Winter Research Scholarship

Project title: 

Pension Withdrawals and Retirement Ages in Australia 

Hours of engagement & delivery mode

For the Winter program, students will be engaged for 4 weeks only.

Hours of engagement: between 20 – 36 hrs per week.

On-site.

Description:

This project has two components. The first component is positive. It investigates the role of early pension withdrawal, and the corresponding rise in consumption, on inflation during COVID-19 in Australia. The project combines empirical analysis, sectoral price indexes and regional/sectoral data on withdrawal rates and amounts. Using a quantitative model of heterogeneous agents that explicitly models the early withdrawal policy---as in Hamilton, Liu, Miranda-Pinto, Sainsbury (2024)--- the project aims to study the inflationary effects of the policy under different economic scenarios.

The second component is normative. It aims at evaluating the welfare effects of pension reforms in Australia, focusing on retirement ages. The methodology builds on the "sufficient statistics” approach to welfare analysis (see, e.g., Chetty (2009)) which decomposes potential welfare effects of policy reforms into estimable elasticities.

Relevant Literature:

Hamilton, S., Liu, G., Miranda-Pinto, J., & Sainsbury, T. (2024). A $100,000 marshmallow experiment: Withdrawal and spending responses to early retirement-savings access.

Schneider, P & Moran, P." Situational and Behavioral Determinants of Early Withdrawal from Retirement Accounts." January, 2025 .

Chetty, R. (2009) Sufficient Statistics for Welfare Analysis: A Bridge Between Structural and Reduced-Form Methods. Annual Review of Economics.

Kolsrud, J., Landais, C., Reck, D. and Spinnewijn, J. (2024). Retirement Consumption and Pension Design. American Economic Review.

Haller, A. (2022). Welfare Effects of Pension Reforms. Working Paper.

Moran, P., & Schneider, P.  "Household Liquidity Policy". Working paper, 2024.

Expected learning outcomes and deliverables:

Applicants would gain valuable skills in areas such as data collection, Australian micro-level data, macroeconomic modelling, and numerical computing.

Suitable for:

This project is open to applications with students with the following qualities:

• Background in Economics
• Outstanding quantitative and writing skills
• High level of English proficiency
• Econometric skills, and some experience with econometrics software (such as Stata or R)
• Some experience with computational software (such as Matlab or Phython)

Primary Supervisor:

Dr Jorge Miranda-Pinto

Dr Antonio Andrés Bellofatto

Further info:

Supervisors can be contacted by students prior to submitting an application.

Project title: 

Impacts of teacher autonomy and government interventions on student performance

Hours of engagement & delivery mode

30 hrs per week for 4 weeks (30 June – 25 July 2025).

The core of the project can be completed remotely. Meetings could be in-person or online. 

Description:

The scholar will join an existing project that aims to estimate the impact of teacher autonomy (defined as teachers having decision-making power in areas such as teaching practices, disciplinary actions, and budget management) and government intervention (defined as governments having decision-marking power in the same areas) on students' educational and mental health outcomes. The project will use data from the Organisation for Economic Co-operation and Development's Programme for International Student Assessment (PISA). The research fellow may be involved in data cleaning and analysis, literature review and manuscript preparation. Exact responsibilities may vary depending on the stage of the project at the time of the placement and the individual interests and background of the fellow.

Expected learning outcomes and deliverables:

Expected learning outcomes include knowing how to conduct literature review using digital tools, knowing how to apply econometric skills to analyse real-world datasets, and knowing how to report research findings.

Expected deliverables may include a literature review report, a data analysis report, and a draft manuscript.

Suitable for:

This project is open to applications from Masters students and third or fourth-year students in economics, management or education programmes.

Primary Supervisor:

Prof KK Tang (principal); Dr Elcin Tuzel (CBEH; associate)

Further info:

Students wishing to find out more about the project before applying can contact Prof Tang at kk.tang@uq.edu.au.

