Computer testing of a non-parametric partial equilibrium model prototype
- Авторлар: Svetlov N.M.1,2
-
Мекемелер:
- Laboratory of financial and industrial integration mechanisms
- Central Economics and Mathematics Institute of Russian Academy of Science
- Шығарылым: Том 59, № 2 (2023)
- Беттер: 100-111
- Бөлім: Articles
- URL: https://clinpractice.ru/0424-7388/article/view/653343
- DOI: https://doi.org/10.31857/S042473880025862-7
- ID: 653343
Дәйексөз келтіру
Аннотация
On the basis of non-parametric formulations of the production program problem (previously known) and the consumer choice problem (new), a computable partial equilibrium model with a non-parametric representation of both supply and demand is proposed. In this model the problems of the producer and the consumer are represented by simultaneous inequalities of the dual problems pair. This converts the problem of finding an equilibrium to minimizing the differences between objective functions in each pair, summarized over producers and consumers. Such a problem, however, may have multiple local optima. Computer tests on artificial data sets confirmed that inserting such “technical” constraints into a computable model, that are always valid in an equilibrium, can effectively direct the search for a solution using the CONOPT4 procedure to the global optimum (to which the sought equilibrium corresponds). In all 36 tests carried out, equilibrium solutions were found on the first try. The result obtained is of significant importance for the creation of tools used at the sectoral level in managing the unstable economic dynamics that are characteristic of periods of change in systems of dominant technologies. Such tools will make better use of the information in the original empirical data.
Авторлар туралы
Nikolai Svetlov
Laboratory of financial and industrial integration mechanisms; Central Economics and Mathematics Institute of Russian Academy of ScienceMoscow, Nakhimovsky prospekt, 47
Әдебиет тізімі
- Акаев А.А., Садовничий В.А. (2016). Замкнутая динамическая модель для описания и рас-чета длинной волны экономического развития Кондратьева // Вестник Российской ака-демии наук. Т. 86. № 10. С. 883–896. doi: 10.7868/S0869587316100029
- Дементьев В.Е. (2021). Модель интерференции длинных волн экономического развития // Компьютерные исследования и моделирование. Т. 13. №3. С. 649–663. doi: 10.20537/2076-7633-2021-13-3-649-663
- Дементьев В.Е., Евсюков С.Г., Устюжанина Е.В. (2020). О важности стратегического под-хода при ценообразовании на рынках сетевых благ // Журнал Новой экономической ас-социации. № 2 (46). С. 57–71. doi: 10.31737/2221-2264-2020-46-2-3
- Земцов С.М., Филипцов А.М. (2009). Калибровка функций расходов и прибыли в модели частичного равновесия BEL-ASIM: теоретический аспект // Вестник Полоцкого госу-дарственного университета. Серия D. Экономические и юридические науки. № 4. С. 52–58.
- Киселёв С.В., Ромашкин Р.А., Белугин А.Ю. (2022). Агропродовольственный экспорт России до 2030 г.: прогноз на основе модели частичного равновесия // Журнал Новой экономической ассоциации. № 4 (56). С. 69–90.
- Полтерович В.М. (1990). Экономическое равновесие и хозяйственный механизм. М.: Наука. 256 с.
- Прокопьев М.Г. (2015). Классификация и методические аспекты разработки моделей час-тичного равновесия // Региональные проблемы преобразования экономики. № 6 (56). С. 88–95; №7 (57). С. 83–91.
- Светлов Н.М. (2002). На пути к новой концепции стоимости. М.: Издательство МСХА. 108 с.
- Светлов Н.М. (2019a). Модели непараметрических границ производственных возможно-стей: опыт применения в сельском хозяйстве // Вестник ЦЭМИ. №1. Статья 5. 14 с. doi: 10.33276/S265838870004477-7
- Светлов Н.М. (2019б). Непараметрическая граница производственных возможностей в вы-числимой модели частичного равновесия // Экономика и математические методы. Т. 55. №4. С. 104–116. doi: 10.31857/S042473880006779-5
- Светлов Н.М., Буць В.И., Карачевская Е.В., Ленькова Р.К., Редько Д.В., Светлова Г.Н., Шафранская И.В., Шафранский И.Н. (2020). Применение математических методов в управлении АПК Беларуси и России. М.: ЦЭМИ РАН. 177 с. doi: 10.33276/978-5-8211-0782-4
- Светлов Н.М., Шишкина Е.А. (2019). Инновационная модель частичного равновесия в приложении к анализу эффектов изменения климата // Международный сельскохозяй-ственный журнал. № 5. С. 58–60. doi: 10.24411/2587-6740-2019-11587
- Britz W., Witzke P. (eds.) (2014). CAPRI model documentation 2014. Bonn: Institute for Food and Resource Economics, University of Bonn. 277 p.
