In an era of unprecedented financial challenges, health emergencies, and technological disruptions, pension funds are critical to economic stability. Focused on the contexts of Indonesian employee pension funds, the study navigates the intricate dynamics of pension systems within the broader economy. Against an evolving global landscape marked by financial uncertainties and demographic shifts, the research scrutinizes how distinct pension schemes adopted by Indonesian employee pension funds shape the resilience and efficacy of their respective pension funds. The research employs two distinct yet complementary models to investigate the dynamic of pension fund outcomes amidst varying macroeconomic conditions and micro-level management practices. Firstly, a Vector Autoregression (VAR) model is utilized to explore the intricate interactions between macroeconomic variables. The VAR model allows for the simultaneous examination of multiple variables to understand the short and long-term effects on pension fund dynamics. Secondly, a micro-level panel data regression model is employed to delve deeper into specific factors influencing pension fund performance, including contribution rates, investment strategies, coverage, regulatory frameworks, and risk management practices. The analysis incorporates treatment variables related to the COVID-19 pandemic to examine the resilience of pension funds to external shocks. The empirical findings reveal significant associations between various macroeconomic factors, micro-level management practices, and pension fund performance outcomes. Notably, higher contribution rates, broader coverage, and effective risk management are found to positively impact pension fund performance, while certain aspects of the funding mechanism and regulatory framework exhibit negative associations. The study contributes to the existing literature by offering insights into the complex interplay between macroeconomic conditions, micro-level management practices, and pension fund outcomes, providing valuable implications for policymakers, practitioners, and stakeholders in the pension fund industry.

This paper explores the effects of automation and the creation of new tasks on labour market outcomes by incorporating the task-based production of Acemoglu and Restrepo (2018a) into a modified Diamond-Mortensen-Pissarides (DMP) search and matching framework. While the effect on wages aligns with existing literature, the introduction of search frictions offers new insights regarding effects on unemployment. Automation is found to have a dual impact: it displaces workers from routine tasks but simultaneously generates productivity gains which can offset its negative effects. The net impact on unemployment and wages depends on the relative magnitude of these displacement and productivity effects which are analytically derived in the research. In contrast, the creation of new tasks has a more uniformly positive impact, as it both enhances the productivity and reinstates displaced workers, leading to lower unemployment and higher wages. The findings suggest that policies should ensure not to promote excessive automation, where it negatively affect the labour market. In contrast, fostering innovation and task creation can be effective ways to benefiting from technological advancements.

This paper investigates the impact of psychological distress on hourly wages and labour market participation within the Australian population, focusing on gender differences. The findings indicate that psychological distress significantly affects labour market outcomes, with varying effects based on gender and mental health status. Specifically, psychological distress significantly decreased hourly wages for healthy males and unhealthy females. An increase in labour market participation amongst mentally unhealthy males and both healthy and unhealthy females was also found. The research utilised data from biennial waves between 2007 and 2021, sourced from the Household, Income and Labour Dynamics in Australia (HILDA) survey.

Political polarisation has become a prevalent phenomenon in the past decades. Parallelly, citizens have increasingly resorted to collective actions to demand change, resulting in incidents such as the Jan 6 US Capitol riot. Evidence suggests that such public remonstrations exacerbated the extent of opinion divergence. This paper therefore presents a model that explains the dynamic connection between political polarisation and collective actions. In the setup, voting, abstention, and participation in collective actions are novelly modelled as individual components of a citizen’s political toolkit. With endogenous voter preferences alone, polarisation has an exacerbating but limited effect on the level of collective actions. In turn, collective actions accelerate the process of polarisation for the election-losing partisans, creating asymmetry in the voter distribution. It is only when combined with strategic behaviour of the parties that polarisation may lead to substantially intensified collective actions.

Over the last 40 years, populist leaders have been elected, as heads of government, to at least 27 of the world’s 105 electoral democracies. With most of these successful election bids occurring in the last two decades, researchers have had to expeditiously update their intuitions of the political phenomena, retrofitting new concepts and assumptions to a literature once ill-prepared for non-Latin American manifestations of populist governance. Leveraging this new, generalised understanding of populism, my paper aims to analyse the economic causes of populism through a globalised, rather than regionalist, description of the phenomena. In particular, I attempt to draw parallels between our updated understanding of populism and Brazil’s 2018 election of right-wing populist Jair Bolsonaro. Grounding my analysis in this recent example, I introduce a two-way fixed effects logistic model to estimate the relationship between macroeconomic variables and the successful election of populist heads of government more broadly. This is performed on a panel of 105 countries between the years 1980-2020. Finding limited evidence for a relationship between variables typically associated with populist success – namely, austerity, unemployment and globalisation – my research casts some doubt towards the generalisability of past European and Latin American explanations of the causes of populism. Nonetheless, my model does find a statistically significant relationship between annual GDP growth and the likelihood of a populist being elected, with a 1% increase in GDP reducing the odds of a populist being elected by 12.5%, within the next zero to five years.

