Predicting Future of Senior Housing Markets amid COVID-19 Pandemic in India Using Dependency Models

Abstract

The COVID-19 pandemic has contributed to a very high percentage of senior deaths in India. Senior citizens constitute about 10% of total population while 73% of deaths during COVID-19 pandemic in India have been of people with co-morbidities such as diabetes, hypertension, heart and respiratory diseases. Amidst this pandemic, the senior housing market is poised for exponential growth despite a low market share as well as slow sales. To inquire as to which factors influence the seniors for not buying into exclusive senior housing communities and whether the decision varies among ages as well as genders; a questionnaire survey was conducted pre-COVID-19 using sales leads of 143 senior respondents from five cities; Delhi, Lavasa, Chennai, Pune and Ahmedabad. These data were tested using binary probit regression models for age and gender. The survey required the respondents to rate decision factors which included; amenities, location, social isolation, wealth, family, urban connect, new relationships, inheritance and moral values - on Likert scale of 1 to 9. The tested model for gender shows that males are dependent on factors of location of the project and fear isolation as compared to females. Males also rated new acquaintances as a discouraging factor as compared to females. The age model shows that older seniors (aged 66-75) do not wish to move to an exclusive senior citizen homes due to factors of distance, fear of social isolation and attachment to urban elements as compared to younger seniors (aged 55-65). An attempt is made to use the results arising from these models to predict the future of senior housing market post-COVID-19 pandemic in India. By integrating new factors such as social distancing, personal hygiene and recreational activities, the existing models can be used to forecast post-COVID-19 senior housing markets in India.