Peer-reviewed publications


  1. Wenzhe Yin, Shujian Yu, Yicong Lin, Jie Liu, Jan-Jakob Sonke, and Stratis Gavves (2024). Domain adaptation with Cauchy-Schwarz divergence. Proceedings of the Uncertainty in Artificial Intelligence (UAI 2024).  [Accepted]
  2. Marina Friedrich and Yicong Lin (2024). Sieve bootstrap inference for linear time-varying coefficient models. Journal of Econometrics 239(1), 105345. [Open Access]
  3. Eric Beutner, Yicong Lin, and Stephan Smeekes (2023). GLS estimation and confidence sets for the date of a single break in models with trends. Econometric Reviews 42(2), 195-219. [Open Access]

Working papers


  1. Eric Beutner, Yicong Lin, and Andre Lucas. Consistency, distributional convergence, and optimality of filtered time-varying parameter paths of observation-driven models. [Submitted]
    • previous title: Consistency, distributional convergence, and optimality of score-driven filters.
    • TI discussion paper
  2. Yicong Lin, Mingxuan Song, and Bernhard van der Sluis. Bootstrap inference for linear time-varying coefficient models in locally stationary time series. [R&R]
    • Python code and data (maintainer: Mingxuan Song, Bernhard van der Sluis)
    • previous title: Robust bootstrap inference for linear time-varying coefficient models: Some Monte Carlo evidence
  3. Yicong Lin and Hanno Reuvers. Cointegrating polynomial regressions with power law trends [R&R]
  4. Yicong Lin, Bernhard van der Sluis, and Marina Friedrich. Bootstrapping trending time-varying coefficient panel models with missing observations. [Submitted]
  5. Marina Friedrich, Yicong Lin, Pavitram Ramdaras, Sean Telg, and Bernhard van der Sluis. Modelling time-varying relations in housing prices: A semiparametric panel approach. [Submitted]
  6. Yicong Lin and Hanno Reuvers. Fully modified estimation in cointegrating polynomial regressions: Extensions and Monte Carlo comparison. [Revision requested]