Thematische Bibliographien / Economic modelling

Inhaltsverzeichnis

  1. Zeitschriftenartikel
  2. Dissertationen
  3. Bücher
  4. Buchteile
  5. Konferenzberichte
  6. Berichte der Organisationen

Auswahl der wissenschaftlichen Literatur zum Thema „Economic modelling“

Autor: Grafiati
Veröffentlicht am 4. Juni 2021
Zuletzt aktualisiert am 9. Juni 2025

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Zeitschriftenartikel zum Thema "Economic modelling"

1

Torgerson, D. J. "Economics Notes: Economic modelling before clinical trials." BMJ 325, no. 7355 (July 13, 2002): 98. http://dx.doi.org/10.1136/bmj.325.7355.98.

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Osborn, Denise R. "Macro-economic modelling." International Journal of Forecasting 6, no. 1 (January 1990): 140–41. http://dx.doi.org/10.1016/0169-2070(90)90105-k.

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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.

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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.

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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.

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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.

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Mills, Terence C. "Modelling Compositional Economic Data." Indian Economic Journal 55, no. 3 (October 2007): 99–115. http://dx.doi.org/10.1177/0019466220070307.

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Öller, Lars-Erik. "Modelling nonlinear economic relationships." International Journal of Forecasting 10, no. 1 (June 1994): 169–71. http://dx.doi.org/10.1016/0169-2070(94)90064-7.

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Blake, Adam. "Economic Modelling of Tourism." Tourism Economics 14, no. 4 (December 2008): 669–71. http://dx.doi.org/10.5367/000000008786440193.

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Blažević, Branko, and Adriana Jelušić. "Modelling regional economic development." Kybernetes 35, no. 7/8 (August 2006): 1190–202. http://dx.doi.org/10.1108/03684920610675265.

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Dissertationen zum Thema "Economic modelling"

1

Clements, Michael P. "Cointegration and dynamic econometric modelling." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334980.

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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.

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Oliinyk, V. "Modelling of ecology-economic systems." Thesis, Видавництво СумДУ, 2009. http://essuir.sumdu.edu.ua/handle/123456789/8234.

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Fatouros, Dimitrios Michael. "Mathematical modelling for international tax planning." Thesis, Imperial College London, 1998. http://hdl.handle.net/10044/1/7954.

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Clyde, W. C. "A study of exchange rate modelling." Thesis, University of Edinburgh, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.372198.

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Ferrante, Francesco. "Technical change and environmental policy modelling." Thesis, University of York, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283539.

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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.

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Dorsey, Ronald. "Economic and statistical modelling in cricket." Thesis, University of Salford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.492410.

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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.

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Metris, Aline. "Technical and economic modelling of biofilters." Thesis, Teesside University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.686444.

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Bücher zum Thema "Economic modelling"

1

Bolder, David Jamieson. Modelling Economic Capital. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95096-5.

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Colombo, Stefano. Spatial Economic Modelling. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-82787-7.

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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.

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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.

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George, Donald A. R. Economic modelling: An introduction. New York: B. Blackwell, 1988.

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Timo, Teräsvirta, ed. Modelling nonlinear economic relationships. Oxford [England]: Oxford University Press, 1993.

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Olajuwon, Olayide S., ed. Modelling Nigeria's economic development. [Ibadan]: Published by Ibadan University Press for the Centre for Econometric and Allied Research, University of Ibadan, 1985.

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Dag, Tjøstheim, and Granger, C. W. J. (Clive William John), 1934-2009, eds. Modelling nonlinear economic time series. Oxford: Oxford University Press, 2010.

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United Nations. Dept. of International Economic and Social Affairs, ed. Modelling of world economic development. New York: United Nations, 1988.

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Kreps, David M. Game theory and economic modelling. Oxford: Clarendon Press, 1991.

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Buchteile zum Thema "Economic modelling"

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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.

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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.

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Kunst, Natalia, Christopher Jackson, and Anna Heath. "Health Economic Modelling." In Value of Information for Healthcare Decision-Making, 3–30. Boca Raton: Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003156109-1.

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Bolder, David. "Introducing Economic Capital." In Modelling Economic Capital, 1–50. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-95096-5_1.

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Bolder, David. "Approximating Economic Capital." In Modelling Economic Capital, 281–340. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-95096-5_5.

