Paper Summary
Source: National Bureau of Economic Research
Authors: James Feigenbaum and Daniel P. Gross
Published Date: 2020-11-01
Podcast Transcript
Hello, and welcome to paper-to-podcast. Today, we have a fascinating paper to discuss, titled "Answering the Call of Automation: How the Labor Market Adjusted to the Mechanization of Telephone Operation." I've read 100% of this paper, authored by James Feigenbaum and Daniel P. Gross, and it provides some intriguing insights into the effects of automation on employment.
Ready for a blast from the past? Let's dive into the early 20th century when young, white, American-born women were working as telephone operators. Feigenbaum and Gross found that when cities switched to automated telephone systems, the number of young operators dropped by a whopping 50 to 80%. But fear not, for these women proved to be quite adaptable! Instead of suffering from unemployment, they shifted into other occupations like secretarial work and restaurant jobs. So, the labor market essentially said, "New phone, who dis?" and the ladies answered, "We got this."
The authors didn't stop there, though. They also studied the effects of automation on incumbent operators by linking women in the 1920 and 1930 census data. Turns out, incumbent operators were more affected, facing a 10% reduction in employment rates. Moreover, displacement effects were more dominant in environments that were less conducive to task reinstatement for young women, such as manufacturing-intensive cities or those with slack aggregate demand due to the Great Depression.
Now, you may ask, "How on earth did they dig up this info?" Well, the researchers went all Sherlock Holmes by collecting data on local adoption of mechanical switching from AT&T archival records and historical newspaper articles. They then used U.S. census data to measure local outcomes in cities between 1910 and 1940, focusing on adult non-farm populations.
To expand their analysis, Feigenbaum and Gross employed a novel approach using the FamilySearch genealogy platform to link women working as telephone operators in the 1920 and 1930 census data. This method helped them trace the impact of automation on these workers and their families over time. The gathered data was then analyzed using econometric techniques to understand the effects of automation on employment, wages, and occupational mobility across different cohorts of workers, as well as the role of labor unions in the process.
Now, let's talk strengths and limitations. The most compelling aspects of this research include the use of a unique historical setting to study the effects of automation on employment, an in-depth analysis of both existing and future workers, and the innovative use of various data sources, such as historical newspapers and genealogical records. However, potential limitations include concerns about external validity due to the historical setting and specificity of the job and industry, as well as the focus on a single demographic group, which may not represent the entire labor force.
This research offers valuable insights for policymakers, educators, businesses, and industry leaders, helping them understand the implications of technology-driven job displacement and the importance of task creation for workforce adaptation. By understanding how historical automation events affected workers and labor markets, decision-makers can design policies that facilitate smooth transitions for workers in the face of today's rapidly advancing technology.
Moreover, these findings can contribute to the ongoing discussion on the future of work, particularly regarding the need for social safety nets and support systems for workers displaced by technology. By considering the historical context and the experiences of different cohorts of workers, stakeholders can develop targeted interventions that address the specific challenges faced by individuals in the context of automation and labor market shifts.
And that's a wrap! You can find this paper and more on the paper2podcast.com website. Thanks for tuning in and catch you on the next episode!
Supporting Analysis
In this research, the authors investigate the effects of automation on the employment of young, white, American-born women who worked as telephone operators in the early 20th century. They found that when cities switched to automated telephone systems, there was a sharp decline in the number of young operators, dropping by 50 to 80%. However, despite this significant decrease in operator jobs, the overall employment rates for these women did not suffer. Instead, they shifted into other occupations, particularly secretarial work and restaurant jobs. The negative impact of automation on telephone operator demand was counteracted by growth in these other sectors. The authors also studied the effects of automation on incumbent operators by linking women in 1920 and 1930 census data. They discovered that incumbent operators were more affected by automation, with a 10% reduction in their employment rates. Furthermore, they found that displacement effects were more dominant in environments that were less conducive to task reinstatement for young women, such as manufacturing-intensive cities or those with slack aggregate demand due to the Great Depression.
The researchers in this study focused on the impact of automation on telephone operators in the early 20th century. They collected data on local adoption of mechanical switching from AT&T archival records and historical newspaper articles. They then used complete count U.S. census data to measure local outcomes in cities between 1910 and 1940, focusing on adult non-farm populations. In order to study individual-level adjustments to automation, a longitudinally-linked sample of women telephone operators was used. To expand their analysis, the researchers employed a novel approach using the FamilySearch genealogy platform to link women working as telephone operators in the 1920 and 1930 census data. This method helped them trace the impact of automation on these workers and their families over time. The gathered data was then analyzed using econometric techniques to understand the effects of automation on employment, wages, and occupational mobility across different cohorts of workers, as well as the role of labor unions in the process. The researchers also considered the external validity of their findings and the implications of the historical setting and industry-specific context.
The most compelling aspects of this research include the use of a unique historical setting to study the effects of automation on employment, an in-depth analysis of both existing and future workers, and the innovative use of various data sources, such as historical newspapers and genealogical records. The researchers followed best practices by thoroughly examining the robustness of their results using different estimation methods, controlling for potential confounders, and employing a detailed description of their data collection process. Furthermore, they made an effort to establish the external validity of their findings by comparing their insights to task-based theories of automation and economic growth. The researchers also contributed to the literature by providing a unified view of how automation affects a range of exposed workers, including future generations, which is often difficult to study in other settings. Overall, the study is well-executed, and the insights drawn are informative for understanding the impacts of automation on employment in various contexts.
Possible limitations of the research include concerns about external validity due to the historical setting and specificity of the job and industry. The study focuses on a single firm (AT&T) and a particular occupation (telephone operators) during a specific time period. This may raise questions about the generalizability of the findings to other industries, jobs, and time periods. Furthermore, the research relies on historical newspaper articles and archival records, which could be incomplete or subject to inaccuracies. Although the authors attempt to validate their findings through various methods, there remains a possibility that some data might be missing or misinterpreted. Additionally, the study largely focuses on smaller cities, which might exhibit different trends and outcomes compared to larger urban areas. Finally, the research examines a specific demographic group (young, white, American-born women), which may not represent the entire labor force and could limit the applicability of the findings to other demographic groups or contexts.
Potential applications for this research include informing policymakers and educators on the implications of technology-driven job displacement and the importance of task creation for workforce adaptation. By understanding how historical automation events affected workers and labor markets, decision-makers can design policies that facilitate smooth transitions for workers in the face of today's rapidly advancing technology. These insights can also help guide the development of educational and vocational training programs that focus on skills relevant to the evolving job market. Additionally, this research can be valuable for businesses and industry leaders in understanding how to better integrate new technologies without causing significant disruptions to the workforce. By recognizing the potential for endogenous task reinstatement, companies can invest in the development of new tasks and roles that complement automation, ultimately benefiting both the labor force and the economy. Moreover, the research can contribute to the ongoing discussion on the future of work, particularly regarding the need for social safety nets and support systems for workers displaced by technology. By considering the historical context and the experiences of different cohorts of workers, stakeholders can develop targeted interventions that address the specific challenges faced by individuals in the context of automation and labor market shifts.