Spatial Variability of the ‘Airbnb Effect’: A Spatially Explicit Analysis of Airbnb’s Impact on Housing Prices in Sydney

Over the last decade, the emergence and significant growth of home-sharing platforms, such as Airbnb, has coincided with rising housing unaffordability in many global cities. It is in this context that we look to empirically assess the impact of Airbnb on housing prices in Sydney—one of the least affordable cities in the world. Employing a hedonic property valuation model, our results indicate that Airbnb’s overall effect is positive. A 1% increase in Airbnb density is associated with approximately a 2% increase in property sales price. However, recognizing that Airbnb’s effect is geographically uneven and given the fragmented nature of Sydney’s housing market, we also employ a GWR to account for the spatial variation in Airbnb activity. The findings confirm that Airbnb’s influence on housing prices is varied across the city. Sydney’s northern beaches and parts of western Sydney experience a statistically significant value uplift attributable to Airbnb activity. However, traditional tourist locations focused around Sydney’s CBD and the eastern suburbs experience insignificant or negative property price impacts. The results highlight the need for policymakers to consider local Airbnb and housing market contexts when deciding the appropriate level and design of Airbnb regulation.

Spatial Variability of the ‘Airbnb Effect’: A Spatially Explicit Analysis of Airbnb's impact on Housing Prices in Sydney

Over the last decade, the emergence and significant growth of home sharing platforms such as Airbnb has coincided with rising housing unaffordability in many global cities. It is in this context that we look to empirically assess the impact of Airbnb on housing prices in Sydney - one of the least affordable cities in the world. Employing a hedonic property valuation model, our results indicate that Airbnb’s overall effect is positive. A 1% increase in Airbnb density is associated with approximately a 2% increase in property sales price. However, recognising that Airbnb’s effect is geographically uneven and given the fragmented nature of Sydney’s housing market, we also employ a GWR to account for the spatial variation in Airbnb activity. The findings confirm that Airbnb’s influence on housing prices is varied across the city. Sydney’s northern beaches and parts of western Sydney experience a statistically significant value uplift attributable to Airbnb activity. However, traditional tourist locations focused around Sydney’s CBD and the eastern suburbs experience insignificant or negative property price impacts. The results highlight the need for policymakers to consider local Airbnb and housing market contexts when deciding the appropriate level and design of Airbnb regulation.

EXPRESS: Measuring the real-time stock market impact of firm-generated content

Firms increasingly follow an ‘always on’ philosophy, producing multiple pieces of firm-generated content (FGC) throughout the day. Current methodologies used in marketing are unsuited to unbiasedly capturing the impact of FGC disseminated intermittently throughout the day in stock markets characterized by ultra-high frequency trading. They also neither distinguish between the permanent (i.e. long-term) and temporary (i.e. short-term) price impacts nor identify FGC attributes capable of generating these price impacts. In this study, the authors define price impact as the impact on the variance of stock price. Employing a market microstructure approach to exploit the variance of high frequency changes in stock price the authors estimate the permanent and temporary price impacts of the firm-generated Twitter content of S&P 500 IT firms. The authors find that firm-generated tweets induce both permanent and temporary price impacts, which are linked to tweet attributes; valence and subject matter. Tweets reflecting only valence or subject matter concerning consumer or competitor orientation result in temporary price impacts, while those embodying both attributes generate permanent price impact; negative valence tweets about competitors generate the largest permanent price impacts. Building on these findings, the authors offer suggestions to marketing managers on the design of intraday FGC.

Analysing the behavioural finance impact of 'fake news' phenomena on financial markets: a representative agent model and empirical validation

This paper proposes an original behavioural finance representative agent model, to explain how fake news’ empirical price impacts can persist in finance despite contradicting the efficient-market hypothesis. The model reconciles empirically-observed price overreactions to fake news with empirically-observed price underreactions to real news, and predicts a novel secondary impact of fake news: that fake news in a security amplifies underreactions to subsequent real news for the security. Evaluating the model against a large-sample event study of the 2019 Chinese ADR Delisting Threat fake news and debunking event, this paper finds strong qualitative validation for its model’s dynamics and predictions.

Market Fragmentation

We model a simple market setting in which fragmentation of trade of the same asset across multiple exchanges improves allocative efficiency. Fragmentation reduces the inhibiting effect of price-impact avoidance on order submission. Although fragmentation reduces market depth on each exchange, it also isolates cross-exchange price impacts, leading to more aggressive overall order submission and better rebalancing of unwanted positions across traders. Fragmentation also has implications for the extent to which prices reveal traders’ private information. While a given exchange price is less informative in more fragmented markets, all exchange prices taken together are more informative. (JEL D47, D82, G14)

Insect-based protein feed: from fork to farm

Numerous studies show that insects are efficient in converting organic waste into proteins and fats, which makes them an interesting alternative source of feed. Moreover, since around one-third of global food produced for human consumption is lost or wasted, the production of insect-based meals from food waste is considered a sustainable alternative to other protein sources. This paper introduces a quantitative framework able to analyse the economic implications of developing a large-scale insect-based meal industry worldwide, which would require important regulatory changes. Our calculations, based on findings from the literature, suggest that almost 1.4 billion tonnes of food, that could potentially be used as insect feed, went to waste at the world level in 2018, a figure that is projected to rise to 2 billion tonnes by 2030. Results show that the use of food waste for insect meal and oil production would have important downward price impacts on meals and oils (fish- and plant-based), reducing feed costs and stimulating global aquaculture and livestock production, reducing total land use for agriculture production and lead to a lower dependence on protein imports.

Loss sensitive investors and positively biased analysts in Hong Kong stock market

The Hong Kong stock market is known to be highly volatile. Professional investors have a strong demand for timely information because of the infrequent nature of Hong Kong analysts’ interim reports (Cheng et al., 2003). Our paper provides a comprehensive study of investor reactions to analysts’ recommendations in the Hong Kong stock market from 2009 to 2014 under different sentiment scenarios. We find that analysts’ recommendation upgrades and downgrades deliver significant information to the Hong Kong stock market. However, analysts’ initiation coverages convey little information and bring about limited impact to the stock market. In addition, analysts’ upgrades and downgrades result in significant differential price impacts in bullish and the bearish phases.

Meeting Challenges in Forestry: Improving Performance and Competitiveness

Improving the efficiency of the forestry sector will have an important impact on our possibility to attain long-term sustainability and mitigate climate change. In this study, attainable, and sustainable, efficiency improvements in the harvesting of forest products are analyzed using Data Envelopment Analysis (DEA). The price impacts of the efficient harvesting volumes are evaluated in a second step using a spatial forest sector model. The results indicate that the harvested volumes of forest products, both for the industry and energy sectors, can be significantly increased if a more efficient forest management is adopted. This supply-side effect will also result in general price decreases for sawlogs, pulpwood, fuelwood and harvesting residues. However, in certain counties, and for specific forest products, the estimated decreasing price effect from a more efficient forest management cannot fully offset the increasing price effect of the energy sector expanding its use of forest products. More forest biomass enters the market, which is needed in the transition towards a bioeconomy, and the increased availability of forest biomass will restrict the price effect making investments in the bioeconomy more likely to be profitable.