Luis Mireles-Flores

In this article, I offer a methodological analysis of the empirical research on the causal effects of trade liberalisation, and assess whether such studies can be of any use for guiding policy prescriptions in real-world economies. The analysis focuses on the mainstream economic research that has been used to support arguments in favour of trade liberalisation during the last decades. Even though there are empirical results that could be taken as valid evidence for a causal connection between free trade and economic gains, none of the existing evidence licences trustworthy inferences about the policy effectiveness of trade liberalisation reforms in real-world cases. There are three aspects of the empirical literature that make it highly problematic for making reliable policy inferences: (a) the criteria used to define the notion of ‘free trade’, (b) the background assumptions embedded in the econometric techniques used for estimating causal effects, and (c) the widespread desire among academic economists to attain scientific results in terms of universally valid generalisations. The analysis exposes a worrisome mismatch between, on the one hand, the research aims and outcomes of scientific economics and, on the other, the kind of evidence that would be useful for guiding actual policy deliberations.

This article comprises an up-to-date critical review of the field known as Economic Methodology or Philosophy of Economics (EM/PE). Two edited volumes (Kincaid and Ross 2021; Heilmann and Reiss 2021), a special issue of the Journal of Economic Methodology (2021), and a recent bibliometric analysis of the field (Claveau et al. 2021) constitute the basis of the review. Drawing on these sources, we identify a number of problematic trends in current EM/PE research. We claim that these trends could be interpreted as two kinds of biases, namely a micro-level bias and a mainstream bias. We discuss the respective details of these biases and their normative implications for the discipline.

Current philosophical accounts of causation suggest that the same causal assertion can have different meanings. Yet, in actual social-scientific practice, the possible meanings of some causal generalisations intended to support policy prescriptions are not always spelled out. In line with a standard referentialist approach to semantics, we propose and elaborate on four questions to systematically elucidate the meaning of causal generalisations. The analysis can be useful to a host of agents, including social scientists, policy-makers, and philosophers aiming at being socially relevant. To illustrate our proposal, we analyse the complexities related to the meaning of causal generalisations in the context of a concrete case of economic research which is explicitly intended to guide public policy, namely, the OECD research on the causes of unemployment

Mark Blaug used to begin his history of economics course with an old Greek proverb: “the fox knows many little things, but the hedgehog knows one big thing”. He would then say that one could characterise most thinkers in the history of economic thought as either a fox or a hedgehog. As a student, I found that this character-driven view illuminated past economists’ theories in a fresh way and brought home to me the distinctiveness of their approaches. Nevertheless, after reading his work, attending his course, listening to him at seminars, and becoming familiar with his ideas on the history and methodology of economics, one question has always remained unanswered in my mind: was Mark Blaug a fox or a hedgehog?

The most common way of analysing the meaning of causal generalisations relies on referentialist semantics. In this article, we instead develop an analysis based on inferentialist semantics. According to this approach, the meaning of a causal generalisation is constituted by the web of inferential connections in which the generalisation participates. We distinguish and discuss five classes of inferential connections that constitute the meaning of causal generalisations produced in policy-oriented economic research. The usefulness of our account is illustrated with the analysis of generalisations about unemployment put forward by the Organisation for Economic Co-operation and Development in its highly influential 1994 OECD Jobs Study. The article ends with a discussion of some crucial philosophical questions about the use of inferentialism in the analysis of causal generalisations.