research proposal behavioral economics

Behavioral Economics Research Paper Topics

This list of behavioral economics research paper topics is intended to provide students and researchers with a comprehensive guide for selecting research topics in the field of behavioral economics. The importance of choosing a pertinent and engaging topic for your research paper is paramount, and this guide is designed to facilitate this crucial process. We offer an extensive list of topics, divided into ten categories, each with ten unique ideas. Additionally, we provide expert advice on how to select a topic from this multitude and how to write a compelling research paper in behavioral economics. Lastly, we introduce iResearchNet’s professional writing services, tailored to support your academic journey and ensure success in your research endeavors.

100 Behavioral Economics Research Paper Topics

Choosing a research paper topic is a critical step in the research process. The topic you select will guide your study and influence the complexity and relevance of your work. In the field of behavioral economics, there are numerous intriguing topics that can be explored. To assist you in this process, we have compiled a comprehensive list of behavioral economics research paper topics. These topics are divided into ten categories, each offering a different perspective on behavioral economics.

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• The role of heuristics in decision-making
• Prospect theory and its applications
• Time inconsistency and hyperbolic discounting
• The endowment effect and loss aversion
• Mental accounting and its implications
• The role of anchoring in economic decisions
• Framing effect in marketing strategies
• The paradox of choice: More is less
• Nudge theory in public policy
• Trust game in behavioral economics
• The role of emotions in economic decisions
• Overconfidence bias in financial markets
• Decision-making under uncertainty
• The impact of social norms on economic behavior
• The role of fairness and inequality aversion in economic decisions
• The effect of cognitive dissonance on consumer behavior
• The impact of stress on economic decisions
• The role of regret and disappointment in economic decisions
• The effect of peer influence on economic behavior
• The role of culture in economic decision-making
• The use of nudges in public policy
• The impact of behavioral economics on tax policy
• The role of behavioral economics in health policy
• Behavioral insights in environmental policy
• The influence of behavioral economics on education policy
• The role of behavioral economics in social welfare policy
• The impact of behavioral economics on retirement policy
• Behavioral economics and traffic policy
• The role of behavioral economics in energy policy
• The influence of behavioral economics on housing policy
• The role of behavioral biases in personal financial decisions
• The impact of financial literacy on economic behavior
• Behavioral economics and retirement savings
• The role of behavioral economics in credit card debt
• The impact of behavioral economics on investment decisions
• Behavioral economics and insurance decisions
• The role of behavioral economics in household budgeting
• The impact of behavioral economics on mortgage decisions
• Behavioral economics and financial planning
• The role of behavioral economics in financial education
• The role of behavioral economics in pricing strategies
• Behavioral economics and consumer choice
• The impact of behavioral economics on advertising
• Behavioral economics and product design
• The role of behavioral economics in sales strategies
• Behavioral economics and customer loyalty
• The impact of behavioral economics on branding
• Behavioral economics and e-commerce
• The role of behavioral economics in business negotiations
• Behavioral economics and corporate decision-making
• The role of behavioral economics in health behaviors
• Behavioral economics and healthcare decisions
• The impact of behavioral economics on health insurance choices
• Behavioral economics and preventive health care
• The role of behavioral economics in obesity and diet choices
• Behavioral economics and smoking cessation
• The impact of behavioral economics on medication adherence
• Behavioral economics and mental health
• The role of behavioral economics in exercise and physical activity
• Behavioral economics and alcohol consumption
• The role of behavioral economics in promoting sustainable behavior
• Behavioral economics and energy conservation
• The impact of behavioral economics on recycling behavior
• Behavioral economics and water conservation
• The role of behavioral economics in climate change mitigation
• Behavioral economics and sustainable transportation
• The impact of behavioral economics on sustainable consumption
• Behavioral economics and green investments
• The role of behavioral economics in biodiversity conservation
• Behavioral economics and waste reduction
• The role of behavioral economics in digital marketing
• Behavioral economics and online shopping behavior
• The impact of behavioral economics on social media usage
• Behavioral economics and cybersecurity
• The role of behavioral economics in technology adoption
• Behavioral economics and online privacy decisions
• The impact of behavioral economics on mobile app usage
• Behavioral economics and virtual reality
• The role of behavioral economics in video game design
• Behavioral economics and artificial intelligence
• The role of behavioral economics in educational choices
• Behavioral economics and student motivation
• The impact of behavioral economics on study habits
• Behavioral economics and school attendance
• The role of behavioral economics in academic performance
• Behavioral economics and college enrollment decisions
• The impact of behavioral economics on student loan decisions
• Behavioral economics and teacher incentives
• The role of behavioral economics in educational policy
• Behavioral economics and lifelong learning
• The role of neuroscience in behavioral economics
• Behavioral economics and inequality
• The impact of behavioral economics on economic modeling
• Behavioral economics and big data
• The role of behavioral economics in addressing social issues
• Behavioral economics and virtual currencies
• The impact of behavioral economics on behavioral change interventions
• Behavioral economics and the sharing economy
• The role of behavioral economics in understanding happiness and well-being
• Behavioral economics and the future of work

This comprehensive list of behavioral economics research paper topics provides a wide range of options for your research. Each category offers unique insights into the different aspects of behavioral economics, from fundamental concepts to future directions. Remember, the best research paper topic is one that not only interests you but also has sufficient resources for you to explore. We hope this list inspires you and aids you in your journey to write a compelling research paper in behavioral economics.

Introduction to Behavioral Economics

Behavioral economics is an intriguing and dynamic field that bridges the gap between traditional economic theory and actual human behavior. It integrates insights from psychology, judgment, and decision-making into economic analysis, providing a more accurate and nuanced understanding of human behavior.

Traditional economic theory often assumes that individuals are rational agents who make decisions based on maximizing their utility. However, behavioral economics challenges this assumption, recognizing that individuals often act irrationally due to various cognitive biases and heuristics. These deviations from rationality can significantly impact economic decisions and outcomes, making behavioral economics a critical field of study.

Research papers in behavioral economics allow students to delve deeper into specific areas of interest, contributing to their personal knowledge and the broader academic community. These papers can explore a wide range of topics, from understanding the role of cognitive biases in financial decision-making to examining the impact of behavioral interventions on public policy.

The importance of behavioral economics extends beyond academia. It has real-world implications in various sectors, including policy-making, business, finance, and healthcare. By understanding the psychological underpinnings of economic decisions, we can design better products, policies, and interventions that align with actual human behavior.

How to Choose a Behavioral Economics Topic

Choosing a research topic is a critical step in the research process. The topic you select will guide your study, influence the complexity and relevance of your work, and determine how engaged you are throughout the process. In the field of behavioral economics, there are numerous intriguing topics that can be explored. Here are some expert tips to assist you in this process:

• Understanding Your Interests: The first step in choosing a research topic is to understand your interests. What areas of behavioral economics fascinate you the most? Are you interested in how behavioral economics influences policy making, or are you more intrigued by its role in personal finance or marketing? Reflecting on these questions can help you narrow down your options and choose a topic that truly engages you. Remember, research is a time-consuming process, and your interest in the topic will keep you motivated.
• Evaluating the Scope of the Topic: Once you have identified your areas of interest, the next step is to evaluate the scope of potential topics. A good research topic should be neither too broad nor too narrow. If it’s too broad, you may struggle to cover all aspects of the topic effectively. If it’s too narrow, you may have difficulty finding enough information to support your research. Try to choose a topic that is specific enough to be manageable but broad enough to have sufficient resources.
• Assessing Available Resources and Data: Before finalizing a topic, it’s important to assess the available resources and data. Are there enough academic sources, such as books, journal articles, and reports, that you can use for your research? Is there accessible data that you can analyze if your research requires it? A preliminary review of literature and data can save you from choosing a topic with limited resources.
• Considering the Relevance and Applicability of the Topic: Another important factor to consider is the relevance and applicability of the topic. Is the topic relevant to current issues in behavioral economics? Can the findings of your research be applied in real-world settings? Choosing a relevant and applicable topic can increase the impact of your research and make it more interesting for your audience.
• Seeking Advice: Don’t hesitate to seek advice from your professors, peers, or other experts in the field. They can provide valuable insights, suggest resources, and help you refine your topic. Discussing your ideas with others can also help you see different perspectives and identify potential issues that you may not have considered.
• Flexibility: Finally, be flexible. Research is a dynamic process, and it’s okay to modify your topic as you delve deeper into your study. You may discover new aspects of the topic that are more interesting or find that some aspects are too challenging to explore due to constraints. Being flexible allows you to adapt your research to these changes and ensure that your study is both feasible and engaging.

Remember, choosing a research topic is not a decision to be taken lightly. It requires careful consideration and planning. However, with these expert tips, you can navigate this process more effectively and choose a behavioral economics research paper topic that not only meets your academic requirements but also fuels your passion for learning.

How to Write a Behavioral Economics Research Paper

Writing a research paper in behavioral economics, like any other academic paper, requires careful planning, thorough research, and meticulous writing. Here are some expert tips to guide you through this process:

• Understanding the Structure of a Research Paper: A typical research paper includes an introduction, literature review, methodology, results, discussion, and conclusion. The introduction presents your research question and its significance. The literature review provides an overview of existing research related to your topic. The methodology explains how you conducted your research. The results section presents your findings, and the discussion interprets these findings in the context of your research question. Finally, the conclusion summarizes your research and suggests areas for future research.
• Developing a Strong Thesis Statement: Your thesis statement is the central argument of your research paper. It should be clear, concise, and debatable. A strong thesis statement guides your research and helps your readers understand the purpose of your paper.
• Conducting Thorough Research: Before you start writing, conduct a thorough review of the literature related to your topic. This will help you understand the current state of research in your area, identify gaps in the literature, and position your research within this context. Use academic databases to find relevant books, journal articles, and other resources. Remember to evaluate the credibility of your sources and take detailed notes to help you when writing.
• Writing and Revising Drafts: Start writing your research paper by creating an outline based on the structure of a research paper. This will help you organize your thoughts and ensure that you cover all necessary sections. Write a first draft without worrying too much about perfection. Focus on getting your ideas down first. Then, revise your draft to improve clarity, coherence, and argumentation. Make sure each paragraph has a clear topic sentence and supports your thesis statement.
• Proper Citation and Avoiding Plagiarism: Always cite your sources properly to give credit to the authors whose work you are building upon and to avoid plagiarism. Familiarize yourself with the citation style required by your institution or discipline, such as APA, MLA, Chicago/Turabian, or Harvard. There are many citation tools available online that can help you with this.
• Seeking Feedback: Don’t hesitate to seek feedback on your drafts from your professors, peers, or writing centers at your institution. They can provide valuable insights and help you improve your paper.
• Proofreading: Finally, proofread your paper to check for any grammatical errors, typos, or inconsistencies in formatting. A well-written, error-free paper makes a good impression on your readers and enhances the credibility of your research.

