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Determining the Impact of Residential Neighbourhood Crime on Housing Investment Using Logistic Regression

Author

Listed:
  • Sunday Emmanuel Olajide

    (University Tun Hussein Onn Malaysia)

  • Mohd Lizam

    (University Tun Hussein Onn Malaysia)

Abstract

This paper discusses the impact of criminal activities on residential property value. With regard to criminal activities, the paper emphasizes on the contribution of each component of property crime. One thousand (1000) sets of structured questionnaire were administered on the residents of residential estates within the South Western States of Nigeria out of which 467 were considered useable after the data screening. Purposive and systematic sampling techniques were used while logistic regression was used to determine the impact of each of the components of residential property crime on housing investment. The results showed the P-Values of 0.000, 0.322, 0.335, 0.545 and 0.992 for violent crime, incivilities and street crime, burglary and theft, vandalism and robbery respectively. However, the R2 which represents the generalisation of the impact of neighbourhood crime on housing investment was 44 % and aggregate P-value was 0.000. Using the Hosmer and Lemeshow (H-L) test of goodness of fit, the model had approximately 89% predictive probability which is considered excellent. This indicates that the alternative hypothesis is upheld that residential neighbourhood crime is capable of impacting on residential property value. The policy implication of this result is that no effort should be spared in combating residential neighbourhood crime in order to boost and encourage housing investment.

Suggested Citation

  • Sunday Emmanuel Olajide & Mohd Lizam, 2016. "Determining the Impact of Residential Neighbourhood Crime on Housing Investment Using Logistic Regression," Traektoriâ Nauki = Path of Science, Altezoro, s.r.o. & Dialog, vol. 2(12(17)), pages 6.8-6.6.17, December.
    • Handle: RePEc:pos:journl:17-2
    DOI: 10.22178/pos.17-13
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Housing investment; Logistic regression; Property values; Residential neighbourhood crime; Socio-Environmental Design Factors.;
    All these keywords.

    JEL classification:

    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services
    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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