Author: Karen Browning
Publisher:
ISBN:
Category : Balance of trade
Languages : en
Pages : 22
Book Description
Provisional Data and Unbiased Prediction of Economic Time Series
Author: Karen Browning
Publisher:
ISBN:
Category : Balance of trade
Languages : en
Pages : 22
Book Description
Publisher:
ISBN:
Category : Balance of trade
Languages : en
Pages : 22
Book Description
Introduction to Time Series and Forecasting
Author: Peter J. Brockwell
Publisher: Springer Science & Business Media
ISBN: 1475725264
Category : Mathematics
Languages : en
Pages : 429
Book Description
Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.
Publisher: Springer Science & Business Media
ISBN: 1475725264
Category : Mathematics
Languages : en
Pages : 429
Book Description
Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.
Time Series Econometrics
Author: Pierre Perron
Publisher:
ISBN: 9789813237896
Category : Econometrics
Languages : en
Pages :
Book Description
Part I. Unit roots and trend breaks -- Part II. Structural change
Publisher:
ISBN: 9789813237896
Category : Econometrics
Languages : en
Pages :
Book Description
Part I. Unit roots and trend breaks -- Part II. Structural change
The Optimal Size of a Preliminary Test of Linear Restrictions in a Mis-specified Regression Model
Author: David E. A. Giles
Publisher:
ISBN:
Category : Least squares
Languages : en
Pages : 24
Book Description
Publisher:
ISBN:
Category : Least squares
Languages : en
Pages : 24
Book Description
Comparing Standard and Robust Serial Correlation Tests in the Presence of Garch Errors
Author: John P. Small
Publisher:
ISBN:
Category : Correlation (Statistics)
Languages : en
Pages : 36
Book Description
Publisher:
ISBN:
Category : Correlation (Statistics)
Languages : en
Pages : 36
Book Description
Some Recent Developments in Econometrics
Author: David Evan A. Giles
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 46
Book Description
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 46
Book Description
Business Conditions Digest
Author:
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 124
Book Description
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 124
Book Description
Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation
Author: Estela Bee Dagum
Publisher: Springer
ISBN: 3319318225
Category : Business & Economics
Languages : en
Pages : 293
Book Description
This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling.
Publisher: Springer
ISBN: 3319318225
Category : Business & Economics
Languages : en
Pages : 293
Book Description
This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling.
Estimation of the Error Variance After a Preliminary-test of Homogeneity in a Regression Model with Spherically Symmetric Disturbances
Author: Judith Anne Giles
Publisher:
ISBN:
Category : Error analysis (Mathematics)
Languages : en
Pages : 34
Book Description
Publisher:
ISBN:
Category : Error analysis (Mathematics)
Languages : en
Pages : 34
Book Description
Business Cycles, Indicators, and Forecasting
Author: James H. Stock
Publisher: University of Chicago Press
ISBN: 0226774740
Category : Business & Economics
Languages : en
Pages : 350
Book Description
The inability of forecasters to predict accurately the 1990-1991 recession emphasizes the need for better ways for charting the course of the economy. In this volume, leading economists examine forecasting techniques developed over the past ten years, compare their performance to traditional econometric models, and discuss new methods for forecasting and time series analysis.
Publisher: University of Chicago Press
ISBN: 0226774740
Category : Business & Economics
Languages : en
Pages : 350
Book Description
The inability of forecasters to predict accurately the 1990-1991 recession emphasizes the need for better ways for charting the course of the economy. In this volume, leading economists examine forecasting techniques developed over the past ten years, compare their performance to traditional econometric models, and discuss new methods for forecasting and time series analysis.