The book is a collection of essays in honour of Clive Granger. The chapters are by some of the world's leading econometricians, all of whom have collaborated with or studied with (or both) Clive Granger. Central themes of Granger's work are reflected in the book with attention to tests for unit roots and cointegration, tests of misspecification, forecasting models and forecast evaluation, non-linear and non-parametric econometric techniques, and overall, a careful blend of practical empirical work and strong theory. The book shows the scope of Granger's research and the range of the profession that has been influenced by his work.

This study, first published in 1979, examines and contrasts two concepts of credit rationing. The first concept takes the relevant price of credit to be the explicit interest rate on the loan and defines the demand for credit as the amount an individual borrower would like to receive at that rate. Under the alternative definition, the price of credit consists of the complete set of loan terms confronting a class of borrowers with given characteristics, while the demand for credit equals the total number of loan which members of the class would like to receive at those terms. This title will be of interest to students of monetary economics.

This study, first published in 1994, is intended to deepen the readers understanding of the phenomenon of equilibrium credit rationing in two areas. The first area concerns the form that equilibrium credit rationing assumes and its importance in determining the behaviour of interest rates. The second concerns the role of equilibrium credit rationing in transmitting monetary shocks to the real sector. This title will be of interest to students of monetary economics.

There are many problems regarding poverty, inequality and growth in developing countries in Asia and Africa. Policy makers at the national level and at international institutions such as the United Nations, World Bank, International Monetary Fund and others have implemented various policies in order to decrease poverty and inequality. This book provides empirical observations on Asian countries and Africa. Each chapter provides theoretical and empirical analysis on regional case studies with an emphasis on policy implications. The book will be of use to many who wish to assess and improve policies in developing countries and mitigate poverty and inequality, and stimulate growth, by drawing on relevant empirical research and economic theories. Clearly, there have been numerous policy failures and the book aims to provide a basis for improving policies and outcomes based on relevant empirical observations.

Originally published in 1984. This book examines two important dimensions of efficiency in the foreign exchange market using econometric techniques. It responds to the macroeconomics trend to re-examining the theories of exchange rate determination following the erratic behaviour of exchange rates in the late 1970s. In particular the text looks at the relation between spot and forward exchange rates and the term structure of the forward premium, both of which require a joint test of market efficiency and the equilibrium model. Approaches used are the regression of spot rates on lagged forward rates and an explicit time series analysis of the spot and forward rates, using data from Canada, the United Kingdom, the Netherlands, Switzerland and Germany.

This short book introduces the main ideas of statistical inference in a way that is both user friendly and mathematically sound. Particular emphasis is placed on the common foundation of many models used in practice. In addition, the book focuses on the formulation of appropriate statistical models to study problems in business, economics, and the social sciences, as well as on how to interpret the results from statistical analyses. The book will be useful to students who are interested in rigorous applications of statistics to problems in business, economics and the social sciences, as well as students who have studied statistics in the past, but need a more solid grounding in statistical techniques to further their careers. Jacco Thijssen is professor of finance at the University of York, UK. He holds a PhD in mathematical economics from Tilburg University, Netherlands. His main research interests are in applications of optimal stopping theory, stochastic calculus, and game theory to problems in economics and finance. Professor Thijssen has earned several awards for his statistics teaching.

This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series, bridging the gap between methods and realistic applications. It presents the most important approaches to the analysis of time series, which may be stationary or nonstationary. Modelling and forecasting univariate time series is the starting point. For multiple stationary time series, Granger causality tests and vector autogressive models are presented. As the modelling of nonstationary uni- or multivariate time series is most important for real applied work, unit root and cointegration analysis as well as vector error correction models are a central topic. Tools for analysing nonstationary data are then transferred to the panel framework. Modelling the (multivariate) volatility of financial time series with autogressive conditional heteroskedastic models is also treated.

Introduction to Statistics with SPSS offers an introduction to statistics that can be used before, during or after a course on statistics. Covering a wide range of terms and techniques, including simple and multiple regressions, this book guides the student to enter data from a simple research project into a computer, provide an adequate analysis of the data and present a report on the findings.

