Abstract: I present empirical evidence that rental vacancy rate is correlated with prices and liquidity in the housing market. A decrease in rental vacancies is associated with a “hot” housing market and vice versa. Existing literature considers the rental and the housing market to be two separate markets but this paper aims to build a link between the two. I develop a search and matching model of the housing market which incorporates a rental market with search frictions, heterogeneous buyers and free entry of sellers and landlords. I simulate the model using perfectly correlated demand and supply side shocks to match the new and existing stylized facts. The model shows that a change in rental vacancies affects the agent’s decision to enter the housing market which creates a link between the two markets. The model is able to reproduce the cyclical co-movement of rental vacancies, price to rent ratio, sales, housing vacancies and time to sell. In addition to this, the model is also able to match the upwards sloping Beveridge curve that is observed in the housing and rental market.
Abstract: Housing vacancies are influenced by the decision to move. In this paper, we investigate this endogenous decision of when to put a house up for sale, while explicitly allowing for the entry of new houses and first-time buyers. Thus, variation in time on the market is governed by changes in market tightness as well as shifts in the reservation value of homeowner utility. In a calibrated version of the model, we show that following a demand shock, most of the variation in prices, sales, and housing vacancies is due to changes in new home construction, while a non-negligible portion arises from homeowners’ decisions to move. We also use the framework to study the impact of various housing policies, such as property tax and transaction tax, on housing tenure. For example, an increase in property tax makes home buying less attractive, resulting in higher tenure along with lower sales and prices.
Abstract: This study examines the impact of short-term rental (STR) bans, such as those on Airbnbs, using a quasi-experimental design. Since 2012, 18 out of 88 cities in Los Angeles have implemented STR bans. By employing a difference-in-differences approach with surrounding cities as controls, the study investigates how these bans affect housing market frictions. Preliminary findings indicate that, following the bans, housing prices and sales decline, while the impact on days on market varies depending on the level of aggregation. The study also distinguishes between regular households and investors, revealing that while household sales decrease in the regular market, investor-owned single-family residential properties are more likely to be foreclosed and subsequently purchased by regular households in the foreclosed market.