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Tuesday, July 14, 2020 | History

4 edition of Are apparent findings of nonlinearity due to structural instability in economic time series? found in the catalog.

Are apparent findings of nonlinearity due to structural instability in economic time series?

Gary Koop

Are apparent findings of nonlinearity due to structural instability in economic time series?

by Gary Koop

  • 69 Want to read
  • 19 Currently reading

Published by Federal Reserve Bank of New York in [New York, N.Y.] .
Written in English

    Subjects:
  • Time-series analysis.

  • Edition Notes

    StatementGary Koop and Simon M. Potter.
    SeriesStaff reports ;, no. 59, Staff reports (Federal Reserve Bank of New York : Online) ;, no. 59.
    ContributionsPotter, Simon M., Federal Reserve Bank of New York.
    Classifications
    LC ClassificationsHB1
    The Physical Object
    FormatElectronic resource
    ID Numbers
    Open LibraryOL3476916M
    LC Control Number2005616488

    This book explains modeling at standard level how other general books, but not in full details in and out. Also down side is not examples to understand the problem better. I recommended to go for other time series modeling book if people want do some sort of research on time series modelling in Cited by: Sayers C.L. () Testing for Chaos and Nonlinearities in Macroeconomic Time Series. In: Semmler W. (eds) Business Cycles: Theory and Empirical Methods. Recent Economic Thought Series, vol Cited by: 2.

    aggregate time series of actual variables would typically have a broad band power spectrum, of-ten with a predominance of low frequencies - see, for example, Clive Granger and Paul Newbold (). 4Ibid., pp. 5Even when the outcome is periodic, however, if the periodicity is long and the time path very. of time series Billio et al. (, ); Allen et al. (). Such comparison is not correct in general and fails to capture the true underlying network as we will see in the next example. For moredetailspleaseseeQuinnetal.(). Example1: As an example, consider a network of three times series {X,Y,Z} with the following 5.

    Additive, multiple, and time-varying STR models 40 Vector smooth transition autoregressive model 41 Polynomial models 41 Artificial neural network models ~ 43 Min-max models 45 Nonlinear moving average models 46 Bilinear models 47 Time-varying parameters and state space models undertake a systematic study of a wide variety of economic time series and find that the majority of these are subject to structural breaks. Alogoskoufis and Smith () and Garcia and Perron () are other examples of studies that document instability related to the autoregressive terms in forecasting models. Clements and Hendry (


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Are apparent findings of nonlinearity due to structural instability in economic time series? by Gary Koop Download PDF EPUB FB2

For a published version of this report, see Gary Koop and Simon Potter, "Are Apparent Findings of Nonlinearity Due to Structural Instability in Economic Time Series?" Econometrics Journal 4, no. 1 (January ): Are apparent findings of nonlinearity due to structural instability in economic time series.

Article in Econometrics Journal 4(1) February with 7 Reads How we measure 'reads'. An empirical exercise involving several macroeconomic time series shows that apparent findings of threshold type nonlinearities could be due to structural instability.

Many modelling issues and policy debates in macroeconomics depend on whether macroeconomic time series are best characterized as linear or nonlinear.

An empirical exercise involving several macroeconomic time series shows that apparent findings of threshold-type nonlinearities could be due to structural instability.

Many modeling issues and policy debates in macroeconomics depend on whether macroeconomic times series are best characterized as linear or nonlinear. "Are apparent findings of nonlinearity due to structural instability in economic time series?," Econometrics Journal, Royal Economic Society, vol.

4(1), pages 1 Cited by: 1. "Are apparent findings of nonlinearity due to structural instability in economic time series?," Econometrics Journal, Royal Economic Society, vol.

4(1), pages 1. Koop G, Potter S () Are apparent findings of nonlinearity due to structural instability in economic time series.