Remember, writing a research paper is a process that requires time, effort, and patience. Don’t rush through it. Take your time to understand your topic, conduct thorough research, and write carefully. With these expert tips, you can write a compelling behavioral economics research paper that contributes to your academic success and the broader field of behavioral economics.

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• Writing a Research Proposal

This InfoGuide assists students starting their research proposal and literature review.

• Introduction
• Research Process
• Types of Research Methodology
• Data Collection Methods
• Anatomy of a Scholarly Article
• Finding a topic
• Identifying a Research Problem
• Problem Statement
• Research Question
• Research Design
• Search Strategies
• Psychology Database Limiters
• Literature Review Search
• Annotated Bibliography
• Writing a Literature Review

Writing a Rsearch Proposal

A  research proposal  describes what you will investigate, why it’s important, and how you will conduct your research.  Your paper should include the topic, research question and hypothesis, methods, predictions, and results (if not actual, then projected).

Research Proposal Aims

The format of a research proposal varies between fields, but most proposals will contain at least these elements:

Literature review

• Research design

Reference list

While the sections may vary, the overall objective is always the same. A research proposal serves as a blueprint and guide for your research plan, helping you get organized and feel confident in the path forward you choose to take.

Proposal Format

The proposal will usually have a  title page  that includes:

• The proposed title of your project
• Your supervisor’s name
• Your institution and department

Introduction The first part of your proposal is the initial pitch for your project. Make sure it succinctly explains what you want to do and why.. Your introduction should:

• Introduce your  topic
• Give necessary background and context
• Outline your  problem statement  and  research questions To guide your  introduction , include information about:  
• Who could have an interest in the topic (e.g., scientists, policymakers)
• How much is already known about the topic
• What is missing from this current knowledge
• What new insights will your research contribute
• Why you believe this research is worth doing

As you get started, it’s important to demonstrate that you’re familiar with the most important research on your topic. A strong  literature review  shows your reader that your project has a solid foundation in existing knowledge or theory. It also shows that you’re not simply repeating what other people have done or said, but rather using existing research as a jumping-off point for your own.

In this section, share exactly how your project will contribute to ongoing conversations in the field by:

• Comparing and contrasting the main theories, methods, and debates
• Examining the strengths and weaknesses of different approaches
• Explaining how will you build on, challenge, or  synthesize  prior scholarship

Research design and methods

Following the literature review, restate your main  objectives . This brings the focus back to your project. Next, your  research design  or  methodology  section will describe your overall approach, and the practical steps you will take to answer your research questions. Write up your projected, if not actual, results.

Contribution to knowledge

To finish your proposal on a strong note, explore the potential implications of your research for your field. Emphasize again what you aim to contribute and why it matters.

For example, your results might have implications for:

• Improving best practices
• Informing policymaking decisions
• Strengthening a theory or model
• Challenging popular or scientific beliefs
• Creating a basis for future research

Lastly, your research proposal must include correct  citations  for every source you have used, compiled in a  reference list . To create citations quickly and easily, you can use free APA citation generators like BibGuru. Databases have a citation button you can click on to see your citation. Sometimes you have to re-format it as the citations may have mistakes. 

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Development economics, lecture 4: behavioral development economics: introduction.

Description: Part 1 of 2 of Behavioral Development Economics. Introduces and provides history of behavioral development, discusses the Euler Puzzle, provides an application to health, and a discussion of demand for commitment.

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Instructor: Frank Schilbach

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Behavioral Economics

A Tutorial for Behavior Analysts in Practice

• Published: 01 June 2017
• Volume 6 , pages 34–54, ( 2013 )

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• Derek D. Reed 1 ,
• Christopher R. Niileksela 2 &
• Brent A. Kaplan 1  

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In recent years, behavioral economics has gained much attention in psychology and public policy. Despite increased interest and continued basic experimental studies, the application of behavioral economics to therapeutic settings remains relatively sparse. Using examples from both basic and applied studies, we provide an overview of the principles comprising behavioral economic perspectives and discuss implications for behavior analysts in practice. A call for further translational research is provided.

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Hypothesized Pathway and Bias

Behavioral Medicine/Behavioral Science in Pharmacy

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Department of Applied Behavioral Science, University of Kansas, 4048 Dole Human Development Center, 1000 Sunnyside Avenue, Lawrence, KS, 66045-7555, USA

Derek D. Reed & Brent A. Kaplan

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The authors thank the various clinicians and behavior analysts with whom they have worked with over the years that prompted the writing of this tutorial, as well as Scott Wiggins and Dave Jarmolowicz for their assistance to the authors during the course of manuscript preparation. Finally, they acknowledge the role of their Applied Behavioral Science (ABSC) 509 students for persistently asking for examples of how basic behavioral science translates to practice. The examples derived from these conversations and discussions have been integrated throughout the tutorial.

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Reed, D.D., Niileksela, C.R. & Kaplan, B.A. Behavioral Economics. Behav Analysis Practice 6 , 34–54 (2013). https://doi.org/10.1007/BF03391790

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9 Behavioral Economics, Program Implementation, and Policy Design

William J. Congdon, Urban Institute

Joshua L. Wright, ideas42

• Published: 18 September 2023
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Public policy increasingly draws on insights from behavioral science—research from psychology and behavioral economics about how individuals decide and act—to inform both program administration and policy design. This chapter surveys the range of the potential channels by which behavioral insights can inform questions of program design and delivery. The authors define, clarify, and characterize the distinction between applications of low-cost, choice-preserving nudges for improving program implementation, on the one hand, and the application of behavioral insights for informing program and policy design, on the other. In doing so, they provide alternative, systematic processes for identifying, evaluating, and extrapolating from behavioral interventions in either case. The chapter is illustrated with examples of applications to issues in retirement security, safety net programs, and healthcare policies.

Economic and social policy outcomes almost universally depend on how individuals respond to the markets, incentives, and other conditions that they create. Retirement savings incentives only work if the intended group of workers understand and are motivated by them. Nutrition assistance programs are only effective if food-insecure families can successfully claim, maintain access to, and use the benefits they offer. Carbon taxes may more or less effectively address climate change depending on how individuals perceive those taxes and are dissuaded from purchasing carbon-intensive goods and services as a result. A health insurance program that requires individuals to sign up and choose from among a menu of insurance options depends on individuals doing this consistently and well. And so on.

Recognizing this, policy design and program implementation increasingly draw on behavioral insights—research from psychology and behavioral economics about how individuals decide and act—to inform both program administration and policy design. The key perspective this approach brings to policy questions is to take an empirical approach to how human behavior might mediate outcomes ( Thaler 2016 ) (box 9.1 elaborates briefly on the distinction between behavioral and traditional economic approaches). Often the relationship between policy design and individual behavior is assumed, or based on theory, or simply not investigated very carefully. But, based on a growing body of both research and policy applications, we now know that how individuals actually interact with policies and programs can contradict traditional assumptions or depend on details of program features that standard approaches may overlook. For example, changing a default rule in a retirement savings plan can double participation, and even sending an email reminder can lead to substantial increases in plan participation and retirement savings ( Madrian and Shea 2001 ; Benartzi et al. 2017 ).

This approach is no longer new. Examples of behavioral policy applications at the federal level in the United States have proliferated, from the early experience of encouraging automatic enrollment in retirement plans, to the Obama-era Social and Behavioral Sciences Team (SBST), to ongoing work by the Department of Health and Human Services and Department of Labor (for more on recent work by the DOL, see chapter 10 in this volume by Nightingale, Amin, and Perez-Johnson). 1 These efforts have often been undertaken in conjunction with or build on the work of an expanding network of policy-focused academic research in behavioral economics, as well as applied research organizations, like ideas42 and MDRC. Recent years have seen a growing number of policy applications at the state and local levels, in places like Massachusetts, New Mexico, Chicago, and New York City. And in fact these approaches are increasingly employed by governments around the world, from the early work of the UK Behavioral Insights Team to work in Australia, Canada, and Singapore, among other countries. A comprehensive review of these efforts could run to literally hundreds of distinct applications.

Economic theory and analysis traditionally make a set of standard assumptions about how individuals make decisions in the roles as economic agents—as consumers, for example, or workers. The essence of these assumptions is that individuals make consistent decisions reflecting stable and well-ordered preferences. This approach assumes, for example, that people choose consistently over time, or make decisions under uncertainty that reflect the true probabilities associated with different potential outcomes. Behavioral economics is an approach to economic analysis that treats individual preferences and decision-making as more empirical questions. This approach draws in evidence from economic and psychological research on how individuals actually form preferences, make choices, and take actions—often showing how choices and behavior are inconsistent or imperfect. For example, a behavioral economics analysis may find that individuals often make choices over time that are biased toward the present. This approach then draws out the implications of such inconsistencies for economic conclusions, such as how markets operate. In the case of policy analysis in particular, a behavioral approach can both update and modify how economists and policymakers understand the nature of market failures and, as we discuss in more detail in this chapter, inform the optimal design and implementation of policy responses.

What we will argue in this chapter, however, is that the recent explosion in policy applications of behavioral insights, while making real and positive contributions to program outcomes, policy effectiveness, and social welfare, has become too narrowly focused on questions of program implementation , to the exclusion of questions related to policy design . Our goal in this chapter is to clarify this distinction and its implications, and begin to unpack (1) the different starting points and methods for applied behavioral research that is intended to tackle the two sets of issues, and (2) the relationships between the two sets of questions and approaches. We argue in particular that despite the focus of much past work, a behavioral perspective both can and should be brought to study and inform more fundamental policy design questions. We note that we do not intend to minimize the impacts of current approaches and efforts in any way, but rather to build upon them, to widen the scope of inquiry and application of behavioral economics in policy contexts.

The remainder of this chapter proceeds as follows: In section 1 , we define, clarify, and characterize the distinction between applications of low-cost, choice-preserving nudges for understanding and improving program implementation, on the one hand, and the application of behavioral economics research for informing program and policy design, on the other. Section 2 gives an overview of using behavioral insights for research focused primarily on program implementation, laying out a process for identifying, evaluating, and extrapolating from behavioral interventions, and gives examples. Section 3 , in contrast, defines and explains how to apply the perspective of behavioral economics to questions of policy design. Section 4 concludes with some implications for policy and practice, and directions for future research.

1 Behavioral Insights, Program Implementation, and Policy Design

1.1 illustrative example: the behavioral economics of snap.

To clarify the distinction we mean to draw between behavioral economics applied to program implementation and questions of policy design, consider the specific case of the policy and program issues related to alleviating food insecurity. To make the set of issues concrete, consider the principal such program in the United States, the Supplemental Nutrition Assistance Program (SNAP), formerly the food stamps program, which provides benefits to over 40 million Americans each year. The program provides individuals and families who qualify based on income limits and other criteria with monthly benefits so they can purchase healthy food. The dollar value of the benefit varies based on economic circumstances and household size.

