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

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.

 Graphitization of Small Carbonate Samples for Paleoceanographic Research at the Godwin Radiocarbon Laboratory, University of Cambridge

A new radiocarbon preparation facility was set up in 2010 at the Godwin Laboratory for Palaeoclimate Research, at the University of Cambridge. Samples are graphitized via hydrogen reduction on an iron powder catalyst before being sent to the Chrono Centre, Belfast, or the Australian National University for accelerator mass spectrometry (AMS) analysis. The experimental setup and procedure have recently been developed to investigate the potential for running small samples of foraminiferal carbonate. By analyzing background values of samples ranging from 0.04 to 0.6 mg C along with similar sized secondary standards, the setup and experimental procedures were optimized for small samples. “Background” modern 14C contamination has been minimized through careful selection of iron powder, and graphitization has been optimized through the use of “small volume” reactors, allowing samples containing as little as 0.08 mg C to be graphitized and accurately dated. Graphitization efficiency/fractionation is found not to be the main limitation on the analysis of samples smaller than 0.07 mg C, which rather depends primarily on AMS ion beam optics, suggesting further improvements in small sample analysis might yet be achieved with our methodology.