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Author: Estela Bee Dagum Publisher: ISBN: Category : Seasonal variations (Economics) Languages : en Pages : 22
Book Description
"Two strategies have been followed for the development of model-based seasonal adjustment methods. One, where each of the unobserved components, trend-cycle, seasonal and irregular is assumed to follow a normal stochastic process of the ARIMA class and the other, where the observed data are assumed to follow an ARIMA process and from it similar kind of models are derived for the components. The first approach is known as "structural" and the second, as the "reduced-form" given their similarities to the problems of identification of structures from the data in econometrics. This paper discusses the major properties and operational limitations of these two approaches. It also analyses the salient characteristics of the empirical comparisons made between model-based seasonal adjustment methods and the X-11-ARIMA which is used by the majority of government statistical agencies"--Abstract.
Author: Estela Bee Dagum Publisher: ISBN: Category : Seasonal variations (Economics) Languages : en Pages : 22
Book Description
"Two strategies have been followed for the development of model-based seasonal adjustment methods. One, where each of the unobserved components, trend-cycle, seasonal and irregular is assumed to follow a normal stochastic process of the ARIMA class and the other, where the observed data are assumed to follow an ARIMA process and from it similar kind of models are derived for the components. The first approach is known as "structural" and the second, as the "reduced-form" given their similarities to the problems of identification of structures from the data in econometrics. This paper discusses the major properties and operational limitations of these two approaches. It also analyses the salient characteristics of the empirical comparisons made between model-based seasonal adjustment methods and the X-11-ARIMA which is used by the majority of government statistical agencies"--Abstract.
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.
Author: William R. Bell Publisher: CRC Press ISBN: 1439846588 Category : Mathematics Languages : en Pages : 544
Book Description
Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and seasonality, presenting cutting-edge research that would otherwise be scattered throughout diverse peer-reviewed journals. This compilation of 21 chapters showcases the cross-fertilization between the fields of time s
Author: Andrew G. Bruce Publisher: ISBN: Category : Computer simulation Languages : en Pages : 48
Book Description
This study compares X-12-ARIMA and MING, two new seasonal adjustment methods designed to handle outliers and structural changes in a time series. X-12-ARIMA is a successor to the X-11-ARIMA seasonal adjustment method, and is being developed at the U.S. Bureau of the Census (Findley et al. (1988)). MING is a "Mixture based Non-Gaussian" method for seasonal adjustment using time series structural models. It was developed for this study based on methodology proposed by Kitagawa (1990).
Author: Barend Abeln Publisher: Springer Nature ISBN: 3031228456 Category : Business & Economics Languages : en Pages : 94
Book Description
Seasonality in economic time series can "obscure" movements of other components in a series that are operationally more important for economic and econometric analyses. In practice, one often prefers to work with seasonally adjusted data to assess the current state of the economy and its future course. This book presents a seasonal adjustment program called CAMPLET, an acronym of its tuning parameters, which consists of a simple adaptive procedure to extract the seasonal and the non-seasonal component from an observed series. Once this process is carried out, there will be no need to revise these components at a later stage when new observations become available. The authors describe the main features of CAMPLET, evaluate the outcomes of CAMPLET and X-13ARIMA-SEATS in a controlled simulation framework using a variety of data generating processes, and illustrate CAMPLET and X-13ARIMA-SEATS with three time series: US non-farm payroll employment, operational income of Ahold and real GDP in the Netherlands. Furthermore they show how CAMPLET performs under the COVID-19 crisis, and its attractiveness in dealing with daily data. This book appeals to scholars and students of econometrics and statistics, interested in the application of statistical methods for empirical economic modeling.
Author: Dominique Ladiray Publisher: Springer Science & Business Media ISBN: 1461301750 Category : Computers Languages : en Pages : 245
Book Description
The most widely used statistical method in seasonal adjustment is implemented in the X-11 Variant of the Census Method II Seasonal Adjustment Program. Developed by the US Bureau of the Census, it resulted in the X-11-ARIMA software and the X-12-ARIMA. While these integrate parametric methods, they remain close to the initial X-11 method, and it is this "core" that Seasonal Adjustment with the X-11 Method focuses on. It will be an important reference for government agencies, and other serious users of economic data.
Author: Imad A. Moosa Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
It is argued that the X-11 seasonal adjustment procedure suffers from severe drawbacks, and so it should be abandoned in favour of model-based seasonal adjustment. Furthermore, it is argued that Harvey's structural time series model is superior to the conventional seasonal ARIMA models for the purpose of model-based seasonal adjustment. It is shown, with the help of a large number of Australian time series, that the nature of seasonality differs from one series to another, and this is why model selection is crucial for seasonal adjustment. It is further shown that model-based seasonal adjustment could produce results that are significantly different from those obtained by applying the X-11 procedure. Since the X-11 procedure is not based on an explicit model and in view of its other serious drawbacks, it is concluded that the procedure should be abandoned in favour of model-based seasonal adjustment.
Author: F. A. G. den Butter Publisher: North Holland ISBN: Category : Seasonal variations (Economics) Languages : en Pages : 236
Book Description
Presented in this book is the theory and the practice of seasonal adjustment of economic series from the viewpoint of economic policy design. The book offers the economist and practical statistician the opportunity to acquire new and important analytical insights as well as practical tools. Moreover, it discusses the historical development of the practice of seasonal adjustment as applied for policy analysis with Persons in the early twenties, via Zaycoff and Mendershausen in the thirties, through present day modelling with the aid of Kalman filters. Each method treated is empirically illustrated while a comparative analysis is made to assess the appropriateness of the various methods.
Author: Rob J Hyndman Publisher: OTexts ISBN: 0987507117 Category : Business & Economics Languages : en Pages : 380
Book Description
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Author: Estela Bee Dagum
Author: Estela Bee Dagum
Author: Estela Bee Dagum
Author: S. C. Hillmer
Author: William R. Bell
Author: Andrew G. Bruce
Author: Barend Abeln
Author: Dominique Ladiray
Author: Imad A. Moosa
Author: F. A. G. den Butter
Author: Rob J Hyndman