BROWSE STATISTICS BY COUNTRY
The Phantom Urbanism phenomenon is being defined as a high-speed urbanization process through large-scale development projects which struggle to find residents to inhabit these physical platforms. Therefore, the purpose of this research is to analyze a selection of projects that meet the criteria of a phantom urbanism development to further explore broad trends of population growth, employment growth, expenditure growth, commodity prices in relation to public policies to try to identify meaningful patterns and associations that could induce Phantom Urbanism. In that sense, the criteria set to create a database of the projects that
present this phenomenon was the following:
A) Settlements of size above one square kilometer,
B) reported with vacancy rates above 50%,
C) for a minimum period of time of one year.
For the purpose of this research, we have selected fifty projects that met the criteria, based on data availability. The spectrum of collection is worldwide, thus, the projects selected are located throughout five
continents and twenty-three countries. The geopolitical (country) locations of the projects are taken as start point for a “broad brush” analysis, because it is based on broadly available statistical data, limited in terms of level of detail, at which the different issues ca be explored. However, because simple descriptions of trends are insufficient to shed light on the phenomena, we introduce the country real estate policy to better understand possible reasons behind historical and forecast movement in the major growth indicators to better assess implications of the country urbanization process. The objective of this effort is to identify first meaningful patterns and associations and eventually the underlying forces driving phantom urbanism
In order to develop a consistent explanation of the statistical trends in each context and implications of patterns in demand for real estate products, we present a simple analytic framework in an easier plot as it is a holistic graph that converts magnitudes into indices, which will graphically suggest the connections between basic growth indicators with the phenomena of Phantom Urbanism. This study synthesis is complemented
with a time line of the real estate policy implemented in each country. Growth indicators represent the most important source of increases in the aggregate (new) demand for residential real estate. It is because estate is physically durable, most of the demand for new space comes from growth. The basic growth trends selected for this study are the following: GDP growth, Population growth, Household consumption/ expenditure, and the Unemployment rate of the total labor force. The GDP growth rate would tell us how fast a country’s economy is growing. Population growth rate will show the change in population over a unit time period, the Household consumption spending including goods and services which will indicate the average purchasing power of individuals assuming nearly two thirds includes real estate consumption. The last indicator relates to the unemployment rate to show if the economy is growing at a healthy rate and if jobs are relatively plentiful it can be expected to fall. This numeric framework is complemented with an overview of each country real estate policy regarding household’s access to the property market to assess the possible effects public policy could have had on the development of the project. With both statistics and policy analysis based on the year of the project implementation (YOI) in a time frame from 1990 to 2016, we will try to explain past and following patterns and implications regarding the development the phantom urbanism projects.
In each country chapter, we will develop basic growth indicators analysis into the country policy perspective to discuss the different patterns in the urbanization growth, their possible mechanisms, causes, and their implications for real estate market supply. Each country case presents an example a broad-brush urbanization growth analysis process for a specific year of a ghost urbanism project.
CLASSIFICATION - STATISTICAL AND POLICY PATTERNS
COUNTRY SPECIFIC ANALYSIS - INVESTMENT SOURCE AND LIABLE ACTORS
CAPITAL PATTERNS - IDENTIFYING FINANCING SOURCES
CLASSIFICATION - DOWNFALL PATTERNS
CLASSIFICATION - REVIVAL PATTERNS