- uncertainty, complexity and rank. First, the concept of epistemic uncertainty is sufficient for modeling and the concept of … model rank, as the Cowles Foundation erroneously prescribed in the early 1950s, and superimposing that model rank on the … data, when a model is estimated. But the model rank does not have to be presumed: it can be identified from the data and …

This paper presents recent developments in model selection and model averaging for parametric and nonparametric models … the context of nonparametric models. In applications, estimation and inference are often conducted under the selected … and nonparametric cases. Some possible topics for future research are also indicated. …

heterogeneity. This paper proposes two nonparametric slope estimation where the unobserved effect is treated as fixed across cross …. In this paper we estimate nonparametric slope of age and tenure on earnings using NLSY data and compare it to the …In panel data the interest is often in slope estimation while taking account of the unobserved cross sectional …

This paper presents recent developments in model selection and model averaging for parametric and nonparametric models … the context of nonparametric models. In applications, estimation and inference are often conducted under the selected … and nonparametric cases. Some possible topics for future research are also indicated. …

is unknown but parametric, it is conjectured from the literature that we still need nonparametric propensity score … estimate the propensity score by a nonparametric method in applications. …