Search Results for author: Liangjun Su

Found 8 papers, 1 papers with code

A Robust Residual-Based Test for Structural Changes in Factor Models

no code implementations3 Jun 2024 Bin Peng, Liangjun Su, Yayi Yan

In this paper, we propose an easy-to-implement residual-based specification testing procedure for detecting structural changes in factor models, which is powerful against both smooth and abrupt structural changes with unknown break dates.

Tests for Many Treatment Effects in Regression Discontinuity Panel Data Models

no code implementations2 Dec 2023 Likai Chen, Georg Keilbar, Liangjun Su, Weining Wang

We find that in the Gaussian approximations to the test statistics, the dependence structures in the data can be safely ignored due to the localized nature of the statistics.


Panel Data Models with Time-Varying Latent Group Structures

no code implementations29 Jul 2023 Yiren Wang, Peter C B Phillips, Liangjun Su

With the preliminary nuclear-norm-regularized estimation followed by row- and column-wise linear regressions, we estimate the break point based on the idea of binary segmentation and the latent group structures together with the number of groups before and after the break by sequential testing K-means algorithm simultaneously.

Low-rank Panel Quantile Regression: Estimation and Inference

no code implementations20 Oct 2022 Yiren Wang, Liangjun Su, Yichong Zhang

In this paper, we propose a class of low-rank panel quantile regression models which allow for unobserved slope heterogeneity over both individuals and time.


A One-Covariate-at-a-Time Method for Nonparametric Additive Models

no code implementations26 Apr 2022 Liangjun Su, Thomas Tao Yang, Yonghui Zhang, Qiankun Zhou

Similarly to Chudik, Kapetanios and Pesaran (2018), we consider the statistical significance of individual nonparametric additive components one at a time and take into account the multiple testing nature of the problem.

Additive models

Interactive Effects Panel Data Models with General Factors and Regressors

no code implementations22 Nov 2021 Bin Peng, Liangjun Su, Joakim Westerlund, Yanrong Yang

This paper considers a model with general regressors and unobservable factors.

L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis

1 code implementation19 Oct 2020 Zhentao Shi, Liangjun Su, Tian Xie

This paper tackles forecast combination with many forecasts or minimum variance portfolio selection with many assets.

Detecting Latent Communities in Network Formation Models

no code implementations7 May 2020 Shujie Ma, Liangjun Su, Yichong Zhang

This paper proposes a logistic undirected network formation model which allows for assortative matching on observed individual characteristics and the presence of edge-wise fixed effects.

Clustering regression

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