IDEAS home Printed from
   My bibliography  Save this paper

Projection bias in decision-making: Daily air pollution and willingness to pay for better air quality


  • Jie He

    (Département d'économique, École de gestion, Université de Sherbrooke)

  • Bing Zhang

    (Nanjing University)


Previous psychological and economic studies have observed systematic biases in people’s predictions of their future utilities. In this paper, using repeated contingent valuation (CV) surveys conducted with a very high frequency (every two weeks, in total 29 waves) in Nanjing, China during July 2014 to June 2015, we tested whether people’s expected future utility for better air quality is overly influenced by the air quality at the moment of valuation. As air quality, in general, is subject to high day-to-day variability, its negative impact on people’s utility (health, happiness etc.), according to rational logic, should be essentially stationary in the long-run and dependent on the yearly average air quality. Following this logic, based on the classical random utility model, we should not expect the daily air quality to be a determining factor in a rational person’s valuation decision. Our results show, however, that people’s willingness to pay (WTP) is significantly and positively affected by the level of PM2.5 concentration, one of the key air pollution indicators that has been well understood for several years and is widely available on different media platforms for almost all large cities in China. We explored a range of rational explanations but found that our results were more consistent with the effects of psychological mechanisms, in particular, projection bias.

Suggested Citation

  • Jie He & Bing Zhang, 2018. "Projection bias in decision-making: Daily air pollution and willingness to pay for better air quality," Cahiers de recherche 18-03, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
  • Handle: RePEc:shr:wpaper:18-03

    Download full text from publisher

    File URL:
    Download Restriction: no


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Yu, Shuangli & Shen, Yuxin & Zhang, Fan & Shen, Yongjian & Xu, Zefeng, 2022. "Air pollution and executive incentive: Evidence from pay-performance sensitivity," International Review of Financial Analysis, Elsevier, vol. 82(C).

    More about this item


    Psychological effects; projection bias; contingent valuation; air quality; China;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:shr:wpaper:18-03. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jean-François Rouillard (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.