Chencheng Fang

Chencheng Fang

Hausdorff Center for Mathematics
Institute of Finance and Statistics, University of Bonn

About Me

Welcome to my webpage! I am Chencheng Fang, a Ph.D. researcher at Hausdorff Center for Mathematics, and Institute of Finance and Statistics, University of Bonn in Germany. I am co-supervised by Prof. Dr. Dominik Liebl from University of Bonn, and Prof. Dr. Piotr Kokoszka from Colorado State University.
I am currently engaged in theoretical research at the intersection of causal inference and functional data analysis. Also, I have a strong interest in econometric problems arising in applied management and economics research, particularly in developing and refining econometric and statistical methods to better accomodate the practical needs of empirical researchers. Last but not least, I am highly motivated to disseminate my work through the development of R packages and Shiny apps, thereby facilitating transparent and accessible implementation of my research.

Research Interests

  • Econometrics and Statistics
  • Functional Data Analysis
  • Management

Publications and Working Papers

Making Event Study Plots Honest: A Functional Data Approach to Causal Inference

Fang, C., & Liebl, D. (2025)

Working Paper

arXiv

Dimension Adaptive Estimation

Fang, C. (2023)

University of Bonn

PDF

Post-promotion Redemption, Exposure, and Spillover Effects of Electronic Coupons: An Empirical Analysis

Zhang, X., Yao, Y., Zhang, J., & Fang, C (2023)

Production and Operations Management, 32(2), 603-617

DOI

Softwares

fdid

Performing honest causal inference using event study plots

R package

GitHub

fdidHonestInference

Performing honest causal inference using event study plots

Shiny app

Link

nndiagram

Generating LaTeX code for drawing neural network diagrams with TikZ

R Package

CRAN

dimada

Implementing dimension adaptive estimation

R Package

GitHub

HonestDiDSenAnlys

Running sensitivity analysis in Rambachan and Roth (2023) on web browsers.

Shiny app

Link

Work in Progress

  • On a Common Misconception about Count Data Models in Empirical OM Research: A Review and Practical Guide (with Jia Gao)
  • Pain-Free Bandwidth Selection for (Non-)Sparse Functional Data (with Dominik Liebl, Omar Kassi)
  • Simultaneous Testing on the Constant-Parameter Assumption in Panel Data Models (with Dominik Liebl)
  • Post-Registration Inference (with Dominik Liebl)
  • Deep Panel Quantile Regression (with Joonho Phil Hwang and Gayeon)
  • Synthetic Difference-in-Differences with Missing Post-Treatment Outcomes (with Joonho Phil Hwang)
  • Constructing Any-time Valid Confidence Band for Rolling Regression Estimator: Application to Bollinger Band (Job Market Paper)

Contact

Email: ccfang@uni-bonn.de
Phone: +49 152 59326793

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