Large Language Models (LLMs), such as ChatGPT, demonstrate an unprecedented applicability in a variety of domains, and, unlike previous waves of innovation, are capable of nonroutine cognitive tasks - leaving educated, white-collar workers most exposed. However, few studies address the relevant labour market implications outside controlled experimental environments. This project investigates the effects of LLMs on knowledge worker competency requirements using a difference-in-difference model based on a sample of 105,912 online job advertisements (Luxembourg, 2020-2024). The findings contain weak evidence that LLMs cause a reduction in demand for experience, education, cognitive skills and creativity, while leaving soft skills unaffected.

We use an online experiment and survey to establish that consumers are misinformed about electric vehicles and that correcting misinformation has little impact on preferences for electric vehicles but some impact on electric vehicle policy preferences. Specifically, correcting misperceptions does not change consumers’ willingness to support pro-electric vehicle government initiatives but does cause specific EV policies to be preferred more or less. We estimate the effect of correcting misinformation by employing two information treatments : an informative narrative and a fact sheet. These treatments successfully make electric vehicle perceptions more accurate, but neither narratives nor fact sheets are more successful at correcting misperceptions. We determine preferences using survey questions, relying on indirect and incentivised questions to rule out the influence of social desirability bias on participants’ responses.

I examine political favoritism based on prior support during conflicts. In particular, I identify whether or not the new Taliban regime in Afghanistan, which took over in August 2021, is systematically favoring its past allies using a difference-in-differences method. I proxy economic activity using night time light intensity and conflict alignment using a database of 75,915 militarily significant conflict events occurring in Afghanistan from 2004-2009. I find evidence that the Taliban are discriminating against their former enemies. I also find evidence that the Taliban are actively favouring their past allies in periods of low economic activity. This paper augments the literature on political favoritism by creating a new measure for political alignment and also suggests that the Taliban could be contributing to regional instability through favoritism.

Mertens and Zamir (1985) first provided the universal type space construction for finite player games of incomplete information with a compact state space. Brandenburger and Dekel (1993) complemented it for a Polish state space. This paper extends the construction of Brandenburger and Dekel (1993) to games with infinitely many players for Harsanyi’s notion of a type. The extension is formulated by randomly drawing a countably infinite set of actual players from a continuum of potential players, represented by their labels in [0,1]. The random distribution of the countably infinite set of actual players almost surely converges to Lebesgue due to the Glivenko–Cantelli theorem. A coherent type is shown to induce beliefs over other player’s types and common knowledge of coherency closes the model of beliefs. Implications of dropping the Polish space assumption are discussed and an informal extension to measurable spaces is provided for future work. The formalisation provided here allows Harsanyi’s notion of type to be applied in classes of games with many players such as Morris and Shin (2001)

This paper analyses how income inequality changes through the clean energy transition. Gini Coefficients are used to present overall changes in inequality over the chosen time period. Influences of rooftop solar and electrification are considered in this report as the literature suggests there is unequal access to these technologies. Key findings suggest the energy transition contributes to an overall decline in inequality from 2023 to 2050 and energy prices become cheaper. Larger proportion of households with solar, reduces the burden of high energy prices. However, the fall in inequality is shown to not be equal across all income brackets with the lowest two brackets declining the least. In the data, the gap between the highest and lowest income brackets remains prevalent at the point of Net Zero.

Although local government splits have been widely implemented in developing countries, there is limited empirical evidence on their effects on economic activities. This study investigates the impacts of district splits on household business activities using a rich household-level panel dataset that spans over 20 years and covers an episode of massive district splits in Indonesia. Using a difference-in-differences approach, I found that district splits do not improve non-farm business revenue growth. Instead, they drive more businesses to exit from the industry. On the other hand, district splits improve farm business revenue growth and entry into this industry. However, the growth effect is not driven by productivity improvement as expected, but solely the result of land input expansion, which is likely acquired in unsustainable ways. Additionally, district splits decrease out-migration, aligning with the Tiebout sorting model. Taken together, these findings add another argument for the need to reevaluate the current practices and regulations on local government splits.

