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Books > Business & Economics > Economics > Econometrics > General
This book provides an introduction to the technical background of
unit root testing, one of the most heavily researched areas in
econometrics over the last twenty years. Starting from an
elementary understanding of probability and time series, it
develops the key concepts necessary to understand the structure of
random walks and brownian motion, and their role in tests for a
unit root. The techniques are illustrated with worked examples,
data and programs available on the book's website, which includes
more numerical and theoretical examples
This is the second of two volumes containing papers and commentaries presented at the Eleventh World Congress of the Econometric Society, held in Montreal, Canada in August 2015. These papers provide state-of-the-art guides to the most important recent research in economics. The book includes surveys and interpretations of key developments in economics and econometrics, and discussion of future directions for a wide variety of topics, covering both theory and application. These volumes provide a unique, accessible survey of progress on the discipline, written by leading specialists in their fields. The second volume addresses topics such as big data, macroeconomics, financial markets, and partially identified models.
Following the recent publication of the award winning and much acclaimed "The New Palgrave Dictionary of Economics," second edition which brings together Nobel Prize winners and the brightest young scholars to survey the discipline, we are pleased to announce "The New Palgrave Economics Collection." Due to demand from the economics community these books address key subject areas within the field. Each title is comprised of specially selected articles from the Dictionary and covers a fundamental theme within the discipline. All of the articles have been specifically chosen by the editors of the Dictionary, Steven N.Durlauf and Lawrence E.Blume and are written by leading practitioners in the field. The Collections provide the reader with easy to access information on complex and important subject areas, and allow individual scholars and students to have their own personal reference copy.
Bayesian analysis has developed rapidly in applications in the last
two decades and research in Bayesian methods remains dynamic and
fast-growing. Dramatic advances in modelling concepts and
computational technologies now enable routine application of
Bayesian analysis using increasingly realistic stochastic models,
and this drives the adoption of Bayesian approaches in many areas
of science, technology, commerce, and industry.
The availability of microdata has increased rapidly over the last decades, and standard statistical and econometric software packages for data analysis include ever more sophisticated modeling options. The goal of this book, now initssecondedition, istofamiliarizethereaderwithawiderangeofcommonly used models, and thereby to enable her/him to become a critical consumer of current empirical research, and to properly conduct own empirical analyses. The book can be used as a textbook for an advanced undergraduate, a Master's or a ?rst-year Ph.D. course on the topic of microdata analysis. In economicsandrelateddisciplines, suchacourseistypicallyo?eredaftera?rst course on the linear regression model. Alternatively, the book can also serve as a supplementary text to applied ?eld courses, such as those dealing with empirical analyses in labor, health or education. Finally, it might provide a useful reference for graduate students, researchers and practitioners who encounter microdata in their work. The focus of the book is on regression-type models in the context of large cross-section samples where the dependent variable is qualitative or discrete, or where the sample is not randomly drawn from the population of interest, due to censoring or truncation of the dependent variable. While our ba- groundisineconomics, andweoccasionallyrefertoproblemsandapplications fromempiricaleconomics, themodelsdiscussedinthisbookshouldbeequally relevant wherever microdata are used, inside the social sciences, including for example quantitative political science and sociology, as well as outside.
Volume 1 covers statistical methods related to unit roots, trend breaks and their interplay. Testing for unit roots has been a topic of wide interest and the author was at the forefront of this research. The book covers important topics such as the Phillips-Perron unit root test and theoretical analyses about their properties, how this and other tests could be improved, and ingredients needed to achieve better tests and the proposal of a new class of tests. Also included are theoretical studies related to time series models with unit roots and the effect of span versus sampling interval on the power of the tests. Moreover, this book deals with the issue of trend breaks and their effect on unit root tests. This research agenda fostered by the author showed that trend breaks and unit roots can easily be confused. Hence, the need for new testing procedures, which are covered.Volume 2 is about statistical methods related to structural change in time series models. The approach adopted is off-line whereby one wants to test for structural change using a historical dataset and perform hypothesis testing. A distinctive feature is the allowance for multiple structural changes. The methods discussed have, and continue to be, applied in a variety of fields including economics, finance, life science, physics and climate change. The articles included address issues of estimation, testing and/or inference in a variety of models: short-memory regressors and errors, trends with integrated and/or stationary errors, autoregressions, cointegrated models, multivariate systems of equations, endogenous regressors, long-memory series, among others. Other issues covered include the problems of non-monotonic power and the pitfalls of adopting a local asymptotic framework. Empirical analyses are provided for the US real interest rate, the US GDP, the volatility of asset returns and climate change.
