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Books > Business & Economics > Economics > Econometrics
In these two volumes, a group of distinguished economists debate the way in which evidence, in particular econometric evidence, can and should be used to relate macroeconomic theories to the real world. Topics covered include the business cycle, monetary policy, economic growth, the impact of new econometric techniques, the IS-LM model, the labour market, new Keynesian macroeconomics, and the use of macroeconomics in official documents.
An Introduction to Wavelets and Other Filtering Methods in Finance
and Economics presents a unified view of filtering techniques with
a special focus on wavelet analysis in finance and economics. It
emphasizes the methods and explanations of the theory that
underlies them. It also concentrates on exactly what wavelet
analysis (and filtering methods in general) can reveal about a time
series. It offers testing issues which can be performed with
wavelets in conjunction with the multi-resolution analysis. The
descriptive focus of the book avoids proofs and provides easy
access to a wide spectrum of parametric and nonparametric filtering
methods. Examples and empirical applications will show readers the
capabilities, advantages, and disadvantages of each method.
The Handbook is a definitive reference source and teaching aid for
Since the middle of the twentieth century, economists have invested great resources into using statistical evidence to relate macroeconomic theories to the real world, and many new econometric techniques have been employed. In these two volumes, a distinguished group of economic theorists, econometricians, and economic methodologists examine how evidence has been used and how it should be used to understand the real world. Volume 1 focuses on the contribution of econometric techniques to understanding the macroeconomic world. It covers the use of evidence to understand the business cycle, the operation of monetary policy, and economic growth. A further section offers assessments of the overall impact of recent econometric techniques such as cointegration and unit roots. Volume 2 focuses on the labour market and economic policy, with sections covering the IS-LM model, the labour market, new Keynesian macroeconomics, and the use of macroeconomics in official documents (in both the USA and the EU). These volumes will be valuable to advanced undergraduates, graduate students, and practitioners for their clear presentation of opposing perspectives on macroeconomics and how evidence should be used. The chapters are complemented by discussion sections revealing the perspectives of other contributors on the methodological issues raised.
In the last half of the 20th Century, the world economy has benefited from a globalization process driven by the enlightened confluence of technology, innovation, trade, and foreign direct investment. This book broadens our understanding of that process. Opening with a review of current global economic metrics and the significant differences between advanced and developing nations, the book goes on to discuss the globalization paradigm and the forces driving it. Discussing the importance of new ideas and new technology in continued economic growth, the volume shows how the protection of intellectual property encourages innovation. Also covering the evolution of international trade, the book reviews trade distortions from both external and internal sources, comparing trade on a multilateral, non-discriminatory basis with alternative trade practices, such as free trade and custom unions. The work also reviews the origins and functions of the new World Trade Organization. Describing the rapidly growing practice of foreign direct investment, the book shows how FDI is closely linked to international trade and concludes with a review of the important function FDI can play in the bundling and delivery of the resources required for accelerated economic development of the emerging world.
A Probability Metrics Approach to Financial Risk Measures relates the field of probability metrics and risk measures to one another and applies them to finance for the first time. * Helps to answer the question: which risk measure is best for a given problem? * Finds new relations between existing classes of risk measures * Describes applications in finance and extends them where possible * Presents the theory of probability metrics in a more accessible form which would be appropriate for non-specialists in the field * Applications include optimal portfolio choice, risk theory, and numerical methods in finance * Topics requiring more mathematical rigor and detail are included in technical appendices to chapters
Handbook of Computational Economics: Heterogeneous Agent Modeling, Volume Four, focuses on heterogeneous agent models, emphasizing recent advances in macroeconomics (including DSGE), finance, empirical validation and experiments, networks and related applications. Capturing the advances made since the publication of Volume Two (Tesfatsion & Judd, 2006), it provides high-level literature with sections devoted to Macroeconomics, Finance, Empirical Validation and Experiments, Networks, and other applications, including Innovation Diffusion in Heterogeneous Populations, Market Design and Electricity Markets, and a final section on Perspectives on Heterogeneity.