This book brings together cutting edge contributions in the fields of international economics, micro theory, welfare economics and econometrics, with contributions from Donald R. Davis, Avinash K. Dixit, Tadashi Inoue, Ronald W. Jones, Dale W. Jorgenson, K. Rao Kadiyala, Murray C. Kemp, Kenneth M. Kletzer, Anne O. Krueger, Mukul Majumdar, Daniel McFadden, Lionel McKenzie, James R. Melvin, James C. Moore, Takashi Negishi, Yoshihiko Otani, Raymond Riezman, Paul A. Samuelson, Joaquim Silvestre and Marie Thursby.

The purpose of this book is to introduce novice researchers to the tools of meta-analysis and meta-regression analysis and to summarize the state of the art for existing practitioners. Meta-regression analysis addresses the rising "Tower of Babel" that current economics and business research has become. Meta-analysis is the statistical analysis of previously published, or reported, research findings on a given hypothesis, empirical effect, phenomenon, or policy intervention. It is a systematic review of all the relevant scientific knowledge on a specific subject and is an essential part of the evidence-based practice movement in medicine, education and the social sciences. However, research in economics and business is often fundamentally different from what is found in the sciences and thereby requires different methods for its synthesis-meta-regression analysis. This book develops, summarizes, and applies these meta-analytic methods.

Originally published in 1992 this title came out of a conference on emotion and cognition as antecedents and consequences of health and disease processes in children and adolescents. The theoretical rationale for the conference was based on the assumption that the development of emotion, cognition, health and illness are processes that influence each other through the life span and that these reciprocal interactions begin in infancy. The chapters discuss developmental theories, research and implications for interventions as they relate to promoting health, preventing disease, and treating illness in children and adolescents.

This book is designed to introduce graduate students and researchers to the primary methods useful for approximating integrals. The emphasis is on those methods that have been found to be of practical use, and although the focus is on approximating higher-dimensional integrals the lower-dimensional case is also covered. This book covers all the most useful approximation techniques so far discovered; the first time that all such techniques have been included in a single book and at a level accessible for students. In particular, it includes a complete development of the material needed to construct the highly popular Markov Chain Monte Carlo (MCMC) methods.

Over the course of his professional life, John Maynard Keynes altered his views from free trade in the classical tradition to restricted trade. At the end of his career, his position on the issue was still not categorically resolved even though the evidence seems to suggest that he moved closer to a system of managed trade. In that model, nations would not leave their foreign trade interests open to the vagaries of the free market, but rather exercise some degree of control over them just as they would their domestic economies. Nevertheless, there is no general agreement among economists as to whether Keynes ended his career in the camp of the free traders or aligned himself with the protectionists. John Maynard Keynes: Free Trader or Protectionist? seeks an answer to this question by analyzing Keynes' own views on this issue, as stated in his major publications, letters, speeches, testimony before government bodies, newspaper articles, participation in conferences, and other sources. Through this detailed review of what Keynes himself had to say on the issue as opposed to what others have alleged, this book strives to make a significant contribution to the resolution of this issue.

Any discussion of the various facets of petroleum policy in the United States rests to a greater or less extent on the issue of sensitivity of petroleum exploration, and hence of new petroleum discoveries to economic incentives. Indeed, a principle argument in favour of having a special petroleum policy at all is that domestic petroleum exploration is so sensitive to economic considerations that in the absence of special incentives exploration expenditures would sharply decrease, as would the amount of petroleum discovered; consequently, the nation's known oil resources would be reduced to an extent dangerous in the event of an international crisis. This study attempts to answer the question: how sensitive are new petroleum discoveries to economic incentives? This book will be of interest to students of environmental studies.

This book provides a comprehensive overview of the fruitful achievement of China's Quantitative Economics during the past 30 years, assembling pioneering contributions of prominent quantitative economists in China. It chronicles significant events and the detailed evolution of Quantitative Economics in China. This well-organized book is a must-have for scholars to get a full picture of the status quo, and identify possible research gaps.

