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

2022 ◽  
Vol 11 (1) ◽  
pp. 65
Author(s):  
William Thomas Thackway ◽  
Matthew Kok Ming Ng ◽  
Chyi-Lin Lee ◽  
Vivien Shi ◽  
Christopher James Pettit

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.

2021 ◽  
Author(s):  
William Thackway ◽  
Matthew Kok Ming Ng ◽  
Chyi Lin Lee ◽  
Vivien Shi ◽  
Christopher Pettit

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.


ABSTRACT The ecosystem services provided by wetlands can be direct or indirect. The direct services can be mostly valued through market prices, but the indirect service like aesthetic beauty and its impact on property prices surrounding the natural resource cannot be directly measured. To single out the economic effect of particular amenity which influenced the land property prices, the advanced valuation technique Hedonic property pricing was most popularly used. In this study, it was attempted to assess using the hedonic property pricing technique, the impact of the presence of the freshwater body, the Vellayani Lake on land property prices surrounding it. The results revealed that the marginal implicit price of getting one cent of land with lake view evaluated at mean property price of Rs. 2,44250 was Rs.79171. The total aesthetic value of land with the scenic beauty of the lake was Rs. 275.92 crores.


2015 ◽  
Vol 26 (1) ◽  
pp. 79-93 ◽  
Author(s):  
Richard F. Bieker ◽  
Yoonkyung Yuh

The objectives of this study were to evaluate the extent to which homeownership contributed to household financial strain as measured by loan delinquency after the onset of the recent housing market crash, and to examine if the impact of homeownership on household financial strain differed for Black and White households. Using data from the 2010 Survey of Consumer Finances, we found that, after controlling for other factors, a household's housing preferences had a potential effect on the likelihood of experiencing financial strain following the collapse of residential housing prices. In addition, Black homeowners were more likely to have experienced financial strain following the housing collapse than were White homeowners, regardless of the time period in which the home was purchased. The implications of the findings for public policy, personal financial planning and education, and further research are presented.


2021 ◽  
Author(s):  
Elfrida Shehu ◽  
Klodian Skrame

<p>Albania, the small country in the western Balkan, is a disaster-prone country. It ranks as one of the countries in the world with the highest economic risk from natural hazards events. During the past several decades, in average, Albania has been hit by about one major geological event per year. The impact of disasters in Albania are significantly compounded by a relatively high degree of poverty, lack of infrastructure maintenance, unsafe building and land use practices, linked to rapid urbanization, exploitation of natural resources (overgrazing of pasture, overexploitation of forests and riverbeds, etc.) as well as some other consequences of the transition from a centralized to an open marked economy.</p><p>From a geological point of view, Albania is a young and very dynamic territory and is very vulnerable to the geological and hydro-geological hazards as: earthquakes, landslides, flooding, torrential rains, river erosion, coastal erosion and avalanches that cover almost the entire territory. Due to these conditions its average annual losses count for about 2.5% of its GDP.</p><p>The Durrës earthquakes of 2019 had a huge impact on the Albanian economy. The city of Durrës, Thumanë, Tirana, Vora, Shijak and their villages suffered considerable damage after the earthquakes of September 21<sup>st</sup>, 2019 of Mw 5.4 and November 26<sup>th</sup>, 2019 of Mw 6.2. The main event of the <sup>26th</sup> November caused the deaths of 51 persons and the damaging of hundreds of buildings. The degree of damages produced by these earthquakes has been, in some cases, significantly enhanced by the characteristics of the earthquake ground motion affected by the local subsurface soil structure and the quality of the constructions. The situations during and after the seismic events highlight the indispensable need of the seismic microzonation studies for the entire Albanian territory and emergency plans for the main cities of the country.</p><p>This paper shows the impact of the earthquake event on the housing market value by treating the data collected in the city of Durrës for the period December 2019 - September2020.</p><p>The main goal of the paper is to correlate the obtained results with the engineering-geological and geophysical conditions of the city of Durrёs and the seismic vulnerability of the building.</p><p>The findings of this study can be considered as a first step for in-depth studies aiming to calculate the impact of seismic risk and the change in the risk perception on the housing prices.</p>


2014 ◽  
Vol 7 (1) ◽  
pp. 4-28 ◽  
Author(s):  
Paloma Taltavull de la Paz

Purpose – The paper develops a housing model equation for Spain and selected regions to estimate new supply elasticity. The aim of the paper is to assess the role of housing supply on price evolution and explain the fall in housing starts since the start of the credit crunch. Design/methodology/approach – The paper uses a pooled EGLS specification controlling for the presence of cross-section heteroskedasticity. Fixed effect estimators are calculated to capture regional heterogeneity. The model uses secondary data (quarterly) for 17 Spanish regions over the period 1990-2012. A recursive procedure is applied to estimate model parameters starting with a baseline model (1990-1999) and successively adding one-year time information. Elasticities, as well as explanatory power from models, are reported and jointly analyzed. Elasticity is interpreted as the extent to which market mechanisms drive developer responses. Findings – Elasticities of new supply are shown to be very stable during all periods but characterized by differences in response at a regional level. Elasticity ranges from 0.8 to 1.3 across regions. The model reports a non-market-oriented mechanism that guides building decisions. The credit crunch and debt crisis have had a double negative effect capturing the cumulative effect of exogenous shocks. Research limitations/implications – Elastic responses restrained the effects of over-pricing in the period of strong demand pressures in the early 2000s. Changes in elasticity parameters over time suggest that long-term elasticity in housing supply depends on the specific region analyzed. The results show that the credit crunch shock had varying degrees of severity in Spanish regions, dramatically reducing house-building because of the high sensitivity to changes in prices. Practical implications – Estimated elasticity may be used to forecast responses to changes in housing prices. The results add to the understanding of the equilibrium mechanism in the housing market across regions. Originality/value – This is the first article that analyses housing supply, calculates supply elasticities and measures the impact of the credit crunch on the housing market from the supply side in Spain. The paper adds evidence to the debate concerning the equilibrium mechanism in the housing market.


