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Books > Business & Economics > Economics > Econometrics > General
Technical analysis points out that the best source of information to beat the market is the price itself. Introducing readers to technical analysis in a more succinct and practical way, Ramlall focuses on the key aspects, benefits, drawbacks, and the main tools of technical analysis. Chart Patterns, Point & Figure, Stochastics, Sentiment indicators, Elliot Wave Theory, RSI, R, Candlesticks and more are covered, including both the concepts and the practical applications. Also including programming technical analysis tools, this book is a valuable tool for both researchers and practitioners.
Originally published in 1981. Discrete-choice modelling is an area of econometrics where significant advances have been made at the research level. This book presents an overview of these advances, explaining the theory underlying the model, and explores its various applications. It shows how operational choice models can be used, and how they are particularly useful for a better understanding of consumer demand theory. It discusses particular problems connected with the model and its use, and reports on the authors' own empirical research. This is a comprehensive survey of research developments in discrete choice modelling and its applications.
Originally published in 1974. This book provides a rigorous and detailed introductory treatment of the theory of difference equations and their applications in the construction and analysis of dynamic economic models. It explains the theory of linear difference equations and various types of dynamic economic models are then analysed. Including plenty of examples of application throughout the text, it will be of use to those working in macroeconomics and econometrics.
This book serves not only as an introduction, but also as an
advanced text and reference source in the field of deterministic
optimal control systems governed by ordinary differential
equations. It also includes an introduction to the classical
calculus of variations.
This book reports the results of five empirical studies undertaken in the early seventies by a collaboration headed by Professor Morishima. It deals with applications of the general equilibrium models whose theoretical aspects have been one of Professor Morishima's main interests. Four main econometric models are constructed for the USA, the UK, and Japan. These are used as a basis for the discussion of various topics in economic theory, such as: the existence and stability or instability of the neoclassical path of full employment growth equilibrium and a von Neumann-type path of balanced growth at constant proces; the antimony between price-stability and full employment; the Samuelson-LeChatelier principle; the theory of the balanced-budget multiplier; the three Hicksian laws of the gross substitutes system; the Brown-Jones super-multipliers of international trade, and so on. In addition, this 1972 work makes a quantitative evaluation for the US economy of monetary and fiscal policies as short-run measures for achieving full employment; the effectiveness of built-in flexibility of taxes in the UK economy is discussed; and estimates are made of the rapid decrease in disguised unemployment in post-war Japan.
An accessible, contemporary introduction to the methods for determining cause and effect in the social sciences "Causation versus correlation has been the basis of arguments-economic and otherwise-since the beginning of time. Causal Inference: The Mixtape uses legit real-world examples that I found genuinely thought-provoking. It's rare that a book prompts readers to expand their outlook; this one did for me."-Marvin Young (Young MC) Causal inference encompasses the tools that allow social scientists to determine what causes what. In a messy world, causal inference is what helps establish the causes and effects of the actions being studied-for example, the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the influence on economic growth of introducing malaria nets in developing regions. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and the Stata programming languages.
Computational Economics: A concise introduction is a comprehensive textbook designed to help students move from the traditional and comparative static analysis of economic models, to a modern and dynamic computational study. The ability to equate an economic problem, to formulate it into a mathematical model and to solve it computationally is becoming a crucial and distinctive competence for most economists. This vital textbook is organized around static and dynamic models, covering both macro and microeconomic topics, exploring the numerical techniques required to solve those models. A key aim of the book is to enable students to develop the ability to modify the models themselves so that, using the MATLAB/Octave codes provided on the book and on the website, students can demonstrate a complete understanding of computational methods. This textbook is innovative, easy to read and highly focused, providing students of economics with the skills needed to understand the essentials of using numerical methods to solve economic problems. It also provides more technical readers with an easy way to cope with economics through modelling and simulation. Later in the book, more elaborate economic models and advanced numerical methods are introduced which will prove valuable to those in more advanced study. This book is ideal for all students of economics, mathematics, computer science and engineering taking classes on Computational or Numerical Economics.
This book deals with microeconomic theory as it concerns general
economic equilibrium and the implications for prices and resource
allocation.
This Fourth Edition updates the "Solutions Manual for Econometrics" to match the Sixth Edition of the Econometrics textbook. It adds problems and solutions using latest software versions of Stata and EViews. Special features include empirical examples replicated using EViews, Stata as well as SAS. The book offers rigorous proofs and treatment of difficult econometrics concepts in a simple and clear way, and provides the reader with both applied and theoretical econometrics problems along with their solutions. These should prove useful to students and instructors using this book.
