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The ways that statisticians and governments measure the economy were developed in the 1940s, when the urgent economic problems were entirely different from those of today. Diane Coyle argues that the framework underpinning today’s economic statistics is so outdated that it functions as a distorting lens, or even a set of blinkers. When policymakers rely on such an antiquated conceptual tool, how can they measure, understand, and respond with any precision to what is happening in today’s digital economy?

Coyle argues that to understand the current economy, we need different data collected in a different framework of categories and definitions, and she offers some suggestions about what this would entail.

Diane Coyle is a Professor of Public Policy at the University of Cambridge and author of The Soulful Science: What Economists Really Do and Why it Matters and GDP: A Brief but Affectionate History. Her new book is The Measure of Progress: Counting What Really Matters.

Read Diane Coyle’s new article for Skeptic.

The Trouble with Economic Data: Flawed Metrics, Flawed Decisions

The Michael Shermer Show

The Trouble with Economic Data: Flawed Metrics, Flawed Decisions