⚠ Experiments page under construction. The studies and materials shown here are being updated — some links and details may be incomplete or temporarily unavailable.

// live experiments & field materials

Experiments

All studies are built and deployed by me end-to-end — and two of them are playable right on this site.

oTree · Lab (Melbourne) & online (Prolific UK/AU)

Job Market Paper · Playable Demo

The Gold-Mining Game

Anticipatory Utility as a Buffer Against Consumption Delays · solo-authored

Play it now

Waiting for Gold: Delay, Anticipation & Valuation

A miner digs for gold on your behalf. While you wait, you solve brain teasers — and every time you click "See how the miner is doing", that click is data: checking has no instrumental value, so checking frequency and viewing time reveal anticipatory utility. Anticipation is measured primarily by an incentivized willingness to pay for early information, and the delay before the nugget's value is revealed is randomly assigned. The headline result: delays reduce valuations — but only for low-anticipation participants. High anticipators barely discount at all.

Engine: oTree v5 (Python)  ·  N: 360, University of Melbourne lab  ·  Design: between-subject random delay  ·  Elicitations: BDM (WTP for information; WTA for the nugget)

Co-authored · Playable Demo

The Comparative-Information Experiment

Gender and the Demand for Comparative Information · with Nisvan Erkal & Boon Han Koh

Play it now

Who Wants to Know Where They Rank?

Participants solve pattern-matching puzzles, state incentivized beliefs about their absolute performance and their rank (a full five-interval distribution under a binarized scoring rule), and receive a deliberately noisy score. Then the key decision: which rank group would you pay to learn about — and how much? When the information has no instrumental value, women who believe themselves to be average performers avoid upward comparisons; facing the prospect of doing the task again, they seek them more than men. Revise & resubmit at the Journal of Economic Psychology.

Engine: oTree v5 (Python)  ·  Lab: University of Melbourne  ·  Design: noisy feedback × instrumental vs non-instrumental information  ·  Elicitations: binarized scoring rule, BDM (WTP for information)

Currently in the Field

AIT Life-Year Study — v1.3

Anticipated Information Trade-offs · Wave 3

Active on Prolific

Anticipatory Utility & Health Outcome Trade-Offs

Participants are placed in a simulated GP consultation and must choose between a certain life-year outcome (Standard Care) and a risky treatment (50/50 between a 5-year gain and a 5-year loss). A second between-subject factor varies whether the treatment outcome is revealed immediately or after a six-month delay. The design lets us separately identify hope (anticipation of the gain) and dread (anticipation of the loss) components of anticipatory utility, and how they interact with delay.

Platform: Prolific UK  ·  Engine: oTree v5 (Python)  ·  N per wave: ≈ 200  ·  Design: 2 × 2 between-subject (delay × emotion order)  ·  Ethics: UoM HREC-approved

Click any task below to view the actual experiment page:

Recently Completed

AIT Life-Year Study — earlier waves

Waves 1 & 2 · 2024–2025

Data analysed

Pilot & Calibration Studies

Earlier waves established comprehension benchmarks, calibrated the WTP/WTA bisection procedure, and tested the GP consultation framing. Data from these waves informs the design choices in v1.3.

Status: Closed  ·  Output: Internal pilots, working paper in preparation

Behind the Scenes

Tech Stack

I treat experiment code as production software: version-controlled, ethics-cleared, instrumented for behavioural telemetry (response times, revisions, slider trajectories), and reproducible from raw data to final tables.

Experiment Engine

  • oTree v5
  • Custom JS / CSS
  • Bisection / staircase procedures
  • Attention & comprehension checks

Deployment

  • Prolific (UK / AU)
  • Heroku
  • Server-side data logging

Analysis

  • R (tidyverse, lme4)
  • Stata
  • Python (pandas)
  • Reproducible pipelines

Quality

  • Pre-registration (OSF)
  • Power calculations
  • Simulated data stress tests
  • Manual pilot checklists