approach is loosely based on the sequential Fama-MacBeth approach and developed in a kernel regression framework. However, the …

suggest reporting estimates using nonlinear kernel regressions and the standardization of all variables to avoid p-hacking. We … are filling an essential gap in the literature because p-hacking-related papers do not even mention kernel regressions or … cross-section of firms and financial management in macroeconomic time series. We estimate nonlinear, nonparametric kernel …

parametric estimator and a nonparametric estimator based on machine learning. A popular kernel-based machine learning algorithm …, known as the kernel-regularized least squares estimator, is used to estimate the nonparametric component. We discuss how to …