This book is a review of the analytical methods required in most of the quantitative courses taught at MBA programs. Students with no technical background, or who have not studied mathematics since college or even earlier, may easily feel overwhelmed by the mathematical formalism that is typical of economics and finance courses. These students will benefit from a concise and focused review of the analytical tools that will become a necessary skill in their MBA classes. The objective of this book is to present the essential quantitative concepts and methods in a self-contained, non-technical, and intuitive way.
Financial globalization has increased the significance of methods used in the evaluation of country risk, one of the major research topics in economics and finance. Written by experts in the fields of multicriteria methodology, credit risk assessment, operations research, and financial management, this book develops a comprehensive framework for evaluating models based on several classification techniques that emerge from different theoretical directions. This book compares different statistical and data mining techniques, noting the advantages of each method, and introduces new multicriteria methodologies that are important to country risk modeling. Key topics include: (1) A review of country risk definitions and an overview of the most recent tools in country risk management, (2) In-depth analysis of statistical, econometric and non-parametric classification techniques, (3) Several real-world applications of the methodologies described throughout the text, (4) Future research directions for country risk assessment problems. This work is a useful toolkit for economists, financial managers, bank managers, operations researchers, management scientists, and risk analysts. Moreover, the book can also be used as a supplementary text for graduate courses in finance and financial risk management.
Applied Econometrics: A Practical Guide is an extremely user-friendly and application-focused book on econometrics. Unlike many econometrics textbooks which are heavily theoretical on abstractions, this book is perfect for beginners and promises simplicity and practicality to the understanding of econometric models. Written in an easy-to-read manner, the book begins with hypothesis testing and moves forth to simple and multiple regression models. It also includes advanced topics: Endogeneity and Two-stage Least Squares Simultaneous Equations Models Panel Data Models Qualitative and Limited Dependent Variable Models Vector Autoregressive (VAR) Models Autocorrelation and ARCH/GARCH Models Unit Root and Cointegration The book also illustrates the use of computer software (EViews, SAS and R) for economic estimating and modeling. Its practical applications make the book an instrumental, go-to guide for solid foundation in the fundamentals of econometrics. In addition, this book includes excerpts from relevant articles published in top-tier academic journals. This integration of published articles helps the readers to understand how econometric models are applied to real-world use cases.
In the last 20 years, econometric theory on panel data has developed rapidly, particularly for analyzing common behaviors among individuals over time. Meanwhile, the statistical methods employed by applied researchers have not kept up-to-date. This book attempts to fill in this gap by teaching researchers how to use the latest panel estimation methods correctly. Almost all applied economics articles use panel data or panel regressions. However, many empirical results from typical panel data analyses are not correctly executed. This book aims to help applied researchers to run panel regressions correctly and avoid common mistakes. The book explains how to model cross-sectional dependence, how to estimate a few key common variables, and how to identify them. It also provides guidance on how to separate out the long-run relationship and common dynamic and idiosyncratic dynamic relationships from a set of panel data. Aimed at applied researchers who want to learn about panel data econometrics by running statistical software, this book provides clear guidance and is supported by a full range of online teaching and learning materials. It includes practice sections on MATLAB, STATA, and GAUSS throughout, along with short and simple econometric theories on basic panel regressions for those who are unfamiliar with econometric theory on traditional panel regressions.
