In this article, I clarify some of the key concepts and commitments of realist social ontology in economics. To do so, I make use of a recent critique of Lawson’s Reorienting Economics by Mohun and Veneziani. Their article provides a useful foil because responding to their critique allows us to emphasize that realism’s claims are more conditional and less controversial than one might otherwise anticipate. The basic claim is that ontology matters and that explicit recognition and consideration of ontological issues (...) can be beneficial. However, developing a focus on ontology can create problems of interpretation among economists regarding what is being claimed and offered. I discuss some of these with reference to an adaption of Maki’s concept of economics imperialism and also with reference to Mary Morgan’s recent typology of experiments. (shrink)

In a well-cited book chapter, ecologist Jared Diamond characterizes three main types of experiment performed in community ecology: laboratory experiment, field experiment, and natural experiment. Diamond argues that each form of experiment has strengths and weaknesses, with respect to, for example, realism or the ability to follow a causal trajectory. But does Diamond’s typology exhaust the available kinds of cause-finding practices? Some social scientists have characterized something they call “causal process tracing.” Is this a fourth type of experiment or something (...) else? I examine Diamond’s typology and causal process tracing in the context of a case study concerning the dynamics of wolf and deer populations on the Kaibab Plateau in the 1920s, a case that has been used as a canonical example of a trophic cascade by ecologists but which has also been subject to controversy. I argue that ecologists have profitably deployed causal process tracing together with other types of experiment to help settle questions of causality in this case. It remains to be seen how widespread the use of causal process tracing outside of the social sciences is (or could be), but there are some potentially promising applications, particularly with respect to questions about specific causal sequences. (shrink)

ABSTRACTExperimentation is traditionally considered a privileged means of confirmation. However, why and how experiments form a better confirmatory source relative to other strategies is unclear, and recent discussions have identified experiments with various modeling strategies on the one hand, and with ‘natural’ experiments on the other hand. We argue that experiments aiming to test theories are best understood as controlled investigations of specimens. ‘Control’ involves repeated, fine-grained causal manipulation of focal properties. This capacity generates rich knowledge of the object investigated. (...) ‘Specimenhood’ involves possessing relevant properties given the investigative target and the hypothesis in question. Specimens are thus representative members of a class of systems, to which a hypothesis refers. It is in virtue of both control and specimenhood that experiments provide powerful confirmatory evidence. This explains the distinctive power of experiments: although modelers exert extensive control, they do not exert this control over specimens; although natural experiments utilize specimens, control is diminished. (shrink)

My aim is to question whether the introduction of new technologies in society may be considered to be genuine experiments. I will argue that they are not, at least not in the sense in which the notion of experiment is being used in the natural and social sciences. If the introduction of a new technology in society is interpreted as an experiment, then we are dealing with a notion of experiment that differs in an important respect from the notion of (...) experiment as used in the natural and social sciences. This difference shows itself most prominently when the functioning of the new technological system is not only dependent on technological hardware but also on social ‘software’, that is, on social institutions such as appropriate laws, and actions of operators of the new technological system. In those cases we are not dealing with ‘simply’ the introduction of a new technology, but with the introduction of a new socio-technical system. I will argue that if the introduction of a new socio-technical system is considered to be an experiment, then the relation between the experimenter and the system on which the experiment is performed differs significantly from the relation in traditional experiments in the natural and social sciences. In the latter experiments it is assumed that the experimenter is not part of the experimental system and is able to intervene in and control the experimental system from the outside. With regard to the introduction of new socio-technical systems the idea that there is an experimenter outside the socio-technical system who intervenes in and controls that system becomes problematic. From that perspective we are dealing with a different kind of experiment. (shrink)

In experimental settings, scientists often “make” new things, in which case the aim is to intervene in order to produce experimental objects and processes—characterized as ‘effects’. In this discussion, I illuminate an important performative function in measurement and experimentation in general: intervention-based experimental production (IEP). I argue that even though the goal of IEP is the production of new effects, it can be informative for causal details in scientific representations. Specifically, IEP can be informative about causal relations in: regularities under (...) study; ‘intervention systems’, which are measurement/experimental systems; and new technological systems. (shrink)

