This book collects the revised and edited proceedings of the conference held in honour of the 50th anniversary of Professor Tinbergen's first macroeconomic policy model.
This book is intended to provide a somewhat more comprehensive and unified treatment of large sample theory than has been available previously and to relate the fundamental tools of asymptotic theory directly to many of the estimators of interest to econometricians.
The definition and measurement of the cost of using real capital as an input in production has been much discussed and approached in several ways in earlier literature.
The value of applying system-theoretic concepts to economic modelling problems arises from the fact that it offers a unifying framework for modelling dynamic systems.
The first part of the book presents the estimation of traditional models of investment, their interpretation in the light of the disequilibrium theory and their use in evaluating the economic policies implemented during the seventies.
Advances in computer technology, coupled with the sophistication of econometric modelling, have enabled rapid progress in the formulation and solution of optimal control and filtering programmes, especially in the sphere of macroeconomic policy designing.
Advanced Textbooks in Economics, Volume 7: Foundations of Econometrics focuses on the principles, processes, methodologies, and approaches involved in the study of econometrics.
This book introduces stochastic processes and their applications for students in engineering, industrial statistics, science, operations research, business, and finance.
This volume comprises selected papers presented at the 12th Winter School on Stochastic Processes and their Applications, which was held in Siegmundsburg, Germany, in March 2000.
Focusing on a data-centric perspective, this book provides a complete overview of data mining: its uses, methods, current technologies, commercial products, and future challenges.
Modelling Spatial and Spatial-Temporal Data: A Bayesian Approach is aimed at statisticians and quantitative social, economic and public health students and researchers who work with spatial and spatial-temporal data.
Packed with insights, Lorenzo Bergomi's Stochastic Volatility Modeling explains how stochastic volatility is used to address issues arising in the modeling of derivatives, including:Which trading issues do we tackle with stochastic volatility?
With the aim to sequentially determine optimal allocations across a set of assets, Online Portfolio Selection (OLPS) has significantly reshaped the financial investment landscape.
Competitive Innovation and Improvement: Statistical Design and Control explains how to combine two widely known statistical methods'statistical design and statistical control in a manner that can solve any business, government, or research problem quickly with sustained results.
Despite the unobserved components model (UCM) having many advantages over more popular forecasting techniques based on regression analysis, exponential smoothing, and ARIMA, the UCM is not well known among practitioners outside the academic community.
Although portfolio management didn't change much during the 40 years after the seminal works of Markowitz and Sharpe, the development of risk budgeting techniques marked an important milestone in the deepening of the relationship between risk and asset management.
Financial engineering has been proven to be a useful tool for risk management, but using the theory in practice requires a thorough understanding of the risks and ethical standards involved.
Proven Methods for Big Data Analysis As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data.
Revised and updated for the second edition, this textbook allows students to work through classic texts in economics and finance, using the original data and replicating their results.
The most authoritative and comprehensive synthesis of modern econometrics availableEconometrics provides first-year graduate students with a thoroughly modern introduction to the subject, covering all the standard material necessary for understanding the principal techniques of econometrics, from ordinary least squares through cointegration.
This book is intended to provide a summarized knowledge of the various fields that make up the management discipline for executives, entrepreneurs, doctors, architects, engineers, lawyers, etc.
Industrial Price, Quantity, and Productivity Indices: The Micro-Economic Theory and an Application gives a comprehensive account of the micro-economic foundations of industrial price, quantity, and productivity indices.
Empirical Studies on Volatility in International Stock Markets describes the existing techniques for the measurement and estimation of volatility in international stock markets with emphasis on the SV model and its empirical application.
Books on time series models deal mainly with models based on Box-Jenkins methodology which is generally represented by autoregressive integrated moving average models or some nonlinear extensions of these models, such as generalized autoregressive conditional heteroscedasticity models.
This book is an introductory exposition of different topics that emerged in the literature as unifying themes between two fields of econometrics of time series, namely nonlinearity and nonstationarity.
Standard macroeconomic monographs often discuss the mechanism of monetary transmission, usually ending by highlighting the complexities and uncertainties involved in this mechanism.
Over the past 25 years, applied econometrics has undergone tremen- dous changes, with active developments in fields of research such as time series, labor econometrics, financial econometrics and simulation based methods.
Almost half a century has elapsed since the demand for money began to attract widespread attention from economists and econometricians, and it has been a topic of ongoing controversy and research ever since.
