Memorial University of Newfoundland, Canada
Probability as input or output of a social science model?
In this talk we attempt to first discuss why the separation of state and measurement in economics and finance may (or may not) have reason of existence. What can be a palatable meaning of a state function in economics and finance? Those questions revolve around a more general (and very important) issue: does the model inform the probability, or can probability be part of the model? As an example, say we want to investigate a certain phenomenon in economics. We build a model to come up with a probability value (which obviously must have relevance to the phenomenon studied). The model gives us a probability value, and probability itself does not explain anything. Rather the model does explain why the probability value is x or y. Can we argue for cases in economics or finance, where the probability formalism is an intricate part of the model? Finally, how much formalism (or little formalism) from physics does one need in economics or finance, to declare the whole ‘physics-social science’ endeavour defunct or not? Or is that question completely irrelevant?