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CSQIEP Environmental & Energy Economics Session

Paper Session

Saturday, Jan. 4, 2025 2:30 PM - 4:30 PM (PST)

Hilton San Francisco Union Square, Yosemite B
Hosted By: American Economic Association & Committee on the Status of LGBTQ+ Individuals in the Economics Profession
  • Chair: Maureen Cropper, University of Maryland

Why Do Central Banks ‘Go Green’?

Alina Azanbayev
,
EBS University
Jan-Christoph Rulke
,
EBS University

Abstract

Central banks are integral to financial systems and increasingly active in promoting environmental sustainability. Our research is the first to empirically investigate the determinants driving central banks towards green policies. Analyzing the green initiatives of G20 central banks, we explore the trade-offs involved in green central banking, and particularly how these efforts align with the traditional mandate of price stability. Our findings reveal a green-inflation trade-off, i.e. central banks with lower inflation rates are more likely to adopt green policies. Specifically, a one percentage point decrease in the medium-term inflation rate increases the probability of a central bank going green by 0.72 points. This trade-off adds a complex layer to the decision-making processes of central banks as they balance price stability with environmental objectives. We also identify conditions like the natural resource availability as key facilitators of green initiatives. Regarding the discussion of policy implications, our study emphasizes that a low inflation environment is essential for the adoption of green policies. By investigating the motivations, economic implications, and policy contexts of green central banking, our study offers a nuanced understanding that can guide the integration of environmental considerations into monetary policy frameworks.

Impacts of Uncertainty in Transmission Interconnection on Energy Transition

Xiaochen Sun
,
New Mexico State University

Abstract

The paper investigates a three-stage interconnection process that electric transmission system operators mandate for generators seeking grid access. Recent years have seen a surge in interconnection requests alongside a persistent trend of high project withdrawals, leading to a challenging backlog. This backlog poses a significant threat to electric grid resilience and energy transition, which is essential to combat climate change. A key reason for the high withdrawal rates is the uncertainty associated with the interconnection cost allocation under current policy. To estimate this impact, the study applies a dynamic discrete choice model with Bayesian learning to capture the evolving means and variances of interconnection cost signals across different stages of the process, as cost uncertainty decreases with progress. Parameter estimates show that generators are more likely to stay when cost uncertainty is high, which indicates the benefit of learning. Furthermore, the effect of network upgrade costs varies by fuel source, with wind generators being most sensitive. The paper presents two counterfactual analyses to inform discussions concerning FERC Order 2023. First, I show that interconnection studies should prioritize providing more accurate information early in the process to encourage early learning, thus facilitating early decision-making to resolve backlog issues. Second, I find increasing withdrawal penalties may not significantly address backlog concerns. Additionally, subsidy policies regarding network upgrades may be most effective when tailored to specific fuel types.

The Impact of Natural Disasters on Risk Preferences and Subjective Beliefs: Evidence from Typhoon Ketsana

Marcos Sugastti
,
University of California-Davis
Sean Kiely
,
University of California-Davis and NBER

Abstract

We study how individuals’ risk preferences and subjective beliefs about future shocks change after natural disasters. We focus on the impact of Typhoon Ketsana in 2009—one of the most devastating storms to hit Southeast Asia in recent times. Our analysis reveals that individuals who were affected by the typhoon become more risk averse a year after landfall. This effect persists up to four years later. We base our findings on household-level panel data from Vietnam and a difference-in-differences strategy with a continuous treatment variable that exploits variation in the intensity of the typhoon. We conclude that a standard deviation (SD) increase in excess rainfall during the typhoon leads to a 0.23 SD increase in risk aversion one year after landfall, and a 0.25 SD increase four years after landfall. Moreover, individuals exposed to higher excess rainfall are more likely to believe that storms will not transpire in the following five years or will occur less frequently. This result supports the view that the main observed effects on risk preferences indeed reflect updated risk attitudes, rather than changes in the subjective probability structure assigned to the occurrence of storms. Our paper contributes to the literature that empirically documents how negative shocks may alter risk preferences and helps illuminate the way climate-related hazards can induce changes in the attitudes of individuals.

Implications of Wildfire-Derived PM2.5 for U.S. Air Quality Regulation

Andrew Wilson
,
Columbia University

Abstract

Growing wildfire activity across North America generates large amounts of smoke that can travel long distances. Characterizing the influence of this smoke on surface air quality is critical for regulation of air quality and protection of public health. Here we provide granular, daily estimates of smoke fine particulate matter (PM2.5) concentrations across the contiguous U.S. and use them to assess the influence of wildfire smoke on surface PM2.5 from 2006 to 2023, using a combination of surface measurements, satellites, and machine learning. Each year from 2020 to 2023, population-average smoke PM2.5 exposures were 2.6–6.7 times higher than the 2006 to 2019 average and exposure periods were twice as long. Despite wildfire smoke being historically more common in the Western U.S., the worst 5 days for population-average smoke exposure in our sample period all occurred in 2023, a year with limited Western exposure. We estimate that wildfire smoke is pushing 34% of monitoring stations above the recently-updated ambient air quality standards, necessitating increased use of extreme event exemptions to remain within regulatory limits; we show that such use could become increasingly challenging. Absent wildfire smoke, we estimate that PM2.5 concentrations would have continued to improve throughout the contiguous U.S.

Discussant(s)
Stephie Fried
,
Federal Reserve Bank of San Francisco
Karen Palmer
,
Resources for the Future
Maureen Cropper
,
University of Maryland
Joshua Linn
,
University of Maryland-College Park
JEL Classifications
  • Q4 - Energy
  • Q5 - Environmental Economics