An accessible treatment of Monte Carlo methods, techniques, and applications in the field of finance and economics Providing readers with an in-depth and comprehensive guide, the Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics presents a timely account of the applicationsof Monte Carlo methods in financial engineering and economics. Written by an international leading expert in thefield, the handbook illustrates the challenges confronting present-day financial practitioners and provides various applicationsof Monte Carlo techniques to answer these issues. The book is organized into five parts: introduction andmotivation; input analysis, modeling, and estimation; random variate and sample path generation; output analysisand variance reduction; and applications ranging from option pricing and risk management to optimization. The Handbook in Monte Carlo Simulation features: * An introductory section for basic material on stochastic modeling and estimation aimed at readers who may need a summary or review of the essentials * Carefully crafted examples in order to spot potential pitfalls and drawbacks of each approach * An accessible treatment of advanced topics such as low-discrepancy sequences, stochastic optimization, dynamic programming, risk measures, and Markov chain Monte Carlo methods * Numerous pieces of R code used to illustrate fundamental ideas in concrete terms and encourage experimentation The Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics is a complete reference for practitioners in the fields of finance, business, applied statistics, econometrics, and engineering, as well as a supplement for MBA and graduate-level courses on Monte Carlo methods and simulation.
Dynamic factor models (DFM) constitute an active and growing area of research, both in econometrics, in macroeconomics, and in finance. Many applications lie at the center of policy questions raised by the recent financial crises, such as the connections between yields on government debt, credit risk, inflation, and economic growth. This volume collects a key selection of up-to-date contributions that cover a wide range of issues in the context of dynamic factor modeling, such as specification, estimation, and application of DFMs. Examples include further developments in DFM for mixed-frequency data settings, extensions to time-varying parameters and structural breaks, for multi-level factors associated with subsets of variables, in factor augmented error correction models, and in many other related aspects. A number of contributions propose new estimation procedures for DFM, such as spectral expectation-maximization algorithms and Bayesian approaches. Numerous applications are discussed, including the dating of business cycles, implied volatility surfaces, professional forecaster survey data, and many more.
This is the first 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 first volume includes theoretical and applied papers addressing topics such as dynamic mechanism design, agency problems, and networks.
Theory and application of a variety of mathematical techniques in
economics are presented in this volume. Topics discussed include:
martingale methods, stochastic processes, optimal stopping, the
modeling of uncertainty using a Wiener process, Ito's Lemma as a
tool of stochastic calculus, and basic facts about stochastic
differential equations. The notion of stochastic ability and the
methods of stochastic control are discussed, and their use in
economic theory and finance is illustrated with numerous
applications.
This title, first published in 1984, is a contribution to applied international trade theory. The author explores the specification and estimation of a multisector general equilibrium model of the open economy. The model is formulated with the aim of assessing empirically the effects of three key policy variables on trade flows, domestic prices, and the trade balance. The policy variables with which the author is concerned are the rate of growth of the stock of domestic credit, commercial policy, as represented by tariffs, and, finally, the exchange rate. This title will be of interest to students of economics.
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.
Originating from the International Network for Economic Method conference, hosted by the Erasmus Institute for Economics and Philosophy (EIPE) at the Erasmus University Rotterdam in 2013, this book chooses key themes that reflect on fascinating new developments in the philosophy of economics. Contributions discuss new avenues and debates in important and upcoming areas, such as the philosophy of economic policy making, decision theory, ethics, and new questions in economic methodology. The book offers an excellent insight into cutting edge research in these fields that are about to shape the future of the philosophy of economics. This book was originally published as a special issue of The Journal of Economic Methodology.
Originally published in 1981. Discrete-choice modelling is an area of econometrics where significant advances have been made at the research level. This book presents an overview of these advances, explaining the theory underlying the model, and explores its various applications. It shows how operational choice models can be used, and how they are particularly useful for a better understanding of consumer demand theory. It discusses particular problems connected with the model and its use, and reports on the authors' own empirical research. This is a comprehensive survey of research developments in discrete choice modelling and its applications.
