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制造业是实体经济的主体，是产业数字化转型的主战场。制造企业顺应数字化变革趋势，积极利用互联网、大数据、人工智能等信息通信技术，持续推动企业数字化、服务化升级。然而，在推动产业数字化过程中，对制造业就业结构产生影响，会产生“机器换人”的现象，即产业数字化对制造业就业产生替代效应，也会使得企业生产规模扩大，从而促进制造业就业等。我国制造业如何在产业数字化对其就业的“破坏效应”和“补偿效应”中进行均衡，实现数字化和就业的双重保障都是值得我们细细研究的问题。分析产业数字化和制造业就业之间的关系不仅丰富了产业数字化理论和就业结构理论的交叉性研究，对国家、企业和个人都具有强烈的现实意义。

本文将基于2008-2019年中国30个省份面板数据，采用组合赋权法测算产业数字化指标体系；分析了制造业就业结构及劳动生产率的变化，计算了2008-2019年我国制造业21个行业的弹性系数、就业结构偏离度；最后，构建面板分位数回归和固定效应模型，实证分析产业数字化对各区域制造业就业结构的影响。

结果表明：（1）各省份产业数字化存在较大差异，经济越发达的地区越能加快促进产业数字化的发展，广东、江苏、浙江等产业数字化水平发展地相对较好，而海南、青海、宁夏等地的数字化水平偏低；随着时间的推移，产业数字化水平稳步上升。从地区差异看，各区域产业数字化水平表现出明显的阶梯化分布格局，东部较西部发展水平高，南部较北部发展水平高，沿海地区较非沿海地区发展水平高，长江流域地区较黄河流域地区发展水平高。（2）高技术产业就业人数占比逐年增加，而低、中低技术产业就业人数占比均下降；食品、饮料、烟草、纺织业、服饰业、石油煤炭、金属制品业等就业弹性系数和就业结构偏离度为负值，对劳动力具有挤出效应；医药制造业、交通运输设备制造业、专用设备制造业、计算机、通信、电子设备制造业、仪器仪表制造业等就业弹性系数和就业结构偏离度为正值，对其劳动力具有吸纳作用。（3）产业数字化对低技术产业制造业不发达的省份产生的负影响较小，随发达程度的增加产生的负影响越大，当低技能产业发展到一定发达的程度，影响不显著；产业数字化对中低技术产业制造业在低分位点处产生负向影响，对中高技术产业就业影响不显著；产业数字化对高技术产业制造业产生正向影响，条件分布系数呈现“倒U”型。（4）从地区异质性分析，中部、西部和东北地区产业数字化对低技术产业制造业均产生负向影响，东部地区不显著，且中部地区受影响的系数最大；东部和东北地区产业数字化对中低技术产业制造业均产生负向影响，而西部地区不显著；由于东北地区钢铁、石化、机床装备制造等发展较为发达，该地区产业数字化对中高技术产业制造业产生正向影响，其他地区不显著。东、中、西部地区产业数字化对高技术产业制造业均产生正向影响，而东北地区产业数字化对高技术产业制造业产生显著负向影响。

根据结论提出以下几点建议：把握产业数字化计划和 “稳就业”政策并肩前进；加强高技术产业应用型高技能人才的培养和储备体系建设；根据地区差异性，有效发挥各省份的“龙头”产业建设；优化传统模式，突破关键技术，加快就业平台信息建设。

Manufacturing industry is the main body of the real economy and the main battlefield of industrial digital transformation. Manufacturing enterprises comply with the trend of digital transformation and actively use information and communication technologies such as Internet, big data and artificial intelligence to continuously promote the digitization and service-oriented upgrading of enterprises. However, in the process of promoting industrial digitization, it will have an impact on the employment structure of manufacturing industry, which will produce the phenomenon of "machine replacement", that is, industrial digitization will have a substitution effect on manufacturing employment, and will also expand the production scale of enterprises, so as to promote manufacturing employment. It is worth studying how to realize the dual effects of "digital employment protection" and "Digital Manufacturing" in China. Analyzing the relationship between industrial digitization and manufacturing employment not only enriches the cross research of industrial digitization theory and employment structure theory, but also has strong practical significance for countries, enterprises and individuals.

Based on the panel data of 30 provinces in China from 2008 to 2019, this paper uses the combination weighting method to calculate the industrial digitization index system; This paper analyzes the changes of employment structure and labor productivity in manufacturing industry, and calculates the elasticity coefficient and deviation degree of employment structure of 21 manufacturing industries in China from 2008 to 2019; Finally, the panel quantile regression and fixed effect model are constructed to empirically analyze the impact of industrial digitization on the employment structure of manufacturing industry in various regions.

The results show that: (1) there are great differences in industrial digitization among provinces. The more economically developed regions can accelerate the development of industrial digitization. The level of industrial digitization in Guangdong, Jiangsu and Zhejiang is relatively good, while the level of digitization in Hainan, Qinghai and Ningxia is relatively low; With the passage of time, the level of industrial digitization has increased steadily. The level of development of the coastal areas in the north is higher, and the level of development of the Yellow River Basin in the south is higher than that in the coastal areas. (2) The proportion of employment in high-tech industries has increased year by year, while the proportion of employment in low, medium and low-tech industries has decreased; The employment elasticity coefficient and employment structure deviation degree of food, beverage, tobacco, textile industry, clothing industry, petroleum, coal and metal products industry are negative, which has a crowding out effect on the labor force; The employment elasticity coefficient and employment structure deviation of pharmaceutical manufacturing industry, transportation equipment manufacturing industry, special equipment manufacturing industry, computer, communication, electronic equipment manufacturing industry and instrument manufacturing industry are positive, which can absorb their labor force. (3) The negative impact of industrial digitization on the provinces with underdeveloped low-tech industries and manufacturing industries is small, and the greater the negative impact with the increase of the degree of development. When the low skilled industries develop to a certain degree of development, the impact is not significant; Industrial digitization has a negative impact on the manufacturing industry of low and medium-tech industries at the low quantile, and has no significant impact on the employment of medium and high-tech industries; Industrial digitization has a positive impact on high-tech industry and manufacturing industry, and the conditional distribution coefficient presents an "inverted U" shape. (4) From the analysis of regional heterogeneity, the industrial digitization in the central, Western and northeast regions has a negative impact on the low-tech manufacturing industry, the eastern region is not significant, and the coefficient affected in the central region is the largest; The industrial digitization in the East and Northeast China has a negative impact on the manufacturing industry of medium and low-tech industries, while it is not significant in the West; Due to the relatively developed development of iron and steel, petrochemical and machine tool equipment manufacturing in Northeast China, the industrial digitization in this region has a positive impact on the manufacturing industry of medium and high-tech industries, which is not significant in other regions. Industrial digitization in the East, middle and west regions has a positive impact on high-tech manufacturing, while industrial digitization in the northeast region has a significant negative impact on high-tech manufacturing.

According to the conclusion, the following suggestions are put forward: grasp the industrial digitization plan and the "stable employment" policy to move forward side by side; Strengthen the training and reserve system construction of applied high skilled talents in high-tech industries; Give full play to the construction of "leading" industries in various provinces according to regional differences; Optimize the traditional model, break through key technologies, and speed up the construction of employment platform information.