World bank data prediction

Hello all,

Given an indicator, for example "School enrollment, primary (% gross)" of the United States.
We have a series of discrete data from 1980 to 2009, which is counted for every years.

We want to predict the data for the year 2010 so we need to find a relation between it
and the previous data.

The problem is that I don't know which rule it is subjected to.
# Of course, the rules are different from indicators to indicators.

It is unlikely that we can predict the data for the year 2010 by simple (linear or polynomial)
interpolation or extrapolation.

I don't think that the data is subjected to some probabilistic rule like Markov chains.

My guess is that the data may be subjected to some Auto-Regression Moving-Average Models (ARMA) rule
or some time series rule like GARCH.

Being said that, I also have no idea which is the right direction to go or it is a no-go.

Please give me some hints,

Best regards,

Nguyen Vu Hung

cf. http://groups.google.com/group/world-bank-api/browse_thread/thread/c3a9a38b9f014ba8