Air pollution kills more people than AIDS and malaria combined, and climate change is one of the biggest threats to human survival and well-being in the twenty-first century. Motivated by these problems, my research explores how incentives shape environmental politics, especially in developing countries.
I believe interdisciplinary techniques can generate new data, reveal new patterns, and offer new insights into critical questions. Hence, my research integrates relevant techniques from political science, engineering, earth systems, computer science, and other disciplines to understand the problems of energy and the environment better.
*Please email me for working paper drafts if they are not already posted.
Shen, Shiran Victoria. “The Political Pollution Cycle.” (First draft: November 2014. Current draft: September 2018). Under review. [SSRN]
— Winner of the 2017 Paul A. Sabatier Award. Award by the American Political Science Association for the best paper on science, technology, and environmental politics presented at APSA 2016.
— Winner of the 2018 Malcolm Jewell Award. Award by the Southern Political Science Association for the best graduate student paper presented at SPSA 2017.
Building on the principal-agent (P-A) tradition with more recent insights, this paper challenges the implicit assumption in existing P-A models that the level of local compliance in autocracies like China is constant over time. Studying the critical case of air pollution control policies to fathom the effect of political incentives on policy implementation over time, I advance a theory of what I call the “political pollution cycle.” I theorize that local agents cater to the policy prioritization of the principal and in the process foster systematic regional patterns of air quality over time. Using remote sensing, box modeling, observational data, and qualitative field research, I find that top prefectural leaders in China ordered laxer regulation of pollution towards the end of their tenure so that the delivery of economic achievements and social stability boded well for their career advancement. Such strategic implementation came unintentionally with tremendous human costs.
Shen, Shiran Victoria. “Pricing Carbon to Contain Violence.” Under review.
Violence is destructive to social order, economic growth, and the human condition. The annual total cost of violence is estimated to be 11 percent of the world’s GDP. However, security has rarely made its way into economic models. In the meantime, increasing scientific evidence points to an active link between climate change and the incidence of interpersonal and inter-group violence. This study connects the climate-economy and the climate-violence systems by putting forth a new method to internalize the costs of climate-induced violence in the established MERGE integrated assessment model. It finds that such internalization can double the carbon price, a relationship that holds across different specifications regarding climate sensitivity, GDP growth rate, and the willingness to pay (WTP) to avoid nonmarket climate damages. Normatively, under the realistic assumption that the WTP is at 1 percent of regional income, the avoided costs from climate-induced violence in sub-Saharan Africa is modeled to reach 3.69 percent of the region’s GDP in 2200, a figure very significant for an area that is already riddled with underdevelopment and violence.
Shen, Shiran Victoria, Bruce E. Cain, and Iris S. Hui. “Public Receptivity in China towards Wind Energy Generators: A Survey Experimental Approach.” Revised & Resubmitted to Energy Policy. [SSRN]
China leads the world’s wind energy market, but little has been written about public receptivity towards wind energy generators in China. To fill this gap, we pursue a survey experimental approach to examine explanations based on evidence from OECD countries as well as the importance of public knowledge in augmenting public acceptance of wind energy generators in China. We find that Chinese respondents are sensitive to siting near their residences, to cost considerations when imposed on them directly, to wildlife externalities, and to noise from turbines. Interestingly, Chinese respondents seem to be concerned about radiation, a finding unprecedented in the literature, and are less assured by scientific assurances that radiation is not a problem. Instead, the Chinese government is best suited to address concerns about this topic. Targeted information provision to the public can improve public knowledge about aspects of wind energy of concern. Hence, China can possibly pursue a transition to wind energy more quickly not just because it has an authoritarian government determined to get things done, but also because it can provide relevant information to reduce potential public resistance
Shen, Shiran Victoria. “Using Machine Learning to Find Environmentally At-Risk Communities.”
Environmental health persists as a genuine concern in many US localities. However, public agencies often face limited capacity and resources to collect comprehensive environmental health data. Inspired by CalEnviroScreen, an environmental health assessment tool used to identify environmentally at-risk communities in California, I calculate pollution burden scores at the census tract level for the entire contiguous United States. Pollution burden is a composite score that encompasses 12 environmental (air, water, waste) indicators. I combine the actual pollution burden indicator data with predicted statistics using machine learning. I create an interactive, publicly accessible National Pollution Burden Map using ArcGIS Online.
Shen, Shiran Victoria. “Failing Great Expectations: How Local Incentives Undermine Sustainable Energy Transition in China.”
Select Works in Progress
“Political Pollution Cycle: Evidence from Mexican Municipalities” (with Edgar Franco and Cesar Martinez)
Refereed Journal Articles
Shao, Qinglong, and Shiran Shen. “When Reduced Working Time Harms the Environment: A Panel Threshold Analysis for EU-15, 1970-2010.” Journal of Cleaner Production 147 (2017): 319 – 329. Journal 5-year IF: 6.35.
Conventional wisdom has it that less working time is good for mitigating environmental pressure. Only a few studies have documented contradictory evidence. In this paper, we use panel threshold model, which is arguably the first of its kind in environmental analysis, to further document nonlinear relationships between working time and environmental pressure in EU-15 countries between 1970 and 2010. We find that the sign of this relationship shifts from positive to negative, as the working hours per worker decreases; France, Denmark, Germany, and the Netherlands experienced more environmental pressure with shorter working week. To the backdrop of reduced working time during our research period, our paper sheds new light on the traditional view of “the less, the better,” as curtailing working time beyond certain thresholds may inadvertently incur exacerbation of environmental pressure.