This project analyses a Discrete Choice Experiment (DCE) conducted by Czajkowski, Jusypenko, and White (2025; data collected 2021) on a representative sample of Victorian households. Respondents chose between a heritage conservation scenario described by multiple attributes and a status quo (no additional conservation expenditure). The experiment covered three heritage types: historic buildings, historic sites, and cultural landscapes. Research questions: RQ1: Which heritage attributes most strongly drive conservation choices, and how do willingness-to-pay (WTP) estimates differ across heritage types? RQ2: Are there latent preference segments with systematically different valuations? RQ3: Can socio-demographic characteristics explain class membership? RQ4: Do respondents engage in Attribute Non-Attendance (ANA) for cost and distance, and how does accounting for ANA affect welfare measures?

Analytical flow: Category Risk → Root-Cause Split (delivery vs product) → Text Evidence → Priority Matrix → Recommendations.

This study investigates how total health expenditure and the public share of health spending are associated with life expectancy in 37 OECD countries from 2000 to 2022. Using a two-way fixed-effects panel model, the results show positive associations for total health expenditure, GDP per capita, and urbanisation, while the public expenditure share carries a negative coefficient. A pre-COVID robustness check suggests that this negative association is not driven solely by the pandemic period.

How can the LAPD identify unique crime ‘fingerprints’ by integrating spatial hotspots, temporal patterns, and victim demographics to transition from reactive to proactive policing? This analysis aims to move from broad patrolling to Precision Policing. By segmenting crimes into specific “Risk Fingerprints,” we provide the LAPD with actionable intelligence to deploy specialized units where they are most needed.

Can we identify the ‘Hidden Logic’ of criminal operations in Los Angeles by analyzing the non-random associations between environment, method, and weaponry? To transition from traditional patrolling to Context-Aware Dispatching. By applying the Apriori Algorithm, we treat each incident as a “behavioral transaction.” Our goal is to empower dispatchers with the ability to predict weapon presence or specific criminal signatures the moment a location is reported, long before an officer arrives at the scene.