This book offers a fresh perspective on the early history of macroeconomics, by examining the macro-dynamic models developed from the late 1920s to the late 1940s, and their treatment of economic instability. It first explores the differences and similarities between the early mathematical business cycle models developed by Ragnar Frisch, Michal Kalecki, Jan Tinbergen and others, which were presented at meetings of the Econometric Society and discussed in private correspondence. By doing so, it demonstrates the diversity of models representing economic phenomena and especially economic crises and instability. Jan Tinbergen emerged as one of the most original and pivotal economists of this period, before becoming a leader of the macro-econometric movement, a role for which he is better known. His emphasis on economic policy was later mirrored in the United States in Paul Samuelson's early work on business cycles analysis, which, drawing on Alvin Hansen, aimed at interpreting the 1937-1938 recession. The authors then show that the subsequent shift in Samuelson's approach, from the study of business cycle trajectories to the comparison of equilibrium points, provided a response to the econometricians' critique of early Keynesian models. In the early 1940s, Samuelson was able to link together the tools that had been developed by the econometricians and the economic content that was at the heart of the so-called Keynesian revolution. The problem then shifted from business cycle trajectories to the disequilibrium between economic aggregates, and the issues raised by the global stability of full employment equilibrium. This was addressed by Oskar Lange, who presented an analysis of market coordination failures, and Lawrence Klein, Samuelson's first PhD student, who pursued empirical work in this direction. The book highlights the various visions and approaches that were embedded in these macro-dynamic models, and that their originality is of interest to today's model builders as well as to students and anyone interested in how new economic ideas come to be developed.

Ranking of Multivariate Populations: A Permutation Approach with Applications presents a novel permutation-based nonparametric approach for ranking several multivariate populations. Using data collected from both experimental and observation studies, it covers some of the most useful designs widely applied in research and industry investigations, such as multivariate analysis of variance (MANOVA) and multivariate randomized complete block (MRCB) designs. The first section of the book introduces the topic of ranking multivariate populations by presenting the main theoretical ideas and an in-depth literature review. The second section discusses a large number of real case studies from four specific research areas: new product development in industry, perceived quality of the indoor environment, customer satisfaction, and cytological and histological analysis by image processing. A web-based nonparametric combination global ranking software is also described. Designed for practitioners and postgraduate students in statistics and the applied sciences, this application-oriented book offers a practical guide to the reliable global ranking of multivariate items, such as products, processes, and services, in terms of the performance of all investigated products/prototypes.

This book, which was first published in 1980, is concerned with one particular branch of growth theory, namely descriptive growth theory. It is typically assumed in growth theory that both the factors and goods market are perfectly competitive. In particular this implies amongst other things that the reward to each factor is identical in each sector of the economy. In this book the assumption of identical factor rewards is relaxed and the implications of an intersectoral wage differential for economic growth are analysed. There is also some discussion on the short-term and long-run effects of minimum wage legislation on growth. This book will serve as key reading for students of economics.

The past ten years for the Middle East and North Africa (MENA) region countries have registered an extreme deterioration in at least one measure of social and economic welfare: earnings inequality, unemployment, and poverty. The combination of slow economic growth, population explosion, and decline in labor productivity led to the reversal of the economic gains achieved during the economic boom in the 1970s. In contrast to that period, growth per capita (GDP) in 1980-1991 for Arab countries was -0.2%. Several indicators point to the extent of the problems faced today by the region's countries. Although the percentage of poverty declined for the majority of the regions in the world in 1985-1990, it has increased in the MENA region.

The purpose of this volume is to address the conditions of earnings inequality, unemployment, and poverty in the MENA region and the problems associated with these factors; to determine the state and magnitude of these problems through various country studies; and to provide solutions to alleviate the negative conditions facing developing economies, with special emphasis on the MENA countries.

This new book will be welcomed by econometricians and students of econometrics everywhere. Introducing discrete time modelling techniques and bridging the gap between economics and econometric literature, this ambitious book is sure to be an invaluable resource for all those to whom the terms unit roots, cointegration and error correction forms, chaos theory and random walks are recognisable if not yet fully understood.

Originally published in 1930, this book was formed from the content of three lectures delivered at London University during March of that year. The text provides a concise discussion of the relationship between theoretical statistics and actuarial science. This book will be of value to anyone with an interest in the actuarial profession, statistics and the history of finance.