The effectiveness of this program is determined, in part, by several clear behavioral mediators. To participate, eligible individuals must become aware of their eligibility, sign up for the program, and in some instances show up for interviews and follow up with other information. To maintain access to the benefit, individuals must successfully respond to recertification requests or, increasingly, meet work requirements. And to effectively use the benefit to improve the nutritional outcomes for their household, recipients must undertake the planning, budgeting, shopping, and preparation activities that are required to translate the program benefits into the outcomes of good nutrition and health.

And at each point, we see evidence that is consistent with the presence and importance of these behavioral mediators: program participation rates are less than complete, eligible individuals churn off and then back on to the program at recertification, and there is evidence that the monthly benefit cycle poses planning and consumption challenges for beneficiaries ( Gennetian et al. 2016 ; Shapiro 2005 ; Seligman et al. 2014 ; Gassman-Pines and Bellows 2018 ).

One approach to applying behavioral insights to address this set of issues is to consider this as a program implementation problem—that is, taking SNAP as designed, how can we make it work better, through the application of behavioral insights? How can we extend the reach and coverage of SNAP to a broader swath of the individuals who are already eligible? Can we improve communications to make more eligible individuals aware of the program? Can we streamline applications, either by removing extraneous questions from forms, or by using of administrative data to determine eligibility? Is there something about the required office visits or interviews that could be made less onerous? Are the recertification or re-enrollment processes clear to individuals? Are they reminded of them? Can we assist individuals with planning their consumption over the month? And so on.

For this reason, these are issues that have been researched and addressed in a number of behavioral applications. For example, sending notices to people who appear eligible for SNAP based on their participation in other programs can increase participation ( Finkelstein and Notowidigdo 2018 ). Sending reminders to individuals on SNAP to recertify their eligibility to maintain access to their benefits can reduce churn. And based on this and related research, the federal government, state and local agencies, and third parties have developed innovations and improvements in how these programs are implemented. For example, the state of California is working to simplify its SNAP recertification form. Third parties like Propel have developed apps to help beneficiaries with spending and consumption smoothing. 2

But notice that this perspective and this evidence not only identify ways in which we might more effectively administer SNAP as it currently exists, but also raise questions, and point to directions, related to policy design at a much more fundamental level. That is, taking the broader set of program or social objectives that SNAP is intended to achieve—reducing food and economic insecurity, and alleviating their consequences—how might the program be better designed by taking a behavioral perspective? What is the set of eligibility criteria—such as income, assets, and household size—that should determine program eligibility to optimally balance the desire to screen and target benefits against their deterrent effect on participation? Should the program require in-person interviews or impose work requirements at all? If so, which participants should have to meet these requirements? How frequently should the program require that participants recertify their eligibility? Should it pay benefits, or offer the option to receive benefits, more frequently than monthly? And so on.

1.2 The Behavioral Economist as Plumber and Engineer

In this chapter, we label the first approach, which leverages behavioral science insights to understand and improve program outcomes, a program implementation approach, given the close relationship of this approach to implementation research ( Pressman and Wildavsky 1984 ). This research, in general, seeks to understand the detailed factors of program implementation that mediate program outcomes. Behavioral insights work in this vein operates similarly, with a focus specifically on the behavioral factors that mediate program performance and outcomes.

The defining feature of this style of work is that it takes policy and program design features—and program goals—as fixed, seeking to understand how a behavioral perspective might inform our understanding of how and why the program is or is not meeting its goals. In economics, one analogy that has been used for work in this vein is to think of one role (though not the only role) of the social scientist in the policy process as that of a plumber: someone who takes the system as built, and then repairs flaws or modifies aspects of it to make it work better ( Duflo 2017 ). This is the approach used in many behavioral applications: Taking the policy as it has been designed, can we come in and use behavioral insights to make small adjustments to implementation or administration that will make it work better?

We label the second approach, which applies the perspective of behavioral economics to inform broader questions about the optimal functional form of policies, or program parameters, a policy design approach. Applied behavioral research in this vein seeks to understand the potential implications of a behavioral perspective for how well policies and programs are meeting their underlying social and economic goals. It considers how changes in the structures of policies that reflect lessons from psychology or behavioral economics might better achieve those underlying goals.

The defining feature of this style of work is that it starts with the underlying social goal or challenge that the policy is intended to achieve or address ( Furman 2016 ). The analogy that has sometimes been used in economics is to think about this role of the social scientist in the policy process as akin to that of an engineer: someone who considers questions of how to design and build the systems, policies, and programs that might achieve particular social goals or solve important social problems ( Mankiw 2006 ). 3 This describes well the approach often taken by economists in conducting or applying research to inform policy development: given the goal of a policy to improve social welfare along some dimension, how can we draw on economic theory and evidence to design policies that do so more effectively and efficiently?

Below, we elaborate on each approach, in turn, providing illustrative examples and describing characteristic methods.

2 Behavioral Insights for Program Implementation

As noted above, behavioral insights have been widely used in policy applications to learn about and improve program implementation. This work is usually a matter of taking discrete insights about human behavior and using them to better understand how programs are or are not working as intended, and, correspondingly, how those insights can be used to improve program performance. In practice, many such applications take the form of what can be broadly classified as information interventions—communications to program participants or targeted individuals that draw on behavioral science insights to frame, remind, clarify, or make salient information in ways that promote behaviors that support program goals. As this is the more widely practiced variant of applied behavioral work, there is not only a large body of examples, but also a now relatively common method for conducting this work. Below we provide a few examples of the use of this approach and discuss the general methods used to develop and test behavioral insights interventions.

2.1 Examples of This Approach

Earned income tax credit..

The Earned Income Tax Credit (EITC) is the largest cash benefit program in the United States. It provides an important source of income security to tens of millions of working families each year, and research increasingly identifies important long-term benefits to participants and society ( Manoli and Turner 2018 ; Dow et al. 2019 ). But participation in the program remains imperfect: it is estimated that about 75 percent of eligible families claim the credit, and for some groups, such as single filers without children, the participation rate may be only a bit above 50 percent ( Plueger 2009 ). A series of research projects by academics and partners in government, taking a behavioral approach, has found that clear and simple notices to taxpayers can increase rates of EITC claiming by eligible individuals ( Bhargava and Manoli 2013 ; Manoli and Turner 2014 ; Social and Behavioral Sciences Team 2016 ; Guyton et al. 2016 ).

Temporary Assistance to Needy Families.

In Temporary Assistance to Needy Families (TANF), as with some other human services programs, failure to engage with required activities or services can result in sanctioning or other penalties. A behavioral perspective to implementing this program feature has been used to help families comply and retain benefits. In one example, the Administration for Children and Families and MDRC worked with Los Angeles County to increase the number of TANF recipients who re-engaged in the county’s welfare-to-work program by sending variants of behaviorally designed messages. The group receiving messages was 3.6 percentage points more likely to positively engage 30 days after their appointment date, overall, and the majority of this difference was driven by a loss-framed message, which improved engagement by 4.4 percentage points over a no-message control ( Farrell et al. 2016 ).

Financial aid and college completion.

The process of applying to, matriculating at, and completing college, at both two- and four-year post-secondary education institutions, is complex and fraught with behavioral challenges. Work has been done to use behavioral insights to improve success all along this spectrum, including in applying to schools, filing and refiling financial aid forms, choosing the right amount of debt to take on, starting college, succeeding in school, and repaying loans after school ( Bettinger et al. 2012 ; Castleman and Page 2015 ; ideas42 2016 ). In one example of this work, ideas42 worked with the University of Arizona to design emails to students and parents to encourage earlier financial aid application, which can increase benefits. This messaging “chunked” complex information (broke it into time-bound, understandable pieces), debiased students, and presented the action as an active choice. The most successful intervention caused filing by the early date to increase from 29 percent to 50 percent of students and increased total financial aid renewals by 3 percent.

2.2 Method of This Approach

A central feature of this approach is that it can be conducted methodically, using now well-tested processes to determine what to change in an existing program and in what way(s) to change it. This is important because too often the available set of behavioral interventions—such as defaults, social norms, or reminders—are treated as a menu of options that can simply be ported across programs and contexts. But just as a good doctor diagnoses each patient before prescribing a particular solution, applying behavioral insights to program implementation questions requires a diagnosis of the situation before suggesting a design solution. The methodology below is the one used and popularized by ideas42, created in collaboration with University of Chicago economist Sendhil Mullainathan. 4 This methodology has five parts, as illustrated in figure 9.1 and described below:

Behavioral diagnosis and design.

  Define. The first step is to accurately define the problem. This involves articulating a specific behavior to be focused on that matters to program outcomes, often in conversation with program leadership. If there are existing easily available qualitative or quantitative data, these can be looked at as well, but that is not necessary, as data will be examined more closely in the next phase of the methodology and the problem definition can be revised. More than one problem can be defined in any application, and often what is initially thought of as the problem has more than one specific behavior challenge. Each challenge will need to be diagnosed separately and considered in the design phase. At this starting point, all assumptions about what may be contributing to the problem and the potential solutions should be eliminated from the problem statement. Defining the problem(s) clearly and succinctly also ensures all stakeholders are on the same page about what problem is being worked on.

  Diagnose. The next step is to diagnose the behavioral barriers that are preventing individuals from making decisions or taking actions in ways that are consistent with program objectives and often their own preferences. This involves looking closely at the details of the context in which people (both end users and providers) are operating, and understanding the variety of psychological phenomenon that help to understand how individuals decide and do or do not take action. For example, it involves determining the effects of specific psychological factors on the behaviors of interest, such as loss aversion, failures of prospective memory, or limited attention. The information that can be drawn on to develop behavioral diagnosis can take many forms, including interviews with or surveys of program participants and staff, observations of program operations from site visits, reviews of program materials, and administrative and programmatic data.

 Drawing on an analysis of various types of programmatic data, both qualitative and quantitative, as well as insights and evidence from the broader literature, a behavioral map can be created to identify where and how behavioral factors may interact with the program context. 5 A behavioral map is a schematic representation of the decisions and actions a person must take to achieve an outcome, such as enrolling in a program. This map is then iterated on as additional data are collected and analyzed, with the aim of refining hypotheses about the ways in which program outcomes are mediated by behavioral factors. This is accomplished by looking specifically at how the particular context and features of the environment and psychological factors interact to affect decisions or actions. For example, it could mean looking at how a program participation requirement that is not salient might interact with limited attention to lead individuals to fail to access a program.

