Tag Archives: Statistics & Econometrics

Introduction to instrumental variables .[embedded content] Great presentation, but maybe Angrist  should also have pointed out the mistake many economists do when they use instrumental variables analysis and think that their basic identification assumption is empirically testable. It is not. And just swapping an assumption of residuals being uncorrelated with the independent variables with the assumption that the same residuals are uncorrelated with an...

Which causal inference method is the best one? .[embedded content]

Graphical causal models and collider bias Why would two independent variables suddenly become dependent when we condition on their common effect? To answer this question, we return again to the definition of conditioning as filtering by the value of the conditioning variable. When we condition on Z, we limit our comparisons to cases in which Z takes the same value. But remember that Z depends, for its value, on X and Y. So, when comparing cases where Z...

Econometrics — science based on whimsical assumptions It is often said that the error term in a regression equation represents the effect of the variables that were omitted from the equation. This is unsatisfactory … There is no easy way out of the difficulty. The conventional interpretation for error terms needs to be reconsidered. At a minimum, something like this would need to be said: The error term represents the combined effect of the omitted...

A tragedy of statistical theory Methodologists (including myself) can at times exhibit poor judgment about which of their new discoveries, distinctions, and methods are of practical importance, and which are charitably described as ‘academic’ … Weighing the costs and benefits of proposed formalizations is crucial for allocating scarce resources for research and teaching, and can depend heavily on the application … Much benefit can accrue from thinking a...

Econometrics — formal modelling that has failed miserably An ongoing concern is that excessive focus on formal modeling and statistics can lead to neglect of practical issues and to overconfidence in formal results … Analysis interpretation depends on contextual judgments about how reality is to be mapped onto the model, and how the formal analysis results are to be mapped back into reality. But overconfidence in formal outputs is only to be expected when...

The biggest problem in science In 2016, Vox sent out a survey to more than 200 scientists, asking, “If you could change one thing about how science works today, what would it be and why?” One of the clear themes in the responses: The institutions of science need to get better at rewarding failure. One young scientist told us, “I feel torn between asking questions that I know will lead to statistical significance and asking questions that matter.” The...

Statistical power (student stuff) .[embedded content]

Mainstream economists often hold the view that criticisms of econometrics are the conclusions of sadly misinformed and misguided people who dislike and do not understand much of it. This is a gross misapprehension. To be careful and cautious is not equivalent to dislike. The ordinary deductivist ‘textbook approach’ to econometrics views the modelling process as foremost an estimation problem since one (at least implicitly) assumes that the model provided by economic theory is...

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...