Marco Bee & Giuseppe Espa 
Econometric Modeling Perspectives [PDF ebook] 

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In this book the authors present a reassessment of some recently proposed econometric methods for the analysis of continuous-time specifications of economic models. Given the vastness of this stream of the literature, that does not allow for a full exposition of the topic, the authors concentrate on the estimation and simulation analysis of a continuous-time econometric model based on a theoretical framework – the SETI model – developed in Padoan (1996). The application is almost completely instrumental to a more thorough analysis of methodological issues entailed with continuous-time econometrics. Nevertheless, it presents some interesting theoretical aspects such as the process of diffusion of ICT and the role of services in international diffusion of technology. The standard methods are not suitable for theoretical models in which disequilibrium analysis is necessary and, in general, presents a clear limitation when the structural multi-equation form of the model should be preserved. Thus the authors show how, by means of continuous-time econometric, it is possible to estimate the parameters of the model using the Full Information Maximum Likelihood techniques in a time series setup. Then, the authors extend the econometric analysis in order to evaluate the out-of-equilibrium dynamic properties of a system via simulation techniques. The declared aim of the present work is to define the conditions to the equilibrium and to discuss its stability properties. Furthermore, the application provides the guidelines for the formulation and empirical validation of a model considering growth-driven-by-technology phenomena, interactions between countries through trade effects, and the diffusion of technology. Finally, spatial aspects of the problem are explicitly taken into account.
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Format PDF ● Strony 107 ● ISBN 9781616688042 ● Redaktor Marco Bee & Giuseppe Espa ● Wydawca Nova Science Publishers ● Opublikowany 2018 ● Do pobrania 3 czasy ● Waluta EUR ● ID 7219537 ● Ochrona przed kopiowaniem Adobe DRM
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