Articoli di riviste: "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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3

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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5

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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6

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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7

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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8

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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9

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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10

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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11

Puu, T. "Continuous economic space modelling." Annals of Regional Science 43, no. 1 (January 9, 2008): 5–25. http://dx.doi.org/10.1007/s00168-007-0200-0.

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12

Sørensen, Jan Rose. "Applied political economic modelling." European Journal of Political Economy 6, no. 3 (December 1990): 442–44. http://dx.doi.org/10.1016/0176-2680(90)90073-r.

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13

Jefferson, Tom, and Vittorio Demicheli. "Economic Evaluation of Influenza Vaccination and Economic Modelling." PharmacoEconomics 9, Supplement 3 (1996): 67–72. http://dx.doi.org/10.2165/00019053-199600093-00015.

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14

Malek, Mo. "Economic Evaluation of Influenza Vaccination and Economic Modelling." PharmacoEconomics 9, Supplement 3 (1996): 73–74. http://dx.doi.org/10.2165/00019053-199600093-00016.

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15

Mills, Terence C., and N. F. R. Crafts. "Modelling Trends in Economic History." Statistician 45, no. 2 (1996): 153. http://dx.doi.org/10.2307/2988404.

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16

Szczerbicki, Edward, and Maciej Waszczyk. "Modelling of Complex Economic Systems." International Journal of Enterprise Information Systems 2, no. 1 (January 2006): 67–78. http://dx.doi.org/10.4018/jeis.2006010105.

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17

Düppe, Till. "German Fears in Economic Modelling." OEconomia, no. 12-1 (March 1, 2022): 1–26. http://dx.doi.org/10.4000/oeconomia.12457.

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18

Gardini, Laura, Fabio Lamantia, Davide Radi, Ferenc Szidarovszky, and Fabio Tramontana. "Nonlinear dynamics in economic modelling." Decisions in Economics and Finance 44, no. 2 (October 18, 2021): 485–87. http://dx.doi.org/10.1007/s10203-021-00353-8.

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19

Brennan, Alan, and Ron Akehurst. "Modelling in Health Economic Evaluation." PharmacoEconomics 17, no. 5 (May 2000): 445–59. http://dx.doi.org/10.2165/00019053-200017050-00004.

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20

Clements, Michael P., and David F. Hendry. "Macro-Economic Forecasting and Modelling." Economic Journal 105, no. 431 (July 1995): 1001. http://dx.doi.org/10.2307/2235166.

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21

Silva, Afonso, Bruno Augusto, Sandra Rafael, Johnny Reis, Myriam Lopes, Sérgio Costa, and Carlos Borrego. "Modelling of Regional Economic Metabolism." Climate 8, no. 4 (April 2, 2020): 52. http://dx.doi.org/10.3390/cli8040052.

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The current linear economic system has led Europe to unsustainable development, aggravating several issues, such as climate change, limitation of resources, and pollution. As a sustainable alternative, circular economy (CE) has been promoted around the world. This economic system allows for the maximization of a product’s life, thus decreasing its environmental impact and increasing its value. The main goal of this work is to scrutinise the concepts of CE over time, from the beginning of the concept, to its implementation in Europe and its application in Portugal. In addition, the requirement for strategies that led to studies on regional urban metabolism are addressed. Another goal is to examine Portugal and see how the country is dealing with the implementation of strategies for CE, moving from concept to practice. This part of the work resulted in the creation of the REMET-UA model, a tool to assess the regional economic metabolism, which also has the potential to evaluate synergies of materials in terms of fluxes between regions, maximizing the amount of information available at this scale for municipalities and enterprises to be used, having taken into account the purpose of circular economy. The results showed that REMET-UA is fully operational and corresponds to the goal for which the model was made. Future developments have been identified and are underway to improve the model and bring it as close to reality as possible.

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22

Kravtsova, L. V. "Mathematical modelling in economic processes." Information Technologies in Education, no. 1 (April 12, 2008): 60–65. http://dx.doi.org/10.14308/ite000008.

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23

Brännäs, Kurt, Clive W. J. Granger, Timo Teräsvirta, Kurt Brannas, and Timo Terasvirta. "Modelling Non-Linear Economic Relationships." Scandinavian Journal of Economics 96, no. 4 (December 1994): 576. http://dx.doi.org/10.2307/3440801.

