Multiple Time Serie3 Models Applied To Panel Data
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| Author | : Patrick T. Brandt |
| Publisher | : SAGE |
| Total Pages | : 121 |
| Release | : 2007 |
| Genre | : Mathematics |
| ISBN | : 1412906563 |
Many analyses of time series data involve multiple, related variables. Modeling Multiple Time Series presents many specification choices and special challenges. This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. Specification, estimation, and inference using these models is discussed. The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available. Key Features: * Offers a detailed comparison of different time series methods and approaches. * Includes a self-contained introduction to vector autoregression modeling. * Situates multiple time series modeling as a natural extension of commonly taught statistical models.
| Author | : Christian Kleiber |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 229 |
| Release | : 2008-12-10 |
| Genre | : Business & Economics |
| ISBN | : 0387773185 |
R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.
| Author | : David Darmofal |
| Publisher | : Cambridge University Press |
| Total Pages | : 263 |
| Release | : 2015-11-12 |
| Genre | : Mathematics |
| ISBN | : 0521888263 |
This book shows how to model the spatial interactions between actors that are at the heart of the social sciences.
| Author | : Rob J Hyndman |
| Publisher | : OTexts |
| Total Pages | : 380 |
| Release | : 2018-05-08 |
| Genre | : Business & Economics |
| ISBN | : 0987507117 |
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
| Author | : M. Hashem Pesaran |
| Publisher | : Oxford University Press, USA |
| Total Pages | : 1095 |
| Release | : 2015 |
| Genre | : Business & Economics |
| ISBN | : 0198759983 |
The book describes and illustrates many advances that have taken place in a number of areas in theoretical and applied econometrics over the past four decades.
| Author | : M. Hashem Pesaran |
| Publisher | : Oxford University Press |
| Total Pages | : 1443 |
| Release | : 2015-10-01 |
| Genre | : Business & Economics |
| ISBN | : 0191058475 |
This book is concerned with recent developments in time series and panel data techniques for the analysis of macroeconomic and financial data. It provides a rigorous, nevertheless user-friendly, account of the time series techniques dealing with univariate and multivariate time series models, as well as panel data models. It is distinct from other time series texts in the sense that it also covers panel data models and attempts at a more coherent integration of time series, multivariate analysis, and panel data models. It builds on the author's extensive research in the areas of time series and panel data analysis and covers a wide variety of topics in one volume. Different parts of the book can be used as teaching material for a variety of courses in econometrics. It can also be used as reference manual. It begins with an overview of basic econometric and statistical techniques, and provides an account of stochastic processes, univariate and multivariate time series, tests for unit roots, cointegration, impulse response analysis, autoregressive conditional heteroskedasticity models, simultaneous equation models, vector autoregressions, causality, forecasting, multivariate volatility models, panel data models, aggregation and global vector autoregressive models (GVAR). The techniques are illustrated using Microfit 5 (Pesaran and Pesaran, 2009, OUP) with applications to real output, inflation, interest rates, exchange rates, and stock prices.
| Author | : Edward W. Frees |
| Publisher | : Cambridge University Press |
| Total Pages | : 492 |
| Release | : 2004-08-16 |
| Genre | : Business & Economics |
| ISBN | : 9780521535380 |
An introduction to foundations and applications for quantitatively oriented graduate social-science students and individual researchers.
| Author | : Gebhard Kirchgässner |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 288 |
| Release | : 2008-08-27 |
| Genre | : Business & Economics |
| ISBN | : 9783540687351 |
This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It contains the most important approaches to analyze time series which may be stationary or nonstationary.
| Author | : Yves Croissant |
| Publisher | : John Wiley & Sons |
| Total Pages | : 435 |
| Release | : 2018-08-10 |
| Genre | : Mathematics |
| ISBN | : 1118949188 |
Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemiology, this book presents classic methodology and applications as well as more advanced topics and recent developments in this field including error component models, spatial panels and dynamic models. They have developed the software programming in R and host replicable material on the book’s accompanying website.
| Author | : Panchanan Das |
| Publisher | : Springer Nature |
| Total Pages | : 574 |
| Release | : 2019-09-05 |
| Genre | : Business & Economics |
| ISBN | : 9813290196 |
This book introduces econometric analysis of cross section, time series and panel data with the application of statistical software. It serves as a basic text for those who wish to learn and apply econometric analysis in empirical research. The level of presentation is as simple as possible to make it useful for undergraduates as well as graduate students. It contains several examples with real data and Stata programmes and interpretation of the results. While discussing the statistical tools needed to understand empirical economic research, the book attempts to provide a balance between theory and applied research. Various concepts and techniques of econometric analysis are supported by carefully developed examples with the use of statistical software package, Stata 15.1, and assumes that the reader is somewhat familiar with the Strata software. The topics covered in this book are divided into four parts. Part I discusses introductory econometric methods for data analysis that economists and other social scientists use to estimate the economic and social relationships, and to test hypotheses about them, using real-world data. There are five chapters in this part covering the data management issues, details of linear regression models, the related problems due to violation of the classical assumptions. Part II discusses some advanced topics used frequently in empirical research with cross section data. In its three chapters, this part includes some specific problems of regression analysis. Part III deals with time series econometric analysis. It covers intensively both the univariate and multivariate time series econometric models and their applications with software programming in six chapters. Part IV takes care of panel data analysis in four chapters. Different aspects of fixed effects and random effects are discussed here. Panel data analysis has been extended by taking dynamic panel data models which are most suitable for macroeconomic research. The book is invaluable for students and researchers of social sciences, business, management, operations research, engineering, and applied mathematics.
