Presentation by Dr. Ed Rubin, University of Oregon | How do consumers respond to even small shifts in #naturalgas prices, and what might be the impact of other factors on these responses? The talk describes research that deploys causal inference to estimate consumer responses to changes in #naturalgas prices, using data from 600 million California #residential natural gas bills. The research also seeks to estimate the heterogeneity underlying this commonly pooled parameter, with particular attention to seasons and income groups. The research yields insights about the timing for application of fixed costs, fees, and taxes to residential consumers' natural gas bills, and its approach could also be relevant for other kinds of #utilities and sectors.

0:00 - 15:43 - Presentation
15:43 - end - Audience Q&A

About the Presenter: Dr. Ed Rubin's research focuses on environmental/energy economics and inequality—particularly policy impacts, strategic responses to regulation, and measuring exposure/access. Ed is especially interested in combining causally informed econometrics/statistics with data science (machine learning, spatial analysis) to shed new light on previously resolved or unanswered questions. He received his Ph.D. in Agricultural and Resource Economics from the University of California, Berkeley.

This presentation was a part of the Energy Data Analytics Symposium hosted by Duke University on December 8-9, 2020. The Symposium’s theme was “Transforming Energy Systems with Data Science Techniques.”

Learn more about the 2020 Energy Data Analytics Symposium and view all presentations:
https://energy.duke.edu/energy-data-a...
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   • Energy Data Analytics Symposium  

The 2020 Energy Data Analytics Symposium was organized by the Energy Data Analytics Lab at Duke University and was supported by a grant from the Alfred P. Sloan Foundation. Note: Conclusions reached or positions taken by researchers or other grantees represent the views of the grantees themselves and not those of the Alfred P. Sloan Foundation or its trustees, officers, or staff.

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