Value of a Statistical Life
Attributes
Medium: Health and/or Human Capital
Country: China
Analytical Framework(s): Cost of Illness Approach
Study Date: 2007
Publication Date: 2010
Major Result(s)
| Category | Resource/Environmental Good | CNY, million currency units (2007) |
|---|---|---|
| Wang and Mullahy (2006) | VSL - lower bound1 | 0.30 |
| Wang and Mullahy (2006) | VSL - upper bound | 1.25 |
| Zhang Xiao (2002) | VSL - lower bound | 0.24 |
| Zhang Xiao (2002) | VSL - upper bound | 1.70 |
| Hammitt and Zhou (2005) | VSL - lower bound | 0.26 |
| Hammitt and Zhou (2005) | VSL - upper bound | 0.51 |
| Krupnick et al. (2006) | VSL | 1.40 |
Study Note: The general goal of this project is to understand the proximate reasons for past changes in aggregate energy intensity and to use the estimates of the contribution of these various factors to project future energy consumption and emissions if past policies are maintained. With these estimates of past energy use we also analyzed the effects of other policies in reducing energy use and emissions to meet China's sustainable development targets.
Study Details
Summary: Since the economic reforms that began in 1978, China has experienced a dramatic decline in energy intensity but in 2002 it flattened out and even rose slightly. There have been considerable debates about the origins of this dramatic decline in energy intensity before the year 2000: is this decline mostly due to changes in the composition of economic activity? (structural change) or is it mostly due to changes in technology? (energy per ton of steel, for example). However, very few studies have examined the slightly rising energy intensity trend for the post-2000 period. In this report, we use a new time-series input-output data set from 1981-2007 to decompose the reduction in energy use into technical change and various types of structural change, including changes in the quantity and composition of imports and exports. We use two different decomposition methodologies: Structural Decomposition Analysis (SDA) and Index Decomposition Analysis (IDA) methods. Based on these estimates of changes in energy intensity, we project Autonomous Energy Efficiency Improvement (AEEI) parameters in forecasting future capital, labor and energy input shares of output for each industry. We then construct a recursive-dynamic computable general equilibrium (CGE) model of the Chinese economy to analyze both command-and-control policies and carbon taxes, and provide policy recommendations on how China could pursue a more sustainable development trajectory to deal with greenhouse gas emissions.
Site Characteristics: As the largest developing country in the world, and a country experiencing dramatic change and economic growth, China is expected to consume a large and rapidly rising share of the world's energy. This trend is viewed with alarm by anyone worried about the sustainability of such economic development. China's energy intensity had been declining for 20 years, since the economic reforms of 1978. However, this frugal pattern may have reversed since 2002, causing analysts to raise the previous high projection even further. How the Chinese government can reverse this rise in energy intensity, or at least lower the growth rate, i.e. how it can achieve its 20% reduction target, as stated in the 11th Five-Year Plan, and reduce carbon emissions in the future, is becoming a crucial question. In particular, should the government follow a command-and-control policy, such as the energy conservation mandates currently used in the 11th Five-Year Plan, or alternatively, should economic incentive-based policies - such as energy or carbon taxes - be used? These questions are the focus of our study. We provide a methodological framework for energy intensity decomposition, and for projecting future energy use and carbon emissions using industry-level estimates of improvements in energy use. In the process we provide a new set of AEEI estimates by detailed sectors for other analysts to use in their models.
Comments: Data covered a newly revised data set covering the period 2000-2005, after the NBS adjusted the GDP level. A new GDP series I-O table was revised upward so that the GDP adjustments in major service sectors could be incorporated. Therefore the entire series was used in this report