Using Behavioral Insights For a Better Understanding of Economic Decisions (Regarding Savings, Inequality and Dishonesty)

This dissertation consists of three essays on behavioral economics, with a general aim of enriching our understanding of economic decisions using behavioral insights and experimental methodology. Each essay takes on one particular topic with this general aim.

The first chapter studies savings behavior of the poor. In this project, partnering with a savings product provider in Kenya, we tested the extent to which behavioral interventions and financial incentives can increase the saving rate of individuals with low and irregular income. Our experiment lasted for six months and included a total of twelve conditions. The control condition received weekly reminders and balance reporting via text messages. The treatment conditions received in addition one of the following interventions: (1) reminder text messages framed as if they came from the participant’s kid (2) a golden colored coin with numbers for each week of the trial, on which participants were asked to keep track of their weekly deposits (3) a match of weekly savings: The match was either 10% or 20% up to a certain amount per week. The match was either deposited at the end of each week or the highest possible match was deposited at the start of each week and was adjusted at the end. Among these interventions, by far the most effective was the coin: Those in the coin condition saved on average the highest amount and more than twice as those in the control condition. We hypothesize that being a tangible track-keeping object; the coin made subjects remember to save more often. Our results support the line of literature suggesting that saving decisions involve psychological aspects and that policy makers and product designers should take these influences into account.

The second chapter is related to views towards inequality. In this project, we investigate how the perceived fairness of income distributions depends on the beliefs about the process that generated the inequality. Specifically, we examine how two crucial features of this process affect fairness views: (1) Procedural justice - equal treatment of all, (2) Agency - one's ability to determine his/her income. We do this in a lab experiment by varying the equality of opportunity (procedural justice), and one's ability to make choices, which consequently influence subjects’ ability to influence their income (agency). We then elicit ex-post redistribution decisions of the earnings as a function of these two elements. Our results suggest both agency and procedural justice matter for fairness. Our main findings can be summarized as follows: (1) Highlighting the importance of agency, we find that inequality resulting from risk is considered to be fair only when risk is chosen freely; (2) Highlighting the importance of procedural justice, we find that introducing inequality of opportunity significantly increases redistribution, however the share of subjects redistributing none remain close to the share of subjects redistributing fully revealing an underlying heterogeneity in the population about how fairness views should account for inequality of opportunity.

The third chapter is on morality. In this project, we study whether religious rituals act as an internal reminder for basic moral principles and thus affect moral judgments. To this end, we conducted two survey experiments in Turkey and Israel to specifically test the effect of Ramadan and Yom Kippur. The results from the Turkish sample how that Ramadan has a significant effect on moral judgments to some extent for those who report to believe in God. Those who believe in God judged the moral acceptability of ten out of sixty one actions significantly differently in Ramadan, whereas those who reported not to believe in God significantly changed their judgments only for one action in Ramadan. Our results extends the hypothesis established by lab experiments that religious reminders have a significant effect on morality, by testing it in the field in the natural environment of religious rituals.

This thesis is part of a broader collaborative research agenda with both colleagues and advisors. The programming, analyses, and writing, as well as any errors in this work, are my own.

Patient beliefs and behaviors about genomic risk for type 2 diabetes: Implications for prevention

Copyright © Taylor & Francis Group, LLC 2015.Type 2 diabetes is a major health burden in the United States, and population trends suggest this burden will increase. High interest in, and increased availability of, testing for genetic risk of type 2 diabetes presents a new opportunity for reducing type 2 diabetes risk for many patients; however, to date, there is little evidence that genetic testing positively affects type 2 diabetes prevention. Genetic information may not fit patients illness representations, which may reduce the chances of risk-reducing behavior changes. The present study aimed to examine illness representations in a clinical sample who are at risk for type 2 diabetes and interested in genetic testing. The authors used the Common Sense Model to analyze survey responses of 409 patients with type 2 diabetes risk factors. Patients were interested in genetic testing for type 2 diabetes risk and believed in its importance. Most patients believed that genetic factors are important to developing type 2 diabetes (67%), that diet and exercise are effective in preventing type 2 diabetes (95%), and that lifestyle changes are more effective than drugs (86%). Belief in genetic causality was not related to poorer self-reported health behaviors. These results suggest that patients interest in genetic testing for type 2 diabetes might produce a teachable moment that clinicians can use to counsel behavior change.