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24

Kuorikoski, Jaakko, Aki Lehtinen, and Caterina Marchionni. "Economic Modelling as Robustness Analysis." British Journal for the Philosophy of Science 61, no. 3 (September 1, 2010): 541–67. http://dx.doi.org/10.1093/bjps/axp049.

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25

Roberts, Colin J. "AUSTRALASIAN ECONOMIC MODELLING CONFERENCE 1992." Journal of Economic Surveys 7, no. 2 (June 1993): 203–4. http://dx.doi.org/10.1111/j.1467-6419.1993.tb00165.x.

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26

Inadomi, John M. "Decision analysis and economic modelling." European Journal of Gastroenterology & Hepatology 16, no. 6 (June 2004): 535–42. http://dx.doi.org/10.1097/00042737-200406000-00005.

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27

Shepherd, David, and Francis K. C. Shi. "Economic Modelling with Fuzzy Logic." IFAC Proceedings Volumes 31, no. 16 (June 1998): 435–40. http://dx.doi.org/10.1016/s1474-6670(17)40518-0.

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28

Serra, Pablo. "Mathematical modelling and economic evaluation." Mathematical Modelling 8 (1987): 718–22. http://dx.doi.org/10.1016/0270-0255(87)90676-2.

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29

Tauber, S. "Economic modelling by lump algebras." Mathematical and Computer Modelling 10, no. 5 (1988): 389–93. http://dx.doi.org/10.1016/0895-7177(88)90142-2.

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30

Heidinger, Philipp, Jürgen Dornstädter, and Axel Fabritius. "HDR economic modelling: HDRec software." Geothermics 35, no. 5-6 (October 2006): 683–710. http://dx.doi.org/10.1016/j.geothermics.2006.10.005.

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31

McAleer, Michael. "Modelling economic and environmental systems." Environmental Modelling & Software 20, no. 11 (November 2005): 1365–67. http://dx.doi.org/10.1016/j.envsoft.2004.09.009.

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32

Maycock, G. "Accident modelling and economic evaluation." Accident Analysis & Prevention 18, no. 2 (April 1986): 169–74. http://dx.doi.org/10.1016/0001-4575(86)90061-8.

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33

Hy, Ronald John. "Economic modelling and public policy." International Journal of Public Administration 18, no. 1 (January 1995): 1–11. http://dx.doi.org/10.1080/01900699508524996.

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34

Becker, William E., and David M. Kreps. "Game Theory and Economic Modelling." Journal of Economic Education 23, no. 2 (1992): 189. http://dx.doi.org/10.2307/1183259.

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35

Gottinger, Hans W. "Artificial intelligence and economic modelling." Expert Systems 8, no. 2 (May 1991): 99–105. http://dx.doi.org/10.1111/j.1468-0394.1991.tb00257.x.

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36

Lindfield, G. "Economic modelling and computer programming." Information and Software Technology 31, no. 5 (June 1989): 283. http://dx.doi.org/10.1016/0950-5849(89)90010-4.

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37

Manfredi, Piero, and Luciano Fanti. "Cycles in dynamic economic modelling." Economic Modelling 21, no. 3 (May 2004): 573–94. http://dx.doi.org/10.1016/j.econmod.2003.08.003.

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38

Jakutis, Algirdas. "MODELLING OF ECONOMICS REGULATIONS." Technological and Economic Development of Economy 10, no. 3 (September 30, 2004): 102–8. http://dx.doi.org/10.3846/13928619.2004.9637665.

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Abstract (sommario):