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Bolder, David. "Seeking External Comparison." In Modelling Economic Capital, 667–757. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-95096-5_11.

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Bolder, David. "Computing Loan Impairments." In Modelling Economic Capital, 543–609. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-95096-5_9.

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Bolder, David. "Default-Probability Fundamentals." In Modelling Economic Capital, 403–61. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-95096-5_7.

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Bolder, David. "Measuring Derivative Exposure." In Modelling Economic Capital, 613–65. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-95096-5_10.

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Bolder, David. "Constructing a Practical Model." In Modelling Economic Capital, 53–128. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-95096-5_2.

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Konferenzberichte zum Thema "Economic modelling"

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Ozora Situngkir, Angelika Putri, Adilan Widyawan Mahdiyasa, Kurnia Novita Sari, and Udjianna Sekteria Pasaribu. "Modelling Peatland Fire Risk and Economic Losses in Indonesia." In 2025 5th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET), 1–6. IEEE, 2025. https://doi.org/10.1109/iraset64571.2025.11008022.

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Wang, Dalin, Weiyan Meng, Tianzuo Qu, Yu Yang, Yang Chen, and Ningling Wang. "Hybrid Modelling-based Economic Performance Diagnosis for Nuclear Second-Loop System." In 2024 3rd International Conference on Energy, Power and Electrical Technology (ICEPET), 1489–94. IEEE, 2024. http://dx.doi.org/10.1109/icepet61938.2024.10626613.

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Mendler, Friedrich, Nikolas Müller, Christopher Voglstätter, Tom Smolinka, Christopher Hebling, Friedrich Mendler, and Barbara Koch. "Modelling the Transformation of Hydrogen Ecosystems via Geo-Techno-Economic Optimization." In 2024 20th International Conference on the European Energy Market (EEM), 1–5. IEEE, 2024. http://dx.doi.org/10.1109/eem60825.2024.10609009.

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Singh, Akshita, Ramendra Singh, Davendra Kumar Chauhan, Ashok Kumar Shrivastava, and Haider Alabdeli. "Predictive Modelling of Economic Indicators using Machine learning and Data Analytics." In 2024 4th International Conference on Advancement in Electronics & Communication Engineering (AECE), 539–43. IEEE, 2024. https://doi.org/10.1109/aece62803.2024.10911486.

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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.

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Rakhmanovich, Ibragimov Ulmas, Rituparna Bhattacharjee, Nilesh Anute, and Giyosiddinov Abdurakhim Nasritdin Ugli. "Sustainable economics: The role of green technology in shaping future economic policies." In INTERNATIONAL CONFERENCE ON MODELLING STRATEGIES IN MATHEMATICS: ICMSM 2024, 060042. AIP Publishing, 2025. https://doi.org/10.1063/5.0276471.

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Stenis, Jan. "FLOW ANALYSIS AND ECONOMIC MODELLING THEORY." In 18th International Multidisciplinary Scientific GeoConference SGEM2018. Stef92 Technology, 2018. http://dx.doi.org/10.5593/sgem2018/5.3/s28.049.

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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.

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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.

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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.

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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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Berichte der Organisationen zum Thema "Economic modelling"

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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.

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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.

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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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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/10.18235/0011777.

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This paper develops and operationalizes the Integrated Economic-Environmental Modelling (IEEM) platform which integrates environmental data organized under the first international standard for environmental-economic accounting with a powerful economy-wide modelling approach. IEEM enables the ex-ante economic analysis of public policies and investment on the economy and the environment in a quantitative, comprehensive and consistent framework. IEEM elucidates the two-way interrelationships between the economy and environment, considering how economic activities depend on the environment as a source of inputs and as a sink for its outputs. In addition to standard economic impact indicators such as gross domestic product, income and employment, IEEM generates indicators that describe policy impacts on the use of environmental resources, wealth and environmental quality which together determine prospects for future economic growth and well-being. To illustrate the analytical capacity of IEEM, the model is calibrated with Guatemala's environmental-economic accounts and applied to analysis of its forest and fuelwood sector where negative health and environmental impacts arise from inefficient household fuelwood use.
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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.

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Phillips, David, and Kate Ogden. The economic and fiscal outlook: modelling the impact on local government. The IFS, January 2023. http://dx.doi.org/10.1920/ps.ifs.2023.0001.

