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Latent vs. Observed Variables: Analysis of Irrigation Water Efficiency Using SEM and SUR
Author(s) -
Tang Jianjun,
Folmer Henk
Publication year - 2016
Publication title -
journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.157
H-Index - 61
eISSN - 1477-9552
pISSN - 0021-857X
DOI - 10.1111/1477-9552.12137
Subject(s) - multicollinearity , econometrics , latent variable , allocative efficiency , irrigation , mathematics , statistics , structural equation modeling , water use efficiency , economics , environmental science , regression analysis , microeconomics , agronomy , biology
In this paper we compare conceptualising single factor technical and allocative efficiency as indicators of a single latent variable, or as separate observed variables. In the former case, the impacts on both efficiency types are analysed by means of structural equation modeling ( SEM ), in the latter by seemingly unrelated regression ( SUR ). We compare estimation results of the two approaches based on a dataset on single factor irrigation water use efficiency obtained from a survey of 360 farmers in the Guanzhong Plain, China. The main methodological findings are that SEM allows identification of the most important dimension of irrigation water efficiency (technical efficiency) via comparison of their factor scores and reliability. Moreover, it reduces multicollinearity and attenuation bias. It thus is preferable to SUR . The SEM estimates show that perception of water scarcity is the most important positive determinant of both types of efficiency, followed by irrigation infrastructure, income and water price. Furthermore, there is a strong negative reverse effect from efficiency on perception.