These essays honor Professor Peter C.B. Phillips of Yale University and his many contributions to the field of econometrics. Professor Phillips's research spans many topics in econometrics including: non-stationary time series and panel models partial identification and weak instruments Bayesian model evaluation and prediction financial econometrics and finite-sample statistical methods and results. The papers in this volume reflect additions to and amplifications of many of Professor Phillips' research contributions. Some of the topics discussed in the volume include panel macro-econometric modeling, efficient estimation and inference in difference-in-difference models, limiting and empirical distributions of IV estimates when some of the instruments are endogenous, the use of stochastic dominance techniques to examine conditional wage distributions of incumbents and newly hired employees, long-horizon predictive tests in financial markets, new developments in information matrix testing, testing for co-integration in Markov switching error correction models, and deviation information criteria for comparing vector autoregressive models.
The volume contains articles that should appeal to readers with computational, modeling, theoretical, and applied interests. Methodological issues include parallel computation, Hamiltonian Monte Carlo, dynamic model selection, small sample comparison of structural models, Bayesian thresholding methods in hierarchical graphical models, adaptive reversible jump MCMC, LASSO estimators, parameter expansion algorithms, the implementation of parameter and non-parameter-based approaches to variable selection, a survey of key results in objective Bayesian model selection methodology, and a careful look at the modeling of endogeneity in discrete data settings. Important contemporary questions are examined in applications in macroeconomics, finance, banking, labor economics, industrial organization, and transportation, among others, in which model uncertainty is a central consideration.
Microsimulation Modelling involves the application of simulation methods to micro data for the purposes of evaluating the effectiveness and improving the design of public policy. The field has existed for over 50 years and has been applied to many different policy areas and is a methodology that is applied within both government and academia. This handbook brings together leading authors in the field to describe and discuss the main current issues within the field. The handbook provides an overview of current developments across each of the sub-fields of microsimulation modelling such as tax-benefit, pensions, spatial, health, labour, consumption, transport and land use policy as well as macro-micro, environmental and demographic issues. It focuses also on the modelling different micro units such as households, firms and farms. Each chapter discusses its sub-field under the following headings: the main methodologies of the sub-field; survey the literature in the area; critique the literature; and propose future directions for research within the sub-field.
This book comprises ten carefully chosen, up-to-date and
comprehensive surveys on econometrics taken from the prestigious
Journal of Economic Surveys. The contributions are accessible to
technically competent students and those wishing to develop an
interest in current econometric issues.
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.
Vector autoregressive (VAR) models are among the most widely used econometric tools in the fields of macroeconomics and financial economics. Much of what we know about the response of the economy to macroeconomic shocks and about how various shocks have contributed to the evolution of macroeconomic and financial aggregates is based on VAR models. VAR models also have been used successfully for economic and business forecasting, for modelling risk and volatility, and for the construction of forecast scenarios. Since the introduction of VAR models by C.A. Sims in 1980, the VAR methodology has continuously evolved. Even today important extensions and reinterpretations of the VAR framework are being developed. Examples include VAR models for mixed-frequency data, VAR models as approximations to DSGE models, factor-augmented VAR models, new tools for the identification of structural shocks in VAR models, panel VAR approaches, and time-varying parameter VAR models. This volume collects contributions from some of the leading VAR experts in the world on VAR methods and applications. Each chapter highlights and synthesizes a new development in this literature in a way that is accessible to practitioners, to graduate students, and to readers in other fields.
Analyze key indicators more accurately to make smarter market moves The Economic Indicator Handbook helps investors more easily evaluate economic trends, to better inform investment decision making and other key strategic financial planning. Written by a Bloomberg Senior Economist, this book presents a visual distillation of the indicators every investor should follow, with clear explanation of how they're measured, what they mean, and how that should inform investment thinking. The focus on graphics, professional application, Bloomberg terminal functionality, and practicality makes this guide a quick, actionable read that could immediately start improving investment outcomes. Coverage includes gross domestic product, employment data, industrial production, new residential construction, consumer confidence, retail and food service sales, and commodities, plus guidance on the secret indicators few economists know or care about. Past performance can predict future results if you know how to read the indicators. Modern investing requires a careful understanding of the macroeconomic forces that lift and topple markets on a regular basis, and how they shift to move entire economies. This book is a visual guide to recognizing these forces and tracking their behavior, helping investors identify entry and exit points that maximize profit and minimize loss. * Quickly evaluate economic trends * Make more informed investment decisions * Understand the most essential indicators * Translate predictions into profitable actions Savvy market participants know how critical certain indicators are to the formulation of a profitable, effective market strategy. A daily indicator check can inform day-to-day investing, and long-term tracking can result in a stronger, more robust portfolio. For the investor who knows that better information leads to better outcomes, The Economic Indicator Handbook is an exceptionally useful resource. |
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