Using data from the Household, Income and Labour Dynamics (HILDA) survey, I explore the effects of housing wealth on healthcare utilisation in Australia. I use exogenous variations in house prices to estimate the potential direct and indirect effects of housing wealth on homeowners’ healthcare utilisation. I find no evidence of a direct wealth effect on healthcare utilisation, nor do I find evidence of an indirect healthcare insurance effect. However, my findings indicate an indirect health investment effect. Increases in housing wealth cause improvements in homeowners’ health which in turn reduces their use of GP services

This study examines the changes in buy-to-let property prices and their transaction shares before and after the implementation of Section 24 of the Finance (No. 2) Act 2015, a residential landlord tax reform. A novel data set of 7,318,913 property transactions spanning from October 2013 to December 2021 is constructed from 53.27GB of raw data. The data is organised into two sub-samples: one with all transactions and one with only new properties. Difference-in-differences and Logit are used to investigate price change and buy-to-let likelihood. In general, the results show that, after the reform, buy-to-let prices did not fall compared to non-buy-to-let prices but rather climbed slightly. Due to additional limitations, the results should primarily be considered descriptive. Only the new-build property sub-sample passes the common trend test, and the models used cannot adequately account for other concurrent events like COVID-19 and the increase in stamp duty.

Australia has been at the global forefront in using higher cigarette taxes to curb smoking behaviours. This paper aims to utilise Australia’s precipitous increase in cigarette taxes (via its tobacco excise) to examine how it is affecting smoking behaviours across the population. Data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey are used to estimate individuals’ behavioural changes in response to rising cigarette taxes, with the analysis extended to detail household income quintiles and discrete age groups. In general, it is difficult to separate the effect of rising cigarette taxes with growth in anti-smoking sentiment, but it is evident that higher cigarette taxes work to reduce smoking behaviours, and that it affects different groups in different ways. Notably, financially constrained people in the lowest-income households are much more likely to quit smoking or reduce their smoking intensity in response to higher cigarette taxes than those in higher-income household, while younger people are becoming less inclined to start smoking and subsequently become addicted.

I study the effect of lifting restrictions on night – shift work for women on their labour market outcomes. Using the staggered repeal of night – shift restrictions for women under the Factories Act, 1948 in the Indian states of Punjab, Gujarat, Maharashtra, and Assam, I employ a Triple Difference model to estimate its effect on the share of women workers and daily wages for women in manufacturing. My results suggest no significant impact as the estimated effects are close to 0 and statistically insignificant. I am also able to rule out effects larger than 0.95 p.p and 2.8% on the share of women workers and daily wages respectively, and these estimates are robust to the use of the Stacked Triple Difference regression. I also provide several possible explanations for my results using case studies.

This paper estimates the causal effects of electing criminally accused politicians on Maoist-initiated incidents in India at the constituency level. The research leverages the methodology of regression discontinuity design, contrasting constituency where criminally accused candidates barely lost with constituencies where non-accused candidates barely lost. The findings provide preliminary indications of the negative effect of electing criminally accused leaders on the Maoist-initiated incidents. Notably, this effect is more pronounced when accounting for variations across different states. The analysis reveals that the election of criminally accused leaders correlated with a reduction of nearly three Maoist-initiated incidents in Jharkhand, and notably, this effect remains observable over an extended period.

This paper studies the effect of mineral price shocks on the probability of offshore incorporations in tax-havens. Since offshore accounts are widely tied to rent-seeking and corruption in the natural resource sector, we use these observed effects to gain insight into patterns of rent-seeking in mineral dependent countries. We construct a novel dataset that combines monthly data on the incorporation of offshore accounts from the Panama Papers with information about a country’s mineral endowments and monthly world mineral prices. Using a fixed-effects linear probability model, we find that that a large price increase has a positive effect on probability of offshore incorporations in subsequent months, in mineral dependent countries. This effect is stronger in countries with weak institutional quality and higher levels of foreign ownership of mines. We deviate from previous work through our focus on the effects of mineral rents rather than petroleum rents and through our introduction of ownership structure as a key variable of importance.

