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http://dx.doi.org/10.7465/jkdi.2014.25.6.1253

Panel data analysis with regression trees  

Chang, Youngjae (Department of Information Statistics, Korea National Open University)
Publication Information
Journal of the Korean Data and Information Science Society / v.25, no.6, 2014 , pp. 1253-1262 More about this Journal
Abstract
Regression tree is a tree-structured solution in which a simple regression model is fitted to the data in each node made by recursive partitioning of predictor space. There have been many efforts to apply tree algorithms to various regression problems like logistic regression and quantile regression. Recently, algorithms have been expanded to the panel data analysis such as RE-EM algorithm by Sela and Simonoff (2012), and extension of GUIDE by Loh and Zheng (2013). The algorithms are briefly introduced and prediction accuracy of three methods are compared in this paper. In general, RE-EM shows good prediction accuracy with least MSE's in the simulation study. A RE-EM tree fitted to business survey index (BSI) panel data shows that sales BSI is the main factor which affects business entrepreneurs' economic sentiment. The economic sentiment BSI of non-manufacturing industries is higher than that of manufacturing ones among the relatively high sales group.
Keywords
Business survey index; mixed effects model; panel data; regression tree;
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