Multiple regression analysis to predict the value of a residential building and to compare with the conventional method values

Dheeraj Vishwanatha Shetty, B. Prakash Rao, Chandra Prakash, S. Vaibhava

Research output: Contribution to journalConference articlepeer-review

Abstract

Valuation is an art which has found various use in different sectors. But it is seldom restricted to the boundaries of engineers and architects when it comes to property valuation. In the present study, the market value of a residential building situated in Udupi, Karnataka State, India is predicted using Multiple Regression Analysis (MRA) based on the factors affecting the value of the property. This value is then compared with the values obtained by the conventional approaches of valuation like Land and Building method, Rental Income Approach, Composite Rate method and by detailed estimation approach. The property under valuation has a plinth area of 2545.42 square feet standing on a free hold land of 4207.896 square feet. The market value predicted by Multiple Regression Analysis (MRA) shows a variation of 14.10% in comparison with Land and Building method, a variation of - 22.17% in comparison with Rental Income approach, a variation of 4.90% in comparison with Composite Rate method and a variation of 8.81% in comparison with detailed estimate method. The advantage of using MRA is that it uses statistical modelling and reduces the chance of human bias and error.

Original languageEnglish
Article number012118
JournalJournal of Physics: Conference Series
Volume1706
Issue number1
DOIs
Publication statusPublished - 22-12-2020
Event1st International Conference on Advances in Physical Sciences and Materials 2020, ICAPSM 2020 - Coimbatore, Virtual, India
Duration: 13-08-202014-08-2020

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

Fingerprint Dive into the research topics of 'Multiple regression analysis to predict the value of a residential building and to compare with the conventional method values'. Together they form a unique fingerprint.

Cite this