The impact of COVID-19 on housing price: Evidence from China

Online listing data and their interaction with market dynamics: evidence from Singapore during COVID-19

With the emergence of Property Technology, online listing data have drawn increasing interest in the field of real estate-related big data research. Scraped from the online platforms for property search and marketing, these data reflect real-time information on housing supply and potential demand before actual transaction data are released. This paper analyzes the interactions between the keywords of online home listings and actual market dynamics. To do so, we link the listing data from the major online platform in Singapore with the universal transaction data of resale public housing. We consider the COVID-19 outbreak as a natural shock that brought a significant change to work modes and mobility and, in turn, consumer preference changes for home purchases. Using the Difference-in-Difference approach, we first find that housing units with a higher floor level and more rooms have experienced a significant increase in transaction prices while close proximity to public transportation and the central business district (CBD) led to a reduction in the price premium after COVID-19. Our text analysis results, using the natural language processing, suggest that the online listing keywords have consistently captured these trends and provide qualitative insights (e.g. view becoming increasingly popular) that could not be uncovered from the conventional database. Relevant keywords reveal trends earlier than transaction-based data, or at least in a timely manner. We demonstrate that big data analytics could effectively be applied to emerging social science research such as online listing research and provide useful information to forecast future market trends and household demand.

COVID-19 and housing prices: evidence from U.S. county-level data

This paper investigates the effects of coronavirus disease 2019 (COVID-19) on housing prices at the U.S. county level. The effects of COVID-19 cases on housing prices are formally investigated by using a two-way fixed effects panel regression, where county-specific factors, time-specific factors, and mobility measures of individuals are controlled for. The benchmark results show evidence for negative and significant effects of COVID-19 cases on housing prices, robust to the consideration of several permutation tests, where the negative effects are more evident in counties with higher poverty rates. Exclusion tests further suggest that U.S. counties in the state of California or the month of May 2020 are more responsible for the empirical results, although the results based on other counties and months are still in line with the benchmark results.

Do COVID-19 pandemic-related policy shocks flatten the bid-rent curve? Evidence from real estate markets in Shanghai

The COVID-19 pandemic has drastically affected the socioeconomic activities and peoples' daily life, resulting in a change in locational preferences in the real estate markets. Although enormous efforts have been devoted to examining the housing price impacts of the COVID-19 pandemic, little is known about the responses of the real estate markets to the evolving pandemic control measures. This study investigates the price gradient effects of various pandemic-related policy shocks using a hedonic price model on the district-level property transaction data in Shanghai, China over a 48-month period from 2018 to 2021. We found that these shocks have significantly altered the bid-rent curves. The price gradient for residential property units decreased in absolute value to - 0.433 after Wuhan's lockdown, demonstrating peoples' preferences to avoid the high infection risks in districts closer to the city center. However, in the post-reopening and post-vaccine periods, the price gradient increased to - 0.463 and - 0.486, respectively, implying rational expectations of a recovering real estate market for the low infection and mortality rates. In addition, we discovered that Wuhan's lockdown has steepened the price gradient for commercial property units, suggesting a decline in business volumes and an increase in operating costs in the low-density districts imposed by the strict pandemic control measures. This study contributes to the empirical literature on the price gradient effects of the COVID-19 pandemic by extending the study period to the post-vaccine era.

JUE Insight: COVID-19 and household preference for urban density in China

This paper investigates the effect of COVID-19 on both housing prices and housing price gradients in China using transaction level data from 60 Chinese cities. After using a difference-in-differences (DID) specification to disentangle the confounding effects of China's annual Spring Festival, we find that housing prices decreased by two percent immediately after the COVID-19 outbreak but gradually recovered by September 2020. Moreover, our findings suggest that COVID-19 flattens the horizontal housing price gradient, reduces the price premium for living in tall buildings, and changes the vertical gradient within residential buildings. This is likely explained by the changing household preferences towards low-density areas associated with lower infection risk.