The state-space approach provides a formal framework where any result or procedure developed for a basic model can be seamlessly applied to a standard formulation written in state-space form. Moreover, it can accommodate with a reasonable effort nonstandard situations, such as observation errors, aggregation constraints, or missing in-sample values. Exploring the advantages of this approach, State-Space Methods for Time Series Analysis: Theory, Applications and Software presents many computational procedures that can be applied to a previously specified linear model in state-space form. After discussing the formulation of the state-space model, the book illustrates the flexibility of the state-space representation and covers the main state estimation algorithms: filtering and smoothing. It then shows how to compute the Gaussian likelihood for unknown coefficients in the state-space matrices of a given model before introducing subspace methods and their application. It also discusses signal extraction, describes two algorithms to obtain the VARMAX matrices corresponding to any linear state-space model, and addresses several issues relating to the aggregation and disaggregation of time series. The book concludes with a cross-sectional extension to the classical state-space formulation in order to accommodate longitudinal or panel data. Missing data is a common occurrence here, and the book explains imputation procedures necessary to treat missingness in both exogenous and endogenous variables. Web Resource The authors' E4 MATLAB (R) toolbox offers all the computational procedures, administrative and analytical functions, and related materials for time series analysis. This flexible, powerful, and free software tool enables readers to replicate the practical examples in the text and apply the procedures to their own work.

Prepares readers to analyze data and interpret statistical results using the increasingly popular R more quickly than other texts through LessR extensions which remove the need to program. By introducing R through less R, readers learn how to organize data for analysis, read the data into R, and produce output without performing numerous functions and programming first. Readers can select the necessary procedure and change the relevant variables without programming. Quick Starts introduce readers to the concepts and commands reviewed in the chapters. Margin notes define, illustrate, and cross-reference the key concepts. When readers encounter a term previously discussed, the margin notes identify the page number to the initial introduction. Scenarios highlight the use of a specific analysis followed by the corresponding R/lessR input and an interpretation of the resulting output. Numerous examples of output from psychology, business, education, and other social sciences demonstrate how to interpret results and worked problems help readers test their understanding. www.lessRstats.com website features the lessR program, the book's 2 data sets referenced in standard text and SPSS formats so readers can practice using R/lessR by working through the text examples and worked problems, PDF slides for each chapter, solutions to the book's worked problems, links to R/lessR videos to help readers better understand the program, and more. New to this edition: o upgraded functionality and data visualizations of the lessR package, which is now aesthetically equal to the ggplot 2 R standard o new features to replace and extend previous content, such as aggregating data with pivot tables with a simple lessR function call.

Valuable software, realistic examples, clear writing, and fascinating topics help you master key spreadsheet and business analytics skills with SPREADSHEET MODELING AND DECISION ANALYSIS, 8E. You'll find everything you need to become proficient in today's most widely used business analytics techniques using Microsoft (R) Office Excel (R) 2016. Author Cliff Ragsdale -- respected innovator in business analytics -- guides you through the skills you need, using the latest Excel (R) for Windows. You gain the confidence to apply what you learn to real business situations with step-by-step instructions and annotated screen images that make examples easy to follow. The World of Management Science sections further demonstrates how each topic applies to a real company. Each new edition includes extended trial licenses for Analytic Solver Platform and XLMiner with powerful simulation and optimization tools for descriptive and prescriptive analytics and a full suite of tools for data mining in Excel.

Model a Wide Range of Count Time Series Handbook of Discrete-Valued Time Series presents state-of-the-art methods for modeling time series of counts and incorporates frequentist and Bayesian approaches for discrete-valued spatio-temporal data and multivariate data. While the book focuses on time series of counts, some of the techniques discussed can be applied to other types of discrete-valued time series, such as binary-valued or categorical time series. Explore a Balanced Treatment of Frequentist and Bayesian Perspectives Accessible to graduate-level students who have taken an elementary class in statistical time series analysis, the book begins with the history and current methods for modeling and analyzing univariate count series. It next discusses diagnostics and applications before proceeding to binary and categorical time series. The book then provides a guide to modern methods for discrete-valued spatio-temporal data, illustrating how far modern applications have evolved from their roots. The book ends with a focus on multivariate and long-memory count series. Get Guidance from Masters in the Field Written by a cohesive group of distinguished contributors, this handbook provides a unified account of the diverse techniques available for observation- and parameter-driven models. It covers likelihood and approximate likelihood methods, estimating equations, simulation methods, and a Bayesian approach for model fitting.