  Design. Drawing on the diagnosis, scalable interventions are designed that address the key bottlenecks. Designs can range from small-scale changes to existing programs (e.g., changing a form or outbound letter) to more complex interventions (e.g., two-way interactive text messaging). Designs can draw on the existing body of behavioral interventions—for example, tailoring, defaults, or reminders to the specific context—and they can also be new innovations developed for the specific application and concept. Initial design concepts are refined and polished to account for operational and financial limitations and are prototyped as much as possible with the users to ensure they work operationally and can be implemented with high quality and a high degree of fidelity.

  Test. In order to determine the efficacy of the design, build evidence, and learn, the designed interventions should be rigorously tested—through a randomized controlled trial (RCT), if possible. In many instances, behavioral innovations in program implementation contexts are conducive to low-cost, rapid-cycle RCTs, making use of administrative data on program outcomes and taking advantage of behavioral interventions that have low marginal costs, such as email reminders. However, if a randomized evaluation is not possible, either because of the nature of the innovation or because conducting the RCT would be too costly, other evaluation methods, such as quasi-experimental designs, can be used. 6

  Scale. Making sure that successful interventions reach scale is a critical, final stage of the process. Unless the intervention is implemented at scale, then social impact is limited.

The issue of translating rigorously tested innovations for social programs, of a behavioral science nature or otherwise, to implementation or impact at scale is a thorny one that is the subject of extensive study. Below, we highlight two notable approaches that have been taken to scaling behavioral applications in the context of public programs.

One particular approach to scaling behavioral program implementation innovations that is afforded by the often low-cost nature of this type of intervention and testing is to focus applied research efforts on applications within programs or systems that already operate at scale. Federal programs administered at the federal level sometimes have this property. Consider the examples given earlier on work with the IRS on the EITC, or work related to the Department of Education’s Free Application for Federal Student Aid (FAFSA)—these are tests where the potential for scale is often already baked in by virtue of the scale of the programs and operations. Once interventions are shown to be successful on pilot populations, they can be adopted directly by the implementing agency for the full program population.

An alternative approach to scaling the impact of behavioral innovation in program implementation is to scale capacity rather than interventions. This approach aims to enable a wider range of entities and people within policy implementing and program operating organizations to apply behavioral science rigorously, so that it becomes a normal practice for operating and continuously improving programs. At the organizational level, this sometimes includes creating an embedded behavioral science team within programs and agencies. For example, ideas42 has used this approach in partnering with cities to establish behavioral design teams within city governments, including New York City and Chicago. 7

3 Behavioral Economics and Policy Design

A complementary approach to applying behavioral economics to policy questions comes from focusing on issues related to policy design. As noted above, this work focuses on incorporating an empirical approach to human behavior into research designed to inform the more general functional form of policies or policy parameters. Because it takes broader social and economic goals as its starting point, this work typically requires a framework or model for thinking about, and evaluating, how program outcomes translate into social welfare. This approach can best be illustrated through examples; while common elements of approaches to conducting this type of research can be outlined, in practice this work is more varied.

3.1 Examples of this Approach

Student financial aid..

An important component of education policy in the United States is the set of programs that provide financial aid to students in postsecondary education, principally in the form of grants and subsidized student loans. These benefits are targeted to some extent (Pell grants, for example, are available only to low-income students), and so students are required to complete the Free Application for Federal Student Aid, or FAFSA, to access these benefits and determine their eligibility. A key consideration for policy is how to effectively target the benefits the program offers to the students it is intended to help.

Economics provides a standard model for thinking about how program access and targeting works in such cases. On the one hand, effectively targeting the benefits to the intended set of students requires gathering information about the financial status of the students and their families. On the other hand, doing so imposes some friction costs on applicants, in the form of their time and other costs associated with completing the application ( Currie 2004 ). In this model, students and families weigh the costs of completing the application against the benefits of the program, in the form of the reduced price of college. Students who will receive substantial benefits will find the friction costs worth paying, and so even a complicated and lengthy form like the FAFSA should be worthwhile. And the screening effects are, if anything, likely to be efficient: because the financial aid benefits are greater for lower-income students, these are the students for whom the costs of completing the application are most worth paying ( Nichols and Zeckhauser 1982 ).

A behavioral economics model allows for important deviations within this framework. First, it considers evidence from psychology suggesting that individuals can be significantly deterred from taking even beneficial actions by relatively small frictions or hassles such as completing a complex and lengthy application ( Bertrand et al. 2006 ). It also allows that the effect of these costs might lead to inefficient screening, that lower-income or economically disadvantaged individuals might be the most sensitive to these costs, and so most deterred by such an application ( Kleven and Kopczuk 2011 ; Mullainathan and Shafir 2013 ).

In a now famous experiment, Bettinger et al. (2012) tested the impact of providing application assistance to individuals completing the FAFSA, and found that this leads to an increase in applications for aid and college-going. This finding, along with subsequent research, motivated some improvements in the administration of the program, such as simplifying the FAFSA and allowing applicants to import data from their tax return in the online version.

But this finding has potentially more structural implications for the design of the program. While the policy was designed, implicitly or explicitly, on the assumption that the targeting benefits of having an extensive and complex FAFSA would be worth the presumed small costs of nonparticipation, this appears to be empirically incorrect. As a result, this research has implications for effectively targeting the program that go well beyond streamlining the application; it also supports and informs policy proposals to radically reduce the set of information required to determine financial aid benefits.

Health insurance.

An important policy goal for healthcare in the United States is expanding health insurance coverage and access to healthcare in an efficient way. To this end, millions of Americans now receive public or subsidized coverage through market-based mechanisms, including beneficiaries under the Affordable Care Act (ACA), Medicare Part D prescription drug coverage, and participants in Medicare Advantage programs.

There is a compelling, standard economic logic to the use of marketplaces for providing coverage, which is that by offering choices, the programs allow for variation in plans to better fit the heterogeneity of customers’ preferences and needs, while market mechanisms will generate efficient pricing and offerings as providers compete for customers. A behavioral model of health insurance plan choice allows that individuals might have difficulty choosing optimally from among health insurance offerings: that in selecting from among many plans that vary along multiple and complex dimensions—including premiums, copays, provider networks, and so on—individual choices may fall short of full optimization ( Johnson et al. 2013 ; Loewenstein et al. 2013 ). This might not only lead to individual welfare losses as participants select dominated plans, but might more generally lead to a failure of market mechanisms to generate efficiencies by diminishing the competitive pressures for providers to offer the highest quality plans at the lowest possible prices.

A growing body of literature suggests that individuals, in fact, have difficulty choosing optimally from among health insurance plans. For example, Kling et al. (2012) offered participants in Medicare Part D personalized assistance with choosing lower cost plans, and found that individuals receiving assistance elect plans that save them about $100 on average. Bhargava, Loewenstein, and Sydnor (2017) present evidence from health insurance plans with a menu of options at a large employer, showing that many individuals selected plans that were strictly dominated by other available plans. Ericson and Starc (2013) show welfare gains from additional standardization of health insurance plans in the Massachusetts exchange. These findings have led to or suggested improvements in the administration of programs, such as smart defaults in Medicare Part D, or choice support tools in ACA exchanges ( Handel and Kolstad 2015 ).

But behavioral models have potentially even larger implications, not just for the effective implementation of health insurance policies, but also for their functional form. This body of evidence suggests that the conditions of the standard model might not obtain, and that the benefits of offering consumers a choice of plans—and so expanding coverage through marketplace-based mechanisms—might be of limited value ( Ericson and Sydnor 2017 ). This line of research has direct implications for contemporary policy debates about topics such as expanding coverage through extensions of programs such as the ACA versus expanding coverage through extensions of programs such as Medicare.

Unemployment insurance.

As a final example, consider the federal-state unemployment insurance (UI) system. The system provides benefits to workers when they lose work through no fault of their own, in order to insure workers against precipitous declines in consumption, funded by taxes on employers. The benefits are time-limited and require workers to search for and be willing to return to work.

The form of UI is justified, in part, by reference to a standard economic model of UI where the program seeks to balance providing consumption smoothing benefits against any moral hazard it might create, in the form of a disincentive to quickly return to work ( Baily 1978 ; Chetty 2008 ). For this reason, the system imposes work search requirements, limits the duration and generosity of benefits, and so on. A behavioral model of unemployment insurance augments this model by allowing for forces such as procrastination or over-optimism on the part of workers to operate alongside simple work disincentives ( DellaVigna and Paserman 2005 ; Spinnewijn 2015 ; DellaVigna et al. 2017 ). In this model, moral hazard might not operate as strongly, and these other behavioral responses to UI coverage might imply a quite different set of challenges for policy ( Babcock et al. 2012 ).

The accumulating evidence on the role of behavioral factors in unemployment and how individuals respond to UI is suggestive, but is still emerging. Again, however, note that while this research points to scope for innovation in program administration, it also raises questions about larger policy design issues—the value and optimal form of work search requirements, for example, or the optimal path of weekly benefits. And note that taking that perspective, seeking to inform those aspects of policy design, points to a much different research agenda than a narrow focus on improving the implementation of the current program. The interesting policy questions—and thus the informative interventions to test, experiments to do, and research to conduct—are quite different from the implementation questions and research.

3.2 Methods

Conducting applied policy research in this vein requires a different approach than developing and testing program improvements. The methods and approach of this type of research resemble those of policy-focused, empirical economic research more broadly. These methods can be thought of as having at least several distinguishing characteristics.

Starting from policy problems.

This approach requires starting from broader social goals or policy problems, as understood within some explicit conceptualization of social welfare. The goal of this type of research is ultimately to bring a behavioral perspective to improving our understanding of how policies do, or could, improve social or economic outcomes, or solve important social problems. This research starts from, for example, the issue of college-going and completion, considering the individual and social returns, economic and otherwise, from higher levels of educational attainment, rather than starting from the issue of, say, low levels of participation in a particular financial aid program. The research brings a behavioral perspective to supplement our understanding of why observed outcomes might be less than socially optimal, either in the absence of a policy response or under prevailing policy, in order to inform the design of higher education policies that can raise social welfare.

Specifying alternative models.

This approach often requires specifying alternative models of how policy problems arise, or how individuals respond to policy. Typically, this involves a standard model, usually already implicit or explicit in policy design, or from standard economic models, along with a corresponding behavioral model. This often involves supplementing a model of a market failure with behavioral factors ( Congdon et al. 2011 ; Mullainathan et al. 2012 ). Consider again the example of unemployment insurance: beginning with the standard economic model, which emphasizes the work disincentives created by moral hazard, then specifying a behavioral alternative that includes a role for factors such as procrastination, provides both a clear direction for policy research, to determine which model better fits the evidence, as well as a lens through which researchers and policymakers can interpret evidence on, for example, job search behavior.

Developing research agendas.

