ABSTRACTA residential water demand equation is estimated using the only data set on water consumption that contains time series (monthly) observations on individual customers facing an increasing block rate schedule. Because the price of water both determines, and is determined by, usage, ordinary least squares estimation will yield biased estimates. Thus, two‐stage least squares and instrumental variables techniques are used. The estimated coefficients on lawn size, weather, house size, and income have the expected signs and are statistically significant. However, there is not any significant response to changes in water price, perhaps due to the relatively low cost of wate