The Rising Labor Costs,Automation And The Transfer Of Manufacturing Sector

In the 21st century,with the change of population structure,China has gradually entered the era of labor supply shortage from unlimited labor supply,driving up labor costs.According to Flying Geese Paradigm Theory,as labor wages continue to rise,manufacturing enterprises sensitive to labor costs will actively flow to areas with lower wages in order to seek production advantages.After 2003,the proportion of industrial output value in coastal areas began to decrease significantly,while the proportion of industry in Central and Western regions,which are relatively backward in economic development and abundant in labor resources,has increased significantly,showing Flying Geese Paradigm of Large Country of industrial transfer among regions within the independent economy.However,after 2012,coastal industries are moving inland at a slower pace.Meanwhile,increasingly sophisticated automation technologies are beginning to replace labor in manufacturing production,potentially triggering innovations in labor and production and boosting the emergence of new industrial geographies.After entering the new normal,the problem of aging and the decline of demographic dividend has become increasingly prominent.Has the rising labor cost changed the spatial pattern of China’s manufacturing industry?Can the rapid development of machine automation technology change the impact of labor cost factors on the industrial transfer of manufacturing industry?What is the mechanism behind it?The answers to these questions have enlightening significance for grasping the development law of China’s manufacturing industry and maintaining the development advantages of manufacturing industry.Using the database of the Chinese Annual Survey of Industrial Firms,the customs database,the database of International Federation of Robots(IFR)and combined with the minimum wage data of prefecture-level cities,this paper empirically examines the impact of rising labor costs on the spatial shift of manufacturing industries from the automation perspective,both at the city and firm levels.The results of the study show that:(1)The minimum wage increase significantly reduces the share of urban manufacturing and accelerates manufacturing relocation,but automation can alleviate the negative impact of the minimum wage on the manufacturing industry and relieve the relocation pressure of manufacturing firms.(2)The results of heterogeneity analysis show that when a city’s industries are more dominated by the government,the mitigation effect of machine automation on industrial transfer will be reduced;compared with cities with low trade openness,automation can play a more stable role in manufacturing in cities with high trade openness;only in areas with high overall education level and high human capital of college students,automation will have a positive regulatory effect on industrial relocation caused by labor cost.In areas with low overall education level and weak senior human capital,this effect is not obvious.(3)Mechanism analysis shows that the minimum wage increases the exit risk of manufacturing firms,and the use of automation technology offsets the negative impact of labor cost on the survival and operation of manufacturing firms,and reduces the exit probability of firms,which explains the heterogeneous manufacturing industry transfer phenomenon at the macro level.In addition,compared with other firms,the labor productivity of firms introducing industrial robots has increased significantly,and the labor productivity effect of industrial robots is an important mechanism to expand firms’ production scale,improve investment enthusiasm and encourage firms to stay in the city.In order to cope with the pressure of rising labor costs and maintain the integrity of China’s industrial chain and the competitiveness of manufacturing industry,combined with the above analysis conclusions,this paper puts forward policy suggestions in terms of optimizing the environment for industry transfer,promoting intelligent production in manufacturing industry and improving the talent training system,etc.