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"Approximately one in six top economic research papers draws an explicitly causal conclusion. But what do economists mean when they conclude that A 'causes' B? Does 'cause' say that we can influence B by intervening on A, or is it only a label for the correlation of variables? Do quantitative analyses of observational data followed by such causal inferences constitute sufficient grounds for guiding economic policymaking? The Philosophy of Causality in Economics addresses these questions by analyzing the meaning of causal claims made by economists and the philosophical presuppositions underlying the research methods used. The book considers five key causal approaches: the regularity approach, probabilistic theories, counterfactual theories, mechanisms, and interventions and manipulability. Each chapter opens with a summary of literature on the relevant approach and discusses its reception amongst economists. The text details case studies, and goes on to examine papers which have adopted the approach in order to highlight the methods of causal inference used in contemporary economics. It analyses the meaning of the causal claim put forward, and finally reconstructs the philosophical presuppositions accepted implicitly by economists. The strengths and limitations of each method of causal inference are also considered in the context of using the results as evidence for policymaking. This book is essential reading to those interested in literature on philosophy of economics, as well as the philosophy of causality and economic methodology in general."

AbstractThe results of econometric modeling are fragile in the sense that minor changes in estimation techniques or sample can lead to statistical models that support inconsistent causal hypotheses. The fragility of econometric results undermines making conclusive inferences from the empirical literature. I argue that the program of evidential pluralism, which originated in the context of medicine and encapsulates to the normative reading of the Russo-Williamson Thesis that causal claims need the support of both difference-making and mechanistic evidence, offers a ground for resolving empirical disagreements. I analyze a recent econometric controversy regarding the tax elasticity of cigarette consumption and smoking intensity. Both studies apply plausible estimation techniques but report inconsistent results. I show that mechanistic evidence allows for discriminating econometric models representing genuine causal relations from accidental dependencies in data. Furthermore, I discuss the differences between biological and social mechanisms and mechanistic evidence across the disciplines. I show that economists mainly rely on mathematical models to represent possible mechanisms (i.e., mechanisms that could produce a phenomenon of interest). Still, claiming the actuality of the represented mechanisms requires establishing that crucial assumptions of these models are descriptively adequate. I exemplify my approach to assessing the quality of mechanistic evidence in economics with an analysis of two models of rational addiction.

The article is aimed at reconsidering the question if the project of econometrics can be read in line with scientific realism. Previously, the methodological literature focused on the philosophy of econometrics, voices criticizing realist interpretations of econometrics were raised. The criticism was aimed at showing that econometric models lack robustness. The use of slightly different methods leads to obtaining different and often contrary models what supposedly undermine the project of econometrics. In this article, I aim at offering a new argument in defence of the current practice of the economists devoted to the empirical branch of macroeconomics. To do so, I apply Uskali M?ki?s (2009) model of representation to three case studies of contradictory pairs of econometric models and argue that contrary results are not necessarily a drawback of econometrics. Instead, the seemingly contradictory pairs of models are useful in various contexts constituted by their purpose and audience.

Zgodnie z dwiema najpopularniejszymi teoriami filozoficznymi poznanie relacji przyczynowej można sprowadzić do (1) zbadania mechanizmów zachodzących pomiędzy zmiennymi (jak mówią zwolennicy realizmu przyczynowego) lub (2) analizy korelacji zachodzącej pomiędzy zmiennymi (za czym opowiadają się filozofowie kontynuujący tradycję Hume'a). W badaniach zastosowano obie metody w celu odpowiedzi na pytanie, czy istnieje relacja przyczyna – skutek pomiędzy wymiarem kultury indywidualizm-wspólnotowość oraz tempem rozwoju ekonomicznego. Przeprowadzona analiza wykazała, że zorientowanie społeczeństwa na wspólnoty powoduje szybszy wzrost gospodarczy.

The argument put forth in this article shows that the hitherto scientific-realist approaches to econometrics are incongruent with the realistically reconstructed empirical macroeconomics. The SR approaches share in common being realist about the relations depicted by (successful) models. The economic models of data are sensitive to minor changes in sample and estimating methods what creates the 'emerging contrary result' phenomenon: the community of econometricians accept models that are inconsistent. Being SR about econometrics equals committing oneself to the following trilemma: (1) it is feasible to indicate the successful models that rightly isolate/idealize the regularities of the economy (the knowledge thesis); (2) econometric models are about the economic world (the independence thesis); and, at least in some areas of application, (3) successful econometric models contradict each other.

In this article, I focus on the difference in moral judgment of macroeconomic interventions between the deterministic world of a thought experiment and the uncertain reality. The macroeconomic theory coined by Keynes is, in its most popular reading, deterministic and justifies interventionism. However, incorporating uncertainty into the analysis leads to the contrary result. Namely, if economic output is a random process, such as Gaussian white noise or a stochastic Markov chain, then intervening can bring either economic recovery or inflationary pressure and a next bubble. In the trolley‑problem philosophy, the one who pulls the lever instead of the trolley itself is believed to be guilty of the death of an innocent passer‑by standing on the side track. Similarly, if the Federal Reserve decided to intervene and failed (causing a bubble on the house market, instantiating), their monetary policy can be said to be a cause of the financial crisis. Therefore, governments should refrain from interventions.

The paper addresses the question whether the now- infamous piece of econometric research conducted by Reinhart and Rogoff (2010) that set the threshold hypothesis in the relation between public debt and economic growth was conducted in accordance with the neopositivist doctrine. The article consists of two parts. First, the epistemic advice given by logical positivism is reconstructed and operationalized. Second, the cliometric method employed by Reinhart and Rogoff (2010) is analyzed. The answer to the research question is affirmative. 'Growth in a Time of Debt' is a piece of logical-positivist science because (1) the research is data-based and aimed at confirming the results, (2) its authors are committed to the neopositivist theory-observation distinction, (3) its goal is describing an empirical generalization and the result's interpretations suggest that (4) Reinhart and Rogoff (2010) understand causality in a reductionist way, as a constant conjunction.

Methods used to infer causal relations from data rather than knowledge of mechanisms are most helpful and exploited only if the theoretical background is insufficient or experimentation impossible. The review of literature shows that when an investigator has no prior knowledge of the researched phenomenon, no result of the Grangercausality test has any epistemic utility due to different possible interpretations. (1) Rejecting the null in one of the tests can be interpreted as either a true causal relation, opposite direction of the true causation, instant causality, time series cointegration, not frequent enough sampling, etc. (2) Bi-directional Granger causality can be read either as instant causality or common cause fallacy. (3) Non-rejection of both nulls possibly means either indirect or nonlinear causality, or no causal relation.

The contemporary methodological debate focuses on studying the relation between models and reality regarding idealization and resemblance. Limited attention is put on the process of model building. The study focuses its attention on the latter. The purpose of this article is twofold. First, we reconstruct the philosophical presuppositions of the participants of a cliometric debate. Second, we employ the Fleckian constructivist philosophy with the aim of offering an account of how econometric facts are constructed. Contrary to our reconstruction of the process of 'observing' macroeconomic phenomena, econometricians ground their viewpoint in the scientific-realist and neopositivist philosophies of science.