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因子数随样本量增长时的因子数量确定AI 解读

Correctly specifying the number of factors (r) is a fundamental issue for the application of factor models. In this paper we develop an econometric method to estimate the number of factors in factor models of large dimensions where the number of factors is allowed to increase as the two dimensions, cross-section size (N) and time period (T) increase. Using similar information criteria as proposed by Bai and Ng (2002), we show that the number of factors can be consistently…

基于k近邻估计的一致模型设定检验AI 解读

We propose a simple consistent test for a parametric regression functional form based on k-nearest-neighbor (k-nn) method. We derive the null distribution of the test statistic and show that the test achieves the minimax rate optimality against smooth alternatives. A wild bootstrap method is used to better approximate the null distribution of the test statistic. We also propose a k-nn statistic which tests for omitted variables nonparametrically. Simulations and an empirical…

固定效应面板部分指定Tobit回归的估计AI 解读

This paper presents an estimation of a partly specified Tobit model with fixed effects by extending the symmetric trimming procedure proposed in Honoré (1992). Under some sufficient conditions, we present conditions to identify both the parametric and the nonparametric component of the unknown parameter. Under some sufficient conditions, we establish that the proposed estimates are consistent and the estimates of the parametric component are asymptotically normally…