Benefit Transfers with Latent Class Models: Air Pollution Risk Management of Power Plants in China

We examine the benefit transfer of air quality improvement using latent class model (LCM) in China. We conduct Contingent rankings (CR) to estimate the implicit price of reducing health risk related to the air pollution of power plants. CR results are analyzed using random parameter logit model (RPL) and LCM with repeated choice data. Then, we conduct benefit transfer (BT) functions to alleviate transfer errors of the implicit price in accordance with conventional BT studies. Moreover, we investigate whether BT with LCM improves transferability of benefits because of incorporating the membership function, which is consisted of psychological attitudes of respondents, into estimating the implicit price. As a result, we show that variables on psychological attitudes improve the transferability of the implicit price more than socioeconomic characteristics. We concluded that BT be used along with more information about residents, such as psychological attitudes. We also advocate that uniform psychological survey protocols and an associated database would contribute to performance improvements in BT and therefore to assessment of environmental policies in China.