Dingel and Tintelnot (2026)
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Econometrica distributed the published version of Spatial Economics for Granular Settings in March. It’s relevant for anyone working with high-dimensional data like commuting flows, trade flows, or migration flows. Our main point is that spatial models calibrated to observed flows suffer overfitting problems in granular settings. Felix Tintelnot and I diagnose the problem, show data smoothing performs better, and introduce a finite model to quantify counterfactual uncertainty.
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