Xuexin Wang

Xuexin Wang

Associate professor at the Wang Yanan Institute for Studies in Economics, Xiamen University, Fujian, China

CV

Education

Publications

  1. Generalized spectral tests for multivariate martingale difference hypotheses, 2024, Journal of Business & Economic Statistics, 42(4) 1195-1209.

  2. An Asymptotically F-Distributed Chow Test in the Presence of Heteroscedasticity and Autocorrelation, 2022, Econometric Reviews, 41:2, 177-206 (with Yixiao Sun, UCSD)

  3. A Simple Asymptotically F-Distributed Portmanteau Test for Time Series Models with Uncorrelated Innovations, 2022, JBES, 40:2, 505-521 ( with Yixiao Sun, UCSD)

  4. Asymptotic F Tests under Possibly Weak Identification, 2020, Journal of Econometrics, 218 (1) 140-177 (with Julián Martínez-Iriarte and Yixiao Sun, UCSD)

  5. An Asymptotic F Test for Uncorrelatedness in the Presence of Time Series Dependence, 2020, Journal of Time Series Analysis, 41(4):536-550 (with Yixiao Sun, UCSD)

  6. A New Class of Tests for Overidentifying Restrictions in Moment Condition Models, 2020, Econometric Reviews, Volume 39, 5, 495-509.

  7. A General Approach to Conditional Moment Specification Testing with Projections, 2018, Econometric Reviews, Volume 37, 2, 140-165

  8. A Joint Portmanteau Test for Conditional Mean and Variance Time Series Models, 2015, Journal of Time Series Analysis, Volume 36, 1, 39-60 (with Carlos Velasco, UC3M)

Working Papers

  1. Instrumental variable estimation via a continuum of instruments with an application to estimating the elasticity of intertemporal substitution in consumption, 2024, with Carlos Velasco, UC3M.
  2. Generalized Spectral Tests for Martingale Difference Hypotheses of Functional Time Series
  3. Consistent Estimation of Models Defined by Conditional Moment Restrictions Under Minimal Identifying Conditions (2019).

Working in Progess

  1. A new class of JIVE estimator for linear instrumental variable models.

  2. A consistent overidentification test for linear models with weak instruments.

  3. Specification Tests for High-dimensional Linear Regression Models.

Teaching

Research Grants