Distributional issues may not have always been among the main
concerns of the economic profession. Today, in the beginning of the
2000s, the position is different. During the last quarter of a
century, economic growth proved to be unsteady and rather slow on
average. The situation of those at the bottom ceased to improve
regularly as in the preceding fast growth and full-employment
period. Europe has seen prolonged unemployment and there has been
widening wage dispersion in a number of OECD countries. Rising
affluence in rich countries coexists, in a number of such
countries, with the persistence of poverty. As a consequence, it is
difficult nowadays to think of an issue ranking high in the public
economic debate without some strong explicit distributive
implications. Monetary policy, fiscal policy, taxes, monetary or
trade union, privatisation, price and competition regulation, the
future of the Welfare State are all issues which are now often
perceived as conflictual because of their strong redistributive
content.
For more information on the Handbooks in Economics series, please see our home page on http: //www.elsevier.nl/locate/hes
The Economics and Econometrics of the Energy-Growth Nexus recognizes that research in the energy-growth nexus field is heterogeneous and controversial. To make studies in the field as comparable as possible, chapters cover aggregate energy and disaggregate energy consumption and single country and multiple country analysis. As a foundational resource that helps researchers answer fundamental questions about their energy-growth projects, it combines theory and practice to classify and summarize the literature and explain the econometrics of the energy-growth nexus. The book provides order and guidance, enabling researchers to feel confident that they are adhering to widely accepted assumptions and procedures.
This contributed volume applies cliometric methods to the study of family and households in order to derive global patterns and determine their impact on economic development. Family and households are a fundamental feature of societies and economies. They are found throughout history and are the place where key decisions on fertility, labour force participation, education, consumption are made. This is especially relevant for the position of women. The book gathers key insights from a variety of fields - economics, history, demography, anthropology, biology - to shed light on the relation between family organisation and the long-term process of economic development.
This textbook offers a comprehensive overview of the main developments in game theory since the 1950s. It provides a wide variety of examples and exercises, mostly drawn from applications in economics, to illustrate key concepts and ideas in the field. The book should prove an invaluable reference tool for teachers, students, and researchers of microeconomics and game theory.
This book studies the evolution of the middle class in Russia after the fall of the Soviet Union. Using data from the RLMS (Russian Longitudinal Monitoring Survey), the volume covers the period of transition (1991-2008) during which many fundamental economic reforms were implemented. The first part of the book is devoted to a discussion of the concept of middle class and a description of the economic situation in Russia during the transition period. Particular attention is given to variations in the distribution of Russian incomes and the estimated importance of the middle class. The second part of the book focuses on the link between the middle class and income bipolarization. The third and last section of the book uses the semiparametric "mixture model" to discover how many different groups may be derived from the income distribution in Russia, as well as what the main socio-economic and demographic characteristics of those groups are. The mobility of households into and out of the middle class during the transition period is also studied in hopes of determining the factors that contribute to such mobility. Using rigorous empirical methods, this volume sheds light on a relatively unstudied economic group and provides insight for countries which are about to enter a transition period. As such, this book will be of great interest to researchers in economics and inequality as well as professionals and practitioners working with international organizations.
