forecasting of economic processes

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Forecasting of economic processes'

Author: Grafiati
Published: 28 May 2022
Last updated: 30 July 2025

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Journal articles on the topic "Forecasting of economic processes"

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Clements, Michael P., and David F. Hendry. "Forecasting economic processes." International Journal of Forecasting 14, no. 1 (1998): 111–31. http://dx.doi.org/10.1016/s0169-2070(97)00057-5.

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Kuznetsova, Olga. "MARL: potential applications in socio-economic processes forecasting." Herald of CEMI 7, no. 3-4 (2024): 0. https://doi.org/10.33276/s265838870033401-4.

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This article describes one of the methods of artificial intelligence – Multiagent Reinforcement Learning (MARL). MARL is a modern and useful instrument for analyzing and forecasting the behavior of complex systems (agents). The first part of the article discusses the methods of artificial intelligence: machine learning, reinforcement learning and MARL. Second part contains detailed information about MARL, including description, limitations and application spheres. The third part provides the example of a MARL model for socio-economic forecasting. The conclusion gives the information about MARL
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Гажур and A. Gazhur. "The System Criteria Score of Basic Economic Structure: Territory, Infrastructure, Processes, Technological Processes, And Final Products." Economics of the Firm 2, no. 3 (2014): 35–39. http://dx.doi.org/10.12737/2494.

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Various approaches to forecasting the future economic development of
 civilization are explored. The author suggests a uniform criteria scoring method
 to evaluate the array of energy indicators, which characterize an economic
 unit as a basis for forecasting of energy-effective development.
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P.I., Bidyuk, Gozhyj O.P., Kalinina I.O., Danilov V.J., and Jirov O.L. "ADAPTIVE MODELING AND FORECASTING ECONOMIC AND FINANCIAL PROCESSES." Informatics and mathematical methods in simulation 9, no. 4 (2019): 231–50. http://dx.doi.org/10.15276/imms.v9.no4.231.

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Mičeková, Mária. "Another perspective on the forecasting of economic processes." Communications - Scientific letters of the University of Zilina 1, no. 2 (1999): 45–51. http://dx.doi.org/10.26552/com.c.1999.2.45-51.

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Wojciechowski, Łukasz, and Tadeusz Cisowski. "Modeling of Economic Forecasting of Manufacturing Processes in Transport Services Market." Applied Mechanics and Materials 791 (September 2015): 141–45. http://dx.doi.org/10.4028/www.scientific.net/amm.791.141.

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Kononenko, Zhanna, Roman Sharavara, and Olena Zinchenko. "STATISTICAL ANALYSIS OF TIME TRENDS IN FORECASTING ECONOMIC PROCESSES." Economic scope, no. 200 (May 9, 2025): 184–90. https://doi.org/10.30838/ep.200.184-190.

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The article is devoted to the study of statistical analysis of time trends as a key tool in forecasting economic processes. In the context of high dynamism in the modern economy and the limited predictability of market changes, the effective modeling of trends in economic indicators is of particular importance. The paper examines the sequence of actions in the process of statistical forecasting, starting from preliminary data processing to the selection of an appropriate time series model. The primary focus is on analyzing the trend component as a determining factor in the dynamics of economic
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Кладченко, Ірина. "ПРОГНОЗУВАННЯ ТРАЄКТОРІЇ НАЦІОНАЛЬНОГО ЕКОНОМІЧНОГО РОЗВИТКУ МЕТОДАМИ ГАРМОНІЙНОГО І СПЕКТРАЛЬНОГО АНАЛІЗУ". Economical 1, № 1(22) (2020): 115–31. http://dx.doi.org/10.31474/1680-0044-2020-1(22)-115-131.

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Improving of the methodological tools for the national economies behavior’s forecasting in the context of increasing the validity and analytical characteristics of state economic strategies in conditions of high volatility, lack of trend stability and non-stationary dynamics of external and internal socio-economic processes by implementing interdisciplinary methods of Fourier analysis and their adaptation to the specifics of the socio-economic systems’ functioning and development. Methodology. The forecasting’s targeting as an important independent stage in the process of analytical assessment
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Rustambekov, G., and F. Efendiev. "ECONOMIC PROCESSES IN THE LIGHT OF ENVIRONMENTAL REALITIES." Danish scientific journal, no. 71 (April 24, 2023): 11–13. https://doi.org/10.5281/zenodo.7878538.

