This paper outlines several difficulties with testing economic theories, particularly that the theories may be vague, may relate to a decision interval different from the observation period and may need construction of a metric to convert a complicated testing situation to an easier one. We argue that it is better to use model selection procedures rather than formal hypothesis testing when asking the data to decide on model specification. This is because testing favors the null hypothesis, typically uses an arbitrary choice of significance level and researchers working with the same data could easily end up with different final models, which would make policy recommendations difficult.