Hal Varian (Google Chief Economist) – Hal Varian on the Economics of Information (Dec 2021)

Chapters

Abstract

The Evolving Landscape of Labor, Technology, and Economic Metrics: An Updated Analysis

Engaging the Future: Technology’s Role in Shaping Labor and Economic Understanding

In the rapidly evolving world of technology and economics, the interplay between automation, demographic changes, and the challenge of accurately measuring economic growth stands at the forefront of contemporary discourse. Hal Varian, Google’s chief economist, recently shed light on these complex dynamics at a symposium, offering a multifaceted view that intertwines the future of the labor market, the role of automation, and the intricacies of GDP measurement.

Automation and the Labor Market: A Symbiotic Relationship

Varian’s insights reveal a labor market in flux, primarily influenced by technological advancements in automation, including robotics and AI. Contrary to the fear of widespread job replacement, automation has led to a shift in the nature of jobs rather than their outright disappearance. Tasks are evolving, with highly varied roles like gardening and hotel services showing resilience against automation due to their diverse nature. Moreover, the development of autonomous vehicles, a hallmark of modern automation, faces practical challenges in adapting to complex environments like city streets.

Automation and computerization shift the demand for human labor, and the supply side is also influenced by demographic determinants. While automation may displace certain tasks, it can also create new ones, leading to shifts in the nature of work within organizations and across occupations. However, routine tasks in standardized environments are often more susceptible to automation than complex and diverse ones.

The value of software and design contributes significantly to the mobile phone industry’s revenue. Half of the iPhone SE’s $400 billion industry value is derived from software and design, demonstrating the importance of intangible assets.

Demographic Trends and the Labor Force

Demographic factors, such as aging populations and slowing labor force growth, add another layer to this narrative. They necessitate increased productivity, a gap that automation is poised to fill. However, the complete automation of complex tasks remains a distant goal, requiring significant time and investment. The gradual impact of automation allows for workforce adjustment and upskilling, an essential factor in mitigating job displacement.

The labor force growth rate is slowing down due to the retirement of baby boomers and the reduced entry of women into the labor force. This trend is evident in developed countries like the US, Japan, Korea, China, Germany, Italy, and Spain, where a demographic crisis is looming with fewer workers supporting a larger non-working population. Increasing productivity through automation is crucial to address these coming labor shortages, which are expected to persist for several decades. Traditional intuitions about firms always finding the labor they need will change dramatically in the 2020s and 2030s due to labor shortages.

Hal Varian suggests that demographic trends will lead to a tighter labor market, as the supply of workers is expected to decrease relative to demand. Varian emphasizes that the shift in labor supply and demand could lead to increased wages, particularly for low-skill jobs that are susceptible to automation. Varian cites the Netherlands as an example of a country with a shorter workweek and more flexible work arrangements, which could be a model for other countries to follow.

The Puzzle of Productivity and GDP Measurement

Despite technological progress, a paradox emerges: the slowdown in productivity growth. This contradiction becomes more pronounced when examining the complexities of GDP measurement in a modern economy dominated by services and intangible assets like design and software. These intangible elements, while increasingly prevalent, present significant challenges in quantification.

The debate centers on whether GDP and other economic well-being measures are inaccurate, leading to an underestimation of actual progress. The increasing prevalence of services and intangible goods poses measurement difficulties. Services, which employ 80% of the labor force, are hard to assess for quality improvements and quantify. Traditional GDP measurement, designed during World War II, was straightforward for physical goods production. Measuring services and intangibles is more challenging due to the absence of market transactions. Design and software, integral to the economy, are hard to quantify in GDP. Apple’s iPhone design and software, produced in the US and assembled in China, are measurable. However, the accompanying email attachments, software updates, and design plans, which don’t involve market transactions, are difficult to measure. Google’s Android operating system, being open source and free, poses measurement challenges. The zero price of Android makes it hard to gauge its economic value.

Free or shared photos, despite their increasing quantity, are not reflected in GDP due to their lack of market sales. Similarly, GPS prices have fallen to zero, resulting in their removal from GDP calculations, neglecting quality improvements.

