摘要
2018年政府工作报告中将城镇新增就业1100万人以上作为主要发展预期目标之一,同时指出要着力促进就业。近些年来,海洋产业的迅速发展为海洋劳动力就业、缓解全国整体就业压力提供了良好机遇。在此背景下,基于对2006-2016年间我国主要海洋产业与海洋就业结构偏离度的测算,首次建立偏最小二乘通径模型对可能影响结构偏离度的相关因素进行科学探究。结果表明:(1)主要海洋产业的第一产业结构偏离度为负,存在劳动力转出的可能;第二产业、第三产业结构偏离度为正,有继续吸纳劳动力的潜力。(2)科学技术水平、地区基础设施建设、地区人均收入与消费、对外贸易四大因素均有助于减小结构性偏差,劳动力、固定资产投资两因素则会加大结构性偏差。据此,提出一系列促进海洋产业与海洋就业协调发展、实现海洋劳动力充分就业的对策建议。
In the 2018 government work report,more than 11 million urban jobs will be created as one of the main development goals,and the government will focus on promoting employment.In recent years,the rapid development of the marine industry has provided a good opportunity for the employment of the marine labor force and alleviating the employment pressure of the whole country.In this context,based on the calculation of the deviation degree of major marine industries and marine employment structure in China between 2006 and 2016,this paper established the partial least square path model for the first time to conduct a scientific research on related factors that may affect the structural deviation degree.The results show that(1)the deviation degree of the primary industrial structure of the major marine industries is negative,and there is the possibility of labor force transferring out.The structural deviation degree of secondary industry and tertiary industry is positive,having the potential to continue to absorb labor force;(2)the four factors of science and technology level,regional infrastructure construction,regional per capita income and consumption,and foreign trade are conducive to reducing structural bias,while the two factors of labor force and fixed asset investment will increase structural bias.Accordingly,a series of measures and suggestions are put forward to promote the coordinated development of marine industry and marine employment,and realize the goal of the full employment of marine labor force.
作者
赵领娣
王亚薇
脱颖
Zhao Lingdi;WangYawei;Tuo Ying(School of Economics,Ocean University of China,Qingdao266100,China;Research Institute of Marine Development,Ocean University of China,Qingdao 266100,China)
出处
《中国海洋大学学报(社会科学版)》
2020年第2期64-72,共9页
Journal of Ocean University of China(Social Sciences)
基金
国家社科基金重大课题“中国沿海典型区域风暴灾害损失监测预警研究”(14ZDB151)
国家社科基金专项课题“新时代中国特色社会主义思想指引下的海洋强国建设方略研究”(18VSJ067)