An Intelligent Computing Approach to Evaluating the Contribution Rate of Talent on Economic Growth

Yong He, Siwei Gao and Nuo Liao ()
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Yong He: Guangdong University of Technology
Siwei Gao: Eastern Kentucky University
Nuo Liao: Guangdong University of Technology

Computational Economics, 2016, vol. 48, issue 3, No 2, 399-423

Abstract: Abstract We set out in this study to develop an intelligent computing method for the evaluation of the ‘economic contribution rate of talent’ (ECRT). We begin by constructing an indicator system for comprehensive evaluation of the talent environment and then go on to classify our (country or region) target system using our proposed GA-DE-FCM methodology. We subsequently identify total ‘human capital’ as comprising of ‘talent capital’ and ‘general labor’, which, along with ‘fixed assets’, are used as the input variables of the economic system, whilst the corresponding gross domestic product is used as the output variable. The mapping between the inputs and output is modeled in this study by a ‘fuzzy artificial neural network’ from which several fuzzy rules can be extracted. Having extracted these fuzzy rules, we subsequently go on to investigate the effect of each input factor (fixed assets, talent capital and general labor) on the level of economic growth within each category (obtained in Step 1), and then carry out an examination of the ECRT within each category, as well as that within the whole target system. The traditional methods of evaluating ECRT are not regarded as satisfactory, given that the ECRT problem is non-linear and involves lags; however, we argue that based upon intelligent computing, the model proposed here can effectively deal with these issues. The results, based upon a 2001–2010 sample of 31 provinces in mainland China, indicate that during this period, China could be classified into three categories according to the talent environment. The first category (high level talent environment) comprises of just two regions, with an average ECRT of 44.61 per cent, whilst the second category (median level talent environment) comprises of five regions, with an average ECRT of 37.57 per cent, and the third category (low level talent environment) comprises of 24 regions, with an average ECRT of 14.8 per cent. The average ECRT for China as a whole is 25.67 per cent.

Keywords: Economic contribution rate of talent (ECRT); Talent environment; Talent capital; GA-DE-FCM classification; Fuzzy artificial neural network (FANN) (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s10614-015-9536-1

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