Is concerned with forecasting aggregated time series variables. Investigates impact of the level of aggregation on the forecast efficiency. Temporal aggregation over several time periods and contemporaneous aggregation over regions, firms, etc. are considered. The data on which the forecasts are based are assumed to be generated by vector ARMA processes. The consequences of the estimation and specification uncertainty for the forecast efficiency are analyzed.

Forecasting Aggregated Vector Arma Processes (Lecture Notes in Economics & Mathematical Systems)

Business & Money

Lütkepohl, Helmut

Accounting

Springer, Verlag

Introduction to the Theory and Practice of Econometrics (Probability &amp; Mathematical Statistics) [hardcover] Judge, George G.,etc. [Apr 01, 1982]

Introduction to the Theory and Practice of Econometrics (Probability & Mathematical Statistics) (Wiley series in probability and mathematical statistics)

Hill, R. Carter

Griffiths, William E.

Judge, George G.

Economics

wiley

A computer handbook to accompany "Introduction to the Theory and Practice of Econometrics" (Second edition).

Learning Econometrics Using GAUSS

Griffith, William

Lee, Tsoung-Chao

Introduction to the Theory and Practice of Econometrics, Solutions Manual

This broadly based graduate-level textbook covers the major models and statistical tools currently used in the practice of econometrics. It examines the classical, the decision theory, and the Bayesian approaches, and contains material on single equation and simultaneous equation econometric models. Includes an extensive reference list for each topic.

The Theory and Practice of Econometrics

Matrices are used in many fields such as statistics, econometrics, mathematics, natural sciences and engineering. They provide a concise, simple method for describing long and complicated computations. This is a comprehensive handbook and dictionary of terms for matrix theory.

Handbook of Matrices

Reference

Lutkepohl, H.

Dictionaries & Thesauruses

Structural Vector Autoregressive Analysis (Themes in Modern Econometrics)

Structural vector autoregressive (VAR) models are important tools for empirical work in macroeconomics, finance, and related fields. This book not only reviews the many alternative structural VAR approaches discussed in the literature, but also highlights their pros and cons in practice. It provides guidance to empirical researchers as to the most appropriate modeling choices, methods of estimating, and evaluating structural VAR models. The book traces the evolution of the structural VAR methodology and contrasts it with other common methodologies, including dynamic stochastic general equilibrium (DSGE) models. It is intended as a bridge between the often quite technical econometric literature on structural VAR modeling and the needs of empirical researchers. The focus is not on providing the most rigorous theoretical arguments, but on enhancing the reader's understanding of the methods in question and their assumptions. Empirical examples are provided for illustration.

Kilian, Lutz

Cambridge University Press

This study is concerned with forecasting time series variables and the impact of the level of aggregation on the efficiency of the forecasts. Since temporally and contemporaneously disaggregated data at various levels have become available for many countries, regions, and variables during the last decades the question which data and procedures to use for prediction has become increasingly important in recent years. This study aims at pointing out some of the problems involved and at pro­ viding some suggestions how to proceed in particular situations. Many of the results have been circulated as working papers, some have been published as journal articles, and some have been presented at conferences and in seminars. I express my gratitude to all those who have commented on parts of this study. They are too numerous to be listed here and many of them are anonymous referees and are therefore unknown to me. Some early results related to the present study are contained in my monograph "Prognose aggregierter Zeitreihen" (Lutkepohl (1986a)) which was essentially completed in 1983. The present study contains major extensions of that research and also summarizes the earlier results to the extent they are of interest in the context of this study.

Forecasting Aggregated Vector ARMA Processes (Lecture Notes in Economics and Mathematical Systems, 284)

Springer

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.

New Introduction to Multiple Time Series Analysis

See the best price to sell, buy, or rent books by Lütkepohl, Helmut. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Lütkepohl, Helmut

See the best price to sell, buy, or rent books by Lütkepohl, Helmut. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Forecasting Aggregated Vector Arma Processes (Lecture Notes in Economics & Mathematical Systems)

Introduction to the Theory and Practice of Econometrics (Probability & Mathematical Statistics) (Wiley series in probability and mathematical statistics)

Learning Econometrics Using GAUSS

Introduction to the Theory and Practice of Econometrics, Solutions Manual

The Theory and Practice of Econometrics

Handbook of Matrices

Structural Vector Autoregressive Analysis (Themes in Modern Econometrics)

Structural Vector Autoregressive Analysis (Themes in Modern Econometrics)

Forecasting Aggregated Vector ARMA Processes (Lecture Notes in Economics and Mathematical Systems, 284)

New Introduction to Multiple Time Series Analysis