Advanced Econometrics. Concepts and Exercises with IBM SPSS

Advanced Econometrics. Concepts and Exercises with IBM SPSS

Author: Cesar Lopez

Publisher: Createspace Independent Publishing Platform

Published: 2013-10-20

Total Pages: 0

ISBN-13: 9781493533688

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This book includes a wide typology of econometric models advanced, among them the following: Limited dependent variable model Logit binary model Logit Multinomial model Logit conditional model Logit nested models Probit binary model Probit Multinomial models Dynamic models Classification and segmentation models Decision trees models CHAID trees CART trees QUEST trees Discriminant analysis models Panel data models Panel data models with constant coefficients Panel data models with fixed effects Panel data models with random effects Dynamic panel data models Logit and Probit panel data models Nonlinear models Data partitioned regression models Segmented regression models The development of practical exercises is performed using the SPSS software, one of the most modern on the market suitable for these non-trivial econometric task.


Advanced Econometrics. Dynamic Models. Exercises with SPSS, SAS, Stata and Eviews

Advanced Econometrics. Dynamic Models. Exercises with SPSS, SAS, Stata and Eviews

Author: César Pérez López

Publisher: CreateSpace

Published: 2013-10

Total Pages: 222

ISBN-13: 9781493628193

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Usually variables that appear how explanatory in econometric models are supposed related at one time with the endogenous variable, so usually the temporary subscripts of all variables are equal. However, economic theory, econometrics, and other sciences lead us to relationship dynamic between the variables, since the impacts between variables can become manifest in later periods or extended to many periods. In this way appear dynamic models with variables out in time. Dynamic models usually seen three different situations according to the variables affected by delays. It may be that the delays involved only to exogenous variables, only the endogenous variable or simultaneously to endogenous and exogenous variables. This book covers a wide typology of dynamic models including models with distributed delays, models with stochastic regressors, models with structural change and dynamic panel data models. Widely is the theory of unit roots, the Cointegration and error correction models. And all this from a perspective multi-software, using the latest software on the market suitable for these non-trivial econometric tasks (SAS, EVIEWS, SPSS and STATA). The book develops the following themes: Dynamic models Dynamic models with delays in exogenous variables Dynamic models with delays in the endogenous variable Dynamic models with delays in the endogenous variable and the exogenous variables simultaneously Special types of dynamic models Models with finite distributed delays Models with distributed delays infinite EVIEWS and the specific dynamic models SPSS and the dynamic models SPSS and dynamic models with stochastic regressors. instrumental variables EVIEWS and dynamic models with stochastic regressors. instrumental variables SAS and the dynamic models Stable models. Structural change, unit roots and cointegration Structural stability in econometric models Parameters constant in time and prediction of Chow test Chow prediction test Structural Change and Chow test Recursive models: contrasts based on recursive estimation CUSUM and CUSUMQ tests Unstable models: spurious regressions Stationary time series. Detecting stationarity Seasonality detection Unit roots test Dickey-Fuller Unit Roots Tests Phillips-Perron Unit Roots Test Stable models in the long term: the cointegration analysis Phillips-Oularis for the Cointegration Test Error correction models mce Unit roots and cointegration in seasonal series Unit roots and cointegration in series with structural change Stationary and seasonality with EVIEWS Unit roots, cointegration and structural change with EVIEWS Panel data models. Unit roots and cointegration in panel. Dynamic panels Econometric models with panel data Panel data models with constant coefficients Panel data models with fixed effects Panel data models with random -effects Dynamic panel data models Logit and probit panel data models Unit roots and cointegration in panel data models EVIEWS and panel data models SPSS and panel data models Panel data models with SAS EVIEWS and dynamic models with panel data. methodology of ARELLANO and BOND EVIEWS and the contrasts of unit roots with panel data. Cointegration in panel


