MoL-2021-23: Measuring What Exactly? A Critique of Causal Modelling in Atheoretical Econometrics

MoL-2021-23: Køhlert, Sebastian N. (2021) Measuring What Exactly? A Critique of Causal Modelling in Atheoretical Econometrics. [Report]

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An important part of econometrics is modelling causality. One way of getting causal predictions is to rely on data-driven models. This tradition is also known as atheoretical econometrics. Thus, atheoretical econometrics represents a range of methods that use models to infer causal relations directly from data. This is contrasted to theoretical econometrics that relies on economic theory. The main problem in getting causal knowledge from data in econometrics is that the investigator often faces large volumes of conflicting results from different models and that these models are highly sensitive, which conflict with one of the main goals of econometric modeling, obtaining stable outcomes. In this thesis, I strengthen the case against using atheoretical econometrics to infer causal relations from data, based on its inability to generate reliable evidence, due to its high sensitivity and lack of stable outcomes. I argue that we can understand econometrics models as measuring instruments not that different from thermometers and clocks, but what characterizes these measuring instruments are their high level of stability in outcomes. By relying on new literature in measurement theory, I show that the main problem in athereoteical econometrics occurs due to a misunderstanding of how measurement generates evidence and stable outcomes. In the end, I conclude that the evidence from Granger models is hardly strong enough to make any strong inferences based on it and argue that calibration may provide a way to bridge the atheoretical, and the theoretical view of econometrics.

Item Type: Report
Report Nr: MoL-2021-23
Series Name: Master of Logic Thesis (MoL) Series
Year: 2021
Subjects: Logic
Depositing User: Dr Marco Vervoort
Date Deposited: 21 Oct 2021 14:40
Last Modified: 21 Oct 2021 14:40

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