GIS-based Association Between PM10 and Allergic Diseases in Seoul: Implications for Health and Environmental Policy.

PURPOSE: The role of PM10 in the development of allergic diseases remains controversial among epidemiological studies, partly due to the inability to control for spatial variations in large-scale risk factors. This study aims to investigate spatial correspondence between the level of PM10 and allergic diseases at the sub-district level in Seoul, Korea, in order to evaluate whether the impact of PM10 is observable and spatially varies across the subdistricts. METHODS: PM10 measurements at 25 monitoring stations in the city were interpolated to 424 sub-districts where annual inpatient and outpatient count data for 3 types of allergic diseases (atopic dermatitis, asthma, and allergic rhinitis) were collected. We estimated multiple ordinary least square regression models to examine the association of the PM10 level with each of the allergic diseases, controlling for various sub-district level covariates. Geographically weighted regression (GWR) models were conducted to evaluate how the impact of PM10 varies across the sub-districts. RESULTS: PM10 was found to be a significant predictor of atopic dermatitis patient count (P<0.01), with greater association when spatially interpolated at the sub-district level. No significant effect of PM10 was observed on allergic rhinitis and asthma when socioeconomic factors were controlled for. GWR models revealed spatial variation of PM10 effects on atopic dermatitis across the sub-districts in Seoul. The relationship of PM10 levels to atopic dermatitis patient counts is found to be significant only in the Gangbuk region (P<0.01), along with other covariates including average land value, poverty rate, level of education and apartment rate (P<0.01). CONCLUSIONS: Our findings imply that PM10 effects on allergic diseases might not be consistent throughout Seoul. GIS-based spatial modeling techniques could play a role in evaluating spatial variation of air pollution impacts on allergic diseases at the sub-district level, which could provide valuable guidelines for environmental and public health policymakers.

The tithe: Public research university STEM faculty perspectives on sponsored research indirect costs

This study sought to understand the phenomenon of faculty involvement in indirect cost under-recovery. The focus of the study was on public research university STEM (science, technology, engineering and mathematics) faculty, and their perspectives on, and behavior towards, a higher education fiscal policy. The explanatory scheme was derived from anthropological theory, and incorporated organizational culture, faculty socialization, and political bargaining models in the conceptual framework. This study drew on two key assumptions. The first assumption was that faculty understanding of, and behavior toward, indirect cost recovery represents values, beliefs, and choices drawn from the distinct professional socialization and distinct culture of faculty. The second assumption was that when faculty and institutional administrators are in conflict over indirect cost recovery, the resultant formal administrative decision comes about through political bargaining over critical resources. The research design was a single site, qualitative case study with a focus on learning the meaning of the phenomenon as understood by the informants. In this study the informants were tenured and tenure track research university faculty in the STEM fields who were highly successful at obtaining Federal sponsored research funds, with individual sponsored research portfolios of at least one million dollars. The data consisted of 11 informant interviews, bolstered by documentary evidence. The findings indicated that faculty socialization and organizational culture were the most dominant themes, while political bargaining emerged as significantly less prominent. Public research university STEM faculty are most concerned about the survival of their research programs and the discovery facilitated by their research programs. They resort to conjecture when confronted by the issue of indirect cost recovery. The findings direct institutional administrators to consider less emphasis on compliance and hierarchy when working with expert professionals such as science faculty. Instead a more effective focus might be on communication and clarity in budget processes and organizational decision-making, and a concentration on critical administrative support that can relieve faculty administrative burdens. For higher education researchers, the findings suggest that we need to create more sophisticated models to help us understand organizations dependent on expert professionals.