Project title: 

Assortative Matching in Soccer Leagues

Hours of engagement & delivery mode

The project requires a commitment of 36 hours per week, scheduled between 30 June and 25 July 2025. The student has the flexibility to choose whether to work remotely or in person, depending on their preference.

Description:

In labour economics, the theory of assortative matching focuses on the mutual selection of workers and firms, aiming to explain how different characteristics of workers and firms interact to produce efficient pairings. The presence of positive assortative matching (PAM) suggests that more productive workers match with more productive firms, leading to efficiency gains. While this theory has been extensively studied in traditional labour markets (Becker, 1973; Shimer & Smith, 2000), its empirical validation remains always an ongoing challenge. This project intends to use data from the most important soccer leagues to empirically test the presence of positive assortative matching in professional sports. The setting of soccer leagues provides a unique opportunity to observe market mechanisms in a controlled yet competitive environment, where player transfers closely resemble workers' accessions to and separations from firms.

Specifically, we seek to answer the following questions:

1. Are better players systematically sorting into better teams?
2. To what extent do performance measures align with theoretical predictions of positive sorting?
3. How do wages and transfer fees correlate with player productivity and team quality?

To answer these questions, we will construct a dataset containing detailed player statistics, team performance indicators, wage distributions, and transfer histories from leading soccer leagues such as the English Premier League, La Liga, Bundesliga, Serie A, and Ligue 1. Using econometric techniques, we will assess whether the observed matching patterns conform to theoretical expectations.

This project aims to contribute to the literature on assortative matching by providing empirical evidence from the soccer labour market. The analysis will help clarify the mechanisms that drive player-team matching, the impact of sorting on competitive balance, and the role of contractual frictions in shaping market efficiency. Ultimately, this research may inform best practices aimed at improving competition, market efficiency, and fairness in both sports and traditional labour markets.

1. Sorting in Soccer Leagues.

The first objective of this research is to determine whether positive assortative matching exists in soccer leagues. Additionally, we aim to characterize differences in sorting in each league and across the different player positions (goalkeeper, defender, midfielder, forward, etc.).

2. Sorting and League Competitiveness

A second key objective is to analyse the relationship between sorting and league competitiveness. Theoretically, a high degree of positive sorting—where the best players consistently join the best teams—could either enhance or diminish competitiveness:

• If positive sorting leads to increased concentration of talent in a few top teams, it may reduce overall league competitiveness, as weaker teams struggle to compete.
• Conversely, if positive sorting improves the performance of all teams through spillover effects and efficient allocation of talent, the league may become more competitive overall.

This research will assess the empirical relationship between sorting and competitive balance. If stronger positive sorting leads to reduced competition, regulatory interventions such as transfer caps or salary limitations could be justified to maintain competitive balance.

3. Contractual Frictions and Market Efficiency

A final component of this project is to estimate the size and effect of contractual frictions that may limit efficient sorting. In many labour markets, contracts create frictions that prevent optimal worker-firm matches from occurring instantaneously. In soccer, contracts play a crucial role in player mobility, influencing the timing, cost, and feasibility of transfers. Important questions include:

• To what extent do long-term contracts distort efficient sorting?
• How do release clauses, transfer fees, and wage structures impact player mobility?
• Do teams use contractual mechanisms to strategically limit sorting for competitive advantage?

By estimating the magnitude of these contractual frictions, this research will shed light on the efficiency of player allocation in soccer leagues and provide insights relevant to broader labour markets.

Expected learning outcomes and deliverables:

Expected Outcomes:

1. Gain a deeper understanding of assortative matching in labor markets, particularly in professional sports.
2. Develop skills in data collection, database management, and econometric analysis.
3. Improve ability to analyze real-world data and interpret the results in the context of economic theory.

Deliverables:

1. A dataset containing player and team statistics, transfer details, and performance metrics.
2. A report summarizing findings on assortative matching and its implications for competitiveness and market efficiency.
3. Preliminary econometric analysis of sorting patterns in soccer leagues.

