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The 9th Chinese Stata Conference will be held on 11 July 2025 at Jilin University. This year's conference will be combined with The 14th International Symposium of Quantitative Economics on July 12th. All users are invited to participate in both events.
Share valuable insights and new functions and commands with top Stata experts and Stata R&D engineers from various fields, learn the most cutting-edge scientific research methods, and improve your Stata knowledge. This conference not only is an annual summary of Stata's technical applications but also injects new momentum into academic research and policy analysis in the digital economy era.
All times are in CST (UTC +8)
| 1:00–1:05 | Opening
Sun Wei
Jilin University
|
| 1:05–1:10 | Message from StataCorp
Enrique Pinzón
StataCorp
|
| 1:10–1:20 | Group photo |
| 1:20–2:00 | Linear models and related using Stata: More speed and more inference
Abstract:
In the last three releases, we have upgraded the most commonly used linear models in Stata, namely, areg, regress, and xtreg, fe. Some of the improvements are for speed and convenience. Some have added new options to compute valid standard errors and confidence intervals for cases in which traditional computations will underperform. And some have added estimators that leverage this technology. In this talk, I will go through these upgrades and present the theoretical results that motivate them.
Enrique Pinzón
StataCorp
|
| 2:00–2:45 | Mobile share instrumental variables and Stata application
Abstract:
The shift share instrument, also known as the “Bartik IV”, has become increasingly popular in empirical research in recent years and has made breakthroughs in theoretical research. This talk will combine classic papers to introduce the historical development and latest results of the shift share instrument, as well as the corresponding Stata practical examples.
Chen Qiang
Shandong University
|
| 2:45–2:55 | Break |
| 2:55–3:40 | Conditional average treatment effects estimation using Stata
Abstract:
Treatment effects estimate the causal effects of a treatment on an outcome. The effect may be heterogeneous. Average treatment effects conditional on a set of variables (CATEs) help us understand heterogeneous treatment effects, and, by construction, are useful to evaluate how different treatment-assignment policies affect different groups in the population. In this talk, I will show how to use Stata's new cate command to answer questions such as the following:
Di Liu
StataCorp
|
| 3:40–4:25 | Causal inference in machine learning and Stata application
Abstract:
This presentation introduces the application of machine learning causal inference in economics, including dual machine learning estimation, inference and evaluation of conditional (heterogeneous) treatment-effect models (local linear models and interaction models), dual machine learning causal inference (DML instrumental variables, DML breakpoint design, etc.), and policy learning methods.
Wang Qunyong
Nankai University
|
| 4:25–4:35 | Prize drawing: Stata/MP4 one-year license |
| 4:35–4:45 | Closing
Xu Qingqing
Youwan Technology
|
Enrique Pinzón
Enrique Pinzón is the Director of Econometrics and part of the statistical development team at StataCorp LLC. He teaches a variety of Stata courses and is a frequent contributor to The Stata Blog. He holds a master's degree in economics from the Universidad de los Andes and a PhD from the University of Wisconsin–Madison.
Di Liu
Di Liu is a Principal Econometrician in the econometric development team at StataCorp LLC. Di is fascinated by writing statistical software for researchers and doing research in both theoretical and applied econometrics. He is the primary developer of some Stata features, including heterogeneous DID, instrumental-variables quantile regression, treatment-effects estimation using lasso, lasso for prediction, lasso for inference, spatial autoregressive models, heckpoisson, and betareg. He also published research articles in Canadian Journal of Economics, Econometrics Reviews, Empirical Economics, Econometrics and Statistics, and the Stata Journal. Di has a PhD degree in economics from Concordia University in Montreal, Canada; an engineer's degree in software engineering and statistics from Polytech'Lille in Lille, France; and master's and bachelor's degrees in computer science from Hohai University in Nanjing, China.
The conference is free, but registration is required. All participants are responsible for their own travel and accommodation expenses.
Registration deadline is 8 July 2025.
Visit the official conference page for more information.
The 2025 Chinese Stata Conference is organized by Beijing Uone Info & Tech Co., Ltd. (Uone-Tech), an official reseller of Stata in China.
View the proceedings of previous Stata Conferences and international meetings.
