Published Aug 3, 2020

John Kay and Mervyn King on Radical Uncertainty

Economists John Kay and Mervyn King challenge the reliance on traditional economic models, advocating for a broader, more flexible approach to decision-making in the face of radical uncertainty, where embracing human judgment and abductive reasoning becomes essential.
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Episode Highlights

  • Models as Puzzles

    Economic models often resemble puzzles that provide insights but fail to capture the complexity of the real world. argues that while these models can offer valuable perspectives, they are limited to "small worlds" where assumptions hold true 1. In reality, decisions in government, business, and personal life occur in a "larger world" where such models fall short. He emphasizes the danger of over-relying on models, noting that they are not equipped to provide precise predictions due to their dependence on human behavior parameters 2.

    The great danger of the use of models by economists is that they believe that this applies to the whole panoply of human life.

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    Kay's critique highlights the need for broader perspectives in economic decision-making.

       

    Critique of Predictions

    The failure of economic models to predict significant events is a critical issue. points out that these models often rely on assumptions that don't hold up in real-world scenarios, especially during major economic shifts 3. He criticizes the "as if" methodology, which assumes people behave in predictable ways, leading to flawed predictions. adds that cost-benefit analyses often rely on fabricated data, rendering their conclusions meaningless 4.

    Whenever economics has tried to make forecasts about the future, the results have been pretty woeful.

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    This critique underscores the limitations of traditional economic forecasting methods.

       

    Complexity in Economics

    Economics is inherently complex, and traditional models often oversimplify this complexity. compares economics to physics, noting that unlike physics, economics cannot easily quantify its variables due to their dynamic nature 5. argues that economists often forget the "as if" nature of models, mistakenly treating them as reality 6. This leads to misguided policy recommendations based on flawed assumptions.

    Life is not an optimization problem, and we'd like to think it is sometimes.

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    The discussion calls for a reevaluation of how economic models are used in understanding human behavior.

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