Author: David A. PiercePublisher:
ISBN:
Category : Money supply
Languages : en
Pages : 52
Book Description
Seasonal Adjustment of Daily Data with Special Reference to the U.S. Money Supply
Author: David A. PiercePublisher:
ISBN:
Category : Money supply
Languages : en
Pages : 52
Book Description
A Survey of Recent Developments in Seasonal Adjustment
Author: David A. PiercePublisher:
ISBN:
Category : Seasonal variations (Economics)
Languages : en
Pages : 56
Book Description
Data Revisions with Moving Average Seasonal Adjustment Procedures
Author: David A. PiercePublisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 50
Book Description
Seasonal Adjustment Without Revisions
Author: Barend AbelnPublisher: 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.
Estimating Current Trend and Growth Rates in Seasonal Time Series
Author: George E. P. BoxPublisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 44
Book Description
The importance of appropriate stochastic models in choosing efficient methods of statistical analysis is discussed. The fitting to data of Seasonal Autoregressive Moving Average models is described and it is shown how trend may be estimated in an appropriate class of models of this kind. The procedure is illustrated for a model fitted to a money supply series published by the Federal Reserve Board. Error limits are calculated. In a series of appendices the properties of the adaptive coefficients which determine the trend estimates are derived. (Author).
The Foundations of Econometrics
Author: Swamy. P. A. V. B.Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 64
Book Description
An Examination of Distributed Lag Model Coefficients Estimated with Smoothness Priors
Author: S. S. ThurmanPublisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 46
Book Description
Seasonal Adjustment as a Practical Problem
Author: F. A. G. den ButterPublisher: 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.
Seasonal Adjustment of Daily Time Series
Author: Daniel OllechSeasonal Adjustment Methods and Real Time Trend-Cycle Estimation
Author: Estela Bee DagumPublisher: 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.