Following the financial crisis of 2008, central banks started paying more attention to the issue of financial stability and to the amount of credit circulating in the economy. However, the methods used to forecast credit often are underdeveloped and don’t make the most out of access to big data. This paper evaluates the performance of various models in forecasting the Dynamics of Credit to the Non-Financial Sector in the United States. It explores three approaches: the reduced form Vector Autoregressive model, Vector Error Correction model and Factor-Augmented Autoregressive model. The paper compares the RMSE of the models and finds that FAVAR approach outperforms traditional VAR and VEC models and produces more accurate forecasts of credit dynamics.

This paper analyses the importance of age, experience and team stability for on-field success for clubs in the Australian Football League (AFL). We use a fixed effects model to estimate our main results, with the key findings showing the importance of team composition and team stability. Team stability, representing social capital within the team, was shown to be a key factor in estimating home and away wins in the AFL over the years of 2010 to 2021. We find the importance of age as a limiting factor in a team’s capacity to generate home and away wins, whereby a minimum average age of a team is a necessary but not sufficient requirement for team success. Additionally, it was found the age bracket with the greatest impact on win percentage is players in their early twenties (21-25 years old). We find the most important component of a team’s composition is the level of match experience held by the team as a whole, with the proportion of players with greater than 100 matches experience contributing positively and significantly to team performance.

I present a two-stage model of committee voting with costly expert information. For every member of the committee to observe and synthesise independent testimony of some fixed and known quality, a majority of the agents must contribute to its acquisition. When testimony is observed with positive probability, I show that adding agents to the committee depresses the probability with which any single agent contributes - due to free-riding and demonstrate how, with some careful assumptions, the probability of reaching the correct decision should correspondingly fall with the committee size. Moreover, I show individuals will make more accurate decisions than all groups whose aggregated signals are, collectively, inferior to the expert testimony. In keeping with Mukhopadhayas (2003) seminal work on the acquisition of private signals, these findings argue against arbitrarily enlarging committees to improve the quality of majority decisions but instead propose the dichotomous choice between individual decision-makers, and collectives whose aggregated signals are more accurate than the expert signal. Further research might permit agents to choose the amount of information they acquire, or model both private and expert information as costly

With Australia recently legislating a 2030 emissions reduction target, market-based approaches (such as carbon pricing) should be considered as a policy approach to achieve these reductions at least cost to the economy. This paper begins by delving into the economic theory behind carbon pricing and why it is considered the least cost emissions reduction method, then synthesises the literature on the outcomes of carbon pricing implemented in other jurisdictions to inform a potential Australian policy. This paper then explores market-based approaches in the Australian context by analysing Australia’s previous attempt to implement carbon pricing. Empirical analysis in the paper demonstrates what level of emissions reductions can be expected for different levels of carbon tax, for instance, a carbon tax of AUD$112/tCO2 would reduce emissions by 41.18% from 2005 levels by 2030 (Australia's target is 43%). These findings inform policymakers determining the best policy mix to achieve emissions reduction targets, and what level of reductions should come from a carbon price compared to other policy measures. This paper also highlights the importance of accompanying carbon pricing with policies addressing the inequality effects to increase the longevity of the policy and to avoid mistakes of previous failed attempts to implement carbon pricing.

Misinformation dissemination in social media has emerged as a critical contemporary issue. This paper augments existing models of online misinformation by incorporating endogenous reputation dynamics. In contrast to prior research, reputation plays a pivotal role in shaping agents Bayesian-Nash equilibrium strategy through two key avenues : (i) the sharer’s reputation positively impacts the likelihood of sharing, and (ii) agents with higher initial reputations are less willing to share compared to their counterparts with lower initial reputations. Furthermore, this paper provides insights into the formation of individuals’ networks on social media. Surprisingly, individuals with high reputations are not universally favoured as network connections. Additionally, the paper examines relevant comparative statics, including the importance of interactions, and the implications of homophily. This research establishes a foundation for understanding the dynamics of reputation-based information sharing and network structure.

As climate change continues to amplify the incidence of extreme weather events, policymakers are increasingly cognizant of the mounting financial burdens brought by a warming world. This paper examines the costs which have followed natural disasters in Australia between 1970-2022, utilising data from the Insurance Council of Australia and the Australian Institute for Disaster Resilience. The financial impact of disasters is estimated by applying loss ratios to insurance claim data and overlaying mortality and injury costs. An autoregressive integrated moving average model is then applied to forecast these costs out to 2030. The results show an average annual cost of between $2.9 billion to $6.7 billion between 1970-2022 and highlight the tendency for large-scale events to drive the majority of losses, with events in the top decile of costs accounting for 68% of all losses incurred in the period. The scale and volatility of costs following extreme weather events reinforces the need for both physical and fiscal preparedness of governments in meeting the economic challenges presented by climate change.

