Behavioural Economics and Non-Market Interactions

Program Lead: Professor Benno Torgler   |   Deputy Program Lead: Dr Ho-Fai (Ben) Chan

Humans do not always behave the way we would expect, making decisions based on emotions, beliefs, biases, feelings or habits. This program applies behavioural economics of social and non-market interactions to understand how humans behave and interact.


Large Scale Decisions in Human Mating

09/07/2015 - 30/11/2018

Funded by the BEST Centre

Scientist career path: An explorative analysis

01/02/2018 - Ongoing

Funded by ARC DP180101169

Decision making and behaviour of Australian women

01/09/2019 - Ongoing

Partially funded by YWCA Australia

Non-Market Behavioural Economics

Economics is no longer what it used to be. In the past, economics was contained to the sphere of commercial life, revolving around topics such as money, taxes, tariffs, stocks and bonds. In recent years behavioural economics has helped to significantly expand economists’ areas of concern. As a consequence the boundaries of economics as a discipline are rapidly expanding outward, exploring areas that have historically been the exclusive domain of other social sciences. In this research program we will look at extraordinarily important areas of inquiry, covering topics such as academia, sports, crime, sex, war, and politics, the understanding of which will benefit from a behavioural economics perspective. At the core of the endeavour is to understand human nature and human behaviour. As McKenzie and Gordon Tullock once said: “crimes cannot be committed, children cannot be reared, sex cannot be had, and government cannot operate without people “behaving” in one respect or another”. For this, the Behavioural Non-Market Economics program will take advantage of a broad set of methods applied in behavioural economics such as laboratory, field, and natural experiments. Beyond that, a common theme is to find controlled settings to understand how humans behave and interact. It will look at scientists, artists, sports athletes, or innovators. Such environments offer a unique arena for career path investigation, one in which we can easily identify names, measure performance, how people communicate and interact, follow life histories, and pinpoint the precise environmental conditions and changes of a large number of observations over time. In this arena, the incentive structure (e.g. publish, win a game or tournament, enhance knowledge, build a reputation, gain a crowdfunding project, develop innovative ideas and projects etc.), the constraints, and the job profiles are clearly spelled out, making it akin to a real-world laboratory in which all else can approximately be held equal. Hence, the data produced, although drawn using real incentives in an actual field setting, are relatively clean and subject to low measurement error. The next sections discuss the core sub-programs that will guide the research agenda.


Science and innovation are the most significant engines of a nation’s long run sustainable economic growth and prosperity. One important avenue for understanding scientific development and innovation is scientific endeavour, as represented by scientific career paths. The proposed study will thus examine the major driving forces of scientists’ careers, including key points over the life-cycle (e.g. key positive or negative events or changes), collaboration dynamics, creative development or innovative activities, and success (measured by number and quality of publications, citations, and patents). Although every research endeavour aims to expand the frontiers of science and innovation, empirical evidence on and comprehension of the dynamics underlying scientific careers is limited. This sub-program will expand this knowledge by uncovering valuable new insights on both the research landscape and the scientists and their interactions. At the core of our analysis will be such aspects as scientists’ resilience to both positive and negative life event shocks, as well as to environmental conditions and changes; patterns of collaboration and co-operation; the characteristics of innovators or followers and their environment, and how ideas emerge and disappear. To this end, we will also explore how performance and success are linked to collaborative relationships and mentoring, or perhaps driven by ‘catalysts’; that is, scientists who evoke better performance in others. Covering this range of important factors in scientific careers adds rigor, allowing exploration of a plethora of new ideas and providing a substantial number of new empirical insights in an area in which evidence is limited. This sub-program will thus contribute to a better understanding of the scientific process. The sub-program will benefit from our recent ARC DP grant through which we collaborate with leading scholars in that field, working at universities and organizations such as Yale, UCLA or the Institute for Advanced Studies in Vienna. Methodologically, the aim is to generate the largest panel data set on scientists ever collected and analysed.


