scholarly journals Hysteresis and the Welfare Effect of Corrective Policies: Theory and Evidence From an Energy-Saving Program

2021 ◽  
Author(s):  
Francisco J M Costa ◽  
François Gerard
Keyword(s):  
2019 ◽  
Author(s):  
Francisco J M Costa ◽  
François Gerard

This paper provides stark evidence of hysteresis -- the failure of an effect to reverse itself as its underlying cause is reversed -- in energy demand. We estimate that half of the 23%-reduction in residential electricity use caused by a 9-month-long policy that was imposed on millions of Brazilians has persisted for at least 12 years. We examine the implications of our finding by extending the traditional welfare analysis of corrective policies to allow for hysteresis. Our estimate highlights that failing to take hysteresis into account could severely bias the welfare evaluation of policies aimed at reducing (long-run) energy demand.


2001 ◽  
Vol 32 (3) ◽  
pp. 133-141 ◽  
Author(s):  
Gerrit Antonides ◽  
Sophia R. Wunderink

Summary: Different shapes of individual subjective discount functions were compared using real measures of willingness to accept future monetary outcomes in an experiment. The two-parameter hyperbolic discount function described the data better than three alternative one-parameter discount functions. However, the hyperbolic discount functions did not explain the common difference effect better than the classical discount function. Discount functions were also estimated from survey data of Dutch households who reported their willingness to postpone positive and negative amounts. Future positive amounts were discounted more than future negative amounts and smaller amounts were discounted more than larger amounts. Furthermore, younger people discounted more than older people. Finally, discount functions were used in explaining consumers' willingness to pay for an energy-saving durable good. In this case, the two-parameter discount model could not be estimated and the one-parameter models did not differ significantly in explaining the data.


2018 ◽  
pp. 143-149 ◽  
Author(s):  
Ruijie CHENG

In order to further improve the energy efficiency of classroom lighting, a classroom lighting energy saving control system based on machine vision technology is proposed. Firstly, according to the characteristics of machine vision design technology, a quantum image storage model algorithm is proposed, and the Back Propagation neural network algorithm is used to analyze the technology, and a multi­feedback model for energy­saving control of classroom lighting is constructed. Finally, the algorithm and lighting model are simulated. The test results show that the design of this paper can achieve the optimization of the classroom lighting control system, different number of signals can comprehensively control the light and dark degree of the classroom lights, reduce the waste of resources of classroom lighting, and achieve the purpose of energy saving and emission reduction. Technology is worth further popularizing in practice.


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