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Behavioral Economics has Never Been Hotter

Behavioral Economics has Never Been Hotter | Bounded Rationality and Beyond | Scoop.it

Behavioral economics is a perfect example of interdisciplinary thinking, as ideas first developed by psychologists have come to inspire all sorts of microeconomic models. This trendy economics theory shows how emotions, instincts and biases shape our behavior. .

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Bounded Rationality and Beyond
News on the effects of bounded rationality in economics and business, relationships and politics
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Nudging Better Consumer Decisions: Provide Useful Information

Nudging Better Consumer Decisions: Provide Useful Information | Bounded Rationality and Beyond | Scoop.it

In recent years, the new field of behavioral economics has used psychology to identify strategies (or “nudges”) that can help people make better decisions for themselves and for society. This talk will review research on a few simple strategies for providing clear information to consumers and employees. We argue that the best way to help decision makers is not to simply give them information (picture the long credit card disclosure statements you periodically receive), but to make it usable. Our main focus has been on energy use. Every time consumers buy a new automobile in the U.S., they see a window sticker on every vehicle describing the car’s fuel economy, expressed as miles per gallon (MPG). What information would you put on an energy label to help consumers make better decisions about energy use (and the environment)?

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What is Nudging?

What is Nudging? | Bounded Rationality and Beyond | Scoop.it

By PG Hansen, PhD., Over the past four decades, advances in the behavioral sciences have revealed how human behavior and decision-making is boundedly rational[i], systematically biased, and strongly habitual owing to the interplay of psychological forces with what ought to be, from the perspective of rationality, irrelevant features of complex decision-making contexts. These behavioral insights teach us how contextual aspects of decision-making may systematically lead people to fail to act on well-informed preferences and thus fail to achieve their preferred ends. In the domain of public policy such advances may also teach us how neglecting these insights can be responsible for the failures of policies to reach intended effects and why paying more attention to them may provide the key for dealing more effectively with some of the main challenges modern societies and organizations face. Nudge In their popular book Nudge – Improving Decisions about Health, Wealth and Happiness (2008), Richard Thaler and Cass Sunstein suggested that if a particular unfortunate behavioral or decision making pattern is the result of cognitive boundaries, biases, or habits, this pattern may be “nudged” toward a better option by integrating insights about the very same kind of boundaries, biases, and habits into the choice architecture surrounding the behavior – i.e. the physical, social, and psychological aspects of the contexts that influence and in which our choices take place – in ways that promote a more preferred behavior rather than obstruct it. In particular, they argue that such nudges may avoid some of the challenges and potential pitfalls of traditional regulation, such as costly procedures and ineffective campaigning, unintended effects of incentivizing behaviors, and invasive choice regulation, such as bans. The advantage, they claim, of applying nudges is that public policy makers might thus supplement – or, perhaps, even replace (Thaler & Sunstein 2008, p. 14) – traditional regulation with nudges to influence people’s everyday choices and behaviors in cheaper, less invasive, and more effective ways. That is, nudging seems to offer policy makers an effective way to influence citizens’ behavior without further restricting freedom of choice, imposing mandatory obligations, or introducing new taxations, or tax reliefs.

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» Moments of Choice: how young people make career decisions | The Behavioural Insights Team

» Moments of Choice: how young people make career decisions | The Behavioural Insights Team | Bounded Rationality and Beyond | Scoop.it
Today, young people across England receive their GCSE results. Many will now be looking forward to the next exciting step in their education; for others, it may be a time for to reflect on what their options are and what they would like to do next. In these ‘moments of choice’, young people may seek information and support to help them make decisions. But will they find information online that can help them make good choices? A new report by The Behavioural Insights Team (BIT) finds that although young people feel like they have access to all the careers information they might need, this is not translating to a generation of young people more informed than their predecessors about their options and the future of the labour market. BIT was commissioned by the Careers and Enterprise Company to talk to young people about their future careers and aspirations, the resources they draw upon to make these decisions and the context in which these decisions occur. We conducted 43 interviews and five observations with young people aged 11-18 and careers guidance professionals (CGPs) in eleven schools and colleges across England. Empty description
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FACTS AND TIME IN QUANTUM MECHANICS: A STUDY IN PHENOMENOLOGY AND PRAGMATICS

FACTS AND TIME IN QUANTUM MECHANICS: A STUDY IN PHENOMENOLOGY AND PRAGMATICS | Bounded Rationality and Beyond | Scoop.it

By Michel Bitbol in Quantum Physics and Philosophy. The concept of well-defined and mutually exclusive objective facts has no counterpart in the formalism of standard quantum mechanics.

