2017
DOI: 10.1016/j.advwatres.2016.08.013
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To trade or not to trade: Link prediction in the virtual water network

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Cited by 48 publications
(24 citation statements)
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“…By exploring the impact of multiple factors, such as embedded water, population, GDP, geographical distance, arable land, and dietary demand, the main drivers of virtual water flow appear to be GDP, population, and geographical distance with a nonnegligible effect of exporter production (Tamea et al, ). Subsequent work has leveraged this information to explore both link and flux predictions, population, geographical distance, and GDP strongly controlling link activation and the fluxes along those links (Tuninetti et al, ). Econometric analyses have been used to investigate the extent to which water is a source of comparative advantage (Debaere et al, ), in addition to the classic factors (i.e., labor, capital, and land, Wichelns, , ) typically considered by international trade theories.…”
Section: Globalization Of Food and Watermentioning
confidence: 99%
“…By exploring the impact of multiple factors, such as embedded water, population, GDP, geographical distance, arable land, and dietary demand, the main drivers of virtual water flow appear to be GDP, population, and geographical distance with a nonnegligible effect of exporter production (Tamea et al, ). Subsequent work has leveraged this information to explore both link and flux predictions, population, geographical distance, and GDP strongly controlling link activation and the fluxes along those links (Tuninetti et al, ). Econometric analyses have been used to investigate the extent to which water is a source of comparative advantage (Debaere et al, ), in addition to the classic factors (i.e., labor, capital, and land, Wichelns, , ) typically considered by international trade theories.…”
Section: Globalization Of Food and Watermentioning
confidence: 99%
“…These trading communities evolve over time, and many trade links are created and dissolved every year (Carr et al, ). Due to the strong effect of trade community structures and on the trade‐offs associated with virtual water, a number of studies attempt to identify the factors driving the structure of the trade network (e.g., Dalin, Suweis, et al, ; D'Odorico et al, ; Fracasso, ; Konar et al, ; Sartori et al, ; Suweis et al, ; Tamea et al, ; Tuninetti et al, ). Yet identification of primary drivers is challenging because variables that represent central features of a virtual water trade system, such as GDP or population, may be simultaneously a determinant and an outcome of trade (see section for a discussion of causal relationships).…”
Section: Problem 2: Theoretical Explanatory Powermentioning
confidence: 99%
“…In recent years, the virtual water network related to internationally traded food commodities has been investigated to disclose its temporal patterns and dynamics (Carr et al, ; Dalin et al, ; Tuninetti et al, ), and it has been recognized that virtual water trade is mainly driven by socioeconomic factors rather than water resources availability (D'Odorico et al, ; Tamea et al, ; Yang & Zehnder, ; Zhao et al, ). A large number of outsourcing patterns of water consumption has been linked to the unsustainable use of freshwater resources worldwide (Dalin et al, ; Lenzen et al, ; Marston et al, ).…”
Section: Introductionmentioning
confidence: 99%