Effect of COVID-19 lockdowns on city-center and suburban housing markets: Evidence from Hangzhou, China

In 2020, governments worldwide enforced lockdowns to contain the spread of COVID-19, severely impeding aspects of daily life such as work, school, and tourism. Consequently, numerous economic activities were affected. Before the COVID-19 outbreak, city-center housing markets in areas surrounding popular tourist attractions performed better than did suburban housing markets because of the output of the tourism industry. This study examines the changes in the performance of city-center and suburban housing markets in regions with popular tourist attractions after the lockdown. Specifically, the dynamics of city-center and suburban housing markets in Hangzhou, where West Lake is located, and the changes in the information transfer between these housing markets after the lockdown are explored. Transaction data from January 1, 2019 to September 30, 2020 are used to perform analysis, in which adjusted housing prices and asking prices are employed to measure market performance and sellers' pricing strategies, and transaction volume and time on the market are used to measure market liquidity and transaction frequency. The results reveal that the effects of lockdowns differ between city-center and suburban housing markets. After the lockdown, a substantial structural change is observed in the suburban housing market; the volatility risk of housing prices decreases substantially, causing an increase in transaction premiums. Housing prices and transaction volume increase in the city-center housing market after the lockdown; this is possibly because of the influence from the overall housing market booms. In addition, because sellers raise their asking prices and the transaction time is extended, the sellers in the city-center housing market are particularly influenced by the disposition effect. This leads to a reversal in the lead-lag relationship between the city center and suburban housing markets in terms of informativeness. Specifically, before the lockdown, the city-center market transfers information to the suburban market, but after the lockdown, the suburban market transfers information to the city-center market. The COVID-19 pandemic has changed the world in many aspects; this paper finds that it will also change the development pattern of the real estate market in different locations.

The private rental housing market before and during the COVID-19 pandemic: A submarket analysis in Cracow, Poland

How the COVID-19 pandemic has altered the segmentation of residential rental markets is largely unknown. We therefore assessed rental housing submarkets before and during the pandemic in Cracow, Poland. We used geographically and temporally weighted regression to investigate the marginal prices of housing attributes over space-time. The marginal prices were further reduced to a few principal components per time period and spatially clustered to identify housing submarkets. Finally, we applied the adjusted Rand index to evaluate the spatiotemporal stability of the housing submarkets. The results revealed that the pandemic outbreak significantly lowered rents and modified the relevance of some housing characteristics for rental prices. Proximity to the university was no longer among the residential amenities during the pandemic. Similarly, the virus outbreak diminished the effect of a housing unit's proximity to the city center. The market partitioning showed that the number of Cracow's residential rental submarkets increased significantly as a result of the COVID-19 pandemic, as it enhanced the spatial variation in the marginal prices of covariates. Our findings suggest that the emergence of the coronavirus reshaped the residential rental market in three ways: Rents were decreased, the underlying rental price-determining factors changed, and the spatiotemporal submarket structure was altered.

COVID-19 effects on property markets: The pandemic decreases the implicit price of metro accessibility

The metro (or underground railways) has become a backbone in the transit systems of many cities. It has numerous externalities, such as ameliorating traffic congestion and enhancing nearby property prices. Previous studies extensively focused on the relationship between metro accessibility and property prices and obtained various interesting findings and enriched practical implications. However, this relationship in the era of the coronavirus disease 2019 (COVID-19) and other epidemic shocks has not been investigated. Based on a unique property transaction dataset (including tens of thousands of transactions stretching from 2018 to 2020) in Chengdu, China, this study develops a battery of hedonic pricing models and difference-in-differences models to decipher the time-varying relationship between metro accessibility and residential property prices. The results show that the implicit price of metro accessibility modestly decreases in COVID-19, which can be explained by the declining role of the metro. In other words, the price gap between proximate and distant properties is narrowed, and the property price gradient is flattened. Specifically, the price elasticity of distance to the metro is − 0.024 before COVID-19, but it turns to − 0.018 during the pandemic. The relative price of properties within 500 m from metro stations to those farther away (500 m − 3 km) decreases by 15.4% during the pandemic. Additionally, COVID-19 does not jeopardize property prices in Chengdu. Furthermore, the decrease in metro access premiums may be short-lived and only persisted for several months or years. The plausibility and robustness of the core findings have been confirmed through alternative treatment groups, alternative model specifications, and placebo tests.

Conservative Media Use and COVID-19 Related Behavior: The Moderating Role of Media Literacy Variables

At the start of the COVID-19 pandemic, there was no vaccine to cure or slow its impact due to the novelty of the virus, nor were there were any other standardized measures to handle its spread. Yet, despite the detrimental consequences of the pandemic and its impact on people’s lives, the behavior of individuals to combat the pandemic was not necessarily consistent with official guidelines. To make things worse, the pandemic was highly politicized in countries such as the U.S. With a help of a national survey from the U.S., we examine the associations between media literacy variables and willingness to perform recommended COVID-19 related health behavior. Moreover, we also examine the moderating role of conservative media use in this relationship. Our findings show that conservative media use was negatively associated with these protective behaviors, and that both media literacy variables were positively related with willingness to perform recommended COVID-19 related health behavior. Our results show that media literacy can mitigate some of the impact of conservative media use on individuals. Our findings help understand the complexity of protective behavior against the virus during a highly politicized pandemic.