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Dilbert Explains Donald Trump

Dilbert Explains Donald Trump | Bounded Rationality and Beyond | Scoop.it
Best of the Web columnist James Taranto writes that Dilbert cartoonist Scott Adams figured out Donald Trump’s persuasion skills before the pundits did. And he still thinks Trump can win.
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Heuristica: An R package for testing models of binary choice

Heuristica: An R package for testing models of binary choice | Bounded Rationality and Beyond | Scoop.it

It just got a lot easier to simulate the performance of simple heuristics. The post Heuristica: An R package for testing models of binary choice appeared first

Here’s the heuristica package’s home on CRAN and here’s a description of the package in the authors’ own words: The heuristica R package implements heuristic decision models, such as Take The Best (TTB) and a unit-weighted linear model. The models are designed for two-alternative choice tasks, such as which of two schools has a higher drop-out rate. The package also wraps more well-known models like regression and logistic regression into the two-alternative choice framework so all these models can be assessed side-by-side. It provides functions to measure accuracy, such as an overall percentCorrect and, for advanced users, some confusion matrix functions. These measures can be applied in-sample or out-of-sample. The goal is to make it easy to explore the range of conditions in which simple heuristics are better than more complex models. Optimizing is not always better!

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Welcome to the Future of Homo Oeconomicus

Welcome to the Future of Homo Oeconomicus | Bounded Rationality and Beyond | Scoop.it
Homo Oeconomicus (HOEC) started life in 1983 as a German language occasional series concerned with various aspects of the theoretical and behavioral concept of homo economicus and its application in economics, philosophy, political science, and sociology. In 1995 it became a quarterly journal and in 1998 was fully internationalized with articles being exclusively in English. Since then Homo Oeconomicus has become an outlet for researchers working in the field of political economy, and a huge number of important papers have been published in the journal. From 2016 onward, Homo Oeconomicus is published by Springer. The journal will benefit from the modern technology and large distribution of an international publisher. We are proud to present the first issue of Homo Oeconomicus after its relaunch in early 2016.
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The evolution of economics and Homo Economicus

The evolution of economics and Homo Economicus | Bounded Rationality and Beyond | Scoop.it

“Behavioral economics" is still economics, but it is economics done with strong injections of good psychology and other social sciences.

Early in my teaching career I managed to inadvertently get most of the students in my microeconomics class mad at me, and for once, it had nothing to do with anything I said in class. The problem was caused by a midterm exam. I had composed an exam that was designed to distinguish among three broad groups of students: the stars who really mastered the material, the middle group who grasped the basic concepts, and the bottom group who just didn’t get it. To successfully accomplish this task, the exam had to have some questions that only the top students would get right, which meant that the exam was hard. The exam succeeded in my goal—there was a wide dispersion of scores—but when the students got their results they were in an uproar. Their principal complaint was that the average score was only 72 points out of a possible 100.

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Enroll Abm
Introduction to Agent-Based Modeling

Enroll Abm<br/>Introduction to Agent-Based Modeling | Bounded Rationality and Beyond | Scoop.it
About the Course: This course will explore how to use agent-based modeling to understand and examine a widely diverse and disparate set of complex problems. During the course, we will explore why agent-based modeling is a powerful new way to understand complex systems, what kinds of systems are amenable to complex systems analysis, and how agent-based modeling has been used in the past to study everything from economics to biology to political science to business and management. We will also teach you how to build a model from the ground up and how to analyze and understand the results of a model using the NetLogo programming language, which is developed and supported at Northwestern University by Uri Wilensky. We will also discuss how to build models that are sound and rigorous. No programming background or knowledge is required, and the methods examined will be useable in any number of different fields. While this course is in session, the first unit will be completely free and open; we request a modest tuition to continue through the course and to receive a certificate. Once the course is closed, the videos and quizzes will all be open and freely available. A limited number of scholarships are available, please see the FAQ for more details.
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Statistical mechanics of ecological systems: Neutral theory and beyond

