Writing
Book, peer-reviewed papers, industry chapters, and selected articles in the popular press.
Book
- Shaw, C. Causal Inference in Marketing: A Practical Toolkit for Panel Data, Volumes 1 & 2. Under contract with Taylor & Francis / CRC Press; scheduled for publication November 2026. View on Routledge or pre-order on Amazon.
Peer-reviewed papers
- Shaw, C. (2022) “Dynamic causal effects of pandemic-induced uncertainty on output, credit, and asset prices: a Symbolic Transfer Entropy approach”, Industrial Engineering & Management Systems 21(1), pp. 119-127.
- Shaw, C. (2018) “Conditional Heteroskedasticity in Cryptoasset Returns”, Journal of Statistics: Advances in Theory and Applications 20(1), pp. 15-65.
- Shaw, C., Vanadia, S. (2022) “Utilitarianism on the front lines: COVID-19, public ethics, and the ‘hidden assumption’ problem”, Ethics & Bioethics 12(1-2), pp. 60-78.
Industry and edited-volume chapters
- Ryan, B., Griffiths, A., Shaw, C., Clarke, T., Munton, P. (2025) “Turning Insights into Action: Closing the Loop in Marketing Activation & Analytics”, in Meta’s Measurement Playbook, Meta.
- Shaw, C., Pycock, D. (2019) “Simplified Planning Zones and the realignment of fiscal incentives”, in Raising the Roof: How to Solve the United Kingdom’s Housing Crisis, Institute of Economic Affairs. Link.
Selected articles in popular media
- “More homes, lower prices: the case for Simplified Planning Zones” (2018), CapX / Policy Exchange.
- “Untangling the complex web of the UK housing market” (2018), Institute of Economic Affairs.
- Interviewed on business and leadership. Read the interview.
Open source
- Epsilon.jl — a Julia-native library for Bayesian Marketing Mix Modelling (MMM). GitHub.
- SRVAR Toolkit — a shadow-rate Vector Autoregression toolkit for Bayesian macroeconomic forecasting, written in Python. GitHub.
- D-IV-LATE — distributional instrumental-variable Local Average Treatment Effect estimators; submitted to Journal of Statistical Computation and Simulation. arXiv · GitHub.
- Contributor to Hayashi, an interpreted, statically-typed language for applied econometrics. GitHub.