Child marriage remains a prevalent practice in many countries around the world and can detrimentally affect various life outcomes for young women and girls. Using data from the India Human Development Survey (IHDS-II), this paper explores the relationship between early marriage and the educational attainment of Indian women. The study uses age of menarche as an instrumental variable to isolate the causal effect of marriage timing, with results indicating that each additional year that marriage is delayed is associated with 0.32 additional years of schooling and a 1.9 percentage-point increase in literacy. The findings highlight the lack of regulation of current marriage laws and the need for stringent enforcement, rather than the Indian government’s current aims to increase the legal age of marriage for women further. In addition, this study also conducts heterogeneity analysis to determine the possible benefit of this policy recommendation across different residence types, as well as estimates the effect of marriage timing on secondary outcomes.

This paper extends research conducted on the wage premia in Australia from acquiring tertiary education qualifications, covering the period 2007-08 to 2019-20. This analysis finds that while there is an increase in wages for those that complete tertiary education, the proportional increase in wages from obtaining university qualification declines marginally over the period. Conversely, the proportional increase in wages from obtaining other tertiary qualifications remains constant, with males consistently earning higher proportional increases than females. When accounting for location, there is no consistent significant effect on wages when comparing capital city and regional populations. However, when the mining industry is also accounted for, there is a significant positive effect to wages from living in a capital city in most years assessed, ranging from 2.5 to 6.7 per cent

The optimal allocation of human resources into different areas of the economy is vital for the growth and productivity of countries, particularly in a rapidly changing workforce environment. Previous literature and statistics indicate that overeducation (when an individual is overqualified for their career) lengthens unemployment at the individual level after graduation, among other negative outcomes. This study aimed to assess whether increasing the proportion of higher degree graduates affected the unemployment rate of countries in the subsequent year, using a differences in differences model. The study used graduation data from 2013-2018 in 23 countries. The results suggest that having more bachelor’s and master’s degree graduates increases the next year’s unemployment rate in countries with higher relative levels of overeducation, while increasing graduates from other degree types did not have this effect. This study was severely limited by a small sample size, but the results suggest further research on this issue is warranted.

This paper examines the relationship between economic inequality and expansions of bank credit in Australia throughout recent decades. This relationship is a central component of what has become colloquially known as the “Rajan hypothesis” and more technically referred to as the “inequality, credit, crisis nexus”. The findings of the paper suggest that although there is a strong positive relationship between inequality and expansions of bank credit in Australia at the most aggregated level (consistent with international studies of the phenomenon in which Australia was included in panel data), when the types of loans are examined in more detail, their correlation with inequality is not consistent with the belief that credit is channelled specifically to low income households as inequality worsens (as is suggested by the Rajan hypothesis). There are multiple ways in which the Australian case differs from the American which may contribute to the differing results, some of which include a lower levels of income inequality, more progressive taxation policy which reduces consumption inequality, and stricter macroprudential policy which resulted in fewer subprime loans.

This paper gives a fresh perspective on the New Keynesian Philips Curve (NKPC) when combining the rational inattention hypothesis, which will give a new insight into backward-looking evidence. A further contribution of this paper is to give a unique application method of the development of the rational inattention hypothesis in other economic fields. This study provides the viewpoint that OLS (ordinary least squares) estimators have an imperfect information bias under the noise information model where economic agents optimize their behaviors through the rational inattention hypothesis. Specifically, the information flow constraint is redefined as the regression coefficient constraint by information theory extension. As a result, if the rational inattention hypothesis is expected to hold in economic fields, the Ridge regression can provide optimal estimations for economists in their fields by allowing them to consider the imperfect information bias through penalizing the coefficients. In empirical work, the rational inattention model complements the NKPC by including the imperfect information bias error in the regression analysis. The estimation reveals that the imperfect information bias error can play a backward-looking role. The rational inattention NKPC introduces the backward-looking element theoretically and demonstrates inflation inertia well.

This paper investigates the impact of car sharing services (GoGet and Flexicar) on transport equity in Melbourne and Brisbane, Australia, including two lower socio-economic regions of Melbourne. The results show evidence of strong latent demand for car sharing services in these areas, indicating the potential for car sharing to improve access to transport and transport equity for disadvantaged communities. The study also finds that the main barriers to the adoption of car sharing were lack of availability, cost and lack of awareness. The findings suggest that expanding car sharing services could improve transport equity outcomes in low socio-economic areas.

