Segmenting agricultural land market according to development potential: a latent class approach

Not all farmlands are purchased for farming. Where development pressures are strong and urban boundaries still fluid, some farmlands are purchased for non-agricultural purposes. However, since the future development use is not evident or pre-determined at the time of transaction, the farmland mark...

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Main Author: Haniza Khalid,
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2017
Online Access:http://journalarticle.ukm.my/11250/1/jeko_51%281%29-12.pdf
http://journalarticle.ukm.my/11250/
http://www.ukm.my/fep/jem/content/2017.html
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spelling my-ukm.journal.112502018-01-13T23:29:59Z http://journalarticle.ukm.my/11250/ Segmenting agricultural land market according to development potential: a latent class approach Haniza Khalid, Not all farmlands are purchased for farming. Where development pressures are strong and urban boundaries still fluid, some farmlands are purchased for non-agricultural purposes. However, since the future development use is not evident or pre-determined at the time of transaction, the farmland market may appear 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 shadow prices of different land attributes can be differentiated by market segments. Using an extensive dataset of over 2,000 Malaysian farmland sales, our Latent Class Analysis confirms that there are two underlying distinct distributions and that within each distribution, relationships between variables display considerable local independence. Strength of potential drivers of farmland price is proven to differ according to segments. In addition, we are able to show that the segment classification results based on the parcel’s ‘developability’ was fairly accurate when compared to the classification given by official land valuation documents. This exercise proves that unobserved segmentation can be predicted with a reasonable degree of accuracy simply by letting the data ‘speak for itself’. In terms of agricultural support funding, the segmentation may allow for the country’s better targeting of recipients and refinement of farm support programs. Penerbit Universiti Kebangsaan Malaysia 2017 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/11250/1/jeko_51%281%29-12.pdf Haniza Khalid, (2017) Segmenting agricultural land market according to development potential: a latent class approach. Jurnal Ekonomi Malaysia, 51 (1). pp. 145-157. ISSN 0127-1962 http://www.ukm.my/fep/jem/content/2017.html
institution Universiti Kebangsaan Malaysia
building Perpustakaan Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description Not all farmlands are purchased for farming. Where development pressures are strong and urban boundaries still fluid, some farmlands are purchased for non-agricultural purposes. However, since the future development use is not evident or pre-determined at the time of transaction, the farmland market may appear 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 shadow prices of different land attributes can be differentiated by market segments. Using an extensive dataset of over 2,000 Malaysian farmland sales, our Latent Class Analysis confirms that there are two underlying distinct distributions and that within each distribution, relationships between variables display considerable local independence. Strength of potential drivers of farmland price is proven to differ according to segments. In addition, we are able to show that the segment classification results based on the parcel’s ‘developability’ was fairly accurate when compared to the classification given by official land valuation documents. This exercise proves that unobserved segmentation can be predicted with a reasonable degree of accuracy simply by letting the data ‘speak for itself’. In terms of agricultural support funding, the segmentation may allow for the country’s better targeting of recipients and refinement of farm support programs.
format Article
author Haniza Khalid,
spellingShingle Haniza Khalid,
Segmenting agricultural land market according to development potential: a latent class approach
author_facet Haniza Khalid,
author_sort Haniza Khalid,
title Segmenting agricultural land market according to development potential: a latent class approach
title_short Segmenting agricultural land market according to development potential: a latent class approach
title_full Segmenting agricultural land market according to development potential: a latent class approach
title_fullStr Segmenting agricultural land market according to development potential: a latent class approach
title_full_unstemmed Segmenting agricultural land market according to development potential: a latent class approach
title_sort segmenting agricultural land market according to development potential: a latent class approach
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2017
url http://journalarticle.ukm.my/11250/1/jeko_51%281%29-12.pdf
http://journalarticle.ukm.my/11250/
http://www.ukm.my/fep/jem/content/2017.html
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score 13.214268