The impact of R&D on GDP study based on grey delay Lotka-Volterra model. Issue 1 (2nd February 2015)

• Record Type: Journal Article
• Authors: Mao, Shuhua; Gao, Mingyun; Zhu, Min
• Is Part Of: Grey systems. Volume 5:Issue 1(2015)
• Page Start: 74
• Page End: 88
• Publication Date: 2015-02-02
• Subjects: Grey systems modeling and prediction -- Practical applications of grey models; Cybernetics -- Periodicals; Systems engineering -- Periodicals; 003.5
• DOI: 10.1108/GS-11-2014-0042
• Languages: English
• ISSNs: 2043-9377

Abstract

Abstract : Purpose: – The purpose of this paper is to elevate the accuracy when predicting the gross domestic product (GDP) on research and development (R&D) and to develop the grey delay Lotka-Volterra model. Design/methodology/approach: – Considering the lag effects between input in R&D and output in GDP, this paper estimated the delay value via grey delay relation analysis. Taking the delay into original Lotka-Volterra model and combining with the thought of grey theory and grey transform, the authors proposed grey delay Lotka-Volterra model, estimated the parameter of model and gave the discrete time analytic expression. Findings: – Collecting the actual data of R&D and GDP in Wuhan China from 1995 until 2008, this paper figure out that the delay between R&D and GDP was 2.625 year and found the dealy time would would gradually be reduced with the economy increasing. Practical implications: – Constructing the grey delay Lotka-Volterra model via above data, this paper shown that the precision was satisfactory when fitting the data of R&D and GDP. Comparing the forecasts with the actual data of GDP in Wuhan from 2009 until 2012, the error was small. Social implications: – The result shows that R&D and GDP would be both growing fast in future. Wuhan will become a city full of activity. Originality/value: – Considering the lag between R&D and GDP, this work estimated the delay value via a grey delay relation analysis and constructed a novel grey delay Lotka-Volterra model.