[From Bill Powers (2011.05.28.1207 MDT)]
Adam Matic 2011.05.28 0050 gmt+1 --
AM: Perhaps only more free time could be a common goal that everyone wants
to have more than before. Not that every single human really wants
more free time, but that might be a useful simplification. If there is
a fixed number of needs an agent has, and in the beginning he can't
even correct all the errors, then "more free time" might be an
ultimate goal.
It could be achieved by reorganizing the amounts off goods to be
produced, bought or sold.
So, in the beginning, an agent produces what he needs, but when he
consumes it, there is not enough to fulfill the need. There is also an
error in "free time". Reorganization begins and some goods are
produced in excess and offered in the market, some are bought from the
market
COMMENT: BP: The moderator was trying to question the assumption of some special characteristic of all people to be incorporated into a model of the economy. Instead of assuming that everyone always wants more of anything he has or is getting, a better approach is to define a variable or a variable parameter of behavior, and construct the model so that if the variable doesn't have the correct value, the model will behave differently from the real population. If no value will work, the model is wrong. That way your model qualifies as a falsifiable hypothesis.
This is the reason for the "How many people ..." kind of question -- it was intended as a reminder that people are not all alike in their perceptions or their preferences. Some people may be "rational actors," while not everyone is. So if you want to use that premise, first you have to admit the possibility that it may be incorrect, and then you have to set up the model to catch the mistake if the premise turns out to be false. You have to see what difference it makes to the model's behavior if everyone is a rational actor, most people are, most people are not, or nobody is. If the model's behavior depends entirely on the first possibility, and the possibility is false, then you will find yourself making up good reasons why it's still true. There's a lot of that sort of model-rescuing excuse-making going around.
People do not generate behavior; they control. Their actions -- their behaviors -- are a result of both internal and external factors: reference signals and perceptual functions on the inside, and disturbances and feedback functions on the outside. What is constant or repeatable is not behavior, but the controlled results of behavior. Even the desired result can change when a system at a higher level experiences a disturbance. Any model that assumes a fixed behavior pattern or fixed preferences, therefore, is likely to predict poorly, and more poorly still if there is no provision for changing the model's parameters to fit the real control processes when they change.
Final word of, one hopes, wisdom: when we make models we don't have to guess how they will behave, because we can run the model and see. I think it's best simply to make the components of the model itself as realistic as possible and not assume that one can guess what will happen when they are assembled and set into motion. We don't make models to prove a theory is right; we make them first to find out how they will actually work, then to test whether they work right, and finally to see if the theory behind them is right. The more vulnerable we make the model to failure if it's wrong, the more confident in it we can be when we can't find anything wrong with it.
Best,
Bill P.