Application of S-curve and Modified S-curve in Transition Economies’ GDP Forecasting. Visegrad Four Countries Case

Rafał Siedlecki (), Daniel Papla () and Agnieszka Bem ()
Additional contact information
Rafał Siedlecki: Wroclaw University of Economics
Daniel Papla: Wroclaw University of Economics
Agnieszka Bem: Wroclaw University of Economics

A chapter in Contemporary Trends and Challenges in Finance, 2018, pp 91-98 from Springer

Abstract: Abstract S-curve is usually used to describe economic or natural phenomena, which follow the rule of the logistic growth. In this paper we propose to use the modified S-curve, due to the “unlimited growth” phenomenon. The aim of this research is to show the application of the S-curve as well as the modified S-curve in GDP growth forecasting, using data from transition economies. This paper presents also the proposal of numerical estimation of the modified S-curve parameters. According to paper’s aims, we have posed the following research hypotheses: (H1) the S-curve and the modified S-curve are effective tools of economic development forecasting for transition economies; (H2) the modified S-curve is more efficient than ordinary S-curve in GDP forecasting for transition economies.

Keywords: Transition economies; Logistic law of growth; Forecasting; Business cycle (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-319-76228-9_9

Ordering information: This item can be ordered from
http://www.springer.com/9783319762289

DOI: 10.1007/978-3-319-76228-9_9

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().