Latent vs. Observed Variables: Analysis of Irrigation Water Efficiency Using SEM and SUR

Jianjun Tang, Henk Folmer

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)173-185
Number of pages13
JournalJournal of Agricultural Economics
Issue number1
Early online date20 Oct 2015
Publication statusPublished - Feb 2016


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