Heavy-tailed distributions for building stock data

Abstract

The question of inferring the owner of a set of building stocks (e.g. from which country the buildings are taken) from building-related quantities like number of buildings or types of building event histories necessitates the knowledge of their distributions in order to compare them. If the distribution function is a power law, then a version of the 80/20 rule can be applied to describe the variable. This distribution is an example of a heavy-tailed distribution; another example is the log-normal distribution. Heavy-tailed distributions have the property that studying the effects of the few large values already yields most of the overall effect of the whole quantity. For example, if reducing the CO2 emissions of the buildings of a country is the issue, then in case of a heavy-tailed distribution, only the effects of the relatively few large cities need to be considered. It is shown that the number of buildings in German municipalities or counties or the number of building-related event histories of a certain vanished building stock follow a heavy-tailed distribution and give evidence for the type of underlying distribution. The methodology used is a recent statistical framework for discerning power law and other heavy-tailed distributions in empirical data.

Are patterns of vacant lots random? Evidence from empirical spatiotemporal analysis in Chiba prefecture, east of Tokyo

“…Third, spatial data regarding vacant lots are unavailable, as few government agencies specifically collect such information (Hollander, 2018). Furthermore, spatial data on the shape of building lots per se are difficult to obtain (Bradley and Behnisch, 2018;Gao and Asami, 2005;Usui, 2018). Thus, in the literature CSR regarding the generation and accumulation patterns of vacant lots has yet to be tested.…”

Size Distribution of Building Lots and Density of Buildings and Road Networks: Theoretical Derivation Based on Gibrat’s Law and Empirical Study of Downtown Districts in Tokyo

“…They are, however, limited in quantity because the documents are kept for only ten years after applications are made (Gao and Asami 2005). Second, only giving the average which always works with density can be meaningless or misleading because there are many different kinds of statistical distribution having the same average (Bradley and Behnisch 2019). In particular, high building density which is equivalent to a small average building lot size is considered as one of the major causes of the spread of fire, the low quality of sanitation, ventilation and privacy in Japan, and tends to make the residential environment worse.…”