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Moscardini, A. O., K. Lawler, T. Vlasova, and E. Merza. "The Future of Economic Modelling." Bulletin of Taras Shevchenko National University of Kyiv. Economics, no. 205 (2019): 20–26. http://dx.doi.org/10.17721/1728-2667.2019/205-4/3.
This is the third in a trilogy of papers concerning the reform of Economics. This paper tackles the subject of Economic modelling, If modelling is a representation of reality then the concept of “wha t is real” must be discussed. A description of the purpose of modelling and the processes involved in creating models then follows. The debate then switches to Economic modelling, its purpose and its effectiveness. Traditional Economic modelling is still a useful tool for understanding and teaching but Data Analytics and intelligent algorithms are better for economic predictions.
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McKenzie, Sandra, C. W. J. Granger, and T. Terasvirta. "Modelling Nonlinear Economic Relationships." Journal of the American Statistical Association 90, no. 432 (December 1995): 1491. http://dx.doi.org/10.2307/2291548.
Jansen, Dennis W., Clive W. J. Granger, and Timo Terasvirta. "Modelling Nonlinear Economic Relationships." Southern Economic Journal 61, no. 4 (April 1995): 1241. http://dx.doi.org/10.2307/1060764.
Aalabaf-Sabaghi, Morteza. "Economic Modelling and Inference." Journal of the Royal Statistical Society: Series A (Statistics in Society) 174, no. 1 (January 2011): 240. http://dx.doi.org/10.1111/j.1467-985x.2010.00676_2.x.
Clements, Michael P. "Cointegration and dynamic econometric modelling." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334980.
Biekpe, Nicholas Budeo. "Modelling currency volatility and returns." Thesis, Queen's University Belfast, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.264084.
Fatouros, Dimitrios Michael. "Mathematical modelling for international tax planning." Thesis, Imperial College London, 1998. http://hdl.handle.net/10044/1/7954.
Ferrante, Francesco. "Technical change and environmental policy modelling." Thesis, University of York, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283539.
Lundbergh, Stefan. "Modelling economic high-frequency time series." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 1999. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-637.
Dorsey, Ronald. "Economic and statistical modelling in cricket." Thesis, University of Salford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.492410.
Professional cricket is a sport rich in readily available data and provides fertile ground for the analysis of a wide range of economic issues. Despite this, until recent years there has been a relatively sparse amount of academic research into the economics of cricket compared to other sporting activities. This thesis considers four issues relevant to English professional cricket: player movement and exit behaviour; the impact of toss and weather on championship outcomes; the effect of central contracts on county productivity; relative age effects in professional cricket.
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Makriyannis, Elpida. "Intelligent systems for modelling economic policies." Thesis, University College London (University of London), 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.407455.
Brøgger-Jensen, Steffen, Simon Laursen Bager, Jesper Karup Pedersen, and Michael Munk Sørensen. Biodiversity and economic modelling. Copenhagen: Nordic Council of Ministers, 2018. http://dx.doi.org/10.6027/tn2018-531.
Renaud, Paul S. A. Applied Political Economic Modelling. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-83912-2.
Olofin, Sam Oladapo. Modelling Nigeria's economic development. [Ibadan]: Published by Ibadan University Press for the Centre for Econometric and Allied Research, University of Ibadan, 1985.
Carnot, Nicolas, Vincent Koen, and Bruno Tissot. "Modelling Behaviour." In Economic Forecasting, 103–32. London: Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230005815_5.
Rohatinski, Željko. "Modelling Economic Activity." In Time and Economics, 115–23. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61705-3_10.
Тези доповідей конференцій з теми "Economic modelling":
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Ashimov, A. A., B. T. Sultanov, Zh M. Adilov, Yu V. Borovskiy, N. Yu Borovskiy, and As A. Ashimov. "Parametrical Regulation of Economic Growth on the Basis of CGE Model of Economic Sectors." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.685-033.
Kamenev, Ivan, and Zhukova Aleksandra. "The Problem of Automating Economic Modelling." In 2022 15th International Conference Management of large-scale system development (MLSD). IEEE, 2022. http://dx.doi.org/10.1109/mlsd55143.2022.9934575.