This book presents a broad range of statistical techniques to address emerging needs in the field of repeated measures. It also provides a comprehensive overview of extensions of generalized linear models for the bivariate exponential family of distributions, which represent a new development in analysing repeated measures data. The demand for statistical models for correlated outcomes has grown rapidly recently, mainly due to presence of two types of underlying associations: associations between outcomes, and associations between explanatory variables and outcomes. The book systematically addresses key problems arising in the modelling of repeated measures data, bearing in mind those factors that play a major role in estimating the underlying relationships between covariates and outcome variables for correlated outcome data. In addition, it presents new approaches to addressing current challenges in the field of repeated measures and models based on conditional and joint probabilities. Markov models of first and higher orders are used for conditional models in addition to conditional probabilities as a function of covariates. Similarly, joint models are developed using both marginal-conditional probabilities as well as joint probabilities as a function of covariates. In addition to generalized linear models for bivariate outcomes, it highlights extended semi-parametric models for continuous failure time data and their applications in order to include models for a broader range of outcome variables that researchers encounter in various fields. The book further discusses the problem of analysing repeated measures data for failure time in the competing risk framework, which is now taking on an increasingly important role in the field of survival analysis, reliability and actuarial science. Details on how to perform the analyses are included in each chapter and supplemented with newly developed R packages and functions along with SAS codes and macro/IML. It is a valuable resource for researchers, graduate students and other users of statistical techniques for analysing repeated measures data.
This book, dedicated to Winfried Stute on the occasion of his 70th birthday, presents a unique collection of contributions by leading experts in statistics, stochastic processes, mathematical finance and insurance. The individual chapters cover a wide variety of topics ranging from nonparametric estimation, regression modelling and asymptotic bounds for estimators, to shot-noise processes in finance, option pricing and volatility modelling. The book also features review articles, e.g. on survival analysis.
Probability, Statistics and Econometrics provides a concise, yet rigorous, treatment of the field that is suitable for graduate students studying econometrics, very advanced undergraduate students, and researchers seeking to extend their knowledge of the trinity of fields that use quantitative data in economic decision-making. The book covers much of the groundwork for probability and inference before proceeding to core topics in econometrics. Authored by one of the leading econometricians in the field, it is a unique and valuable addition to the current repertoire of econometrics textbooks and reference books.
This is the second volume in a two-part series on frontiers in regional research. It identifies methodological advances as well as trends and future developments in regional systems modelling and open science. Building on recent methodological and modelling advances, as well as on extensive policy-analysis experience, top international regional scientists identify and evaluate emerging new conceptual and methodological trends and directions in regional research. Topics such as dynamic interindustry modelling, computable general equilibrium models, exploratory spatial data analysis, geographic information science, spatial econometrics and other advanced methods are the central focus of this book. The volume provides insights into the latest developments in object orientation, open source, and workflow systems, all in support of open science. It will appeal to a wide readership, from regional scientists and economists to geographers, quantitatively oriented regional planners and other related disciplines. It offers a source of relevant information for academic researchers and policy analysts in government, and is also suitable for advanced teaching courses on regional and spatial science, economics and political science.
This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series. The contributions were originally presented at the International Work-Conference on Time Series, ITISE 2016, held in Granada, Spain, June 27-29, 2016. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing the disciplines of computer science, mathematics, statistics and econometrics.
This contributed volume applies spatial and space-time econometric methods to spatial interaction modeling. The first part of the book addresses general cutting-edge methodological questions in spatial econometric interaction modeling, which concern aspects such as coefficient interpretation, constrained estimation, and scale effects. The second part deals with technical solutions to particular estimation issues, such as intraregional flows, Bayesian PPML and VAR estimation. The final part presents a number of empirical applications, ranging from interregional tourism competition and domestic trade to space-time migration modeling and residential relocation.
The two-volume book studies the economic and industrial development of Japan and China in modern times and draws distinctions between the different paths of industrialization and economic modernization taken in the two countries, based on statistical materials, quantitative analysis and multivariate statistical analysis. The first volume analyses the relationship between technological innovation and economic development in Japan before World War II and sheds light on technological innovation in the Japanese context with particular emphasis on the importance of the patent system. The second volume studies the basic conditions and overall economic development of industrial development, chiefly during the period of the Republic of China (1912-1949), taking a comparative perspective and bringing the case of modern Japan into the discussion. The book will appeal to academics and general readers interested in economic development and the modern economic history of East Asia, development economics, as well as industrial and technological history.