2019 ◽  
Vol 22 (2) ◽  
pp. 197-229
Author(s):  
Hui An ◽  
◽  
Qianmiao Zou ◽  
Ying Zhang ◽  
◽  
...  

In recent years, China has uniquely implemented various policies to control housing prices, particularly its property- purchasing limitation policy. This research proposes a vector autoregression (VAR) model with likelihood-ratio (LR) tests to examine the effects of such a policy on housing prices at the national, provincial and city levels in China, with the use of monthly data from 2002 to 2013. The results show that at the national level, the effect of the policy is very significant, and the impact on housing prices is far greater than monetary and credit policies. However, the policy is not applicable at the provincial level. The policy has a significant role at the city level in first-tier cities, but no significant effect in second- tier cities. Overall, property-purchasing limitations inhibit the growth of housing prices to some extent, and the effects show strong regional characteristics, especially at the city level. Policymakers should therefore take into account regional characteristics in the formulation and implementation of a property-purchasing limitation policy.


2017 ◽  
Vol 20 (3) ◽  
pp. 375-396
Author(s):  
Gary Wai Chung Wong ◽  
◽  
Lok Sang Ho ◽  

This paper builds on the literature that shows policy often plays a key role in housing cycles. Using the cointegration approach which focuses on the supply and demand dynamics of the housing market, and with explicit consideration of housing price expectations proxied by the price-earning ratio in financial markets, this paper identifies two cointegrating relations: a long run demand-side relation that involves housing property price, interest rate, price expectation and income; and a supply-side relation that involves private housing completion, property price, interest rate, and building and land costs. Based on Hong Kong data from 1990 a£á¡§ 2012, which covers big cycles in the housing market, this paper suggests that policies to augment or restrain housing supply in the attempt to stabilize housing prices have been counterproductive.


Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 879
Author(s):  
Leeyoung Kim ◽  
Wonseok Seo

This study examined the price spillover effect of housing submarkets in cities in the Seoul metropolitan area in South Korea by using the Granger causality test and vector autoregressive model (VAR). We found that housing prices showed a higher spillover effect within regions with similar housing market characteristics. Additionally, the spatial spillover of housing prices revealed a difference between sales price and jeonse price. The spillover of jeonse price was characterized by mutual influence among neighboring cities, while that of sales price was characterized by the influence being transferred in one direction hierarchically. Furthermore, the effects of housing price indicated a slight difference between sales price and jeonse price. Although jeonse price was mainly affected by a neighboring area (geographic boundary), sales price was more influenced by the city with the highest housing prices. Lastly, the housing price spillover tended to be expansive around the city with the highest price. These results suggest that housing price policies targeting specific regions or areas in Korea must be differentiated according to the type of occupancy (jeonse or sales), and it is essential to consider the externalities when promoting policies in the housing market wherein externalities may be significant.


2020 ◽  
Vol 13 (6) ◽  
pp. 112
Author(s):  
Mats Wilhelmsson

The main objective is to answer the question: What role does the housing market play for the transmission mechanism and (in particular) is the impact constant over time? The research question also includes analyzing the importance of the housing market for the transmission mechanism. We estimate an eight-variable structural vector autoregression (SVAR) model of the Swedish economy over the period 1993 and 2018 using quarterly data, covering both the internet bubble in 2000 and the financial crises in 2008. The results indicate that interest rates have both a direct effect on housing prices and an indirect impact through the bank lending channel. Over time, the traditional interest rate channel importance has been stable. On the other hand, the role of the bank lending channel has increased over time. Household debt has increased substantially in Sweden and elsewhere. That means that the interest rate sensitivity in society has increased. Based on the results, it is possible to evaluate and forecast potential house price effects (both direct and indirect) when the interest rate changes.


2018 ◽  
pp. 1-18 ◽  
Author(s):  
XIAO-CUI YIN ◽  
CHI-WEI SU ◽  
RAN TAO

This paper examines whether broader money supply (M2) and interest rate as two monetary policy tools may have differently affected housing prices in China. Empirical results show that there is a co-movement between housing prices and M2 in the short run and it becomes more pronounced after 2006 in the medium run. In addition, generally M2 positively affects housing prices. This supports the asset price channel which indicates that an easing monetary policy offers ample liquidity and results in raising the housing prices. The excess liquidity after 2008 spread to housing market, resulting in too much money chasing relatively few assets and triggering a surge in housing prices. On the other hand, we observe that co-movement between housing prices and interest rate is not very evident in most time. Moreover, we find that interest rate has a positive effect on housing prices which is not consistent with the user cost approach and indicates that a contracting monetary policy is not effective in curbing housing market. Not completely liberalized interest rate system and the high return on housing investments reduce the impact of interest rate on housing prices. These findings indicate that money supply is more effective than interest rate as channel to control the housing prices in China. The results are helpful for the scientific formulation of monetary policy for reasonable regulation of the market.


Sign in / Sign up

Export Citation Format

Share Document