Pan Zhao
@panzhao.bsky.social
Postdoctoral Research Associate, Statistical Laboratory, University of Cambridge
Reposted by Pan Zhao
Wrote a new paper on the econometrics of financial event studies, would value feedback! It's very new.
With my amazing grad student Tianshu Lyu www.tianshulyu.com, who is on the market. You should hire him!
paulgp.com/papers/finan...
With my amazing grad student Tianshu Lyu www.tianshulyu.com, who is on the market. You should hire him!
paulgp.com/papers/finan...
November 19, 2025 at 4:43 AM
Wrote a new paper on the econometrics of financial event studies, would value feedback! It's very new.
With my amazing grad student Tianshu Lyu www.tianshulyu.com, who is on the market. You should hire him!
paulgp.com/papers/finan...
With my amazing grad student Tianshu Lyu www.tianshulyu.com, who is on the market. You should hire him!
paulgp.com/papers/finan...
Reposted by Pan Zhao
Today, the @houseoflords.parliament.uk Home-based Working Committee released a report which repeatedly references research by an interdisciplinary team at @cam.ac.uk highlighting the need for better data on productivity & mental health in the workplace to inform policy on home-based working.
November 13, 2025 at 2:17 PM
Today, the @houseoflords.parliament.uk Home-based Working Committee released a report which repeatedly references research by an interdisciplinary team at @cam.ac.uk highlighting the need for better data on productivity & mental health in the workplace to inform policy on home-based working.
Reposted by Pan Zhao
🥳 Registration for abstracts for EuroCIM 2026 (Oxford) is now OPEN and the deadline for submissions is 9 January 2026: eurocim.org/oxford-2026/...
👉 Theme? “Causal inference in health, economic and social science”
👉 When? April 14-17
👉 Where? Oxford
👉 Register? eurocim.org/oxford-2026/...
👉 Theme? “Causal inference in health, economic and social science”
👉 When? April 14-17
👉 Where? Oxford
👉 Register? eurocim.org/oxford-2026/...
November 11, 2025 at 10:55 AM
🥳 Registration for abstracts for EuroCIM 2026 (Oxford) is now OPEN and the deadline for submissions is 9 January 2026: eurocim.org/oxford-2026/...
👉 Theme? “Causal inference in health, economic and social science”
👉 When? April 14-17
👉 Where? Oxford
👉 Register? eurocim.org/oxford-2026/...
👉 Theme? “Causal inference in health, economic and social science”
👉 When? April 14-17
👉 Where? Oxford
👉 Register? eurocim.org/oxford-2026/...
Reposted by Pan Zhao
link 📈🤖
Synthetic Parallel Trends (Liu) Popular empirical strategies for policy evaluation in the panel data literature -- including difference-in-differences (DID), synthetic control (SC) methods, and their variants -- rely on key identifying assumptions that can be expressed through a specific
Synthetic Parallel Trends (Liu) Popular empirical strategies for policy evaluation in the panel data literature -- including difference-in-differences (DID), synthetic control (SC) methods, and their variants -- rely on key identifying assumptions that can be expressed through a specific
November 11, 2025 at 4:34 PM
link 📈🤖
Synthetic Parallel Trends (Liu) Popular empirical strategies for policy evaluation in the panel data literature -- including difference-in-differences (DID), synthetic control (SC) methods, and their variants -- rely on key identifying assumptions that can be expressed through a specific
Synthetic Parallel Trends (Liu) Popular empirical strategies for policy evaluation in the panel data literature -- including difference-in-differences (DID), synthetic control (SC) methods, and their variants -- rely on key identifying assumptions that can be expressed through a specific
Reposted by Pan Zhao
link 📈🤖
A sensitivity analysis for the average derivative effect (Zhang) In observational studies, exposures are often continuous rather than binary or discrete. At the same time, sensitivity analysis is an important tool that can help determine the robustness of a causal conclusion to a certain
A sensitivity analysis for the average derivative effect (Zhang) In observational studies, exposures are often continuous rather than binary or discrete. At the same time, sensitivity analysis is an important tool that can help determine the robustness of a causal conclusion to a certain
November 11, 2025 at 4:58 PM
link 📈🤖
A sensitivity analysis for the average derivative effect (Zhang) In observational studies, exposures are often continuous rather than binary or discrete. At the same time, sensitivity analysis is an important tool that can help determine the robustness of a causal conclusion to a certain