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<strong>Abstract</strong> One of the urgent problems of our time is the scientific forecasting of economic processes. At the same time, it should be taken into account that the forecast is a specific type of knowledge, the development of which requires a multifaceted analysis and the development of a special theory. Finally, forecasting is a way of reflection, which can be called a leading reflection, in which consciousness goes ahead of the developing reality, as it were. <strong>Аннотация</strong> Одной из актуальных проблем современности&nbsp; является научное прогнозирование экономических
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Safarov, G. A., and M. D. Urazayeva. "Cost analysis and estimation in oil extraction." Azerbaijan Oil Industry, no. 04 (April 15, 2024): 47–53. http://dx.doi.org/10.37474/0365-8554/2024-04-47-53.

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The analysis is used in the economy to determine the regularities, essence, tendencies of social and economic processes, economic activities as a whole. Analysis in economics acts as a starting point for planning, forecasting and managing economic objects and the processes occurring there. Economic analysis is recognized for scientifically justifying decision-making and actions in the field of socio-economic policy, economics, and helping to select the best options for action.
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Dissertations / Theses on the topic "Forecasting of economic processes"

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Chevillon, Guillaume. "Multi-step estimation for forecasting economic processes." Thesis, University of Oxford, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.416533.

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Loll, Tina [Verfasser]. "Forecasting Economic Time Series using Locally Stationary Processes : A New Approach with Applications / Tina Loll." Frankfurt : Peter Lang GmbH, Internationaler Verlag der Wissenschaften, 2012. http://d-nb.info/1042413754/34.

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Ніконорова, О. В. "Парадокси в теорії ймовірностей". Thesis, Сумський державний університет, 2018. http://essuir.sumdu.edu.ua/handle/123456789/67026.

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Сучасна людина, яка живе в умовах постійних змін, практично кожного дня зустрічається з практичним застосуванням теорії ймовірностей. Економічна інформація також не є досить точною і часто має випадковий характер, отже знайомство з елементами теорії ймовірностей є дуже важливим для сучасних економістів. Дуже важко уявити сучасні дослідження і прогнозування економічних процесів без регресійного аналізу, економетричного моделювання, трендових моделей та інших методів.
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Hunt, Julian David. "Integration of rationale management with multi-criteria decision analysis, probabilistic forecasting and semantics : application to the UK energy sector." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:2cc24d23-3e93-42e0-bb7a-6e39a65d7425.

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This thesis presents a new integrated tool and decision support framework to approach complex problems resulting from the interaction of many multi-criteria issues. The framework is embedded in an integrated tool called OUTDO (Oxford University Tool for Decision Organisation). OUTDO integrates Multi-Criteria Decision Analysis (MCDA), decision rationale management with a modified Issue-Based Information Systems (IBIS) representation, and probabilistic forecasting to effectively capture the essential reasons why decisions are made and to dynamically re-use the rationale. In doing so, it allows e
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Odendahl, Florens. "Essays in economic forecasting." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/664016.

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This thesis consists of three chapters on forecasting techniques in economics. In chapter 1, I use copulas to estimate multivariate density forecasts based on univariate densities from survey data. Survey-based predictions are often competitive to time series models in their forecasting performance but have a univariate focus and my estimation strategy exploits the information in the surveys’ marginal densities. I subsequently demonstrate the importance of the multivariate aspect for forecasters. In chapter 2, we propose novel tests for forecast rationality, which are robust under the presence
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Souza, André B. M. "Essays in economic forecasting." Doctoral thesis, Universitat Pompeu Fabra, 2021. http://hdl.handle.net/10803/672997.

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This dissertation consists of two independent chapters on economic and financial forecasting. The first chapter introduces a nonlinear forecasting framework that combines forecasts of the sign and absolute value of a time series into conditional mean forecasts. In contrast to linear models, the proposed framework allows different predictors to separately impact the sign and absolute value of the target series. An empirical application using the FRED-MD dataset shows that forecasts from the proposed model substantially outperform linear forecasts for series that exhibit persistent volati
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Acar, Emmanuel. "Economic evaluation of financial forecasting." Thesis, City University London, 1993. http://openaccess.city.ac.uk/8256/.

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This thesis examines the economic evaluation of forecasting strategies based on past prices, bringing together academics and practitioners techniques Forecasting methods based on past prices are convex and path-dependent dynamic strategies Therefore, they must be able to profitably exploit positive serial dependences in financial prices The most important measure of financial forecasting ability is the rate of return achieved by the predictor The expected return of forecasting strategies is first investigated by applying stochastic modelling Then, the presence of serial dependences in financia
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Bezsmertna, Julia. "Modern methods of economic forecasting." Thesis, Київський національний університет технологій та дизайну, 2019. https://er.knutd.edu.ua/handle/123456789/14350.

