加权平均有限信息极大似然估计

IF 1.2 3区数学 Q2 STATISTICS & PROBABILITY

Statistical Papers Pub Date : 2023-10-07 DOI:10.1007/s00362-023-01485-2

Muhammad Qasim

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引用次数: 0

摘要

摘要提出了一种stein型加权有限信息极大似然估计。它基于普通最小二乘(OLS)和LIML估计量的加权平均值，其权重与Hausman检验统计量成反比。利用局域到外生渐近理论推导了该估计量的渐近分布。此外，还计算了stein型LIML估计量的渐近风险，并证明了在一定条件下，其风险严格小于LIML的风险。通过蒙特卡罗模拟和北欧国家绿色专利数据集的实证应用，证明了stein型LIML估计量在仪器数量较大时优于OLS、两阶段最小二乘、LIML和组合估计量。

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A weighted average limited information maximum likelihood estimator

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A weighted average limited information maximum likelihood estimator

Abstract In this article, a Stein-type weighted limited information maximum likelihood (LIML) estimator is proposed. It is based on a weighted average of the ordinary least squares (OLS) and LIML estimators, with weights inversely proportional to the Hausman test statistic. The asymptotic distribution of the proposed estimator is derived by means of local-to-exogenous asymptotic theory. In addition, the asymptotic risk of the Stein-type LIML estimator is calculated, and it is shown that the risk is strictly smaller than the risk of the LIML under certain conditions. A Monte Carlo simulation and an empirical application of a green patent dataset from Nordic countries are used to demonstrate the superiority of the Stein-type LIML estimator to the OLS, two-stage least squares, LIML and combined estimators when the number of instruments is large.

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来源期刊

Statistical Papers 数学-统计学与概率论

CiteScore

2.80

自引率

7.70%

发文量

审稿时长

6-12 weeks

期刊介绍： The journal Statistical Papers addresses itself to all persons and organizations that have to deal with statistical methods in their own field of work. It attempts to provide a forum for the presentation and critical assessment of statistical methods, in particular for the discussion of their methodological foundations as well as their potential applications. Methods that have broad applications will be preferred. However, special attention is given to those statistical methods which are relevant to the economic and social sciences. In addition to original research papers, readers will find survey articles, short notes, reports on statistical software, problem section, and book reviews.