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on Cognitive and Behavioural Economics |
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Issue of 2018‒10‒29
ten papers chosen by Marco Novarese Università degli Studi del Piemonte Orientale |
| By: | Carlos Alós-Ferrer; Michele Garagnani |
| Abstract: | Why do some individuals cooperate with their fellow human beings while others take advantage of them? The human drive for cooperation and altruism is one of the most powerful forces shaping our society, but there is an enormous behavioral variance in individual behavior. At the same time, whether it is intuitive to behave in a cooperative manner or whether such behaviors are calculated deeds remains an unanswered question. Indeed, recent empirical investigations regarding the spontaneity of human cooperation have found mixed evidence, possibly due to a failure to induce compliance in the behavioral manipulations employed. We conducted a laboratory experiment inducing intuitive and deliberative behavior through gradual economic incentives that ensure compliance. To account for individual heterogeneity, we independently measured social value orientation and aversion to interpersonal (strategic) uncertainty. We find that these measures determine the intrinsic predisposition towards cooperation. Subjects with more altruistic social values or a higher tolerance towards interpersonal uncertainty are more cooperative. Crucially, we find causal evidence that there is no universal default mode of behavior. Rather, intuition enhances intrinsic predispositions, while deliberation moderates them towards socially acceptable behavior. That is, subjects with a higher (resp. lower) predisposition towards cooperation became more (resp. less) cooperative under time pressure compared with time delay. |
| Keywords: | Cooperation, heterogeneity, time manipulations |
| JEL: | D01 D81 C9 |
| Date: | 2018–10 |
| URL: | http://d.repec.org/n?u=RePEc:zur:econwp:303&r=cbe |
| By: | Grimm, Stefan (LMU Munich) |
| Abstract: | Most economic decisions are embedded in a specific social context. In many such contexts, individual choices are influenced by their observability due to underlying social norms and social image concerns. This study investigates the impact of choices being observed, compared to anonymity of choices, on risk taking in a laboratory experiment. I relate participants\' investments in a risky asset directly to social norms for risk taking that are elicited in an incentivized procedure. I find that risk taking is not affected by the choice being observed by a matched participant. Nor do investments follow elicited norms for risk taking more closely when observed. This holds when considering males and females separately. However, I provide strong evidence for gender-specific norms in risk taking. While these explain part of the existing gender gap in risk taking, males still \"overshoot\" by investing more than the norm dictates. This is particularly true for males being matched with a female participant. |
| Keywords: | risk taking; observability; social image; norms; gender; |
| JEL: | C91 D01 D81 D91 G11 |
| Date: | 2018–10–11 |
| URL: | http://d.repec.org/n?u=RePEc:rco:dpaper:119&r=cbe |
| By: | Sheremeta, Roman |
| Abstract: | Costly competitions between economic agents are modeled as contests. Researchers use laboratory experiments to study contests and test comparative static predictions of contest theory. Commonly, researchers find that participants’ efforts are significantly higher than predicted by the standard Nash equilibrium. Despite overbidding, most comparative static predictions, such as the incentive effect, the size effect, the discouragement effect and others are supported in the laboratory. In addition, experimental studies examine various contest structures, including dynamic contests (such as multi-stage races, wars of attrition, tug-of-wars), multi-dimensional contests (such as Colonel Blotto games), and contests between groups. This article provides a short review of such studies. |
| Keywords: | Contest; All-pay auction; Tournament; Dynamic Contest; Multi-battle Contest; Multi-dimensional Contest; Group Contest; Rent-seeking; Experiment; Overbidding; Over-dissipation; Incentive Effect; Size Effect; Discouragement Effect; Strategic Momentum |
| JEL: | C7 C9 D4 D7 D9 H4 J4 K4 L2 M5 |
| Date: | 2018–10–03 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:89327&r=cbe |
| By: | Bruhin, Adrian (University of Lausanne); Fehr, Ernst (University of Zurich); Schunk, Daniel (University of Mainz) |
