Risk Perception, Location Choice and Land-use Patterns under Disaster Risk: Long-term Consequences of Information Provision in a Spatial Economy

Hirokazu Tatano (), Kentaro Yamaguchi () and Norio Okada ()
Additional contact information
Hirokazu Tatano: Kyoto University
Kentaro Yamaguchi: Mitsubishi Research Institute Co.
Norio Okada: Kyoto University

Chapter 9 in Modeling Spatial and Economic Impacts of Disasters, 2004, pp 163-177 from Springer

Abstract: Abstract It appears that the number of death and magnitude of damage due to natural disaster is increasing in the last decades. Worldwide economic losses due to natural disasters are increased exponentially: the measured worldwide economic loss in 1990s is US$608.5 billion and is nine times larger than in 1960s according to Munich Re (2003). Although the number of the catastrophic events in the 1990s is three times as large as in 1960s, the economic loss per event has increased in the three times faster than the growth of the number. There is no doubt that accumulation of population and assets into the disaster prone area is one of the main factors which cause such a large increase in economic losses due to natural disasters.

Keywords: Risk Perception; Disaster Risk; Location Choice; Central Business District; Land Rent (search for similar items in EconPapers)
Date: 2004
References: Add references at CitEc
Citations: View citations in EconPapers (6)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:adspcp:978-3-540-24787-6_9

Ordering information: This item can be ordered from
http://www.springer.com/9783540247876

DOI: 10.1007/978-3-540-24787-6_9

Access Statistics for this chapter

More chapters in Advances in Spatial Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().