Foundations for modern social sciences were laid in the early twentieth century, and were strongly influenced by logical positivism. The central idea of positivism is that science is true and valid because it deals (principally) with observables, while religion is false and invalid because it deals (principally) with unobservables. For a detailed discussion, see “Logical Positivism … Continue reading »
The problem at the heart of modern economics is buried in the logical positivist methodological foundations created in the early twentieth century by Lionel Robbins. Substantive debates over the content actually strengthen the illusion of validity of these methods, and hence are counterproductive. As Solow said about Sargent and Lucas, you do not debate cavalry … Continue reading »
Below, I will reproduce extracts from the opening Chapter, titled as above, of Karl Polanyi’s The Great Transformation: the Political and Economic Origins of Our Times . This is essential background in conjunction with the history of Central Banking which was covered in Lecture 13 of Advanced Macro II . The central concept underlying the course is that of “Entanglement (Lecture 18B) “ – … Continue reading »
Polanyi offers a deep historical study of how European societies based on traditional values of cooperation and social responsibility were transformed into modern secular societies. In Polanyi’s terminology, social relations became embedded within the market, creating a market society driven by the imperative of commercialization, which makes money the measure of all things, including human … Continue reading »
Ever since the spectacular failure of modern economic theory became obvious to all in the Global Financial Crisis, the search for alternative ways of organizing our economic affairs has intensified. The vast majority of alternatives under consideration offer minor tweaks and patches, remaining within the methodological framework of neoclassical economics. In contrast, Polanyi offers a … Continue reading »
Case 4: Drug as Mediator — The causal sequence in map #8 could be reversed. It may be that Blood Pressure governs whether or not the drug is taken, and has no direct effect on recovery. Causal Map # 9 Suppose the drug is extremely helpful. Recovery rate in treatment groups (with the drug) is … Continue reading »
Fifth of sequence of 6 pedagogical posts on the Simpson’s Paradox. Our last example considers the classical case of testing the effectiveness of a drug as a treatment for a disease. It is standard to divide the population into two groups, and compare recovery rates. The group which does not take the drug is called … Continue reading »
Fourth of sequence of 6 pedagogical posts on the Simpson’s Paradox. It is standard practice in statistical analysis to separate the role of the field expert from the statistical consultant. The field expert has deep knowledge of the processes which generate the numbers, while the statistician knows about the numbers, and has superficial knowledge of … Continue reading »
Third of sequence of 6 pedagogical posts on the Simpson’s Paradox. As Hume realized a long time ago, observations cannot reveal the underlying causes. Studying alternative hidden causal structures for the same data set could radically change the interpretations discussed in previous sections. Understanding data REQUIRES understanding causal structures which generate the data and these … Continue reading »
This is the second in a series of posts which discusses the causality and Simpson’s Paradox. For the 1st part see Causality, Confounding, and Simpson’s Paradox 1 where, there is not one (gender) but two causal factors (gender and difficulty level per department) that influence the admission rates. Being female is a positive influencer in … Continue reading »