This study provides novel evidence on how monitoring and evaluation affects racial health inequality, with data from the Primary Care Access and Quality (PMAQ) Program in Brazil. By using the heterogeneity-robust estimator from de Chaisemartin and D'Haultfoeuille (2022), this study considers the non-staggered and non-binary characteristics of the treatment. The results show that an increase in monitoring and evaluation intensity can reduce racial health inequality, achieved by improving the health conditions for non-white individuals and deterioration of the health conditions for white individuals. It is suggested for policy makers to increase the allocation of health resources to ensure that while racial health inequality is reduced, both white and non-white individuals can benefit from an improvement in primary health care, rather than narrowing the gap by reducing the quality of care for one group.

This article uses economic analysis of the marcher lord actor theorised by sociology literature, particularly the work of Michael Mann (1986), to explain the shifting nature of power in the ancient world. We model the marcher lord to argue that a first mover advantage from developing state institutions first does not bring a lasting military advantage as lesser developed lords located closer to the periphery of a region are better able to diversify their armies. We develop a second model to analyse Mann's strategies of control and a rational calculus of technology adoption to consider whether new empires will emerge to dominate existing empires. We find that advancement does not emanate from the seat of power, rather marcher lords on the periphery of civilisation development have the opportunity to expand leading to them being more innovative and able to shift the centre of power away from stablished empires in later time periods.

Infectious disease has always been a concern to people, especially under the current COVID-19 pandemic. The aim of this paper is to find a causal relationship between social interaction and disease spreading. This paper takes the ‘Spanish Flu’ in 1918 in the background of Sweden rather than COVID to rule out some uncertainty in transmission tunnels and use railway access as proximity to social contact. Using Diff-in-Diff identification, combined with a short-term event-study design, I show that localities that have railway stations nearby are likely to have more death cases during the influenza period. I use exogenous variation in railway station emergence from initial railway plans in addition and verifying that railway indeed facilitates the disease transmission and mortality rate as well but only with limited effects.

This paper analyses for the first time, the relationship between private health insurance and household savings behaviour in Australia. Using the nationally representative longitudinal dataset from the Household, Income and Labour Dynamics in Australia (HILDA) Survey, we estimate the effect of private health insurance on savings, wealth accumulation and different types of asset holdings. We find strong evidence of a positive relationship between private health insurance and savings using a variety of panel fixed-effects, instrumental and non- instrumental methods. The magnitude of the effect is larger for households that do not receive public transfers, reside in a major city, have better health or have completed tertiary education. Our findings show that time preference is a partial mediation channel between private health insurance and savings, resulting in larger effects for non-financial asset holdings driven mostly by real estate wealth.

The Minimum Energy Efficiency Standard (MEES) aims to improve the energy efficiency of privately rented properties in England and Wales. Previous literature identifies this policy intervention as a driver of transition risk as it devalues substandard real estate. This paper reveals that MEES also devalues neighbouring houses meant to be una↵ected by the policy, i.e. above-standard properties. The study leverages a dataset that combines energy efficiency and transaction data at the postcode level to capture this spatial externality. A concentration measure for sub-standard properties within a neighbourhood is constructed, which is applied to aggregate and property level analyses using a difference-in-difference specification. The aggregate analysis reveals that an incremental increase in the concentration of sub-standard housing within a postcode sector after introducing the standard leads to a 20.1% decrease in aggregate prices for above-standard houses. A repeated sales regression run on property-level data finds that an increase in concentration leads to a more plausible 4.03% decrease in prices for above-standard properties. These results imply potential problems for homeowners who may find themselves in negative equity due to the aggregate price drop, which may also negatively impact their pro-environmental investments.

Wildlife hunting is one of the largest causes of biodiversity loss, yet its drivers are still poorly understood. This paper quantifies the relationship between income and wildlife hunting in Cambodia, a country at the forefront of the clash between economic development and biodiversity loss. We use two nationally representative datasets which, unusually, collect detailed data on both the consumption and sales of hunted wildlife to estimate the importance of income on wildlife hunting in rural areas. Using rainfall shocks in the beginning of the main agricultural production season and prices of other protein sources as sources of exogenous variation in household income, we show that income has a causal negative relationship with wildlife hunting in rural Cambodia. We use these estimates to explore the effectiveness of cash transfers as a policy that promotes both wildlife conservation and poverty alleviation by primarily reducing the value of hunted wildlife as a coping strategy.

