The political pollution cycle : an inconvenient truth and how to break it
Abstract/Contents
- Abstract
- Scholars have applied the principal-agent (p-a) framework widely to explain policy implementation in democratic and authoritarian contexts alike. The conventional wisdom is that the misalignment of interests and information asymmetry between the principal and the agent contribute to policy distortion on the ground. Building on the p-a tradition with more recent insights, this dissertation challenges the implicit assumption in existing p-a models that the level of local compliance is constant over time, especially in autocracies like China. The dissertation centers on the critical case of air pollution control policies. Air pollution is the biggest environmental health threat to humanity in the twenty-first century, causing one in eight deaths and endangering the health of 95 percent of the world's population. As the dissertation demonstrates, politics play a major role in the regulation of air pollution. Furthermore, air pollution is highly responsive to the intensity and scale of regulatory efforts (i.e., very little time lag). Hence, the case of air pollution has offered a unique opportunity to fathom the effect of political incentives on policy implementation over time. This dissertation offers a new answer for when environmental policy implementation becomes deficient or excessive while extant works have almost unanimously focused on why. Using China as a natural experiment, this dissertation shows that local agents in China catered to the policy prioritization of the principal and in the process fostered local political regulation cycles. These cycles resulted in regional patterns of air pollution over time. Towards the end of a local leader's tenure in office, s/he would ease environmental regulation when the economy and stability were highly priced by the principal, leading to what I call "political pollution cycles." When the environment became significantly valued by the principal, s/he would order more environmental regulation near the end of tenure, resulting in dampened political pollution cycles, or even what I call "political environmental protection cycles." Both types of political regulation cycles incurred tremendous welfare losses and human costs. Different from extant publications, while dirty economic growth (or degrowth) explains why the amount of pollution, regulatory relief (or pressure) ordered by career-minded local leaders or politicians accounts for the systematic variation in air quality over time. Combining empirical evidence from China and some very preliminary analysis based on the United States and Mexico, I argue that electoral and career incentives of local politicians or leaders influence their prioritization of multiple policy goals over time, with systematic environmental consequences, and this may hold across regime types.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Shen, Shiran Victoria | |
|---|---|---|
| Degree supervisor | Cain, Bruce E | |
| Degree supervisor | Oi, Jean C. (Jean Chun) | |
| Thesis advisor | Cain, Bruce E | |
| Thesis advisor | Oi, Jean C. (Jean Chun) | |
| Thesis advisor | Sweeney, James L | |
| Thesis advisor | Tomz, Michael | |
| Degree committee member | Sweeney, James L | |
| Degree committee member | Tomz, Michael | |
| Associated with | Stanford University, Department of Political Science. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Shiran Victoria Shen. |
|---|---|
| Note | Submitted to the Department of Political Science. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Shiran Shen
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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