This book presents in detail methodologies for the Bayesian estimation of sing- regime and regime-switching GARCH models. These models are widespread and essential tools in n ancial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique. As this study aims to demonstrate, the Bayesian approach o ers an attractive alternative which enables small sample results, robust estimation, model discrimination and probabilistic statements on nonlinear functions of the model parameters. The author is indebted to numerous individuals for help in the preparation of this study. Primarily, I owe a great debt to Prof. Dr. Philippe J. Deschamps who inspired me to study Bayesian econometrics, suggested the subject, guided me under his supervision and encouraged my research. I would also like to thank Prof. Dr. Martin Wallmeier and my colleagues of the Department of Quantitative Economics, in particular Michael Beer, Roberto Cerratti and Gilles Kaltenrieder, for their useful comments and discussions. I am very indebted to my friends Carlos Ord as Criado, Julien A. Straubhaar, J er DEGREES ome Ph. A. Taillard and Mathieu Vuilleumier, for their support in the elds of economics, mathematics and statistics. Thanks also to my friend Kevin Barnes who helped with my English in this work. Finally, I am greatly indebted to my parents and grandparents for their support and encouragement while I was struggling with the writing of this t
This book presents a macroeconomic dynamic model a la Solow-Swan, including the market for labor, in a discrete time structure. The model is expanded to include expenditure on R&D and public expenditure on infrastructure. For each of the three models the results are shown in time series figures, which demonstrate that even small changes in the parameters produce responses in the time behavior of the main variables: from steady growth, to regular cycles, to chaotic-like time paths."
This book looks at the PPP persistence puzzle, and econometric aspects of exchange rate dynamics and their implications. It also explores the importance of exchange rate dynamics in the pass-through effects (PTE) and the econometric aspects of the exchange rates dynamics linked to structural shocks on different economies.
This book is written in light of the latest developments in the field of multidimensional poverty measurement. It includes clear presentations of more than a dozen different quantitative techniques and provides empirical illustrations based on data sources from developed or developing countries.
In Econometrics the author has provided a text that bridges the gap between classical econometrics (with an emphasis on linear methods such as OLS, GLS and instrumental variables) and some of the key research areas of the last few years, including sampling problems, nonparametric methods and panel data analysis. Designed for advanced undergraduate and postgraduate students of the subject, Econometrics provides rigorous, yet accessible, coverage of the subject. Key features include:
Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial Econometrics presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observations. It explores a wide range of alternative topics, including maximum likelihood and Bayesian estimation, various types of spatial regression specifications, and applied modeling situations involving different circumstances. Leaders in this field, the authors clarify the often-mystifying phenomenon of simultaneous spatial dependence. By presenting new methods, they help with the interpretation of spatial regression models, especially ones that include spatial lags of the dependent variable. The authors also examine the relationship between spatiotemporal processes and long-run equilibrium states that are characterized by simultaneous spatial dependence. MATLAB (R) toolboxes useful for spatial econometric estimation are available on the authors' websites. This work covers spatial econometric modeling as well as numerous applied illustrations of the methods. It encompasses many recent advances in spatial econometric models-including some previously unpublished results.
This title, first published in 1970, provides a comprehensive account of the public finance system in Britain. As well as providing a concise outline of the monetary system as a basis for the realistic understanding of public finance, the author also describes the pattern of government expenditure and revenue in the twentieth-century and goes on to give a detailed account of the taxation system up until April 1969. This title will be of interest to students of monetary economics.
This book provides an essential toolkit for all students wishing to know more about the modelling and analysis of financial data. Applications of econometric techniques are becoming increasingly common in the world of finance and this second edition of an established text covers the following key themes: - unit roots, cointegration and other developments in the study of time series models - time varying volatility models of the GARCH type and the stochastic volatility approach - analysis of shock persistence and impulse responses - Markov switching and Kalman filtering - spectral analysis - present value relations and rationality - discrete choice models - analysis of truncated and censored samples - panel data analysis. This updated edition includes new chapters which cover limited dependent variables and panel data. It continues to be an essential guide for all graduate and advanced undergraduate students of econometrics and finance.
