Estimating Consumer Welfare Gains from Free Online Services

Featured in print Digest

This figure is a scatter plot titled, Correlation between Valuation of Digital Goods and GDP per capita. The y-axis is labeled, Valuation of digital goods by Facebook users, percentage of GDP per capita. It ranges from 0 to 25 percent, increasing in increments of 5. The x-axis is labeled, GDP per capita, 2020 USD. It ranges from 0 to 100000, increasing in increments of 20000.  There are 13 points on the scatter plot, each point representing a different country. There is a dotted line representing a best fit line. The dotted line starts in the upper left corner of the graph and declines towards the bottom right hand side of the graph, showing a negative correlation between the valuation of digital goods and GDP per capita.  The note on the figure reads, Estimates are based on survey valuations of willingness to pay. Bars represent 95% confidence intervals. The source line reads, Source: Researchers’ calculations using data from multiple sources and surveys.

Over the last decade, digital products such as Google, WhatsApp, and Facebook have proliferated. In the US and UK, for example, people now spend an average of 24 hours online each week. The statistics suggest the possibility of substantial welfare gains for consumers, who typically access these products at no cost. They also present a measurement challenge to traditional measurement methods that rely on price data to construct national accounts metrics such as GDP.

In The Digital Welfare of Nations: New Measures of Welfare Gains and Inequality (NBER Working Paper 31670), Erik BrynjolfssonAvinash CollisAsad LiaqatDaley KutzmanHaritz GarroDaniel DeisenrothNils Wernerfelt, and Jae Joon Lee use a survey-based experiment to estimate the welfare impacts of digital goods. The researchers use Facebook’s internal survey platform to administer a large-scale incentivized online choice experiment to 39,717 Facebook users across 13 countries. They query users about their preferences regarding ten digital goods — Facebook, Twitter, Instagram, WhatsApp, Snapchat, TikTok, Google Search, Google Maps, YouTube, and Amazon Shopping — as well as the amount of money they would be willing to accept in exchange for deactivating their Facebook accounts for one month. They use the resulting survey data to calculate the consumer welfare gains generated by each of these products.

Freely available digital goods reduce welfare inequality between richer and poorer countries as well as between richer and poorer individuals.

The survey data suggest that among Facebook users, the ten digital goods generate $2.52 trillion in consumer welfare across the 13 countries, corresponding to 5.95 percent of the countries’ total GDP, and ranging from $1.29 trillion in the United States to $13 billion in Romania. The gains represent a higher share of income in lower-income countries as well as a higher share of income among individuals with lower income and wealth. The researchers therefore conclude that freely available digital goods reduce disparities in consumer welfare both within and across nations.

The results suggest that most of the welfare gains from using these digital goods accrue to consumers and not to the platforms. For example, the researchers estimate that the user value generated by Facebook is $284 billion for the 13 countries studied, more than twice as much as Meta’s $115 billion in advertising revenue from Facebook, Instagram, and WhatsApp globally.

Because free digital goods generate substantial welfare for consumers but are not included in GDP, economic growth and labor productivity — typically defined as GDP per hour worked — have been underestimated in recent years, at least for the countries in the study’s sample. Traditional measures of output and productivity do not reflect the full contribution of digital goods.

The researchers’ findings are not driven by consumers who spend an outsize amount of time on digital platforms. The estimated welfare gains are distributed across a broad range of users, not concentrated among those who are very active online.

— Abby Hiller

A.L., D.K., H.G., and D.D. are employees of Meta Platforms and hold a financial interest in Meta. N.W. was an employee of Meta while this research was conducted though he no longer holds a financial interest in the company. All other authors declare no current competing interests, although E.B. and A.C. have in the past been awarded unrestricted gifts from Meta and receive final support from the Stanford Digital Economy Lab which is in turn partially funded by a variety of entities.