- Brown A., Deaton A. (1972). Surveys in applied economics: models of consumer behavior. The Economic Journal, 82, 328, 1145–1236.
- Chantreuil F., Hanrahan K., Leeuwen M. van (2012). The future of EU agricultural markets by AGMEMOD. Dordrecht: Springer. XVI, 128 p. doi: 10.1007/978-94-007-2291-0
- Charnes A., Cooper W.W., Rhodes E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444.
- Drud A. (1992). CONOPT — a large-scale GRG code. ORSA Journal on Computing, 6, 207–216.
- Drud A. (2023). CONOPT4. GAMS – Documentation. GAMS Development Corp., 1547–1581.
- Ermolieva T., Havlík P., Ermoliev Yu., Mosnier A., Obersteiner M., Leclère D., Khabarov N., Valin H., Reuter W. (2016). Integrated management of land use systems under systemic risks and security targets: A stochastic global biosphere management model. Journal of Agricultural Economics, 67, 3, 584–601. doi: 10.1111/1477-9552.12173
- Farrell M.J. (1957). The measurement of productive efficiency. Journal of Royal Statistical Society: Series A (General), 3, 253–290.
- Fock A., Weingarten P., Wahl O., Prokopiev M. (2000). Russia's bilateral agricultural trade: First results of a partial equilibrium analysis. Russia's Agro-food sector: Towards truly functioning markets / P. Wehrheim et al. (eds.). Kluwer Academic Publishing, 271–197.
- Goldberger A.S., Gamaletsos T. (1970). A cross-country comparison of consumer expenditure patterns. European Economic Review, 1, 357–400. doi: 10.1016/0014-2921 (70)90020-6
- Gstach D. (1998). Another approach to data envelopment analysis in noisy environments: DEA+. Journal of Productivity Analysis, 9, 2, 161–176. doi: 10.1023/A:1018312801700
- Houthakker H.S. (1965). New evidence on demand elasticities. Econometrica, 33, 277–288.
- Huppmann D. (2013). Endogenous shifts in OPEC market power — a Stackelberg oligopoly with fringe. DIW Discussion Papers, 1313. Berlin: German Institute for Economic Research. 26 p.
- Just R.E. (2011). Behavior, robustness, and sufficient statistics in welfare measurement. Annual Review of Resource Economics, 3, 33–70. doi: 10.1146/annurev-resource-040709-135125
- Kiselev S., Strokov A., Belugin A. (2016). Projections of Russia’s agricultural development under the conditions of climate change. Studies on Russian Economic Development, 5, 548–556. doi: 10.1134/S1075700716050063
- Lee J. D., Hwang S., Kim T. Y. (2005). The measurement of consumption efficiency considering the discrete choice of consumers. Journal of Productivity Analysis, 23, 65–83. doi: 10.1007/s11123-004-8548-y
- Matsumoto M., Nishimura T. (1998). Mersenne twister: A 623-dimensionnally equidistributed uniform pseudorandom number generator. ACM Transactions on Modeling and Computer Simulation, 8 (1), 3–30. doi: 10.1145/272991.272995
- Pollak R.A. (1977). Price dependent preferences. The American Economic Review, 67, 2, 64–75.
- Ruhnau O., Bucksteeg M., Ritter D., Schmitz R., Böttger D., Koch M., Pöstges A., Wied-mann M., Hirth L. (2022). Why electricity market models yield different results: Carbon pricing in a model-comparison experiment. Renewable and Sustainable Energy Reviews, 153. Paper 111701. doi: 10.1016/j.rser.2021.111701
- Savvidis G., Siala K., Weissbart C., Schmidt L., Borggrefe F., Kumar S., Pittel K., Madlener R., Hufendiek K. (2019). The gap between energy policy challenges and model capabilities. Energy Policy, 125, 503–520. doi: 10.1016/j.enpol.2018.10.033
- Svetlov N.M., Siptits S.O., Romanenko I.A., Evdokimova N.E. (2019). The effect of climate change on the location of branches of agriculture in Russia. Studies on Russian Economic Development, 30, 4, 406–418. doi: 10.1134/S1075700719040154
- Thompson R.G., Langemeier L.N., Lee C., Lee E., Thrall R.M. (1990). The role of multiplier bounds in efficiency analysis with application to Kansas farming. Journal of Econometrics, 46, 93–108.
Қосымша файлдар