Ashimov, Abdykappar A., Bahyt T. Sultanov, Zheksenbek M. Adilov, Yuriy V. Borovskiy, Dauren K. Suissinbayev, and Askar A. Ashimov. "Parametrical Regulation of Economic Growth based on the Jones Endogenous Model." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.735-038.
Felfoeldi-Szuecs, Nora, Peter Juhasz, Gabor Kuerthy, Janos Szaz, and Agnes Vidovics-Dancs. "Modelling Economic Crises In Hua He Framework." In 35th ECMS International Conference on Modelling and Simulation. ECMS, 2021. http://dx.doi.org/10.7148/2021-0095.
In our paper we model firms’ liquidity using the Hua He methodology. We investigate how cooperation of firms improve the possibilites of liquidity management. During a crisis, various effects identified in the literature hurt firms’ liquidity position and lead to increased bankruptcy risk. We may counterbalance these adverse effects by providing immediate cash transfers and granting periodic cash flow transfers or additional credit lines. Cooperating with peers pays off. The importance of liquidity transfer between agents is higher during a crisis than in normal economic environment. It contributes to a lower default rate the losses are more moderate as well. Several consequences can be drawn for policy makers how ameliorate resilience of agents.
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Diaz, A. "A Model For The Measurement Of Economic Freedom." In 22nd Conference on Modelling and Simulation. ECMS, 2008. http://dx.doi.org/10.7148/2008-0357.
de Lucas Santos, Sonia, Immaculada Alvarez Ayuso, and Maria Jesus Delgado Rodriguez. "Speed of Convergence And Economic Policy Instruments." In 23rd European Conference on Modelling and Simulation. ECMS, 2009. http://dx.doi.org/10.7148/2009-0310-0314.
Azzopardi, Leif. "Modelling interaction with economic models of search." In SIGIR '14: The 37th International ACM SIGIR Conference on Research and Development in Information Retrieval. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2600428.2609574.
Bothos, Ioannis, Vasileios Vlachos, Dimitris M. Kyriazanos, Ioannis Stamatiou, Konstantinos Georgios Thanos, Pantelis Tzamalis, Sotirios Nikoletseas, and Stelios C. A. Thomopoulos. "Modelling Cyber-Risk in an Economic Perspective." In 2021 IEEE International Conference on Cyber Security and Resilience (CSR). IEEE, 2021. http://dx.doi.org/10.1109/csr51186.2021.9527994.
Waller, Ephraim Nii Kpakpo, Pamela Delali Adablah, and Quist-Aphetsi Kester. "Markov Chain: Forecasting Economic Variables." In 2019 International Conference on Computing, Computational Modelling and Applications (ICCMA). IEEE, 2019. http://dx.doi.org/10.1109/iccma.2019.00026.
Nechaev, V., Володимир Миколайович Соловйов, and A. Nagibas. Complex economic systems structural organization modelling. Politecnico di Torino, 2006. http://dx.doi.org/10.31812/0564/1118.
One of the well-known results of the theory of management is the fact, that multi-stage hierarchical organization of management is unstable. Hence, the ideas expressed in a number of works by Don Tapscott on advantages of network organization of businesses over vertically integrated ones is clear. While studying the basic tendencies of business organization in the conditions of globalization, computerization and internetization of the society and the results of the financial activities of the well-known companies, the authors arrive at the conclusion, that such companies, as IBM, Boeing, Mercedes-Benz and some others companies have not been engaged in their traditional business for a long time. Their partner networks performs this function instead of them. The companies themselves perform the function of system integrators. The Tapscott’s idea finds its confirmation within the framework of a new powerful direction of the development of the modern interdisciplinary science – the theory of the complex networks (CN) [2]. CN-s are multifractal objects, the loss of multifractality being the indicator of the system transition from more complex state into more simple state. We tested the multifractal properties of the data using the wavelet transform modulus maxima approach in order to analyze scaling properties of our company. Comparative analysis of the singularity spectrumf(®), namely, the difference between maximum and minimum values of ® (∆ = ®max ¡ ®min) shows that IBM company is considerably more fractal in comparison with Apple Computer. Really, for it the value of ∆ is equal to 0.3, while for the vertically integrated company Apple it only makes 0.06 – 5 times less. The comparison of other companies shows that this dependence is of general character. Taking into consideration the fact that network organization of business has become dominant in the last 5-10 years, we carried out research for the selected companies in the earliest possible period of time which was determined by the availability of data in the Internet, or by historically later beginning of stock trade of computer companies. A singularity spectrum of the first group of companies turned out to be considerably narrower, or shifted toward the smaller values of ® in the pre-network period. The latter means that dynamic series were antipersistant. That is, these companies‘ management was rigidly controlled while the impact of market mechanisms was minimized. In the second group of companies if even the situation did changed it did not change for the better. In addition, we discuss applications to the construction of portfolios of stock that have a stable ratio of risk to return.
