Get More Info!

Announcement
Announcement
The impact of metro rail infrastructure on commercial property real estate values in Delhi: a hedonic approach

Student Name: Mr Yogesh Tyagi
Guide: Prof. Shaleen Singhal
Year of completion: 2022

Abstract:

The influence of proximity to new and enhanced rail transportation on real estate values has emerged as a major issue of debate related to public infrastructure and economic growth. Existing empirical research examines a broad range of estimates regarding the influence of the different rail systems on real estate property values, indicating the advantages of transit-oriented neighbourhoods. These estimates will take into account both transportation and its benefits resulting from neighbourhood planning and general liveability. Despite a large number of researches conducted on the impact of rail systems on real estate values, currently no study is available on Delhi Metro Rail Transit System (MRTS). The main purpose of this research is to investigate the influence of four selected stations along the Blue Line of the Delhi MRTS, commonly known as Delhi Metro, on commercial property values.

This research examined commercial property values before and after the opening of the Blue Line of Delhi Metro in 2005. The impact of proximity to metro rail on commercial property prices was estimated using the multivariate regression analysis with random effects (GLS) technique on a panel dataset of selected stations to develop a hedonic pricing analysis (HPA) model. In the first section of this investigation, the method was applied to 785 and 931 separate panel datasets from 2000-2004 and 2005-2008 respectively, coinciding with metro rail planning and construction (the pre-commissioning phase from 2000-2004) and operation (the post-commissioning phase from 2005-2008) using actual sale prices of commercial units. In a second section, a more comprehensive analysis of 1,413 property panel datasets (panel year, 2000-2008) was performed using the random effects (GLS) technique to generate hedonic price models (HPMs) for all four stations along the Blue Line of Delhi MRTS. According to preliminary findings, a station node has a moderately positive and negative trend during the planning and construction stages.

The operational period, on the other hand, has resulted in a significant price premium for commercial properties ranging from INR 246.19 to INR 732.80 due to improved accessibility, as shown in the following section of the analysis. The comprehensive analysis of this research from 2000 to 2008 resulted in a price increase of INR 125.48 to INR 418.99 per metre decrease in distance from station, within a 0.5 km radius of the four selected stations. This study summarizes the existing literature as well as a few selected international commercial property cases in order to identify critical factors and establish a methodology for empirical analysis. The influence of selected stations along Blue Line of Delhi Metro on commercial property values is estimated using the methodologies and findings from these literature studies, select international cases, and the preferred dataset. The approach and findings shed light on metro rails, with a special emphasis on commercial real estate values in the development and expansion of Metro Rail Transit Systems (MRTSs).

This research contributed to the existing literature by generating panels from datasets and analysing the influence of the Delhi Metro on property prices using repeat sales data from the study period. The research also contributes to the method of analysing the impact of the Delhi MRTS on commercial property values, which contributes to better empirical methodologies. The findings of this research will also be of interest to other cities that are planning their first metro rail transit system. The positive impact of metro rail suggests that a mechanism of value capture may be investigated to address relevant policy issues.

Key Words of the Research: Metro Rail Transit System (MRTS), Metro Rail, Commercial Property Values, Proximity, Accessibility, Hedonic, Panel Data.