Author: Brianna Kong

University of California, Berkeley

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“Will Cleaning Up the Local Environment Narrow or Widen Inequality?”

Time: 12:10pm-1:30pm

Note: We will send out a notice in the future when this is rescheduled.

Abstract: If cleaning up a local environment also raises prices, does that widen or narrow inequality? We combine an equilibrium sorting model characterizing location choices with a new approach to causally estimate the impact of a cleaner environment on location utility to answer this question. We estimate the model leveraging a plausibly exogenous change in the local environment due to shale gas propensity, together with spatially-granular bilateral migration, air quality, and emissions data. Our preliminary results characterize relative welfare changes by racial groups under the observed environmental quality improvements, as well as simulated under counterfactual environmental policies. The results aim to quantify the connection between equity oriented place-based environmental policy and residential location choices.

Rice University

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Liquid Markets: An Empirical Analysis of a Water Exchange

Time: 12:10pm-1:30pm

Location: 241 Giannini (please bring your own lunch)

Abstract: This paper empirically analyzes the performance of one of the world’s most developed water exchanges, which operates as a primitive limit order market. Upon modeling participants’ incentives to shade their order prices and their choice between limit and market orders, I identify the distribution of participants’ willingness to pay (or accept) from the observed orders and trades. The model flexibly allows for dynamics, risk aversion, and default behavior. Counterfactual simulations suggest the observed exchange attains substantially lower trade surplus than periodic uniform-price market clearing. Droughts exacerbate the gap in surplus per unit traded. The exchange exhibits noticeable price dispersion, which enables suboptimal buyer-seller matching and incentivizes price shading.

Stanford University

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“The Growing Risk and Burden of Wildfire Smoke”

Time: 12:10pm-1:30pm

Location: 241 Giannini (please bring your own lunch)

Abstract: We study the growing societal burden of wildfire smoke. Using a combination of remote sensing, machine learning, and causal inference, we quantify how exposure to wildfire-sourced particulate matter is changing across the contiguous US. We then use this information in a number of downstream tasks: we develop a new metric of wildfire severity related to population smoke exposures, we quantify the contribution of wildfire smoke to overall pollution trends, and we link smoke exposures to the universe of emergency department visits in CA to understand health impacts.

Cornell University

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“Attribute-based Subsidies and Market Power: an Application to Electric Vehicles”

(co-authored with Hyuk-soo Kwon and Shanjun Li)

Time: 12:10pm-1:30pm

Location: 241 Giannini (please bring your own lunch)

Abstract: Attribute-based subsidies are commonly used to promote the diffusion of energy-efficient products in industries with significant market power. We first develop a theoretical framework for optimal policy design that incorporates endogenous product attributes, environmental externalities, and market power. We then estimate an equilibrium model with endogenous product attributes using comprehensive data on China’s vehicle market. Simulations show that relative to attribute-based subsidies, uniform subsidies favor small and environmental-friendly vehicles but exacerbate the quantity distortion from market power for high-quality products. In contrast, subsidies based on the driving range and battery capacity or vehicle weight generate a large consumer surplus by improving product quality and mitigating market power. Among commonly used policies, capacity-based subsidies induce attributes valued by consumers, mitigate market power, and lead to the largest welfare gain at a moderate loss of environmental benefit. These findings highlight the importance of incorporating product-attribute choices and market power considerations in designing attributes-based policies.

University of Southern California

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“Welfare and Congestion”

Time: 12:10pm-1:30pm

Location: 241 Giannini (please bring your own lunch)

Abstract: Sufficient statistics have proven to be a very useful tool for measuring welfare changes. Our paper extends this literature in three ways: First, we extend the theory for estimating the welfare impacts of price changes by including externalities that affect consumption decisions. Second, we apply the theory to an area of growing policy importance: congestion pricing. We develop estimates of peak and off-peak demand elasticities for urban mass transit in San Francisco using a large natural experiment and a natural field experiment that subsidized travel across 4.8 million trip sessions. Third, we estimate the welfare impacts for these subsidies using a sufficient statistics approach and a marginal value of public funds (MVPF) approach, and provide a way to connect these approaches. Our analysis suggests that off-peak subsidies can increase welfare, but the positive effects are reduced when consumers take the decisions of others into account compared to when they do not. We also find a large variation in the welfare impacts of shifting travel to different periods, which is explained by differences in demand and congestion characteristics. Finally, we show that the targeting of subsidies can increase welfare, but need not do so if the regulator does not have accurate information on demand.

Yale University

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“Money (Not) to Burn: Payment for Ecosystem Services for Crop Residue Burning”

Time: 12-1:30pm Pacific

Location: Zoom / Passcode: 930535

Harvard University

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“Does Directed Innovation Mitigate Climate Damage? Evidence from US Agriculture”

[joint with Trade/ARE/EI]

Abstract:

This paper studies how innovation reacts to climate change and shapes its economic impacts, focusing on US agriculture. We show in a model that directed innovation can either mitigate or exacerbate climate change’s economic damage depending on whether new technology is on average a substitute for or complement to favorable climatic conditions. To study the technological response to climate change empirically, we combine data on the geography of agricultural production, shifting temperature distributions, and crop-specific temperature tolerance to estimate crop-specific exposure to damaging extreme temperatures; we then use a database of crop-specific biotechnology releases and patent grants to measure technology development. We first find that innovation has re-directed toward crops with increasing extreme temperature exposure and show that this effect is driven by types of agricultural technology most related to environmental adaptation. We next find that US counties’ exposure to innovation significantly dampens the local economic damage from extreme temperatures, and estimate that directed innovation has offset 20% of the agricultural sector’s climate damage since 1960 and could offset 15% of projected damage by 2100.

Time: 2:10-3:30pm Pacific

Location: 597 Evans