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How Statistics Fool Us Into Bad Policy

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Manage episode 264992649 series 2413433
Innhold levert av Adam Smith Center. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Adam Smith Center eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

In another episode of the Governance and Policy Podcast, we interview Dr Phil Magness, Senior Research Fellow at the American Institute for Economic Research. He is also an economic historian whose work covers the intersection of history and political economy.

Here, he shares his thoughts about how statistics and mathematical models may sometimes be misused or even abused, leading us into bad policy decisions. We discuss the flawed data collection that led to coronavirus city lockdowns and the problems in the research of Thomas Piketty, and his collaborators Saez and Zucman.

  continue reading

32 episoder

Artwork
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Manage episode 264992649 series 2413433
Innhold levert av Adam Smith Center. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Adam Smith Center eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

In another episode of the Governance and Policy Podcast, we interview Dr Phil Magness, Senior Research Fellow at the American Institute for Economic Research. He is also an economic historian whose work covers the intersection of history and political economy.

Here, he shares his thoughts about how statistics and mathematical models may sometimes be misused or even abused, leading us into bad policy decisions. We discuss the flawed data collection that led to coronavirus city lockdowns and the problems in the research of Thomas Piketty, and his collaborators Saez and Zucman.

  continue reading

32 episoder

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