Economics may be presented in the form of corroborated rules. Economics may be defined as a science consisting of economic principles, laws, features, criteria, limitations, axioms, etc. Each listed entity may be divided into categories. Categories (category ‐ instruction) are theoretical concepts meaning the most important aspects of restoration of reality. Categories are forms giving theoretical meaning to practical experience. Categories give names to economic phenomena. Categories are presented and analysed in textbooks, reference books, and encyclopaedias. Categories are interconnected since the economic phenomena reflected by the categories are mutually connected. There are numerous relations among categories. These relations are like a network or a tree since one category is connected with several other categories, whereas the latter, in their own turn, are connected with the other categories. We may analyze the category “investment” as an example. The term “investments” is defined as the putting of capital into an enterprise. Capital is everything that has been created by the labour of people and it is being used for the manufacture of a final product. An enterprise is the production or commercial economic entity. Further, the following categories should be defined: labour, benefit, a product, production, commerce, and economy. Then the categories included in the above mentioned categories should be defined. A man models economic corroborated rules by means of a computer. The computer can find the main compositions to systematise the tremendous number thereof, quickly find necessary information, group corroborated rules, register and analyse them, and store information. However, the creation of a suitable program is quite a long and hard process. Corroborated rules which are regular and stable (are not variable) in real life may be simulated by a computer. A computer cannot apply the observation, verification, and genetic methods since it is only capable to analyse available information. Information changes very quickly and for this reason the results obtained are not accurate. The following distribution of work is possible: a man models separate (single) and couple compositions. The compositions consisting of three and a larger number of compounds are simulated by a computer. The identification of corroborated rules means that the types of corroborated rules taken out of the known economic text must be identified: laws, principles, features, and so on. It is quite easy to perform this work without using a computer provided that the volume of work is not large. However sometimes some doubts arise: to which type should a certain corroborated rule be attributed. Doubts are caused by the insufficiently accurate and simple definition of types of corroborated rules. While computerising the identification of economic corroborated rules it is important to accurately define the types of economic corroborated rules, then make algorithms and programs for the identification of each type of a corroborated rule. Identification enables to assess an economic text. The text the corroborated rules of which are presented in a certain order is acceptable for a reader. Consistent presentation facilitates the understanding of a text.

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Zitko, Mislav. "Models, fictions and explanations: A study in historical epistemology of economics." Filozofija i drustvo 24, no. 4 (2013): 84–101. http://dx.doi.org/10.2298/fid1304084z.

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This paper examines the standard criticism of the neoclassical economic theory that takes mathematical formalism and the practice of modelling as the most problematic aspect of orthodox economics. The aim of the paper is to explore the epistemic properties of models in science (particularly in economics), and to incorporate the insights from the recent debates in the philosophy of science into the framework of historical epistemology of economics. The main claim of this paper is that history is important for understanding how economic models operate and why have they been accepted as legitimate instruments of inquiry in economic theory. However, since modelling practice clearly is not limited to neoclassical economic theory, the difference between economic orthodoxy and heterodoxy has to be explained in a different way. The paper argues that the theory of fiction can provide an important clue inasmuch as the epistemological and political commitments are a part of the story that underpins the modelling practice in economics.

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Байхонов, Баходирхан, and Bahodirhan Bayhonov. "ECONOMIC MATHEMATIC-STATISTICAL MODELLING IN DISTRIBUTION OF INVESTMENTS IN UZBEKISTAN." Construction and Architecture 5, no. 3 (November 26, 2017): 183–87. http://dx.doi.org/10.12737/article_59cd06825bf906.44843817.

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The main purpose in attracting and using of investments is an achievement of leading positions in economic development and supply world’s market with local products of Uzbekistan. There is no doubt that to achieve such targets needs accordance plan and forecasting based on scientific researches. Hence, here in this article were given conclusions of effective using of investments on the basis forecast related to econometrics modeling of such indexes as, GNP, basic funds, conditions of industrial investments, also, inflation rates and employment in the country

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41

Marhasova, V. G., O. S. Sakun, and T. V. Klymenko. "MODELLING AND PROGNOSTICATION OF MACROECONOMIC DYNAMICS OF PROVIDING THE ECONOMIC SUSTAINABILITY TO THE ECONOMIC SECURITY THREATS." SCIENTIFIC BULLETIN OF POLISSIA 1, no. 1(9) (2017): 43–54. http://dx.doi.org/10.25140/2410-9576-2017-1-1(9)-43-54.

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42

Lakić, Dragana, Ivana Stević, Marina Odalović, and Ivana Tadić. "Modelling in economic evaluations of medicines." Arhiv za farmaciju 71, no. 4 (2021): 354–64. http://dx.doi.org/10.5937/arhfarm71-32404.

