Originally posted by: LegendKiller
Originally posted by: Dari
Originally posted by: LegendKiller
Originally posted by: Dari
To promote effectively the goals of maximum employment, stable prices, and moderate long-term interest rates
Those are the goals of the Federal Reserve. They are contradictory, yes, but nobody says anything. In my opinion, the part about maximum employment should be the redoubt of the Treasury or elected government while the last two should be the goals of the Feds. That way, we can have the two groups promoting policies that may balance each other out. But for the Feds to worry about unemployment would make it a victim of short-term thinking, when it should really be thinking about prices. The European Central Bank is far more concerned about inflation than employment and it has done a much better job than the Feds in that department. But if we were to concentrate all the Feds resources on battling inflation and take away many of its current powers, leaving regulation to another government body, we could have multi-headed system that would complement and balance each other out. Since there would be no need for discretionary thinking, all this could be done via an algorithm using stochastic and regression processes to determine what the interest rate should be.
Inflation in Europe is about on par with the US, but unemployment is much higher. So your first premise is wrong.
Who programs the computer with what variables? I think you're missing the very first premise of building models, GIGO.
Unemployment is higher because of rigid European laws, not because of monetary policy.
As for the variables, you throw in as many variables as possible and do stepwise regression on the data with an alpha of 1% in and 5% out and see which variables are the most pertinent. This is all basic statistics that economists ignore because they like to focus on simple equations. Once you figure out the correlation between the variables you can setup a nice equation and do a simulation to see what happens. If the results are competent, then you have yourself a winner.
Do you even know the complexity of measuring and regressing a whole fricking economy, but then not having all variables?
I love when armchair generals attempt to understand economics and finance from outside the universe, claiming all the while it's as simple as a regression.
There isn't one model pre 2007 that would have thought that subprime securitization would cause the problems they have. The Fed, nor a model, would have been able to adjust for the global flood of capital into the US debt markets, more than $20TR in total, which drove down long-term interest rates far outside the control of the Fed. That variable alone accounted for the majority of the issues we now face, a variable that has never been accounted for before.
It only takes one independent variable outside of the current IV's in a model to blow the whole model. Look at the rating agencies. They have collected data on over 100Tr of securitization debt over the last 40 years, yet blew it with CDO's because their models didn't include the whole gamut of exotic mortgages.
What's even funnier is that people try to extrapolate this situation to other forms of securitization debt, such as auto and credit cards. Yet they fail to realize that those models work quite well, even under severe stressed situations.
The entire economy cannot be encapsulated in a model because you are attempting to gauge human behavior, which is far outside quantifiable terms. Consumer, corporate, worldwide investor sentiment ebbs and flows on a moments notice and are impossible to predict.
If models worked at encapsulating all human behavior and economic variables, then a hedge fund would have created it and would be rolling in so much money as to make all other "rich" people seem like paupers. As somebody who has worked with some of the most profitable hedge funds, I know that they can't even get close to this.
The last time people thought a model could predict the correct market movements it required one of the biggest financial bailouts in history, LTCM, which was created by a few of the smartest people that finance has ever known. One of the other largest problems models caused, from program trades, was 1987.
The first thing you learn about models when you go into finance is that they can and do fail quite often. Human intuition is far more accurate at gaugeing changing human behavior.
Models have one fatal flaw, they run on data that's already stale from the market's perspective, because they cannot predict the next second's human's behavior.
I can point out dozens of econometric models that have failed miserably in the last year.