Digital goods and services play an ever-increasing role in people’s private and professional lives. We spend hours consuming content, often free at the point of use. However, in the absence of price signals, traditional metrics such as GDP and productivity fail to fully account for the welfare effects from digital goods. While GDP measures market-based production and consumption, it arguably does not account for most aspects that make life worth living. Following Kuznets, it was never designed to be a measure of welfare, though de facto GDP per capita is being used to approximate a country’s welfare. There is concern that the wedge between measured GDP and implied consumer welfare is increasing over time. Given that we are ultimately interested in people’s well-being makes it more pertinent than ever to get a better measure of consumer welfare. Our approach starts from basic principles of economics: changes in well-being stem from changes in the economic surplus created by goods and services, rather than the money spent on them. We use massive online survey-based experiments to estimate the welfare contributions of digital and non-digital goods. We elicit willing-ness-to-pay and willingness-to-accept measures for hundreds of items in the United States and the United Kingdom. This presentation will cover the basic framework, theory, and empirical methods used to derive GDP-B. We will also discuss some recent findings from the US and pilot results from China.

scoco@ceibs.edu