Rechnet sich Freiheitsstrafe? Es ist schwierig, Freiheitsstrafen zu bewerten. Kosten und Nutzen sind komplex und beinhalten vielschichtige Dimensionen wie SA1/4hne, Ausschaltung, Abschreckung und Rehabilitation auf der einen Seite und betriebswirt- und gesellschaftliche Kosten auf der anderen. Erst ein mAglichst umfassendes Abbild der Kosten- und Nutzenkomponenten lAsst RA1/4ckschlA1/4sse auf den a žErfolg" - im Sinne von Schutz vor KriminalitAt - des Justizvollzugs zu. Die vorliegende Arbeit dokumentiert den Versuch, dieser Erfassung mittels einer bundesweiten Feldstudie nAher zu kommen. Die Auswertung der FragebAgen von ca. 1.800 Inhaftierten in rund 30 Haftanstalten, der Auskunft der zugehArigen Anstaltsleitungen und der Antworten von etwa 1.200 Personen aus einer ergAnzenden BevAlkerungsbefragung stellen a" zusammen mit einer umfangreichen Analyse von anstalts- und lAnderspezifischem Datenmaterial a" eine in diesem Umfang bisher einzigartige Evaluation des deutschen Strafvollzugs dar.
The complexity and volatility of energy markets creates strong demand for quantitative analysis and econometric techniques. This book offers an introduction to the state of the art in econometric modelling applied to the most pertinent issues in today's energy markets for a better understanding of the working of energy systems and energy economics.
Decision-theoretic ideas can structure the process of inference together with the decision-making that inference supports. Statistical decision theory is the sub-discipline of statistics which explores and develops this structure. Typically, discusion of decision theory within one discipline does not recognise that other disciplines may have considered the same or similar problems. This text, Volume 9 in the prestigious Kendall's Library of Statistics, provides an overview of the main ideas and concepts of statistical decision theory and sets it within the broader concept of decision theory, decision analysis and decision support as they are practised in many disciplines beyond statistics - including artificial intelligence, economics, operational research, philosophy and psychology.
"Palgrave Handbook of Econometrics" is comprised of landmark essays
by the world's leading scholars and provides authoritative and
definitive guidance in key areas of econometrics. With definitive
contributions on the subject, the Handbook is an essential source
of reference for professional econometricians, economists,
researchers and students.
This book provides a better understanding of how intellectual property can improve economic and business performance. It focuses on three particular issues: the valuation of patents, the transfer of knowledge, and the management of innovation and intellectual property. Scholars from leading worldwide institutions use quantitative methods and advanced survey techniques to explore the complex relationship between patents, innovation, venture capital and scientific research. The book focuses on three broad issues: the valuation of patents, the transfer of knowledge, and the management of innovation and intellectual property.
This book provides new evidence on the magnitude and sources of pay inequalities between women and men in European countries and New Zealand on the basis of micro data. Particular attention is devoted to job access and workplace practices, promotions and wage growth, sectoral affiliation and rent-sharing, and unobserved heterogeneity and dynamics.
This state-of-the-art account unifies material developed in journal articles over the last 35 years, with two central thrusts: It describes a broad class of system models that the authors call 'stochastic processing networks' (SPNs), which include queueing networks and bandwidth sharing networks as prominent special cases; and in that context it explains and illustrates a method for stability analysis based on fluid models. The central mathematical result is a theorem that can be paraphrased as follows: If the fluid model derived from an SPN is stable, then the SPN itself is stable. Two topics discussed in detail are (a) the derivation of fluid models by means of fluid limit analysis, and (b) stability analysis for fluid models using Lyapunov functions. With regard to applications, there are chapters devoted to max-weight and back-pressure control, proportionally fair resource allocation, data center operations, and flow management in packet networks. Geared toward researchers and graduate students in engineering and applied mathematics, especially in electrical engineering and computer science, this compact text gives readers full command of the methods. |
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