Summary: | China's key forested region is located in the northeast. This region consists of state forest enterprises which manage harvesting and reforestation and have represented the most important source of wood supplies since the 1950s. Deforestation is a major problem there, however, and has resulted in several central government reforms. We develop a framework for assessing the social cost of state forest enterprise deforestation. We first develop a two-principal, one-agent model that fits the federalistic organization state forests, in that state forest managers make (potentially hidden) decisions under influence of provincial and central government policies and quotas meant to direct manager behavior. This model is used to derive an expression of the social cost of these hidden actions as well as a comparison of first and second best government policies. We then use panel data from a survey conducted by the Environmental Economics Program in China (EEPC) to compute social welfare losses and use a regression approach to confirm the main factors in these costs in practice. A sensitivity analysis shows that lower harvesting limits and a more accurate monitoring system are the keys to lowering social welfare loss. These are more important than conventional instruments used by the governments such as wages for managers that achieve certain targets. Through regression analysis we find that the remote areas with a higher percentage of mature natural forests are the ones that will always have the highest social welfare loss. These areas are the hardest to monitor, but our results show they must be a critical focus moving forward. === M.S. === China's key forested region is located in the northeast. This region consists of state forest enterprises which manage harvesting and reforestation and have represented the most important source of wood supplies since the 1950s. Deforestation is a major problem there. We develop a framework for assessing the damage to the society because of deforestation. We develop a theoretical model to describe the forest management structure, in which state forest managers make (potentially hidden) decisions under influence of provincial and central government policies. This model is used to derive an expression of the damage. We then use data from a survey conducted by the Environmental Economics Program in China (EEPC) to compute the damage and confirm the main factors in these damages in practice. We find that lower harvesting limits and a more accurate monitoring system are the keys to lowering the damage. These are more important than conventional instruments used by the governments such as wages for managers that achieve certain targets. We also find that the remote areas with a higher percentage of mature natural forests are the ones that will always have the largest damage. These areas are the hardest to monitor, but our results show they must be a critical focus moving forward.
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