Francesco Guala

The development of capability indicators

This paper is motivated by sustained interest in the capabilities approach to welfare economics combined with the paucity of economic statistics that measure capabilities at the individual level. Specifically, it takes a much discussed account of the normatively desirable capabilities constitutive of a good life, argued to be comprehensive at a high level of abstraction, and uses it to operationalize the capabilities approach by developing a survey instrument to elicit information about capabilities at the individual level. The paper explores the extent to which these capabilities are covariates of a life satisfaction measure of utility and investigates aspects of robustness and subgroup differences using standard socio‐demographic variables as well as a relatively novel control for personality. In substantial terms, we find there is some evidence of quantitative, but no qualitative, gender and age differences in the capabilities–life satisfaction relationship. Furthermore, we find that indicators from a wide range of life domains are linked to life satisfaction, a finding that supports multi‐dimensional approaches to poverty and the non‐materialist view that people do not just value financial income per se. Our most important contribution, however, is primarily methodological and derives from the demonstration that, within the conventions of household and social surveys, human capabilities can be measured with the aid of suitably designed statistical indicators.

Models, Simulations, and Experiments

I discuss the difference between models, simulations, and experiments from an epistemological and an ontological perspective. I first distinguish between “static” models (like a map) and “dynamic” models endowed with the capacity to generate processes. Only the latter can be used to simulate. I then criticize the view according to which the difference between models/simulations and experiments is fundamentally epistemic in character. Following Herbert Simon, I argue that the difference is ontological. Simulations merely require the existence of an abstract correspondence between the simulating and the simulated system. In experiments, in contrast, the causal relations governing the experimental and the target systems are grounded in the same material. Simulations can produce new knowledge just as experiments do, but the prior knowledge needed to run a good simulation is not the same as that needed to run a good experiment. I conclude by discussing “hybrid” cases of “experimental simulations” or “simulating experiments”.

Building economic machines : the FCC auctions

Abstract The auctions of the Federal Communication Commission, designed in 1994 to sell spectrum licences, are one of the few widely acclaimed and copied cases of economic engineering to date. This paper includes a detailed narrative of the process of designing, testing and implementing the FCC auctions, focusing in particular on the role played by game theoretical modelling and laboratory experimentation. Some general remarks about the scope, interpretation and use of rational choice models open and conclude the paper.

Experiments in economics: External validity and the robustness of phenomena

External validity is the problem of generalizing results from laboratory to non‐laboratory conditions. In this paper we review various ways in which the problem can be tackled, depending on the kind of experiment one is doing. Using a concrete example, we highlight in particular the distinction between external validity and robustness, and point out that many experiments are not aimed at a well‐specified real‐world target but rather contribute to a ‘library of robust phenomena’, a body of experimental knowledge to be applied case by case.

Experimental Localism and External Validity

Experimental “localism” stresses the importance of context‐specific knowledge, and the limitations of universal theories in science. I illustrate Latours radical approach to localism and show that it has some unpalatable consequences, in particular the suggestion that problems of external validity (or how to generalize experimental results to nonlaboratory circumstances) cannot be solved. In the last part of the paper I try to sketch a solution to the problem of external validity by extending Mayos error‐probabilistic approach.

Institutions, rules, and equilibria: a unified theory *

We propose a new framework to unify three conceptions of institutions that play a prominent role in the philosophical and scientific literature: the equilibria account, the regulative rules account, and the constitutive rules account. We argue that equilibrium-based and rule-based accounts are individually inadequate, but that jointly they provide a satisfactory conception of institutions as rules-in-equilibrium. In the second part of the paper we show that constitutive rules can be derived from regulative rules via the introduction of theoretical terms. We argue that the constitutive rules theory is reducible to the rules-in equilibrium theory, and that it accounts for the way in which we assign names to social institutions.

The problem of external validity (or “parallelism”) in experimental economics

This article is in three parts: in the first section, a real case of laboratory experimentation in economics illustrates what experimentalists do in order to test the external validity of their results. Then, it is shown that such a practice presupposes a specific conception of the causal relations economists are seeking. Some general remarks about the notions of external validity and parallelism are provided in conclusion.

Autonomy-Freedom and Deliberation

Recent attempts to model and measure freedom in the Freedom of Choice Literature (FCL) have focused on the range of opportunities enjoyed by individuals. In this article we focus instead on the range of autonomous choices available to individuals. We illustrate how this approach differs from traditional proposals in FCL and discuss a metric that captures the autonomy aspect of freedom of choice.

Artefacts in experimental economics: preference reversals and the Becker Marschak mechanism

Controversies in economics often fizzle out unresolved. One reason is that, despite their professed empiricism, economists find it hard to agree on the interpretation of the relevant empirical evidence. In this paper I will present an example of a controversial issue first raised and then solved by recourse to laboratory experimentation. A major theme of this paper, then, concerns the methodological advantages of controlled experiments. The second theme is the nature of experimental artefacts and of the methods devised to detect them. Recent studies of experimental science have stressed that experimenters are often merely concerned about determining whether a certain phenomeonon exists or not, or whether, when, and where it can be produced, without necessarily engaging in proving or disproving any theoretical explanation of the phenomenon itself. In this paper I shall be concerned mainly with such a case, and focus on the example of preference reversals, a phenomenon whose existence was until quite recently denied by the majority of economists. Their favourite strategy consisted in trying to explain the phenomenon away as an artefact of the experimental techniques used to observe it. By controlled experimentation, as we shall see, such an interpretation has been discredited, and now preference reversals are generally accepted as real. The problem of distinguishing an artefact from a real phenomenon is related to methodological issues traditionally discussed by philosophers of science, such as the theory-ladenness of observation and Duhems problem. Part of this paper is devoted to clarifying these two philosophical problems, and to arguing that only the latter is relevant to the case in hand. The solutions to Duhems problem devised by economic experimentalists will be presented and discussed. I shall show that they belong in two broad categories: independent tests of new predictions derived from the competing hypotheses at stake, and ‘no-miracle arguments’ from different experimental techniques delivering converging results despite their being theoretically independent.

Extrapolation, Analogy, and Comparative Process Tracing

Comparative process tracing is the best analysis of extrapolation inferences in the philosophical and scientific literature so far. In this essay I examine some similarities and differences between comparative process tracing and former attempts to capture the logic of extrapolation, such as the analogical approach. I show that these accounts are not different in spirit, although comparative process tracing supersedes previous proposals in terms of analytical detail. I also examine some qualms about the possibility of drawing extrapolation inferences in the social sciences and conclude by suggesting that there may be cases of extrapolation without process tracing.