Statistical mechanics of ecological systems: Neutral theory and beyond | Bounded Rationality and Beyond | Scoop.it
It is of societal importance to advance the understanding of emerging patterns of biodiversity from biological and ecological systems. The neutral theory offers a statistical-mechanical framework that relates key biological properties at the individual scale with macroecological properties at the community scale. This article surveys the quantitative aspects of neutral theory and its extensions for physicists who are interested in what important problems remain unresolved for studying ecological systems.
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Past the power law: Complex systems and the limiting law of restricted diversity - Castellani - 2016 - Complexity - Wiley Online Library

Past the power law: Complex systems and the limiting law of restricted diversity - Castellani - 2016 - Complexity - Wiley Online Library | Bounded Rationality and Beyond | Scoop.it
Abstract Probability distributions have proven effective at modeling diversity in complex systems. The two most common are the Gaussian normal and skewed-right. While the mechanics of the former are well-known; the latter less so, given the significant limitations of the power-law. Moving past the power-law, we demonstrate that there exists, hidden-in-full-view, a limiting law governing the diversity of complexity in skewed-right systems; which can be measured using a case-based version inline image of Shannon entropy, resulting in a 60/40 rule. For our study, given the wide range of approaches to measuring complexity (i.e., descriptive, constructive, etc), we examined eight different systems, which varied significantly in scale and composition (from galaxies to genes). We found that skewed-right complex systems obey the law of restricted diversity; that is, when plotted for a variety of natural and human-made systems, as the diversity of complexity inline image (primarily in terms of the number of types; but also, secondarily, in terms of the frequency of cases) a limiting law of restricted diversity emerges, constraining the majority of cases to simpler types. Even more compelling, this limiting law obeys a scale-free 60/40 rule: when measured using inline image, 60%(or more) of the cases in these systems reside within the first 40% (or less) of the lower bound of equiprobable diversity types—with or without long-tail and whether or not the distribution fits a power-law. Furthermore, as an extension of the Pareto Principle, this lower bound accounts for only a small percentage of the total diversity; that is, while the top 20% of cases constitute a sizable percentage of the total diversity in a system, the bottom 60% are highly constrained. In short, as the central limit theorem governs the diversity of complexity in normal distributions, restricted diversity seems to govern the diversity of complexity in skewed-right distributions. © 2016 Wiley Periodicals, Inc. Complexity, 2016
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How the Brain Makes Blame and Punishment Decisions | Law and Neuroscience Blog | Vanderbilt University

How the Brain Makes Blame and Punishment Decisions . New work by researchers at Vanderbilt University and Harvard University confirms that a specific area of the brain, the dorsolateral prefrontal cortex, is crucial to punishment decisions. Researchers predicted and found that by altering brain activity in that region of the brain they could not only change how much subjects punished hypothetical defendants, bu
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Adaptive Computation: The Multidisciplinary Legacy of John H. Holland

Adaptive Computation: The Multidisciplinary Legacy of John H. Holland | Bounded Rationality and Beyond | Scoop.it

