Forecasting monthly industrial production in real-time: from single equations to factor-based models

The aim of this paper is to analyze the performance of alternative forecasting methods to predict the index of industrial production in Italy from 1 to 3 months ahead. We use twelve different models, from simple ARIMA to dynamic factor models exploiting the timely information of up to 110 short-term indicators, both qualitative and quantitative. This allows to assess the relevance for the forecasting practice of alternative combinations of types of data (real-time and latest available), estimation methods and periods. Out-of-sample predictive ability tests stress the relevance of more indicators in disaggregate models over sample periods covering a complete business cycle (about 7 years in Italy). Our findings downgrade the emphasis on both the estimation method and data revision issues. In line with the classical “average puzzle”, the use of simple averages of alternative forecasts often improves the predictive ability of their single components, mainly over short horizons. Finally, selected indicators and factor-based models always perform significantly better than ARIMA models, suggesting that the short-run indicator signal always dominates the noise component. On this regard, selected indicators models can further increase the amount of signal extracted to improve up to 30–40% the short-run predictive ability of factor-based models and to forecast-encompass them.     

Sectoral shifts, diversification and regional unemployment: evidence from local labour systems in Italy

Using Local Labour Systems (LLSs) data, this work aims at assessing the effects of sectoral shifts and industry specialization patterns on regional unemployment in Italy over the years 2004–2008. Italy represents an interesting case study because of the high degree of spatial heterogeneity in local labour market performance and the well-known North–South divide. Furthermore, the presence of strongly specialized LLSs (Industrial Districts, IDs) allows us to test whether IDs perform better than highly diversified urban areas thanks to the effect of agglomeration economies, or viceversa. Building on a semiparametric spatial auto-regressive framework, our empirical investigation documents that sectoral shifts and the degree of specialization exert a negative role on unemployment dynamics. By contrast, highly diversified areas turn out to be characterized by better labour market performances.     

Unemployment as an Adverse Trigger Event for Mortgage Default

The Journal of Real Estate Finance and Economics - There is limited evidence of the role of household-level adverse trigger events in driving mortgage default, and the evidence based on proxies,...     

Economics of externalities and public policy

In this paper we study a particular case of “multiple” externalities associated to the production of a good/activity, whose external effects can change from positive to negative depending on the level of output (intersecting externalities). To analyze their impact on the public policy we propose a very simple two-agent partial equilibrium model in the technological context of externalities. In a static framework, the centralized solution always implies an optimal policy, which may consist of taxation or subsidization depending on the individual optimum and on the technology parameters. In a dynamic model with local knowledge of the efficiency function and instantaneous output adjustments, such an optimal policy can be structurally stable or unstable. In the latter case, under small changes of the parameters the policy may switch from low taxation/subsidization to high taxation/subsidization or vice versa, or even jump discontinuously from taxation to subsidization or vice versa. Furthermore, the decentralized solution based upon “tradable rights” can be economically equivalent to the centralized solution in the form of taxation policy but the two solutions may be not politically equivalent.