nep-cbe New Economics Papers
on Cognitive and Behavioural Economics
Issue of 2020‒09‒07
seven papers chosen by
Marco Novarese
Università degli Studi del Piemonte Orientale

  1. Social Nudges as Mitigators in Privacy Choice Environments By Klumpe, Johannes
  2. Inverse Reinforcement Learning for Sequential Hypothesis Testing and Search By Kunal Pattanayak; Vikram Krishnamurthy
  3. Are Economics and Psychology Complements in Household Technology Diffusion? Evidence from a Natural Field Experiment By Matilde Giaccherini; David Herberich; David Jimenez-Gomez; John List; Giovanni Ponti; Michael Price
  4. Forecasting Skills in Experimental Markets: Illusion or Reality? By Brice Corgnet; Cary Deck; Mark DeSantis; David Porter
  5. The Show Must Go On: How to Elicit Lablike Data on the Effects of COVID-19 Lockdown on Fairness and Cooperation By Irene Maria Buso; Daniela Di Cagno; Sofia De Caprariis; Lorenzo Ferrari; Vittorio Larocca; Francesca Marazzi; Luca Panaccione; Lorenzo Spadoni
  6. Framing in and through International Law By van Aaken, Anne; Elm, Jan-Philip
  7. Driven to Succeed? Teenagers' Drive, Ambition and Performance on High-Stakes Examinations By Jerrim, John; Shure, Nikki; Wyness, Gill

