EXPLORING INNOVATION FACTORS AFFECTING ECONOMIC PERFORMANCE IN EMERGING ASIAN COUNTRIES: A MACHINE LEARNING APPROACH

Yuwen Liu and Chin-Chia Liang
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Yuwen Liu: Institute of Technology Management, National Tsing Hua University, No. 101 Section 2, Guangfu Rd, Hsinchu 30013, Taiwan, ROC
Chin-Chia Liang: ��Department of Finance, Da-Yeh University, No. 168 University Road, Dacun, Changhua 51592, Taiwan, ROC

The Singapore Economic Review (SER), 2022, vol. 67, issue 03, 1029-1045

Abstract: In this study, we aimed to identify the main innovation factors that affect the economic performance of emerging countries. We analyzed data on 21 innovation-related variables in six emerging Asian countries (China, Indonesia, Malaysia, the Philippines, Thailand and Vietnam) from 1990 to 2008. Using principal component analysis (PCA), we identified six factors that explained up to 90.6% of the variation of all of the variables. Taking the least absolute shrinkage and selection operator clustering approach to variable selection, along with the other classification and estimation methods, we explored the effects of the six identified factors on economic growth. Research and development expenditure and contract enforcement (cost) had negative effects on economic growth, whereas gross enrolment ratio (tertiary), primary-school pupil–teacher ratio (inverse), paved roads and number of registered carrier departures worldwide had positive effects on economic growth.

Keywords: Panel data model; innovation factors; economic growth; machine learning; principal component analysis; cluster-LASSO (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0217590820450058

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