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Economic evaluation in health (also known as pharmacoeconomic in case of medicines) identifies, measures, and values costs and outcomes of alternative healthcare technologies, and can be performed alongside controlled clinical trials, but analytical modelling is usually used. Decision trees and Markov models are the two most common approaches used in economic evaluation. The biggest advantages of a decision tree are clarity, simplicity, and straightforwardness. On the other hand, the main advantage of the Markov model is its ability to incorporate complex events into the simulation, which is practically impossible to do with a decision tree. Reimbursement policy in Serbia mandatorily incorporates economic evaluations to promote availability and accessibility of the prescription medicines. To show current pharmacoeconomic value of a medicine, budget impact analysis and the cost-effectiveness analysis should be included. The latter should be conducted using appropriate modelling techniques. However, since no official methodological guidelines about the modelling and economic analysis exist, the submissions by marketing authorization holders vary greatly. The future of pharmacoeconomic modelling depends on the research area of interest, with new frameworks and approaches being developed.

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43

Ball, Michael, and Andrew Wood. "Some Comments on Modelling Economic Trends." Statistician 45, no. 2 (1996): 161. http://dx.doi.org/10.2307/2988405.

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44

Xepapadeas, A. "Economic modelling for groundwater resources management." Water Supply 5, no. 6 (December 1, 2005): 41–52. http://dx.doi.org/10.2166/ws.2005.0048.

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Conceptual models related to the management of groundwater resources are presented. Socially optimal and privately optimal, or atomistic, management rules and outcomes are compared, and decentralized policy schemes, in the form of water taxes, that can be used to sustain socially optimal use of groundwater resources are explored.

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45

Scott, Douglas, David Taylor, Safinaz El-Solh, and Trevor Elliott. "Port Simulation Modelling and Economic Assessment." Journal of Marine Science and Engineering 4, no. 1 (February 25, 2016): 16. http://dx.doi.org/10.3390/jmse4010016.

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46

Jefferson, Tom, and Vittorio Demicheli. "Methodological Quality of Economic Modelling Studies." PharmacoEconomics 14, no. 3 (1998): 251–57. http://dx.doi.org/10.2165/00019053-199814030-00002.

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47

Wilde, Michelle. "Methodological Quality of Economic Modelling Studies." PharmacoEconomics 14, no. 3 (1998): 335. http://dx.doi.org/10.2165/00019053-199814030-00009.

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48

Anonychuk, Andrea, and Murray Krahn. "Health Economic and Infectious Disease Modelling." PharmacoEconomics 29, no. 5 (May 2011): 367–69. http://dx.doi.org/10.2165/11589240-000000000-00000.

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49

Fleurence, Rachael L., and Christopher S. Hollenbeak. "Rates and Probabilities in Economic Modelling." PharmacoEconomics 25, no. 1 (2007): 3–6. http://dx.doi.org/10.2165/00019053-200725010-00002.

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50

Brazaitienė, Tatjana, and Zenonas Brazaitis. "Volumetric modelling of economic index structures." Informacijos mokslai 41 (January 1, 2007): 70–75. http://dx.doi.org/10.15388/im.2007.0.3455.

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Economic index structures perform very important role in economy management and especially in process of preparing instant decisions. Therefore, timely and reasoned decision making and consequences of their implementation often depends on rationality of such structures. Volumetric model of economic index files, its development and adaptation are described in this article. This mathematical model allows to choose rational structure of particular index file, to evaluate it and to use it in practice gaining particular benefits. Specific example of model appliance is presented.Tūrinis ekonominių rodiklių struktūrų modeliavimasTatjana Brazaitienė, Zenonas Brazaitis SummaryEkonominių rodiklių struktūros atlieka labai svarbų vaidmenį ūkio valdyme ir ypač – skubiai rengiant sprendimus. Todėl nuo tų struktūrų racionalumo labai dažnai priklauso pagrįstų sprendimų priėmimas laiku ir jų įgyvendinimo rezultatai. Straipsnyje aprašomas tūrinis ekonominių rodiklių rinkmenų modelis, jo kūrimas ir adaptavimas. Šis matematinis modelis leidžia išrinkti racionalią konkretaus rodiklio rinkmenos struktūrą, ją įvertinti ir taikyti gaunant tam tikrą naudą. Pateikiamos rodiklių rinkmenos dalies apimties matematinės vilties ir dispersijos skaičiavimo formulės, taip pat parodomi skaičiavimai visiems galimiems rinkmenos skaidymo būdams. Pateikiamas konkretus modelio naudojimo pavyzdys.

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Articoli di riviste sul tema "Economic modelling"

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