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Marrocu, Emanuela. "Modelling identification and forecasting nonlinear processes." Thesis, University of Warwick, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340086.

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Marsilli, Clément. "Mixed-Frequency Modeling and Economic Forecasting." Thesis, Besançon, 2014. http://www.theses.fr/2014BESA2023/document.

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La prévision macroéconomique à court terme est un exercice aussi complexe qu’essentiel pour la définition de la politique économique et monétaire. Les crises financières récentes ainsi que les récessions qu’ont endurées et qu’endurent aujourd’hui encore, en ce début d’année 2014, nombre de pays parmi les plus riches, témoignent de la difficulté d’anticiper les fluctuations économiques, même à des horizons proches. Les recherches effectuées dans le cadre de la thèse de doctorat qui est présentée dans ce manuscrit se sont attachées à étudier, analyser et développer des modélisations pour la prév
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Books on the topic "Forecasting of economic processes"

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Godley, Wynne. Seven unsustainable processes: Medium-term prospects and policies for the United States and the world. Jerome Levy Economics Institute, 1999.

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Pauhofová, Iveta. Adaptačné procesy a pulzujúca ekonomika: V cykle Paradigmy zmien v 21. storočí = Adaptation processes and pulsating economy : paradigms in the cycle of changes in the 21st century. Ekonomický ústav Slovenskej akadémie vied, 2016.

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Konishi, Toru. Stochastic trends and short-run relationships between financial variables and real activity. National Bureau of Economic Research, 1993.

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Koop, Gary. Forecasting and estimating multiple change-point models with an unknown number of change points. Federal Reserve Bank of New York, 2004.

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Chauvet, Marcelle. Markov switching in disaggregate unemployment rates. Federal Reserve Bank of New York, 2001.

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Vollmer, Sebastian. A Contribution to the Empirics of Economic and Human Development. Peter Lang International Academic Publishers, 2018.

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Fogel, Robert William. Economic growth, population theory, and physiology: The bearing of long-term processes on the making of economic policy. National Bureau of Economic Research, 1994.

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Shumilina, Vera, Galina Krokhicheva, Tat'yana Sidorina, et al. Socio-economic and legal problems of modern society. AUS PUBLISHERS, 2022. http://dx.doi.org/10.26526/monography_61e7f12a5a16c6.22843996.

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The problems of the socio-economic development of Russia, as well as the problems associated with law enforcement that exist today, are associated with many factors that have their roots since the collapse of the Soviet Union, as well as a result of subsequent reforms, crises, total economic changes and other factors ... Currently, the pandemic is having a big impact.&#x0D; In addition, the development of modern society is influenced by the processes of globalization and digitalization, which resulted in a reassessment of values, changes in education, culture, and legal aspects of society.&#x0
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Spath, Pamela L. Update of hydrogen from biomass: Determination of the delivered cost of hydrogen : milestone completion report. National Renewable Energy Laboratory, 2003.

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Christiano, Lawrence J. Unit roots in real GNP: Do we know and do we care? National Bureau of Economic Research, 1989.

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Book chapters on the topic "Forecasting of economic processes"

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Neusser, Klaus. "Forecasting Stationary Processes." In Springer Texts in Business and Economics. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32862-1_3.

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Neusser, Klaus. "Forecasting Stationary Processes." In Springer Texts in Business and Economics. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-88838-0_3.

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Lütkepohl, Helmut. "Forecasting Vector Stochastic Processes." In Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-61584-9_3.

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Krolzig, Hans-Martin. "Forecasting MS-VAR Processes." In Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-51684-9_5.

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Lütkepohl, Helmut. "Forecasting Contemporaneously Aggregated Known Processes." In Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-61584-9_4.

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Lütkepohl, Helmut. "Forecasting Contemporaneously Aggregated Estimated Processes." In Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-61584-9_5.

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Lütkepohl, Helmut. "Forecasting Temporally and Contemporaneously Aggregated Known Processes." In Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-61584-9_6.

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Bidyuk, Peter, Aleksandr Gozhyj, Yoshio Matsuki, Natalia Kuznetsova, and Irina Kalinina. "Modeling and Forecasting Economic and Financial Processes Using Combined Adaptive Models." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54215-3_25.

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Elkina, Olga S., and Stanislav E. Elkin. "Modeling and Forecasting Social Processes in the Labor Market." In Finance, Economics, and Industry for Sustainable Development. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56380-5_26.

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Sharko, Marharyta, Nestor Shpak, Olga Gonchar, Kateryna Vorobyova, Olena Lepokhina, and Juliya Burenko. "Methodological Basis of Causal Forecasting of the Economic Systems Development Management Processes Under the Uncertainty." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54215-3_27.