John H. Holland's general theories of adaptive processes apply across biological, cognitive, social, and computational systems.In August 2015, Professor John H. Holland passed away in Ann Arbor, MI, where he had served on the University of Michigan faculty for more than 50 years. John, as he was known universally to his colleagues and students, leaves behind a long legacy of intellectual achievements. As a descendant of the cybernetics era, he was influenced by the work of John von Neumann, Norbert Wiener, W. Ross Ashby, and Alan Turing, all of whom viewed computation as a broad, interdisciplinary enterprise. Holland thus became an early proponent of interdisciplinary approaches to computer science and an active evangelist of what is now called computational thinking, reaching out enthusiastically to psychologists, economists, physicists, linguists, philosophers, and pretty much anyone he came in contact with. As a result, even though he received what was arguably one of the world's first computer science Ph.D. degrees in 1959,23 his contributions are sometimes better known outside computer science than within. Holland is best known for his invention of genetic algorithms (GAs), a family of search and optimization methods inspired by biological evolution. Since their invention in the 1960s, GAs have inspired many related methods and led to the thriving field of evolutionary computation, with widespread scientific and commercial applications. Although the mechanisms and applications of GAs are well known, they were only one offshoot of Holland's broader motivation—to develop a general theory of adaptation in complex systems. Here, we consider this larger framework, sketching the recurring themes that were central to Holland's theory of adaptive systems: discovery and dynamics in adaptive search; internal models and prediction; exploratory modeling; and universal properties of complex adaptive systems.

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New Chief Research Officer Position

New Chief Research Officer Position | Bounded Rationality and Beyond | Scoop.it

The NYC Mayor’s Office of Criminal Justice (MOCJ) is looking for a Chief Research Officer. We are looking for a motivated, entrepreneurial leader, with a demonstrated interest in criminal justice, who will be able to develop our research agenda, manage our research budget and a team of ten researchers, and drive citywide initiatives related to data, research and technology tools.

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Seven Deadly Sins: Envy - Neuromarketing - Philip Harris: What is neuromarketing?

Dr Philip Harris introduces neuromarketing
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E.t.l.e.b.o.r.o: Neuroeconomia e neuropolitica: scenari di totalitarismo

E.t.l.e.b.o.r.o: Neuroeconomia e neuropolitica: scenari di totalitarismo | Bounded Rationality and Beyond | Scoop.it
Nell'era della cybernetica e del web, che fanno da sfondo ad una crisi economica non circoscrivibile, è la neuroscienza la nuova frontiera della società globalizzata che conosciamo e che si sta trasformando. Lo studio del cervello umano e dei comportamenti degli individui attraverso tecniche di Imaging da Risonanza Magnetica (IRM) viene sperimentato da anni all'interno dei laboratori scientifici di un ristrettissimo numero di società nel mondo. Dietro progetti di ricerca per la cura contro cancro, parkinson o alzheimer, si nasconde un'attività di tracciamento e archiviazione delle immagini proiettate dal nostro cervello rispondendo a degli stimoli esterni, che permettono così di comprendere i meccanismi del subconscio umano, e quindi i meccanismi che sono alla base di una decisione razionale. L'IRM sottopone alle 'cavie' una serie di foto, video, odori, oggetti, cibo, per vedere quali aree del cervello vengono attivate. Gli scienziati specializzati nelle neuroscienze analizzano le interazioni tra queste aree che, avendo una diretta influenza sull'inconscio e sulla predeterminazione sociale, condizionano il comportamento dei consumatori e la loro coscienza.
https://t.co/fusmjveV6Z
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How Science Can Help Get Out the Vote

How Science Can Help Get Out the Vote | Bounded Rationality and Beyond | Scoop.it

Research offers several proved strategies for boosting turnout on Election Day

TO VOTE OR NOT TO VOTE Although tackling political barriers to voting remains critical, the great strength of these behavioral interventions lies in their ability to overwhelm obstacles by catalyzing citizen motivation. And for people who do not vote because they believe one person's ballot cannot change election outcomes, behavioral science also offers a reason why voting is important for individuals. Research has found that in addition to signaling who we are to others, our actions tell us something about ourselves—shaping our own preferences and beliefs. From this perspective, people who do not vote are not merely abstaining from the democratic process in one instance. They are also “telling” themselves: “I don't care about politics.” Moving forward, they may also become less interested in civic rights, local governance, foreign affairs, and so on. And for those who do vote, participation is not just an expression of interest in current politics but also a seed that could grow into an active political life.

