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Books > Business & Economics > Economics > Econometrics > General
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.
A careful basic theoretical and econometric analysis of the factors determining the real exchange rates of Canada, the U.K., Japan, France and Germany with respect to the United States is conducted. The resulting conclusion is that real exchange rates are almost entirely determined by real factors relating to growth and technology such as oil and commodity prices, international allocations of world investment across countries, and underlying terms of trade changes. Unanticipated money supply shocks, calculated in five alternative ways have virtually no effects. A Blanchard-Quah VAR analysis also indicates that the effects of real shocks predominate over monetary shocks by a wide margin. The implications of these facts for the conduct of monetary policy in countries outside the U.S. are then explored leading to the conclusion that all countries, to avoid exchange rate overshooting, have tended to automatically follow the same monetary policy as the United States. The history of world monetary policy is reviewed along with the determination of real exchange rates within the Euro Area.
This book investigates why economics makes less visible progress over time than scientific fields with a strong practical component, where interactions with physical technologies play a key role. The thesis of the book is that the main impediment to progress in economics is "false feedback", which it defines as the false result of an empirical study, such as empirical evidence produced by a statistical model that violates some of its assumptions. In contrast to scientific fields that work with physical technologies, false feedback is hard to recognize in economics. Economists thus have difficulties knowing where they stand in their inquiries, and false feedback will regularly lead them in the wrong directions. The book searches for the reasons behind the emergence of false feedback. It thereby contributes to a wider discussion in the field of metascience about the practices of researchers when pursuing their daily business. The book thus offers a case study of metascience for the field of empirical economics. The main strength of the book are the numerous smaller insights it provides throughout. The book delves into deep discussions of various theoretical issues, which it illustrates by many applied examples and a wide array of references, especially to philosophy of science. The book puts flesh on complicated and often abstract subjects, particularly when it comes to controversial topics such as p-hacking. The reader gains an understanding of the main challenges present in empirical economic research and also the possible solutions. The main audience of the book are all applied researchers working with data and, in particular, those who have found certain aspects of their research practice problematic.
Often applied econometricians are faced with working with data that is less than ideal. The data may be observed with gaps in it, a model may suggest variables that are observed at different frequencies, and sometimes econometric results are very fragile to the inclusion or omission of just a few observations in the sample. Papers in this volume discuss new econometric techniques for addressing these problems.
In this book leading German econometricians in different fields present survey articles of the most important new methods in econometrics. The book gives an overview of the field and it shows progress made in recent years and remaining problems.
Co-integration, equilibrium and equilibrium correction are key
concepts in modern applications of econometrics to real world
problems. This book provides direction and guidance to the now vast
literature facing students and graduate economists. Econometric
theory is linked to practical issues such as how to identify
equilibrium relationships, how to deal with structural breaks
associated with regime changes and what to do when variables are of
different orders of integration.
This book covers the econometric methodsnecessary for a practicing applied economist or data analyst. This requiresboth an understanding of statistical theory and how it is used in actual applications. Chapters 1 to 9 present the material concerned with basic statistical theory. Chapters 10 to 13 introduce a number of topics which form the basis of more advanced option modules, such as time series methods in applied econometrics. To get the most out of these topics, companion files include Excel datasets and 4-color figures. It includes pull down menus to graph the data, calculate sample statistics and estimate regression equations. FEATURES: Integration of econometrics methods with statistical foundations Worked examples of all models considered in the text Includes Excel datasheets to facilitate estimation and application of models Features instructor ancillaries for use as atextbook
* Includes many mathematical examples and problems for students to work directly with both standard and nonstandard models of behaviour to develop problem-solving and critical-thinking skills which are more valuable to students than memorizing content which will quickly be forgotten. * The applications explored in the text emphasise issues of inequality, social mobility, culture and poverty to demonstrate the impact of behavioral economics in areas which students are most passionate about. * The text has a standardized structure (6 parts, 3 chapters in each) which provides a clear and consistent roadmap for students taking the course.
This book presents selected peer-reviewed contributions from the International Conference on Time Series and Forecasting, ITISE 2018, held in Granada, Spain, on September 19-21, 2018. The first three parts of the book focus on the theory of time series analysis and forecasting, and discuss statistical methods, modern computational intelligence methodologies, econometric models, financial forecasting, and risk analysis. In turn, the last three parts are dedicated to applied topics and include papers on time series analysis in the earth sciences, energy time series forecasting, and time series analysis and prediction in other real-world problems. The book offers readers valuable insights into the different aspects of time series analysis and forecasting, allowing them to benefit both from its sophisticated and powerful theory, and from its practical applications, which address real-world problems in a range of disciplines. The ITISE conference series provides a valuable forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing computer science, mathematics, statistics and econometrics.