This type of work proceeds by developing and advancing, implicitly or explicitly, research agendas that address knowledge gaps associated with understanding and solving policy problems. This often involves developing and investigating research questions that can build or contribute to a body of evidence that distinguishes between standard and behavioral models (or among alternative behavioral models). This approach emphasizes, for example, the need not just for research on how individuals make health insurance plan choices within a particular program context, or how those choices might be improved through specific behavioral interventions, but also research to understand how people choose and understand health insurance plans in general, to inform how policymakers should understand the value of providing plan choice.

Building bodies of evidence.

Finally, this type of work involves taking an empirical approach to these questions that involves building bodies of evidence on the behavioral dimensions of policy challenges and solutions. While this research can be experimental, like applied microeconomic research more broadly, it naturally employs a range of experimental and quasi-experimental methods to credibly and rigorously identify effects and relationships of interest. Tests of interventions to inform program implementation can contribute to these bodies of evidence when situated in a broader research framework. For example, the FAFSA experiment referred to in section 3.1 can also be situated within a model of program participation and can be related to the policy problem associated with educational attainment more generally; it thus contributes to a body of evidence that informs policy design. This evidence can, in addition, be used to update or refine estimates of response parameters in projection modeling, using microsimulation models or other methods, to estimate how policy and welfare outcomes might change under alternative forms of policy. These policy projections can then be used to directly inform policy development.

3.3 Implications and Policy Development

Drawing on findings and lessons from this research for the purposes of policymaking also takes a different approach than behavioral applications that focus on program implementation. Because the lessons from this research are for how policy parameters are set, or the functional form policies may take, this is rarely a matter of simply scaling up a particular intervention or empirical finding. Rather, it will often require incorporating the lessons from this research into the processes that inform policy design, typically through legislation or regulatory processes.

The general approach to drawing on this research to inform policy design, and improve social welfare, is then to bring these perspectives and bodies of evidence into standard mechanisms for policy development. Policymaking already has institutions and processes that refer to and draw on research from economics and other social sciences in formulating policy, and these can—and increasingly do—include and consider new and updated theory or evidence from behavioral economics on, for example, how markets fail, or how individuals respond to program parameters, or how alternative forms of policies affect social welfare. For example, research on the likely effects of reducing the FAFSA to just a few questions on, on the one hand, the social benefits that accrue due to increases in college-going, and, on the other hand, the costs this would impose to the targeting efficiency of the program has been influential in the development of legislative proposals that would dramatically simplify the FAFSA ( Dynarski and Scott-Clayton 2008 ).

4 Conclusion

Much of the research applying behavioral science or behavioral economics to policy and program issues to date has focused on questions related to program implementation, but there remains substantial scope for a behavioral perspective to inform more fundamental questions related to policy design. For applied behavioral researchers, this suggests potentially different and more expansive research agendas, beyond tests of whether particular, low-cost program innovations improve program outcomes. For policymakers, it suggests bringing a behavioral perspective into the policy development process, and not just employing behavioral insights for program improvement after policies have been designed. It also suggests that in the role policymakers and program officials can play in setting research agendas, they can seek to direct applied behavioral research to more fundamental policy questions.

Finally, although we have discussed behavioral science applications for program implementation and policy design as discrete approaches for the purposes of clarifying the distinction, in reality there are of course substantial complementarities and interactions between the two, and this is in practice more of a spectrum than a dichotomy. For example, program implementation research can clearly contribute to bodies of evidence that can inform important policy design questions, and research that seeks to inform policy design questions can leverage opportunities to experiment and learn in program implementation contexts. What the distinction highlights and cautions, for both researchers and policymakers, is that this connection is not automatic. While behavioral research can address broader policy problems or inform policy design, it can require an intentional approach that involves embedding those tests within broader research agendas, policy frameworks, or theory.

Acknowledgements

We are grateful to Samia Amin, Rekha Balu, Anthony Barrows, and Anu Rangarajan for helpful and insightful discussions and comments that informed the development of this chapter. Any errors are of course our own.

For an archive of work by SBST, see www.sbst.gov . For an example of recent DOL work, see https://www.dol.gov/agencies/oasp/evaluation/topic-areas/behavioral-interventions . For a summary of some of the efforts at HHS, see https://www.acf.hhs.gov/opre/behavioral-interventions-to-advance-self-sufficiency-bias-research-portfolio

See https://www.joinpropel.com/ .

These analogies are, obviously, imperfect. Note that both are in contrast to the role of the economist (or behavioral economist) as scientist , an analogous role that academic researchers play in building knowledge about the world, as opposed to the more applied roles as engineers or plumbers.

A more detailed description of this method is given in the ideas42 publication Changing Behavior to Improve People’s Lives: A Practical Guide , available at https://www.ideas42.org/wp-content/uploads/2020/02/I42-1152_ChangingBehaviorPaper_3-FINAL.pdf .

An example of a behavioral map can be viewed in Appendix A of Darling et al. 2017 , available at https://www.ideas42.org/wp-content/uploads/2017/06/7-Practitioner-Playbook-Final-20170517.pdf

Recall that one of the most famous policy applications in behavioral economics—default enrollment in retirement savings—is based on principally quasi-experimental evidence ( Madrian and Shea 2001 ).

See ideas42’s Behavioral Design Team Playbook on the establishment and operation of policy teams ( http://www.ideas42.org/wp-content/uploads/2018/05/BDT_Playbook_FINAL-digital.pdf ).

Babcock, Linda , William J. Congdon , Lawrence F. Katz , and Sendhil Mullainathan . 2012 . “ Notes on Behavioral Economics and Labor Market Policy. ” IZA Journal of Labor Policy 1 (1): 1–14.

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Research Group Behavioral Economics

The research group behavioral economics comprises researchers at the Alfred-Weber-Institute who aim to integrate psychological insights into economics and finance.

From a descriptive perspective, we combine theoretical analyses with experimental and empirical methods to understand how individuals and groups make economic and financial decisions. From a prescriptive perspective, we study how to design institutions that help people making better decisions.  

The Behavioral Economics group publishes theoretical, experimental and empirical work that studies economic behavior in markets, strategic interactions, and individual decisions. Its work has been published in influential economics outlets including the  American Economic Review ,  Journal of Political Economy ,  Econometrica ,  Review of Economic Studies ,  Economic Journal  or  Journal of Economic Theory ,  as well as Finance and Management outlets such as the  Review of Financial Studies ,  Management Science  or  Operations Research .

Group members serve as editors for several journals in the field, including European Economic Review, Journal of Economic Behavior and Organization, Journal of Risk and Insurance, Management Science and Operations Research .

The Behavioral Economics group offers several lectures and seminars in the field of experimental and behavioral economics and finance in both the Bachelor and Master programs. It offers the Behavioral Economics Track in the Master Program. Its members supervise Master and Bachelor theses in the field of behavioral economics.

M.Sc. Economics Study Guide Behavioral Economics

Current Courses

Behavioral finance, topics in behavioral finance, programming for experimental economics, experimental and behavioral economics: methods and case studies, organizational behavior, topics in economic theory.

Dr. Theodoros Alysandratos

PD Dr. Alexandra Avdeenko

Dr. Moumita Deb

Prof. Dr. Sebastian Ebert

Dr. Pascal Kieren

Juniorprofessorship Macroeconomics

Katharina Momsen, Ph.D.

Prof. Jörg Oechssler, Ph.D.

Prof. Dr. Christiane Schwieren

Prof. Dr. Stefan Trautmann

Prof. Christoph Vanberg, Ph.D.

Development Economics

Macro & Financial Econometrics

Environmental Economics

School of Economics

Writing a research proposal.

Developing a research proposal is a necessary part of the application process it:

• provides a basis for decision-making;
• helps to make sure that you get the most appropriate supervisor for your research.

Your research proposal does not commit you to researching in a specific area if your application is successful. 

Following a successful application, you need to provide a more comprehensive proposal which will be useful reference as your research develops.

How to write a research proposal

Organise your proposal should around a small set of ideas or hypotheses that you would like to investigate. Provide some evidence of relevant background reading if possible.

A typical research proposal might look something like this:

• Rationale for the research project, including: a description of the phenomenon of interest, and the context(s) and situation in which you think the research will take place; an explanation of why the topic is of interest to the author; and an outline of the reasons why the topic should be of interest to research and/ or practice (the 'so what?' question); a statement of how the research fits in with that of potential supervisor(s) in the School of Economics.
• Issues and initial research question. Within the phenomenon of interest: what issue(s) do you intend to investigate? (This may be quite imprecise at the application stage); what might be some of the key literatures that might inform the issues (again, indicative at the application stage); and, as precisely as you can, what is the question you are trying to answer?
• Intended methodology: How do you think you might go about answering the question? Do you have a preference for using quantitative methods such as survey based research, or for qualitative methods such as interviews and observation?
• Expected outcomes: how do you think the research might add to existing knowledge; what might it enable organisations or interested parties to do differently?
• Timetable: What is your initial estimation of the timetable of the dissertation? When will each of the key stages start and finish (refining proposal; literature review; developing research methods; fieldwork; analysis; writing the draft; final submission). There are likely to overlaps between the stages.

An initial research proposal that forms part of a PhD application should be between 600 and 1,000 words in length.

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Behavioral and Cognitive Sciences Sample Proposal

Note to readers: This example of a successful doctoral dissertation research improvement grant proposal in cultural anthropology is being made available with permission from the authors in order to provide guidance to potential principal investigators.

Dissertation Research: The Effects of Water Scarcity on Reciprocity and Sociability in Bolivia

Principal Investigator: H. Russell Bernard Co-principal Investigator: Amber Y. Wutich

On this page

• Bernard and Wutich Sample Proposal Cover Page (PDF, 14.67 KB)

Project summary

Problem statement Impending water shortages and conflicts over scarce water are now widely predicted (Ohlsson 1995, Elhance 1999). Ross (1993) has shown that the presence of cooperative ties within a community mitigates both the incidence and the intensity of conflict. Laughlin and Brady argue that if resource scarcity becomes severe enough, cooperative ties will break down as people focus on their own needs, and withdraw from reciprocal exchange relationships and social relationships. This theory produces a series of testable hypotheses. The proposed research will determine if severe water scarcity erodes reciprocal exchange and social relationships in Villa Israel, a barrio of Cochabamba, Bolivia.

Methods and Analysis Between January and April, the researcher will select a 60-household purposive sample, create and test interview protocols, choose key informants, and train a research assistant. Between May and November, the researcher will conduct in-depth interviews with key informants and four ethnographic interviews with each household in the sample. In November and December, the researcher will conduct a series of experimental economic games will be run to determine the norms of trust and reciprocity in the community. Inferential statistics Πt-tests, ANOVA, and repeated measures ANOVA Πwill be used to test the hypotheses.

