Causality and inference in economics: An unended quest

The aim of this article is to point to the unsolved research problems connected to causation in the philosophy of economics. First, the paper defines causation and discusses two notable approaches, i.e. the realist theory of causation and the instrumentalist theory of causation. Second, it offers a review the current research activity focusing on the problem of causation in economics. Third, it discusses several case studies. On the grounds of comparison of the research practice of economists and the current issues undertaken by the philosophers of economics, the paper concludes that there is a gap between the research practice and the normative methodological analyses and indicate the research questions that need to be addressed.Financed by the National Science Center (grant No. 2015/19/N/HS1/01066); financed through contract no. 501/1/P-DUN/2017 from the funds of the Ministry of Science and Higher Educatio

Ethics, Uncertainty, and Macroeconomics

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 “Annales. Ethics in Economic Life” is affiliated and co-financed by the Faculty of Economics and Sociology of the University of Lodz

Causation in Economics. The Most Recent Analyses and the Unsolved Problems

The main aim of my article is indicating the unsolved research problems connected to causation in the area of the philosophy of economics. First, I briefly define causation and discuss two most notable approaches, i.e. the realist theory of causation and the instrumentalist theory of causation. Second, I review the most recent researches focused on the problem of causation in economics. Third, I discuss a number of case studies. On the grounds of comparison of the research practice of economists and the current issues undertaken by the philosophers of economics, I conclude that there is a gap between the research practice and the normative methodological analyses and indicate the research questions that need to be answered.Badania, których wyniki opisano w niniejszym artykule, zostały sfinansowane przez Narodowe Centrum Nauki (grant nr 2015/19/N/HS1/01066)

A review of the Granger-causality fallacy

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 Granger-causality 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

Methodological pluralism in economics : the "why" and "how" of causal inferences

Recently, two distinct notions of pluralism have been put forward in regard to research methods in economics: (1) model pluralism, stating that economists construct many theoretical models offering descriptions of actual or possible mechanisms and use different models for different purposes, and (2) evidential pluralism, according to which causal claims are established on the basis of theoretical conjecture and by observing the operation of a difference-making factor. In this paper, I make a case for methodological pluralism. I argue that economists not only use different research methods but also interpret their role in causal inference differently - depending on which (big-M) Methodological school they subscribe to. The argument proceeds by analyzing examples of recent economic research appealing to different Methodological commitments

The failure of drug repurposing for COVID-19 as an effect of excessive hypothesis testing and weak mechanistic evidence

The current strategy of searching for an effective treatment for COVID-19 relies mainly on repurposing existing therapies developed to target other diseases. Conflicting results have emerged in regard to the efficacy of several tested compounds but later results were negative. The number of conducted and ongoing trials and the urgent need for a treatment pose the risk that false-positive results will be incorrectly interpreted as evidence for treatments’ efficacy and a ground for drug approval. Our purpose is twofold. First, we show that the number of drug-repurposing trials can explain the false-positive results. Second, we assess the evidence for treatments’ efficacy from the perspective of evidential pluralism and argue that considering mechanistic evidence is particularly needed in cases when the evidence from clinical trials is conflicting or of low quality. Our analysis is an application of the program of Evidence Based Medicine Plus (EBM+) to the drug repurposing trials for COVID. Our study shows that if decision-makers applied EBM+, authorizing the use of ineffective treatments would be less likely. We analyze the example of trials assessing the efficacy of hydroxychloroquine as a treatment for COVID-19 and mechanistic evidence in favor of and against its therapeutic power to draw a lesson for decision-makers and drug agencies on how excessive hypothesis testing can lead to spurious findings and how studying negative mechanistic evidence can be helpful in discriminating genuine from spurious results

