Mathematical models of socio-economic processes
Yu. A. Dubnov, A. V. Boulytchev An entropy-robust approach to evaluating the economic effect of basic research
System diagnostics of socio-economic processes
Community informatics and the formation of social networking
Scientometrics and management science
Computer analysis of texts
Yu. A. Dubnov, A. V. Boulytchev An entropy-robust approach to evaluating the economic effect of basic research

Abstract.

The work is devoted to the evaluation of the influence of fundamental science on macroeconomic indicators. The regression model of the specific gross domestic product elasticity is considered with the aim of revealing the dependence between the indicators of innovation and economic development. As a tool for restoring model parameters, a method of entropy-robust estimation based on the maximum entropy principle was developed. The main advantage of this approach is the invariance by measurement error distribution and the likelihood function. The developed model is used to construct a randomized forecast of GDP growth for the next 5 years.

Keywords:

macroeconomy, GDP, elasticity, math modeling, principle of maximum entropy.

PP. 51-63.

REFERENCES

1. Innovation Report 2014. Innovation Research and Growth. Policy Paper. BIS, March 2014. p.20.
2. Main Science and Technology Indicators. Volume 2014/1, OECD 2014.
3. Varshavskiy L.E. Problimi nauki I ee resultativnost’ // Voprosi economiki, 2011, no.1, p.151-157.
4. Aldoshin S.M. Razvitie material’no-technicheskoy basi nauki kak factor povisheniya resul’tativnosti nauchnih issledovaniy // Vestnik Rossiiskoi Akademii Nauk, 2014, vol.84, no.10, p.874-881.
5. World Population Prospects: The 2015 Revision, Methodology of the United Nations Population Estimates and Projections; Working Paper No. ESA/P/WP.242; Department of Economic and Social Affairs, Population Division: New York, NY, USA, 2015.
6. Popkov Yu.S., Popkov A.Yu. New Method of Entropy-Robust Estimation for Randomized Models under Limited Data // Entropy, 2013, vol.16, p.675-698.
7. Popkov Yu.S., Dubnov Yu.A., Entropy-robust randomized forecasting under small sets of retrospective data // Avtomat. i Telemekh., 2016, no.5, p.109–127.
8. Cover T.M., Thomas J.A. Elements of information theory. – John Wiley and Sons Ltd, New York, 1991. – 561 p.
9. Varshavsky L.E. Analiz podhodov k garmonizacii svyazey mejdu naukoy I ekonomikoy // Proceedings of the Institute of System Analysis of the Russian Academy of Sciences, 2015, vol.65, p.44-52.
10. Shelyubskaya N.V. Innovaacionniye strategii stran zapadnoy Evropi I indicatori vostrebovannosti resultatov nauki (Na primere Velikobritanii) // Identification of priority scientific directions: interdisciplinary approach / Ed .: I.Ya. Kobrinskaya, V.I. Tishchenko. - Moscow: IMEMO RAS, 2016. - 181 p.
11. Open access statistical data repository - World DataBank, URL: www.worldbank.org
12. Barnett, Vic; Lewis, Toby. Outliers in Statistical Data (3 ed.) – Wiley, 1994.
13. Magnus Ya.R., Katyshev P.K, Peresetskiy A.A. Ekonometrika. Nachal’niy kurs: Ucheb. pos. – 6-oe izd. – M.: Delo, 2004. – 576 p.
14. A. Zellner. Bayesovskiye metodi v ekonometrii // Transl. from English. G.G. Pirogova and Yu.P. Fedorovskogo - M.: Statistics, 1980 - 438 p.
15. Alekseev V.M., Tikhomirov V.M., and Fomin S.V., Optimal’noe upravlenie (Optimal Control), M.: Nauka, 1979.
16. Amos Golan, George G. Judge, Douglas Miller. Maximum Entropy Econometrics: Robust Estimation with Limited Data. – John Wiley and Sons Ltd. Chichester, U.K., 1996. – 324 p.
17. Popkov Yu.S., Popkov A.Yu., Darkhovskii B.S., Parallel Monte Carlo for Entropy Robust Estimation // Math. Models Comput. Simul., 2016, vol.8, no.1, p.27–39.
18. Ximing Wu. A Weighted Generalized Maximum Entropy Estimator with a Data-driven Weight // Entropy, 2009. no.11.
19. Grinin L.E., Korotaev A.V. The global crisis in retrospect. A brief history of rises and crises: from Lycurgus to Alan Greenspan. - 2 nd ed. - M.: Librocom, 2012. - 336 s.
20. Daniel Yergin. The Prize: The Epic Quest for Oil, Money, and Power. - M .: “Alpina Pablisher”, 2011. - 960 s.
 

 

2024-74-1
2023-73-4
2023-73-3
2023-73-2

© ФИЦ ИУ РАН 2008-2018. Создание сайта "РосИнтернет технологии".