Conference Agenda

Economic preference are strongly heterogeneous across the globe. This paper adds to the study of the causes of this variation, using a novel and unique setting allowing to disentangle the roles of culture and climate on preference formation. In particular, we use data from the southern slope of Mount Kilimanjaro which exhibits a steep continuous gradient of ecological variation vis a vis minimal socio-political heterogeneity across space and time. Matching data on economic preferences from 14 villages with data on climatic conditions (i) between 1982 - 2011 and (ii) during the farming season directly preceding the preference data collection, we are able to distinguish between long-term and short-term effects of environmental conditions on economic preferences. Overall we find that variations in climatic baseline conditions can be related to variations in patience and risk tolerance along the mountain slope. Indicators of climate uncertainty increase risk aversion, larger exposure to extreme events however coerces more risk tolerance, and larger agricultural suitability increases patience. Findings on the role of climate on prosociality variables are less clear-cut.

This paper explores how the quality of emission disclosures shapes public perceptions of pollution and trust in officially reported data. I examine a nationwide platform that provides daily emission records for all municipal Waste-to-Energy (WtE) plants in China. I combine emission data from 2020 to 2022 with a second-hand housing dataset covering 92 cities. I estimate pollution beliefs using a residential sorting model where households base housing choices on perceived pollution exposure and the quality of disclosed information. I find that, in most cities, pollution is perceived as higher when emission records are flawed, compared to when they are valid. I then explore possible sources of the prevalent "over-perception," including plant manipulation and city-specific characteristics. Such divergence, however, can be mitigated by enhancing long-run information quality, defined as the valid rate of emission records over the three years. Finally, I estimate an average marginal willingness-to-pay of $4.13 for a 1% improvement in information quality within a reference period. The substantial substitution effect between information quality and distance to the plant reveals that better-informed households are more willing to live closer to WtE plants, suggesting reduced local opposition to these facilities.

We analyze ecosystem resilience under uncertainty as a public good. Due to the self-protection structure of the (private and public) optimization problems and non-convex ecosystem dynamics, the optimization problems might not be convex. We extend an existing ecological-economic model of resilience to capture the public good aspect. We show that in contrast to the traditional public good literature, Nash-equilibria can be Pareto-efficient under certain conditions. We illustrate our findings in a numerical example. Our results suggest that new policy measures for decentralized provision of ecosystem resilience are conceivable. For example, the government can ensure initial conditions such that there is no incentive for free-riding and individuals cooperate in their best interest. This policy is possible because the public good problem can become a coordination game due to the tipping point of the ecosystem.

This paper examines how (re)labeling changes perception and preference by exploiting an unexpected information shock due to the tightening of air quality standards in South Korea. Since March 2018, PM2.5 concentrations between 35-50 μg/m3 are relabeled from “Normal” to “Bad”, while PM2.5 concentrations between 75-100 μg/m3 are relabeled from “Bad” to “Very Bad”. We link the information shock with a unique data set on the universe of over 6 million housing sales and rental contracts in 2015-2020. An extra day of PM2.5 labeling change from “Normal” to “Bad” and from “Bad” to “Very Bad” over the past 30 days lowers home values by approximately 0.31% ($981) and 0.22% ($703), and rental prices by 0.22% ($25) and 0.25% ($28) per year, respectively. Relabeling not only shifts the Hedonic Price Schedule within the categories, but also steepens it by increasing marginal willingness to pay (MWTPs) for clean air across categories. The relabeling raises MWTPs by 0.0007% ($2.2), 0.0024% ($7.6), 0.0029% ($9.2), 0.0032% ($10.2), and 0.0036% ($11.4) for the “Normal”, “Normal to Bad”, “Bad”, “Bad to Very Bad”, and “Very Bad” categories, respectively. Larger relabeling effects are observed at lower floors and in urban areas compared with their counterparts. Relabeling further improves air quality after 10 months since the information shock. Our findings highlight the role of relabeling in shaping risk perception and preference, contribute to the valuation of information and air quality, and provide important policy implications for the environment, real estate, and beyond.