This chapter reviews the evidence of predictability in US residential and commercial real
estate markets. First, we highlight the main methodologies used in the construction of real …

Both space and time are fundamental in human activities as well as in various physical
processes. Spatiotemporal analysis and modeling has long been a major concern of …

Although interest in spatial regression models has surged in recent years, a comprehensive,
up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial …

Assembling a collection of very prominent researchers in the field, the Handbook of Spatial
Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects …

Among the many uses of hierarchical modeling, their application to the statistical analysis of
spatial and spatio-temporal data from areas such as epidemiology And environmental …

Many in the housing literature argue that house prices and income are cointegrated. I show
that the data do not support this view. Standard tests using 27 years of national‐level data …

Relationships between past events, future expectations and present decisions, typically
examined through a temporal prism within applied economics, have been lately moving to …

Understanding scale effects is important and indispensable for geography studies. However,
spatial and spatiotemporal statistical tools for measuring the operational scales of different …

The idea that location is important in real estate economics is not new. However, the spatial
dimension of real estate data is not always taken into account in traditional real estate …

Abstract The European Union issued several directives in the field of energy efficiency which
impact on the building sector in order to avoid a further increase of energy consumption and …