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Masset, Edoardo. Combining economic modelling and randomised controlled trials: An unexploited synergyCombining economic modelling and randomised controlled trials: An unexploited synergy. Edited by Radhika Menon. Centre of Excellence for Development Impact and Learning (CEDIL), 2021. http://dx.doi.org/10.51744/cmb3.
Over the last decade, many researchers have conducted randomised trials alongside economic models. The work of these researchers has shown that both approaches are strengthened by their combined use and the conclusions they lead to are full of policy implications. In the latest CEDIL Methods Brief, Edoardo Masset, Research Director, CEDIL Programme, uses three examples to offer tips on the application of modelling to evaluate development interventions and explore various policy questions. The brief shows that models and experiments should be seen as complementary, rather than as alternative approaches. This brief is based on the CEDIL Inception Paper No. 9, Structural Modelling in Policy Making, by Orazio Attanasio and Debbie Blair. This paper is available on the CEDIL website.
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Filipski, Mateusz J., Ernesto Tiburcio, Paul A. Dorosh, John F. Hoddinott, and Gracie Rosenbach. Modelling the economic impact of the Rohingya influx in Southern Bangladesh. Washington, DC: International Food Policy Research Institute, 2019. http://dx.doi.org/10.2499/p15738coll2.133397.
Banerjee, Onil, Martin Cicowiez, Renato Vargas, and Mark Horridge. The Integrated Economic-Environmental Modelling Framework: An Illustration with Guatemala's Forest and Fuelwood Sectors. Inter-American Development Bank, November 2016. http://dx.doi.org/10.18235/0000570.
Schuenemeyer, J. H., and L. J. Drew. Exploring the lower limits of economic truncation: modelling the oil and gas discovery process. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1990. http://dx.doi.org/10.4095/128118.
Bijlsma, Maarten J., and Ben Wilson. Modelling the socio-economic determinants of fertility: a mediation analysis using the parametric g-formula. Rostock: Max Planck Institute for Demographic Research, May 2017. http://dx.doi.org/10.4054/mpidr-wp-2017-013.
Saptsin, Vladimir, and Володимир Миколайович Соловйов. Relativistic quantum econophysics – new paradigms in complex systems modelling. [б.в.], July 2009. http://dx.doi.org/10.31812/0564/1134.
This work deals with the new, relativistic direction in quantum econophysics, within the bounds of which a change of the classical paradigms in mathematical modelling of socio-economic system is offered. Classical physics proceeds from the hypothesis that immediate values of all the physical quantities, characterizing system’s state, exist and can be accurately measured in principle. Non-relativistic quantum mechanics does not reject the existence of the immediate values of the classical physical quantities, nevertheless not each of them can be simultaneously measured (the uncertainty principle). Relativistic quantum mechanics rejects the existence of the immediate values of any physical quantity in principle, and consequently the notion of the system state, including the notion of the wave function, which becomes rigorously nondefinable. The task of this work consists in econophysical analysis of the conceptual fundamentals and mathematical apparatus of the classical physics, relativity theory, non-relativistic and relativistic quantum mechanics, subject to the historical, psychological and philosophical aspects and modern state of the socio-economic modeling problem. We have shown that actually and, virtually, a long time ago, new paradigms of modeling were accepted in the quantum theory, within the bounds of which the notion of the physical quantity operator becomes the primary fundamental conception(operator is a mathematical image of the procedure, the action), description of the system dynamics becomes discrete and approximate in its essence, prediction of the future, even in the rough, is actually impossible when setting aside the aftereffect i.e. the memory. In consideration of the analysis conducted in the work we suggest new paradigms of the economical-mathematical modeling.