Intellectual Merit This research will contribute to two areas of social science inquiry: urban anthropology and conflict theory. This will be the first study to examine if and how urban social support relationships are transformed by severe water scarcity. Understanding how reciprocal exchange and social ties are strained during periods of severe deprivation will contribute to efforts to understand the dynamics involved in conflict over environmental resources.

Broader Impacts This research will contribute to the doctoral training of a female doctoral student, as well as the methods training of a Bolivian undergraduate student from the Universidad Mayor de San Simón in Cochabamba. The study also has practical applications for those seeking to anticipate and manage coming conflicts over scarce freshwater. By determining when and how social ties become vulnerable during periods of severe water scarcity, the research will point to possible avenues for conflict prevention in marginal urban communities. In Cochabamba, the researcher will disseminate her findings to three local NGOs and will suggest how the research might contribute to the success of future water delivery projects.

Statement of the problem

Reports on the state of freshwater reserves warn that severe local shortages are imminent, and predict that violent conflicts will emerge in water-scarce regions (Ohlsson 1995, Elhance 1999). Water scarcity has been shown to cause civil conflict, particularly when accompanied by high population density, poverty, and income inequality (Homer-Dixon 1994, 1996, Hauge and Ellingsen 1998). Urban migrant communities, where ethnic, religious, and class differences can exacerbate tensions, and community-wide patterns of adaptation to environmental scarcities are not well-formed, may be particularly vulnerable to water conflicts (Moench 2002). To better understand how conflicts develop in water-scarce regions, research is needed on the social and economic factors that mediate cooperation and conflict (Ronnfeldt 1997). I propose to do an in- depth study of Villa Israel, a barrio of Cochabamba, Bolivia, where conflict over water is an established part of life. Every winter, seasonal water shortages threaten the lives of the people of Villa Israel, forcing them to make choices in how they use their economic and social resources.

One factor that mitigates the incidence and intensity of conflicts is the existence of cooperative ties within a community (Ross 1993). In marginal urban settings, poverty and mutual assistance foster social support networks (Low 1999) that strengthen community ties. However, Laughlin and Brady's model (1978) of adaptation to environmental stress predicts that, in times of severe resource scarcity, individuals will withdraw from the generalized reciprocal exchange relationships and social relationships that characterize urban social support networks. The proposed research in Villa Israel will test the Laughlin and Brady model to determine if severe water scarcity erodes reciprocal exchange and social relationships.

Research objectives

The overall objective is to understand how severe water scarcity affects reciprocal exchange relationships and social relationships in a marginal urban setting. The five specific objectives are:

• to document the incidence of water scarcity in the research community. This involves the development and testing of a scale to assess water consumption, as well as conducting interviews to document variation of water use in a sample of households.
• to determine how water scarcity affects the frequency and quality of reciprocal exchanges between households. This involves documenting the reciprocal exchanges that a sample of households engages in over a nine-month period.
• to determine how water scarcity affects the frequency and quality of social interactions between households. This involves documenting the social interactions that a sample of households engages in over a nine-month period.
• to determine if community norms exist for determining the order in which households withdraw from reciprocal exchange relationships. This involves testing how economic interactions change under a variety of hypothetical conditions in an experimental game.
• to determine if households withdraw from reciprocal exchange and social relationships in the order established by community norms.

Literature review

The existence and quality of intracommunity ties has long been recognized as a factor that determines how conflicts evolve over scarce resources and other threats (Simmel 1904 [1955], Coser 1956, Mack 1965). The degree of connectedness and the presence of ties that cross social segments are both elements of social structure that inhibit conflict development (Gluckman in Ross 1993, LeVine and Campbell 1972). Although early conflict theorists called for empirical research to investigate when and in what order social ties are broken (Coleman 1957), such studies have been conducted in only a few geographic regions and on a few environmental scarcities.

Laughlin and Brady's (1978) model of adaptation describes how economic and social interactions fluctuate with seasonal patterns of resource scarcity. They hypothesize that, during times of widespread (but non-lethal) deprivation, households will increase generalized reciprocal exchanges and social interactions. When resource scarcity becomes more severe, households will shift to balanced or negative reciprocal exchanges and will withdraw from social relationships.

Dirks (1980) demonstrated that, whether famines are seasonal or unpredictable, societies pass from an initial stage of alarm (characterized by intensified sharing and sociability) to resistance (characterized by economic and social withdrawal into households and kin groups) to exhaustion (in which kin-based alliances to find food disintegrate) as scarcity worsens. Laughlin and Brady's model was validated by a series of African famine case studies (Laughlin 1974, Cashdan 1985, Corbett 1988, Walker 1989).

Similar to the survival tactics documented in rural African households, urban Andean households engage in frequent reciprocal exchanges to guard against privation. For the purposes of this research, the social support networks of impoverished urban communities are considered to be characteristic of the first stage of response to deprivation. The anthropological literature on Andean survival strategies indicates that people form mutual support relationships based on five major kinds of ties: kin, compadrazgo, paisano, work, and church.

One of the most powerful cooperative strategies that urban migrants use to survive is to form kin-based groups (Halebsky 1995). In the Andes, the basic units for such groups are nuclear and extended households (Lobo 1995 [1982]). Beyond the household, ties with extended families and fictive kin constitute the heart of Andean support networks. In Lima, groups of siblings and cousins migrated together from the highlands. These siblings formed powerful core groups, which they later augmented with marriage alliances (Lobo 1995 [1982]). Familial support is also enhanced with compadrazgo ties, in which ceremonial parents establish relationships for mutual aid with their fictive children (Isbell 1985 [1978]). In addition, paisanos, or people who came from the same highland district, are relied upon to help and defend each other in urban settlements (Lobo 1995 [1982]). Similarly, in Mexico City, kinship, compadrazgo, and informal social networks provided services, goods, and information that were crucial to the survival of residents of a shantytown (Lomnitz 1977).

Andean communities also tend to have strong traditions of mutual support founded on work- based solidarity (Buechler and Buechler 1971). In urban settlements, such ties of mutual support may be formed around cooperative welfare projects (McFarren 1992), union membership or shared professions (Nash 1993 [1979]), and camaraderie established while women do housework or work in markets (Weismantel 2001).

Churches provide another setting in which mutual support relationships are formed (Krause et al. 2001). Regardless of the denomination, parishioners generally belong to church organizations that provide assistance to needy community members, and form informal assistance networks among themselves. One particularly important form of reciprocity is the obligation to provide goods and labor to kin and fictive kin during Catholic festivals (Isbell 1985 [1978]). Protestants, lacking a system of festival-based reciprocity, form informal social support networks to provide goods and services to churchgoers (cf. Stewart-Gambino and Wilson 1997).

While the supportive elements of Latin American urban networks have been extensively documented, the effects of severe resource scarcity on urban networks remain unexplored. Lomnitz (1978) suggested that extreme deprivation would likely cause decrement of generalized reciprocal exchanges and social interactions in urban areas. Still, no empirical research has tested the effects of drought or severe water scarcity on urban support ties.

Assuming that all households engage in exchange and social relationships, and that the amount of water available to the households varies, I propose ten hypotheses:

• H1. Generalized reciprocal exchanges will occur more frequently in the wet season than in the dry season.
• H2. Social interactions will occur more frequently in the wet season than in the dry season.
• H3. During the dry season, households with more water will engage in more generalized reciprocal exchanges than will households with less water.
• H4. During the dry season, households with more water will engage in generalized reciprocal exchange relationships with more households than will households with less water.
• H5. During the dry season, households with more water will engage in more social interactions than will households with less water.
• H6. During the dry season, households with more water will engage in social relationships with more households than will households with less water.
• H7. People will trust partners to reciprocate under experimental conditions most if they believe partners are kin, followed by compadres, then paisanos, then co-workers, and finally co-parishioners.
• H8. People will reciprocate under experimental conditions most if they believe partners are kin, followed by compadres, then paisanos, then co-workers, and finally co-parishioners.
• H9. During the dry season, households will withdraw from generalized reciprocal exchange relationships in the order predicted by the experimental game.
• H10. During the dry season, households will withdraw from social relationships in the order predicted by the experimental game.

Research plan

The research will proceed in two phases. During the first phase, I will use a sampling frame to choose a 60-household purposive sample, create and test interview protocols, choose key informants, and train a research assistant. The first phase will lay the groundwork for the second, so that I will be prepared to complete a baseline assessment of exchange and social interactions before the dry season begins in May. During the second phase, I will conduct in-depth interviews with key informants and four ethnographic interviews with each household in the sample. At the end of the second phase, I will conduct a series of experimental economic games to determine the norms of trust and reciprocity in the community.

The research design has several strengths. First, ethnographic study will yield data with high internal validity about how responses to water scarcity evolve over the wet-to-dry cycle (Kirk and Miller 1986). Second, the household interviews allow me to document change by collecting repeated measurements of household characteristics over time. Third, interviews with key informants allow me to collect information with more time depth than would be available with only the household interviews. Fourth, the experimental game allows me to determine how certain ties affect trust and reciprocity, controlling for other factors like history. Finally, the use of three forms of data collection Πhousehold interviews, interviews with key informants, and an experimental game Πwill enable me to check the results of each method against the other, facilitating identification of sample biases, hoax answers, or other data problems.

Research Schedule

Research Site: Villa Israel, Cochabamba, Bolivia Cochabamba is a large Bolivian city located in a semi-arid zone, made famous in 2000 by city-wide protests and riots over water delivery. There, a rapid increase in water demand caused by urban growth, groundwater scarcity, and topography that drains water away from the city have intensified pressures on the municipal water distribution system (Laurie and Marvin 1999). Lacking the capital to extend water services to its growing periphery, Cochabamba contains a large population of marginal urban residents that lack access to the municipal water system.

Villa Israel, a neighborhood on the outskirts of Cochabamba, is an impoverished community of 565 migrant families. The population contains people of Quechua and Aymara origin, and members of four different Catholic and Protestant churches. Currently, Villa Israel has no municipal water or sanitation services. Most households buy drinking water from a truck, which is operated by a private vendor. Private vendors typically charge 10 to 20 times the fee charged by public utilities, and people living in marginal urban areas pay between 10 and 40 percent of their incomes to acquire water in this way (Marvin and Laurie 1999). Households may purchase between 20 and 40 liters of low-cost, untreated water a day through thirteen public faucets controlled by the Unión Cristiana Evangélica, a Protestant church (Trujillo 2002). During the wet season, households also collect rainfall and water from canal beds used to drain sewage and wastewater. The ability of a household to acquire sufficient water depends on its per capita income and its exchange relationships with other households. Throughout the year, all households lack sufficient water for daily sanitation tasks in Villa Israel. As the winter dry season progresses, the impacts of water scarcity become increasingly severe. For example, between April and July of 2002, fourteen children under the age of one died from water-related illnesses (Trujillo 2002).