Suitable for:

This project is well-suited for motivated students in economics or statistics, ideally in their 3rd or 4th year, with an interest in labor economics, econometrics, and the sports industry. Ideal candidates will have:

1. Strong Analytical Skills: A solid foundation in economic theory and quantitative methods, with the ability to analyze and interpret complex datasets.
2. Research Interest: A keen interest in exploring labor market dynamics, particularly in the context of sports economics.
3. Proficiency in R, Stata, or Similar Packages: Command of R, Stata, or similar econometric software packages for data manipulation, statistical analysis, and econometric modeling is required.
4. Ability and Enthusiasm for Coding: A demonstrated ability and enthusiasm for coding, particularly in data analysis and econometrics, with a willingness to learn and apply new coding techniques.
5. Proactive and Collaborative Approach: The ability to work independently while also collaborating with peers and academic supervisors.

Primary Supervisor:

Allan R. Hernández-Chanto

Further info:

For further information, applicants are welcome to contact Allan Hernandez Chanto at a.hernandezchanto@uq.edu.au. If you have any questions or would like to discuss the project in more detail before submitting an application, please feel free to reach out.

Project title: 

Bribery, Favouritism, and Corruption in Auctions

Hours of engagement & delivery mode

The project requires a commitment of 36 hours per week, scheduled between 30 June and 25 July 2025. The student has the flexibility to choose whether to work remotely or in person, depending on their preference.

Description:

The project seeks to understand how bribery, corruption, and favoritism impact bidding behavior and sellers' expected revenue or costs in auction environments characterized by two-layer uncertainty, such as security-bid auctions and scaling auctions. These auctions involve multiple sources of uncertainty—such as private valuations of bidders and the inherent risks of the auction process—which interact to influence bidding strategies.

A key feature explored will be the role of first right of refusal, a mechanism that can influence bidders' strategies by giving them an advantage in subsequent bidding rounds. This can lead to distortions in bidding behavior, as bidders may adjust their offers to secure or block the first right of refusal, thereby affecting the overall auction outcome. Bribery and favoritism may exacerbate these effects, with some participants seeking to secure advantageous positions through illicit means.

The research will explore how these unethical practices distort auction outcomes. For instance, bribery may incentivize bidders to submit bids that do not reflect true valuations, while favoritism could result in biased pricing, reducing competition. In turn, these practices may lower the seller's expected revenue or increase costs, undermining the efficiency of the auction process.

By examining these dynamics in the context of security-bid and scaling auctions, and considering the role of first right of refusal, the project aims to develop a comprehensive understanding of how unethical behavior influences auction outcomes under conditions of uncertainty. This research will contribute to refining auction theory and inform the design of more robust auction mechanisms that mitigate the impact of corruption and favoritism.

Expected learning outcomes and deliverables:

Participants will gain a deep understanding of the impact of bribery, corruption, and favoritism on auction dynamics, particularly in contexts of two-layer uncertainty, such as security-bid and scaling auctions. They will develop the ability to critically analyze existing literature on these topics and draw connections to real-world cases where such practices have influenced auction outcomes. Additionally, participants will learn to evaluate how mechanisms like the first right of refusal alter bidding behavior and auction efficiency under unethical conditions. This will enhance their ability to apply theoretical concepts to practical situations in market design.

The main deliverables will include a comprehensive review of the literature, summarizing key theories and findings on bribery, favoritism, and corruption in auction environments, particularly in the context of uncertainty. Additionally, participants will be expected to conduct a review of relevant cases, identifying instances where such unethical practices have been observed or suspected in auction settings. This analysis will highlight the implications for both sellers' expected revenue or costs and the efficiency of the auction process. Finally, participants will provide a synthesis of how these findings inform the design of more effective and equitable auction mechanisms.