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Soloviev, V. N., and Y. V. Romanenko. Economic analog of Heisenberg uncertainly principle and financial crisis. ESC "IASA" NTUU "Igor Sikorsky Kyiv Polytechnic Institute", May 2017. http://dx.doi.org/10.31812/0564/2463.
The Heisenberg uncertainty principle is one of the cornerstones of quantum mechanics. The modern version of the uncertainty principle, deals not with the precision of a measurement and the disturbance it introduces, but with the intrinsic uncertainty any quantum state must possess, regardless of what measurement is performed. Recently, the study of uncertainty relations in general has been a topic of growing interest, specifically in the setting of quantum information and quantum cryptography, where it is fundamental to the security of certain protocols. The aim of this study is to analyze the concepts and fundamental physical constants in terms of achievements of modern theoretical physics, they search for adequate and useful analogues in the socio-economic phenomena and processes, and their possible use in early warning of adverse crisis in financial markets. The instability of global financial systems depending on ordinary and natural disturbances in modern markets and highly undesirable financial crises are the evidence of methodological crisis in modelling, predicting and interpretation of current socio-economic conditions.
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Banerjee, Onil, Martin Cicowiez, and Renato Vargas. Integrating the Value of Natural Capital in Evidence-Based Policy Making. Inter-American Development Bank, December 2020. http://dx.doi.org/10.18235/0002900.
This paper describes how Natural Capital Accounting (NCA) can be integrated into economy wide analytical frameworks to enhance evidence based decision making. Examples from applications of the Integrated Environmental Economic Modelling (IEEM) Platform show how explicitly accounting for the contributions of the environment to the economy in economic forecasting can lead to substantially different policy recommendations, overcoming some of the scope limitations of traditional economic performance analysis. Furthermore, the paper describes how NCA can be integrated into more traditional economic performance measurements, such as the System of National Accounts and their indicators such as adjusted Gross Domestic Product and Genuine Savings. Integration of natural capital into economy-wide analytical frameworks leads to better policy uptake of research findings and it empowers policymakers to avoid short-sighted decisions, which, although they can generate short-term economic gain, can have adverse consequences for economic, social, and environmental sustainability in the long run.
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Verburg, Peter H., Žiga Malek, Sean P. Goodwin, and Cecilia Zagaria. The Integrated Economic-Environmental Modeling (IEEM) Platform: IEEM Platform Technical Guides: User Guide for the IEEM-enhanced Land Use Land Cover Change Model Dyna-CLUE. Inter-American Development Bank, September 2021. http://dx.doi.org/10.18235/0003625.
The Conversion of Land Use and its Effects modeling framework (CLUE) was developed to simulate land use change using empirically quantified relations between land use and its driving factors in combination with dynamic modeling of competition between land use types. Being one of the most widely used spatial land use models, CLUE has been applied all over the world on different scales. In this document, we demonstrate how the model can be used to develop a multi-regional application. This means, that instead of developing numerous individual models, the user only prepares one CLUE model application, which then allocates land use change across different regions. This facilitates integration with the Integrated Economic-Environmental Modeling (IEEM) Platform for subnational assessments and increases the efficiency of the IEEM and Ecosystem Services Modeling (IEEMESM) workflow. Multi-regional modelling is particularly useful in larger and diverse countries, where we can expect different spatial distributions in land use changes in different regions: regions of different levels of achieved socio-economic development, regions with different topographies (flat vs. mountainous), or different climatic regions (dry vs humid) within a same country. Accounting for such regional differences also facilitates developing ecosystem services models that consider region specific biophysical characteristics. This manual, and the data that is provided with it, demonstrates multi-regional land use change modeling using the country of Colombia as an example. The user will learn how to prepare the data for the model application, and how the multi-regional run differs from a single-region simulation.
