Language:
English
繁體中文
Help
回圖書館首頁
手機版館藏查詢
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Modeling a market for natural catast...
~
Gao, Yang.
Linked to FindBook
Google Book
Amazon
博客來
Modeling a market for natural catastrophe insurance.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Modeling a market for natural catastrophe insurance./
Author:
Gao, Yang.
Description:
121 p.
Notes:
Source: Dissertation Abstracts International, Volume: 75-06(E), Section: B.
Contained By:
Dissertation Abstracts International75-06B(E).
Subject:
Civil engineering. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3579078
ISBN:
9781303748752
Modeling a market for natural catastrophe insurance.
Gao, Yang.
Modeling a market for natural catastrophe insurance.
- 121 p.
Source: Dissertation Abstracts International, Volume: 75-06(E), Section: B.
Thesis (Ph.D.)--Cornell University, 2014.
This dissertation introduces a game theoretic modeling framework and a series of models to examine the interactions between the key stakeholders (property owners, insurers, reinsurers and government) of a natural catastrophe insurance market, which possesses a complicated structure and faces many challenges from the natural catastrophe loss. Specifically, we integrate (1) a utility-based homeowner decision model; (2) a stochastic optimization model to optimize reinsurance decision by the primary insurer(s); (3) a heuristic government intervention model to reduce uninsured losses through price support for insurance purchase and acquisition; and (4) a state-of-the-art regional catastrophe loss estimation model, all within the framework of a static Cournot-Nash noncooperative game assuming perfect information. We allow the number of primary insurers to increase from one (monopoly) to many (oligopoly) within the Cournot-Nash framework, and examines the impacts of competition on market performance from each stakeholder's perspective. An automatic Response-Surface and Trust-Region algorithm is developed to solve the models for real, regional applications. A case study for residential wood frame buildings in Eastern North Carolina is presented. The case study suggests that: (a) private insurance market competition is an efficient mechanism to reduce uninsured loss, which should be facilitated by government; (b) more competition challenges insurers but benefits homeowners, and there exists a balance between insurer profitability and insurance penetration; (c) acquisition, price support and encouraging insurers to keep catastrophe reserve can all improve market performance and reduce uninsured loss; and (d) catastrophe reserves should be encouraged, which not only help insurers to avoid insolvency, but could also limit competition if imposed as barrier of entry, thus improve their profitability.
ISBN: 9781303748752Subjects--Topical Terms:
860360
Civil engineering.
Modeling a market for natural catastrophe insurance.
LDR
:02763nmm a2200277 4500
001
2065560
005
20151205152209.5
008
170521s2014 ||||||||||||||||| ||eng d
020
$a
9781303748752
035
$a
(MiAaPQ)AAI3579078
035
$a
AAI3579078
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Gao, Yang.
$3
3180265
245
1 0
$a
Modeling a market for natural catastrophe insurance.
300
$a
121 p.
500
$a
Source: Dissertation Abstracts International, Volume: 75-06(E), Section: B.
500
$a
Adviser: Linda K. Nozick.
502
$a
Thesis (Ph.D.)--Cornell University, 2014.
520
$a
This dissertation introduces a game theoretic modeling framework and a series of models to examine the interactions between the key stakeholders (property owners, insurers, reinsurers and government) of a natural catastrophe insurance market, which possesses a complicated structure and faces many challenges from the natural catastrophe loss. Specifically, we integrate (1) a utility-based homeowner decision model; (2) a stochastic optimization model to optimize reinsurance decision by the primary insurer(s); (3) a heuristic government intervention model to reduce uninsured losses through price support for insurance purchase and acquisition; and (4) a state-of-the-art regional catastrophe loss estimation model, all within the framework of a static Cournot-Nash noncooperative game assuming perfect information. We allow the number of primary insurers to increase from one (monopoly) to many (oligopoly) within the Cournot-Nash framework, and examines the impacts of competition on market performance from each stakeholder's perspective. An automatic Response-Surface and Trust-Region algorithm is developed to solve the models for real, regional applications. A case study for residential wood frame buildings in Eastern North Carolina is presented. The case study suggests that: (a) private insurance market competition is an efficient mechanism to reduce uninsured loss, which should be facilitated by government; (b) more competition challenges insurers but benefits homeowners, and there exists a balance between insurer profitability and insurance penetration; (c) acquisition, price support and encouraging insurers to keep catastrophe reserve can all improve market performance and reduce uninsured loss; and (d) catastrophe reserves should be encouraged, which not only help insurers to avoid insolvency, but could also limit competition if imposed as barrier of entry, thus improve their profitability.
590
$a
School code: 0058.
650
4
$a
Civil engineering.
$3
860360
650
4
$a
Economics.
$3
517137
690
$a
0543
690
$a
0501
710
2
$a
Cornell University.
$b
Civil and Environmental Engineering.
$3
2093169
773
0
$t
Dissertation Abstracts International
$g
75-06B(E).
790
$a
0058
791
$a
Ph.D.
792
$a
2014
793
$a
English
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3579078
based on 0 review(s)
Location:
ALL
電子資源
Year:
Volume Number:
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
W9298270
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login