This book scientifically tests the assertion that accommodative monetary policy can eliminate the "crowd out" problem, allowing fiscal stimulus programs (such as tax cuts or increased government spending) to stimulate the economy as intended. It also tests to see if natural growth in th economy can cure the crowd out problem as well or better. The book is intended to be the largest scale scientific test ever performed on this topic. It includes about 800 separate statistical tests on the U.S. economy testing different parts or all of the period 1960 - 2010. These tests focus on whether accommodative monetary policy, which increases the pool of loanable resources, can offset the crowd out problem as well as natural growth in the economy. The book, employing the best scientific methods available to economists for this type of problem, concludes accommodate monetary policy could have, but until the quantitative easing program, Federal Reserve efforts to accommodate fiscal stimulus programs were not large enough to offset more than 23% to 44% of any one year's crowd out problem. That provides the science part of the answer as to why accommodative monetary policy didn't accommodate: too little of it was tried. The book also tests whether other increases in loanable funds, occurring because of natural growth in the economy or changes in the savings rate can also offset crowd out. It concludes they can, and that these changes tend to be several times as effective as accommodative monetary policy. This book's companion volume Why Fiscal Stimulus Programs Fail explores the policy implications of these results.
This book has taken form over several years as a result of a number of courses taught at the University of Pennsylvania and at Columbia University and a series of lectures I have given at the International Monetary Fund. Indeed, I began writing down my notes systematically during the academic year 1972-1973 while at the University of California, Los Angeles. The diverse character of the audience, as well as my own conception of what an introductory and often terminal acquaintance with formal econometrics ought to encompass, have determined the style and content of this volume. The selection of topics and the level of discourse give sufficient variety so that the book can serve as the basis for several types of courses. As an example, a relatively elementary one-semester course can be based on Chapters one through five, omitting the appendices to these chapters and a few sections in some of the chapters so indicated. This would acquaint the student with the basic theory of the general linear model, some of the prob lems often encountered in empirical research, and some proposed solutions. For such a course, I should also recommend a brief excursion into Chapter seven (logit and pro bit analysis) in view of the increasing availability of data sets for which this type of analysis is more suitable than that based on the general linear model."
China's reform and opening-up have contributed to its long-term and rapid economic development, resulting in a much stronger economic strength and much better life for its people. Meanwhile, the deepening economic integration between China and the world has resulted in an increasingly complex environment, growing influencing factors and severe challenges to China's economic development. Under the "new normal" of the Chinese economy, accurate analysis of the economic situation is essential to scientific decision-making, sustainable and healthy economic development and to build a moderately prosperous society in all respects. By applying statistical and national economic accounting methods, and based on detailed statistics and national economic accounting data, this book presents an in-depth analysis of the key economic fields, such as real estate economy, automotive industry, high-tech industry, investment, opening-up, income distribution of residents, economic structure, balance of payments structure and financial operation, since the reform and opening-up, especially in recent years. It aims to depict the performance and characteristics of these key economic fields and their roles in the development of national economy, thus providing useful suggestions for economic decision-making, and facilitating the sustainable and healthy development of the economy and the realization of the goal of building a moderately prosperous society in all respects.
Complex dynamics constitute a growing and increasingly important area as they offer a strong potential to explain and formalize natural, physical, financial and economic phenomena. This book pursues the ambitious goal to bring together an extensive body of knowledge regarding complex dynamics from various academic disciplines. Beyond its focus on economics and finance, including for instance the evolution of macroeconomic growth models towards nonlinear structures as well as signal processing applications to stock markets, fundamental parts of the book are devoted to the use of nonlinear dynamics in mathematics, statistics, signal theory and processing. Numerous examples and applications, almost 700 illustrations and numerical simulations based on the use of Matlab make the book an essential reference for researchers and students from many different disciplines who are interested in the nonlinear field. An appendix recapitulates the basic mathematical concepts required to use the book.
