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Andinet Woldemichael
and
Iyke Maduako
Housing represents the largest asset and liability, in the form of mortgages, on most national balance sheet. For most households it is their largest investment, and when mortgages are required also represents the largest component of household debt. It is also directly tied to financial markets, both the mortgage market and insurance sector. Although many countries have a rich set of housing censuses and statistics, others have large data gap in this area and therefore struggle to formulate effective policies. This paper proposes an approach to construct a global census of residential buildings using opensource satellite data. Such a layer can be used to assess the extent these buildings are exposed to climate hazards and how their production and consumption, in turn, affect the climate. The approach we propose could be scaled globally, combining existing layers of building footprints, climate and socioeconomic data. It adds to the ongoing effort of compiling spatially explicit and granular climate indicators to better inform policies. As a case study, we compute selected indicators and estimate the extent of residential properties exposure to riverine flood risk for Kenya.
Mr. Bas B. Bakker
This paper addresses the puzzling decline of Total Factor Productivity (TFP) levels in rapidly growing economies, such as Singapore, despite advancements in technology and high GDP per capita growth. The paper proposes that TFP growth is not negative; instead, standard growth decompositions have underestimated TFP growth by overestimating the contribution of capital, failing to account for the substantial part of capital income directed to urban land rents. This leads to an overestimation of changes in capital stock's contribution to growth and thereby an underestimation of TFP growth. A revised decomposition suggests that TFP growth in economies with high land rents and rapid capital stock growth, such as Singapore, has been considerably underestimated: TFP levels have not declined but increased rapidly.
Volker Grossman
and
Thomas Steger
There are, by now, several long term, time series data sets on important housing & macro variables, such as land prices, house prices, and the housing wealth-to-income ratio. However, an appropriate theory that can be employed to think about such data and associated research questions has been lacking. We present a new housing & macro model that is designed specifically to analyze the long term. As an illustrative application, we demonstrate that the calibrated model replicates, with remarkable accuracy, the historical evolution of housing wealth (relative to income) after World War II and suggests a further considerable increase in the future. The model also accounts for the close connection of house prices to land prices in the data. We also compare our framework to the canonical housing & macro model, typically employed to analyze business cycles, and highlight the main differences.
International Monetary Fund
This Selected Issues paper for the People’s Republic of China—Hong Kong Special Administrative Region (SAR) reviews the residential property market and implications of an aging population. The fiscal sector impact of price fluctuations is important in Hong Kong SAR with land sales and stamp duties providing an important source of government revenue. The simulations are based on a dynamic general equilibrium system with forward-looking behavior and rational expectations. Hong Kong SAR’s revenue flows are characterized by relatively volatile nontax items.