Residential prices in movida areas: up or down?

In the last three decades European cities have been affected by a particular type of noise pollution stemming from recreational activities generally located in the city centers, the so-called movida. The adverse environment for an apartment located in a "movida" district will result in a lower market value as compared to an apartment with similar characteristics, except for recreational noise. This occurs because potential buyers reduce their demand, as they discount present value of the costs of annoyance, loss of tranquility, and possible health effects. A measure of the noise-induced damages is the difference between the market-determined values of the two apartments. On the contrary, some claim that the price per square metre of properties has increased after "movida" developed, at least in certain districts, which were previously dilapidated and where nighttime economy was seen as a means to restart an area. On the other hand, Patrigest, an Italian company specialized in Valuation and Advisory for real estate, conducted in 2011 a research in Rome and Milan reaching the conclusion that excessive noise, in particular because of nearby pubs and discos, depreciates the real estate's value by 10 to 20% . The two statements are not necessarily contradictory because we face a fragmented situation where two neighbors may report very distant night experiences, according, for instance, to the location of bedrooms. If bedrooms overlook a protected courtyard, the estate is rather quiet and inhabitants may not suffer from noise pollution, but enjoy the lively atmosphere at no environmental costs. Specifically, we address the following two main research questions: 1.Do housing market responses to the noise pollution from recreational activities evidenced in previous studies from urban rail or traffic noise? 2.What are the underlying mechanisms that drive heterogeneity in housing market responses? The aim of this paper is to examine the effect of recreation noise on house prices. We use an original highly detailed housing transactions dataset from the City of Turin covering the period from 2017 to 2018. Using data on all recreational activities placed in the Turin in 2018, we calculate the distance from every property that is sold to the nearest commercial activities. A property represents not only an amount of structural characteristics, but also a set of specific locational characteristics. Disamenities have a negative effect on house price, which means people have a low demand and do not have the willingness to pay more for these characteristics and we use hedonic model urban to estimate this discount.