The aim of our research is to shed some light on the issue related to the effect, negative or positive, of recreational night activities on residential property prices, by examining data collected on property purchases. We started with Turin data and we intend now to make some comparisons with the situation in Milan, by using an original highly detailed housing transactions dataset concerning Milan and Turin, covering the period from 2017 to 2018. Two conflicting views are present. According to the first 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. 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 can be seen as a means to restart an area. 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. 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? Answering these research questions can help reflecting on appropriate interventions that policy makers could specifically implement in movida areas. In this regard, reliable results are quite hard to obtain, implying different methodological challenges. This proposal will discuss critical issues concerning data collection, measurement indicators, econometric techniques.
THE EFFECT OF MOVIDA ON RESIDENTIAL PROPERTY PRICES: AN EXAMPLE FROM TURIN
elisabetta ottoz
First
;Lisa Sella
2020-01-01
Abstract
The aim of our research is to shed some light on the issue related to the effect, negative or positive, of recreational night activities on residential property prices, by examining data collected on property purchases. We started with Turin data and we intend now to make some comparisons with the situation in Milan, by using an original highly detailed housing transactions dataset concerning Milan and Turin, covering the period from 2017 to 2018. Two conflicting views are present. According to the first 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. 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 can be seen as a means to restart an area. 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. 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? Answering these research questions can help reflecting on appropriate interventions that policy makers could specifically implement in movida areas. In this regard, reliable results are quite hard to obtain, implying different methodological challenges. This proposal will discuss critical issues concerning data collection, measurement indicators, econometric techniques.
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