A sensitivity analysis for the average derivative effect (Zhang) In observational studies, exposures are often continuous rather than binary or discrete. At the same time, sensitivity analysis is an important tool that can help determine the robustness of a causal conclusion to a certain
Reposted by Pan Zhao
link 📈🤖
Boundary Discontinuity Designs: Theory and Practice (Cattaneo, Titiunik, Yu) We review the literature on boundary discontinuity (BD) designs, a powerful non-experimental research methodology that identifies causal effects by exploiting a thresholding treatment assignment rule based on a b
Boundary Discontinuity Designs: Theory and Practice (Cattaneo, Titiunik, Yu) We review the literature on boundary discontinuity (BD) designs, a powerful non-experimental research methodology that identifies causal effects by exploiting a thresholding treatment assignment rule based on a b
November 11, 2025 at 5:07 PM
link 📈🤖
Boundary Discontinuity Designs: Theory and Practice (Cattaneo, Titiunik, Yu) We review the literature on boundary discontinuity (BD) designs, a powerful non-experimental research methodology that identifies causal effects by exploiting a thresholding treatment assignment rule based on a b
Boundary Discontinuity Designs: Theory and Practice (Cattaneo, Titiunik, Yu) We review the literature on boundary discontinuity (BD) designs, a powerful non-experimental research methodology that identifies causal effects by exploiting a thresholding treatment assignment rule based on a b
Reposted by Pan Zhao
Born #OnThisDay in 1867 was Marie Skłodowska–Curie, the first woman to win a Nobel Prize, the only woman to win twice and the only person to win a Nobel Prize in two disciplines: Physics for her work on radioactivity, and Chemistry for her discovery of radium and polonium. #WomenInSTEM
November 7, 2025 at 7:25 AM
Born #OnThisDay in 1867 was Marie Skłodowska–Curie, the first woman to win a Nobel Prize, the only woman to win twice and the only person to win a Nobel Prize in two disciplines: Physics for her work on radioactivity, and Chemistry for her discovery of radium and polonium. #WomenInSTEM
Reposted by Pan Zhao
Journal submissions got you stressed? Daniela Witten of the University of Washington shares advice about editing and dealing with rejection when submitting papers to academic journals. magazine.amstat.org/...
November 6, 2025 at 7:00 PM
Journal submissions got you stressed? Daniela Witten of the University of Washington shares advice about editing and dealing with rejection when submitting papers to academic journals. magazine.amstat.org/...
Reposted by Pan Zhao
Excellent report on experiences of @guidoimbens.bsky.social & Mary Wootters co-teaching "Causality, Decision Making, and Data Science" to undergrads at Stanford fall 2024: hdsr.mitpress.mit.edu/pub/uynpjlow... Course material here: stanford-causal-inference-class.github.io
November 3, 2025 at 4:14 PM
Excellent report on experiences of @guidoimbens.bsky.social & Mary Wootters co-teaching "Causality, Decision Making, and Data Science" to undergrads at Stanford fall 2024: hdsr.mitpress.mit.edu/pub/uynpjlow... Course material here: stanford-causal-inference-class.github.io
Reposted by Pan Zhao
Born #OnThisDay in 1815 was George Boole FRS. Boole was a mathematician, logician and philosopher who helped establish modern symbolic logic and whose algebra of logic, now called Boolean algebra, is fundamental to the design of digital computer circuits: https://bit.ly/3g1qY9c
November 2, 2025 at 1:53 PM
Born #OnThisDay in 1815 was George Boole FRS. Boole was a mathematician, logician and philosopher who helped establish modern symbolic logic and whose algebra of logic, now called Boolean algebra, is fundamental to the design of digital computer circuits: https://bit.ly/3g1qY9c
Reposted by Pan Zhao
Reposted by Pan Zhao
link 📈🤖
Prediction-Guided Active Experiments () arXiv:2411.12036v1 Announce Type: cross
Abstract: Here is the revised abstract, ensuring all characters are ASCII-compatible:
In this work, we introduce a new framework for active experimentation, the Prediction-Guided Active Experiment (PGAE), w
Prediction-Guided Active Experiments () arXiv:2411.12036v1 Announce Type: cross
Abstract: Here is the revised abstract, ensuring all characters are ASCII-compatible:
In this work, we introduce a new framework for active experimentation, the Prediction-Guided Active Experiment (PGAE), w
October 17, 2025 at 10:05 PM
link 📈🤖
Prediction-Guided Active Experiments () arXiv:2411.12036v1 Announce Type: cross
Abstract: Here is the revised abstract, ensuring all characters are ASCII-compatible:
In this work, we introduce a new framework for active experimentation, the Prediction-Guided Active Experiment (PGAE), w
Prediction-Guided Active Experiments () arXiv:2411.12036v1 Announce Type: cross
Abstract: Here is the revised abstract, ensuring all characters are ASCII-compatible:
In this work, we introduce a new framework for active experimentation, the Prediction-Guided Active Experiment (PGAE), w
Reposted by Pan Zhao
“All Our Default Models Are Wrong: Causal inference for varying treatment effects”: my talk this Saturday morning in Ottawa
statmodeling.stat.columbia.edu/2025/10/16/a...
statmodeling.stat.columbia.edu/2025/10/16/a...
“All Our Default Models Are Wrong: Causal inference for varying treatment effects”: my talk this Saturday morning in Ottawa | Statistical Modeling, Causal Inference, and Social Science
statmodeling.stat.columbia.edu
October 16, 2025 at 1:29 PM
“All Our Default Models Are Wrong: Causal inference for varying treatment effects”: my talk this Saturday morning in Ottawa
statmodeling.stat.columbia.edu/2025/10/16/a...
statmodeling.stat.columbia.edu/2025/10/16/a...
Reposted by Pan Zhao
For the 3rd day of my #MEstimatorMonday catch-up week (39/52), let's talk proximal causal inference
We can think about proximal causal inference as an extension of the standard identification assumptions to allow for more rich data structures. Specifically, we can account for unmeasured confounding
We can think about proximal causal inference as an extension of the standard identification assumptions to allow for more rich data structures. Specifically, we can account for unmeasured confounding
October 15, 2025 at 6:38 PM
For the 3rd day of my #MEstimatorMonday catch-up week (39/52), let's talk proximal causal inference
We can think about proximal causal inference as an extension of the standard identification assumptions to allow for more rich data structures. Specifically, we can account for unmeasured confounding
We can think about proximal causal inference as an extension of the standard identification assumptions to allow for more rich data structures. Specifically, we can account for unmeasured confounding
Reposted by Pan Zhao
Jane Goodall, world-renowned primatologist, dies aged 91
Jane Goodall, world-renowned primatologist, dies aged 91
Jane Goodall Institute says ‘tireless advocate’ for natural world died in California during US speaking tour
The world-renowned primatologist Jane Goodall has died at the age of 91, her institute has said.
The Jane Goodall Institute announced that she had passed away of natural causes while in California as part of a US speaking tour. Continue reading...
www.theguardian.com
October 1, 2025 at 6:35 PM
Jane Goodall, world-renowned primatologist, dies aged 91
Reposted by Pan Zhao
link 📈🤖
A note on the relation between one--step, outcome regression and IPW--type estimators of parameters with the mixed bias property (Rotnitzky, Smucler, Robins) Bruns-Smith et al. (2025) established an algebraic identity between the one-step estimator and a specific outcome regression-type e
A note on the relation between one--step, outcome regression and IPW--type estimators of parameters with the mixed bias property (Rotnitzky, Smucler, Robins) Bruns-Smith et al. (2025) established an algebraic identity between the one-step estimator and a specific outcome regression-type e
September 29, 2025 at 5:05 PM
link 📈🤖
A note on the relation between one--step, outcome regression and IPW--type estimators of parameters with the mixed bias property (Rotnitzky, Smucler, Robins) Bruns-Smith et al. (2025) established an algebraic identity between the one-step estimator and a specific outcome regression-type e
A note on the relation between one--step, outcome regression and IPW--type estimators of parameters with the mixed bias property (Rotnitzky, Smucler, Robins) Bruns-Smith et al. (2025) established an algebraic identity between the one-step estimator and a specific outcome regression-type e
Reposted by Pan Zhao
“Veridical (truthful) Data Science”: Another way of looking at statistical workflow
statmodeling.stat.columbia.edu/2025/09/28/v...
statmodeling.stat.columbia.edu/2025/09/28/v...
