HCP Q&A with Researchers: The Harvard-China Project on Energy, Economy and Environment, based at the Harvard John A. Paulson School of Engineering and Applied Sciences, is initiating a new Q&A series with our research contributors. This is the fourth.
Harvard-China Project Q&A: Mun S. Ho
“The Politics and Economics of Electricity Reform and Environmental Protection in China: PART 2"
Mun S. Ho, Visiting Scholar with the Harvard-China Project and Visiting Scholar with the Resources for the Future, is an economist working on productivity measurement and environmental policy analysis. His two main research interests include using a multi-sector model of the Chinese economy to analyze energy and environmental policies, and studying energy demand – particularly electricity demand – using survey data of households and enterprises.
Last week the Harvard-China Project featured part one of an interview with Mun on the supply side of the power system. He discussed the unusual institutional features of the electricity system in China; how the state owns nearly all the generation assets and transmission facilities; and how the governance is decentralized down to provincial authorities. In part two of our discussion, below, Mun explores the demand side of the electricity market, including how household consumption and human behavior affects use and demand.
Harvard-China Project: Mun, we understand the demand side of the power system has many influencing factors, and that it is important to not only use less electricity, but to also use it more cleverly. To start, can you explain the basics of electricity demand, and any policy implications?
Mun S. Ho: The simplest way to use less electricity is by improving energy efficiency, that is, getting the same amount of light from less kWh, the same air conditioning from less kWh, or the same production from machines in our factories from less kWh. Another way is what is known as “demand management.” Society’s use of electricity varies enormously by hour and season, as we noted in part 1: there are peak hours where the demand is 50% higher (or even more) than the low hours of a particular day. We currently deal with this by building enough capacity to meet the peak, though this leaves a lot of capacity idle during most hours of the year. Demand management means trying to shift demand across the hours so that the peak is lower, and thus the maximum capacity is lower; therefore, all units get used more often, ultimately lowering average costs.
To develop policies to address these demand-side issues, we need to understand the structure of demand by both businesses and households. We must learn how people use power; how demand reacts when we change prices; and what the future demand will be when we introduce new technologies. This includes exploring how we can change the price structure to encourage people to use power at different hours. Some of our research is devoted to this, learning about demand characteristics.
Harvard-China Project: Speaking of your research, can you elaborate on your work on electricity market pricing with Jianglong Li, Professor at Xian Jiaotong University and a Visiting Scholar or Associate of the Harvard-China Project since 2018?
Mun S. Ho: One project Jianglong and I have is to explore how the so-called “block-pricing system” in Zhejiang province affects household use of electricity. In the old days, like many places in the US today, households were charged a flat rate no matter how much they use. However, since 2012, Zhejiang has a system where the price per kWh rises when a household consumes more than a certain number of kWh per year, i.e., they move to a higher priced block. The idea behind such block pricing systems is to ensure that even poor families can afford some minimum amount of electricity, while presumably wealthier consumers pay higher prices as a means to encourage conservation. The questions that researchers in many countries are trying to answer include: do these block pricing systems actually reduce the use of electricity? Are most people aware of the prices they pay? Do people know whether they are near the use threshold where the price jumps? And even if they know the correct prices, do they reduce electricity use?
One might think that these should be easy questions to answer. Why not just compare the electricity consumption in 2011 versus 2012? That is not feasible because even if we have power consumption data, many things may have changed between 2011 and 2012: the economy has grown, or people are wealthier, or people could have moved in or out of the household. We have data on the daily use of electricity in a sample of houses in all areas of the province, but unfortunately, we do not have information on how many people live there, what their incomes are, or what electrical appliances and devices they have.
We had to do some careful comparisons using our data. The system charges 53.8 fen (Chinese cents) per kWh for usage less than 2760 kWh per year; 58.8 fen for 2760-4800 kWh per year; and 83.8 fen for usage greater than 4800 kWh per year. These prices were chosen by the government so that they ended with about 80% of households in the first block, 15% in the second block, and 5% in the top block. Most urban people in Zhejiang live in apartment buildings, so the electricity consumption is much lower than in more typical houses in the U.S. (For comparison purposes, in my house with 3 kids I use 1200kWh per month during the summer and 400 kWh during spring.) The interesting thing about the Zhejiang system is that there is a cellphone app which people can use to check how much electricity they have used during the year. The year-to-date total is also given in the monthly bill. Consequently, we argue that there is no serious barrier to obtaining information about how close a family is to the end of each price block.
Harvard-China Project: Did you find any other factors affecting their electricity consumption?
Mun S. Ho: We have daily usage data for more than 5,000 households from January 2017 through September 2018. We found 1,400 of them exceeded the first block at some point during 2017, and 370 exceeded the second block. We calculated the day when each of them passed beyond their block, and then noted their usage behavior for 30 days before and 30 days after. We understand people may be using less electricity because their price is now higher, or they may be using less electricity because the seasons changed and they’re now in a cooler autumn season. We took into account the day of the year when they cross the blocks and the temperature of the period before and after crossing. We then compared that with the behavior of households whose prices did not change, but who experienced those same temperatures. We found that electricity usage for the households who cross the blocks decreases. The change is not very big, but noticeable.
We found an elasticity of about -0.4 over a 60-day window, that is, a 10% increase in price leads to a 4% reduction in electricity use. We also looked at behavior when the price reset on January 1 to the low price in the first block. We found that electricity use rises, even after accounting for temperature differences between January and December. That is, people seem to think that prices are lower and use more. These behaviors, of course, raise the issue whether people are shortsighted, in that they do not think ahead when deciding on consumption and ignore the fact that higher use today cumulates into a total that hits the price steps later in the year.
Harvard-China Project: Have you explored how consumption correlates to income?
Mun S. Ho: In research with Yating Li (at that time a Ph.D. student at Duke University), and her professors at Duke and Jing Cao at Tsinghua University, we used household data where we do have information on household size, income and appliances, but not data on daily use (only annual electricity use). We combined this data with temperature data, and estimated that annual demand for electricity depends on prices, incomes and appliances owned. We found that when people have more wealth, they buy more appliances and run their air conditioners and other equipment more often, leading to a significant increase in electricity use. However, this “income elasticity” diminishes as we go up the income scale; that is, the impact is larger when the poor get more income. When the rich get more income, they use only a bit more electricity. We estimated that the income elasticity falls from 0.28 to 0.14 as income rises. Using these estimates, combined with historical data, we project future demand by households based on estimates of growth of future incomes. We project that demand by 2025 may be 85-143% higher than the demand in 2009 as a result of higher appliance ownership and higher use of individual appliances.
Jing Cao, Mun Ho, Wenhao Hu and Dale Jorgenson. 2020. “Effective labor supply and growth outlook in China,” China Economic Review, 61.
Wenhao Hu, Mun Ho and Jing Cao. 2019. “Energy consumption of urban households in China,” China Economic Review, 58.
Jing Cao, Mun Ho, Yating Li, Richard Newell, William Pizer (2019) “Chinese residential electricity consumption estimation and forecast using micro-data,” Resource and Energy Economics (56) 6-27. https://doi.org/10.1016/j.reseneeco.2017.10.003
Jing Cao, Mun Ho and Wenhao Hu. 2020. “Analyzing carbon price policies using a general equilibrium model with household energy demand functions,” in B. Fraumeni (ed) Measuring Economic Growth and Productivity: Foundations, KLEMS Production Models, and Extensions, Academic Press.