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Self‐selection in the residential electricity time‐of‐use pricing experiments
Author(s) -
Aigner Dennis J.,
Ghali Khalifa
Publication year - 1989
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.3950040507
Subject(s) - pooling , electricity , econometrics , selection (genetic algorithm) , selection bias , economics , consumption (sociology) , inference , electricity pricing , computer science , population , microeconomics , electricity market , statistics , mathematics , engineering , machine learning , artificial intelligence , electrical engineering , social science , demography , sociology
In none of the existing studies that attempt to pool the results of the five best residential electricity TOU‐pricing experiments is the problem of selection bias addressed. Three of the five experiments used samples of volunteers and it is well known that this can bias results if the ultimate inference to be made applies to the population of non‐volunteers (i.e. the situation of mandatory TOU‐pricing). In this paper we adapt some well‐used methodology for correcting for self‐selection to the five experiments in question and estimate the extent to which its presence biases estimates of the elasticity of substitution between peak and off‐peak electricity consumption. We find, for example, that the bias is upwards of + 24 per cent in the Los Angeles experiment, resulting in a substantial overstatement of the response of customers to mandatory TOU prices. While we stop short of integrating our methodology into a full‐blown pooling framework, users of the EPRI‐sponsored RETOU program should nevertheless be cautioned to the potential biases inherent in forecasts of TOU response derived from it, since no account for the selfselection phenomenon and its consequences was taken in its development.