Stanford University

MARCH 19, 2024

New Measures of the Economy Workshop 2024
March 19, 2024
Gates Computer Science Building
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As more and more of our economy is driven by digital rather than physical goods, by bits rather than atoms, traditional methods used to measure the economy are not seeing the whole picture. At the same time, techniques for assessing consumer surplus, a key economic concept for value and economic well-being, have improved greatly, reflecting the emergence of massive digital platforms, the explosion of fine-grained digital data, and the increased power of machine learning for prediction and estimation.

At the New Measures of the Economy Workshop, leading academics and subject matter experts join us to explore new tools and techniques to measure modern economies, including the contribution of household production, people’s health, and the environment.

Questions? Please contact David Nguyen or Susan Young.


Bios for panelists below

9:15a PT
Arrivals, breakfast

10:00a PT
David Nguyen, Stanford Digital Economy Lab

Erik Brynjolfsson
Director, Stanford Digital Economy Lab

10:30a PT
Opening keynote
Paul Schreyer
Chief Statistician and Director of Statistics and Data Directorate, OECD

11:15a PT
Session 1: Household Production

Households produce and consume considerable output that is largely overlooked by economic accounts such as GDP. This is because household activities usually do not involve monetary,  market-based transactions. Yet, people make trade-offs between paid and unpaid work all the time (“Should I cook or order dinner?” “Can we afford a nanny?” “Is it worth it getting a cleaner for my 1-bedroom apartment?”). The BEA estimates that in 2020, household production created a value of around $5.3 trillion, or 20% of U.S. GDP. Similarly, the UK’s Office for National Statistics estimates that unpaid household work in 2016 was around 63% of UK GDP and that this kind of work has grown roughly twice as fast as GDP over the previous decade. This panel explores the current state of measuring household production, gaps in conceptual frameworks, methods, and data.

Benjamin Bridgman, US Bureau of Economic Analysis
Diane Coyle, Bennett Institute for Public Policy
John Lourenze Poquiz, King’s College London
Xiupeng Wang, Northeastern University; Digital Fellow, Stanford Digital Economy Lab
David Nguyen, Stanford Digital Economy Lab (Moderator)

12:15p PT

1:30p PT
Session 2: Health

Better health outcomes are desirable. Consider a new health intervention that can prevent certain diseases or reduce their negative effects on people. If such interventions are cheaper than conventional treatment, national accounts would record a decrease in economic activity while people are actually better off. This raises the question of how to properly account for improved welfare from lower mortality or morbidity, also referred to as quality-adjusted life years (QALYs), particularly when there is a time lag between costs and benefit. Similarly, the value of a statistical life (VSL) can be derived using stated preference methods such as people’s willingness to pay for better health outcomes. This panel aims to explore the quality of available measures and data and whether they work in different contexts. We will also discuss new data and techniques that could be leveraged to gain new insights.

David Cutler, Harvard University
Abe Dunn, US Bureau of Economic Analysis
Erica Groshen, Cornell University
Pete Klenow, Stanford University
Angela Aristidou, Stanford University (Moderator)

2:30p PT

3:00p PT
Session 3: Environment

Environmental protection has massive economic and social benefits. Yet, despite considerable progress in estimating the societal benefit of natural and environmental capital (incl. the SEEA), measurement challenges remain. We lack data on people’s willingness to pay for cleaner air and water, preservation of ecosystems and biodiversity, and limiting the rise of global temperatures. The White House’s “National Strategy to Publish Statistics for Environmental-Economic Decisions” (2023) has the stated goal to “quantify the immense value this natural capital provides,” highlighting that current national statistics do not reflect the clear link between the quantity and quality of natural capital and the economy. This panel will explore the limitations of existing measures;what can be done to improve them; and some of the challenges or barriers to getting better measures, including the global dimension of many environmental issues, people’s hypothetical bias, political preferences, or trust in the effectiveness of proposed policies. Is it feasible or even desirable to “produce a single headline summary statistic” within 15 years as the White House strategy calls for?

Matthew Agarwala, Bennett Institute for Public Policy
Matthew Ashenfarb, Yale University, US Department of the Treasury
Vipin Arora, US Bureau of Economic Analysis
Avi Collis, Carnegie Mellon University (Moderator)

4:00p PT
Fireside: Tech Sector Contributions to Welfare

Existing economic measures like GDP are insufficient in capturing the full scope of economic activity, particularly in light of technological advancements like AI. With an increasing reliance on digital rather than physical goods, traditional metrics struggle to account for the value generated, especially in sectors driven by rapid technological changes. As the economy shifts towards intangible goods and services, including those with zero price tags, determining their true impact on people’s welfare becomes crucial. Highlighted by the stagnant share of ICT in GDP, there’s a pressing need to explore alternative yardsticks for assessing the influence of digital platforms and innovations on societal well-being.

Karin Kimbrough, LinkedIn
Nela Richardson, ADP
Hal Varian, Google
Saadia Zahidi, World Economic Forum
Erik Brynjolfsson, Director, Stanford Digital Economy Lab (Moderator)

5:00p PT

6:00p PT


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