Originally published in 1971, this is a rigorous analysis of the economic aspects of the efficiency of public enterprises at the time. The author first restates and extends the relevant parts of welfare economics, and then illustrates its application to particular cases, drawing on the work of the National Board for Prices and Incomes, of which he was Deputy Chairman. The analysis is developed stage by stage, with the emphasis on applicability and ease of comprehension, rather than on generality or mathematical elegance. Financial performance, the second-best, the optimal degree of complexity of price structures and problems of optimal quality are first discussed in a static framework. Time is next introduced, leading to a marginal cost concept derived from a multi-period optimizing model. The analysis is then related to urban transport, shipping, gas and coal. This is likely to become a standard work of more general scope than the authors earlier book on electricity supply. It rests, however, on a similar combination of economic theory and high-level experience of the real problems of public enterprises.
This book provides a detailed introduction to the theoretical and methodological foundations of production efficiency analysis using benchmarking. Two of the more popular methods of efficiency evaluation are Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA), both of which are based on the concept of a production possibility set and its frontier. Depending on the assumed objectives of the decision-making unit, a Production, Cost, or Profit Frontier is constructed from observed data on input and output quantities and prices. While SFA uses different maximum likelihood estimation techniques to estimate a parametric frontier, DEA relies on mathematical programming to create a nonparametric frontier. Yet another alternative is the Convex Nonparametric Frontier, which is based on the assumed convexity of the production possibility set and creates a piecewise linear frontier consisting of a number of tangent hyper planes. Three of the papers in this volume provide a detailed and relatively easy to follow exposition of the underlying theory from neoclassical production economics and offer step-by-step instructions on the appropriate model to apply in different contexts and how to implement them. Of particular appeal are the instructions on (i) how to write the codes for different SFA models on STATA, (ii) how to write a VBA Macro for repetitive solution of the DEA problem for each production unit on Excel Solver, and (iii) how to write the codes for the Nonparametric Convex Frontier estimation. The three other papers in the volume are primarily theoretical and will be of interest to PhD students and researchers hoping to make methodological and conceptual contributions to the field of nonparametric efficiency analysis.
This two-volume work aims to present as completely as possible the methods of statistical inference with special reference to their economic applications. It is a well-integrated textbook presenting a wide diversity of models in a coherent and unified framework. The reader will find a description not only of the classical concepts and results of mathematical statistics, but also of concepts and methods recently developed for the specific needs of econometrics. Although the two volumes do not demand a high level of mathematical knowledge, they do draw on linear algebra and probability theory. The breadth of approaches and the extensive coverage of this two-volume work provide for a thorough and entirely self-contained course in modern economics. Volume 1 provides an introduction to general concepts and methods in statistics and econometrics, and goes on to cover estimation and prediction. Volume 2 focuses on testing, confidence regions, model selection, and asymptotic theory.
In this compelling 1995 book, David Hendry and Mary Morgan bring together the classic papers of the pioneer econometricians. Together, these papers form the foundations of econometric thought. They are essential reading for anyone seeking to understand the aims, method and methodology of econometrics and the development of this statistical approach in economics. However, because they are technically straightforward, the book is also accessible to students and non-specialists. An editorial commentary places the readings in their historical context and indicates the continuing relevance of these early, yet highly sophisticated, works for current econometric analysis. While this book provides a companion volume to Mary Morgan's acclaimed The History of Econometric Ideas, the editors' commentary both adds to that earlier volume and also provides a stand-alone and synthetic account of the development of econometrics.
This book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018, its main focus is on predictive techniques - which directly aim at predicting economic phenomena; and big data techniques - which enable us to handle the enormous amounts of data generated by modern computers in a reasonable time. The book also discusses the applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that employs mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. It is therefore important to develop data processing techniques that explicitly focus on prediction. The more data we have, the better our predictions will be. As such, these techniques are essential to our ability to process huge amounts of available data.
Predicting foreign exchange rates has presented a long-standing challenge for economists. However, the recent advances in computational techniques, statistical methods, newer datasets on emerging market currencies, etc., offer some hope. While we are still unable to beat a driftless random walk model, there has been serious progress in the field. This book provides an in-depth assessment of the use of novel statistical approaches and machine learning tools in predicting foreign exchange rate movement. First, it offers a historical account of how exchange rate regimes have evolved over time, which is critical to understanding turning points in a historical time series. It then presents an overview of the previous attempts at modeling exchange rates, and how different methods fared during this process. At the core sections of the book, the author examines the time series characteristics of exchange rates and how contemporary statistics and machine learning can be useful in improving predictive power, compared to previous methods used. Exchange rate determination is an active research area, and this book will appeal to graduate-level students of international economics, international finance, open economy macroeconomics, and management. The book is written in a clear, engaging, and straightforward way, and will greatly improve access to this much-needed knowledge in the field.
