Tag Archives: Statistics & Econometrics

Econometrics and the problem of unjustified assumptions There seems to be a pervasive human aversion to uncertainty, and one way to reduce feelings of uncertainty is to invest faith in deduction as a sufficient guide to truth. Unfortunately, such faith is as logically unjustified as any religious creed, since a deduction produces certainty about the real world only when its assumptions about the real world are certain … Unfortunately, assumption uncertainty...

In most econometrics textbooks the authors give an interpretation of a linear regression such as Y = a + bX, saying that a one-unit increase in X (years of education) will cause a b unit increase in Y (wages). Dealing with time-series regressions this may well be OK. The problem is that this ‘dynamic’ interpretation of b is standardly also given as the ‘explanation’ of the slope coefficient for cross-sectional data. But in that case, the only increase that can generally come...

Although most social scientists can recite the formal definitions of the various regression assumptions, many have little appreciation of the substantive meanings of these assumptions. And unless the meanings of these assumptions are understood, regression analysis almost inevitably will be a rigid exercise in which a handful of independent variables are cavalierly inserted into a standard linear additive regression and coefficients are estimated. Although such an exercise may...

On the applicability of statistics in social sciences Eminent statistician David Salsburg is rightfully very critical of the way social scientists — including economists and econometricians — uncritically and without arguments have come to simply assume that they can apply probability distributions from statistical theory on their own area of research: We assume there is an abstract space of elementary things called ‘events’ … If a measure on the abstract...

Because I was there when the economics department of my university got an IBM 360, I was very much caught up in the excitement of combining powerful computers with economic research. Unfortunately, I lost interest in econometrics almost as soon as I understood how it was done. My thinking went through four stages: 1.Holy shit! Do you see what you can do with a computer’s help. 2.Learning computer modeling puts you in a small class where only other members of the caste can...

Observational data and causal inference Distinguished Professor of social psychology Richard E. Nisbett takes on the idea of intelligence and IQ testing in his Intelligence and How to Get It (Norton 2011). He also has some interesting thoughts on multiple-regression analysis and writes: Researchers often determine the individual’s contemporary IQ or IQ earlier in life, socioeconomic status of the family of origin, living circumstances when the individual...

The biggest problem in science There’s a huge debate going on in social science right now. The question is simple, and strikes near the heart of all research: What counts as solid evidence? … Prominent statisticians, psychologists, economists, sociologists, political scientists, biomedical researchers, and others … argue that results should only be deemed “statistically significant” if they pass a higher threshold. “We propose a change to P< 0.005,” the...

Improbability and the law of truly large numbers  [embedded content]

The validity of statistical induction In my judgment, the practical usefulness of those modes of inference, here termed Universal and Statistical Induction, on the validity of which the boasted knowledge of modern science depends, can only exist—and I do not now pause to inquire again whether such an argument must be circular—if the universe of phenomena does in fact present those peculiar characteristics of atomism and limited variety which appear more and...

Two must-read statistics books Mathematical statistician David Freedman‘s Statistical Models and Causal Inference (Cambridge University Press, 2010)  and Statistical Models: Theory and Practice (Cambridge University Press, 2009) are marvellous books. They ought to be mandatory reading for every serious social scientist — including economists and econometricians — who doesn’t want to succumb to ad hoc assumptions and unsupported statistical conclusions! How...