Data collection Sampling and choosing key informants Using the Unión Cristiana Evangélica census of Villa Israel as a sample frame, I will select a purposive sample of 60 households. Households will be selected to maximize variation on the following variables: ethnicity, religious affiliation, head of household's profession, number of members, and geographic location of the house (distance from water sources). Although choosing a purposive sample renders generalization from the study impossible, the purposive sample will enable me to choose households that maximize variation on the independent variables (Bernard 2002). A sample of 60 is small enough so that, with the help of a research assistant, I can do rigorous, in-depth study of the sample, and I also have enough observations to do inferential statistics to test the hypotheses.

Upon entering the field, I will also begin to look for key informants through word-of-mouth recommendations. I will attempt to find key informants using an a priori analytic framework (Johnson 1990), that is, based on the characteristics that will give informants access to different experiences in the community (ethnicity, religion, profession, age, and gender). Having several key informants will allow me to check their recollections and assessments of norms against each other.

Measurement of water availability To determine when the wet and dry seasons begin and end (independent variables H1-2), I will consult published records of precipitation in Cochabamba for 2004. To determine the amount of water available to each household at each interview time (independent variables H4-6), I will use a Guttman scale. Attempts to physically measure the volume of water acquired by the household from all sources may result in serious measurement errors. Instead, I will develop a Guttman scale of water use (Guttman 1950). First, I will elicit free lists of water uses from adult women and prepare a list of, say, the 20 most commonly listed items (the exact number will be determined by examining the data, of course, for repetitions of items.). Next, I will determine which tasks appear be part of a common water use domain. To do this, I will ask 20 women to indicate which of the tasks on the streamlined list (e.g., drinking, washing windows, bathing, watering plants, and cooking) each household member has completed in the last day and in the last week. I will then create two scales (for weekly and daily use), calculating the coefficient of reproducibility (CR Πthe statistic that summarizes errors in the scale), for each. If the CR is greater than .85, I will consider water use to scale sufficiently (Bernard 2002). I will then use the modal household water use to represent overall water availability in the household. If water use does not scale, I will collect measures of the volume of water acquired by each household from all sources at the time of each interview, and will also ask the person responsible for collecting water to assess how much water was collected that day. Household interviews Household interviews will produce data for the following variables: number of reciprocal exchanges (H1,3), number of reciprocal exchange relationships (H4), number of social visits (H2,5), and number of social relationships (H6) that each household has reinforced (through visits, for example) during the week preceding each interview; and the order in which households withdraw from exchange and social relationships (H9-10). I will conduct one interview every two months with each of the 60 households in the purposive sample. The interview will be conducted primarily with the adult responsible for housekeeping, but I will verify responses with other household members during the interview. Each household will be allocated 4 to 8 hours per meeting for interviewing and observation. Because residents of marginal Cochabamban neighborhoods tend to mistrust and avoid researchers with structured survey protocols (Goldstein 2002), I will conduct informal, semi-structured interviews with household members. With respondents' permission, I will record interviews using a digital sound recorder (Maloney and Paolisso 2001). I will take detailed field notes and observations using Spradley's method for note-taking (1980). In interviews with key informants, I will also supplement field notes with digital sound recording whenever possible.

For the semi-structured interviews, I will adapt the interview protocol from Stack's classic study of urban survival strategies (1970) for use in Cochabamba (see appendix). To do so, I will translate the protocol with a bilingual Spanish-English speaker, and pre-test the protocol with households outside the sample. The protocol includes questions about daily life, the acquisition of goods, finances, and leisure time. The advantages of using a modified version of the Stack protocol are that it has been pre-tested for research on urban survival strategies, it is flexible enough to accommodate Andean social structure, and successful replication of Stack's results will enhance the external validity of previous findings about how urban support systems function. In interviews with key informants, I will expand on the household interview protocol, and will probe for anecdotes about times when ties have been broken or when people have come into conflict over water.

Experimental game Following anthropologists who have modified experimental economic methods to study economic behaviors in 15 small-scale societies (Henrich et al. 2001), I will use an investment game (Berg et al. 1995) to discover the social norms that determine when and with whom households trust (dependent variable H7) and reciprocate (dependent variable H8). I will set up the games using Barr's (2001) adaptation of the investment game protocol and script for developing nations. The game is an anonymous, one-time economic interaction between two people that uses real money. Player A is given a sum equal to one day's labor (about US $3), and the option to keep the money or send some of it to the player B. If the money is sent to player B, it triples and player B determines how much of the money should be returned to player A. The amount of money offered by player A indicates how much A trusts B, and the amount B returns to A is a measure of reciprocity (Berg et al. 1995). By informing players A and B that the otherwise anonymous opposing player shares kin, compadrazgo, paisano, work, or religious affiliation, the experiment can be manipulated to test the strength of trust and reciprocity for each tie. I will conduct 60 repetitions of each interaction for each scenario, totaling 360 repetitions.

Data analysis

Data entry and coding Interviews will be transcribed by the field assistant as they are conducted. Data from the interviews will be used to construct an ordinal measure of water use (H4-6) and four interval-level dependent variables: the number of generalized reciprocal exchanges that occurred in the last week (H1,3), the number of households with which the respondents exchanged in the last week (H4), the number of social visits that occurred in the last week (H2,5), the number of households with which the respondents visited in the last week (H6). The amount of offers (H7) and counter-offers (H8) made during the investment game will be recorded in Bolivianos. Quantitative data for households will be entered directly into Excel spreadsheets.

Inferential statistics I will use t-tests to compare mean numbers of exchange and social interactions for the wet and dry season (H1, H2), and ANOVA to determine if levels of household water availability are associated with differences in mean levels of exchange and interaction (H3-H6). Analysis of variance tests will also be used to determine if different social ties are associated with differences in mean monetary measures of trust and reciprocity (H7, H8). I will use repeated measures ANOVA to test hypotheses 9 and 10.

Analysis of ethnographic data Field notes and transcribed narratives that include anecdotes about tie breaking and water conflicts will be coded to indicate if the case supports or disproves any of the hypotheses. I will examine each case to better understand the dynamics of tie breakage and water conflicts.

Preliminary Studies In summer 2002, I traveled to Bolivia to conduct preliminary fieldwork and establish relationships with institutions that support this study. I interviewed project coordinators in USAID, CARE, the Peace Corps, and Bolivian NGOs to learn about how communities adapt to conditions of water scarcity. After the interviews, I determined that Villa Israel would be an ideal site to test the research question.

In Cochabamba, I became associated with three organizations that are working on local water problems. The first, The Democracy Center, is a Cochabamba-based organization that works to strengthen the advocacy efforts of community groups. The second organization, Water for People, is an international NGO that helps communities in Cochabamba that lack adequate water delivery install wells, hand pumps, and sanitation systems. The third is the Unión Cristiana Evangélica church, which manages the distribution of water through tap stands in Villa Israel. Each of these organizations has provided me with valuable information about the water situation, introductions to key community leaders in Cochabamba and Villa Israel, and has pledged to support me during the year-long data collection project. Since my return from Bolivia, I have stayed in frequent contact with representatives of the three organizations, and continue to receive data and consult with them on logistics of conducting research and living in Villa Israel. During summer of 2003, I will return to Villa Israel to introduce myself formally to community members, hire a research assistant from the sociology department at the Universidad Mayor de San Simón, and finalize living arrangements for the following January.

Research Competence of the Student Over six years of coursework, I have acquired a solid four-field education in anthropology that enables me to understand the cultural, biological, historical, and symbolic aspects of water scarcity and conflict. My preparation for this research includes coursework in the following subjects: research design and cognitive research methods with Dr. H. Russell Bernard, economic anthropology and studies of race and ethnicity with Dr. Anthony Oliver-Smith, political ecology and development in the tropics with Dr. Marianne Schmink, and anthropological theory with Dr. Maxine Margolis. During spring 2003, I will take a fourth course in statistics, as well as a course in hydrology. I supplemented graduate coursework with an intensive six-week language course in Oaxaca, Mexico during the summer of 2000, in which I polished the Spanish skills I acquired studying and working in South Florida between 1992 and 1996.

While assisting Drs. H. Russell Bernard and Christopher McCarty in research projects between 1997 and 2002, I honed my skills in sampling, questionnaire design, data collection and data analysis. Under Dr. Bernard's direction, I have conducted ethnographic interviews, transcribed narratives, and done text analysis, social network analysis, and multivariate analyses. I currently manage data collection and analysis for the Survey Research Center at the UF Bureau of Economic and Business Research under the supervision of Dr. McCarty. My responsibilities include overseeing a four-survey evaluation of health care in the state of Florida, which involves 300 interviewers and 13,500 interviews. After five years of practice and hands-on instruction in ethnographic and survey research methods, I have become an experienced and capable researcher.

I have also conducted three independent research projects in cities and marginal urban areas. Two of these projects took place in Mexico and Bolivia, where I honed my ability to do research in Spanish. In 2001, I conducted a study on the effects of social support networks on child feeding decisions with the Mexican Social Security Institute in Oaxaca. In 2002, I traveled to Bolivia to conduct preliminary fieldwork and establish relationships with institutions that support my work. When I return to Bolivia in January 2004, I will have the experience, knowledge, and local support to successfully conduct the proposed research.

Significance of proposed research

Intellectual Merit This research will contribute to two areas of social science inquiry: urban anthropology and environment-conflict theory. The research will be the first study to examine if and how urban social support relationships are transformed by severe water scarcity. Understanding how reciprocal exchange and social ties are strained during periods of severe deprivation will contribute to efforts to understand the dynamics involved in conflict over environmental resources.

Through in-depth study of one case, the research will produce data with high internal validity. This is particularly important because the research examines the process of withdrawal from reciprocal exchange and social relationships. In using Stack's ethnographic interview protocol and Berg et al.'s experimental investment game, the proposed research replicates well-known research, and facilitates future replications to establish the external validity of the findings.

Broader Impacts In addition to testing the effects of water scarcity on reciprocity and sociability, the research will facilitate the learning of two students. The proposed research will contribute to the doctoral training of a female graduate student, as well as the methods training of a Bolivian undergraduate from the Universidad Mayor de San Simón in Cochabamba.

The study also has practical applications for those seeking to anticipate and manage coming conflicts over scarce freshwater. In many Latin American cities, the arrival of new immigrants strains the ability of the local government to provide municipal services to all city residents (Gilbert 1998). By determining when and how social ties become vulnerable during periods of severe water scarcity, the research will point to possible avenues for conflict prevention in marginal urban communities. In Cochabamba, the study's findings will be disseminated through partnerships with three local NGOs, along with suggestions regarding ways in which the research might contribute to the success of future water delivery projects.

