Advanced Methodologies in Efficiency Analysis: Novel Developments and Application to Public Hospitals in Queensland, Australia

HDR Candidate: Bao Hoang Nguyen

Milestone: Mid-candidature Review

Title: Advanced Methodologies in Efficiency Analysis: Novel Developments and Application to Public Hospitals in Queensland, Australia

When: Friday, 26 March 2021; 10am-12pm

Where: Zoom (passcode protected, contact HDR Liaison Officer)

Abstract:

As public hospitals are the key institution in the healthcare sector where the majority of healthcare expenditure occurs, improving hospital efficiency has been viewed as a fundamentally important means to contain healthcare cost in Australia. This thesis aims to examine the state of efficiency as well as identify sources of efficiency differentials of public hospitals in the country. To do so, we develop new methodologies as well as apply advanced methodologies recently developed in the field of efficiency analysis to the data on public hospitals in Queensland, Australia.

The thesis is expected to contribute to the literature on both theoretical and empirical perspectives. On the empirical side, this is one of very few studies examining the efficiency of public hospitals in Australia and to the best of our knowledge is the first study investigating the impact of the Activity Based Funding reform on hospital efficiency in the country. Moreover, the thesis adopts a comprehensive approach to study hospital efficiency, investigating efficiency at various levels including individual hospital level and industry level. The thesis also employs various approaches to estimate hospital efficiency including both data envelopment analysis (DEA) and stochastic frontier analysis (SFA).

On the theoretical side, the contributions are two folds. First, the thesis extends the new central limit theorems for aggregate efficiencies recently developed by Simar and Zelenyuk (2018, 2020), who in turn leveraged on developments of Kneip et al. (2015, 2016), to the context where there are several sub-groups in the population. Moreover, the thesis also develops new statistical tests based on the new central limited theorems to compare efficiencies of different groups of hospitals when examining efficiency at an industry level. Second, the thesis incorporates the recent development in the control function method (i.e., adapting Ackerberg et al. (2015) approach) to correct endogeneity in stochastic frontier framework.