Impact of the COVID-19 pandemic on the housing market at the epicenter of the outbreak in China

The outbreak of the COVID-19 in January 2020 has had a profound impact on the global economy, so it is important to study the impact of the pandemic on the housing market. To investigate the impact of the pandemic on the housing market and the response of the housing market, this paper first uses the hedonic price model to compile the second-hand housing price index in Wuhan and its neighboring capital cities and then uses the difference-in-difference (DID) model to conduct a comprehensive study on new commercial housing and second-hand housing market. In addition, this paper also uses the VAR model to explore the housing market’s response to the epidemic situation. The results show that the negative impact of the pandemic on the housing market is mainly reflected in the volume and area of housing transactions, with little impact on housing prices. Second, the reported cases of COVID-19 have a negative impact on the housing market in the short term, which gradually weakens with time and disappears after three weeks. This paper’s findings indicate that the epidemic’s impact on the housing market is mainly due to the real estate enterprises stopping selling houses and local governments implementing home quarantine measures, which affect normal housing transactions. However, the COVID-19 pandemic did not greatly negatively impact consumers’ demand and confidence in buying houses, so the house prices remained stable overall.

COVID-19 vaccines and global stock markets

Global stock markets react positively when different phases of human clinical trials on COVID-19 vaccines begin. The average abnormal stock return on the first day of the trials is both statistically and economically significant at 8.08 basis points. The increase in the average abnormal stock return is threefold higher for leading vaccine candidates. The positive reaction is more pronounced upon the start of phase III trials, and it is also stronger for vaccine candidates developed by the U.S. and China.

COVID-19 vaccines and global stock markets

Global stock markets react positively when different phases of human clinical trials on COVID-19 vaccines begin. The average abnormal stock return on the first day of the trials is both statistically and economically significant at 8.08 basis points. The increase in the average abnormal stock return is threefold higher for leading vaccine candidates. The positive reaction is more pronounced upon the start of phase III trials, and it is also stronger for vaccine candidates developed by the U.S. and China.

COVID-19 and the Economy: Summary of research and future directions

This article presents a literature review of the 81 articles accepted in the Finance Research Letters Special Issue titled "COVID-19 and the Economy". The articles are classified into five broad areas (investments and asset pricing, the macroeconomy and banking, commodities, corporate finance, and other topics). We summarize the key findings of the articles by area and highlight the influence of the articles as measured by Google Scholar citations. We conclude by presenting directions for future research.

PROPERTY MANAGEMENT ENABLED BY ARTIFICIAL INTELLIGENCE POST COVID-19: AN EXPLORATORY REVIEW AND FUTURE PROPOSITIONS

The Covid-19 pandemic outbreak across the globe has disrupted human life and industry. The pandemic has affected every sector, with the real estate sector facing particular challenges. During the pandemic, property management became a crucial task and property managers were challenged to control risks and disruptions faced by their organizations. Recent innovative technologies, including artificial intelligence (AI), have supported many sectors through sudden disruptions; this study was performed to examine the role of AI in the real estate and property management (PM) sectors. For this purpose, a systematic literature review was conducted using structural topic modeling and bibliometric analysis. Using appropriate keywords, the researchers found 175 articles on AI and PM research from 1980 to 2021 in the SCOPUS database. A bibliometric analysis was performed to identify research trends. Structural topic modelling (STM) identified ten emerging thematic topics in AI and PM. A comprehensive framework is proposed, and future research directions discussed.

Spatial Analysis and Modeling of the Housing Value Changes in the U.S. during the COVID-19 Pandemic

COVID-19 has affected almost all sectors of the economy, including the real estate markets across different countries in the world. A rich body of literature has emerged in analyzing real estate market trends and revealing important information. However, few studies have used a spatial perspective to investigate the impact of COVID-19 on property values. The main purposes of this study are as follows: (1) to explore the spatial distribution and spatial patterns of housing price changes during the COVID-19 pandemic crisis in the U.S. real estate market and (2) to model the spatially nonstationary relationships between the housing price change and COVID-19 characteristics. We find that housing price changes differ across space and appear associated with the spatial distribution of the COVID-19 case rates. The housing market volatility is amplified by the uneven distribution of some socioeconomic factors. The spatially uneven housing price changes may bring an uneven spillover effect to the rest of the economy and lead to divergence in economic growth across different areas.

