A parametric bootstrap approach for one-way classification model with skew-normal random effects

Ye, Ren-dao; Xu, Lihua; Luo, Kun; Jiang, Ling

doi:10.1007/s11766-019-3564-x

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…As a kind of mixed effect model containing time series and cross-sectional data, the panel data model has been widely used in the field of econometrics (Ye & Jiang, 2018). Besides skew-normal model, there are different econometric tools to model the panel data, such as panel GEE or panel GMM.…”

Section: Skew-normal Panel Data Modelmentioning

confidence: 99%

Relationship Between Interest Rate and Risk of P2P Lending in China Based on the Skew-Normal Panel Data Model

Ye,

Lin

2023

Sage Open

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This study examines the relationship between interest rate and defunct platform risk of China’s peer-to-peer (P2P) lending platforms. P2P lending provides an alternative funding source for individuals and micro-enterprises and offers a new investment tool for households. But the frequent collapses of many platforms were huge losses to market participants and even led to a decline in China’s P2P lending industry. In this study, weekly data of 76 platforms from December 3, 2017, to October 6, 2019, are employed, and empirical research based on the normal and skew-normal panel data model respectively is conducted. Statistical indicators prove that the skew-normal panel data model is preferable to another one in modeling the data set of interest rates. The empirical results show that China’s P2P market is efficient overall. But the positive correlation between the interest rate and risk is not significant for platforms with excessively high interest rates, whose interest rates are more determined by the types of ownership. The findings and implications are provided in the end.

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Section: Skew-normal Panel Data Modelmentioning

confidence: 99%

Relationship Between Interest Rate and Risk of P2P Lending in China Based on the Skew-Normal Panel Data Model

Ye,

Lin

2023

Sage Open

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“…However, when the sample size is small, the Type I error rates of the RT test in Huwang et al [17] seem to be conservative. To solve this problem, many researchers suggested adopting the PB test to control the Type I error rates, such as Efron and Tibshirani [18], Krishnamoorthy et al [19], Xu et al [20], Xu [21], Ye et al [22], Sun and Fisher [23], among others.…”

Section: Introductionmentioning

confidence: 99%

A Parametric Bootstrap Approach for a One-Way Error Component Regression Model with Measurement Errors

Yue,

Shi,

Luo

et al. 2023

Mathematics

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In this paper, a one-way error component regression model with measurement errors is considered. The unknown parameter vector is estimated by using the bias-corrected method, and its corresponding asymptotic properties are also developed. For the hypothesis testing problem of the vector of the coefficient parameter in the model, a parametric bootstrap (PB) method is proposed. Under various sample sizes and parameter configurations, the effectiveness of our proposed PB test method is discussed by using some numerical simulations and a real data analysis.

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Bootstrap inference of the skew-normal two-way classification random effects model with interaction

Luo

et al. 2022

Appl. Math. J. Chin. Univ.

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A parametric bootstrap approach for one-way classification model with skew-normal random effects

Cited by 6 publications

References 14 publications

Relationship Between Interest Rate and Risk of P2P Lending in China Based on the Skew-Normal Panel Data Model

Relationship Between Interest Rate and Risk of P2P Lending in China Based on the Skew-Normal Panel Data Model

A Parametric Bootstrap Approach for a One-Way Error Component Regression Model with Measurement Errors

Bootstrap inference of the skew-normal two-way classification random effects model with interaction

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