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Bergin, Adele, Hailey Low, Stephen Millard, and Akhilesh Kumar Verma. Modelling Northern Ireland within the context of the all-island economy. ESRI/, January 2025. https://doi.org/10.26504/rs198.

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Northern Ireland occupies a unique position following Brexit and the Windsor Framework. It is part of the UK fiscal, welfare and monetary unions – where the main policy levers are mostly exercised at a UK national level – along with its national economic policies for devolved administrations and regions. Simultaneously, it remains within the EU Single Market for goods with Dual EU/UK regulatory regimes, participates in the Common Travel Area (CTA) between the United Kingdom and Ireland and is supported by a commitment to continue specified areas of North-South cooperation. The economic effects of this will continue to evolve over time. Whatever the background situation, it is clear that the economies of both Northern Ireland and Ireland can have a mutually beneficial impact on each other through improved economic outcomes on both sides of the border and enhanced interaction. This report discusses the development of a model for the Northern Ireland economy. The model can be used to produce economic forecasts and to examine the effects of economic policies and shocks. The framework captures the various linkages between the Northern Ireland economy and that of Ireland and so aids our wider understanding of how the Northern Ireland economy functions within the context of the wider all-island economy. The modelling framework also captures linkages to Great Britain and the international economy. By developing such a model and ensuring that the unique features of the Northern Ireland economy – that it is part of the United Kingdom while also being part of the EU Single Market – are built into the model, we can better understand the evolution of the Northern Ireland economy and what it means for the all-island economy. The model can be used to generate a baseline projection over the medium term for Northern Ireland and the all-island economy. GDP growth in Northern Ireland is expected to average around 1.2 per cent per annum over the medium term, similar to its longer-term historical trend, although it is expected to be somewhat higher in the short term. The challenge of relatively low productivity in Northern Ireland needs to be addressed through sustained productivity enhancing investment to improve long-term economic prospects and living standards. While expected growth in Northern Ireland is relatively modest compared to Ireland, it is slightly stronger than the wider UK, in part driven by stronger export growth bolstered by demand from Ireland and its relatively more favourable (than the UK) trading relationship with the European Union. With growth in Ireland expected to moderate in the coming years from previous extraordinarily high rates, our projections are for growth in the all-island economy to average around 2.2 per cent per annum over the medium term. With the period of high inflation rates over, real wage growth is expected to support increases in real personal disposable income in the all-island economy over the medium term. The modelling framework allows us to examine the effects of economic policies and shocks – both emanating from within Northern Ireland and from the outside world – on Northern Ireland, Ireland, the all-island economy, the UK and the international economy. The report considers a range of policy shocks and other external shocks. For example, the report develops a hypothetical scenario that is consistent with more devolution in Northern Ireland where income tax rates are increased and where the Northern Ireland Executive receives the revenue which it can then use for additional government spending and/or investment. This can also be seen as a proxy for the Northern Ireland Executive raising taxes on Northern Irish households in ways that it can do currently. In both scenarios, the overall impact on the level of Northern Irish output is positive but the impact is stronger and permanent in the case of higher government investment. The simulation results suggest that increased government spending leads to an increase (or ‘crowding-in’) of private sector investment which can enhance productivity. The stronger and permanent impact on overall output in the case of higher investment compared to higher spending highlights the importance of how the revenue is spent. In a similar vein, we examine scenarios where there is an increase in the block grant to Northern Ireland, which stimulates demand, employment and output with stronger impacts when the additional resources are used for government investment rather than government consumption spending. The report also considers a monetary policy shock, specifically an increase in the Bank of England interest rate and the simulation results suggest that the Northern Ireland economy is less sensitive to interest rate changes than the wider UK. The report also considers spillover effects from stronger growth in the Irish economy on the Northern Ireland economy and the impact on the all-island economy, focusing on positive shocks to Irish consumption and exports. The simulations reveal positive impacts in both cases on the Northern Ireland economy. Additionally, the report analyses the sensitivity of Northern Ireland's economy to global oil and gas price shocks. The simulations show a short-term spike in inflation that moderates over time, with output and investment recovering in the medium term after initially falling below the baseline.
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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.

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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.

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9

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.

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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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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.

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