The Trouble with Economic Data: Flawed Metrics, Flawed Decisions episode artwork

EPISODE · Apr 29, 2025 · 54 MIN

The Trouble with Economic Data: Flawed Metrics, Flawed Decisions

from The Michael Shermer Show · host Michael Shermer, Diane Coyle

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 Diane Coyle argues that the framework underpinning today's economic statistics is so outdated that it functions as a distorting lens, or even a set of blinkers.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.

Episode metadata supplied by the publisher feed · Published Apr 29, 2025

Embed this episode

NOW PLAYING

The Trouble with Economic Data: Flawed Metrics, Flawed Decisions

0:00 54:13

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

No similar podcasts found.

Frequently Asked Questions

How long is this episode of The Michael Shermer Show?

This episode is 54 minutes long.

When was this The Michael Shermer Show episode published?

This episode was published on April 29, 2025.

Can I download this The Michael Shermer Show episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!