Evidence from Local Labor Markets This paper analyzes the effect of technology and trade on employment.
For the past two decades international workers have had more employment impact than adoption of US robotics, computers and automation. Robotics and automation could increase in the future and shift the scale of impact, but robotics needs to increase by about 100 times or more to have a larger effect.
The differential effects of trade and technology on employment patterns in U.S. local labor markets between 1990 and 2007. Labor markets whose initial industry composition exposes them to rising import competition from China have experienced significant employment reductions particularly in the manufacturing sector and among non-college-educated worker.
The analysis indicates that computers, robots and automation did not take jobs in the United States, but China did.
There is a wide agreement among economists that technological change and expanding international trade have led to changing skill demands and growing inequality or polarization of labor-market outcomes in the U.S. and in other rich countries. While this paper confirms that both forces have shaped employment patterns in U.S. local labor markets in the last three decades, its main contribution is to highlight important differences in the impact of technology and trade on labor markets. The impacts of trade and technology can be observed separately because local labor market exposure to technological change, as measured by specialization in routine task-intensive production and clerical occupations, is largely uncorrelated with local labor market exposure to trade competition from China.
* Direct employment due to robotics is 4 to 6 million jobs created in world manufacturing through 2011, represented by 3 to 5 jobs created per robot in use.
* Indirect employment created as a result of robots increases this number to 8 – 10 million jobs.
* It is projected that 1.9 to 3.5 million jobs will be created by robots in the next eight years.
* When manufacturing jobs are saved, jobs throughout the community where the factories are located are also saved.
In some industries 50,000 Chinese workers per 10,000 US workers has more impact than 150 robots per 10,000 US workers.
In other industries 40,000 Indian software professionals per 10,000 US software professionals had more employment impact than making certain business processes more automated.
Local labor markets with greater exposure to trade competition experience differential declines in manufacturing employment, with corresponding growth in unemployment and non-employment. The employment decline is not limited to production jobs but instead affects all major occupation groups. Employment losses are particularly large among workers without college education, for whom we also observe employment declines outside the manufacturing sector which may stem from local demand spillovers. While trade exposure reduces overall employment and shifts the distribution of employment between sectors, exposure to technological change has substantially different impacts, characterized by neutral effects on overall employment and substantial shifts in occupational composition within sectors. In particular, we find that susceptibility to technological change predicts declining employment in routine task-intensive production and clerical occupations both in the manufacturing and non-manufacturing sectors. For most demographic groups, these declines in routine employment are largely offset by increasing employment in abstract or manual-task-intensive occupations which tend to comprise the highest and lowest paid jobs in the economy. One exception is among women, for whom the reduction in routine-occupation employment translates to an overall
decline in employment.
Concurrent with the rapid growth of U.S. imports from China, the effect of trade competition on the manufacturing sector has become stronger over time, while the effect of technological change on employment composition in the manufacturing sector has subsided. Conversely, the impact of technology on the non-manufacturing sector is growing as technological change seems to be shifting from automation of production in manufacturing to computerization of information processing in knowledge-intensive industries.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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