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Titlebook: Control Theory Methods in Economics; Jati K. Sengupta,Phillip Fanchon Book 1997 Springer Science+Business Media New York 1997 dynamic mode

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發(fā)表于 2025-3-21 16:34:33 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Control Theory Methods in Economics
編輯Jati K. Sengupta,Phillip Fanchon
視頻videohttp://file.papertrans.cn/238/237290/237290.mp4
圖書封面Titlebook: Control Theory Methods in Economics;  Jati K. Sengupta,Phillip Fanchon Book 1997 Springer Science+Business Media New York 1997 dynamic mode
描述Control theory methods in economics have historically developed over three phases. The first involved basically the feedback control rules in a deterministic framework which were applied in macrodynamic models for analyzing stabilization policies. The second phase raised the issues of various types of inconsistencies in deterministic optimal control models due to changing information and other aspects of stochasticity. Rational expectations models have been extensively used in this plan to resolve some of the inconsistency problems. The third phase has recently focused on the various aspects of adaptive control. where stochasticity and information- adaptivity are introduced in diverse ways e.g .? risk adjustment and risk sensitivity of optimal control, recursive updating rules via Kalman filtering and weighted recursive least squares and variable structure control methods in nonlinear framework. Problems of efficient econometric estimation of optimal control models have now acquired significant importance. This monograph provides an integrated view of control theory methods, synthesizing the three phases from feedback control to stochastic control and from stochastic control to ada
出版日期Book 1997
關(guān)鍵詞dynamic models; econometrics; economics; forecasting
版次1
doihttps://doi.org/10.1007/978-1-4615-6285-6
isbn_softcover978-1-4613-7885-3
isbn_ebook978-1-4615-6285-6
copyrightSpringer Science+Business Media New York 1997
The information of publication is updating

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發(fā)表于 2025-3-21 21:51:23 | 只看該作者
Risk Sensitivity, Adjustment of Control and Estimation,olutions explicitly allow for such mutual consistency. To estimate the optimal decision rule for each player in such a framework, one has to postulate the side condition specifying the second player’s reaction function. Thus the method of maximizing the likelihood function subject to each player’s r
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Friedrich E. Fahlbusch Dr.-Ing.olutions explicitly allow for such mutual consistency. To estimate the optimal decision rule for each player in such a framework, one has to postulate the side condition specifying the second player’s reaction function. Thus the method of maximizing the likelihood function subject to each player’s r
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Stochastic Control Theory,e stochastic process over time that may generate the deterministic control model. The second is the estimation aspect where the parameters of the deterministic control model are assumed to be unknown, and time series data are used for estimating those parameters.
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Variable Structure Systems,licies based on closed loop optimal control (CLOC) laws are the most powerful and stable, but yield a control vector with continuously changing components. Such policies work well in organizations or institutions with reliable information, with a centralized small group of decision makers, and with
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