Behavioural Economics,Hyperbolic Discounting and Environmental Policy

This paper reviews some recent research in “behavioural economics” with an application to environmental issues. Empirical results from behavioural economics provide a reminder that human behaviour is context-dependent, implying that policy may go awry if based upon models of behaviour which are inappropriate to the contexts in which decisions are made. Recognizing that agents may, in some contexts, systematically make mistakes raises challenging questions about the role of “paternalism” in government policy. The paper considers the research into hyperbolic discounting, and examines the implications for environmental policy. We develop a model of resource management under hyperbolic discounting, which shows that if a planner is unable to commit to a policy, the temptation to re-evaluate the policy in future could lead to an inadvertent collapse in the stocks of a natural resource.     

Always Leave Home Without It: A Further Investigation of the Credit-Card Effect on Willingness to Pay

In studies involving genuine transactions of potentially high value we show that willingness-to-pay can be increased when customers are instructed to use a credit card rather than cash. The effect may be large (up to 100%) and it appears unlikely that it arises due solely to liquidity constraints. In addition to demonstrating the effect, we provide a methodology for detecting it, and our findings suggest a source of variance to test alternative explanations.     

Using Segmentation and Prototyping in Engaging Politically-Salient Climate-Change Household Segments

Targeting messages to the different segments of a population is necessary to achieve support for policy addressing climate change. Finer segmentation and archetypal prototyping may be advantageous to provide an in-depth understanding of the most politically-salient segments. The research, conducted in Australia, used quantitative analysis to identify subsegments and prototypical respondents, followed by Jungian-style in-depth interviews to reveal the responses of segment representatives to different marketing stimuli. The results suggest that there are challenges in achieving majority support for action against climate change, but there are archetypal words and images that may garner action.     

Unequal but essential: How subsistence consumer–entrepreneurs negotiate unprecedented shock with extraordinary resilience during COVID‐19

We use qualitative interviews to study subsistence consumers confronting the global, pervasive and extended challenges of COVID‐19, encompassing literally all realms of daily life. For subsistence consumers whose circumstances are filled with day‐to‐day uncertainty and a small margin of error to begin with, the pandemic has led to manifold uncertainties and a disappearing margin of error, with potentially lethal consequences. Their constraints to thinking and lack of self‐confidence arising from both low income and low literacy are magnified in the face of the complex, invisible pandemic and the fear and panic it has caused. Characteristic relational strengths are weakened with social distancing and fear of infection. Yet, subsistence consumers display humanity in catastrophe, and confront the uncontrollable by reiterating a higher power. Consumption is reduced to the very bare essentials and income generation involves staying the course versus finding any viable alternative. We derive implications for consumer affairs.     

Hierarchical Bayesian conjoint models incorporating measurement uncertainty

The authors explore situations where consumers supplement their judgments with a measurement of uncertainty about their own preferences, either implicitly or explicitly, and develop two sets of hierarchical Bayesian conjoint models incorporating such measurements. The first set of models uses the relative location of a rating to determine the importance or weight given to the rating, in a regression setting. The second set uses interval judgment as a dependent variable in a regression setting. After specifying the models, the authors perform a theoretical comparison with a basic Bayesian regression model. They show that, under different conditions, the proposed models will yield more precise individual-level partworth estimates. Two simulated data examples and data from a conjoint study are used to illustrate the gains that could be obtained from modeling uncertainty. In the empirical application, the authors show that model fit improves when ratings for items that respondents do not like are given more weight compared to ratings for items that they do like. Electronic Supplementary Material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.