Sustainability Development: Assessment of Selected Indicators of Sustainable Energy Development in Poland and in Selected EU Member States Prior to COVID-19 and Following the Third Wave of COVID-19

An important question in the literature on climate change and sustainable development is the relationship between countries’ economic growth, household electricity consumption and greenhouse gas emissions. Despite the ongoing COVID-19 pandemic and related economic restrictions, sustainable economic growth remains at the forefront of the global development agenda. However, given the strong relationship between the ever increasing electricity consumption and greenhouse gas CO2 emissions, an increasing number of scientists have been questioning the feasibility of the planned emission reduction. In my research, I strove to determine whether there exists a relationship between the change in the structure of electricity consumption of households in selected EU Member States (15 countries), the impact of innovation, changes in electricity prices and economic growth, and CO2 emissions in 2007–2019, prior to the outbreak of the COVID-19 pandemic, and following its third wave (2021). The aim of the article is to propose a synthetic index to assess the degree of sustainable energy development (SISED) in selected EU countries. Multiobjective decision analysis (MODA) was applied in order to assess the sustainable energy development of the selected European countries. Research findings may contribute to both literature and practice if they are applied by individual EU countries in the process of formulating directions aimed at achieving sustainable energy development.

The Third Wave of COVID-19 versus the Residential Preferences in Poland: An Assessment of Economic Factors and Psychological Determinants

The COVID-19 pandemic triggered a reflection on our need for contact with nature. It was the result of suddenly imposed limitations of the everyday functioning of many people and confining them to the space of their own house or apartment. This paper presents the results of a study on the preferences of Polish city dwellers in terms of their need for contact with nature at their place of residence before the COVID-19 outbreak and after the third wave of the COVID-19 pandemic. The purpose of the study was to identify any relationship between preferences regarding access to nature at the place of residence prior to and during the third wave of the COVID-19 pandemic and variables such as gender, age, background, and distance between the place of residence and any natural or urban green spaces. An online survey was used to examine urban residents’ need for access to nature. Significant gender differences in preferences, both prior to and during the pandemic, were found. Preferences also varied depending on the distance between the place of residence and natural and urban green spaces and depending on the origin of the interviewee (urban or rural). The origin was found to have a significant impact on preferences. The need for contact with nature at the place of residence, both before and after the pandemic, was found to be greater among respondents from rural areas.

Food and healthcare accessibility during COVID-19 pandemic

The pervasive effects of the novel coronavirus (COVID-19) have put the world to test. Its effects permeate all facets of life including healthcare services and food supplies. However, most empirical studies failed to investigate its effects on the prices of food and healthcare services, which by all standards, are essential commodities. On this background, this study evaluates the impact of COVID-19 reported cases and lockdown stringency measures on the food and healthcare prices in the six (6) worst-affected countries. For empirical purposes, daily prices of food and healthcare services between 22nd January and 31st December 2020 were regressed against daily cases of COVID-19 and lockdown stringency measures within the dynamic autoregressive distributed lag procedure. Empirical evidences reveal that prices of healthcare and food are cointegrated with COVID-19 cases and lockdown measures in all the selected countries except Italy. Equally, healthcare and food prices reinforced itself in the long-run in the US, the UK and France. Furthermore, COVID-19 cases lead to significant increases in food and healthcare prices in the US, whereas, food and healthcare prices in France and UK declined significantly as COVID-19 cases mount. Conversely, food and healthcare prices declined significantly in the US and soar in France and the UK in reactions to COVID-19 new cases. Likewise, government stringency measures and containment health measures contributed significantly to healthcare and food price hike in the US and France respectively. Meanwhile, healthcare and food prices in the other selected countries remained unaffected even as the pandemic ravages. Following this empirical discoveries, relevant policy guidelines have been communicated.

Did the COVID-19 Pandemic Crisis Affect Housing Prices Evenly in the U.S.?

