Health Crisis and Housing Market Effects - Evidence from the U.S. Opioid Epidemic

D’Lima, Walter; Thibodeau, Mark

doi:10.1007/s11146-021-09884-8

Cited by 9 publications

(4 citation statements)

References 16 publications

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“…The results indicate that the prices will fall by 0.207% with 1% rise in cases. This result is supported previous researchers such as D’Lima and Thibodeau (2020), Liu and Tang (2021), McCord et al (2022) and Qian et al (2021), who stated that the higher the contingency rate, lower were the housing prices, but these effects were short-lived and varied across cities. However, with a 1% decline in cases, the housing prices starts rising at a rate of 0.98%.…”

Section: Resultssupporting

confidence: 89%

“…This is an important finding, as it distinguishes the impact of onset of COVID-19 from the peak and its impact on the housing market of India. In addition, previous researchers such as D’Lima and Thibodeau (2020), Qian et al (2021), Liu and Tang (2021) and McCord et al (2022) found that the higher the contingency rate, the lower were the housing prices, but these effects were short-lived and varied across cities. This adversely affected the housing market, which was already suffering due to low income and rising unemployment.…”

Section: Resultsmentioning

confidence: 92%

“…Further, the study also explained that the housing prices were severely affected in the region of worse medical facilities. Similarly, D’Lima and Thibodeau (2020) revealed that prices declined in areas of lockdown. The study further indicated that with a one-unit increase in the contagion cases, the prices of the housing declined by 5% approximately.…”

Section: Review Of Literaturementioning

confidence: 99%

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House prices and COVID-19 pandemic shocks in India: a nonlinear ARDL analysis

Mehta

Gupta

Maitra

2022

IJHMA

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Purpose India is one of those countries that are severely affected by the COVID-19 pandemic. With the upsurge in the cases, the country recorded high unemployment rates, economic uncertainties and slugging growth rates. This adversely affected the real estate sector in India. As the relation of the housing market with the gross domestic product is quite lasting thus, the decline in housing prices has severely impacted the economic growth of the nation. Hence, the purpose of this paper is to gauge the asymmetric impact of COVID-19 shocks on housing prices in India. Design/methodology/approach Studies revealed the symmetric impact of macroeconomic variables, and contingencies on housing prices dominate the literature. However, the assumption of linearity fails to apprehend the asymmetric dynamics of the housing sector. Thus, the author uses a nonlinear autoregressive distributed lag model to address this limitation and test the existence of short- and long-run asymmetry. Findings The findings revealed the long- and short-run asymmetric impact of the COVID-19 outbreak and the peak of the COVID-19 on housing prices. The results indicate that the peak of COVID-19 had a greater impact on housing prices in comparison to the outbreak of COVID-19. This can be explained as prices will revert to normal at a speed of 0.978% with the decline in the number of COVID-19 cases. Whereas the housing prices rise at a rate of 0.714 as a result of government intervention to deal with the ill effects of the COVID-19 outbreak. Moreover, it can be inferred that both the outbreak and peak of COVID-19 will lead to a minimal decline in housing prices, while with the decline in the number of cases and reduction in the impact of the outbreak of COVID, the housing prices will rise at an increasing rate. Originality/value To the best of the authors’ knowledge, this is the first study to understand the impact of the outbreak and peak of COVID-19 on the housing prices separately.

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Section: Resultssupporting

confidence: 89%

Section: Resultsmentioning

confidence: 92%

Section: Review Of Literaturementioning

confidence: 99%

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House prices and COVID-19 pandemic shocks in India: a nonlinear ARDL analysis

Mehta

Gupta

Maitra

2022

IJHMA

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“…To provide relevant information about data usage, the visualization shows three recent scholarly publications using the ARCOS dataset. For instance, the study by [24] presents new evidence that changes in house prices near drug dispensaries are negatively correlated with drug quantities. A user might then check the ACS dataset, which is the American Community Survey about households.…”

Section: Resultsmentioning

confidence: 99%

Interactive Network Visualization of Opioid Crisis Related Data- Policy, Pharmaceutical, Training, and More

Scrivner¹,

McAvoy²,

Nguyen³

et al. 2021

Preprint

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Responding to the U.S. opioid crisis requires a holistic approach supported by evidence from linking and analyzing multiple data sources. This paper discusses how 20 available resources can be combined to answer pressing public health questions related to the crisis. It presents a network view based on U.S. geographical units and other standard concepts, crosswalked to communicate the coverage and interlinkage of these resources. These opioid-related datasets can be grouped by four themes: (1) drug prescriptions, (2) opioid related harms,(3) opioid treatment workforce, jobs, and training, and (4) drug policy. An interactive network visualization was created and is freely available online; it lets users explore key metadata, relevant scholarly works, and data interlinkages in support of informed decision making through data analysis.

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