Assessing the Forecasting Performance of a Macroeconomic Model

This paper contains a description of a small quarterly forecasting model for the Finnish economy. We evaluate the forecasting properties of the model by means of stochastic simulation involving both the endogenous and exogenous variables of the model. The simulations allow us to identify and quantify the main sources of forecasting uncertainty. We are also able to assess the linearity of the model. Forecasting performance is also analyzed in a conventional way by means of dynamic simulation. The important issue in these simulations is the stability of the model: how simulated values depend on the estimation period and the ordering of time periods.

Introduction: This paper reports some basic results obtained with a small Finnish quarterly model developed at the Bank of Finland, where it is used mainly for short-term forecasting.The model is called the QMED (Quarterly Model of the Economics Department – of the Bank of Finland). We focus on the simulation properties of the model. First, we scrutinize the properties of the model by means of stochastic simulation, using the procedure suggested by Brown and Mariano (1981) with the actual residuals. For the sake of comparison, several simulations are also performed using Monte Carlo -generated data. The simulations concern both the overall sensitivity of the model and the sensitivity of the model in terms of exogenous variables. The purpose of these simulations is to assess the level of forecasting uncertainty: uncertainty stemming from both endogenous and exogenous variables. This analysis boils down to the computing of certain confidence intervals for a recent model forecast. The simulations also make it possible to examine the linearity of the model. This issue is crucial, for instance, in evaluating the values of various dynamic multipliers of the model.

Author: Juhana Hukkinen,Matti Viren

Source: Research Discussion Papers, Bank of Finland

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