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Another comparison of heuristic optimizers

Another comparison of heuristic optimizers | Bounded Rationality and Beyond | Scoop.it

A herd of heuristic algorithms is compared using a portfolio optimization. Previously “A comparison of some heuristic optimization methods” used two

Previously “A comparison of some heuristic optimization methods” used two simple and tiny portfolio optimization problems to compare a number of optimization functions in the R language. This post expands upon that by using a portfolio optimization problem that is of a realistic size (but still with an unrealistic lack of constraints). Test case The optimization problem is to select 30 assets out of a universe of 474 and find their best weights. The weights must be non-negative and sum to 1. The integer constraint is binding — more than 30 assets in the portfolio can give a better utility. The utility is mean-variance. Each optimizer was run 100 times. To have a fair comparison the amount of time that each run took was controlled to be about 1 kilosecond. (There are a couple that also have runs that take much less time.) The timings are not all particularly close to 1000 seconds, but they are probably all close enough that the picture is minimally distorted.

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Making fast, good decisions with the FFTrees R package

Making fast, good decisions with the FFTrees R package | Bounded Rationality and Beyond | Scoop.it

“…e are suspicious of rapid cognition. We live in a world that assumes that the quality of a decision is directly related to the time and effort that went into...."


Summary 

 The FFTrees package contains lots of other functions for visualising and comparing trees. To see all the details, be sure to check out the package vignettes either in the package or on CRAN (here). For all you judgment and decision making researchers out there, I will also be presenting the package at the annual meeting of the Society for Judgment and Decision Making (SJDM) in Boston in November 2016 The package is also very much in development, so I am grateful for any recommendations, bug-reports, or criticisms. You can post bug-reports at www.github.com/ndphillips/FFTrees/Issues, or email me directly at Nathaniel.D.Phillips.is@gmail.com

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» Designing a behaviourally informed banking market | The Behavioural Insights Team

» Designing a behaviourally informed banking market | The Behavioural Insights Team | Bounded Rationality and Beyond | Scoop.it
Last week the Competition and Markets Authority (CMA) published the final report of their retail banking market investigation. The CMA has identified that currently, only a tiny proportion of customers switch to a different bank in any year; despite the fact that many of them could save about £90 a year by switching. A quarter of people in the UK use an unauthorised overdraft each year, suggesting they do not have the best account for them: this earns the banks £1.2 billion a year from unauthorised overdraft charges. The report proposed three foundation measures as the basis for their package of remedies. All three foundation measures have strong behavioural aspects: Requiring banks to implement Open Banking to help consumers share their data securely with other banks and third parties. This will help make it easier for consumers to shop around and compare banking products (making it easy). Requiring banks to prominently display a number of core indicators of service quality, including whether a personal customer or small business is willing to recommend their bank to friends, family and colleagues (making it attractive). Introducing routine and occasional prompts for personal and business customers to encourage them to consider their current banking arrangements and shop around for alternative banking services (making it timely). Those of you who have read our recent report on applying behavioural insights to regulated markets will recognise that these remedies strongly echo the principles set down in that paper: we will now set out their behavioural underpinning in a bit more detail.
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Can we trust peer review? New study highlights some problems

Can we trust peer review? New study highlights some problems | Bounded Rationality and Beyond | Scoop.it

Peer review is intended to act as a gatekeeper in science. If working researchers deem a paper fit to be published, it should mean that the research is sound, rigorous, and accurate. But an experimental analysis of peer review suggests that peer review might also end up rejecting high-quality material. The analysis points to high levels of competition as the source of the problem. Because peer review is a vastly complex system that can function quite differently in various disciplines, researchers Stefano Balietti, Robert L. Goldstone, and Dirk Helbing constructed an experimental game designed to mimic some of the primary features of peer review. Participants were divided into 16 groups of nine people each and tasked with creating a piece of “art” on a computer interface. The pieces could then be submitted to one of three “art exhibitions.” Each participant was then given three pieces of other people's art to review; pieces that averaged a score higher than five out of ten were accepted into the exhibition. Each group played 30 rounds of the game.