Suitable for:

This project is suitable for third or fourth-year students with a strong interest in microeconomic theory, particularly those with a focus on auction theory, market design, and strategic behavior under uncertainty. Students should have a solid foundation in economic principles and be familiar with advanced economic modeling and statistical analysis to engage with the research questions and literature review.

Primary Supervisor:

Allan R. Hernández-Chanto

Further info:

For further information, applicants are welcome to contact Allan Hernandez Chanto at a.hernandezchanto@uq.edu.au. If you have any questions or would like to discuss the project in more detail before submitting an application, please feel free to reach out.

Project title: 

Disentangling students’ strategies in Centralised Admission Systems

Hours of engagement & delivery mode

The project requires a commitment of 36 hours per week, scheduled between 30 June and 25 July 2025. The student has the flexibility to choose whether to work remotely or in person, depending on their preference.

Description:

This project focuses on a rich administrative dataset from the University of Costa Rica (UCR) spanning the years 2008-2012, capturing data on students' reported preferences for academic programs, their assignment results, and the thresholds for previous years' admissions. The UCR employs a serial dictator algorithm for admissions, where students only report two preferences, often choosing between academic areas such as medicine, pharmacy, microbiology, and others. This project aims to identify patterns in how students report their preferences and understand the factors that influence these decisions. Key aspects of this analysis include:

• Continuity in preferences across academic areas (e.g., medicine → pharmacy).
• Strategic behaviour, such as hedging with safety options.
• The role of probabilities of admission in students’ decision-making.
• The behaviour of students at the top and bottom affecting the outcomes of those in the middle.

The student will work to identify and document these regularities in the dataset, contributing to the broader understanding of centralized admission systems and their implications for student behaviour.

Expected learning outcomes and deliverables:

Outcomes:
Participants in this project will gain comprehensive knowledge in several key areas:

1. Understand Strategic Behavior in Admissions Systems: Learn the principles of centralized admission processes like UCR's serial dictator algorithm and the role of strategic versus truthful reporting.
2. Analyze Reporting Continuity and Hedging: Investigate how students choose academic areas and the role of safety options in decision-making.
3. Explore the Role of Admission Probabilities: Understand how probabilities of admission affect students’ strategic choices.
4. Develop Econometric Analysis Skills: Gain hands-on experience with econometric modeling, focusing on strategic decision-making in admissions.
5. Apply Data Analysis to Real-World Problems: Use real data to derive insights into the design and operation of centralized admissions systems.

Deliverables:
By the end of the project, participants will be expected to:

1. Econometric Analysis: Conduct a thorough statistical analysis to identify patterns in student behavior, including strategic choices, continuity of preferences, and the effects of admission probabilities.
2. Documentation: Provide a comprehensive report summarizing findings related to student reporting behavior, including a detailed analysis of how these behaviors differ by student performance level (top, middle, bottom).
3. Modeling: Develop models to predict student choices based on covariates such as admission scores and the probability of acceptance.
4. Code and Data: Deliver a clean, well-documented dataset and code used to conduct the analysis.

Suitable for:

This project is ideal for motivated students in their third or fourth-year of economics, statistics, or computer science with a strong interest in econometrics, strategic behaviour, and centralized admission systems. It is well-suited for students considering an honours program or applying for a PhD in economics or related fields.

Candidates should have:

1. Strong Analytical Skills: A solid foundation in economic theory, statistics, and quantitative methods.
2. Proficiency in R, Stata, or Python: Experience with econometric software for data analysis.
3. Interest in Centralized Systems: A keen interest in understanding and improving centralized admission processes.
4. Ability and Enthusiasm for Coding: Proficiency in coding and a willingness to solve real-world problems through data analysis.

Primary Supervisor:

Allan R. Hernández-Chanto

Further info:

For further information, applicants are welcome to contact Allan Hernandez Chanto at a.hernandezchanto@uq.edu.au. If you have any questions or would like to discuss the project in more detail before submitting an application, please feel free to reach out.