‘Growth in a Time of Debt’ as an example of the logical-positivist science

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

On informativeness of Granger-causality tests

Celem artykułu jest wykazanie na podstawie przeglądu badań, że zastosowanie testów Granger-przyczynowości nie dostarcza wiarygodnych informacji o zależności pomiędzy badanymi szeregami czasowymi, jeżeli nie dysponuje się wiedzą teoretyczną na ich temat. Dotychczasowa krytyka testowania przyczynowości w sensie Grangera skupiała się przede wszystkim na wskazywaniu różnic pomiędzy tradycyjnie rozumianą przyczynowością a definicją zaproponowaną przez Grangera. Autor wykazuje, że analizowana definicja przyczynowości ma uzasadnienie filozoficzne, jednak stosowanie testów Granger-przyczynowości prowadzi do błędnych wniosków, co jest wynikiem m.in.: nieliniowości szeregów czasowych, zbyt rzadkiego próbkowania szeregów czasowych, skointegrowania zmiennych, zdeterminowania szeregów czasowych przez trzecią zmienną, istnienia zależności nieliniowej oraz racjonalnych oczekiwań podmiotów ekonomicznych. Analiza opisanych w literaturze przypadków zawodności wyników testów przyczynowości w sensie Grangera pozwala stwierdzić, że wyciągnięcie wniosków o istnieniu i kierunku zależności przyczynowej na podstawie testu Granger-przyczynowości jest możliwe tylko wtedy, gdy posiada się wiedzę o mechanizmie łączącym dwa szeregi czasowe.The purpose of this paper is to show that the application of Granger-causality tests is not informative unless one possesses additional theoretical knowledge. Previous criticism on Granger-causality testing pointed out mostly the differences between the common sense understanding of causality and Granger’s definition. The author demonstrates that Granger’s definition of causality is philosophically justified. However, the use of its tests is misleading due to: data non-linearity, too low sampling rate, time series cointegration, thirdvariable fallacy, non-linear causal dependency, and the rational expectations of economic agents. 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Sposoby poznania relacji przyczynowych w ekonomii. Argument na rzecz sceptycyzmu

Współczesna ekonomia wykorzystuje trzy sposoby poznania zależności przyczynowych. W ograniczonym (ze względu na trudności epistemologiczne w izolowaniu oraz koszty) stopniu wykorzystuje się metodę doświadczalną. Z powodu występujących trudności, ekonomiści posługują się teoretycznymi, apriorycznymi modelami, które odpowiadają eksperymentom myślowym. Rozwój metod ekonometrycznych doprowadził do stworzenia testów przyczynowości. Wyniki uzyskane za pomocą każdej z metod są niepewne. Przegląd literatury z zakresu filozofii ekonomii oraz analiza niedawnych badań ekonomicznych prowadzi do wniosku, iż należy zachować pewną dozę sceptycyzmu do wniosków o przyczynowości. W celu uprawdopodobnienia wiedzy o przyczynie i skutku proponuje się wykorzystanie trzech metod: doświadczeń do określenia aksjomatów budowanych teorii, dedukcji relacji przyczynowych na podstawie modeli z zastosowaniem redukcji ontologicznej oraz ekonometrycznych testów przyczynowości do weryfikacji wyciągniętych wniosków.There are three epistemic ways of discovering causality in the contemporary economics. Experiments are applied in a limited number of cases due to the problem of isolation and their costs. Because of these obstacles, economists use theoretical models (i. e. thought experiments). The development of econometrics led to construction of causality-testing methods. Findings based on any of these methods are uncertain. The literature review and case studies of recent economic researches show that scepticism is necessary in causal analysis of an economic phenomenon.. In order to make knowledge on what is a cause and what is an effect more justified, one should apply all three methods. Experiments should be used to discover good axioms for theories. Causes and effects should be deduced from theories and models. Then, hypotheses are to be econometrically tested

Conflicting results and statistical malleability: embracing pluralism of empirical results

Conflicting results undermine making inferences from the empirical literature. So far, the replication crisis is mainly seen as resulting from honest errors and questionable research practices such as p-hacking or the base-rate fallacy. We discuss the malleability (researcher degrees of freedom) of quantitative research and argue that conflicting results can emerge from two studies using different but plausible designs (e.g., eligibility criteria, operationalization of concepts, outcome measures) and statistical methods. We also explore how the choices regarding study design and statistical techniques bias results in a way that makes them more or less relevant for a given policy or clinical question