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Conference papers on the topic "Forecasting of economic processes"

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Dardor, Dareen, Daniel Fl�rez-Orrego, Reginald Germanier, Manuele Margni, and Fran�ois Mar�chal. "On the Economic Uncertainty and Crisis Resiliency of Decarbonization Solutions for the Aluminium Industry." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.116664.

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The aluminium industry emits approximately 1.1 billion tonnes of CO2-eq annually, contributing about 2% of global industrial emissions. Decarbonization pathways aim to achieve net-zero emissions by 2050, but this requires making decisions today for technologies having lifetimes of 20 � 25 years, based on uncertain economic assumptions, particularly given the volatility of energy prices. Traditional price forecasting models often fail to anticipate major disruptions, such as the 2022 energy crisis. This work applies Monte-Carlo Analysis (MCA) to evaluate the financial stability of decarbonizati
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Zaroula, Michaela C., Emilia M. Kondili, and John K. Kaldellis. "An Integrated Approach for the Sustainable Water Resources Optimization." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.196197.

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Ensuring access to clean water, preserving water reserves, and meeting energy needs are fundamental for sustainability and a priority for global organizations like the UN and EU. The Mediterranean, particularly Greece, faces severe water imbalances due to rising demand, prolonged droughts, and seasonal tourism pressure. This over-exploitation of water resources threatens agriculture, employment, and regional sustainability. Addressing these challenges, this study analyzes the water-energy nexus in high-stress areas and develops an optimization model for sustainable water resource management. T
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Mengov, George, Iliyan Nenov, Kaloyan Ganev, and Ralitsa Simeonova-Ganeva. "Neurocomputational Forecasting of Economic Shocks." In 2024 IEEE 12th International Conference on Intelligent Systems (IS). IEEE, 2024. http://dx.doi.org/10.1109/is61756.2024.10705270.

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Gupta, Arhaan, Kirana Kumar, V. Asha, and S. Naveen Kumar. "Machine Learning in Economic Forecasting: A Comprehensive Review." In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, 2024. https://doi.org/10.1109/ic3i61595.2024.10828960.

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Kunitsyn, V., Tatyana Novikova, and A. Shpinev. "FORECASTING THE POPULATION OF VORONEZH CITY IN 2030." In CHALLENGING ISSUES IN SYSTEMS MODELING AND PROCESSES. FSBE Institution of Higher Education Voronezh State University of Forestry and Technologies named after G.F. Morozov, 2025. https://doi.org/10.58168/cismp2024_57-59.

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This article is dedicated to forecasting the population of Voronezh city in 2030. The main methods of population forecasting are considered, including trend extrapolation methods, analysis of migration flows, and models of socio-economic development. Special attention is paid to accounting for population growth dynamics, migration processes, demographic characteristics, and the impact of socio-economic factors. A comprehensive approach to forecasting the population of Voronezh city in 2030 is proposed, which will allow for the consideration of various factors and contribute to the development
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Grishchenko, Marina, and Mariya Tsvil. "FORECASTING THE ECONOMIC PROCESS USING ECONOMETRIC ANALYSIS." In Economy of Russia: problems, trends, forecasts. AUS PUBLISHERS, 2021. http://dx.doi.org/10.26526/conferencearticle_61cc296be8dee5.11017419.

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The article considers the necessity of using econometric research methods in the analysis and forecasting of economic processes and phenomena. A concrete example of managerial decision making examined in the given article is based on the assumption of an econometric model and it’s ability to analyze the effectiveness of applying different types of advertising on the company's activities
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Orlova, Irina. "Modelling and forecasting the dynamics of economic processes using the Prophet package." In Systems Analysis in Economics - 2020. Moscow, "Science" Publishing House, 2021. http://dx.doi.org/10.33278/sae-2020.book1.428-429.

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Petrov, B., and V. Antsiferova. "RESEARCH AND DEVELOPMENT OF SALES FORECAST MODELS BASED ON CORRELATION AND REGRESSION." In CHALLENGING ISSUES IN SYSTEMS MODELING AND PROCESSES. FSBE Institution of Higher Education Voronezh State University of Forestry and Technologies named after G.F. Morozov, 2025. https://doi.org/10.58168/cismp2024_122-125.

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The paper discusses the issues of forecasting financial activity in the context of the strategic development of the organization. It also presents in detail one of the economic and mathematical algorithms used to forecast the financial results of the organization.
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Hoichuk, Vasyl. "THE USE OF ARTIFICIAL INTELLIGENCE FOR ASSESSING AND FORECASTING HUMAN CAPITAL DEVELOPMENT." In Transformation of the Economic System in the Modern Context: Processes, Strategies, Technologies. Publishing House “Baltija Publishing”, 2024. http://dx.doi.org/10.30525/978-9934-26-447-4-2.