Advancing Economic Metrics and Understanding Big Data

In response to these measurement challenges, there’s a growing need for broader metrics that encompass aspects like well-being and sustainability, offering a more holistic view of economic health. The incorporation of private sector data and more unconventional sources, such as Google queries and social media, could enhance statistical methods, although these require rigorous validation.

In the field of big data, economists employ various methods to establish causality. Studies, such as one examining the effect of Super Bowl ads on movie ticket sales, illustrate the potential insights derived from observational data. This evolving landscape also raises questions about the application of antitrust laws in the age of platform technologies and the viability of the free content paid advertising model.

A National Academy of Sciences (NAS) meeting focused on the intersection of causality and big data. Economists have been at the forefront of techniques to establish causality from observational data. Super Bowl ads are sold out months in advance, and home cities of competing teams see elevated viewership by 10-15%. Researchers conducted a study of Super Bowl ads and movie viewership to infer a causal relationship. Movies advertised during the Super Bowl had higher opening weekend audiences in the home cities of competing teams. The study provided evidence that Super Bowl ads can influence purchase behavior. Opening weekend revenue for movies increased by approximately $7 million with an average ad cost of $3 million.

GAFA, or GAFAM, are the large technology companies that are commonly referred to as having monopoly power in Europe. However, these platforms compete intensely against each other in various industries. Each of these companies has a core competency but they constantly compete across different industries. Amazon’s entry into cloud computing is an example of unexpected competition.

The Road Ahead: Labor Market Outlook and Technological Integration

Looking forward, Varian predicts a tighter labor market influenced by demographic trends like an aging population and dwindling workforce entries. This scenario may lead to higher wages and demand for flexible work arrangements. The role of education and training in equipping the workforce for this transition is paramount, with online platforms emerging as key resources.

However, Varian also acknowledges the potential for a widening socioeconomic divide due to automation and technological change. He suggests that mitigating factors such as a tighter labor market and increased access to education could help bridge this gap. Moreover, the interplay of automation and demographic trends could have complex effects on inflation and interest rates, warranting careful analysis.

The coming decades will present challenges due to labor shortages, but these can be addressed through productivity gains enabled by automation. While technological advancements in AI and ML have been significant, the impact of automation on employment may be less disruptive than often portrayed in the media.

The smartphone has replaced multiple devices like cameras, GPS systems, and alarm clocks, reducing sales of these individual items and potentially negatively affecting GDP. The lack of quality adjustment in smartphone figures further limits the accurate reflection of its value in GDP.

Leveraging Technology for Economic and Educational Advancements

Kaggle, an angel investment by Varian, exemplifies the potential of technology in enhancing economic understanding and addressing educational disparities. By hosting machine learning contests with significant incentives, platforms like Kaggle demonstrate how new algorithms can improve prediction and performance. These technological advancements, alongside resources like Khan Academy, provide solutions to educational challenges, thus fostering economic growth and individual success.

Machine Learning Contests:

Kaggle, a platform for machine learning contests, hosts competitions with real-world datasets, such as predicting hospital readmissions or housing prices.

Google and Zillow have also sponsored contests to improve YouTube video categorization and housing price prediction algorithms.

These contests demonstrate the practical value of machine learning and reward improved performance.

Challenges to Labor Dispersion:

Education, particularly higher levels, plays a significant role in labor segmentation and wage inequality.

Factors like family background and access to education contribute to these disparities.

Khan Academy as a Potential Solution:

Platforms like Khan Academy provide educational resources, especially in mathematics, a common stumbling block for students.

Access to Khan Academy can help students overcome educational challenges, potentially leading to increased opportunities and economic growth.

Economic Impact of Parental Involvement:

Children without educated parents may struggle to acquire educational skills, hindering their success and contributing to economic inequality.

Addressing Challenges and Futurity:

While there are no easy solutions, technological advancements and resources like Khan Academy offer potential assistance in addressing these issues.

Ongoing research and exploration are necessary to fully understand and mitigate the challenges affecting labor dispersion and economic growth.

Navigating a Complex Economic Landscape

As we navigate this intricate economic landscape, the insights from Varian and the broader economic discourse highlight the need for adaptability, thoughtful integration of technology, and the evolution of economic metrics. Understanding and harnessing these dynamics is crucial in shaping a future where technology and human labor not only coexist but thrive in synergy.

Notes by: Hephaestus