To test whether education can change risk preference, I exploit the Indonesian school construction programme and the Mexican education reform in compulsory schooling as two separate natural experiments. Applying the instrumental variable approach, I do not find a causal effect of education on risk preference. The results are consistent in the two different settings, so my findings are externally valid. The results suggest that a change in risk preference may not be the channel via which the impact of education on risk-taking in real life. This paper contributes to the literature on the determinants of social preferences and the outcomes of education.

We use individual-level panel data from Australia and a novel fixed-effect instrumental variable approach to estimate the causal effect of housing cost on five measures of household transportation; work commute time, relocation, and the respective expenditure share on motor vehicle fuel, public transport and taxi, and total transportation. The instrumental variable exploits arguably exogenous variation in housing costs induced by foreign investments that flow differentially into regions according to the past geographical distribution of immigrants. We find that rises in housing costs, measured by the composite opportunity costs faced by representative renters and owners living in an area, increase an individual’s work commute time and the probability of relocation, and lead to a shift in the individual’s expenditure away from fuel towards public transportation.

I conduct content analysis and extent the existing models of analysing the reaction of the stock market and foreign currency markets to the release of Federal Open Market Committee (FOMC) statements and meeting minutes. The tone changes and uncertainty level of the monetary policy communication are constructed using the dictionary-based word-count approach at the whole document level. I further apply the Latent Dirichlet Allocation (LDA) algorithm to investigate the different impacts of topics in the meeting minutes. High-frequency data is used as the analysis is an event study. I find that the tone change and uncertainty level have limited explanation power on the magnitude of the effect of the release of FOMC documents especially statements on the financial market. The communication from FOMC is more informative for the market during the zero lower bound period, compared to the whole sample period.

We investigate the role of international credit market constraint in a dynamic stochastic general equilibrium model in determining the effect of government spending policies on macroeconomic variables such as consumption and the real exchange rate in a small open economy. The numerical results show that increasing government expenditure under certain economic shocks can increase the value of the real exchange rate and reduce the chance of the small open economy reaching the borrowing limit. Hence, the dynamics of consumption and the real exchange rate can be significantly affected by government spending policies under international credit market constraints.

Developments in Artificial Intelligence and Machine Learning technologies have had massive implications for labour automation. This paper builds on the task-based methodology first adopted by Frey and Osborne (2013) to predict how the risk of automation evolved in the UK labour between 2012 and 2017 using data from the UK Skills and Employment Survey. The analysis accounts for technological progress, making use of two sets of experts’ assessments for 70 occupations. The probability of automation is predicted for each individual using a set of self-reported job skills. It finds that the proportion of jobs at high-risk from automation has risen from 10.6% to 23.4%, and that this is largely due to better technology rather than changing job skill requirements. It also identifies sectors experiencing the greatest increase in automation risk between the two periods and, in contrast, those which appear complementary to technology, drawing on occupational case studies as evidence.

Nascent and highly dynamic industries such as the rideshare industry have disrupted traditional industries and business models. The use of technology has allowed firms like Uber and Didi to compete over both consumers and workers on an increasingly sophisticated level. This paper explores the use of algorithmic pricing strategies employed by the rideshare industry and the impact of such strategies on the overall level of competition in the market. It uses the Mexico City, Mexico, rideshare industry as a case study. The paper shows that specific firms target specific consumers based on whether those consumers are informed or uninformed about other options in the market, and do so at specific times based on the level of demand in the market. The findings of the paper are relevant for both economic understanding of such markets as well as policy responses.

The impact of teachers’ unions on educational outcomes is theoretically and empirically ambiguous. This study aims to provide additional evidence to this debate by analyzing the educational impact of Wisconsin’s Act 10, which significantly weakened teachers’ unions. A unique school-level dataset is constructed containing data on educational outcomes, high-school and district-level characteristics in Wisconsin and Illinois. Schools in treated and control groups are matched using propensity score matching. A difference-in-difference methodology is used to mitigate problems surrounding simultaneity and omitted variable bias from standard OLS regression. This paper uses an event study design and a triple difference model to estimate the effect of Act 10 on the dropout rate and subject proficiency rate. The triple difference model used has lower power but is more robust to the parallel trends assumption as it takes into account differences in economic conditions between states. Models suggest that weakening teachers’ unions worsens educational outcomes, providing support for the union-voice hypothesis.

