Will the Libyan war be successful? Let’s use math to find out!

We use forecasting models to predict everything from the climate to the stock market, so why not our current war?  We’ll talk through some issues and touch on five principles of forecasting along the way.

First, why do we need a forecasting model at all?  That’s our first principle – any model is better than no model.  People are emotional and ignore data that doesn’t fit their preconceptions – they’re very bad at predicting what’s going to happen.  No matter how bad your model is, it’s going to be better than just going with your gut.

So how complicated should our model be?  That brings us to our second principle – more complicated models are not much better.  Deep in the bowels of the Pentagon the Libyan situation is doubtless being war-gamed in all sorts of ways, with models of great complexity.  But much of this detail will be a waste of time in predicting the outcome.  It doesn’t really matter exactly what Gadaffi’s 53rd Armor Division does – if you want to know how this war will turn out, look at what’s happened with similar countries and similar armies.  In fact, the dirty little secret of statistical modeling is that even exponential smoothing does a pretty good job at forecasting, so if you just guessed this war would go like a weighted average of other recent wars, you’d beat most of the experts.  Exponential smoothing doesn’t get you too much respect, though, so we might try linear or logistic regression.

OK, so if we don’t pay too much attention to modeling, what should we be focusing on?  That’s our third principle – it’s all about the data.  To predict how this war will turn out, we’ll need to look at other U.S. wars.  But how far back?  Vietnam, like the left says?  WWII, like the right wants?  The Spanish-American War?  The Barbary Pirates?  And should we include the wars of other countries?  Libya with Chad?  The U.S.S.R with Afghanistan?  What variables are going to be important?  I’m guessing population size, military technology, terrain, for starters.  Some of these will be available easily, some we’ll have to manually code (well, I suppose you could develop a numerical measure of Afghanistan’s mountain-ness, but would it be worth it?)  It’s all going to be a mess, and we’re going to have to make decisions between contradictory sources.  And what are we trying to predict?  Length of war?  Casualties?  Cost?  Whether it’s a “success”?  How do we measure any of those?  It’s all about the data.

With so many possible variables, we’re going to need to pay attention to our fourth principle – beware of overfitting.  For example, we might have a country-specific variable in our model.  This would look good for the U.S., as Libya seems to have lost every war it was involved in, from the Barbary Pirates on.  But is that a good enough basis for our model?  Maybe so, as Afghanistan seems to have defeated every invader from Alexander on.  Still, worth paying close attention to.

And our final principle – models are only useful if they’re used.  I would be happy to hear that the President has some Excel spreadsheet showing him the likely results of invading every country from Azerbaijan to Zimbabwe.  But I’m guessing there’s nothing in-between the Pentagon’s insanely complicated wargames and the uninformed opinions of politicos.  Don’t be disheartened, though – you can still use your model to try and cut through the propaganda and plain old wishful thinking you’ll hear from all sides.

What about my prediction?  I’m going to go with an average of the last 6 big wars  “success” – determined and selected in a completely arbitrary way – the 2nd Iraq war (50%), Afghanistan (40%), Serbia (80%), Haiti (90%), Somalia (10%), and the 1st Iraq war (95%).  Gives us 61% – not a debacle like Somalia, less of a mess than Afghanistan, but not one of the greatest success stories, either.  It’s a stupid model and stupid data, because nobody’s paying me for it, but, following our first principle, it’s better than nothing.

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2 Responses to “Will the Libyan war be successful? Let’s use math to find out!”

  1. Scott Locklin Says:

    Define “success.”

    Did I ever show you my SBIR proposal for running psy-ops on the Iraqi population? It was pretty fun: I was in full Hari Seldon form. At the end of the day the Army went with a regression model though. Probably because the dude’s brother in law was the grant reviewer, I’m guessing: it was a pretty weak regression model.

    • erehweb Says:

      I’ve left success vague here just to illustrate the idea. If you wanted, you could come up with some objective metric like $ spent, US deaths, length of engagement, popularity as measured by polls, or whether a friendly regime is still in place after x years.

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