Read Dominique Ladiray - Lecture Notes in Statistics: Seasonal Adjustment with the X-11 Method 158 DOC, PDF
9780387951713 0387951717 The authors, Dominique Ladiray and Benoit Quenneville, provide a unique and comprehensive r view of the X-11 Method of seasonal adjustment. They review the original X-11 Method developed at the US Bureau of the Census in the mid-1960's, the X-ll core of the X-ll-ARTMA Method developed at Statistics Canada in the 1970's, and the X-11 module in the X- 12-ARTMA Method developed more recently at the Bureau of the Census. The review will prove extremely useful to anyone working in the field of seasonal adjustment who wants to understand the X-11 Method and how it fits into the broader picture of seasonal adjustment. What the authors designate as the X-11 Method was originally desig nated the X-11 Variant of the Census Method IT Seasonal Adjustment Program. It was the culmination of the pioneering work undertaken at the Bureau of the Census by Julius Shiskin in the 1950's. Shiskin introduced the Census Method T Seasonal Adjustment Program in 1954 and soon followed it with the introduction of Method TT in 1957.", 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., The most widely used statistical method in seasonal adjustment is without doubt that implemented in the X-11 Variant of the Census Method II Seasonal Adjustment Program. Developed at the US Bureau of the Census in the 1950's and 1960's, this computer program has undergone numerous modifications and improvements, leading especially to the X-11-ARIMA software packages in 1975 and 1988 and X-12-ARIMA, the first beta version of which is dated 1998. While these software packages integrate, to varying degrees, parametric methods, and especially the ARIMA models popularized by Box and Jenkins, they remain in essence very close to the initial X-11 method, and it is this "core" that Seasonal Adjustment with the X-11 Method focuses on. With a Preface by Allan Young, the authors document the seasonal adjustment method implemented in the X-11 based software. It will be an important reference for government agencies, macroeconomists, and other serious users of economic data. After some historical notes, the authors outline the X-11 methodology. One chapter is devoted to the study of moving averages with an emphasis on those used by X-11. Readers will also find a complete example of seasonal adjustment, and have a detailed picture of all the calculations. The linear regression models used for trading-day effects and the process of detecting and correcting extreme values are studied in the example. The estimation of the Easter effect is dealt with in a separate chapter insofar as the models used in X-11-ARIMA and X-12-ARIMA are appreciably different. Dominique Ladiray is an Administrateur at the French Institut National de la Statistique et des Etudes Economiques. He is also a Professor at the Ecole Nationale de la Statistique et de l'Administration Economique, and at the Ecole Nationale de la Statistique et de l'Analyse de l'Information. He currently works on short-term economic analysis. Benoit Quenneville is a methodologist with Statistics Canada Time Series Research and Analysis Centre. He holds a Ph.D. from the University of Western Ontario. His research interests are in time series analysis with an emphasis on official statistics.
9780387951713 0387951717 The authors, Dominique Ladiray and Benoit Quenneville, provide a unique and comprehensive r view of the X-11 Method of seasonal adjustment. They review the original X-11 Method developed at the US Bureau of the Census in the mid-1960's, the X-ll core of the X-ll-ARTMA Method developed at Statistics Canada in the 1970's, and the X-11 module in the X- 12-ARTMA Method developed more recently at the Bureau of the Census. The review will prove extremely useful to anyone working in the field of seasonal adjustment who wants to understand the X-11 Method and how it fits into the broader picture of seasonal adjustment. What the authors designate as the X-11 Method was originally desig nated the X-11 Variant of the Census Method IT Seasonal Adjustment Program. It was the culmination of the pioneering work undertaken at the Bureau of the Census by Julius Shiskin in the 1950's. Shiskin introduced the Census Method T Seasonal Adjustment Program in 1954 and soon followed it with the introduction of Method TT in 1957.", 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., The most widely used statistical method in seasonal adjustment is without doubt that implemented in the X-11 Variant of the Census Method II Seasonal Adjustment Program. Developed at the US Bureau of the Census in the 1950's and 1960's, this computer program has undergone numerous modifications and improvements, leading especially to the X-11-ARIMA software packages in 1975 and 1988 and X-12-ARIMA, the first beta version of which is dated 1998. While these software packages integrate, to varying degrees, parametric methods, and especially the ARIMA models popularized by Box and Jenkins, they remain in essence very close to the initial X-11 method, and it is this "core" that Seasonal Adjustment with the X-11 Method focuses on. With a Preface by Allan Young, the authors document the seasonal adjustment method implemented in the X-11 based software. It will be an important reference for government agencies, macroeconomists, and other serious users of economic data. After some historical notes, the authors outline the X-11 methodology. One chapter is devoted to the study of moving averages with an emphasis on those used by X-11. Readers will also find a complete example of seasonal adjustment, and have a detailed picture of all the calculations. The linear regression models used for trading-day effects and the process of detecting and correcting extreme values are studied in the example. The estimation of the Easter effect is dealt with in a separate chapter insofar as the models used in X-11-ARIMA and X-12-ARIMA are appreciably different. Dominique Ladiray is an Administrateur at the French Institut National de la Statistique et des Etudes Economiques. He is also a Professor at the Ecole Nationale de la Statistique et de l'Administration Economique, and at the Ecole Nationale de la Statistique et de l'Analyse de l'Information. He currently works on short-term economic analysis. Benoit Quenneville is a methodologist with Statistics Canada Time Series Research and Analysis Centre. He holds a Ph.D. from the University of Western Ontario. His research interests are in time series analysis with an emphasis on official statistics.