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Abstract:The upper reaches of a river system are often trapped in the dilemma of choosing between industrial development and headwater protection. One of the solutions is eco-compensation, which, however, is a public-fiscal arrangement lacking inspiration and sustainability. Instead, industrial discharge quota (IDQ) was put forward as a marketized approach: the maximum industrial discharge a river can afford is allocated as quotas and quotas are allowed to be traded. However, what pricing principle in the primary market can IDQ price refer to? How can enough incentives be given to local governments when they are reluctant to implement emission reduction policy? Given that some previous studies have proven the influence of fiscal income and reputation on governments' incentives, this paper introduces these into our model as main factors. Through analysis, two models-government model and enterprise model-are formulated based on opportunity cost theory to deal with this problem. The first sets basic prices and the latter notifies enterprises' behaviors. Then, this paper applies our first model to a sample region, Fogang County in Pearl River Basin. The results demonstrate that the upstream can obtain adequate compensation for their opportunity loss and local governments can be with strong motivation by our method.

We suggest the use of outdegrees from graph theory to rank locations in terms of their contagiousness. We show that outdegrees are equal to the column sums of spatial autoregressive matrices, which may be estimated using econometric methods for spatial panel data. In contrast to outdegree, R is invalid for 'traffic light' shading because it fails to distinguish between the export and import of contagion between sub-national locations. Simulation methods are used to illustrate the concept of outdegrees and its structural determinants in terms of centrality, indigenous contagion and spatial contagion. An empirical illustration is presented for Israel. A secondary criterion for traffic light shading involves the stochastic structure of morbidity shocks, which induce 'spiking' through their autoregressive persistence, conditional heteroscedasticity and diffusion jump parameters.