| Summary: | <p>This thesis explores the use of observational microdata in cost-effectiveness analysis. The application of econometric methods adjusting for selection bias is first reviewed and critically appraised in the economic evaluation literature using a structured template. Limitations of identified studies include lack of good quality evidence regarding the performance of different analytical approaches; inadequate assessment of the sensitivity of their results to violations of fundamental assumptions or variations to crucial estimator parameters; failure to combine the cost and effectiveness outcomes in a summary measure; and no consideration of stochastic uncertainty for the purpose of evaluating cost-effectiveness. Data from the Birthplace national cohort study are used in an attempt to address these limitations in the context of an empirical comparison of estimators relying on regression, matching, as well as the propensity score. It is argued that although these methods cannot address the potential impact of unobservable confounding, a novel approach to bias-corrected matching, combining entropy balancing with seemingly unrelated regression, still has the potential to offer important advantages in terms of analytical robustness. The net economic benefit is proposed as a straightforward way to exploit the strengths of rigorous econometric methodology in the development of reliable and informative cost-effectiveness analyses.</p>
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