Massimiliano Serati

The literature on the evaluation of how the well-being is measured is full of different contributions, ranging from the subjective measure, to the batch of indicators approach, to the provision of synthetic objective indexes. However, up to date, there is still a lack of such measures on micro-territorial level, i.e. on town-by-town basis. This paper, thanks to the statistic platform 100% Lombardia, aims to develop such indexes, named WIT (Well-being Index for Towns), using a cluster analysis, a Bayesian dynamic factor model and a Panel-FAVARX.

Since its inception, EMU adequacy to be an Optimal Currency Area was questioned, and, along with it, the homogeneous transmission of the monetary impulses across the Eurozone. Adopting a Bayesian Time-Varying parameter FAVAR model that fixes the flaws present in the existing literature and exploits a sufficiently extended dataset, we provide an updated assessment of the transmission mechanism's functioning and of its symmetry along these first years of ECB operations. The empirical analysis shows that the occurrence of the two crises significantly altered the policy transmission, with the interest rate channel being the most affected. Policy-wise, our findings suggest that authorities must push towards a consistent innovation both on fiscal and monetary sides.

One of the most problematic aspects in the work of policy makers and practitioners is having efficient forecasting tools combining two seemingly incompatible features: ease of use and completeness of the information set underlying the forecasts. Econometric literature provides different answers to these needs: Dynamic Factor Models (DFMs) optimally exploit the information coming from large datasets; composite leading indexes represent an immediate and flexible tool to anticipate the future evolution of a phenomenon. Curiously, the recent DFM literature has either ignored the construction of leading indexes or has made unsatisfactory choices as regards the criteria for aggregating the index components and the identification of factors that feed the index. This paper fills the gap and proposes a multi-step procedure for building composite leading indexes within a DFM framework. Once selected the target economic variable and estimated a DFM based on a large target-oriented dataset, we identify the common factor shocks through sign restrictions on the impact multipliers and simulate the structural form of the model. The Forecast Error Variance Decompositions obtained over a k steps-ahead simulation horizon define k sets of weights for aggregating factors (in a different way depending on the leading horizon) in order to get composite leading indexes. This procedure is used for a very preliminar empirical exercise aimed at forecasting crude nominal oil prices. The results seem to be encouraging and support the validity of the proposal: we generate a wide range of horizon-specific leading indexes with appreciable forecasting performances.

In the last decades a liberalization of the electric market has started; prices are now determined on the basis of contracts on regular markets and their behaviour is mainly driven by usual supply and demand forces. A large body of literature has been developed in order to analyze and forecast their evolution: it includes works with different aims and methodologies depending on the temporal horizon being studied. In this survey we depict the actual state of the art focusing only on the recent papers oriented to the determination of trends in electricity spot prices and to the forecast of these prices in the short run. Structural methods of analysis, which result appropriate for the determination of forward and future values are left behind. Studies have been divided into three broad classes: Autoregressive models, Regime switching models, Volatility models. Six fundamental points arise: the peculiarities of electricity market, the complex statistical properties of prices, the lack of economic foundations of statistical models used for price analysis, the primacy of uniequational approaches, the crucial role played by demand and supply in prices determination, the lack of clearcut evidence in favour of a specific framework of analysis. To take into account the previous stylized issues, we propose the adoption of a methodological framework not yet used to model and forecast electricity prices: a time varying parameters Dynamic Factor Model (DFM). Such an eclectic approach, introduced in the late ‘70s for macroeconomic analysis, enables the identification of the unobservable dynamics of demand and supply driving electricity prices, the coexistence of short term and long term determinants, the creation of forecasts on future trends. Moreover, we have the possibility of simulating the impact that mismatches between demand and supply have over the price variable. This way it is possible to evaluate whether congestions in the network (eventually leading black out phenomena) trigger price reactions that can be considered as warning mechanisms.

