The sharing economy, also known as collaborative consumption or peer economy, has grown rapidly thanks to technology innovation and supply-side flexibility. The growth of sharing platform of Airbnb, one of the pioneers of the share economy, allows suppliers to supply underutilized short-term accommodation. At the demand side, consumers eagerly welcome these services due to fee sharing benefit. Since its introduction in 2008, more than 50 million guests has utilized its service. Its growth in fact has brought disruption to the hotel industry, particularly those targeting budget customers and non-business travelers. In some cities, Airbnb not only interrupt hotel industry, but also upset its housing market. Some academics argue that Airbnb has triggered the upswing in the accommodation cost for local renters as some landlords has switched from providing long-term housing into short-term housing to non-residents tourists due to higher short-term rental rate they can offer. Others argue that local renters lease up long-term housing from landlord and turn it into short-term housing to generate profit. All these prompts an increase in housing rents.  In this paper, we use Hong Kong as our case to empirically test whether Airbnb is responsible for higher housing rents. We hypothesize that the impact of Airbnb may not be of significance in Hong Kong the result of a small market for short-term rental as opposed to the market for long-term rental. There is an actual strong demand from local residents to occupy the space rather than lease it to non-residents tourists. 

We attempt to examine these hypotheses empirically. Two methodologies appear pertinent to study the likely impact of Airbnb on rental levels. Using time series data it is expected that a model containing fundamental determinants of rents would lose some of its capacity in explaining rent movements if Airbnb is a new significant driver of residential rents not accounted for. Hence such a fundamentals model will lose some of its explanatory power and make larger errors as Airbnb expands. The second approach is a hedonic framework in which rents are examined with reference to key housing characteristics and Airbnb rentals. The latter approach has major data requirements. This analysis provides the initial steps for a fuller treatment of the impact of Airbnb on residential rents in Hong Kong and makes direct contributions to the relevant international literature.