A common misconception is that the risk of overfitting increases with the number of parameters in the model. In reality, a single parameter suffices to fit most datasets: arxiv.org/abs/1904.12320
Implementation available at: github.com/Ranlot/single-…
Implementation available at: github.com/Ranlot/single-…
This is problematic, because many popular econometric methods regularize fitted functions by counting the number of regressors (eg AIC, aR2). This paper shows that those classical approaches are misguided. Model complexity is not necessarily a function of the number of regressors
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