In your model of the decision you only have two actors, the prime minister and his opponents. In the real world you have more actors. In the real world there are more than two different actors. Within the party of the prime minister there's somebody else who's going to take power of the party when the prime minister stepped down.
That other person might have made a deal with the prime minister that he succeeds the prime minister if he in return steps down within three months.
Different opposition groups might compete with each other over being the central opposition group. There are foreign countries that have interests.
Holding relections takes some time and if a prime minister stays 3 months in office till you have relections, what's the problem? You don't want months without a prime minister.
The question is not hypothetical: I was faced with precisely this problem in December, and got it wrong.
You can't decide based on one data point that you got it wrong.
It's not clear to me what direction of update your additional model considerations call for.
Holding relections takes some time
Sorry, I was unclear. The choices are "Call new election in December" or "Call new election in March". The PM does stay in office until the election is over, but the question is when it starts.
You can't decide based on one data point that you got it wrong.
Well, at any rate I updated in the direction opposite of what actually happened. You are of course correct that this is not necessarily wrong, but it should at least tickle your oops-detector.
Suppose you want to assign a probability that a government will fall (ie the Prime Minister resigns) before the end of the year. Lacking any particular information - I haven't even told you which government it is - you say "Obviously, it's 50% - either it happens or not" (or perhaps "Oh, say, 10%, governments can usually rely on lasting a year at least"), put that prediction into your registry, and go on with your life. Then, on December 1st, you hear that the Prime Minister in question has promised to resign and call an election in March of next year. How should this affect your probability that he will resign before the end of this year?
I see several arguments:
1. Having gotten this public commitment out of him, his opponents have no particular reason to push his government further. It should become more stable for the finite time it has left. My probability of a resignation in December should go down.
2. His opponents were able to extract such a promise; it follows that he cannot be quite confident in his ability to survive a vote of no confidence. Such a signal of weakness might easily lead to a "blood-in-the-water" effect whereby his opponents become more aggressive and go for the immediate kill. His government will surely fall before this attempted compromise date; my probability should go up.
3. The March date wasn't chosen at random. Presumably there is something the PM thinks he can get accomplished if he retains his position until March, but not if he resigns right away. So, presumably, his opponents will be all the more eager for him to resign before he gets it done, whatever it is; they will put more resources into toppling him. Again, my probability should go up.
The question is not hypothetical: I was faced with precisely this problem in December, and got it wrong. I'd like to see how others think about it.