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...
| Main Author: | |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2014
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/38623/ http://irep.iium.edu.my/38623/4/ICRMMS_latent.pdf |
| Summary: | 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‟. |
|---|