Cao, Jing

In Press
Jing Cao, Mun Sing Ho, Yating Li, Richard G. Newell, and William A. Pizer. In Press. “Chinese residential electricity consumption estimation and forecast using micro-data.” Resource and Energy Economics. Publisher's VersionAbstract
Based on econometric estimation using data from the Chinese Urban Household Survey, we develop a preferred forecast range of 85–143 percent growth in residential per capita electricity demand over 2009–2025. Our analysis suggests that per capita income growth drives a 43% increase, with the remainder due to an unexplained time trend. Roughly one-third of the income-driven demand comes from increases in the stock of specific major appliances, particularly AC units. The other two-thirds comes from non-specific sources of income-driven growth and is based on an estimated income elasticity that falls from 0.28 to 0.11 as income rises. While the stock of refrigerators is not projected to increase, we find that they contribute nearly 20 percent of household electricity demand. Alternative plausible time trend assumptions are responsible for the wide range of 85–143 percent. Meanwhile we estimate a price elasticity of demand of −0.7. These estimates point to carbon pricing and appliance efficiency policies that could substantially reduce demand.
Jing Cao, Mun S. Ho, and Govinda R. Timilsina. Submitted. “Carbon Tax for Achieving China's NDC: Simulations of Some Design Features Using a CGE Model.” Climate Change Economics.
Jing Cao, Mun S. Ho, Wenhao Hu, and Dale W. Jorgenson. Submitted. “Urban Household Consumption in China.” Review of Economics and Statistics.
Nan Zhong, Jing Cao, and Yuzhu Wang. 2017. “Traffic congestion, ambient air pollution and health: Evidence from driving restrictions in Beijing.” Journal of the Association of Environmental and Resource Economists, 4, 3, Pp. 821–856. Publisher's VersionAbstract

Vehicles have recently overtaken coal to become the largest source of air pollution in urban China. Research on mobile sources of pollution has foundered due both to inaccessibility of Chinese data on health outcomes and strong identifying assumptions. To address these, we collect daily ambulance call data from the Beijing Emergency Medical Center and combine them with an idiosyncratic feature of a driving restriction policy in Beijing that references the last digit of vehicles’ license plate numbers. Because the number 4 is considered unlucky by many in China, it tends to be avoided on license plates. As a result, days on which the policy restricts license plates ending in 4 unintentionally allow more vehicles in Beijing. Leveraging this variation, we find that traffic congestion is indeed 22% higher on days banning 4 and that 24-hour average concentration of NO2 is 12% higher. Correspondingly, these short term increases in pollution increase ambulance calls by 12% and 3% for fever and heart related symptoms, while no effects are found for injuries. These findings suggest that traffic congestion has substantial health externalities in China but that they are also responsive to policy. 

Jing Cao, Mun S. Ho, and Huifang Liang. 2016. “Household energy demand in urban China: Accounting for regional prices and rapid economic change.” The Energy Journal, 37. Publisher's VersionAbstract

Understanding the rapidly rising demand for energy in China is essential to efforts to reduce the country's energy use and environmental damage. In response to rising incomes and changing prices and demographics, household use of various fuels, electricity and gasoline has changed dramatically in China. In this paper, we estimate both income and price elasticities for various energy types using Chinese urban household micro-data collected by National bureau of Statistics, by applying a two-stage budgeting AIDS model. We find that total energy is price and income inelastic for all income groups after accounting for demographic and regional effects. Our estimated electricity price elasticity ranges from - 0.49 to -0.57, gas price elasticity ranges from -0.46 to -0.94, and gasoline price elasticity ranges from -0.85 to -0.94. Income elasticity for various energy types range from 0.57 to 0.94. Demand for coal is most price and income elastic among the poor, whereas gasoline demand is elastic for the rich.

Jing Cao, Mun S Ho, and Dale W Jorgenson. 2013. “The Economics of Environmental Policies in China.” In Clearer Skies Over China: Reconciling Air Quality, Climate, and Economic Goals, Pp. 329-372. Cambridge, MA: MIT Press. Publisher's Version
Chris P Nielsen, Mun S Ho, Jing Cao, Yu Lei, Yuxuan Wang, and Yu Zhao. 2013. “Summary: Carbon Taxes for 2013-2020.” In Clearer Skies Over China: Reconciling Air Quality, Climate, and Economic Goals, Pp. 103-157. Cambridge, MA: MIT Press. Publisher's Version
Chris P Nielsen, Mun S Ho, Yu Zhao, Yuxuan Wang, Yu Lei, and Jing Cao. 2013. “Summary: Sulfur Mandates and Carbon Taxes for 2006-2010.” In Clearer Skies Over China: Reconciling Air Quality, Climate, and Economic Goals, Pp. 59-102. Cambridge, MA: MIT Press. Publisher's Version
Jing Cao, Mun S Ho, and Dale W Jorgenson. 2012. “An integrated assessment of the economic costs and environmental benefits of pollution and climate control.” In The Chinese Economy: A New Transition, edited by Masahiko Aoki. London: Palgrave Macmillan. Publisher's Version
Jing Cao, Richard Garbaccio, and Mun S Ho. 2009. “China's 11th Five-Year Plan and the environment: Reducing SO2 emissions.” Review of Environmental Economics and Policy, 3, 2, Pp. 189-208. Publisher's Version
Jing Cao, Mun S Ho, Dale W Jorgenson, Rouen Ren, Linlin Sun, and Ximing Yue. 2009. “Industrial and aggregate measures of productivity growth in China, 1982-2000.” Review of Income Wealth , 55, s1, Pp. 485-513. Publisher's Version
Jing Cao, Mun S Ho, and Dale W Jorgenson. 2009. “The local and global benefits of green tax policies in China.” Review of Environmental Economics and Policy, 3, 2, Pp. 231-250. Publisher's Version