| Abstract: | There is vast heterogeneity in the human willingness to weigh others' interests in decision making. This heterogeneity concerns the motivational intricacies as well as the strength of other-regarding behaviors, and raises the question how one can parsimoniously model and characterize heterogeneity across several dimensions of social preferences while still being able to predict behavior over time and across situations. We tackle this task with an experiment and a structural model of preferences that allows us to simultaneously estimate outcome-based and reciprocity-based social preferences. We find that non-selfish preferences are the rule rather than the exception. Neither at the level of the representative agent nor when we allow for several preference types do purely selfish types emerge in our sample. Instead, three temporally stable and qualitatively different other-regarding types emerge endogenously, i.e., without pre-specifying assumptions about the characteristics of types. When ahead, all three types value others' payoffs significantly more than when behind. The first type, which we denote as strongly altruistic type, is characterized by a relatively large weight on others' payoffs – even when behind – and moderate levels of reciprocity. The second type, denoted as moderately altruistic type, also puts positive weight on others' payoff, yet at a considerable lower level, and displays no positive reciprocity, while the third type is behindness averse, i.e., puts a large negative weight on others' payoffs when behind and behaves selfishly otherwise. We also find that there is an unambiguous and temporally stable assignment of individuals to types. In addition, we show that individual-specific estimates of preferences offer only very modest improvements in out-of-sample predictions compared to our three-type model. Thus, a parsimonious model with only three types captures the bulk of the information about subjects' social preferences. |
| Keywords: | social preferences, heterogeneity, stability, finite mixture models |
| JEL: | C49 C91 D03 |
| Date: | 2018–09 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp11815&r=cbe |
| By: | Eichenseer, Michael; Moser, Johannes |
| Abstract: | We examine how leadership affects a dynamic public goods game. Using a setting where cooperation gains can be reinvested, our findings suggest that leadership has a positive impact on final wealth. Somewhat surprisingly, leadership also has a positive impact on reducing inequality within groups as measured by the Gini index. Based on a sequential prisoner's dilemma, we elicit types for conditional cooperation. Our results indicate that groups work best when led by cooperatively inclined individuals. Furthermore, early contributions by the leader are crucial and yield a high return. |
| Keywords: | Leadership,Public Goods Game,Conditional Cooperation,Inequality,Growth,Lab Experiment |
| JEL: | C72 C92 H41 D63 C72 C92 H41 D63 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:vfsc18:181599&r=cbe |
| By: | Adrian Bruhin (University of Lausanne); Ernst Fehr (Universität Zürich); Daniel Schunk (Johanes Gutenberg - Universität Mainz) |
| Abstract: | We uncover heterogeneity in social preferences with a structural model that accounts for outcome-based and reciprocity-based social preferences and assigns individuals to endogenously determined preferences types. We find that neither at the aggregate level nor when we allow for several distinct preference types do purely selfish types emerge, suggesting that other-regarding preferences are the rule and not the exemption. There are three temporally stable other-regarding types. When ahead, all types value others' payoffs more than when behind. The first, strongly altruistic type puts a large weight on others' payoffs even when behind and displays moderate levels of reciprocity. The second, moderately altruistic type also puts positive weight on others’ payoff, yet at a lower level, and displays no positive reciprocity. The third, behindness averse type puts a large negative weight on others’ payoffs when behind and is selfish otherwise. In addition, we show that individual-specific estimates of preferences offer only very modest improvements in out-of-sample predictions compared to our three-type model. Thus, a parsimonious model with three types captures the bulk of the information about subjects' social preferences. |
| Keywords: | social preferences, heterogeneity, Stability, finite mixture models |
| JEL: | C49 C91 D03 |
| Date: | 2018–10 |
| URL: | http://d.repec.org/n?u=RePEc:hka:wpaper:2018-079&r=cbe |
| By: | Kuan-Yang Chen (National Taipei University of Nursing and Health Sciences); Chih-Hui Hsiao (National Chiayi University); Po-Yuan Chen (National Dong Hwa University); Cheng-Fei Lee (Shih Chien University, Kaohsiung Campus) |
