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Statistical Inference on the Monotonic Index Model Based on Monotone Rank Estimate

LIU, Peng (2020) Statistical Inference on the Monotonic Index Model Based on Monotone Rank Estimate. Working paper. TBA (Submitted) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:81832)

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In this paper, we propose a likelihood ratio test statistic for the monotone rank estimators on the monotonic linear index model. Unlike the usual likelihood ratio test, we treat the U-statistic

object function as a likelihood, and different from the traditional asymptotic results for likelihood ratio test, we prove that the limiting distribution is a weighted sum of chi-squared istribution, with weights depend on the unknown parameters. To handle this obstacle in practical situation, we apply two methods to approximate the null distribution, the first one is to use a scale-shifted chi-squared approximation, the second one is to use the Rao-Scott correction. We find that both methods work well. A real data is used to illustrate its use in practical situation.

Item Type: Reports and Papers (Working paper)
Subjects: H Social Sciences > HB Economic Theory
Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Peng Liu
Date Deposited: 23 Jun 2020 14:43 UTC
Last Modified: 16 Feb 2021 14:13 UTC
Resource URI: (The current URI for this page, for reference purposes)

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