The honest broker; making sense of science in policy and politics

p.81-82

The honest broker; making sense of science in policy and politics

p.81-82

An investigation of assessment policy and practices in terms of broad social and educational purposes

Based upon relevant literature, this study investigated the assessment policy and practices for the BSc (Hons) Computing Science programme at the University of Greenwich (UOG), contextualising these in terms of broad social and educational purposes. It discusses Assessment, and then proceeds to give a critical evaluation of the assessment policy and practices at the UOG. Although this is one case study, because any of the features of the programme are generic to other programmes and institutions, it is of wider value and has further implications. The study was concluded in the summer of 2002. It concludes that overall, the programme's assessment policy and practices are well considered in terms of broad social and educational purposes, although it identifies and outlines several possible improvements, as well as raising some major issues still to be addressed which go beyond assessment practices.

A policy-definition language and prototype implementation library for policy-based autonomic systems

This paper presents work towards generic policy toolkit support for autonomic computing systems in which the policies themselves can be adapted dynamically and automatically. The work is motivated by three needs: the need for longer-term policy-based adaptation where the policy itself is dynamically adapted to continually maintain or improve its effectiveness despite changing environmental conditions; the need to enable non autonomics-expert practitioners to embed self-managing behaviours with low cost and risk; and the need for adaptive policy mechanisms that are easy to deploy into legacy code. A policy definition language is presented; designed to permit powerful expression of self-managing behaviours. The language is very flexible through the use of simple yet expressive syntax and semantics, and facilitates a very diverse policy behaviour space through both hierarchical and recursive uses of language elements. A prototype library implementation of the policy support mechanisms is described. The library reads and writes policies in well-formed XML script. The implementation extends the state of the art in policy-based autonomics through innovations which include support for multiple policy versions of a given policy type, multiple configuration templates, and meta-policies to dynamically select between policy instances and templates. Most significantly, the scheme supports hot-swapping between policy instances. To illustrate the feasibility and generalised applicability of these tools, two dissimilar example deployment scenarios are examined. The first is taken from an exploratory implementation of self-managing parallel processing, and is used to demonstrate the simple and efficient use of the tools. The second example demonstrates more-advanced functionality, in the context of an envisioned multi-policy stock trading scheme which is sensitive to environmental volatility

Generic support for policy-based self-adaptive systems

This paper presents a policy definition language which forms part of a generic policy toolkit for autonomic computing systems in which the policies themselves can be modified dynamically and automatically. Targeted enhancements to the current state of practice include: policy self-adaptation where the policy itself is dynamically modified to match environmental conditions; improved support for non autonomics-expert developers; and facilitating easy deployment of adaptive policies into legacy code. The policy definition language permits powerful expression of self-managing behaviours and facilitates a diverse policy behaviour space. Features include support for multiple versions of a given policy type, multiple configuration templates, and meta policies to dynamically select between policy instances. An example deployment scenario illustrates advanced functionality in the context of a multi policy stock trading system which is sensitive to environmental volatility.

Policy-based techniques for self-managing parallel applications

This paper presents an empirical investigation of policy-based self-management techniques for parallel applications executing in loosely-coupled environments. The dynamic and heterogeneous nature of these environments is discussed and the special considerations for parallel applications are identified. An adaptive strategy for the run-time deployment of tasks of parallel applications is presented. The strategy is based on embedding numerous policies which are informed by contextual and environmental inputs. The policies govern various aspects of behaviour, enhancing flexibility so that the goals of efficiency and performance are achieved despite high levels of environmental variability. A prototype self-managing parallel application is used as a vehicle to explore the feasibility and benefits of the strategy. In particular, several aspects of stability are investigated. The implementation and behaviour of three policies are discussed and sample results examined.

The AGILE policy expression language for autonomic systems

This paper presents the AGILE policy expression language. The language enables powerful expression of self-managing behaviours and facilitates policy-based autonomic computing in which the policies themselves can be adapted dynamically and automatically. The language is generic so as to be deployable across a wide spectrum of application domains, and is very flexible through the use of simple yet expressive syntax and semantics. The development of AGILE is motivated by the need for adaptive policy mechanisms that are easy to deploy into legacy code and can be used by non autonomics-expert practitioners to embed self-managing behaviours with low cost and risk. A library implementation of the policy language is described. The implementation extends the state of the art in policy-based autonomics through innovations which include support for multiple policy versions of a given policy type, multiple configuration templates, and higher-level ‘meta-policies’ to dynamically select between differently configured business-logic policy instances and templates. Two dissimilar example deployment scenarios are examined.

