Lecture Applied econometric time series (4e) - Chapter 7: Nonlinear models and breaks

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Lecture Applied econometric time series (4e) - Chapter 7: Nonlinear models and breaks

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This chapter presents the following content: Linear versus nonlinear adjustment, simple extensions of the ARMA model, testing for nonlinearity, threshold autoregressive models, extensions of the TAR model, three threshold models, smooth transition models,...

Applied Econometric Time Series  4rd ed Walter Enders Chapter 7 Walter Enders, University of Alabama AETS 3rd edition Copyright © 2015 John, Wiley & Sons, Inc. All rights reserved LINEAR VERSUS NONLINEAR ADJUSTMENT • • • On a long automobile trip to a new location, you might take  along a road atlas. … For most trips, such a linear  approximation is extremely useful. Try to envision the  nuisance of a nonlinear road atlas.  For other types of trips, the linearity assumption is clearly  inappropriate. It would be disastrous for NASA to use a flat  map of the earth to plan the trajectory of a rocket launch.  Similarly, the assumption that economic processes are linear  can provide useful approximations to the actual time­paths of  economic variables.  – Nevertheless, policy makers could make a serious error if  they ignore the empirical evidence that unemployment  increases more sharply than it decreases Copyright © 2015 John, Wiley & Sons, Inc. All rights reserved The Use of Nonlinear Models • • It is now generally agreed that linear econometric models do not  capture the dynamic relationships present in many economic time­ series.  – The observation that firms are more apt to raise than to lower  prices is a key feature of many macroeconomic models.  – Neftci (1984), Falk(1986), DeLong and Summers (1988), Granger  and Lee (1989), and Teräsvirta and Anderson (1992) establish the  result that many real variables display non­linear adjustment over  the course of the business cycle.  – In several papers, Enders and Sandler model many terrorist  incident series as nonlinear However, adopting an incorrect non­linear specification may be more  problematic than simply ignoring the non­linear structure in the data.  It is not surprising, therefore, that non­linear model selection is an  importantareaofcurrentresearch Copyrightâ2015John,Wiley&Sons,Inc.Allrightsreserved TheInterestRateSpread Thereisevidencethatinterestratespreads(st)displaya nonlinearadjustmentpattern st s s a1 ( st a2 ( st 1 s) s) 1t 2t when st when st 1 s s As long as | a2 | > | a1 |, periods when st–1 

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Mục lục

  • Slide 1

  • LINEAR VERSUS NONLINEAR ADJUSTMENT

  • The Use of Nonlinear Models

  • The Interest Rate Spread

  • Slide 5

  • Slide 6

  • Autoregressive Moving Average (ARMA) Models

  • The NLAR(p) Model

  • Generalized Autoregressive (GAR) Models

  • Bilinear Autoregressive (BL) Models

  • Slide 11

  • Rothman’s unemployment estimates (1998)

  • Rothman II

  • Exponential Autoregressive (EAR) Models

  • The ACF Can be Misleading in a Nonlinear Model

  • Some Tests for Nonlinearity

  • Regression Error Specification Test (RESET)

  • Specific Testing for Nonlinearity

  • Example 1

  • Example 2: Bilinear Model

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