Statistical Analysis of Time Series - Cointegration and VECM Models
Application to the case of carbon and electricity markets using statistical software
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The theme of the work falls within the scope of multivariate statistics, namely, the econometric analysis of time series with non-stationary data. Multivariate analysis using autoregressive vector systems (VAR), integrated process modeling, cointegration and vector error correction model (VECM) are the central themes of the work. The econometric analysis of time series has undergone profound developments, especially in the field of nonstationary data analysis. The aim of this book is to provide students, researchers and professionals who work or research in econometric time series analysis wit...
The theme of the work falls within the scope of multivariate statistics, namely, the econometric analysis of time series with non-stationary data. Multivariate analysis using autoregressive vector systems (VAR), integrated process modeling, cointegration and vector error correction model (VECM) are the central themes of the work. The econometric analysis of time series has undergone profound developments, especially in the field of nonstationary data analysis. The aim of this book is to provide students, researchers and professionals who work or research in econometric time series analysis with a simple and applied textbook that covers this subject. It is intended that reading and consulting the book does not require in-depth knowledge. The book is structured in two components: presentation of concepts and application to a specific case. In this space, it is explored in detail the use of various statistical processing programs, both open source, such as GRETL, and the commercial program EVIEWS, very popular among the academic and scientific community.
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