While it is well-known that housing prices generally increased in the United States (U.S.) during the COVID-19 pandemic crisis, to the best of our knowledge, there has been no research conducted to understand the spatial patterns and heterogeneity of housing price changes in the U.S. real estate market during the crisis. There has been less attention on the consequences of this pandemic, in terms of the spatial distribution of housing price changes in the U.S. The objective of this study was to explore the spatial patterns and heterogeneous distribution of housing price change rates across different areas of the U.S. real estate market during the COVID-19 pandemic. We calculated the global Moran’s I, Anselin’s local Moran’s I, and Getis-Ord’s Gi∗ statistics of the housing price change rates in 2856 U.S. counties. The following two major findings were obtained: (1) The influence of the COVID-19 pandemic crisis on housing price change varied across space in the U.S. The patterns not only differed from metropolitan areas to rural areas, but also varied from one metropolitan area to another. (2) It seems that COVID-19 made Americans more cautious about buying property in densely populated urban downtowns that had higher levels of virus infection; therefore, it was found that during the COVID-19 pandemic year of 2020–2021, the housing price hot spots were typically located in more affordable suburbs, smaller cities, and areas away from high-cost, high-density urban downtowns. This study may be helpful for understanding the relationship between the COVID-19 pandemic and the real estate market, as well as human behaviors in response to the pandemic.

Analysis on the spatio-temporal characteristics of COVID-19 in mainland China

COVID-19 has brought many unfavorable effects on humankind and taken away many lives. Only by understanding it more profoundly and comprehensively can it be soundly defeated. This paper is dedicated to studying the spatial-temporal characteristics of the epidemic development at the provincial-level in mainland China and the civic-level in Hubei Province. Moreover, a correlation analysis on the possible factors that cause the spatial differences in the epidemic's degree is conducted. After completing these works, three different methods are adopted to fit the daily-change tendencies of the number of confirmed cases in mainland China and Hubei Province. The three methods are the Logical Growth Model (LGM), Polynomial fitting, and Fully Connected Neural Network (FCNN). The analysis results on the spatial-temporal differences and their influencing factors show that: (1) The Chinese government has contained the domestic epidemic in early March 2020, indicating that the number of newly diagnosed cases has almost zero increase since then. (2) Throughout the entire mainland of China, effective manual intervention measures such as community isolation and urban isolation have significantly weakened the influence of the subconscious factors that may impact the spatial differences of the epidemic. (3) The classification results based on the number of confirmed cases also prove the effectiveness of the isolation measures adopted by the governments at all levels in China from another aspect. It is reflected in the small monthly grade changes (even no change) in the provinces of mainland China and the cities in Hubei Province during the study period. Based on the experimental results of curve-fitting and considering the time cost and goodness of fit comprehensively, the Polynomial(Degree = 18) model is recommended in this paper for fitting the daily-change tendency of the number of confirmed cases.

Has COVID-19 Changed the Hedge Effectiveness of Bitcoin?

The Bitcoin market has become a research hotspot after the outbreak of Covid-19. In this paper, we focus on the relationships between the Bitcoin spot and futures. Specifically, we adopt the vector autoregression-dynamic correlation coefficient-generalized autoregressive conditional heteroskedasticity (VAR-DCC-GARCH) model and vector autoregression-Baba, Engle, Kraft, and Kroner-generalized autoregressive conditional heteroskedasticity (VAR-BEKK-GARCH) models and calculate the hedging effectiveness (HE) value to investigate the dynamic correlation and volatility spillover and assess the risk reduction of the Bitcoin futures to spot. The empirical results show that the Bitcoin spot and futures markets are highly connected; second, there exists a bi-directional volatility spillover between the spot and futures market; third, the HE value is equal to 0.6446, which indicates that Bitcoin futures can indeed hedge the risks in the Bitcoin spot market. Furthermore, we update the data to the post-Covid-19 period to do the robustness checks. The results do not change our conclusion that Bitcoin futures can hedge the risks in the Bitcoin spot market, and besides, the post-Covid-19 results indicate that the hedging ability of Bitcoin futures increased. Finally, we test whether the gold futures can be used as a Bitcoin spot market hedge, and we further control other cryptocurrencies to illustrate the hedging ability of the Bitcoin futures to the Bitcoin spot. Overall, the empirical results in this paper will surely benefit the related investors in the Bitcoin market.