“Veridical (truthful) Data Science”: Another way of looking at statistical workflow | Statistical Modeling, Causal Inference, and Social Science
statmodeling.stat.columbia.edu
September 28, 2025 at 4:51 PM
“Veridical (truthful) Data Science”: Another way of looking at statistical workflow
statmodeling.stat.columbia.edu/2025/09/28/v...
statmodeling.stat.columbia.edu/2025/09/28/v...
Reposted by Pan Zhao
Excited to see our paper on evaluating whether AI can help humans make better decisions is now out in @pnas.org!
www.pnas.org/doi/10.1073/...
www.pnas.org/doi/10.1073/...
Does AI help humans make better decisions? A statistical evaluation framework for experimental and observational studies | PNAS
The use of AI, or more generally data-driven algorithms, has become ubiquitous in
today’s society. Yet, in many cases and especially when stakes ar...
www.pnas.org
September 25, 2025 at 2:41 AM
Excited to see our paper on evaluating whether AI can help humans make better decisions is now out in @pnas.org!
www.pnas.org/doi/10.1073/...
www.pnas.org/doi/10.1073/...
Reposted by Pan Zhao
Herbert P. Susmann, Alec McClean, Iv\'an D\'iaz
Non-overlap Average Treatment Effect Bounds
https://arxiv.org/abs/2509.20206
Non-overlap Average Treatment Effect Bounds
https://arxiv.org/abs/2509.20206
September 25, 2025 at 4:38 AM
Herbert P. Susmann, Alec McClean, Iv\'an D\'iaz
Non-overlap Average Treatment Effect Bounds
https://arxiv.org/abs/2509.20206
Non-overlap Average Treatment Effect Bounds
https://arxiv.org/abs/2509.20206
Reposted by Pan Zhao
NEW PAPER!!! "Causal Machine Learning Methods and Use of Cross‐Fitting in Settings With High‐Dimensional Confounding"
led by Susie Ellul, with Stijn Vansteelandt & John Carlin
Published in Stats in Med
Check it out 👇
onlinelibrary.wiley.com/doi/10.1002/...
#EpiSky #CausalSky
led by Susie Ellul, with Stijn Vansteelandt & John Carlin
Published in Stats in Med
Check it out 👇
onlinelibrary.wiley.com/doi/10.1002/...
#EpiSky #CausalSky
Causal Machine Learning Methods and Use of Cross‐Fitting in Settings With High‐Dimensional Confounding
Observational epidemiological studies commonly seek to estimate the causal effect of an exposure on an outcome. Adjustment for potential confounding bias in modern studies is challenging due to the p...
onlinelibrary.wiley.com
September 25, 2025 at 2:35 AM
NEW PAPER!!! "Causal Machine Learning Methods and Use of Cross‐Fitting in Settings With High‐Dimensional Confounding"
led by Susie Ellul, with Stijn Vansteelandt & John Carlin
Published in Stats in Med
Check it out 👇
onlinelibrary.wiley.com/doi/10.1002/...
#EpiSky #CausalSky
led by Susie Ellul, with Stijn Vansteelandt & John Carlin
Published in Stats in Med
Check it out 👇
onlinelibrary.wiley.com/doi/10.1002/...
#EpiSky #CausalSky
Reposted by Pan Zhao
New paper on generative modeling of counterfactual distributions! We give a way to answer "what if" questions with generative models.
For example: what would faces look like if they were all smiling?
arxiv.org/abs/2509.16842
For example: what would faces look like if they were all smiling?
arxiv.org/abs/2509.16842
September 24, 2025 at 8:42 PM
New paper on generative modeling of counterfactual distributions! We give a way to answer "what if" questions with generative models.
