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on Cognitive and Behavioural Economics |
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Issue of 2019‒07‒22
six papers chosen by Marco Novarese Università degli Studi del Piemonte Orientale |
| By: | Emir Hrnjic; Nikodem Tomczak |
| Abstract: | Behavioral economics changed the way we think about market participants and revolutionized policy-making by introducing the concept of choice architecture. However, even though effective on the level of a population, interventions from behavioral economics, nudges, are often characterized by weak generalisation as they struggle on the level of individuals. Recent developments in data science, artificial intelligence (AI) and machine learning (ML) have shown ability to alleviate some of the problems of weak generalisation by providing tools and methods that result in models with stronger predictive power. This paper aims to describe how ML and AI can work with behavioral economics to support and augment decision-making and inform policy decisions by designing personalized interventions, assuming that enough personalized traits and psychological variables can be sampled. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1907.02100&r=all |
| By: | Bauer, Michal (Charles University, Prague); Chytilová, Julie (Charles University, Prague); Miguel, Edward (University of California, Berkeley) |
| Abstract: | Can a short survey instrument reliably measure a range of fundamental economic preferences across diverse settings? We focus on survey questions that systematically predict behavior in incentivized experimental tasks among German university students (Becker et al. 2016) and were implemented among representative samples across the globe (Falk et al. 2018). This paper presents results of an experimental validation conducted among low-income individuals in Nairobi, Kenya. We find that quantitative survey measures - hypothetical versions of experimental tasks - of time preference, attitude to risk and altruism are good predictors of choices in incentivized experiments, suggesting these measures are broadly experimentally valid. At the same time, we find that qualitative questions - self-assessments - do not correlate with the experimental measures of preferences in the Kenyan sample. Thus, caution is needed before treating self-assessments as proxies of preferences in new contexts. |
| Keywords: | preference measurement, experiment, survey, validation |
| JEL: | C83 D90 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp12450&r=all |
| By: | Anita Kopányi-Peuker (University of Amsterdam); Jin Di Zheng (Nanjing Audit University) |
| Abstract: | We study a giver’s generosity depending on her relationship with the recipient and the observer. We assign different group identities to the players using a variation of the minimumgroup paradigm, and test the effect of group memberships on altruistic giving in the dictator game with a passive observer. The results show that the dictator gives the least when she is from a different group than the other two. We further show that dictators give more when there is no observer. This is driven by male subjects who react more to the presence of the observer. |
| Keywords: | dictator game, observer, group identity, laboratory experiment |
| JEL: | D91 C72 C92 |
| Date: | 2019–07–16 |
| URL: | http://d.repec.org/n?u=RePEc:tin:wpaper:20190049&r=all |
| By: | Pelau, Corina; Ene, Irina |
| Abstract: | The presence of Artificial Intelligence in our everyday life has become one of the most debated topics nowadays. In opposition to the past, nowadays, in the age of broadband connectivity, it is difficult for individuals to imagine their everyday life, at work or in their spare time, without computers, internet, mobile applications or other devices. Most of these devices have had a contribution to the improvement of our everyday life by being more efficient and having a higher convenience. Few people are aware of the fact that, by continuously developing and improving these technologies, they might become more intelligent than we are and that they will have the potential to control us. In the attempt to make these devices friendlier to consumers, they have started to take human-like aspect and even having own identities. We have nowadays call center answering machines with names or robots with names and citizenship. The objective of this article is to determine the acceptance and preference of consumers for personalized or human-like robots or devices. For four different cases, the respondents had to choose between a classic device and a human-like robot. The results of the research show, with a high significance, that consumers still prefer the classic devices over anthropomorphic robots. |
| Keywords: | Artificial intelligence, robots, consumer, anthropomorphism, perception |
| JEL: | M0 M31 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:94617&r=all |
| By: | Pietro Guarnieri; Tommaso Luzzati; Stefano Marchetti |
| Abstract: | The paper experimentally investigates whether adding a dominated strategy changes subjects’ decisions in a stag hunt decision context. Specifically, we run two two-periods treatments where respectively 1) the decision makers firstly face the standard stag-hunt matrix and then the modified three-options matrix and 2) the decision makers firstly face the modified three-options matrix and then the standard two-options stag-hunt matrix. Given the circumstance that the added strategy is dominated, standard rationality assumption would predict no changes in participants decisions across periods and treatments. On the contrary, our results show that the exposure to one or the other treatment frames the decision-situation in a different way. Decision makers become less propense to take the risk of “hunting stags” in the modified three-options matrix, after they are firstly exposed to the two-options standard stag-hunt matrix. Vice versa, they appear more propense to change their decision towards the payoff dominant quilibrium, when they are firstly exposed to the modified three-options matrix and then to the two-options standard stag-hunt matrix. |
| Keywords: | stag hunt, coordination, risk-dominance, risk framing |
| JEL: | C91 C72 D8 |
| Date: | 2019–07–01 |
| URL: | http://d.repec.org/n?u=RePEc:pie:dsedps:2019/246&r=all |
| By: | Armando N. Meier |
| Abstract: | Previous work has shown that preferences are not always stable across time, but surprisingly little is known about the reasons for this instability. I examine whether variation in people’s emotions over time predicts changes in preferences. Using a large panel data set, I find that within-person changes in happiness, anger, and fear have substantial effects on risk attitudes and patience. Robustness checks indicate a limited role of alternative explanations. I further address potential endogeneity concerns by exploiting information about the death of a parent or child. This identification strategy confirms a large causal impact of emotions on preferences. |
| Keywords: | Emotions, risk attitudes, patience, risk preferences, time preferences |
| JEL: | D01 D90 D91 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:diw:diwsop:diw_sp1041&r=all |