 Besides their applicability to physical measurement, model-based analyses also shed light on measurement in economics. Like physical quantities, values of economic variables often cannot be observed directly and must be inferred from observations based on abstract and idealized models. The nineteenth century economist William Jevons, for example, measured changes in the value of gold by postulating certain causal relationships between the value of gold, the supply of gold and the general level of prices (Hoover and Dowell 2001: 155–159; Morgan 2001: 239). As Julian Reiss (2001) shows, Jevons’ measurements were made possible by using two models: a causal-theoretical model of the economy, which is based on the assumption that the quantity of gold has the capacity to raise or lower prices; and a statistical model of the data, which is based on the assumption that local variations in prices are mutually independent and therefore cancel each other out when averaged. Taken together, these models allowed Jevons to infer the change in the value of gold from data concerning the historical prices of various  goods.[19]