In experimental settings, scientists often “make” new things, in which case the aim is to intervene in order to produce experimental objects and processes—characterized as ‘effects’. In this discussion, I illuminate an important performative function in measurement and experimentation in general: intervention-based experimental production. I argue that even though the goal of IEP is the production of new effects, it can be informative for causal details in scientific representations. Specifically, IEP can be informative about causal relations in: regularities under study; (...) ‘intervention systems’, which are measurement/experimental systems; and new technological systems. (shrink)

It is an open question whether well-being ought to primarily be understood as a temporal concept or whether it only makes sense to talk about a person’s well-being over their whole lifetime. In this article, I argue that how this principled philosophical disagreement is settled does not have substantive practical implications for well-being science and well-being policy. Trying to measure lifetime well-being directly is extremely challenging as well as unhelpful for guiding well-being public policy, while temporal well-being is both an (...) adequate indirect measure of lifetime well-being, and an adequate focus for the purposes of improving well-being through public policy. Consequently, even if what we ought to care about is lifetime well-being, we should use temporal measures of well-being and focus on temporal well-being policies. (shrink)

In economics, thought experiments are frequently justified by the difficulty of conducting controlled experiments. They serve several functions, such as establishing causal facts, isolating tendencies, and allowing inferences from models to reality. In this paper, I argue that thought experiments served a further function in economics: facilitating the quantitative definition and measurement of the theoretical concept of utility, thereby bridging the gap between theory and statistical data. I support my argument by a case study, the “hypothetical experiments” of the Norwegian (...) economist Ragnar Frisch (1895-1973). Frisch aimed to eliminate introspection and a subjective concept of utility from economic reasoning. At the same time, he sought behavioral foundations for economic theory that enabled quantitative reasoning. By using thought experiments to justify his set of choice axioms and facilitating the operationalization of utility, Frisch circumvented the problem of observing utility via actual experiments without eliminating the concept of utility from economic theory altogether. As such, these experiments helped Frisch to empirically support the theory’s most important results, such as the laws of demand and supply, without the input of new empirical findings. I suggest that Frisch’s experiments fulfill the main characteristics of thought experiments. (shrink)

Natural experiments are an increasingly popular research design in political science. This popularity raises a number of questions. First, what are natural experiments and why are they appealing? Second, what makes a good natural experiment? And finally, are natural experiments able to provide resources for knowledge production that other methodologies cannot or do not provide? Using Mary Morgan’s and Thad Dunning’s recent work on natural experiments, I offer answers to the first two questions and use the analysis to argue that (...) natural experiments highlight features of knowledge production that support methodological pluralism and the multiple aims of research. (shrink)

The most conspicuous form of agricultural experiment is the field trial, and within the history of such trials, the arrival of the randomised control trial is considered revolutionary. Originating with R.A. Fisher within British agricultural science in the 1920s and 30s, the RCT has since become one of the most prodigiously used experimental techniques throughout the natural and social sciences. Philosophers of science have already scrutinised the epistemological uniqueness of RCTs, undermining their status as the ‘gold standard’ in experimental design. (...) The present paper introduces a historical case study from the origins of the RCT, uncovering the initially cool reception given to this method by agricultural scientists at the University of Cambridge and the National Institute of Agricultural Botany. Rather than giving further attention to the RCT, the paper focuses instead on a competitor method – the half-drill strip – which both predated the RCT and remained in wide use for at least a decade beyond the latter’s arrival. In telling this history, John Pickstone’s Ways of Knowing is adopted, as the most flexible, and productive way to write the history of science, particularly when sciences and scientists have to work across a number of different kinds of place. It is shown that those who resisted the RCT did so in order to preserve epistemic and social goals that randomisation would have otherwise run a tractor through. (shrink)