This book presents a comprehensive study of multivariate time series with linear state space structure. The emphasis is put on both the clarity of the theoretical concepts and on efficient algorithms for implementing the theory. In particular, it investigates the relationship between VARMA and state space models, including canonical forms. It also highlights the relationship between Wiener-Kolmogorov and Kalman filtering both with an infinite and a finite sample. The strength of the book also lies in the numerous algorithms included for state space models that take advantage of the recursive nature of the models. Many of these algorithms can be made robust, fast, reliable and efficient. The book is accompanied by a MATLAB package called SSMMATLAB and a webpage presenting implemented algorithms with many examples and case studies. Though it lays a solid theoretical foundation, the book also focuses on practical application, and includes exercises in each chapter. It is intended for researchers and students working with linear state space models, and who are familiar with linear algebra and possess some knowledge of statistics.
The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted form this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are seen in finance (banking, brokerage, insurance), marketing (customer relationships, retailing, logistics, travel), as well as in manufacturing, health care, fraud detection, home-land security, and law enforcement.
This clearly written volume provides an accessible examination of the nature of disequilibrium models. Srivastava and Rao contend that existing software packages can be easily used to implement some of the relatively simple methods. This study furnishes a substantial grounding in the economics and econometrics of the disequilibrium models by reviewing the Walrasian general equilibrium theory and by comparing the two genuine alternative frameworks for analyzing economic phenomena. Srivastava and Rao demonstrate that while both frameworks share a common set of basic assumptions about the behavior of the economic decision making units, they differ in their assumptions about the ability of the markets to attain equilibrium within a single trading period and whether trading can take place out of equilibrium. The first two chapters provide background, divide the existing methods of estimation of disequilibrium models into two categories, and explain the estimation methods for the basic model that belongs to the first category. The next three chapters explain the estimation methods for the directional, quantitative, and generalized stochastic models of the second category. Various methods for testing and evaluating equilibrium versus disequilibrium hypotheses are investigated in chapter six. Chapter seven examines the assumptions on which the models are formulated and discusses some alternative specifications of the disequilibrium models. The final chapters provide analyses of the economics and econometrics of the multi-market models and illustrate how some simple estimation methods can be used to estimate the disequilibrium formulations of the U. S. labor market. This is an important volume that will aid in the achievement of methodological consistency between analytical philosophy and the estimation methods in the applied work on disequilibrium economics.
State Profiles 2018: The Population and Economy of Each U.S. State provides a wealth of current, authoritative, and comprehensive data on key demographic and economic indicators for each U.S. state and the District of Columbia. Each state is covered by a compact standardized chapter that allows for easy comparisons and timely analysis between the states. A ten-page profile for each U.S. state plus the District of Columbia provides reliable, up-to-date information on a wide range of topics, including: population, labor force, income and poverty, government finances, crime, education, health insurance coverage, voting, marital status, migration, and more. If you want a single source of key demographic and economic data on each of the U.S. states, there is no other book like State Profiles. This book provides an overview of the U.S. economy which provides a framework for understanding the state information. This book is primarily useful for public, school, and college and university libraries, as well as for economic and sociology departments. However, anyone needing state-level information-students, state officials, investors, economic analysts, concerned citizens-will find State Profiles wealth of data and analysis absolutely essential! A LOOK AT THE STATES South Carolina once again had the highest rate of traffic fatalities in the U.S. in 2016, with 1.88 deaths per 100 million vehicle miles driven. In 2016, 16.6 of Texans did not have health insurance, making it the state with the highest percent of uninsured residents. At more than twice the national average, West Virginia had the highest rate of drug overdose deaths in 2016 (52.0 deaths per 100,000 residents) Of all the states, Utah had the highest percent of children in 2017, with 29.9 percent of its population under age 18. Maryland's 2016 median household income of $78,945 was the highest in the country, and its poverty rate of 9.7 percent was the 3rd lowest among the states. |
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