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Identifying latent groupings in market data: a latent class approach

Not all farmlands are purchased for farming. Certain types of farmland are purchased for non-agricultural (development) purposes, but because the new potential use is not evident or determined at the time of transaction, the farmland market appears to operate as one albeit with latent segments. Anal...

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Main Author: Khalid, Haniza
Format: Conference or Workshop Item
Language:English
Published: 2014
Subjects:
HA29 Theory and method of social science statistics
HD1401 Agriculture
Online Access:http://irep.iium.edu.my/38623/4/ICRMMS_latent.pdf
http://irep.iium.edu.my/38623/
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spelling my.iium.irep.38623 http://irep.iium.edu.my/38623/ Identifying latent groupings in market data: a latent class approach Khalid, Haniza HA29 Theory and method of social science statistics HD1401 Agriculture Not all farmlands are purchased for farming. Certain types of farmland are purchased for non-agricultural (development) purposes, but because the new potential use is not evident or determined at the time of transaction, the farmland market appears to operate as one albeit with latent segments. Analyses of land price determinants should involve some measures to ascertain the cause and the degree of functional segmentation in the market, so that the effects of explanatory variables on price can be differentiated according to the segments‟ profiles. One way this can be achieved is by using Latent Class Analysis (LCA). Results for the Malaysian agricultural land price model confirm that there are two underlying distinct distributions and that within each distribution, relationships between variables display considerable local independence. The LCA is particularly appealing where studies lacks quality data or suffers from other forms of data constraints, or where there are more than one expected outcome or response measures. This exercise proves that unobserved segmentation can be predicted with a fair degree of accuracy simply by letting the data „speak for itself‟. 2014-09-27 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/38623/4/ICRMMS_latent.pdf Khalid, Haniza (2014) Identifying latent groupings in market data: a latent class approach. In: International Conference on Research Methods in Management and Social Sciences (ICRMMS-2014), 27-28 September 2014, Kuala Lumpur.
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic HA29 Theory and method of social science statistics
HD1401 Agriculture
spellingShingle HA29 Theory and method of social science statistics
HD1401 Agriculture
Khalid, Haniza
Identifying latent groupings in market data: a latent class approach
description Not all farmlands are purchased for farming. Certain types of farmland are purchased for non-agricultural (development) purposes, but because the new potential use is not evident or determined at the time of transaction, the farmland market appears to operate as one albeit with latent segments. Analyses of land price determinants should involve some measures to ascertain the cause and the degree of functional segmentation in the market, so that the effects of explanatory variables on price can be differentiated according to the segments‟ profiles. One way this can be achieved is by using Latent Class Analysis (LCA). Results for the Malaysian agricultural land price model confirm that there are two underlying distinct distributions and that within each distribution, relationships between variables display considerable local independence. The LCA is particularly appealing where studies lacks quality data or suffers from other forms of data constraints, or where there are more than one expected outcome or response measures. This exercise proves that unobserved segmentation can be predicted with a fair degree of accuracy simply by letting the data „speak for itself‟.
format Conference or Workshop Item
author Khalid, Haniza
author_facet Khalid, Haniza
author_sort Khalid, Haniza
title Identifying latent groupings in market data: a latent class approach
title_short Identifying latent groupings in market data: a latent class approach
title_full Identifying latent groupings in market data: a latent class approach
title_fullStr Identifying latent groupings in market data: a latent class approach
title_full_unstemmed Identifying latent groupings in market data: a latent class approach
title_sort identifying latent groupings in market data: a latent class approach
publishDate 2014
url http://irep.iium.edu.my/38623/4/ICRMMS_latent.pdf
http://irep.iium.edu.my/38623/
_version_ 1643616717867319296
score 13.211869

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