Since the contribution of Linder (1961) product quality is considered as a factor potentially boosting exports, especially for the most industrialized countries. However, being quality difficult to be measured, the macro-econometric studies on its role are not numerous and have not produced clear-cut results. In this paper we shed some light on the theoretical and empirical impact of product quality on the export performance of the EU-12 area. To avoid problems of mis-specification and endogeneity usual in the empirical literature on trade equations, we model exports as jointly endogenous with GDP, inflation and exchange rate. For this purpose we modify and enlarge a New Keynesian open economy model à la Clarida, Galì and Gertler (2001) to adapt it to a large open economy. Sign restrictions, based on theoretical impact multipliers, enable the identification of quality as one of the structural shocks of the corresponding Bayesian VAR, avoiding drawbacks connected to the choice of an incomplete, partial or biased proxy of the phenomenon. The empirical evidence shows that a quality upgrade might reinforce the EU competitiveness leading to an improvement of the current account, without any unfavourable effect on terms of trade.

In this work, we have applied non-linear time series techniques to the Nordic spot electricity market data. The time series are given in two periods, from May 1992 to December 1998 in Norwegian Kröne per MWh and from January 1999 to January 2007 in EUR per MWh. Our main interest was on trying to classify these series and analysing if their dynamical behaviour were in some way correlated with known events, e.g. the evolution of the Nord Pool and the climatic factors. First, a preliminary study was carried out with the aim of characterising the time series in terms of power spectral distribution, long term memory (R/S analysis), stationarity (space-time separation plots) and tails (stable distributions). Then, we used two types of surrogate time series, the first type was generated by a Gaussian linear random process with the same FFT of the real data set, whereas the second type consisted on a shuffled version of the original data series i.e. with the same statistic properties but without any correlation. We used these surrogates to check if RQA measures were able to detect differences with the real data. Finally, we used two RQA measures, %determinism and %laminarity, for developing a new measure of volatility which was able of detecting important historical and meteorological events with better resolution than by measuring the time series standard deviation.

In this paper we address two relevant issues among those characterising the macroeconomic literature on migration. (a) We evaluate which impact is produced by the immigration flows coming from the enlargement countries on the EU-15 labour market. (b) We draw clues on the migrant characteristics as for their skill levels. We adopt an insider/outsider model inspired by that of Amisano and Serati (2003), but enlarged in order to model the migration flows and fit to wage, participation and employment differentials between skilled and unskilled workers. We identify the structural shocks of the reduced VAR form of the model through sign restrictions imposed to the Impulse Response Functions, leaving unconstrained only the impact multipliers of relative (skilled to unskilled) wage, employment and labour force with respect to a migration shock. This is equivalent to adopt an agnostic approach, letting emerge freely the signals coming from the data: combining them with theoretical suggestions we derive at least weak indications on the fact that the skill mix of migrants is either biased towards high or low qualified labour. It does emerge that migration from Eastern European countries towards the EU-15 is mainly constituted by skilled workers and generates effects of reduction of the employment gap; on the other side, it enlarges the skilled to unskilled relative wage gap. The whole picture suggests the adoption of policies aimed at attract skilled migration through economic but also social and environmental incentives.

In the final part of the nineties both the theoretical literature and also the effective Governance experience stressed the fact that the Public administrations strongly need for a model specifically dedicated to evaluate the activity of planning of development policies. In this paper we propose a quite innovative methodology for specify an evaluation model on which basis the "planner" is able to assess the effects of strategic and sector development regional plans, both at the aggregate level and also in terms of their geographical distribution. On the basis of a set of economic indicators, that the model combines to define a Synthetic Priority Index (SPI), the administrators involved in the planning activity (sector oriented or local oriented) are able to make optimal choices on: a) The regional distributions of public Investments b) The economic and financial features and characteristics of public Investments c) The Architecture of public Investments In other terms our methodology allows for handling three fundamental and often puzzling questions: Assessing the determinants of the public investment Finding the "priority" areas to which redirect the public investments Evaluating the economic impact of the investments One of the main features of the model lies on its eclectic approach; in fact the definition of the SPI is based on the combination of an eterogeneous and large set of informations, emphazising the relationships among the economic theory (aimed at quantifying the impact of investments and evaluating the policies planning), the territory (to be intended as the working and intervention space), and the public finance (to be viewed as the optimal rule of collecting and spending the public resources). An empirical application to the Lombardy case gives some encouraging insight into the model performance.