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Curriculum vita: Amber Wutich

Professional Preparation

University of Florida , Anthropology (specialization in Tropical Conservation and Development in Latin American Studies), Doctoral program , September 2000-curr. Español Interactivo , Spanish language classes, May-June 2000 University of Florida , Anthropology and Chinese Language and Literature, B.A., May 2002 Honors thesis in cultural anthropology Shaanxi Teacher’s University , Chinese Language and Literature, Aug. 1998-May 1999

Appointments: Employment and Research Experience

2002 Preliminary fieldwork , interviews on water scarcity in Bolivia 2002 Project manager , led data collection and analysis on a study of ethnicity and social support funded by the University of Florida 2000-02 Survey research , supervised sampling, data collection and analysis on a series of surveys for the state of Florida at UF Bureau of Economic and Business Research Survey Research Center 2002 Text analysis, performed text analysis on a project for Dr. H.R. Bernard 2001 Field Research , The Effect of Social Support Networks on Oaxacan Mothers’ Weaning Decisions (with the Mexican Social Security Institute, Oaxaca, Mexico) 2000 Interviewer , Ford-funded Web Research Materials Project, a project to develop web-based cognitive research tools Undergraduate Honors Research, The Effects of Estimation on Elicitation in Social Network Research 1999 Undergraduate Research , study of information networks in Xi’an, China 1998 NSF Research Education for Undergraduates grant , to study the estimation of hard-to-count populations with Russ Bernard

Paper Presentations

2003 (under review) Presenter, “ Using personal networks to measure race and ethnicity ” Sunbelt Social Networks Conference, Cancun, Mexico (under review) Panel Co-Organizer, Measuring Race and Ethnicity in Anthropology and Beyond ; Presenter, “ A Social Network Approach To Measuring Race and Ethnicity ” Society for Applied Anthropology Conference, Portland, OR 2002 Presenter, “ Getting Health Care Advice on Her Own: Social Network Effects on Weaning Decisions in Oaxaca, Mexico " Society for Applied Anthropology Conference, Atlanta, GA 2001 Presenter, “ Living Local and Going Global: Integrating Quantitative and Qualitative Methods in a Study of Internet Use in Xi'an, China " Society for Applied Anthropology Conference, Merida, Mexico

Collaborators: Christopher McCarty (U. Florida), Clarence Gravlee (U. Michigan)

Graduate Advisors: H. Russell Bernard (U. Florida), Anthony Oliver-Smith (U. Florida), Marianne Schmink (U. Florida)

Semi-structured interview protocol

(Modified version of Stack 1970)

1. DAILY LIVES My aim is to learn how people spend their time from the moment they wake up in the morning until they go to bed at night -- to learn who they visit, which relatives they see daily or weekly, what they do for each other, whether they exchange goods and services, and how these exchanges are arranged. a. Describe a typical day in great detail. (Probe repeatedly.) b. Who do you visit each day, each week? Which relatives? (Name relationship) c. Did you trade food, money, child care, or anything else with anyone this week? With whom? d. What did you do for someone else this week? Did anyone help you out? e. Did you give anything (goods/services) to any of the individuals listed in d? Did you receive anything (goods/services) from the individuals listed in d?

2. THE ACQUISITION OF GOODS (Elicit the names of all of the items -- furniture, pictures, radios, etc. -- in each room in the house that were acquired in the last week. Ask the following questions about each item.) a. Give a physical description of the item. b. Was the item in anyone else’s home before? Whose? c. Does it belong to anyone in the house? Who? d. Where did it come from? Was it bought at a store? Where? e. Who bought it? f. Was it a gift or a loan? g. Who loaned or gave it to you? h. Who will it be given to or loaned to? i. Is it home-made? Who made it? j. What else should we ask you about it?

3. FINANCES Everyone has a hard time making it on the money they get and has to get some help from others. The aim is to try to figure out how people make it. This gets very complicated because some people live together, others eat together, and others share their income. a. Who is living in this house right now? (List relationships.) Who contributes to the finances of the household? How do they contribute (rent, utilities, etc.)? b. Who fetches the water? Who drinks or uses it? Who helps pay for it? b. Who ate in the household in the last week? Which meals? Who paid for the food and cooked? c. (Try to learn the source of income of everyone who contributes to the household.)

4. LEISURE TIME I’d like to learn about how you spend your free time. a. With whom did you spend your day? b. With whom do you enjoy spending time each week? c. With whom do you participate in special activities (church groups, dancing, etc.)? d. Where and with whom do you eat breakfast, lunch, dinner? e. What housework do you do (shopping, scrubbing, cooking, dishes, etc.)? What other work do you do? With whom do you work?

Budget documents

• Bernard and Wutich Sample Original Budget (PDF, 211.34 KB)
• Bernard and Wutich Sample Revised Budget and Justification (PDF, 223.89 KB)

Rating: Excellent, Very Good Review:

Summary Statement

This proposal deals with conflicts over water shortages in Bolivia. The purpose of the research is to better understand how conflicts develop in water-scarce regions, and to outline the social and economic factors that mediate cooperation and conflict. The research will be conducted in Villa Israel, near Cochabamba, Bolivia. The objectives of the research are to document the incidence of water scarcity, to determine how water scarcity affects the frequency and quality of reciprocal exchanges between households, to determine how water scarcity affects social interactions between households, and to evaluate community norms for engaging in or withdrawing from reciprocal exchange relationships.

A number of hypotheses are outlined, perhaps too many to be accomplished in the scope of the research agenda. For example hypothesis 3 and hypothesis 4 are simply flip sides of the same coin. Moreover hypotheses 5 and 6 are reciprocal suppositions. Nevertheless, the research plan is clearly outlined, including the sampling frame and the methodology by which data will be collected. A major strength of the proposal is the clarity of the sampling pattern for in-depth interviews. The proposal also calls for use of an experimental game to study economic behaviors, analogous to research that has been conducted in fifteen small-scale societies. This game will test trust and reciprocity among participants. The intellectual merit and broader impacts of the research are clearly spelled out. The only other criticism would be a general failure of the investigators to situate the research questions within a larger political economic context. For example why are there water shortages to begin when? What is the role of the state in determining the availability of water? These and other macro-level questions may be of interest as the research is undertaken.

Rating: Very Good

Working within the theoretical perspective that increase in scarcity of resources reduces cooperative ties within communities, the proposal aims to test the proposition that in Villa Isreal, a barrio of Cochabamba, Bolivia, severe water shortages erode reciprocal exchange and social relationships.

This is a very strong and well organized proposal. The Co-PI lists five clear research objectives that delineate aspects of the scarcity-erosion proposal, and in addition, 10 specific hypotheses are proposed, each stated clearly in regard to operationalization and measurement of variables. In order to generate data to test the hypotheses, a two-stage research plan is proposed. A purposive sample of 60households will be chosen, primarily for development of test protocols, mainly for the creation of a water scale. The measure will be designed as a Guttman scale. During phase two, in-depth interviews will be conducted with key informants, and four interviews will be conducted at each household. Data analysis will consist of coding the interviews and using inferential statistics to measure the relationships among social variables and water scarcity. ANOVA and repeated applications of ANOVA will be used for analysis of the data.

The only weakness of any consequence in the proposal is that virtually no attention is given as to how the coding will proceed. What does the Co-PI anticipate that the codes will be, i.e., what will be coded for? How will the codes relate to the methods? To the theoretical perspectives? If that had been clearer, the recommendation would be for a '5', but as it is, the recommendation is a '4', Very Good.

The proposed project is an interesting and clearly formulated inquiry into the effects of water shortage in a periurban barrio of Cochabamba, Bolivia. The researcher proposes to measure whether cooperation among neighbors, especially certain forms of reciprocity, are altered by water scarcity. This researcher will test this problem through a series of hypotheses. The research objectives are clearly outlined and include documenting water scarcity in the community, determining the effects of water scarcity on reciprocal exchanges and social relations between households, and ascertaining whether a community norm exists for determining how people withdraw from reciprocal relations, and whether people follow these norms in practice. (Also, it might be important to determine whether the community follows any kind of water distribution system. Is it a kind of economic free-for-all or are ideas of turn taking employed at times?)

The project will be the first study to examine in what ways urban mutual support networks are affected by a scarce water supply. The topic is timely and important. The theoretical perspective for the research comes from economic/ecological anthropology. It is inspired by studies of reciprocity and conflict theory. Note, however, that there is a wide literature on Andean reciprocity that is only touched upon in the proposalùmuch of it, though based in rural 'traditional' communities might nonetheless be of use for understanding reciprocity among migrants to the city. The researcher has chosen five 'major kinds of ties' that are involved in mutual support networks, and these may in fact be borne out. But I hope the researcher will use participant observation to first test this. These five do not take into account other possible reciprocal ties that migrants might use. For instance, the category of 'neighbors,' especially in the absence of ayllu membership, may be important in this barrio, and would be worth examining. Also, classic Andean forms of reciprocity such as ayni (performed variously from place to place) may also be active in some guise in Cochabamba's barrios. Also forms of 'ayuda' bind people together, or is it certain social units that provide ayuda? The project proposed here would offer a wonderful perspective by additionally taking into consideration some of the rural forms of reciprocity, asking informants to list them and comment on them, and thus providing a comparative angle. The obvious counterpart in the countryside is water distribution for irrigation and there are numerous studies here (e.g., Gelles, Gose, Guillet, Isbell, Sherbondy, Sikkink) that discuss the conflict and cooperation involved in this event, and would serve as a counterpoint to the study proposed here. Also I hope the researcher will work towards a broader bibliography of studies from Bolivia and specifically Cochabamba (such as Albro, Dandler, Larson, Paulson) in which to contextualize the results of the study. (Obviously from my ratings I think this is a strong proposal; it's also a topic of interest to me which is why I offer the suggestions I do.)

The researcher has an excellent background and the necessary skills for undertaking this project. Her anthropological training is exemplary. She has not only been trained in anthropological methodology but has managed data collection and analysis for several projects. The analysis section of the current proposal evidences this. The researcher has also undertaken independent research projects in Mexico and Bolivia, and therefore has the fieldwork and language skills required for the project.

The methodology section is particularly strong. The proposal is based on a clear and reasonable research plan. The research will test a number of hypotheses using interviews of key informants, measurement of water availability, household interviews and observation, an experimental game, and participant observation. Throughout the process the researcher will build on current available data and work with NGOs active in this area. Data analysis will include constructing an ordinal measurement of water use, and analyzing interactions among households, as well as the results of the game. Quantitative data will be analyzed using inferential statistics: t-tests and ANOVA will facilitate this. The researcher addresses the issue of the project's social salience in a clear manner. The researcher plans to hire and train a Bolivian student in the methodology of the project and disseminate the results of the study to three local NGOs. These efforts are aimed at both contributing to the success of future water delivery projects, and to indicating 'possible avenues for conflict prevention in marginal urban communities.'