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Introduction to Dynamical Systems and Chaos

Introduction to Dynamical Systems and Chaos | Bounded Rationality and Beyond | Scoop.it
About the Course: In this course you'll gain an introduction to the modern study of dynamical systems, the interdisciplinary field of applied mathematics that studies systems that change over time. Topics to be covered include: phase space, bifurcations, chaos, the butterfly effect, strange attractors, and pattern formation. The course will focus on some of the realizations from the study of dynamical systems that are of particular relevance to complex systems: 1. Dynamical systems undergo bifurcations, where a small change in a system parameter such as the temperature or the harvest rate in a fishery leads to a large and qualitative change in the system's behavior. 2. Deterministic dynamical systems can behave randomly. This property, known as sensitive dependence or the butterfly effect, places strong limits on our ability to predict some phenomena. 3. Disordered behavior can be stable. Non-periodic systems with the butterfly effect can have stable average properties. So the average or statistical properties of a system can be predictable, even if its details are not. 4. Complex behavior can arise from simple rules. Simple dynamical systems do not necessarily lead to simple results. In particular, we will see that simple rules can produce patterns and structures of surprising complexity.
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Governance, Complexity, and Democratic Participation

Abstract This article applies complexity theory to urban governance. It is argued that expert-based, hierarchical-instrumental policy making encounters insurmountable obstacles in modern liberal democracies. One of the root causes of this erosion of output legitimacy is the complexity of social systems. Complexity is defined as the density and dynamism of the interactions between the elements of a system. Complexity makes system outcomes unpredictable and hard to control and, for this reason, defies such well-known policy strategies as coordination from the center, model building, and reduction of the problem to a limited number of controllable variables. It is argued that participatory and deliberative models of governance are more effective in harnessing complexity because they increase interaction within systems and thereby system diversity and creativity. Using empirical data from research on citizen participation in disadvantaged neighborhoods in the Netherlands, the author shows (a) that neighborhoods can fruitfully be seen as complex social systems and (b) the different ways in which citizen participation is effective in harnessing this complexity.

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Sociology and Complexity Science blog: Interview with David Byrne

Sociology and Complexity Science blog: Interview with David Byrne | Bounded Rationality and Beyond | Scoop.it
Interview with David Byrne The following is a brief interview I conducted with British Sociologist and Complexity Scientist, David Byrne. Dr. Byrne is Professor in the School of Applied Social Sciences at Durham University, England, where he is also Director of Postgraduate Studies. Dr. Byrne is the author of several books and a long list of articles, including his 1998 book, Complexity Theory and the Social Sciences--the first book to critically review and explore the application of complexity science to sociological inquiry. His most recent book, edited with noted sociologist and methodologist, Charles Ragin is The SAGE Handbook of Case-Based Methods Dr. Byrne is an expert in methods, urban planning, community health, social policy, social exclusion and complexity science.
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Evaluating Complex Social Interventions in a Complex World.DS Byrne 

Evaluating Complex Social Interventions in a Complex World.DS Byrne  | Bounded Rationality and Beyond | Scoop.it
Abstract The social world is complex and emergent. Inquiry, directed towards establishing universal empirical regularities (i.e. nomothetic inquiry), cannot establish causality in such a world. We can never assign a causal effect to any intervention without assessing the whole context of that intervention. However, we can develop generalizable knowledge if we adopt research approaches that recognize both the implications of assigning causal powers to context (the essence of the realist take on evaluation) and the significance of human agency in relation to ‘the social type of causal nexus’. There are literatures that can contribute to developing such knowledge. These include macro-political science’s concern with the importance of temporal ordering in relation to outcomes; Ragin’s set theoretic understanding of causal relations and his development of systematic comparison as a basis for explicating those relations through Qualitative Comparative Analysis (QCA); and the presentation of causal narratives as foundation for process tracing. Every complex social intervention has to be considered as a ‘case’. Systematic comparison across cases allows us to generalize within limits – but this still means we can transfer knowledge beyond the unique ideographically described instance. We can never establish universal/nomothetic accounts of causality in complex systems by using variable-based methods such as Randomized Controlled Trials (RCTs). However, through careful comparison and exploration of complex contingent causation, we can begin to get a handle on what works where (in what context), when (in what temporal context), and in what order.
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