Future job automation to hit hardest in low wage metropolitan areas like Las Vegas, Orlando and Riverside-San Bernardino

Jess Chen Analysis, Employment, Income & Wealth, Reports 5 Comments

New research by the Institute for Spatial Economic Analysis (ISEA) finds that job automation will hit certain metropolitan areas significantly harder than others. Low-wage cities like Las Vegas, NV, Orlando, FL, and Riverside-San Bernardino, CA are expected to be among the hardest-hit metros in terms of total job losses.

The impact of automation on jobs is likely to be more severe than previously anticipated. Based on recent advances in machine learning and mobile robotics, even non-routine jobs like truck driving, healthcare diagnostics, or even education can be affected.

“The replacement of jobs by machines has been happening continuously since the Industrial Revolution, but it’s expected to significantly accelerate in the coming 10 or 20 years,” according to Professor Johannes Moenius, founding director of ISEA. “Pretty much everyone will be affected, but some metropolitan areas will see a lot more jobs vanish than others.”

Economists at ISEA combined research by Oxford professors on the probability of automation for various occupations with employment data published by the Bureau of Labor Statistics. Considering the 100 metropolitan areas in the United States with more than 250,000 jobs, the largest share of jobs that are automatable are in:

Metropolitan Statistical Area Share of Jobs Automatable
1 Las Vegas-Henderson-Paradise, NV 65.2%
2 El Paso, TX 63.9%
3 Riverside-San Bernardino-Ontario, CA 62.6%
4 Greensboro-High Point, NC 62.5%
5 North Port-Sarasota-Bradenton, FL 62.4%
6 Bakersfield, CA 62.4%
7 Orlando-Kissimmee-Sanford, FL 61.8%
8 Fresno, CA 61.5%
9 Greenville-Anderson-Mauldin, SC 61.3%
10 Louisville/Jefferson County, KY-IN 61.3%

The groups of occupations contributing the most to future automation across all the listed metro areas are office and administrative support occupations, food preparation and serving related occupations, and sales and related occupations. These three occupational groups regularly account for half of the automation potential in the largest MSAs. Transportation and material moving occupations also contribute substantially to potential job losses in Riverside, Louisville, and Greensboro.

The map below illustrates the share of jobs automatable for all 421 metropolitan statistical areas (MSA). The bubble size shows the number of workers employed in the MSA in December 2016. The bubble color show the share of those jobs that can technically be “automated away” in the next 20 years.

Share of Jobs Facing Automation Risk

As the map shows, almost all large metropolitan areas can lose over 55% of their current jobs due to automation. The ones that fare better than others include high-tech centers like Silicon Valley and Boston.

The researchers traced the share of jobs that could be automated to the implied reduction in wages in each MSA. The map below shows the share of current wages that would disappear if all automation opportunities were realized. The bubble size shows total wages in the MSA in 2016, and the bubble color show the share of wages potentially lost due to automation within the next 20 years.

Share of Wages Facing Automation Risk

Comparing both maps illustrates how stunningly different the effect of automation will be on employment versus wages: Since lower income jobs face higher automation risk, the effect on employment will be much more drastic than the effect on wages. MSAs with a high share of low paying jobs will have larger job and wage losses.

The researchers emphasize that probability of automation does not equal future unemployment rates: “Technical feasibility does not imply that automation necessarily makes economic sense. And historically, automation went hand in hand with new job creation both in skilled and less skilled labor,” explains Dr. Chen. “However, the speed and the high share of automation in less skilled jobs raises many questions about whether the economy will be able to make up for the expected job losses. What we do expect is that automation will create winners and losers among cities and regions of the U.S., where losers may not recover to their original employment levels within even a decade’s time.”

“This looks like especially tough times ahead for Vegas and the Inland Empire,” adds Professor Moenius. “But even though there may be a few winners, pretty much every region in the US is going to get a hair-cut.”

Upcoming research: Job losses by income, demographic group and zip code

ISEA will release more in-depth research on job automation in the coming weeks. This includes more in depth analysis on how automation will affect income as well as employment in each metropolitan area. Since job automation will not affect all demographic groups equally, ISEA will explore potential job losses by race, gender, age, and education level.

Researchers will also use ISEA’s proprietary zip code economic data to calculate zip code estimates for job losses. Not only is job automation changing the relative standing of U.S. cities, but this research will show how automation is changing the structure of a city itself.


For more information about this research, please contact:

Jess Chen, PhD, Faculty Fellow: jess_chen@redlands.edu

Johannes Moenius, PhD, Director: Johannes_moenius@redlands.edu, 909-557-8161

Institute for Spatial Economic Analysis, University of Redlands

About the University of Redlands Institute for Spatial Economic Analysis (ISEA)

The Institute for Spatial Economic Analysis (ISEA) serves regional, national and global business and government leaders in their needs to better understand how socio-economic phenomena affect their communities. A division of the University of Redlands School of Business, ISEA publishes ongoing, timely reports covering retail, employment, housing, logistics and other special topics. A key distinction of the Institute is its ability to illustrate economic trends and patterns through the use of geo-spatial mapping techniques. In addition, ISEA’s ability to provide Zip code level analysis for many of its reports provides unprecedented detail. Current ISEA economic data and interactive maps may be found at http://www.iseapublish.com/map

About ISEA Publish

ISEA Publish is the independent research-publishing arm of the Institute for Spatial Economic Analysis at the University of Redlands, School of Business. ISEA Publish offers consulting services to help regions understand their local economy and prepare for potential threats like job automation. Areas of expertise include:

  • Analyzing local economic structure
  • Identifying “peer” regions with similar economic structure
  • Understanding the threat of automation by region

These services are big-data driven, affordable and customizable, and are based on ISEA’s zip code economic data and mapping platform.

For more information about ISEA Publish and its data and consulting offers, please contact:

Christian Staack, CEO, ISEA Publish, info@iseapublish.com, 909-312-3750