This book provides an up-to-date series of advanced chapters on applied financial econometric techniques pertaining the various fields of commodities finance, mathematics & stochastics, international macroeconomics and financial econometrics. International Financial Markets: Volume I provides a key repository on the current state of knowledge, the latest debates and recent literature on international financial markets. Against the background of the "financialization of commodities" since the 2008 sub-primes crisis, section one contains recent contributions on commodity and financial markets, pushing the frontiers of applied econometrics techniques. The second section is devoted to exchange rate and current account dynamics in an environment characterized by large global imbalances. Part three examines the latest research in the field of meta-analysis in economics and finance. This book will be useful to students and researchers in applied econometrics; academics and students seeking convenient access to an unfamiliar area. It will also be of great interest established researchers seeking a single repository on the current state of knowledge, current debates and relevant literature.
This open access book focuses on the concepts, tools and techniques needed to successfully model ever-changing time-series data. It emphasizes the need for general models to account for the complexities of the modern world and how these can be applied to a range of issues facing Earth, from modelling volcanic eruptions, carbon dioxide emissions and global temperatures, to modelling unemployment rates, wage inflation and population growth. Except where otherwise noted, this book is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0.
The combined efforts of the Physicists and the Economists in recent years in a- lyzing and modeling various dynamic phenomena in monetary and social systems have led to encouragingdevelopments,generally classi?ed under the title of Eco- physics. These developmentsshare a commonambitionwith the alreadyestablished ?eld of Quantitative Economics. This volume intends to offer the reader a glimpse of these two parallel initiatives by collecting review papers written by well-known experts in the respective research frontiers in one cover. This massive book presents a unique combination of research papers contributed almost equally by Physicists and Economists. Additional contributions from C- puter Scientists and Mathematicians are also included in this volume. It consists of two parts: The ?rst part concentrates on econophysics of games and social choices and is the proceedings of the Econophys-Kolkata IV workshop held at the Indian Statistical Institute and the Saha Institute of Nuclear Physics, both in Kolkata, d- ing March 9-13, 2009. The second part consists of contributionsto quantitative e- nomics by experts in connection with the Platinum Jubilee celebration of the Indian Statistical Institute. In this connectiona Forewordfor the volume, written by Sankar K. Pal, Director of the Indian Statistical Institute, is put forth. Both parts specialize mostly on frontier problems in games and social choices. The?rst partofthebookdealswith severalrecentdevelopmentsineconophysics. Game theory is integral to the formulation of modern economic analysis. Often games display a situation where the social optimal could not be reached as a - sult of non co-operation between different agents.
Volumes 45a and 45b of Advances in Econometrics honor Professor Joon Y. Park, who has made numerous and substantive contributions to the field of econometrics over a career spanning four decades since the 1980s and counting. This second volume, Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, focuses on econometric applications related, some closely and some very loosely, to Professor Park’s more recent work before concluding with a retrospective summarizing four decades of Advances in Econometrics.
Focuses on the assumptions underlying the algorithms rather than their statistical properties Presents cutting-edge analysis of factor models and finite mixture models. Uses a hands-on approach to examine the assumptions made by the models and when the models fail to estimate accurately Utilizes interesting real-world data sets that can be used to analyze important microeconomic problems Introduces R programming concepts throughout the book. Includes appendices that discuss many of the concepts introduced in the book, as well as measures of uncertainty in microeconometrics.
It is commonly believed that macroeconomic models are not useful for policy analysis because they do not take proper account of agents' expectations. Over the last decade, mainstream macroeconomic models in the UK and elsewhere have taken on board the Rational Expectations Revolution' by explicitly incorporating expectations of the future. In principle, one can perform the same technical exercises on a forward expectations model as on a conventional model -- and more! Rational Expectations in Macroeconomic Models deals with the numerical methods necessary to carry out policy analysis and forecasting with these models. These methods are often passed on by word of mouth or confined to obscure journals. Rational Expectations in Macroeconomic Models brings them together with applications which are interesting in their own right. There is no comparable textbook in the literature. The specific subjects include: (i) solving for model consistent expectations; (ii) the choice of terminal condition and time horizon; (iii) experimental design: i.e., the effect of temporary vs permanent, anticipated vs. unanticipated shocks; deterministic vs. stochastic, dynamic vs. static simulation; (iv) the role of exchange rate; (v) optimal control and inflation-output tradeoffs. The models used are those of the Liverpool Research Group in Macroeconomics, the London Business School and the National Institute of Economic and Social Research. |
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