Studies in Science of Science ›› 2018, Vol. 36 ›› Issue (9): 1642-1649.
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The Development and Application Study on Spatial Sample of Economic and Social Public Data
马玉琪1,扈瑞鹏1,2,赵彦云2,3
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经济社会公共数据的空间统计样本数据开发及应用研究
Abstract: Based on full-sample data of Zhongguancun Haidian Science Park, this paper explores exit mechanism of high-tech enterprises in China in recent years utilizing Stratified Cox Proportional Hazards model, and comparative analysis is carried out across enterprises of different ownerships and industries. The study reveals that: Zhongguancun high-tech enterprises are constantly facing high exit risk, and the trend is intensifying. The exit rates for enterprises of different ownerships have remarkable difference, the exit risk of state-owned enterprises is significantly lower than that of non-state-owned enterprises, which means administrative forces has generated some barrier effect. Internal factors such as operation efficiency, scale, liability and R&D level have significant impact on exit risk of enterprises. For high-tech enterprises of different ownerships and industries, the marginal effect of each variable is distinct; Government interventions also have some effect, tax incentives help to improve the survival probability of enterprises and the impact is greater for non-state-owned enterprises, while the impact of financial subsidies is insignificant for enterprises of all types. The conclusions provide some policy implications in terms of improving competitiveness environment of high-tech industry and increasing market efficiency.
摘要: 基于中关村海淀园全样本数据,利用分层Cox风险比例模型,探究近年来我国高新技术企业的退出机制,并进行不同所有制、不同行业间的对比研究。结果表明:中关村高新技术企业始终面临较大的淘汰风险,且具有一定的加剧趋势;不同所有制企业的退出率存在明显差异,国有企业的退出风险显著低于非国有企业,行政力量产生了一定的壁垒效应;经营效率、规模、负债和研发水平等内部因素对企业退出风险具有显著影响;对于不同所有制、不同行业的高新技术企业,各变量的边际效应存在异质性;政府干预也会对企业退出产生一定影响,税收优惠有助于提升企业的生存概率,且这一因素对非国有企业的效应高于国有企业,财政补贴对各类企业的作用均不显著。研究结论为改善高新技术产业竞争环境,提升市场效率提供了一定的政策启示。
马玉琪 扈瑞鹏 赵彦云. 企业性质、行业差异与高新技术企业退出研究[J]. 科学学研究, 2018, 36(9): 1642-1649.
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URL: https://journal08.magtechjournal.com/kxxyj/EN/
https://journal08.magtechjournal.com/kxxyj/EN/Y2018/V36/I9/1642