Econometrics Journal 4: 37–55 CrossRef Google Scholar Lo MC, Piger J () Is the response of output to monetary policy asymmetric?Cited by: 1. An extensive performance evaluation of the BDS is ear Dynamics, Chaos, and Instability also reviews important issues in the theoretical economics literature on chaos and complex dynamics, surveys existing work on the detection of chaos and nonlinear structure, and develops models and processes to discover predictable sequencing Cited by:   Are apparent findings of nonlinearity due to structural instability in economic time series.

Econometric Journal, 4, 37– Jones C.M. () Forecasting of Time Series Data Using Multiple Break Points and Mixture Distributions. In: Toni B. (eds) New Frontiers of Multidisciplinary Research in STEAM-H (Science, Technology, Engineering Author: Rajan Lamichhane, Norou Diawara, Cynthia M.

Jones. Nonlinear Econometric Modeling in Time Series: Proceedings of the Eleventh International Symposium in Economic Theory (International Symposia in Economic Theory and Econometrics): Economics Books @ Instability and Nonlinearity in the Euro-Area Phillips Curve∗ Alberto Musso a, Livio Stracca, and Dick van Dijkb aEuropean Central Bank bEconometric Institute, Erasmus University Rotterdam This paper provides a comprehensive analysis of the func-tional form.

1 Introduction. Structural changes or “breaks” appear to affect models for the evolution in key economic and financial time series such as output growth, inflation, exchange rates, interest rates, and stock returns. 1 This could reflect legislative, institutional or technological changes, shifts in economic policy, or could even be due to large macroeconomic shocks such as the doubling or Cited by: Nonlinearity and structural stability in the Phillips curve: Evidence from Turkey Article in Economic Modelling 27(5) September with Reads How we measure 'reads'.

An empirical exercise involving several macroeconomic time series shows that apparent findings of threshold type nonlinearities could be due to structural instability. JEL: C22, C11, E30 ViewAuthor: Jacek Kwiatkowski.

Nonlinear Dynamics, Chaos, and Instability also reviews important issues in the theoretical economics literature on chaos and complex dynamics, surveys existing work on the detection of chaos and nonlinear structure, and develops models and processes to discover predictable sequencing in time-series data, such as stock returns, that currently.

There are two main sources to cause nonlinearity in time series analysis. According to the Giordani et al. (), the presence of nonlinearity is caused by the structural change; however, Goodwin.

This book provides a synthesis of concepts and materials that ordinarily appear separately in time series and econometrics literature, presenting a comprehensive review of both theoretical and applied concepts. Perhaps the most novel feature of the book is its use of Kalman filtering together with econometric and time series methodology.

From a technical point of view, state space models and /5(3). The Structural Econometric Time Series Analysis Approach Bringing together a collection of previously published work, this book provides a timely discussion of major considerations relating to the con-struction of econometric models that work well to explain economic phenomena, predict future outcomes, and be useful for policy-making.

Nonlinear Modelling of High Frequency Financial Time Series Edited by Christian Dunis and Bin Zhou In the competitive and risky environment of today's financial markets, daily prices and models based upon low frequency price series data do not provide the level of accuracy required by traders and a growing number of risk managers.4/5(1).

In economics, structural change is a shift or change in the basic ways a market or economy functions or operates. Such change can be caused by such factors as economic development, global shifts in capital and labor, changes in resource availability due to war or natural disaster or discovery or depletion of natural resources, or a change in political system.

Stock and Watson: Structural Instability in Macroeconomic Time Series Relations 13 test has as its null hypothesis that the parameters are con- stant; that is, pt = p, at(L) = a(L) and 3t3(L) = fl(L).

The derivation of the null distributions of the test statistics also assumes that .This book contains an extensive up-to-date overview of nonlinear time series models and their application to modelling economic relationships.

It considers nonlinear models in stationary and nonstationary frameworks, and both parametric and nonparametric models are discussed. The book contains examples of nonlinear models in economic theory and presents the most common nonlinear.

The book covers econometric modelling and time series analysis techniques in five parts. Part I focuses on sunspot equilibria, the study of uncertainty generated by nonstochastic economic models.

Part II examines the more traditional examples of Author: William A. Barnett.