Person: Ho, Mun
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Publication Estimating Flexible Consumption Functions for Urban and Rural Households in China(Elsevier BV, 2020-06) Cao, Jing; Ho, Mun; Hu, Wenhao; Jorgenson, DaleThere are few comprehensive studies of household consumption in China that covers all commodities due to data restrictions. This prevents the calculation of inequality indices based on consumption. This lack of coverage also makes analysis of policies that affect consumption difficult; economy-wide models used for analysis often have to employ simple consumption forms with unit income elasticities. We estimate a translog demand system distinguished by demographic characteristics, giving price and income elasticities that should be useful for policy analysis. We estimate separate functions for urban and rural households using household expenditure data and detailed commodity prices (1995–2006). This allows future analysis of social welfare and inequality based on consumption to supplement existing studies based on income. To illustrate an application of the model, we project consumption composition based on projected prices, incomes and demographic changes – aging, education improvement and urbanization.Publication Energy consumption of urban households in China(Elsevier BV, 2019-12) Hu, Wenhao; Ho, Mun; Cao, JingWe estimate China urban household energy demand as part of a complete system of consumption demand so that it can be used in economy-wide models. This allows us to derive cross-price elasticities unlike studies which focus on one type of energy. We implement a two-stage approach and explicitly account for electricity, domestic fuels and transportation demand in the first stage and gasoline, coal, LPG and gas demand in the second stage. We find income inelastic demand for electricity and home energy, but the elasticity is higher than estimates in the rich countries. Demand for total transportation is income elastic. The price elasticity for electricity is estimated to be −0.5 and in the range of other estimates for China, and similar to long-run elasticities estimated for the U.S.Publication Emissions Accounting and Carbon Tax Incidence in CGE Models: Bottom-Up Versus Top-Down(Elsevier, 2019) Goettle, Richard; Ho, Mun; Wilcoxen, PeterMulti-sector general equilibrium models are the work-horses used to analyze the impact of carbon prices in climate policy discussions. Such models often have distinct industries to represent coal, liquid fuels, and gas production where the output over time is represented by quantity and price indexes. The industries that buy these fuels, however, do not use a common homogenous quantity (e.g., steam coal vs. metallurgical coal) and have distinct purchasing price indexes. In accounting for energy use or CO2 emissions, modelers choose to attach coefficients either bottom-up to a sector specific input index or top-down to an average output index and this choice has a direct bearing on the incidence of carbon taxation. We discuss how different accounting methods for the differences in prices can have a large effect on the simulated impact of carbon prices. We emphasize the importance for modelers to be explicit about their methods.Publication Modelling Consumption and Constructing Long-Term Baselines in Final Demand(Center for Global Trade Analysis, 2020-06-26) Ho, Mun; Britz, Wolfgang; Delzeit, Ruth; Leblanc, Florian; Roson, Roberto; Schuenemann, Franziska; Weitzel, MatthiasModelling and projecting consumption, investment and government demand by detailed commodities in CGE models poses many data and methodological challenges. We review the state of knowledge of modelling consumption of commodities (price and income elasticities and demographics), as well as the historical trends that we should be able to explain. We then discuss the current approaches taken in CGE models to project the trends in demand at various levels of commodity disaggregation. We examine the pros and cons of the various approaches to adjust parameters over time or using functions of time and suggest a research agenda to improve modelling and projection. We compare projections out to 2050 using LES, CES and AIDADS functions in the same CGE model to illustrate the size of the differences. In addition, we briefly discuss the allocation of total investment and government demand to individual commodities.Publication Analyzing Carbon Price Policies Using a General Equilibrium Model With Household Energy Demand Functions(Elsevier, 2020) Cao, Jing; Ho, Mun; Hu, WenhaoMulti-sector general equilibrium models are used to simulate the effects of environmental policies on industry output and consumption at disaggregated levels. The specification of household demand in such models often use simpler forms such as CES or Linear Expenditure Systems since there are few estimates of more flexible systems. We estimate a 2-stage translog utility function that explicitly accounts for detailed energy expenditures to allow us to capture the price and income effects more accurately than these simpler forms. We incorporate this into a China growth model to simulate the effects of a carbon price to achieve the government targets for the Climate Change (Paris) agreements.Publication Household energy demand in Urban China: Accounting for regional prices and rapid income change(International Association for Energy Economics (IAEE), 2016-09-01) Cao, Jing; Liang, Huifang; Ho, MunUnderstanding 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.