  1. By: Klumpe, Johannes
    Abstract: In light of prominent data leaks and a surge of civilian surveillance systems, information service providers are confronted with an increased level of skepticism towards their privacy practices. The predicament is that not only do providers rely on users' information to optimize their services, users also risk losing the benefits of increasingly personalized services. Research on information privacy has paid great attention to explaining and predicting factors of privacy-related outcomes. On a macro level, researchers have come up with a plethora of models that are focused on deliberate and rational decision-making. In contrast, non-rational decision-making within privacy choice environments (i.e., presentation of privacy-related choices to users) has to date only been sparsely investigated. A more holistic approach to privacy-related outcomes is provided by the Person-Technology fit model. This model describes a relationship between an individual and a technology, which, when it is out of equilibrium, causes stress for the individual. Research on technology-induced stress has discovered that it affects both general stress (e.g., psychological strain) and situational stress outcomes (e.g., behavioral reactions). In this regard, research has explicated intrusive technology features (i.e., features that acquire information from and provide information to the user) as the most salient drivers of stress caused by privacy invasions for users of digital services. However, previous contributions have focused on psychological antecedents of privacy invasions, neglecting how firms may design and enhance privacy choice environments to alleviate privacy-related stress. Likewise, existing literature lacks to address how service providers can combine different technology features in the design of their services to reduce privacy-related stress. Hence, digital nudging, which refers to the practice of influencing user behavior in digital choice environments by leveraging the effect of cognitive biases and decision heuristics in user interface design, holds promising potential for service providers to overcome the detrimental effects of privacy-related stress. Specifically, research has found evidence that social nudges, defined as nudges based on social influences (i.e., unwritten social laws), can guide users to better decisions in choice environments. However, social nudging has been ignored in the context of privacy-related decision making. This thesis draws on four studies that were conducted to investigate how intrusive technology features affect privacy-related outcomes, and how to utilize social nudges as mitigating technology features in privacy choice environments. The first study describes a laboratory experiment and a subsequent field experiment, which investigated how the intrusive effects of unintentional voice activations of smart home assistants drive user strain and interpersonal conflicts through privacy invasions, while the study demonstrates how anthropomorphic design features alleviate user strain. The second study elaborates upon the intrusive effect of push- based information delivery on users’ geographical location information disclosure through privacy concerns, which can be attenuated by signals of social proof in mobile app stores. Finally, for the third study, we cooperated with the German startup Partner der Wissenschaft UG to investigate how low message interactivity affects users’ information disclosure in a chatbot conversation, which we enhanced by employing platform self-disclosure nudges. In sum, this thesis highlights the importance of understanding the technology-stressor-strain causal relationship for information services by providing significant contributions: First, the findings extend previous research on technology-induced stress by illuminating specific design mechanisms for digital services. In this regard, the studies demonstrate how intrusive technology features drive privacy-related stressors and ultimately cause users to disengage with the respective information services. Thereby, we address the calls for particular and context- related intrusive technology features with applicable design recommendations from Ayyagari, Grover, and Purvis (2011) and Speier, Vessey, and Valacich (2003). Second, this thesis expands the Person-Technology model by a new layer of technology features that help to mitigate and overcome users’ privacy-related stress. More specifically, this study illuminates how social nudges can be utilized as mitigating strategies for technology-induced stress and hereby effectuate better privacy-related outcomes. In this regard, this thesis addresses the calls for research from Kretzer and Maedche (2018) and Mirsch, Lehrer, and Jung (2017) on specific and context-related digital nudges with applicable design recommendations by putting together a catalog of social nudges for privacy choice environments.
    Date: 2020–06–24
  2. By: Kunal Pattanayak; Vikram Krishnamurthy
    Abstract: This paper considers a novel formulation of inverse reinforcement learning~(IRL) with behavioral economics constraints to address inverse sequential hypothesis testing (SHT) and inverse search in Bayesian agents. We first estimate the stopping and search costs by observing the actions of these agents using Bayesian revealed preference from microeconomics and rational inattention from behavioral economics. We also solve the inverse problem of the more general rationally inattentive SHT where the agent incorporates controlled sensing by optimally choosing from various sensing modes. Second, we design statistical hypothesis tests with bounded Type-I and Type-II error probabilities to detect if the agents are Bayesian utility maximizers when their actions are measured in noise. By dynamically tuning the prior specified to the agents, we formulate an {\em active} IRL framework which enhances these detection tests and minimizes their Type-II and Type-I error probabilities of utility maximization detection. Finally, we give a finite sample complexity result which provides finite sample bounds on the error probabilities of the detection tests.
    Date: 2020–07
  3. By: Matilde Giaccherini; David Herberich; David Jimenez-Gomez; John List; Giovanni Ponti; Michael Price
    Abstract: This paper uses a field experiment to estimate the effects of prices and social norms on the decision to adopt and efficient technology. We find that prices and social norms influence the adoption and decision along different margins: while prices operate on both the extensive and intensive margins, social norms operate mostly through the extensive margin. This has both positive and normative implications, and suggests that economics and psychology may be strong complements in the diffusion process. To complement the reduced form results, we estimate a structural model that points to important household heterogeneity: whereas some consumers welcome the opportunity to purchase and learn about the new technology, for others the inconvenience and social pressure of the ask results in negative welfare. As a whole, our findings highlight that the design of optimal technological diffusion policies will require multiple instruments and a recognition of household heterogeneity.
    Date: 2020
  4. By: Brice Corgnet (EMLYON Business School); Cary Deck (University of Alabama & Chapman University); Mark DeSantis (Chapman University); David Porter (Chapman University)
    Abstract: Using experimental asset markets, we study the situation of a financial analyst who is trying to infer the fundamental value of an asset by observing the market’s history. We find that such capacity requires both standard cognitive skills (IQ) as well as social and emotional skills. However, forecasters with high emotional skills tend to perform worse when market mispricing is high as they tend to give too much emphasis to the noisy signals from market data. By contrast, forecasters with high social skills perform especially well in markets with high levels of mispricing in which their skills could help them detect possible manipulation attempts. Finally, males outperform females in the forecasting task after controlling for a large number of relevant individual characteristics such as risk attitudes, cognitive skills, emotional intelligence, and personality traits.
    Keywords: Forecasting, experimental asset markets, theory of mind, personality traits, cognitive skills
    JEL: C92 G17 D91
    Date: 2020
  5. By: Irene Maria Buso; Daniela Di Cagno; Sofia De Caprariis; Lorenzo Ferrari; Vittorio Larocca; Francesca Marazzi; Luca Panaccione; Lorenzo Spadoni
    Abstract: Given the impossibility of having participants in the lab during the COVID-19 lockdown, we introduce a novel methodology based on a multi-platform architecture that brings experimental subjects in a “Lab on the Web”. This methodology allows us to study the effects of Covid-19 lockdown in Italy on preferences for fairness and cooperation. Results from sessions of standard Ultimatum and linear Public Good games validate our methodology. Moreover, we show that the circumstances in which participants lived the lockdown significantly affect their behavior in the two games. In particular, participants are more selfish in the ultimatum bargaining and contribute more to public good when lockdown is longer and social isolation is stronger. We interpret these results as evidence of “social embeddedness” to compensate for “social distancing”.
    Keywords: Covid-19, economic experiment, fairness, voluntary contribution mechanism, cooperation
    JEL: C92 H41 C73
    Date: 2020
  6. By: van Aaken, Anne; Elm, Jan-Philip
    Abstract: Framing is pervasive in public international law. International legal norms (incl. soft law) and international politics both inevitably frame how international actors perceive a given problem. Although framing has been an object of study for a long time - be it in domestic or international politics - it has not been systematically explored in the context of social cognition and knowledge production processes in public international law. We aim to close this gap by examining the implications of framing effects for preference and belief formation in specific settings in public international law. By looking at issue framing in addition to equivalency framing (which includes most well-known gain-loss framing effects), we broaden the scope of framing effects as traditionally studied in behavioral law and economics by also including findings from research in political communication. In the first part of this chapter, we provide an overview of the experimental evidence of both types of framing, show how it has already been incorporated into neighboring disciplines to public international law, and untangle the difference between preference reversals and a change in beliefs. In the second part, we identify typical situations in public international law where framing effects play an important role in social cognition and knowledge production processes. Without claiming to be exhaustive, we focus on international negotiations, international adjudication, global performance indicators, and norm framing.
    Date: 2020
  7. By: Jerrim, John (University College London); Shure, Nikki (University College London); Wyness, Gill (University College London)
    Abstract: There has been much interest across the social sciences in the link between young people's socioemotional (non-cognitive) skills and their educational achievement. But much of this research has focused upon the role of the Big Five personality traits. This paper contributes new evidence by examining two inter-related non-cognitive factors that are rarely studied in the literature: ambition and drive. We use unique survey-administrative linked data from England, gathered in the lead-up to high-stakes compulsory school exams, which allow us to control for a rich set of background characteristics, prior educational attainment and, unusually, school fixed effects. Our results illustrate substantial gender and immigrant gaps in young people's ambitiousness, while the evidence for socio-economic differences is more mixed. Conversely, we find a strong socioeconomic gradient in drive, but no gender gap. Both academically ambitious and driven teenagers achieve grades around 0.37 standard deviations above their peers, even controlling for prior academic attainment and school attended.
    Keywords: socio-economic gaps, gender gaps, aspirations, secondary school, higher education
    JEL: I24 J24
    Date: 2020–07

This nep-cbe issue is ©2020 by Marco Novarese. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
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