Sequential precision of predictions in models of economic growth

Krasovskii AA & Tarasyev AM (2010). Sequential precision of predictions in models of economic growth. In: Dynamic Systems, Economic Growth, and the Environment. Eds. Cuaresma, J. Crespo, Palokangas, T. & Tarasyev, A., Heidelberg: Springer-Verlag. ISBN 978-3-642-02131-2 DOI:10.1007/978-3-642-02132-9_2.

Full text not available from this repository.

Abstract

The research deals with the model of economic growth based on the real time series. The methodology for analysis of a country's macroeconomic parameters is proposed. A distinguishing feature of the approach is that real data is analyzed not by direct statistical approximations but through formalization of the process in terms of optimal control theory. The econometric analysis is used only at the stage of calibration of initial parameters of the model. This feature helps to analyze the dynamism in growth of economic factors which drive the economic growth. The study is focused on the gross domestic product (GDP) of a country. There are three production factors in the model: capital, labor and useful work. Several production functions (Cobb-Douglas, modifications of LINEX) are implemented in the model to express the relationship between factors of production and the quantity of output produced. The problem of investments optimization is solved using the version of the Pontryagin maximum principle, elements of the qualitative theory of differential equations and methods of differential games. Numerical algorithm is proposed for constructing synthetic trajectories of economic growth. Numerical experiments are fulfilled via elaborated software. For verification of the proposed approach several model modifications and case studies are presented. By means of comparison of obtained model trajectories with real data one can judge on the forecasting capacity of the model. As time goes by real data is collected and can be compared to forecast. At some stage it is necessary to make the forecast more precise. Using the data updates one restarts the model from the very beginning. Based on the model restart the new forecast is obtained which makes the previous one more accurate. Extensive simulations are done which realized the suggested methodology. They show that based on several data updates a series of forecasting trajectories demonstrate sequential precision of predictions property. Numerical results are based on real data for economies of US, UK, and Japan.

Item Type: Book Section
Research Programs: Dynamic Systems (DYN)
Bibliographic Reference: In: J. Crespo Cuaresma, T. Palokangas, A. Tarasyev (eds); Dynamic Systems, Economic Growth, and the Environment; Springer-Verlag, Heidelberg, Germany pp.23-43
Related URLs:
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 08:44
Last Modified: 17 Feb 2016 12:31
URI: http://pure.iiasa.ac.at/9324

Actions (login required)

View Item View Item

International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313