Spectral analysis of stochastic and analytic simulation results for a nonlinear model for the Italian economy

When dealing with nonlinear econometric models, resort is often made to simulation techniques for the investigation of their dynamic properties. A spectral analysis using stochastic and analytic simulation is carried out on a nonlinear model of the Italian economy. The two approaces are empirically compared.Stochastic simulation; nonlinear econometric models; analytic simulation; spectral analysis; Monte Carlo methods

Spectral analysis of stochastic and analytic simulation results for a nonlinear model for the Italian economy

When dealing with nonlinear econometric models, resort is often made to simulation techniques for the investigation of their dynamic properties. A spectral analysis using stochastic and analytic simulation is carried out on a nonlinear model of the Italian economy. The two approaces are empirically compared

Stochastic simulation and dynamic properties of the new version of the Italian model

This paper describes the results of some stochastic simulation experiments performed on the most updated version of the Italian model. Due to a change in the income accounts system, the model has been completely reestimated using the new quarterly data. It consists of 128 equations, 50 of which are stochastic. As regards to the structure of the model, the main differences with respect to the previous version lie in the income sector: now the different components of income distribution are determined endogenously and disaggregated by sector, and affect directly private disposable income. Stochastic simulation has been performed using the program described in [1]. The generation of pseudo randorn numbers with multivariate normal distribution has been performed using the Box-Muller technique [3] and McCarthy algorithm [9]

Stochastic simulation and dynamic properties of the new version of the Italian model

This paper describes the results of some stochastic simulation experiments performed on the most updated version of the Italian model. Due to a change in the income accounts system, the model has been completely reestimated using the new quarterly data. It consists of 128 equations, 50 of which are stochastic. As regards to the structure of the model, the main differences with respect to the previous version lie in the income sector: now the different components of income distribution are determined endogenously and disaggregated by sector, and affect directly private disposable income. Stochastic simulation has been performed using the program described in [1]. The generation of pseudo randorn numbers with multivariate normal distribution has been performed using the Box-Muller technique [3] and McCarthy algorithm [9]

Stochastic simulation and dynamic properties of the new version of the Italian model

This paper describes the results of some stochastic simulation experiments performed on the most updated version of the Italian model. Due to a change in the income accounts system, the model has been completely reestimated using the new quarterly data. It consists of 128 equations, 50 of which are stochastic. As regards to the structure of the model, the main differences with respect to the previous version lie in the income sector: now the different components of income distribution are determined endogenously and disaggregated by sector, and affect directly private disposable income. Stochastic simulation has been performed using the program described in [1]. The generation of pseudo randorn numbers with multivariate normal distribution has been performed using the Box-Muller technique [3] and McCarthy algorithm [9].Stochastic simulation; econometric model; Italian economy; project Link

Analisi e simulazione stocastica di un modello aggregato dell'economia italiana 1952-1971

Experiments of stochastic simulation on a macro model of the Italian economy; this paper describes the first results produced by the research team

Analysis and stochastic simulation of a macro model of the Italian economy 1952-1971

Experiments of stochastic simulation on a macro model of the Italian economy; this paper describes the first results produced by the research team.Stochastic simulation; macroeconometric model

The pre-vaccination regional epidemiological landscape of measles in Italy: contact patterns, effort needed for eradication, and comparison with other regions of Europe

BACKGROUND: Strong regional heterogeneity and generally sub-optimal rates of measles vaccination in Italy have, to date, hampered attainment of WHO targets for measles elimination, and have generated the need for the new Italian National Measles Elimination Plan. Crucial to success of the plan is the identification of intervention priorities based upon a clear picture of the regional epidemiology of measles derived from the use of data to estimate basic parameters. Previous estimates of measles force of infection for Italy have appeared anomalously low. It has been argued elsewhere that this results from Italian selective under-reporting by age of cases and that the true measles force of infection in Italy is probably similar to that of other European countries. A deeper examination of the evidence for this conjecture is undertaken in the present paper. METHODS: Using monthly regional case notifications data from 1949 to the start of vaccination in 1976 and notifications by age from 1971–76, summary equilibrium parameters (force of infection (FOI), basic reproductive ratio (R(0)) and critical vaccination coverage (p(c))) are calculated for each region and for each of 5 plausible contact patterns. An analysis of the spectra of incidence profiles is also carried out. Finally a transmission dynamics model is employed to explore the correspondence between projections using different estimates of force of infection and data on seroprevalence in Italy. RESULTS: FOI estimates are lower than comparable European FOIs and there is substantial regional heterogeneity in basic reproductive ratios; certain patterns of contact matrices are demonstrated to be unfeasible. Most regions show evidence of 3-year epidemic cycles or longer, and compared with England & Wales there appears to be little synchronisation between regions. Modelling results suggest that the lower FOI estimated from corrected aggregate national data matches serological data more closely than that estimated from typical European data. CONCLUSION: Results suggest forces of infection in Italy, though everywhere remaining below the typical European level, are historically higher in the South where currently vaccination coverage is lowest. There appears to be little evidence to support the suggestion that a higher true force of infection is masked by age bias in reporting

La base monetaria, la moneta ed i prezzi in Italia negli anni '80

Causal relationships between money, the monetary base and consumer prices in Italy in the 80's are analysed in the frequency domain following mainly the methodology developed in Geweke (1982). A frequency domain analysis enables us, not only to detect causal relationships otherwise absent in a time domain analysis, but also to single out che components most responsable for such relationships. Thus we find that the causal relationships between money on the one side and consumer prices and the monetary base on the other are largely due to the long term fluctuations in the series

Stima via simulazione e calibrazione: confronto fra stimatori alternativi di equazioni differenziali stocastiche uni-dimensionali

A simulation based approach is used to compare the performances of some estimators of the drift parameters of selected one-dimensional Stochastic Differential Equations (SDE), namely a maximum likelihood estimator, a naive estimator and an indirect estimator. These estimators are tested on the most classical models of the recent financial literature and on a classical SDE of population dynamics. First, the need for well generated data is evidenced. Second, our results clearly show the role of an indirect estimation procedure as a general strategy to be used in all those circumstances in which the optimal experimental conditions are not satisfied