ADVANCED ECONOMETRICS. Multiple Equation Models. Exercises with SPSS, EVIEWS, SAS and STATA

Multi-equation econometric models are characterized by the presence of several equations to simultaneously estimate. It is thus a generalization of the models in the field of systems of equations. Multi-equational simultaneous equations in linear models, incorporating the identification of models and techniques of estimation theory are covered in this book (MCI, MC2E, MC3E, RANR, SUR, etc.). Then the models are dealt with multivariate time series (VAR VARX, VARMA, BVAR, VEC) dealing...
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Multi-equation econometric models are characterized by the presence of several equations to simultaneously estimate. It is thus a generalization of the models in the field of systems of equations. Multi-equational simultaneous equations in linear models, incorporating the identification of models and techniques of estimation theory are covered in this book (MCI, MC2E, MC3E, RANR, SUR, etc.). Then the models are dealt with multivariate time series (VAR VARX, VARMA, BVAR, VEC) dealing the Cointegration theory from the multi-equational standpoint. Also delves into the non-linear multi-equational models and models of regression partitioned and segmented. The development of practical exercises is carried out from a perspective multi-software, using the latest software on the market suitable for these non-trivial econometric tasks: SAS, EVIEWS, STATA y SPSS.The book develops the following themes:Multiple equation models. Simultaneous equationsMulti-equation linear models. Structural form and simultaneous linear equation models Multi equation model in reduced form Structural simultaneous equations model identification. MCI estimate Estimate simultaneous linear equations modelIndirect Least Squares Instrumental variables Two Stage Least Square Recursive models Maximum Likelihood with limited information Maximum Likelihood Full Information Class k estimators and Tree Stage Least SquareRANR or SUR method The heteroscedasticity robust methods : WHITE and HAC Simultaneous linear equations with time series models Simultaneous linear equations with eviews Simultaneous linear equations models with SAS: SYSLIN and MODEL procedures Simultaneous linear equations models with STATAMultivariate time series models : VAR, VARX, VARMA and BVAR. Cointegration Vector Autoregressive (VAR) models Identification in VAR models Estimate a VAR model VARMA models Cointegration in VAR models. Johansen test VAR models with EVIEWS. Johansen test Estimation VAR models in EVIEWS through menusCointegration in VAR models with EVIEWS through menus Error Correction Model in VAR models with EVIEWSVAR models with SAS. Causality test and cointegration. Johansen test Johansen test in VAR models with SAS Error Correction Vector Model (VEC) in VAR models with SAS VAR models with exogenous variables (VARX) in SAS STATA and the VEC and VAR models. Causality test and cointegration. Johansen test Non-linear models. Partitioned and segmented regression Non- linear models Simple non-linear models Non-linear least squares. Newton and Marquardt algorithms Partitioned regression Segmented regression Non-linear estimation and segmented regression with SPSS Non-linear estimation with SAS. NLIN procedureNon-linear simultaneous equations models with SAS: procedure MODEL Non- linear models with EVIEWS Non- linear models with STATA