Working Papers
Pollution Taxes as a Second-Best: Accounting for Multidimensional Firm Heterogeneity in Environmental Regulations (with Fan Xia and Bing Zhang)
[Abstract]
This paper documents the first-order welfare effects of firm heterogeneity under a homogeneous emission tax regime. Local and firm-level variations in market power, abatement costs, and abatement benefits can create a gap between optimal and realized emission reduction. We examine this question in the context of China’s highly concentrated cement industry, which was subjected to multiple emission tax changes across time and location between 2011 and 2018. Using a comprehensive firm-level data set that allows us to estimate firm-level responses to regulation, we find substantial heterogeneity in the compliance behavior of firms --- through adjustments in output levels, price, and emission intensity. We then use the structurally estimated firm-level marginal abatement costs to quantify the deviation of local marginal pollution abatement costs from its marginal benefits. The model shows that the gap between observed abatement and production firm responses and the socially optimal responses is explained by two factors: the firm’s market power and the correlation between local abatement costs and benefits. By using variation in market power generated by two data-driven approaches and local abatement costs and benefits, we can empirically assess the importance of each of these two drivers of the suboptimal response to emission taxes. A counterfactual analysis shows that output-based rebates coupled with a homogeneous emission tax can help mitigate the distortion from market power.
Coal Phase-out in a Second-Best Setting: Evidence from China's Winter Heating Ban (with Antonio M. Bento and Bing Zhang)
[Abstract]
As countries transition away from coal to achieve carbon neutrality, natural gas is often promoted as a transitional fuel. However, incomplete sectoral policies and preexisting price distortions can lead to emission leakage, undermining coal reduction efforts. This paper examines China’s 2017 coal-to-gas transition policy, which banned coal in central heating across 28 northern cities, triggering a 70% increase in natural gas prices while coal prices remained stable due to price controls. Using a comprehensive dataset of hourly pollution measures from 1,563 monitors and firm-level emissions and energy consumption data covering around 50% coal consumption in China, we find that instead of reducing coal consumption, the policy led to substantial leakage. Baseline industry composition, the stringency of environmental regulations, and uneven enforcement across polluting firms all contribute to leakage. A back-of-the-envelope calculation suggests that for every ton of coal reduced in the heating sector, coal use increased by 0.26 tons in targeted cities, 2.6 tons in northern non-targeted cities, and 3.07 tons in southern cities. The natural gas price shock shifted production to coal-intensive firms and less regulated firms in targeted cities, increasing overall emissions. We estimate that 23.27% of the coal consumption rebound could have been prevented if coal prices had been liberalized to fluctuate with natural gas prices, as in European markets. Alternatively, a carbon price of 17 RMB (2.4 USD) per ton of carbon dioxide would achieve an equivalent reduction in coal use while preventing leakage. These findings highlight the importance of addressing market distortions to enhance the effectiveness of coal phase-out policies.
[Draft Coming Soon]
Electric Vehicle Sharing: Crowding Adoption Out or In? (with Jonathan A. Libgober) submitted
[Abstract]
We estimate the impact of an Electric Vehicle (EV) sharing program — specifically BlueLA — on EV adoption. This program provides EVs in heavily trafficked areas in several low- to middle-income neighborhoods in Los Angeles. Using data on EV purchases from a subsidy program and a difference-in-differences strategy, we estimate that BlueLA caused at least a 32% increase in new EV adoptions within the zip codes it entered. Although car sharing provides a substitute for car ownership, our findings are consistent with the hypothesis that increasing familiarity with EVs could facilitate adoption.
Does Market Power in India's Agricultural Markets Hinder Farmer Climate Change Adaptation? (with Rajat Kochhar and Jeffrey E. Sun)
[Abstract]
What role do government policies which distort market competition play in impeding farmers' climate change adaptation? We study this question in the context of India, where longer-run adaptation to climate change has been inadequate --- posing a considerable risk to its ~250 million agricultural workers. We exploit spatial discontinuities in intermediary market power, created by state-level laws that restrict farmer-intermediary transactions to the same state, to determine how spatial competition affects farmers' adaptation. We find that a farmer selling in the 75th percentile of the competition index compared to one that faces the 25th percentile of the competition index achieves a 4.9 percent higher output for each additional day of extreme heat. This effect is driven by increased input usage by farmers in anticipation of higher prices after climate shocks, an effect limited only to high competition areas. We then propose and estimate a quantitative spatial trade model with intermediary market power to examine the welfare implications of higher competition for adaptation. Our structural estimates suggest that the farmer's economic loss (i.e. their climate damage function) due to extreme weather could be mitigated by 13.8 percent if government regulation distorting market competition is dismantled. These results highlight the importance of understanding the political economy of reforming these competition-distorting laws to accelerate climate change adaptation.
Using Big Data to Estimate the Environmental Benefits of Congestion Pricing: Evidence from California (with Antonio M. Bento, Rajat Kochhar, and Andrew R. Waxman) submitted
[Abstract]
This paper examines the distributional effect of congestion pricing on local air quality. To first estimate the effect of traffic congestion on local air quality, we combine two unique sources of big data: real-time high-frequency pollution readings obtained from Google Street View cars from the firm Aclima , and real-time data on the speed and flow of vehicles in California freeways from the California Performance Measurement System (PeMS). We find a consistent non-linear localized relationship between vehicle congestion on freeways and localized air pollution, depending on vehicle speeds and weather conditions. We also utilize instrumental variables and the LASSO approach to account for traffic endogeneity using a rich dataset on vehicle accidents. Lastly, we simulate the effect of congestion pricing on traffic redistribution and calculate the induced pollution redistribution using the estimates that link the relationship between traffic and pollution.
Environmental Policy Coordination (with Xiongfei Li)
Non-Academic Writings
[Abstract]
This paper studies how carbon policies in the EU lead to inadvertent environmental regulation adjustments in China. Using a novel dataset containing the universe of Chinese environmental penalties and a comprehensive measure of European sectoral carbon costs, we employ a shift-share measure of the exposure to EU carbon price costs among Chinese cities for identification. We find that higher exposure to export-weighted carbon prices has a sizeable positive impact on environmental regulation stringency. Conversely, industries more reliant on imports from the EU receive slightly fewer penalties. We attribute the stricter policies in Chinese cities primarily to the surge in exports and associated pollution resulting from EU carbon policies. Further empirical analysis shows that increased enforcement targets tradable sectors rather than a city-wide policy switch. However, when local officials adopt more lenient regulations toward sectors negatively affected by higher EU carbon costs, they compensate by imposing more penalties on non-tradable sectors. Our study contributes to the debate on optimal unilateral carbon and trade policies by offering new insights into how domestic carbon pricing can trigger passive environmental policy responses abroad, highlighting the complexities of global environmental policy coordination.
Good for the Environment, Good for the Economy: The Potential of Transportation Electrification Policies to Foster Economic Growth in Greater Los Angeles (with Sam Boysel, Dan Ibarrola, Monica Morlacco, and Kate Weber), Public Exchange at University of Southern California and Los Angeles Cleantech Incubator, May 2022