The Social Cost of Fiscal Federalism and the Depletion of China’s Native Forests

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...

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Bibliographic Details
Main Author: Wang, Haoyu
Other Authors: Forest Resources and Environmental Conservation
Format: Others
Language:en_US
Published: Virginia Tech 2021
Subjects:
Online Access:http://hdl.handle.net/10919/103524
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spelling ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-1035242021-07-16T05:26:42Z The Social Cost of Fiscal Federalism and the Depletion of China’s Native Forests Wang, Haoyu Forest Resources and Environmental Conservation Amacher, Gregory S. Xu, Jintao Cobourn, Kelly M. Schons Do Valle, Stella Zucchetti Deforestation Two-principal-one-agent model Social welfare loss Fiscal federalism 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. 2021-05-26T18:19:18Z 2021-05-26T18:19:18Z 2021-05-06 Thesis http://hdl.handle.net/10919/103524 en_US Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ ETD application/pdf application/pdf Virginia Tech
collection NDLTD
language en_US
format Others
sources NDLTD
topic Deforestation
Two-principal-one-agent model
Social welfare loss
Fiscal federalism
spellingShingle Deforestation
Two-principal-one-agent model
Social welfare loss
Fiscal federalism
Wang, Haoyu
The Social Cost of Fiscal Federalism and the Depletion of China’s Native Forests
description 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.
author2 Forest Resources and Environmental Conservation
author_facet Forest Resources and Environmental Conservation
Wang, Haoyu
author Wang, Haoyu
author_sort Wang, Haoyu
title The Social Cost of Fiscal Federalism and the Depletion of China’s Native Forests
title_short The Social Cost of Fiscal Federalism and the Depletion of China’s Native Forests
title_full The Social Cost of Fiscal Federalism and the Depletion of China’s Native Forests
title_fullStr The Social Cost of Fiscal Federalism and the Depletion of China’s Native Forests
title_full_unstemmed The Social Cost of Fiscal Federalism and the Depletion of China’s Native Forests
title_sort social cost of fiscal federalism and the depletion of china’s native forests
publisher Virginia Tech
publishDate 2021
url http://hdl.handle.net/10919/103524
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