We who like to imagine ourselves responsible for the public’s knowledge of society despise description and indeed despise the methods that are generally used for quantitative description. Our social indicators are simply disaggregated variables, ready for input to causal analysis. The notions of complex combinatoric description, of typologies based on multiple variables — these fill the average sociologist with disgust. Our disgust is disingenuous, for ease of computing has...
Read More »Randomization-based vs. model-based inference
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Read More »The 20 Best Econometrics Blogs and Websites
The 20 Best Econometrics Blogs and Websites Yours truly, of course, feels truly honoured to find himself on the list of the world’s 20 Best Econometrics Blogs and Websites. 2. Bruno Rodrigues 7. Eran Raviv Blog Statistics and Econometrics 9. How the (Econometric) Sausage is Made 14. Lars P Syll Pålsson Syll received a PhD in economic history in 1991 and a PhD in economics in 1997, both at Lund University. He became an associate professor in economic history...
Read More »Causal inference — Fisher vs. Neyman (student stuff)
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Read More »Statistical assumptions as empirical commitments
Statistical assumptions as empirical commitments Real probability samples have two great benefits: (i) they allow unbiased extrapolation from the sample; (ii) with data internal to the sample, it is possible to estimate how much results are likely to change if another sample is taken. These benefits, of course, have a price: drawing probability samples is hard work. An investigator who assumes that a convenience sample is like a random sample seeks to...
Read More »Statistical reification — a deadly sin
Statistical reification — a deadly sin It would not be an exaggeration to say that many of us see academic statistics as “the sick man of science,” an alarming diagnosis in light of the central role it plays in science in general. The situation is maintained through specious and often byzantine rationales for destructive traditions, which is as expected from another human condition: Blindness to conceptual mistakes when correcting those would threaten the...
Read More »Better than Diff-in-Diff
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Read More »How to avoid pernicious fictional statistics
How to avoid pernicious fictional statistics Mathematics is a limited component of solutions to real-world problems, as it expresses only what is expected to be true if all our assumptions are correct, including implicit assumptions that are omnipresent and often incorrect. Statistical methods are rife with implicit assumptions whose violation can be life-threatening when results from them are used to set policy. Among them are that there is human...
Read More »Econometrics — a mixture of ‘metaphors, metaphysics, and a pinch of bluff’
Econometrics — a mixture of ‘metaphors, metaphysics, and a pinch of bluff’ This effort to create foundations for the probability approach in econometrics finally results in an inconsistent set of claims in its defence. First, there are vast amounts of experience which warrant a frequency interpretation. This is supported by repetitive discussions of experimental design, but the inability to experiment inspires an epistemological interpretation. Then...
Read More »Resisting the ‘statistical significance testing’ temptation
Resisting the ‘statistical significance testing’ temptation Imagine a dictator “game” in which a mixed-sex group of experimental subjects are used as first players who can decide which share of their initial endowment they give to a second player (one person acts as second player for the whole group). Additionally, assume that the experimental subjects are a convenience sample but not a random sample of a well-defined broader population. What kind of...
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