AUT Economics and Finance Department
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The AUT Economics and Finance Department has an established record and an on-going commitment to excellent research, high-quality supervision, and community and professional engagement. Members of the department sit on editorial boards and serve as referees for professional journals. The department has particular research strength in: Micro and macroeconomics, Econometrics, Industrial organisation, International trade and finance, Natural resource and environmental economics, Labour economics, Economic development, Health economics, and Public policy.
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Recent Submissions
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- ItemEstimating Long-Term Expected Returns(Taylor and Francis Group, 2024-06-13) Ma, R; Marshall, BR; Nguyen, NH; Visaltanachoti, NEstimating long-term expected returns as accurately as possible is of critical importance. Researchers typically base their estimates on yield and growth, valuation, or a combined yield, growth, and valuation (“three-component”) framework. We run a horse race of the abilities of different frameworks and input proxies within each framework to estimate 10- and 20-year out-of-sample returns. The three-component model based on the TRCAPE valuation proxy outperforms estimates based on historical mean benchmark returns, with mean square error improvements exceeding 30%. Using this approach in asset allocation decisions results in an improvement in Sharpe ratios of more than 50%.
- ItemSpillover Between Investor Sentiment and Volatility: The Role of Social Media(Elsevier, 2024-10-05) Yang, Ni; Fernandez-Perez, Adrian; Indriawan, IvanWe examine the spillover effects between social media sentiments and market-implied volatilities among stock, bond, foreign exchange, and commodity markets. We find that information mainly spillovers from volatility to sentiment indices, with the VIX being the most significant net transmitter. Within each asset class, there is a more pronounced spillover from volatility to sentiment compared to the reverse, implying that a significant portion of investor sentiment is volatility-driven. This relationship intensifies in turbulent economic periods, such as during the Global Financial Crisis, Brexit, the US-China trade war, and the COVID-19 pandemic. Our analysis also reveals that sentiment indices can transition from net receivers to net transmitters of shocks during turbulent periods. This can be explained by the echo chamber effect, where social media echo prevailing news signals, and some investors interpret repeated signals as genuinely new information.
- ItemOil Volatility-of-Volatility and Tail Risk of Commodities(Auckland Centre for Financial Research., 2024-10-08) Xu, Yahua; Tourani-Rad, Alireza; Roh, Tai-YongWe examine the information content of oil volatility-of-volatility (VOV), constructed from the past 1-month OVX (implied volatility in crude oil market), on the expected tail risk of commodities. Specifically, we find oil VOV predicts 1-step-ahead tail risks of Energy, Precious Metals, Agriculture, Livestock sectors and the Aggregate Commodity sector (GSCI) for both in-sample and out-of-sample. Our results indicate the important role of crude oil in overall commodity markets by incorporating forward-looking information of OVX. Our findings are robust and complement the strand of literature about the leading role of crude oil in commodity markets.
- ItemThe Role of Inventory in Firm Resilience to the Covid‐19 Pandemic(Wiley, 2024-09-13) Dodd, Olga; Liao, ShushuWe study the role of inventory in corporate resilience to Covid-19 in 2020, which triggered exogenous shocks to consumer demand, commodity prices and supply chains. Unexpected drops in consumer demand and commodity prices increase the costs of inventory. Conversely, inventory holdings can buffer against supply disruptions. Empirically, US firms with higher inventory experienced more negative stock market responses early in the crisis due to falling consumer demand. However, since May 2020, inventory has become valuable as a hedge against supply disruptions, improving firm performance. During Covid-19, unlike other crises, inventory played a unique role as a hedge against supply disruptions.
- ItemInequality Aversion Predicts Support for Public and Private Redistribution(Proceedings of the National Academy of Sciences, 2024-09-17) Epper, TF; Fehr, E; Kreiner, CT; Leth-Petersen, S; Olufsen, IS; Skov, PERising inequality has brought redistribution back on the political agenda. In theory, inequality aversion drives people's support for redistribution. People can dislike both advantageous inequality (comparison relative to those worse off) and disadvantageous inequality (comparison relative to those better off). Existing experimental evidence reveals substantial variation across people in these preferences. However, evidence is scarce on the broader role of these two distinct forms of inequality aversion for redistribution in society. We provide evidence by exploiting a unique combination of data. We use an incentivized experiment to measure inequality aversion in a large population sample (≈9,000 among 20- to 64-y-old Danes). We link the elicited inequality aversion to survey information on individuals' support for public redistribution (policies that reduce income differences) and administrative records revealing their private redistribution (real-life donations to charity). In addition, the link to administrative data enables us to include a large battery of controls in the empirical analysis. Theory predicts that support for public redistribution increases with both types of inequality aversion, while private redistribution should increase with advantageous inequality aversion, but decrease with disadvantageous inequality aversion. A strong dislike for disadvantageous inequality makes people willing to sacrifice own income to reduce the income of people who are better off, thereby reducing the distance to people with more income than themselves. Public redistribution schemes achieve this but private donations to charity do not. Our empirical results provide strong support for these predictions and with quantitatively large effects compared to other predictors.