동아시아 제조업 업종별 고용효과의 DEA를 활용한 분석-한국의 경남지역을 중심으로- = Analysis of employment effects of East Asian manufacturing industry based on DEA -Focused on Gyeongnam province in Korea-

다국어 초록 (Multilingual Abstract)

Along with the recent economic recession in Korea, employment growth has been submerged in stagnation. In developing the industrial policy, not only the economic growth but also the size and quality of employment has gained increasing attention. This paper evaluates the employment effectiveness of manufacturing industry in Gyeongnam province with aims to identify industry sub-categories that are competitive across manufacturing industry and Korea in terms of employment effectiveness. We also provide some findings and implications meaningful for designing an effective industrial policy.
We first investigates the employment size, employment coefficient and added value ratio of 22 manufacturing industry sub-categories in Gyeongnam province. The analysis shows that the manufacturing industry is major contributor to the employment, but there are significant difference in the employment size and its variance across industry sub-categories.
The conventional measures such as employment coefficient fail to consider employment quality and industry size. To overcome these drawbacks, we employ Data Envelopment Analysis(DEA) model, which is capable of handling multiple inputs and outputs, and measure the employment effectiveness of Gyeongnam province in comparison with other cities and provinces in Korea. The DEA efficiency is defined by multiple inputs(equipment investment, R&D investment, employment size) and outputs(gross output, annual salary, changes in employment size).
For each of 22 manufacturing industry sub-categories, a super-efficiency DEA model that has better discrimination power is used to rank 16 cities and provinces in Korea in order of employment effectiveness. There are six industry sub-categories ranked within the top 25%(i.e., 1∼4 ranks), and eight sub-categories are ranked within the top 25%∼50%(5∼8 ranks). The numbers of industry sub-categories ranked within the top 50～75%(9∼12 ranks) and the low 25%(13∼16 ranks) are seven and one, respectively. In overall, the manufacturing industry in Gyeongnam province has relatively better employment effectiveness compared to other cities and provinces in Korea. Further DEA analysis shows that excessive equipment investment, too many employees and slow employment growth mainly contribute to the low employment effectiveness.
Finally, we classify 22 manufacturing industry sub-categories in Gyeongnam province into four groups with respect to the employment coefficient of each sub-categories and the rank obtained from DEA analysis. For example, nine manufacturing industry sub-categories(industry codes 10, 13, 14, 16, 21, 23, 25, 27, 32) are classified into Group I, which is high employment coefficient and high ranked industry sub-categories. It means that these nine industry sub-categories are competitive across manufacturing industry and Korea in terms of employment effectiveness. Based on the analysis, we provide several implications for improving the employment effectiveness in Gyeongnam province.

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