We conducted an experiment in a high-immersive virtual reality environment to study the effect of the presence of a virtual observer on cheating behavior. Participants were placed in a virtual room and played 30 rounds of a cheating game without a chance of their cheating being detected. We varied whether or not a virtual observer (an avatar) was present in the room, and, if so, whether the avatar was actively staring at the decision maker or passively seated in a corner watching his smartphone. Results display significantly less cheating with an active than with a passive avatar, but not less cheating than in a control condition without an avatar. This suggests that an active (virtual) observer can intensify reputational concerns, but that the presence of someone passive and uninterested may actually alleviate such concerns.

Outcomes and strategies shown in control questions prior to experimental play may provide subjects with anchors or induce experimenter demand effects. In a Cournot oligopoly experiment we explore whether control questions influence subjects’ choices in initial periods and over the course of a repeated game. We vary the framing of the control question to explore the cause of potential influences. We find no evidence for an influence of the control question on choices, neither in the first period nor later in the game.

Experimenter demand effects refer to changes in behavior by experimental subjects due to cues about what constitutes appropriate behavior. We argue that they can either be social or purely cognitive, and that, when they may exist, it crucially matters how they relate to the true experimental objectives. They are usually a potential problem only when they are positively correlated with the true experimental objectives’ predictions, and we identify techniques such as non-deceptive obfuscation to minimize this correlation. We discuss the persuasiveness or otherwise of defenses that can be used against demand effects criticisms when such correlation remains an issue.

Agent-based simulations and human-subject experiments explore the emergence of respect for property in a specialization and exchange economy with costless theft. Software agents, driven by reciprocity and hill-climbing heuristics and parameterized to replicate humans when property is exogenously protected, are employed to predict human behavior when property can be freely appropriated. Agents do not predict human behavior in a new set of experiments because subjects innovate, constructing a property convention of “mutual taking” in 5 out of the 6 experimental sessions that allows exchange to crowd out theft. When the same convention is made available to agents, they adopt it and again replicate human behavior. Property emerges as a social convention that exploits the capacity for reciprocity to sustain trade.

In recent years, experimental economics has seen a rise in the collection and analysis of choice-process data, such as team communication transcripts. The main purpose of this paper is to understand whether the collection of team communication data influences how individuals reason and behave as they enter the team deliberation process, i.e. before any communication exchange. Such an influence would imply that team setups have limited validity to speak to individual reasoning processes. Our treatment manipulations allow us to isolate the effects of (1) belonging to a team, (2) actively suggesting an action to the team partner, and (3) justifying the suggestion in a written text to the team partner. Across three different tasks, we find no systematic evidence of changed suggestions and altered individual sophistication due to changes in aspects (1)–(3) of our experimental design. We thus find no threat to said validity of team setups. In addition to investigating how the team setup affects individual behavior before communication, we also investigate the sophistication of decisions after the communication. We find that sophisticated strategies are more persuasive than unsophisticated strategies, especially when communication includes written justifications, thereby explaining why teams are more sophisticated and proving rich communication to be fruitful.

There is an odd contradiction about much of the empirical (experimental) literature: The data is analysed using statistical tools which presuppose that there is some noise or randomness in the data, but the source and possible nature of the noise are rarely explicitly discussed. This paper argues that the noise should be brought out into the open, and its nature and implications openly discussed. Whether the statistical analysis involves testing or estimation, the analysis inevitably is built upon some assumed stochastic structure to the noise. Different assumptions justify different analyses, which means that the appropriate type of analysis depends crucially on the stochastic nature of the noise. This paper explores such issues and argues that ignoring the noise can be dangerous.

This paper derives career lessons for economists by examining the unusual career of Brian J. Loasby in terms of Loasby’s own key ideas. Loasby’s early career ran into difficulties after he chose to become a postgraduate for lifestyle rather than career reasons, with his insufficiently ambitious reference standards resulting in unduly narrow search for both options and new connections. His eventual success came because of a path-dependent process whereby he developed an organizing framework that was conducive to finding problems and making intellectual connections. It was a process in which making personal connections also had a key role, though some intellectual connections that he earlier failed to make resulted from trusting other people. In the market for contributions to knowledge, his way of branding and positioning his work in relation to management decision-making and the growth of knowledge gave it a wider appeal than would have been the case if he had aligned himself with a particular school of thought or ‘heterodox economics’ in general.