Geographic Scope and Real Estate Firm Performance during the COVID-19 Pandemic

This study examines the effect of geographic scope in mitigating the adverse impact of the COVID-19 pandemic in the real estate sector. Utilizing the Chinese setting over the two-month period in 2020 from the beginning of the outbreak to the successful containment of the spread of virus, we show that while the pandemic has negatively impacted real estate firm returns, firms with broader geographic scope and more geographically diversified property allocations have managed to better endure the crisis. We further find that firms with higher leverage report lower returns during the pandemic irrespective of their geographic scope, but larger firms can lessen the adverse impact of the pandemic only if they have adopted a more diversified strategy. Overall, our study provides novel evidence on the benefit of diversification by demonstrating the importance of geographic scope and diversification at times of crises. Specifically, we show corporate diversification could be especially useful to mitigate the negative stock market reactions resulting from the pandemic. Moreover, diversification could even become essential for larger firms that are expected by the market to be more diversified.

Sustainable Construction Investment, Real Estate Development, and COVID-19: A Review of Literature in the Field

Aspects of sustainable construction investment and real estate development (CIRED) and their interrelations during the period pre-, intra-, and post-COVID-19, are presented in the research. Applications of the topic model, environmental psychology theory, building life cycle method, and certain elements of bibliometrics, webometrics, article level metrics, altmetrics, and scientometrics make it possible to perform a quantitative analysis on CIRED. The CIRED topic model was developed in seven steps. This paper aims to present a literature review on CIRED throughout the pandemic and to look at the responses from the real estate and construction sector. This sector is a field that appears to be rapidly expanding, judging from the volume of current research papers. This review focuses on last year’s leading peer-reviewed journals. A combination of various keywords was applied for the review and the criteria for paper selections included construction investment, real estate development, civil engineering, COVID-19, and sustainability, as well as residential, industrial, commercial, land, and special purpose real estate, along with their risks, strategies, and trends. The articles reviewed for this paper, which analyzes three hypotheses, look at pre-, intra-, and post-pandemic CIRED. The three hypotheses were validated by analyzing scientific publications from around the world. Two innovative elements make this study stand out among the most advanced research on pre-, intra-, and post-pandemic CIRED. The first of the two innovations is the integrated analysis of the COVID-19 pandemic, COVID-19-related national policies, and business investment strategies relevant to CIRED and the interests of investors as well as on the impact a CIRED policy and investors make on the spread of COVID-19. In addition, this research demonstrates a marked increase in the effectiveness of a CIRED analysis, when the life cycle of a CIRED, the involved stakeholders with their own individual interests, the COVID-19 situation, and the external micro-, meso-, and macro-environments are covered comprehensively as a single entity.

What Explains Natives and Sojourners Preventive Health Behavior in a Pandemic: Role of Media and Scientific Self-Efficacy

The COVID-19 pandemic triggered a severe global public health emergency. The current research investigated and compared "Natives and Sojourners" health-protective behavior in Mainland China during the pandemic. We adopted a unified view to propose our theoretical model by adapting the Health Belief Model (HBM) and Institutional Theory (IT). The data obtained through an online survey questionnaire from 435 respondents during the second and third quarters of were analyzed. Structural equation modeling (SEM) was used to empirically analyze the proposed model. The media self-efficacy (MSE), scientific self-efficacy (SSE), perceived health risks (PHRs), and the perceived benefits of being protected have positive and significant effects on the definition of health-protective behavioral intentions among natives and sojourners in mainland China. Media and SSE can play a strategic role in formulating public health-protective behavior. The current research recommends an effective communication with sojourners during crisis for them to be a part of the national crisis management plan (i.e., infectious disease).

Housing Market in the Time of Pandemic: A Price Gradient Analysis from the COVID-19 Epicentre in China

While the outbreak of the COVID-19 disease has caused asset markets to experience an unprecedented spike of risk and uncertainty worldwide, the real estate market in many global cities appears to be immune to the adverse effects. How does COVID-19 affect urban housing markets? This study is a first attempt to identify the pandemic’s impact on house prices by applying a price gradient analysis to the COVID-19 epicentre in China. Considering microlevel housing transaction data in 62 areas from nine districts in Wuhan City from January 2019 to July 2020, the hedonic pricing and the price gradient models suggest that there was, respectively, a 4.8% and a 5.0–7.0% year-on-year fall in house prices immediately after the pandemic outbreak. Although house prices rebounded after the lockdown period, the gradient models show that the price gradients were flattened from the epicentre to the urban peripherals. The price premiums in high-density areas were also substantially discounted after the city’s lockdown. Our findings are robust to different model specifications. The implication is that the risk associated with the pandemic is localised and transitory in nature. People may be able to internalise the risk by residing in low-density residential areas.