Data and Code for: Misunderstanding nonlinear prices: Evidence from a natural experiment on residential electricity demand
Principal Investigator(s): View help for Principal Investigator(s) Blake Shaffer, University of Calgary
Version: View help for Version V1
Name | File Type | Size | Last Modified |
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CODE | 09/30/2019 01:19:PM | ||
DATA | 09/30/2019 01:20:PM | ||
MATLAB | 09/30/2019 01:20:PM | ||
README.pdf | application/pdf | 328.4 KB | 09/30/2019 09:22:AM |
Project Citation:
Shaffer, Blake. Data and Code for: Misunderstanding nonlinear prices: Evidence from a natural experiment on residential electricity demand. Nashville, TN: American Economic Association [publisher], 2020. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-07-23. https://doi.org/10.3886/E111481V1
Project Description
Summary:
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This paper examines how consumers respond to nonlinear prices. Exploiting a natural experiment with electricity consumers in British Columbia, I find evidence that some households severely misunderstand nonlinear prices---incorrectly perceiving that the marginal price applies to all consumption, not simply the last unit. While small in number, the exaggerated responses by these households have a large effect in aggregate, masking an otherwise predominant response to average price. Previously largely unexplored in the literature, this type of misunderstanding has important economic, policy and methodological implications beyond electricity markets. I estimate the welfare loss for these households to be the equivalent of 10% of annual electricity expenditure.
Scope of Project
Subject Terms:
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Electricity demand;
nonlinear prices;
misperception;
heterogeneity
JEL Classification:
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C23 Panel Data Models • Spatio-temporal Models
C24 Truncated and Censored Models • Switching Regression Models • Threshold Regression Models
C26 Instrumental Variables (IV) Estimation
D12 Consumer Economics: Empirical Analysis
Q41 Demand and Supply • Prices
C23 Panel Data Models • Spatio-temporal Models
C24 Truncated and Censored Models • Switching Regression Models • Threshold Regression Models
C26 Instrumental Variables (IV) Estimation
D12 Consumer Economics: Empirical Analysis
Q41 Demand and Supply • Prices
Geographic Coverage:
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British Columbia
Time Period(s):
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2005 – 2013
Collection Date(s):
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2005 – 2013
Universe:
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All residential electricity accounts (households) in the City of New Westminster and the surrounding 3-digit postal codes served by BC Hydro.
Data Type(s):
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administrative records data;
program source code
Methodology
Unit(s) of Observation:
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Account (household)
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