In recent decades, sports data have been used to creatively explore various behavioural aspects that offer implications beyond just sports. For example, analyses have focused on strategic behaviour to empirically test game theoretical theorems or concepts such as minimax by looking at penalty kicks, corruption through investigation of non-linear incentive pay-off structures to identify match rigging among Sumo wrestlers, or favouritism for home teams by comparing extra time provided at the end of a soccer game. Thus, sports data offer an opportunity to overcome the difficulties inherent in exploring strategic models of behaviour. Based on these advantages, it follows that scholars in the area of decision science, behavioural economics, or economic psychology have made extensive use of sports data. In this sub-program we will look at a large number of rule changes as a natural experiment. Rule changes are often targeted at modifying behaviours occurring within in games. The professionalization of sports events has substantially increased over the past few decades. We will look not only at the entire career path of professionals but also how they act and the decisions they make before and after becoming professionals. Using data gathered from social media (Twitter and Google), we will explore the implications of positive and negative life events. We will also collaborate with local and global sports teams and providers to conduct field experiments. In addition, we will examine the career and behavioural implications of recognition and reputation. We are particularly interested in the dynamics of receiving awards, as well as the behavioural motivations of performance preceding and following the award. The growing research area on awards using sports data will help extend our understanding of behavioural aspects such as cooperativeness, aggressiveness, and reciprocity.


The increasing use of rigorous scientific methods to answer long-standing questions in the social sciences is producing an environment in which the boundaries between economics, social psychology, and sociology have become increasingly fluid, facilitating what Edward O. Wilson called the mind’s greatest enterprise: promoting the linkage between sciences and humanities. Technological advances in neuroscience, particularly in wearable, nonintrusive, and non-invasive instruments, have opened fruitful new research avenues for the social sciences, on which they are likely in turn to have a major impact. Monitoring physiological processes through non-intrusive means such as surface electrodes, is attractive for its potential to identify psychological or mental processes that are otherwise hard to measure.

Research into how we mentally cope with the complexity faced constantly in daily life is limited by existing technology and comes at a high price. For example, high resolution data derived from functional magnetic resonance imaging (fMRI) is extremely costly because of the sheer magnitude of the equipment and technology needed to retrieve it. Nor are such instruments wearable during daily activities. The sociometrics sub-program will take advantage from the recent exponential growth in technological innovations including the production of an increasing array of wearable sensors that allow the mapping of the behaviours and interactions of large numbers of individuals in their natural everyday environments. More than 4.6 billion unique mobile phone subscribers, offers a clear potential in this area. Smart phones or wearable electronic badges with integrated sensors offer a variety of possibilities for simultaneously tracking the digital footprint of hundreds or thousands of individuals over days, months, or even years. For example, a phone with an emotion-sensing application can provide information on an individual’s habits, movements, conversation patterns, health status, and social network, as well as contextual factors such as ambient sound. The ‘reality mining’ facilitated by such instruments has the power to increase the external validity of social science research orders of magnitude beyond what is possible using other methods of primary data collection.

Wearable technologies allow researchers to move beyond the artificiality of a subject lying in an fMRI scanner during an experiment, while also complementing the use of surveys, helping to compensate for their inherent problems of reporting biases, memory errors, and scarcity of continuous data. If we are to gain realistic insights into complex phenomena such as human intentions, goals, wishes, conflicts, and values, we must not only combine sets of measurements and diverse tools but also pool the data derived from particular situations with randomized controlled trials and/or link them to historical natural experiments. This sub-program will focus on questions that will benefit from a better biological micro-foundation for our understanding of the behaviour of individual humans, as well as from the ability to observe, track, and map individuals’ interactions with one another.

The brain and body interacts in the generation of emotions, thus any realistic theory of thinking, acting, and problem solving must incorporate the influence of emotion. The environment in which humans act is complex. Any realistic model of human behaviour must be able to handle interdependencies between underlying model assumptions, observed social communications, and the resulting individual behaviour. The sub-program Sociometrics will provide a better empirical testing of theories and concepts developed many decades ago in such areas as cybernetics, systems theory, and nonlinear science. Micro-level sensory data in particular can guide both micro and macro-oriented research endeavours such as agent based modelling, feedback loops, and network theory. Combining these factors can catalyse the exploration of heuristics that guide individuals’ behaviour to the identification of emergent behaviour patterns in society that integrate contextual forces. Information gathered by sensing devices could also potentially be used to improve the functioning of teams, work groups, organizations, and even society in general as they may further illuminate the structure of decision making and interpersonal processes.