Why do female leaders do better in crisis situations than their male counterparts as a stylised fact? We integrate intrinsic preference into a Leader – Expert coordination game to model the impact of dominant strategies on the effectiveness of crisis management outcomes. We show that given the Leader has intrinsic preference for cooperative (competitive) behaviour, the Expert will reciprocate in kind which results in the highest (lowest) social outcome. Using cultural transmission theory to develop the theoretical micro-foundation of this preference, we find socialisation inefficiencies arising from two-parent socialisation result in the persistence of cooperative traits in women and competitive traits in men, thereby providing a mechanism for more effective crisis management by female leaders. Drawing upon feminist and leadership theory to inform our assumptions, we suggest that collective ability to deal with crisis will be improved if male leaders are more cooperative.

In today's love market, swipe-based dating platforms (SBDPs) such as Tinder or Bumble have a well-established presence, but novel platform features can add signicant complexities to the user's search problem in ways that have been largely under-studied in previous literature. This paper formulates a model of two-sided search within SBDPs, where agents with heterogeneous preferences seek multiple romantic partners whilst facing intertemporal action constraints. Using numerical methods, I approximate stationary equilibria and perform comparative statics on various exogenous parameters that help explain stylised empirical facts. Finally, agent-based simulations are used to asses the structure of stationary equilibria as well as its attainability under myopic best-response dynamics.

This research project intends to further contribute to academic literature surrounding the relationship between motorsport events and spectators’ driving behaviour. Namely, it attempts to determine if there is a quantifiable human capital cost to Victoria’s economy from greater motor vehicle crashes (MVCs) over the course of the Australian Formula One Grand Prix event. In examining VicRoads traffic incident data from 2006 to 2019, this analysis finds statistically significant evidence to suggest there is on average +7.05 to +13.01 more high-speed MVCs in Victoria throughout the Australian Formula One Grand Prix event. In attempting to improve the accuracy of economic impact assessment methodology, this translates to a previously ignored expected human capital cost to Victoria’s economy when a Formula One event is hosted of $1,326,450.52 to $2,447,818.62. In response, this research project contends that economic impact assessments for motorsport events must include a calculation of the human capital cost from a change in spectators’ driving behaviour.

Ever since star-studded copyright infringement cases in the early 1990s concluded that the process of music sampling did not constitute ‘fair use’ of intellectual property, high licensing costs have made the process prohibitively expensive. Employing streaming service data, this paper reevaluates the traditional ineligibility of the fair use doctrine by presenting empirical evidence of music sampling’s effect on the popularity of sampled songs on Spotify over the period 2016-2022. It then examines for which levels of pre-sampling popularity this effect is strongest, as well as the effect of genre and the relationship between the genres of the sampled and sampling song. We find that sampled songs are added to playlists at a 20-40% higher rate for a seven week period after being repurposed within popular songs. Furthermore, original works see greater increases in the rate of playlist addition when there is more scope for sampling to act as informative advertising: when sampled songs were already well known, or had genre characteristics that imply listener familiarity (such as being repurposed in a song of the same genre), our primary findings diminished or disappeared entirely.

This paper presents results from an online experiment to show whether exchange asymmetry exists with charitable objects; a novelty good not yet used in past experiments. The rationale of this novelty was to excavate the notion of ownership of the goods by reason that charitable objects cannot be kept. These experimental results show exchange asymmetry exists in this novel context, implicating that ownership of the object was not necessary for exchange asymmetry to occur. This supports literature which posits that experimental protocols underpin observed exchange asymmetries in laboratory experiments. This research, therefore, further demarcates a distinguishing line between (1) the increased valuation of an object due to idiosyncratic associations through its ownership over time and (2) an immediately instantiated sense of ownership proclaimed to be the same effect manifesting in laboratory experiments.

This paper investigates the impact of ECB Unconventional Monetary Policy announcements on the 10-year sovereign bond yields of eleven Euro area countries. This paper uses event study methodology to examine expansionary UMP announcements between 1st January 2007 and 31st December 2021. Consistent with the literature, I find significant negative announcement effects on sovereign yields collectively examining all programmes. Differences in the magnitude and significance of individual country reactions are closely related to their solvency status. This is persistent for the most recent programmes in response to the Covid-19 pandemic which extends the scope of current literature. This paper also incorporates intraday analysis to more closely examine the determinants of announcement effects on their respective dates.