In separate blog posts, Russ Roberts and John Cochrane have called for humility on the part of economists. Asking “What do economists know?,” Roberts and Cochrane point out—correctly—that economics is not as strong on quantification as some economists and many pseudo economists pretend, and as is often expected from economists. Economics is not the same as applied statistics although the latter can help clarify, at least to some extent, the empirical relevance of economic theories. Correlation does not imply causation. Identifying assumptions that aim at establishing causal claims based on correlation analysis deserve skepticism, especially when the process that led to the empirical results remains in the dark (see notes on replicability here, here, here). Sound economics heavily relies on consistency checking, or bullshit detection in Cochrane’s words. It insists on keeping accounting identities in mind and never forgetting about incentives. And it is acutely aware of the fact that good models are nothing more than consistent stories—but at least they are consistent stories.
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Dirk Niepelt considers the following as important: Contributions, Economics, Notes, Quantitative research, Replication, Replication crisis, Statistics
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In separate blog posts, Russ Roberts and John Cochrane have called for humility on the part of economists. Asking “What do economists know?,” Roberts and Cochrane point out—correctly—that economics is not as strong on quantification as some economists and many pseudo economists pretend, and as is often expected from economists.
Economics is not the same as applied statistics although the latter can help clarify, at least to some extent, the empirical relevance of economic theories. Correlation does not imply causation. Identifying assumptions that aim at establishing causal claims based on correlation analysis deserve skepticism, especially when the process that led to the empirical results remains in the dark (see notes on replicability here, here, here).
Sound economics heavily relies on consistency checking, or bullshit detection in Cochrane’s words. It insists on keeping accounting identities in mind and never forgetting about incentives. And it is acutely aware of the fact that good models are nothing more than consistent stories—but at least they are consistent stories.