For example: what would faces look like if they were all smiling?
arxiv.org/abs/2509.16842
For example: what would faces look like if they were all smiling?
arxiv.org/abs/2509.16842
Reposted by Pan Zhao
link 📈🤖
DoubleGen: Debiased Generative Modeling of Counterfactuals (Luedtke, Fukumizu) Generative models for counterfactual outcomes face two key sources of bias. Confounding bias arises when approaches fail to account for systematic differences between those who receive the intervention and thos
DoubleGen: Debiased Generative Modeling of Counterfactuals (Luedtke, Fukumizu) Generative models for counterfactual outcomes face two key sources of bias. Confounding bias arises when approaches fail to account for systematic differences between those who receive the intervention and thos
September 23, 2025 at 7:33 PM
link 📈🤖
DoubleGen: Debiased Generative Modeling of Counterfactuals (Luedtke, Fukumizu) Generative models for counterfactual outcomes face two key sources of bias. Confounding bias arises when approaches fail to account for systematic differences between those who receive the intervention and thos
DoubleGen: Debiased Generative Modeling of Counterfactuals (Luedtke, Fukumizu) Generative models for counterfactual outcomes face two key sources of bias. Confounding bias arises when approaches fail to account for systematic differences between those who receive the intervention and thos
Reposted by Pan Zhao
link 📈🤖
Variable Selection for Additive Global Fr\'echet Regression (Yang, Bhattacharjee, Xue et al) We present a novel framework for variable selection in Fr\'echet regression with responses in general metric spaces, a setting increasingly relevant for analyzing non-Euclidean data such as probab
Variable Selection for Additive Global Fr\'echet Regression (Yang, Bhattacharjee, Xue et al) We present a novel framework for variable selection in Fr\'echet regression with responses in general metric spaces, a setting increasingly relevant for analyzing non-Euclidean data such as probab
September 18, 2025 at 4:39 PM
link 📈🤖
Variable Selection for Additive Global Fr\'echet Regression (Yang, Bhattacharjee, Xue et al) We present a novel framework for variable selection in Fr\'echet regression with responses in general metric spaces, a setting increasingly relevant for analyzing non-Euclidean data such as probab
Variable Selection for Additive Global Fr\'echet Regression (Yang, Bhattacharjee, Xue et al) We present a novel framework for variable selection in Fr\'echet regression with responses in general metric spaces, a setting increasingly relevant for analyzing non-Euclidean data such as probab
Reposted by Pan Zhao
Han Cui, Xinran Li
Robust Sensitivity Analysis via Augmented Percentile Bootstrap under Simultaneous Violations of Unconfoundedness and Overlap
https://arxiv.org/abs/2509.13169
Robust Sensitivity Analysis via Augmented Percentile Bootstrap under Simultaneous Violations of Unconfoundedness and Overlap
https://arxiv.org/abs/2509.13169
September 17, 2025 at 4:26 AM
Han Cui, Xinran Li
Robust Sensitivity Analysis via Augmented Percentile Bootstrap under Simultaneous Violations of Unconfoundedness and Overlap
https://arxiv.org/abs/2509.13169
Robust Sensitivity Analysis via Augmented Percentile Bootstrap under Simultaneous Violations of Unconfoundedness and Overlap
https://arxiv.org/abs/2509.13169
Reposted by Pan Zhao
Georgi Baklicharov, Kelly Van Lancker, Stijn Vansteelandt
Weakening assumptions in the evaluation of treatment effects in longitudinal randomized trials with truncation by death or other intercurrent events
https://arxiv.org/abs/2509.10067
Weakening assumptions in the evaluation of treatment effects in longitudinal randomized trials with truncation by death or other intercurrent events
https://arxiv.org/abs/2509.10067
September 15, 2025 at 5:03 AM
Georgi Baklicharov, Kelly Van Lancker, Stijn Vansteelandt
Weakening assumptions in the evaluation of treatment effects in longitudinal randomized trials with truncation by death or other intercurrent events
https://arxiv.org/abs/2509.10067
Weakening assumptions in the evaluation of treatment effects in longitudinal randomized trials with truncation by death or other intercurrent events
https://arxiv.org/abs/2509.10067