Title: Factors affecting long-term economic growth-consistency and stability by soft regression estimation
Authors: Eli Shnaider; Arthur Yosef; Nava Haruvy
Addresses: Peres Academic Center, 10 Shimon Peres St., Rehovot, Israel ' Tel Aviv-Yaffo Academic College, 2 Rabenu Yeruham St., Tel Aviv-Yaffo, Israel ' Netanya Academic College, 1 University St., Netanya, Israel
Abstract: This study demonstrates a challenge of building and validating a model of factors associated with long-term economic success of economies, as reflected by measures of their aggregate value of output/income per capita. We use two quantitative modelling techniques including multiple linear regression (MLR) and a newer technique of soft regression, a modelling tool based on fuzzy information processing technology. The objective of this study is to test and compare the two information-processing tools to find the more reliable and potentially helpful tool for policy decision making. The conclusions of this study are: 1) the soft regression tool generated more consistent and comprehensible results in comparison to the MLR method; 2) based on soft regression tool, the model displayed solid stability over extensive period under study; 3) based on MLR method, we could interpret the results as supporting the validity of the model; however, some of the results were contradictory, thus undermining the reliability of conclusions.
Keywords: multiple linear regression; MLR; soft regression; fuzzy information processing; economic growth; international competitiveness.
International Journal of Society Systems Science, 2018 Vol.10 No.1, pp.16 - 34
Received: 27 Sep 2016
Accepted: 27 Aug 2017
Published online: 19 Jan 2018 *