Policy-driven self-management for an automotive middleware

This paper describes work towards the deployment of self-managing capabilities into an advanced middleware for automotive systems. The middleware will support a range of futuristic use-cases requiring context-awareness and dynamic system configuration. Several use-cases are described and their specific context-awareness requirements identified. The discussion is accompanied by a justification for the selection of policy-based computing as the autonomics technique to drive the self-management. The specific policy technology to be deployed is described briefly, with a focus on its specific features that are of direct relevance to the middleware project. A selected use-case is explored in depth to illustrate the extent of dynamic behaviour achievable in the proposed middleware architecture, which is composed of several policy-configured services. An early demonstration application which facilitates concept evaluation is presented and a sequence of typical device-discovery events is worked through

Policy-centric integration and dynamic composition of autonomic computing techniques

This paper presents innovative work in the development of policy-based autonomic computing. The core of the work is a powerful and flexible policy-expression language AGILE, which facilitates run-time adaptable policy configuration of autonomic systems. AGILE also serves as an integrating platform for other self-management technologies including signal processing, automated trend analysis and utility functions. Each of these technologies has specific advantages and applicability to different types of dynamic adaptation. The AGILE platform enables seamless interoperability of the different technologies to each perform various aspects of self-management within a single application. The various technologies are implemented as object components. Self-management behaviour is specified using the policy language semantics to bind the various components together as required. Since the policy semantics support run-time re-configuration, the self-management architecture is dynamically composable. Additional benefits include the standardisation of the application programmer interface, terminology and semantics, and only a single point of embedding is required.

Towards policy-based self-configuration of embedded systems

This paper describes work towards the deployment of flexible self-management into real-time embedded systems. A challenging project which focuses specifically on the development of a dynamic, adaptive automotive middleware is described, and the specific self-management requirements of this project are discussed. These requirements have been identified through the refinement of a wide-ranging set of use cases requiring context-sensitive behaviours. A sample of these use-cases is presented to illustrate the extent of the demands for self-management. The strategy that has been adopted to achieve self-management, based on the use of policies is presented. The embedded and real-time nature of the target system brings the constraints that dynamic adaptation capabilities must not require changes to the run-time code (except during hot update of complete binary modules), adaptation decisions must have low latency, and because the target platforms are resource-constrained the self-management mechanism have low resource requirements (especially in terms of processing and memory). Policy-based computing is thus and ideal candidate for achieving the self-management because the policy itself is loaded at run-time and can be replaced or changed in the future in the same way that a data file is loaded. Policies represent a relatively low complexity and low risk means of achieving self-management, with low run-time costs. Policies can be stored internally in ROM (such as default policies) as well as externally to the system. The architecture of a designed-for-purpose powerful yet lightweight policy library is described. A suitable evaluation platform, supporting the whole life-cycle of feasibility analysis, concept evaluation, development, rigorous testing and behavioural validation has been devised and is described.

A versatile policy toolkit supporting run-time policy reconfiguration

This paper describes an autonomics development tool which serves as both a powerful and flexible policy-expression language and a policy-based framework that supports the integration and dynamic composition of several autonomic computing techniques including signal processing, automated trend analysis and utility functions. Each of these technologies has specific advantages and applicability to different types of dynamic adaptation. The AGILE platform enables seamless interoperability of the different technologies to each perform various aspects of self-management within a single application. Self-management behaviour is specified using the policy language semantics to bind the various technologies together as required. Since the policy semantics support run-time re-configuration, the self-management architecture is dynamically composable. The policy language and implementation library have integrated support for self-stabilising behaviour, enabling oscillation and other forms of instability to be handled at the policy level with very little effort on the part of the application developer. Example applications are presented to illustrate the integration of different autonomics techniques, and the achievement of dynamic composition.