Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/224290
Title: An Analysis of the Factors Affecting Agricultural Land Price for Determining the Fair Value of Land During Land Acquisition in India
Researcher: Roy, Tapas
Guide(s): Kumar, Anil; Jayaraj, R and Ghosh, Anjan
Keywords: Social Sciences,Economics and Business,Management;Land acquisition - India
University: University of Petroleum and Energy Studies (UPES)
Completed Date: 8/1/2017
Abstract: Valuation of agricultural land has been done for ages and it is market driven. But it evolves out of valuing the attributes of the assets individually and in combinations. Land, as any other asset is also valued by its attributes. However, the relative importance of these attributes change over time as the social and economic priorities also change. Current research focuses on identification of the attributes which are significant in making the land price to change and building a land valuation model. Research treatment is both quantitative and qualitative. Data used are both primary and secondary. To identify factors which determine land prices in India literature review was carried out to identify variables which were to be considered to build models for land valuation. Such modelling studies have so far been mostly carried out in the western world. The variables chosen have been specific to their context. These cannot be replicated directly in the Indian context. Hence, focus group survey was carried out among the subject matter experts to identify variables that could be considered as significant in the Indian context to affect agricultural land price. Both the list of variables emerging from these two sources was reviewed to choose a final list of 31 variables to suit the Indian condition. There was a need to identify the principal components among those variables which could account for most of the variations in land price between the acquired land and the comparable lands sold. The survey aimed at identifying the latent variables from among the 31 variables using factor analysis. newline
Pagination: 242p.
URI: http://hdl.handle.net/10603/224290
Appears in Departments:Department of Infrastructure Management

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02_acknowledgement.pdf13.23 kBAdobe PDFView/Open
03_declaration.pdf10.52 kBAdobe PDFView/Open
04_certificate.pdf206.3 kBAdobe PDFView/Open
05_contents.pdf284.06 kBAdobe PDFView/Open
06_executive summary.pdf262.88 kBAdobe PDFView/Open
07_list of figures.pdf8.14 kBAdobe PDFView/Open
08_list of tables.pdf8.49 kBAdobe PDFView/Open
09_list of charts.pdf6.21 kBAdobe PDFView/Open
10_chapter1.pdf641.5 kBAdobe PDFView/Open
11_chapter2.pdf199.75 kBAdobe PDFView/Open
12_chapter3.pdf272.95 kBAdobe PDFView/Open
13_chapter4.pdf848.74 kBAdobe PDFView/Open
14_chapter5.pdf824.11 kBAdobe PDFView/Open
15_chapter6.pdf875.98 kBAdobe PDFView/Open
16_chapter7.pdf329.53 kBAdobe PDFView/Open
17_chapter8.pdf1.78 MBAdobe PDFView/Open
18_chapter9.pdf1.23 MBAdobe PDFView/Open
19_chapter10.pdf538.33 kBAdobe PDFView/Open
20_annex.pdf746.9 kBAdobe PDFView/Open
21_references.pdf1.83 MBAdobe PDFView/Open
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