Our understanding of how humans perceive and think about a particular situation can also be improved by accommodating both verbal and nonverbal communication, and by seeking the patterns in a dynamic exchange rather than simple behavioural endpoints of social processes. Interaction between individuals produces the social fabric. Thus, new organizational arrangements create new opportunities for individuals. Hence, just as living systems co-evolve with their environment, human behaviour co-evolves within the social fabric, and both social and individual factors determine the interactions that influence individual preferences, beliefs, and opportunities. The social fabric inherently affects decision makers’ learning and cognition, with this influence frequently going unrecognized by decision makers themselves. Large scale sensory data can assist in such endeavours by helping to map the system and the feedback loops that characterize it over time, creating strong path dependence. Continuous and fine-grained data streams prevent the loss of information like ‘footprints in the sand’. Insights in this sub-program will feed back also into the scientometrics program. Both bodies of research raise many important questions. What steps are involved in the mechanism of innovation? Which mixture of competition and co-operation would produce high versus low levels of creativity and innovation in a society? Can progress be hastened, so that the wait for new ideas is reduced? Could an explosion of niches in the form of self-maintaining structures be manufactured, providing an opportunity for society, scientists, or the modern world in general to escape from what Gell-Mann calls the ‘intellectual rut in which we are trapped?’.


The impact of new and sophisticated methods in the study of the past allows a better exploration of human nature from a behavioural economics perspective, combining historical problems with advanced statistical analysis using controlled settings for such natural experiments. The sub-program takes advantage of an increasingly richer set of data to explore many important motives such as national patriotism, political partisanship, religious faith, moral principle, love, hate, and survival. A current project may help clarify what is possible. We are currently exploring whether religious ideology explains effort expenditure decisions in salient settings. For that, we analyse a novel dataset of over 16,000 WWII soldiers from the German military archives and show that, consistent with Max Weber’s proposition, Protestant soldiers expend more effort than Catholics, receiving more military decorations and promotions and sustaining more injuries. We rule out differences in commitment to the Nazi ideology and discrimination against Catholic soldiers as key alternate explanations. The rich nature of our dataset allows us to control for a wide range of covariates, which account for only half of the effect size. Our results are confirmed in instrumental variable regressions exploiting the distance between soldier birthplaces and Wittenberg, where Martin Luther initiated the Reformation, as a source of exogenous variation in the exposure to Protestantism. We find evidence of cultural spillovers, as Catholics from historically Protestant districts exert more effort than Catholics from Catholic districts, and of convergence at the top, as differences are smaller among top performers and insignificant among the most fanatical Nazi group of all, the Waffen-SS.

The key advantage of our study, in comparison with existing work, is that the salient setting allows us to observe behaviour that is more closely related to preferences for work. A central difficulty with the question of whether religious denomination affects preferences for work is that the econometrician does not observe preferences directly. Our setting allows us to observe behaviour that is more closely related to preferences, since incentives to shirk at wartime are extremely high. Put simply, if Protestantism has any ‘bite’ on work effort, we are much more likely to observe its effects in a setting where effort has very serious consequences, as is the case for the soldiers in our dataset. In addition to the above literature on the Protestant work ethic hypothesis, our work is related to other strands of research such as investigation of the role of religion, and of culture more broadly, in shaping economic outcomes or the growing literature on the economics of awards – all of which is linked to the other sub-programs. Awards are widely used in all arenas of society, from the army, to the arts, media, and fashion; sports, religion, voluntary and humanitarian sectors; academia and the business world. The core of the cliometrics program is an investigation that goes beyond people’s daily interactions in families, neighbourhoods, or work groups. This differs from the sociometrics programs, as these behaviours offer only limited understanding of human or cultural values in extreme situations. Most social science studies seek to capture behaviour under “normal” conditions and thus provide no clear evidence on how or whether their results would apply in extreme or difficult environments. Thus, this sub-program extends on recent work that we have conducted that explores decision-making under stress. A key advantage of exploring life-and-death situations is that preferences are clearly revealed.