Economic models are wrong because https://secure.wikimedia.org/wikipedia/en/wiki/Economic_mobi... and https://secure.wikimedia.org/wikipedia/en/wiki/Social_mobili... are mutually exclusive
Why Economic Models are Always Wrong
21–30 of 61 posts
Re: Why Economic Models are Always Wrong
#22From scientist to scientist a little secret: All models are always wrong! If the model would be correct it would be as detailed as reality and thus also as useless.
Re: Why Economic Models are Always Wrong
#23I think what the author is describing is simple overfitting. http://en.wikipedia.org/wiki/Overfitting It is quite a newbie mistake for a scientist to be surprised by it. It affects every kind of modelling. I thought maybe this article would talk about why economic models are worst than other kinds of models. There are issues that arise when applying scientific models to the economy caused by the fact that when even g…
Alternatively, it may be simple information theory: A model that takes in 100 bits of specification simply can not correctly describe a process that has 10,000 bit's worth of degrees of freedom. And that's before we talk about iteration over time, and before we get to the final killer you mention, which is when the models are ruined by their own application to the domain. I think radical underspecification is much mo…
Here's the thing: you're both right. It's both radically underspecified and overfitted. The information-theoretic argument demonstrate that a model cannot exactly match the reality unless it's as complex as the reality.
This article speaks of the separate problem that economic models are not evaluated in any sort of experiments, and thus are prone to overfitting. This makes them unlikely to even approximate well.
Consider a basic multilayer perceptron-style neural network. Overfitting is a well-understood problem in training an MLP. We work around it by training on a part of the data, and then measuring its accuracy on another part -- much as Carter did in his analysis. If the accuracy is poor, something is adjusted: the size of the hidden layer can be increased, the training set expanded, the duration of the training increased or decreased, or the MLP model discarded entirely.
If increase of the training set or reduction of the duration improves accuracy against the test set, this means we had an overfitting problem.
Re: Why Economic Models are Always Wrong
#24This is perhaps naive, but why are the parameters to a model not considered as part of the model as a whole?
In the end it's a matter of convention. If you think about Newton's "model" of gravity, for example, you'll notice that the formula that describes the gravitational force can be plausibly explained based on intuition. However, the gravitational constant (i.e. the parameter) has no explanation. It just is.
Of course, a great deal of physics is ultimately about trying to make the parameters go away by explaining them using more fundamental models. But at any given level of abstraction, you'll have parts of the model that are reasoned intuitively, and parts of the model that just are the way they are, for no good particular reason other than that's what you happen to get by measuring.
Re: Why Economic Models are Always Wrong
#25This article is avoiding terminology, data and any specifics on the problem that it renders it useless. You might be fooled it says something useful if you don't know what a 'model' means in any science. So what is the point of the article? The author is trying to sell you his book where he most probably makes people who don't know anything about economics feel good or push an ideological agenda.
It's not so much useless, it's just far more general than the author probably intends.
All his arguments apply equally well to any scientific models which require fitting, in geophysics (as he acknowledges), atmosphere/ocean science, climate modelling, most of biology, ecology, etc.
Why he singled out economics is beyond me.
Re: Why Economic Models are Always Wrong
#26A "scientist" finds by cross-validation that his model is over fitting the data. Luckily it wasn't published by a reputable source of science journalism.
http://en.wikipedia.org/wiki/Cross-validation_(statistics)
Also who the heck is Wilmott? He just pops up in the last paragraph with no introduction.
Re: Why Economic Models are Always Wrong
#27Actually, even correctly parametrized, any predictive model will suffer from the paradox of the oracle : if you have a "oracle" capable of anticipating the decision of an actor, and that this actor knows about the prediction, this actor can make the prediction false.
In economy, some actors have an interest in faking the prediction, even if it is costly for them : it is often valuable to be unpredictable.
Re: Why Economic Models are Always Wrong
#28Can you really compare Economic models to Physics models without discussing the simplifications necessary to create an Economic model?
Assume a spherical cow...
Re: Why Economic Models are Always Wrong
#29I think that with economic models used for trading there is also another big problem: Their application changes the model itself. So, even if you had a perfect model for the market without you applying your model, as soon as you start applying it, the market changes... and this is also true for all the other quants who do the same with their models. IMHO, it was much better when most stock market decisions were mostl…
> So, even if you had a perfect model for the market without you applying your model Actually, most trader's models do take market impact into account. If you had a perfect model for the market, I'm pretty sure that you (as a participant) would be included. In fact, your own actions are the easiest part of the model to get right, because you control them entirely.
Ok, but you would need to take into account the interaction with other traders' models that are put into play all the time...
Re: Why Economic Models are Always Wrong
#30I think that with economic models used for trading there is also another big problem: Their application changes the model itself. So, even if you had a perfect model for the market without you applying your model, as soon as you start applying it, the market changes... and this is also true for all the other quants who do the same with their models. IMHO, it was much better when most stock market decisions were mostl…
'it was much better when most stock market decisions were mostly based on "fundamentals"' I don't recall such a period. Is there a particular interval you're thinking of?
I'm actually not thinking about a specific period, I was just referring (maybe naively) to the time before computer assisted analysis became so widespread (before the eighties, I guess).