Evaluating and Predicting Shadow Prices of Water Resources in China and Its Nine Major River Basins

Water pricing plays a crucial role in water resources management. Water shadow price is an important reference in setting water price. It was said that in practice it is almost impossible to obtain water shadow price by solving a linear programming model. In this paper we use water conservancy economy input-occupancy-output tables of the nine Chinese major river basins, and combining input–output analysis method with linear programming method we develop a linear programming model with restrictions on the final demand, total output, trade balance and water availability. We estimate the water shadow prices for industrial water and productive water for the nine Chinese major river basins in 1999 and compared these results with the real industrial water price in China in 1999. Then, for operational purposes and to estimate the shadow prices of industrial water and productive water more easily, and using a Gauss–Newton nonlinear simulation method, we present two nonlinear models that relate the ratio of the volume of water used to the total water resources volume with the shadow prices to predict shadow prices of industrial water and productive water in 2020 and 2030 in China and its nine major river basins.

[1]  Jihad Elnaboulsi,et al.  Nonlinear Pricing and Capacity Planning for Water and Wastewater Services , 2001 .

[2]  R. Martínez-Espiñeira,et al.  Residential Water Demand in the Northwest of Spain , 2002 .

[3]  R. Roson,et al.  The Economic Impact of Water Taxes: A Computable General Equilibrium Analysis with an International Data Set , 2008 .

[4]  Peter H. Gleick,et al.  Water in crisis: a guide to the world's fresh water resources , 1993 .

[5]  E. M. Pint.  Household Responses to Increased Water Rates during the California Drought , 1999 .

[6]  Ariel Dinar,et al.  Markets for Water , 1998 .

[7]  Z. Ouyang,et al.  Environmental water requirements and sustainable water resource management in the Haihe River Basin of North China , 2008 .

[8]  James A. Roumasset,et al.  Valuing indirect ecosystem services: the case of tropical watersheds , 2002, Environment and Development Economics.

[9]  L. Yongjun,et al.  Export and Economic Growth in China:A Demand-oriented Analysis , 2003 .

[10]  M. Giordano,et al.  An empirical analysis of the impacts of irrigation pricing reforms in China , 2007 .

[11]  D. Chicoine,et al.  Evidence on the Specification of Price in the Study of Domestic Water Demand , 1986 .

[12]  Munther J. Haddadin,et al.  Limits of pricing policy in curtailing household water consumption under scarcity conditions , 2008 .

[13]  Chao Bao,et al.  Management Implications to Water Resources Constraint Force on Socio-economic System in Rapid Urbanization: A Case Study of the Hexi Corridor, NW China , 2007 .

[14]  Zhao Liange,et al.  Chinese agricultural water resource utilization: problems and challenges , 2007 .

[15]  A. Fisher,et al.  Price and Non-Price Influences on Water Conservation: An Econometric Model of Aggregate Demand under Nonlinear Budget Constraint , 1999 .

[16]  W. Michael Hanemann,et al.  A discrete/continuous choice approach to residential water demand under block rate pricing , 1995 .

[17]  Shouyu Chen,et al.  Fuzzy pricing for urban water resources: model construction and application. , 2008, Journal of environmental management.

[18]  Michael Nieswiadomy,et al.  Comparing Residential Water Demand Estimates under Decreasing and Increasing Block Rates Using Household Data , 1989 .

[19]  Economic analysis of water resources in Japan: using factor decomposition analysis based on input-output tables , 2005 .