Water pricing policy in rural China

The overall goal of this dissertation is to use a new approach to analyze the effects of water pricing policies on water use, crop production and producer income in rural China. To meet this overall goal, in the first part of the dissertation, a two-step approach is developed to select the optimal level of disaggregation for estimating water demand parameters. In the first step the Generalized Maximum Entropy (GME) method is used to estimate three sets of models: a set of community-level models (the least constrained model---which constrains the behavior of producers to only be equal within communities but allows for behavior to differ across communities); a province-level model (the most constrained model---which constrains the behavior of all producers to be equal across the entire province); and a set of county-level models. I estimate these three sets of models with household level data. In the second step I compare the ability of each set of models to capture the heterogeneity in the data and their predictive abilities in order to determine the optimal level of disaggregation.; In the second part of the thesis, I will pursue two objectives. The first objective is to estimate water demand parameters that capture the constrained nature of water demand in rural China. A constrained-primal approach is adopted to estimate a set of water demand parameters for each county. This approach treats shadow values (defined as the gap between the current cost of water and the true value of water that is caused by water resource constraints) as parameters to be estimated and estimates them jointly with other water demand parameters. The second objective is to analyze the effects of water pricing policies. Estimates of water demand parameters are first used in simulations to compare two water pricing policies: one policy does not take into account shadow values and the other does. The latter is shown to be effective in inducing water savings. Simulation results are then used to analyze the effects of increasing water prices on crop production and rural income.