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 and/or studied with 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 book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It contains the most important approaches to analyze time series which may be stationary or nonstationary.
Financial markets respond to information virtually instantaneously. Each new piece of information influences the prices of assets and their correlations with each other, and as the system rapidly changes, so too do correlation forecasts. This fast-evolving environment presents econometricians with the challenge of forecasting dynamic correlations, which are essential inputs to risk measurement, portfolio allocation, derivative pricing, and many other critical financial activities. In Anticipating Correlations, Nobel Prize-winning economist Robert Engle introduces an important new method for estimating correlations for large systems of assets: Dynamic Conditional Correlation (DCC). Engle demonstrates the role of correlations in financial decision making, and addresses the economic underpinnings and theoretical properties of correlations and their relation to other measures of dependence. He compares DCC with other correlation estimators such as historical correlation, exponential smoothing, and multivariate GARCH, and he presents a range of important applications of DCC. Engle presents the asymmetric model and illustrates it using a multicountry equity and bond return model. He introduces the new FACTOR DCC model that blends factor models with the DCC to produce a model with the best features of both, and illustrates it using an array of U.S. large-cap equities. Engle shows how overinvestment in collateralized debt obligations, or CDOs, lies at the heart of the subprime mortgage crisis--and how the correlation models in this book could have foreseen the risks. A technical chapter of econometric results also is included. Based on the Econometric and Tinbergen Institutes Lectures, Anticipating Correlations puts powerful new forecasting tools into the hands of researchers, financial analysts, risk managers, derivative quants, and graduate students.
This book provides a formal analysis of the models, procedures, and measures of economic forecasting with a view to improving forecasting practice. David Hendry and Michael Clements base the analyses on assumptions pertinent to the economies to be forecast, viz. a non-constant, evolving economic system, and econometric models whose form and structure are unknown a priori. The authors find that conclusions which can be established formally for constant-parameter stationary processes and correctly-specified models often do not hold when unrealistic assumptions are relaxed. Despite the difficulty of proceeding formally when models are mis-specified in unknown ways for non-stationary processes that are subject to structural breaks, Hendry and Clements show that significant insights can be gleaned. For example, a formal taxonomy of forecasting errors can be developed, the role of causal information clarified, intercept corrections re-established as a method for achieving robustness against forms of structural change, and measures of forecast accuracy re-interpreted.
The Mekong is the most controversial river in Southeast Asia, and increasingly the focus of international attention. It flows through 6 counties, China, Myanmar, Laos, Thailand, Cambodia and Viet Nam. The 4 downstream countries have formed the Mekong River Commission to promote sustainable development of the river and many of their people depend on it for their subsistence ? it has possible the largest freshwater fishery in the world, and the Mekong waters support rice agriculture in the delta in Viet Nam (which produces about 40% of that country's food) as well as in Cambodia, Laos and Thailand. China is now building the first large mainstream dam on the river, and has proposals for several more. These dams are likely to affect the downstream countries. Several of the downstream countries also have plans for large scale hydropower and irrigation development which could also impact the river. This book will provide a solid overview of the biophysical environment of the Mekong together with a discussion of the possible impacts, biophysical, economic and social, of some possible development scenarios. It is intended to provide a technical basis which can inform the growing political and conservation debate about the future of the Mekong River, and those who depend on it. It is aimed at river ecologists, geographers, environmentalists and development specialists both in the basin and (especially) outside for whom access to this material is most difficult. This book will be the first comprehensive treatment of the Mekong system. - The first comprehensive overview of all aspects of the Mekong River system - Deals with a regionally critical ecosystem and one under threat - The Mekong supports the world's largest freshwater fishery and provides water underpinning a major regional rice paddy system - Presents the authoritative findings of the Mekong River Commission's research for a wider audience for the first time outside of limited distribution reports
This volume in the Challenges in Machine Learning series gathers papers from the Mini Symposium on Causality in Time Series, which was part of the Neural Information Processing Systems (NIPS) confernce in 2009 in Vancouver, Canada. These papers present state-of-the-art research in time-series causality to the machine learning community, unifying methodological interests in the various communities that require such inference.
First published in 2001, Causality in Macroeconomics addresses the long-standing problems of causality while taking macroeconomics seriously. The practical concerns of the macroeconomist and abstract concerns of the philosopher inform each other. Grounded in pragmatic realism, the book rejects the popular idea that macroeconomics requires microfoundations, and argues that the macroeconomy is a set of structures that are best analyzed causally. Ideas originally due to Herbert Simon and the Cowles Commission are refined and generalized to non-linear systems, particularly to the non-linear systems with cross-equation restrictions that are ubiquitous in modern macroeconomic models with rational expectations (with and without regime-switching). These ideas help to clarify philosophical as well as economic issues. The structural approach to causality is then used to evaluate more familiar approaches to causality due to Granger, LeRoy and Glymour, Spirtes, Scheines and Kelly, as well as vector autoregressions, the Lucas critique, and the exogeneity concepts of Engle, Hendry and Richard.
