Abstract
This paper addresses three questions. Why do Central Banks change targeted interest rates so seldomly? Can we model the weekly behavior of a targeted interest rate? What are the driving forces behind rate changes? This paper takes the point of view that Central Banks face a fixed cost when adjusting a targeted interest rate and therefore smoothe it by using a discrete policy rule. When modeling interest rate behavior this discrete nature is taken into account by applying a grouped data model to a Swedish data set. Changes in unemployment, inflation, retail sales, industrial production, money growth and U.S. and German interest - and exchange rates are shown to determine Swedish repo rate changes. Probabilities of the target rate being raised, lowered or kept constant are computed. The model has a prediction rate of 88% versus 78% for the best naive estimator.