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When should we believe the unconfoundedness assumption?

from Lars Syll

Economics may be an informative tool for research. But if its practitioners do not investigate and make an effort of providing a justification for the credibility of the assumptions on which they erect their building, it will not fulfil its task. There is a gap between its aspirations and its accomplishments, and without more supportive evidence to substantiate its claims, critics — like yours truly — will continue to consider its ultimate arguments as a mixture of rather unhelpful metaphors and metaphysics.

In mainstream economics, there is an excessive focus on formal modelling and statistics. The models and the statistical (econometric) machinery build on — often hidden and non-argued for — assumptions that are unsupported by data and whose veracity is highly uncertain.

Econometrics fails miserably over and over again. One reason is that the unconfoundedness assumption does not hold. Another important reason why it does is that the error term in the regression models used is thought of as representing the effect of the variables that were omitted from the models. The error term is somehow thought to be a ‘cover-all’ term representing omitted content in the model and necessary to include to ‘save’ the assumed deterministic relation between the other random variables included in the model. Error terms are usually assumed to be orthogonal (uncorrelated) to the explanatory variables. But since they are unobservable, they are also impossible to empirically test. And without justification of the orthogonality assumption, there is, as a rule, nothing to ensure identifiability: 

Paul-Romer-727x727With enough math, an author can be confident that most readers will never figure out where a FWUTV (facts with unknown truth value) is buried. A discussant or referee cannot say that an identification assumption is not credible if they cannot figure out what it is and are too embarrassed to ask.

Distributional assumptions about error terms are a good place to bury things because hardly anyone pays attention to them. Moreover, if a critic does see that this is the identifying assumption, how can she win an argument about the true expected value the level of aether? If the author can make up an imaginary variable, “because I say so” seems like a pretty convincing answer to any question about its properties.

Paul Romer

  1. Prof Dr James Beckman, Germany
    September 29, 2018 at 9:20 am

    Lars, many of us go to Occam’s razor or Einstein’s alleged, “Everything should be as simple as it can be, but not simpler.” https://quoteinvestigator.com/2011/05/13/einstein-simple/.)
    Yet we must also have clarity & (even) realism. One of every discipline’s problems is that it ALWAYS has poorly defined concepts. (I have yet to see any explanation of quantum theory that provides much beyond some mathematically-expressed conditions.. “Action at a distance” is hardly more than a statement of general process–“how” something happens.) Economics is not an experimental science, so every event–say a boom & bust–is unique due to the specific processes under which some products are produced, sold & the overall activity financed. This is a specific limitation, unlike pharmaceutical trials.
    So non-experimental disciplines dealing with humans, like economics, political science, sociology & anthropology have a special burden. What I am really saying is that more scientists–which we must be– need better to poke their heads into the data they are studying & be less enamored of the numbers produced by inaccurate equations. Many disciplines are guilty of this, so at least we can share some humility, it seems to me. Thanks for reminding us!

    • September 30, 2018 at 11:38 pm

      It is an old of Economists and old habits die hard!
      A good scientist explains complicated phenamena simply and with humility. Even as a tool of research (presumably conducted to find some sort of better truth or authentic knowledge) Economics has failed miserably.
      Will they ever stop?! Personally, I doubt it. They cause nothing but further confusion. That is what they are best at. And even then, they will argue that all they did was to pose questions.

  2. October 1, 2018 at 11:38 am

    Lars, the other side of this issue is just as problematic. You want more supportive evidence to substantiate claims. But just piling one observation on top another observation ad infinitum only substantiates that the later observations agree with earlier observations. How many times must this be done before a critic such as yourself will say the observations in total reveal something important, something that helps in understanding what’s going on in one place or time or another? I don’t know the answer. Do you?

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