{'fraction_non_alphanumeric': 0.018134715025906734, 'fraction_numerical': 0.0, 'mean_word_length': 5.184, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Modelling Zero Bids in Contingent Valuation Surveys

When modelling data generated from a discrete choice contingent valuation question, the treatment of zero bids affects the welfare estimates. Zero bids may come from respondents who are not interested in the provision of the public good; alternatively, some zero-bidders may be protesting about the valuation exercise, but hold positive values for the good. In this paper we investigate the effect of different levels of information on zero-bidders on welfare estimates for the population. We find that different strategies of identification may have non-trivial effects. We recommend use of full debriefing questions for zero-bidders, and use of sample selection models to correct for bias caused by protest behaviour.