| Abstract: | In the knowledge economy era, both academia and industry alike have been focused on the impact of market knowledge on innovation performance. However, research addressing the inconsistencies in empirical findings about its impact (such as a negative or insignificant affect) is scarce. Moreover, ambidexterity (exploratory learning/exploitative learning) is one of the central topics in knowledge management. This article marks the first endeavor to adopt the knowledge-based theory and the ambidextrous learning perspective, attempt to create a theoretical framework of knowledge-learning-innovation, and thoroughly examine related causal relationships between different dimensions of the constructs. The empirical results demonstrated the following: market knowledge depth directly and positively impacts process innovation and product innovation; market knowledge breadth indirectly and positively impacts process innovation and product innovation; and there is no significant difference in the effects of the two types of knowledge on the two types of innovation performance. Ambidextrous learning directly and positively affects process innovation and product innovation; ambidextrous organizational learning mediates the effect of market knowledge breadth on process innovation and product innovation, and this mediating effect is more pronounced with exploitative learning; ambidextrous organizational learning does not mediate the effect of market knowledge depth on both types of innovation performance. |
| Keywords: | market knowledge (depth and breadth), ambidextrous learning, process innovation, product innovation |
| JEL: | M10 |
| Date: | 2018–07 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iacpro:8208758&r=cbe |
| By: | Hopp, Daniel; Becker, Johannes; Kriebel, Michael |
| Abstract: | We report evidence from a series of laboratory experiments that focus on mental accounting of 'public funds'. Groups of three players decide upon how much to redistribute within the group. We measure the preference to redistribute when transfers are made either out of individual accounts (the players' own money) or out of a common account (the group's money). Since the common account is dissolved after each round and paid out to individuals, its size should not affect the decision to redistribute. The experiment is designed to rule out an anchoring effect. We find that the (relative) size of the common account significantly affects redistribution behavior. Specifically, the transfer increases in the relative size of the common account – but only when the transfer is paid out of the common account (and not out of the individual account). We interpret these findings as evidence for a flypaper effect due to mental accounting and discuss implications for tax policy and government spending. |
| Keywords: | mental accounting,flypaper effect,lab experiments |
| JEL: | C92 D72 H31 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:vfsc18:181629&r=cbe |
| By: | Deborah A. Cobb-Clark (The University of Sydney); Colm Harmon (University of Sydney); Anita Staneva (The University of Sydney) |
| Abstract: | In this paper we examine whether – conditional on other family inputs – bilingual children achieve different outcomes in language and emotional development. Our data come from the UK Millennium Cohort Study (MCS) which allows us to analyze children’s language and emotional development in depth. We relax the usual assumption that the production function underpinning child development is not itself a function of the age of the child and estimate the bilingual gap in children’s language and emotional development as a cumulative process that depends on current and past endowments of cognitive and non-cognitive capacity. We find that the language development of bilingual children is not significantly different to that of their monolingual peers; however, there is evidence of a positive effect of bilingualism on emotional development. |
| Keywords: | cognitive skills, non-cognitive skills, production function, value-added model, cohort study |
| JEL: | I20 J24 D10 |
| Date: | 2018–10 |
| URL: | http://d.repec.org/n?u=RePEc:hka:wpaper:2018-075&r=cbe |
| By: | Fischer, Thomas G. |
| Abstract: | The advent of reinforcement learning (RL) in financial markets is driven by several advantages inherent to this field of artificial intelligence. In particular, RL allows to combine the "prediction" and the "portfolio construction" task in one integrated step, thereby closely aligning the machine learning problem with the objectives of the investor. At the same time, important constraints, such as transaction costs, market liquidity, and the investor's degree of risk-aversion, can be conveniently taken into account. Over the past two decades, and albeit most attention still being devoted to supervised learning methods, the RL research community has made considerable advances in the finance domain. The present paper draws insights from almost 50 publications, and categorizes them into three main approaches, i.e., critic-only approach, actor-only approach, and actor-critic approach. Within each of these categories, the respective contributions are summarized and reviewed along the representation of the state, the applied reward function, and the action space of the agent. This cross-sectional perspective allows us to identify recurring design decisions as well as potential levers to improve the agent's performance. Finally, the individual strengths and weaknesses of each approach are discussed, and directions for future research are pointed out. |
| Keywords: | financial markets,reinforcement learning,survey,trading systems,machine learning |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:iwqwdp:122018&r=cbe |