We convey our experiences developing and implementing an online experiment to elicit subjective beliefs and economic preferences. The COVID-19 pandemic and associated closures of our laboratories required us to conduct an online experiment in order to collect beliefs and preferences associated with the pandemic in a timely manner. Since we had not previously conducted a similar multi-wave online experiment, we faced design and implementation considerations that are not present when running a typical laboratory experiment. By discussing these details more fully, we hope to contribute to the online experiment methodology literature at a time when many other researchers may be considering conducting an online experiment for the first time. We focus primarily on methodology; in a complementary study we focus on initial research findings.

Recruitment of representative and generalizable adult samples is a major challenge for researchers conducting economic field experiments. Limited access to representative samples or the high cost of obtaining them often leads to the recruitment of non-representative convenience samples. This research compares the findings from two field experiments involving 860 adults: one from a non-representative in-person convenience sample and one from a representative online counterpart. We find no meaningful differences in the key behaviors of interest between the two samples. These findings contribute to a growing body of literature demonstrating that non-representative convenience samples can be sufficient in certain contexts.

We measure time preferences in a sample of 561 children aged 7–11 years. Using a within-subject design, we compare the behavior of our subjects using two distinct experimental measures of time preferences: a standard choice list with multiple decisions and a single choice time-investment-exercise requiring one decision only. We find that both measures yield very similar aggregate results, correlate significantly within subjects and can be explained by basically the same explanatory variables. Advantages and disadvantages of both measures are discussed. Our findings are relevant for the design of experiments to measure time preferences.

We propose a methodology for normative evaluation when preferences are context-dependent. We offer a precise definition of context-dependence and formulate a normative criterion of self-determination, according to which one situation is better than another if individuals are aware of more potential contexts of a choice problem. We provide two interpretations of our normative approach: an extension of Sugden’s opportunity criterion and an application of Sen’s positional views in his theory of justice. Our proposition is consistent with Muldoon’s and Gaus’ approaches of public reason in social contract theory, which account for the diversity of perspectives in non-ideal worlds.

Multiple selves is a conventional assumption in behavioural welfare economics for modelling intrapersonal well-being. Yet an important question is which self has normative authority over others. In this paper, we advance an argument for what we call the ‘ontological approach’ to personal identity in behavioural welfare economics. According to this approach, ethical questions – such as which preference should be granted normative authority over another – can be informed by the ontological criterion of personal persistence, which aims at determining what it takes for an individual to persist from one time to another.

Price currents and newspapers are major sources of information on prices during the eighteenth and nineteenth centuries, but drawing conclusions about trends and fluctuations in values from the quotations in these sources poses several recurrent difficulties. After discussing the origins of the prices in these sources, we use a range of examples, mainly involving commodity prices, to illustrate important problems in working with historical price data. These include missing observations and price inertia, varying gaps between low and high price quotations, and the splicing together of price series from different sources or for different commodity qualities. The last two problems often arise from changes over time in the detail with which prices for heterogeneous commodities were reported.

The ‘microfoundations’ metaphor had been used by mainstream macroeconomists with the intention of explaining macroeconomics in terms of microeconomics, or more precisely in terms of statements about individuals, viewed as representative agents with rational expectations who maximise lifetime utility, subject to shocks within a general equilibrium framework. Of the three reasons for rejecting this explanatory strategy, the focus here is on downward causation. Although individuals are heavily influenced by society, their decisions and behaviour are not sufficient as the explanatory foundations for a macrotheory.

This paper produces a new estimate of the Argentine cost of living index (COLI) for the period 1912-1943 that amends the oversights of the official series. The lack of an appropriate splice when the shares of the index's components are changed explains the divergence between the official and the Reconstructed COLIs. The 17.3 percentage-point gap for the period 1912-1943 between the official series used by the historiography and the Reconstructed COLI accounts for the oversights of the official estimate. This divergence is also evidenced when generating real wages. Hence, when Juan Domingo Perón arrived at the National Labour Department in 1943, all else being equal, workers of the City of Buenos Aires were worse off economically than the historiography assumes.

