# Xin Liu

## Assistant Professor, Economics

## Washington State University

## xin.liu1@wsu.edu

## Office: Hulbert Hall

## Google Scholar profile

## Curriculum Vitae

## Fields of Interests:

Econometric Theory, Applied Econometrics, Quantile Regression, Panel Data

# Working Papers

## A quantile-based nonadditive fixed effects model

2020/2024, *submitted*

paper | code | online appendix

I propose a quantile-based nonadditive fixed effects model to study heterogeneous causal effects, while allowing endogeneity. This model assumes a more general functional form than the standard fixed effects model and complements certain fixed effects quantile regression model (Canay 2011).

## Inference for Panel Quantile Regression with Time-Invariant Rank

2022, * submitted *

I construct uniform confidence bands and bootstrap confidence interval for a quantile-based heterogeneous causal effects function in a nonadditive fixed effects model.

## Averaging Estimation for Instrumental Variables Quantile Regression

2019/2023, *submitted*

paper | code | online appendix

I propose averaging methods to improve IVQR estimation efficiency.

# Publications

## Testing in smoothed GMM quantile models with an application to quantile Euler equation

Forthcoming, *Econometrics and Statistics*

I propose testing methods in smoothed GMM quantile model (de Castro, Galvao, Kaplan, and Liu, 2019), with quantile Euler equation empirical example.

## Confidence Intervals for Intentionally Biased Estimators

2024, *Econometric Reviews*

(with David M. Kaplan)

We propose simple CIs using estimators that are intentionally biased to reduce MSE (like sivqr/SEE-IVQR). At 95% confidence level, these CIs improve the length and coverage probability compared to the benchmark CI using unbiased estimator.

##
*k*-Class Instrumental Variables Quantile Regression

Forthcoming, * Empirical Economics *

(with David M. Kaplan)

published | accepted | code/tex/etc.

We apply k-class estimation to IVQR to reliably reduce median bias for certain choices of k.

## Smoothed GMM for quantile models

2019, *Journal of Econometrics*

(with Luciano de Castro, Antonio Galvao, and David M. Kaplan)

published | accepted | code/tex/etc.

We extend smoothed IVQR estimation (Kaplan and Sun, 2017) to non-iid data, nonlinear and over-identified models, with a quantile Euler equation empirical example.