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Titlebook: Measuring Business Cycles in Economic Time Series; Regina Kaiser,Agustín Maravall Book 2001 Springer Science+Business Media New York 2001

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发表于 2025-3-21 19:06:48 | 显示全部楼层 |阅读模式
书目名称Measuring Business Cycles in Economic Time Series
编辑Regina Kaiser,Agustín Maravall
视频video
丛书名称Lecture Notes in Statistics
图书封面Titlebook: Measuring Business Cycles in Economic Time Series;  Regina Kaiser,Agustín Maravall Book 2001 Springer Science+Business Media New York 2001
描述lengths, that could not be captured with univariate linear filters. Exam­ ples of research in both directions can be found in Sims (1977), Lahiri and Moore (1991), Stock and Watson (1993), and Hamilton (1994) and (1989). Although the first approach is known to present serious limitations,the new and more sophisticated methods developed in the second approach (most notably, multivariate and nonlinear extensions) are at an early stage, and have proved still unreliable, displaying poor behavior when moving away from the sample period . Despite the fact that business cycle estimation is basic to the conduct of macroeconomic policy and to monitoring of the economy, many decades of attention have shown that formal modeling of economic cycles is a frustrating issue. As Baxter and King (1999) point out, we still face at present the same basic question "as did Burns and Mitchell fifty years ago: how should one isolate the cyclical component of an eco­ nomic time series? In particular, how should one separate business-cycle elements from slowly evolving secular trends, and rapidly varying seasonal or irregular components?" Be that as it may, it is a fact that measuring (in some way) the busi
出版日期Book 2001
关键词Stochastic Processes; calculus; correlation; time series; time series analysis
版次1
doihttps://doi.org/10.1007/978-1-4613-0129-5
isbn_softcover978-0-387-95112-6
isbn_ebook978-1-4613-0129-5Series ISSN 0930-0325 Series E-ISSN 2197-7186
issn_series 0930-0325
copyrightSpringer Science+Business Media New York 2001
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Regina Kaiser,Agustín Maravall structures. It, thus, deals with an intermediate hierarchical level that bridges aggregate production planning and detailed production scheduling characterized by complex product structures. Specifically, this chapter focuses on a typical problem arising in aggregate production planning and master
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Regina Kaiser,Agustín Maravallg. It introduces a leading optimal flow control paradigm which results in efficient solutions for planning and scheduling problems. This book also introduces the reader to analytical and numerical methods of the maximum principle, used here as a mathematical instrument in modeling and solving produc
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Regina Kaiser,Agustín Maravallniques for addressing severalcomputational chemistry and biology problems. A tantalizing problemthat cuts across the fields of computational chemistry, biology,medicine, engineering and applied mathematics is how proteins fold.Global and local optimization provide a systematic framework ofconformati
发表于 2025-3-22 17:33:39 | 显示全部楼层
Regina Kaiser,Agustín Maravallniques for addressing severalcomputational chemistry and biology problems. A tantalizing problemthat cuts across the fields of computational chemistry, biology,medicine, engineering and applied mathematics is how proteins fold.Global and local optimization provide a systematic framework ofconformati
发表于 2025-3-22 21:18:50 | 显示全部楼层
t becomes the more difficult it becomes to control the plant with a single controller. In this paper we consider the problem of finding a set of internally stabilizing controllers which is globally equivalent to a single internally stabilizing controller such that the state of the plant .(.) is driv
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Introduction and Brief Summary,wed the Great Depression, economists developed an interest in the possible existence of (more or less systematic) cycles in the economy; see, for example, Haberler (1944) or Shumpeter (1939). It became apparent that in order to identify economic cycles, one had to remove from the series seasonal flu
发表于 2025-3-23 09:05:29 | 显示全部楼层
A Brief Review of Applied Time Series Analysis,g average (MA) filter, most often the HP filter, to a seasonally adjusted (SA) series, most often adjusted with the X11 filter. It was also mentioned that the procedure presents several drawbacks which, as shown, can be seriously reduced by incorporating some time series analysis tools, such as ARIM
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