In his seminal 1921 book, Risk, Uncertainty, and Profit, Frank Knight distinguished uncertainty and risk. This paper applies Knight's concept of uncertainty to knowledge generated in incumbent organizations to explain the inherent difficulty in assessing potential innovations along with the key role played by knowledge spillover entrepreneurship as a conduit for transforming new knowledge created by an incumbent organization but ultimately commercialized through the creation of a new firm and innovation. Knowledge is inherently uncertain and constitutes what is characterized as the knowledge filter impeding innovative activity in the context of incumbent firms and organizations. The organizational and institutional context and market uncertainty can either facilitate or impede the spillover of knowledge from the firm where it was created to the entrepreneurial startup where it is transformed into innovation. The empirical evidence based on a large, unbalanced panel of 9,126 UK firms constructed from six consecutive waves of a community innovation survey and annual business registry survey during 2002–2014. Implications for managers, scholars, and policymakers are provided.

In Risk, Uncertainty and Profit (RUP), Knight (1921) develops a theory of the firm that stresses the important role of entrepreneurial judgment for a firm's success. For Knight, entrepreneurial judgment is first and foremost the selection of ‘proxy entrepreneurs’ who are capable of making good judgments under uncertainty. In this sense, entrepreneurial judgment is essentially ‘judgment of judgment’. An overlooked implication of Knight's position is the fact that it leads to an endorsement of distributed entrepreneurship and responsibility. We deem this a very modern idea that challenges a completely hierarchical understanding of the firm. Knight himself does not thoroughly examine the institutional implications of the analytical framework he sets up in RUP. In this paper, we summarize the ‘philosophical vision’ of Knight's framework and illustrate his rationale behind the distribution of entrepreneurship. We conclude the paper with a discussion of potential institutional implications by referring to the danger of monocultures, the additional value created by cognitively diverse teams, and the effectiveness of venture capitalists.

Formal economic models of entrepreneurship have two characteristics: they model entrepreneurship as an allocation of resources, and they identify common factors affecting this allocation. These common factors are represented as parameters of optimization models, and they are evaluated at the market level. We argue that although these models are useful, they are incomplete because certain aspects of entrepreneurial behavior, such as judgment, alertness, or innovativeness, cannot be easily transformed into allocative problems. Moreover, entrepreneurial acts involve idiosyncratic elements, which limit the applicability of the market-level analysis to individual cases. Thus, the traditional economic methods have to be complemented by approaches highlighting the role of individual and historical specificity. The study of entrepreneurship, therefore, requires a synthesis of both general theory and historicist approaches, as envisioned a century ago by Frank Knight.

Hayek’s seminal contribution to theoretical neurosciences, The Sensory Order (1952) remains neglected in current efforts at integrating the neurosciences, psychology and economics. I defend the view that Hayek presents the case for an evolutionary alternative to leading paradigms in the field and look at two in more detail: the good-based model in neuroeconomics and the dual systems approach in behavioural economics. In both cases, essential Hayekian insights remain valid in the context of modern neuroscience, allow for taking account of recent research, and sketch a dynamic and selectionist model of choice.

“Uncertain futures” refers to a set of policy problems that possess some combination of the following characteristics: (i) they potentially cause irreversible changes; (ii) they are widespread, so that policy responses may make sense only on a global scale; (iii) network effects are difficult to understand and may amplify (or moderate) consequences; (iv) time horizons are long; and (v) the likelihood of catastrophic outcomes is unknown or even unknowable. These characteristics tend to make uncertain futures intractable to market solutions because property rights are not clearly defined and essential information is unavailable. These same factors also pose challenges for benefit-cost analysis (BCA) and other traditional decision analysis tools. The diverse policy decisions confronting decision-makers today demand “dynamic BCA,” analytic frameworks that incorporate uncertainties and trade-offs across policy areas, recognizing that: perceptions of risks can be uninformed, misinformed, or inaccurate; risk characterization can suffer from ambiguity; and experts’ tendency to focus on one risk at a time may blind policymakers to important trade-offs. Dynamic BCA – which recognizes trade-offs, anticipates the need to learn from experience, and encourages learning – is essential for lowering the likelihoods and mitigating the consequences of uncertain futures while encouraging economic growth, reducing fragility, and increasing resilience.