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This book constitutes the refereed proceedings of the Second Theory of Cryptography Conference, TCC 2005, held in Cambridge, MA, USA in February 2005. The 32 revised full papers presented were carefully reviewed and selected from 84 submissions. The papers are organized in topical sections on hardness amplification and error correction, graphs and groups, simulation and secure computation, security of encryption, steganography and zero knowledge, secure computation, quantum cryptography and universal composability, cryptographic primitives and security, encryption and signatures, and information theoretic cryptography.
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.
This is the new and totally revised edition of Lütkepohl’s classic 1991 work. It provides a detailed introduction to the main steps of analyzing multiple time series, model specification, estimation, model checking, and for using the models for economic analysis and forecasting. The book now includes new chapters on cointegration analysis, structural vector autoregressions, cointegrated VARMA processes and multivariate ARCH models. The book bridges the gap to the difficult technical literature on the topic. It is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on it.
Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution has had a substantial impact on applied analysis. Hence, no textbook has managed to cover the full range of methods in current use and explain how to proceed in applied domains. This gap in the literature motivates the present volume. The methods are sketched out, reminding the reader of the ideas underlying them and giving sufficient background for empirical work. The treatment can also be used as a textbook for a course on applied time series econometrics. Topics include: unit root and cointegration analysis, structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. Crucial to empirical work is the software that is available for analysis. New methodology is typically only gradually incorporated into existing software packages. Therefore a flexible Java interface has been created, allowing readers to replicate the applications and conduct their own analyses.
The EURO has now been in place for more than two years, but only the future will tell if the ECB policy proves successful in the long-term. Whether the monetary authorities have sufficient information, and more important, the right information to manage the EURO currency, has been an open question and will remain so for some time to come. This book discusses the economic principals underlying the demand for money as a potentially useful relationship for policy makers, and the possibilities to recover its properties by means of multivariate time series analysis. It applies the outcome of these considerations to the whole EURO area as well as to France. While for the aggregate, a money demand ...
1. 1 Objective of the Study Vector autoregressive (VAR) models have become one of the dominant research tools in the analysis of macroeconomic time series during the last two decades. The great success of this modeling class started with Sims' (1980) critique of the traditional simultaneous equation models (SEM). Sims criticized the use of 'too many incredible restrictions' based on 'supposed a priori knowledge' in large scale macroeconometric models which were popular at that time. Therefore, he advo cated largely unrestricted reduced form multivariate time series models, unrestricted VAR models in particular. Ever since his influential paper these models have been employed extensively to c...
This book offers a detailed application guide to XploRe - an interactive statistical computing environment. As a guide it contains case studies of real data analysis situations. It helps the beginner in statistical data analysis to learn how XploRe works in real life applications. Many examples from practice are discussed and analysed in full length. Great emphasis is put on a graphic based understanding of the data interrelations. The case studies include: Survival modelling with Cox's proportional hazard regression, Vitamin C data analysis with Quantile Regression, and many others.
The essays collected in this liber amicorum or Festschrift were written in order to pay respect to Gerrit Meijer, a genuine scholar who will retire as reader from Maastricht University on October 17, 2003. His career has involved extensive teaching at all levels, characterized by great erudition, diligence, empathy, and willingness to speak his mind. This stubbornness not to go with intellectual fashions is an extremely important asset in the social sciences. It was his lonely voice in a hostile environment that held up the recognition of European traditions in economic thought which others were willing to either forget or set aside or else never learn. In this sense, the current intellectual landscape in the Netherlands, but not only there, is different from what it would have been had Gerrit Meijer not exerted his influence. Hence, it is no surprise that such a large group of scholars, all somehow related to Gerrit's efforts, have contributed to this volume.
Forecasts guide decisions in all areas of economics and finance. Economic policy makers base their decisions on business cycle forecasts, investment decisions of firms are based on demand forecasts, and portfolio managers try to outperform the market based on financial market forecasts. Forecasts extract relevant information from the past and help to reduce the inherent uncertainty of the future. The topic of this special issue of the Journal of Economics and Statistics is the theory and practise of forecasting and forecast evaluation and an overview of the state of the art of forecasting.