Does risk matter for Monetary policy? An evidence from small open economy model

Today, central banks use linearization techniques to solve their workhorse macroeconomic models. Unfortunately, linearization neglects the role of risk in economic decisions with implies, that households and firms in these models behave as if there were no uncertainty about the future. Linearized model hence abstracts from precautionary savings, risk premia and other results of “self-insurance” of economic agents. This thesis presents a study that explores, how the omission of these features in a model solution can distort monetary policy guidance provided by benchmark New Keynesian small open economy DSGE model calibrated to match the Czech macroeconomic data. Evaluation of impulse response functions shows nontrivial differences in short-term dynamics of crucial macroeconomic variables including policy rate. However, this result is contingent on the Calvo pricing mechanism, and alternative pricing assumption may change this outcome up to some degree. Loss function-based experiment indicates that inclusion of risk and other higher order terms leads to changes in optimal policy rule coefficients. Specifically, these results show, that due to the usage of linearized model, monetary policy authority can systematically underweight output gap in its reaction function and overstates the optimal value of interest rate smoothing parameter by a factor of 3. This second result is materially more robust to alternative pricing mechanism.