Quarterly econometric model
The Bank of Italy's quarterly econometric model, developed in the first half of the 1980s, describes the interactions between the most important macroeconomic aggregates of the Italian economy. It is made up of about 800 equations, of which nearly 100 are stochastic, with a broad specification of the various economic sectors, including the public sector.
The mechanisms that govern the evolution of the main variables are Keynesian in the short term, in which economic activity is influenced above all by the evolution of aggregate demand and there are rigidities in the adjustment of prices and wages; in the long term, as in the neoclassical model, economic growth is the result of investment, productivity and demographic dynamics.
The quarterly model is used for forecasting and economic policy analysis.
Dynamic stochastic general equilibrium (DSGE) models
Dynamic stochastic general equilibrium (DSGE) models describe the movements of the main macroeconomic aggregates as the result of the optimizing choices of households and firms, which also depend on their expectations. Combining rigorous theoretical foundations of behavioural equations (microfoundations) with the estimate (or calibration) of the structural parameters, DSGE models make it possible to replicate the movements of the main macroeconomic variables. In addition, the identification of the structural parameters - which describe the individual preferences and the technological and institutional constraints - allows the models to be used for the analysis of economic policy without running up against the Lucas critique.
The DSGE models of the New Keynesian type developed by the Bank with reference to Italy and the euro area are used for forecasting, the construction of counterfactual scenarios and economic policy analysis.
Models for the short-term forecasting of economic activity
The prompt identification of turning points in the movements of the main macroeconomic variables is crucial for guiding economic policy decisions. The release of fundamental indicators, such as industrial production and GDP and its components, nonetheless takes place with a certain delay with respect to the reference period. Following the progress in the econometric literature, the Bank has therefore developed several short-term forecasting models based on different methodological approaches. In particular, the bridge models have been flanked by other types, including models with Bayesian factors and Mixed Data Sampling (MIDAS).
The short-term forecasts are prepared with the help of these instruments for the whole of the euro area and the major countries, with special reference to Italy.