Advanced Econometrics with Eviews. Concepts an Exercises

Advanced Econometrics with Eviews. Concepts an Exercises

Author: Cesar Lopez

Publisher: CreateSpace

Published: 2013-10

Total Pages: 200

ISBN-13: 9781492991083

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This book develop a wide typology of advanced econometric models including dynamic models, simultaneous equations models, non-linear models, multivariate time series models, models with panel data and the theory of unit roots and models data cointegration. As for dynamic models, include models with distributed delays, models with stochastic regressors, models with structural change and dynamic panel data models. Widely is the theory of unit roots, the Cointegration and error correction models. Multi-equation econometric models are characterized by the presence of several equations to simultaneously estimate. It is thus a generalization of the simple-equation models in the field of systems of equations. 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-equation econometric models. Also discussed in depth econometrics with both static and dynamic panel data models, considering at the same time the static and dynamic models as well as the theory of unit roots and Cointegration in Panel. Finally, it deepens on single-equational models and multi-equational non-linear models. The development of practical exercises is done using software EVIEWS, one of the most current market suitable for these non-trivial econometric tasks.


Advanced Econometrics. Multiple Equation Models. Exercises with SPSS, Eviews, SAS and Stata

Advanced Econometrics. Multiple Equation Models. Exercises with SPSS, Eviews, SAS and Stata

Author: César Pérez López

Publisher: CreateSpace

Published: 2013-10

Total Pages: 168

ISBN-13: 9781493621606

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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 equations Multi-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 model Indirect 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 Square RANR 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 STATA Multivariate 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 menus Cointegration in VAR models with EVIEWS through menus Error Correction Model in VAR models with EVIEWS VAR 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 procedure Non-linear simultaneous equations models with SAS: procedure MODEL Non- linear models with EVIEWS Non- linear models with STATA


Advanced Econometrics

Advanced Econometrics

Author: Takeshi Amemiya

Publisher: Wiley-Blackwell

Published: 1985-01-01

Total Pages: 521

ISBN-13: 9780631133452

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"Advanced Econometrics is both a comprehensive text for graduate students and a reference work for econometricians. It will also be valuable to those doing statistical analysis in the other social sciences. Its main features are a thorough treatment of cross-section models, including qualitative response models, censored and truncated regression models, and Markov and duration models, as well as a rigorous presentation of large sample theory, classical least-squares and generalized least-squares theory, and nonlinear simultaneous equation models. Although the treatment is mathematically rigorous, the author has employed the theorem-proof method with simple, intuitively accessible assumptions. This enables readers to understand the basic structure of each theorem and to generalize it for themselves depending on their needs and abilities. Many simple applications of theorems are given either in the form of examples in the text or as exercises at the end of each chapter in order to demonstrate their essential points.


Quantitative Analysis and IBM® SPSS® Statistics

Quantitative Analysis and IBM® SPSS® Statistics

Author: Abdulkader Aljandali

Publisher: Springer

Published: 2016-11-08

Total Pages: 190

ISBN-13: 3319455281

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This guide is for practicing statisticians and data scientists who use IBM SPSS for statistical analysis of big data in business and finance. This is the first of a two-part guide to SPSS for Windows, introducing data entry into SPSS, along with elementary statistical and graphical methods for summarizing and presenting data. Part I also covers the rudiments of hypothesis testing and business forecasting while Part II will present multivariate statistical methods, more advanced forecasting methods, and multivariate methods. IBM SPSS Statistics offers a powerful set of statistical and information analysis systems that run on a wide variety of personal computers. The software is built around routines that have been developed, tested, and widely used for more than 20 years. As such, IBM SPSS Statistics is extensively used in industry, commerce, banking, local and national governments, and education. Just a small subset of users of the package include the major clearing banks, the BBC, British Gas, British Airways, British Telecom, the Consumer Association, Eurotunnel, GSK, TfL, the NHS, Shell, Unilever, and W.H.S. Although the emphasis in this guide is on applications of IBM SPSS Statistics, there is a need for users to be aware of the statistical assumptions and rationales underpinning correct and meaningful application of the techniques available in the package; therefore, such assumptions are discussed, and methods of assessing their validity are described. Also presented is the logic underlying the computation of the more commonly used test statistics in the area of hypothesis testing. Mathematical background is kept to a minimum.


