I am a recognized expert in causal inference, with foundational contributions to its development and ongoing innovations in experimental design. My academic work includes pioneering the use of spectral analysis to evaluate complex designs, making randomized experimentation feasible under a much wider range of constraints. The unified framework I proposed has advanced the field by enabling the comparison and evaluation of novel designs and estimators, ensuring precision and efficiency in experimental analysis.
In addition to my academic achievements, I bring over 20 years of hands-on experience in political consulting. As one of the first to apply randomized controlled trials to campaign strategies, I helped establish the Analyst Group network and the Analyst Institute, shaping how data-driven tactics are deployed in politics. In the most recent election, I led a digital outreach campaign that utilized iterative experimentation to refine targeting models and treatment strategies, achieving a 5.4x ROI. This work not only delivered immediate results but also laid the groundwork for even greater precision in future campaigns.
Combining academic rigor with deep experience, I empower campaigns to make data-driven decisions that maximize impact. Links to selected research articles are below for those interested in exploring my work. Please contact me at the email address below for more information.
Causal Inference/Statistics
Exact Bias Correction for Linear Adjustment of Randomized Controlled Trials (2024, Econometrica)
Optimized Variance Estimation under Interference and Complex Experimental Designs (2024, R&R, Journal of the American Statistical Association)
Field Experiments
Can Communities Take Charge? A Randomized Controlled Trial on Sustaining Schools in Afghanistan (2023, R&R, Journal of Politics)
Are Ballot Initiatives Influenced by Campaigns? (2014, Political Behavior)
See also
Contact
joel.middleton [at] gmail.com