Modelling Italian Potential Output and the Output Gap

Abstract

The working paper series promotes the dissemination of economic research produced in the Department of the Treasury (DT) of the Italian Ministry of Economy and Finance (MEF) or presented by external economists on the occasion of seminars organized by MEF on topics of institutional interest to the DT, with the aim of stimulating comments and suggestions. The views expressed in the working papers are those of the authors and do not necessarily reflect those of the MEF and the DT.

Real and financial cycles: estimates using unobserved component models for the Italian economy

“…where y t is the N × 1 vector of observed variables, ε t is the N × 1 vector of measurement errors, α t is the m × 1 vector of state variables and η t is the corresponding m × 1 vector of innovations. The two innovation vectors are assumed to be Gaussian distributed and uncorrelated for all time periods, that is, E(ε t η s ) = 0 ∀t, s. 6 The initial value of the state vector is also assumed to be Gaussian α 1 ∼ N (a 1 , P 1 ) and uncorrelated ∀t with ε and η.…”

Adjusting the External Adjustment: Cyclical Factors and the Italian Current Account

“…Notice that the elasticity of imports to GDP typically tends to be higher than that to the domestic IAD (see Bussière et al, 2013). 15 The key exogenous variable is the output gap: to this end, for Italy we use the measure computed by Banca d'Italia as the average of estimates based on four different approaches: a Bayesian unobserved component method, a univariate time-varying autoregressive model, a production function approach and a structural VAR (Bassanetti et al, 2010).…”

Firm Characteristics and Potential Output: A Growth Accounting Approach

“…In this paper, we applied a growth accounting method to aggregate statistics from a very rich firm-level dataset for the period 2000-18. Our approach is similar to the production function methodology for potential output estimation traditionally used at the Bank of Italy and described in Bassanetti et al (2010). The aim of our work is to exploit the information available from a microdataset to shed light on the heterogeneity below the dynamics we observe for aggregate potential output.…”

“…The traditional methodologies used to estimate potential output are based on aggregate time series, mainly the national accounts. The most popular methods adopted by international institutions and central banks are either statistical filters or more complex approaches, such as those based on aggregate production functions, on semi-structural Bayesian unobserved component methods, as well as on dynamic factor or dynamic stochastic general equilibrium models (see for example Havik et al, 2014;De Masi, 1997;Alichi et al, 2019;Edge and Rudd, 2016;Anderton et al, 2014;Vetlov et al, 2011;Chalaux and Guillemette, 2019;Bassanetti et al, 2010;Busetti and Caivano, 2016;Burlon and D'Imperio, 2020).…”

“…4 In particular, we follow a growth accounting approach (Barro, 1999), where total factor productivity is estimated as a Solow residual from a Cobb-Douglas value added production function under the assumption of constant returns to scale, by using aggregate statistics retrieved from a very rich firm-level dataset in the time window between 2000 and 2018. The methodology is broadly similar to the production function approach to the potential output estimation used in several institutions, including the Bank of Italy (Bassanetti et al, 2010).…”