Publication detail

The Assessment of Building’s Insurable Value Using Multivariate Statistics: The Case of Czech Republic

CUPAL, M. SEDLAČÍK, M. MICHÁLEK, J.

Original Title

The Assessment of Building’s Insurable Value Using Multivariate Statistics: The Case of Czech Republic

English Title

The Assessment of Building’s Insurable Value Using Multivariate Statistics: The Case of Czech Republic

Type

journal article in Scopus

Language

en

Original Abstract

When concluding a property insurance agreement, adjustment of the insured amount poses a certain risk. From the policyholder's point of view, the risk measure translates into the chosen target amount which should correspond to the insurable value. The aim of the research is to determine a statistical model for prediction of the insurable value with using current models in Czech Republic. The model for insurable value prediction is based on a synthesis of four core models. The methodology is based on a classification tree created by the CART method, and multivariate linear regression. After the classification tree is created, the input variables which contributed to the classification are used in the regression model. Database consists of 125 family houses which went through a detailed examination (they were documented, measured, and their technical state and legal status were determined), and were described in experts’ reports. Obtained results showed a high degree of statistical association of selected predictors with the estimated insurable value of property, as well as with the acceptable risk, and subsequently, a relatively low percentage of misclassified objects. The proposed multiple regression model proved as statistically significant and can be used for objective estimations of insurable value.

English abstract

When concluding a property insurance agreement, adjustment of the insured amount poses a certain risk. From the policyholder's point of view, the risk measure translates into the chosen target amount which should correspond to the insurable value. The aim of the research is to determine a statistical model for prediction of the insurable value with using current models in Czech Republic. The model for insurable value prediction is based on a synthesis of four core models. The methodology is based on a classification tree created by the CART method, and multivariate linear regression. After the classification tree is created, the input variables which contributed to the classification are used in the regression model. Database consists of 125 family houses which went through a detailed examination (they were documented, measured, and their technical state and legal status were determined), and were described in experts’ reports. Obtained results showed a high degree of statistical association of selected predictors with the estimated insurable value of property, as well as with the acceptable risk, and subsequently, a relatively low percentage of misclassified objects. The proposed multiple regression model proved as statistically significant and can be used for objective estimations of insurable value.

Keywords

regression; CART algorithm; classification tree; building; insurable value

Released

31.10.2019

Publisher

Towarzystwo Naukowe Nieruchomości

Location

Olsztyn, Poland

ISBN

1733-2478

Periodical

Real Estate Management and Valuation

Year of study

27

Number

3

State

PL

Pages from

81

Pages to

96

Pages count

21

URL

Documents

BibTex


@article{BUT157781,
  author="Martin {Cupal} and Marek {Sedlačík} and Jaroslav {Michálek}",
  title="The Assessment of Building’s Insurable Value Using Multivariate Statistics: The Case of Czech Republic",
  annote="When concluding a property insurance agreement, adjustment of the insured amount poses a certain risk. From the policyholder's point of view, the risk measure translates into the chosen target amount which should correspond to the insurable value.
The aim of the research is to determine a statistical model for prediction of the insurable value with using current models in Czech Republic. The model for insurable value prediction is based on a synthesis of four core models. The methodology is based on a classification tree created by the CART method, and multivariate linear regression. After the classification tree is created, the input variables which contributed to the classification are used in the regression model.
Database consists of 125 family houses which went through a detailed examination (they were documented, measured, and their technical state and legal status were determined), and were described in experts’ reports.
Obtained results showed a high degree of statistical association of selected predictors with the estimated insurable value of property, as well as with the acceptable risk, and subsequently, a relatively low percentage of misclassified objects. The proposed multiple regression model proved as statistically significant and can be used for objective estimations of insurable value.",
  address="Towarzystwo Naukowe Nieruchomości",
  chapter="157781",
  howpublished="online",
  institution="Towarzystwo Naukowe Nieruchomości",
  number="3",
  volume="27",
  year="2019",
  month="october",
  pages="81--96",
  publisher="Towarzystwo Naukowe Nieruchomości",
  type="journal article in Scopus"
}