IBM SPSS by Example

IBM SPSS by Example

Author: Alan C. Elliott

Publisher: SAGE Publications

Published: 2014-12-31

Total Pages: 278

ISBN-13: 1483319040

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The updated Second Edition of Alan C. Elliott and Wayne A. Woodward’s "cut to the chase" IBM SPSS guide quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision making in a wide variety of disciplines. This one-stop reference provides succinct guidelines for performing an analysis using SPSS software, avoiding pitfalls, interpreting results, and reporting outcomes. Written from a practical perspective, IBM SPSS by Example, Second Edition provides a wealth of information—from assumptions and design to computation, interpretation, and presentation of results—to help users save time, money, and frustration.


SPSS Statistics For Dummies

SPSS Statistics For Dummies

Author: Jesus Salcedo

Publisher: John Wiley & Sons

Published: 2020-09-09

Total Pages: 487

ISBN-13: 1119560837

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The fun and friendly guide to mastering IBM’s Statistical Package for the Social Sciences Written by an author team with a combined 55 years of experience using SPSS, this updated guide takes the guesswork out of the subject and helps you get the most out of using the leader in predictive analysis. Covering the latest release and updates to SPSS 27.0, and including more than 150 pages of basic statistical theory, it helps you understand the mechanics behind the calculations, perform predictive analysis, produce informative graphs, and more. You’ll even dabble in programming as you expand SPSS functionality to suit your specific needs. Master the fundamental mechanics of SPSS Learn how to get data into and out of the program Graph and analyze your data more accurately and efficiently Program SPSS with Command Syntax Get ready to start handling data like a pro—with step-by-step instruction and expert advice!


Statistics for Criminal Justice and Criminology in Practice and Research

Statistics for Criminal Justice and Criminology in Practice and Research

Author: Jack Fitzgerald

Publisher: SAGE Publications

Published: 2013-01-17

Total Pages: 609

ISBN-13: 1452292167

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Statistics for Criminal Justice and Criminology in Practice and Research—by Jack Fitzgerald and Jerry Fitzgerald—is an engaging and comprehensive introduction to the study of basic statistics for students pursuing careers as practitioners or researchers in both Criminal Justice and Criminology programs. This student-friendly text shows how to calculate a variety of descriptive and inferential statistics, recognize which statistics are appropriate for particular data analysis situations, and perform hypothesis tests using inferential statistics. But it is much more than a "cook book." It encourages readers to think critically about the strengths and limitations of the statistics they are calculating, as well as how they may be misapplied and misleading. Examples of statistics and statistical analyses are drawn from the worlds of the practitioner as well as the policymaker and researcher. Students will also gain a clear understanding of major ethical issues in conducting statistical analyses and reporting results, as well as insight into the realities of the life of researchers and practitioners as they use statistics and statistical analyses in their day-to-day activities.


Partial Least Squares Path Modeling

Partial Least Squares Path Modeling

Author: Hengky Latan

Publisher: Springer

Published: 2017-11-03

Total Pages: 434

ISBN-13: 3319640690

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This edited book presents the recent developments in partial least squares-path modeling (PLS-PM) and provides a comprehensive overview of the current state of the most advanced research related to PLS-PM. The first section of this book emphasizes the basic concepts and extensions of the PLS-PM method. The second section discusses the methodological issues that are the focus of the recent development of the PLS-PM method. The third part discusses the real world application of the PLS-PM method in various disciplines. The contributions from expert authors in the field of PLS focus on topics such as the factor-based PLS-PM, the perfect match between a model and a mode, quantile composite-based path modeling (QC-PM), ordinal consistent partial least squares (OrdPLSc), non-symmetrical composite-based path modeling (NSCPM), modern view for mediation analysis in PLS-PM, a multi-method approach for identifying and treating unobserved heterogeneity, multigroup analysis (PLS-MGA), the assessment of the common method bias, non-metric PLS with categorical indicators, evaluation of the efficiency and accuracy of model misspecification and bootstrap parameter recovery in PLS-PM, CB-SEM, and the Bollen-Stine methods and importance-performance map analysis (IPMA) for nonlinear relationships. This book will be useful for researchers and practitioners interested in the latest advances in PLS-PM as well as master and Ph.D. students in a variety of disciplines using the PLS-PM method for their projects.