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Trofymchuk, Oleksandr. "The Features of Application of the Integrated Approach to Forecasting Ecology-Economic Processes." In 2020 IEEE 2nd International Conference on System Analysis & Intelligent Computing (SAIC). IEEE, 2020. http://dx.doi.org/10.1109/saic51296.2020.9239148.

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Reports on the topic "Forecasting of economic processes"

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Iurasova, Olga, and Jelena Dementjeva. Impact of Manufacturing Sector Development on Economic Growth. Vilnius Business College, 2024. https://doi.org/10.57005/ab.2024.3.3.

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This study presents a model of GDP development based on production sectors. Analysis of actual data reveals the presence of several oscillatory processes, which are associated with the heterogeneity of investments and the aggregation of various production processes with their unique characteristics in statistical data. Fluctuations in aggregated macroeconomic indicators result from the superposition of different oscillations and do not exhibit strictly defined periods, particularly for long-term fluctuations. The model indicates that these fluctuations are asymmetrical relative to extreme poin
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Galeano-Ramírez, Franky Juliano, Nicolás Martínez-Cortés, Carlos D. Rojas-Martínez, and Margaret Guerrero. Nowcasting Colombian Economic Activity: DFM and Factor-MIDAS approaches. Banco de la República, 2021. http://dx.doi.org/10.32468/be.1168.

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Economic policy decision-making requires constantly assessing the state of economic activity. However, this is not an easy task: official figures have significant lags, and the timely information is usually partial and has different frequencies. This paper applies two types of short-term forecasting methodologies (Factor-MIDAS and DFM) for Colombian economic activity involving information with mixed frequencies. We present a heuristic process to select relevant variables, and we evaluate the proposed models' fits by comparing them with traditional forecasting methodologies. Overall, DFM and Fa
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Kucherova, Hanna, Anastasiia Didenko, Olena Kravets, Yuliia Honcharenko, and Aleksandr Uchitel. Scenario forecasting information transparency of subjects' under uncertainty and development of the knowledge economy. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4469.

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Topicality of modeling information transparency is determined by the influence it has on the effectiveness of management decisions made by an economic entity in the context of uncertainty and information asymmetry. It has been found that information transparency is a poorly structured category which acts as a qualitative characteristic of information and at certain levels forms an additional spectrum of properties of the information that has been adequately perceived or processed. As a result of structuring knowledge about the factor environment, a fuzzy cognitive model of information transpar
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Gómez Loscos, Ana, Miguel Ángel González Simón, and Matías José Pacce. Short-term real-time forecasting model for spanish GDP (Spain-STING): new specification and reassessment of its predictive power. Banco de España, 2024. http://dx.doi.org/10.53479/36137.

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The predictive power of short-term forecasting models was impaired by the increased volatility observed in most economic indicators following the outbreak of COVID-19. This paper sets out a revision of the Spain-STING model (one of the tools used by the Banco de España for short-term forecasts of quarter-on-quarter GDP growth) with a view to improving its predictive power in the wake of the pandemic. In particular, the revision entails three main changes: (i) the correlation between the indicators included in the model and the estimated common component is now coincident for all of the indicat
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Snowberg, Erik, Justin Wolfers, and Eric Zitzewitz. Prediction Markets for Economic Forecasting. National Bureau of Economic Research, 2012. http://dx.doi.org/10.3386/w18222.

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Higgins, Patrick, Tao Zha, and Karen Zhong. Forecasting China's Economic Growth and Inflation. National Bureau of Economic Research, 2016. http://dx.doi.org/10.3386/w22402.

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Zarnowitz, Victor. The Record and Improvability of Economic Forecasting. National Bureau of Economic Research, 1986. http://dx.doi.org/10.3386/w2099.

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Ponce-Parra, Montserrat. Improvements for the Iowa Economic Forecasting Model. Iowa State University, 2022. http://dx.doi.org/10.31274/cc-20240624-884.

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Giacomini, Raffaella. Economic theory and forecasting: lessons from the literature. Cemmap, 2014. http://dx.doi.org/10.1920/wp.cem.2014.4114.

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Nenov, Iliyan, George Mengov, Kaloyan Ganev, and Ralitsa Simeonova-Ganeva. Neurocomputational Economic Forecasting with a Handful of Data. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, 2021. http://dx.doi.org/10.7546/crabs.2021.10.11.

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