Economics Honours Thesis Topics
The Honours Program features a supervised thesis on an agreed topic, providing students with a comprehensive introduction to economic research.
The following projects have been proposed by School of Economics staff for 2027. Please note that this is not an exhaustive list; additional projects will be added as they become available.
Students who are enrolled in, or considering the Bachelor of Economics (Honours) program for 2027 are encouraged to contact the potential supervisors listed to express their interest if there is a particular topic they would like to explore for their thesis.
Project | Firm-Worker Matching and Wage Inequality LEED and PLIDA |
Supervisor(s) | |
Industry Partner | Australian Bureau of Statistics |
Description | Rising wage inequality could reflect increasing returns to skill (productivity-based) or increasing sorting of high-skill workers into high-wage firms (matching-based), with profoundly different policy implications. If inequality is productivity-driven, education policy matters; if sorting-driven, competition policy and firm-worker bargaining institutions matter. BLADE's matched employer-employee data can estimate firm and worker fixed effects to decompose inequality, but distinguishing whether high-wage workers and high-wage firms match because of complementarities (they're more productive together) versus market frictions (good matches are rare) requires additional assumptions about production technology and matching processes that may not be testable. How much of rising wage inequality reflects sorting of high-skill workers into high-wage firms versus increasing within-firm wage dispersion, and can matched employer-employee data distinguish productivity complementarities from search-and-matching frictions as mechanisms? The student will estimate two-way fixed effects (AKM), decompose inequality into worker, firm, and match components; test sorting patterns and complementarities. Possible methods to use include AKM two-way FE modelling; variance decomposition; correlation of effects; mobility-based identification; counterfactual decomposition. |
Relevant Literature |
Project | Resource Misallocation and Zombie Firms (BLADE) |
Supervisor(s) | |
Industry Partner | Australian Bureau of Statistics |
Description | Global productivity growth has slowed dramatically, with misallocation of capital and labour dragging down productivity by 0.6 percentage points annually. Financial crises may impede efficient firm expansion through credit rationing, allowing "zombie firms" with low returns to continue operating while high-return firms face capital constraints. Measuring misallocation requires distinguishing genuine productivity differences from measurement error, and identifying which policies drive misallocation requires untangling multiple confounding factors. Zombie firms may be transitioning to new business models rather than genuinely unproductive, or may provide valuable employment stability during downturns even if economically inefficient. What is the magnitude of productivity loss from resource misallocation to zombie firms in Australian manufacturing, and can firm-level administrative data identify specific policy barriers preventing capital and labour reallocation to high-productivity firms? The student will identify zombie firms; estimate productivity drag; test policies (credit, protection, regulation) associated with zombie survival; counterfactual reallocation. Possible methods include: Hsieh–Klenow misallocation metrics; frontier estimation; survival analysis; structural productivity modelling; counterfactual simulations. |
Relevant Literature |
Project | Productivity and Efficiency Analysis for Energy Sector with a focus on Australia |
Supervisor(s) | Prof Valentin Zelenyuk |
Description | How efficiently does Australia’s energy sector use its resources, and what opportunities exist to improve its performance? This honours research topic invites students to examine productivity and efficiency in an industry central to economic prosperity, energy security and environmental sustainability. The project will explore how energy producers or network operators transform inputs into energy services (energy generation or energy distribution), while considering the role of emissions and other environmental outcomes. Depending on the student’s interests and data availability, the thesis could focus on electricity generation, transmission or distribution, or comparisons across energy technologies, firms, regions or countries. Potential research questions include whether productivity has improved over time, what explains differences in efficiency across producers, and how accounting for emissions changes assessments of performance. A clearly defined Australian case study could also be placed in an international context with aim to understand how to improve Australian energy sector further. The project offers an opportunity to apply methods such as Data Envelopment Analysis (DEA), Stochastic Frontier Analysis (SFA), or productivity index techniques to real-world data, along with other tool in econometric and statistical analysis. The scope and methodology will be developed with the supervisor to ensure a focused and feasible honours thesis. Students will gain practical experience in data analysis, economic modelling and interpreting evidence relevant to energy policy and industry performance. This topic is well suited to students interested in applied economics, econometrics, energy or environmental policy. An interest in quantitative analysis and a willingness to develop empirical research skills are particularly welcome. |
| Relevant Literature | For an example of related research and references, see: https://www.aer.gov.au/documents/quantonomics-report-phase-2-26-november-2025 More about the field of Productivity and Efficiency Analysis can be found here: https://www.cambridge.org/core/books/measurement-of-productivity-and-efficiency/F8851B759C0BFB4840F4603218943E9F For examples of other finished projects (both theoretical works as well as applications to other sectors and countries) by Valentin Zelenyuk, see: https://scholar.google.com/citations?user=KBGcuJEAAAAJ&hl=en |
Project | The Gig Economy and Career Trajectories (L-LEED) |
Supervisor(s) | Dr Josh Merfeld |
| Industry Partner | Australian Bureau of Statistics |
Description | Platform gig work may represent temporary flexibility allowing workers to smooth income during career transitions, or permanent precarity trapping workers in low-quality employment. If gig work facilitates transitions to stable employment, policies should support it; if it traps workers, stronger regulation may be needed. LEED data may partially capture gig workers through tax records (though independent contractors pose classification challenges), enabling comparison of workers with gig economy spells to traditional employment trajectories. Yet identifying true gig workers in administrative data is difficult and those identified may be selected samples not representative of all gig participants. The student may Identify gig-like patterns in LEED; track pre/post trajectories; test whether gig participation predicts advancement or stagnation; analyse heterogeneity. Possible methods to use could include: Classification algorithms; event-study; matching; trajectory modelling; latent class analysis. |
| Relevant Literature |
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