22 February 2021
Our model allows us to evaluate household-level elasticities in price elasticity of demand. The counterfactual analysis shows that a seemingly welfare-improving policy might trigger the consumers’ strategic behaviour and, ultimately, be contrary to the original purpose.
Quantitatively, our results reasonably explain the distribution of total demand and time-of-use consumption in the data. After controlling for the heterogeneous preference of time-sharing consumption, our estimate confirms an “uncontrollable final consumption” phenomenon, captured by consumption errors in our model. We find that consumer errors directly lead to the final consumption being on average 1.5% higher than household consumption optimal value. Our counterfactual analysis also quantifies the impact of multidimensional nonlinear pricing schedules on the price elasticity. On average, for every 1% increase in price, the total power demand will decrease by 1%.
During the past 18 months, I have conducted a number of research activities. I hosted the academic visit of the co-investigator, Dr. Xintong Han from Concordia University to the University of Edinburgh. This visit boosted our collaboration and Prof. Han gave a seminar talk in the Management Science and Business Economics (MSBE) group. Also, to run the structural estimation, we rented a cloud computing server for two years, which means that it could not only be used to serve the purpose of this project but also for other research that needs strong computing power. Therefore, the spillover effect across projects is also significant.
Moreover, our research assistant also delivered excellent results in time. All these efforts have been condensed into our working paper “Multidimensional Nonlinear Pricing: Evidence from Energy Consumption with a Mixture Pricing Mechanism”. The paper has been submitted to one of the top journals in the field of environmental economics, and currently in its reviewing process.
Impact-wise, we delivered two seminars. One is in the Centre for Competition Policy, the University of East Anglia, participants included scholars and policymakers, and we received very useful feedback. The other one is at Zhejiang University in Hangzhou, where the data was generated. In Particular, several experts from the Electric Power Bureau of Zhejiang Province (the public agent in the energy field) attended the seminar. They were very interested in the policy insight of our paper and invited us to give a further talk. However, the trip was postponed to November 2021 due to the Covid-19 pandemic.
Since we have built connections with the public agents and relevant regulators, In the future, we would attempt to approach more administrative data and conduct broader analysis to help better understand consumers’ energy consumption structure. By combining factory cost structure with data on industrial and office electricity usage, we could address the environmental and climate concerns, and conduct more detailed and reliable social welfare analysis as well.
Tong Wang is Lecturer in Business Economics at the University of Edinburgh Business School