Smooth Transition Regression models: Theory and Applications in JMulti
DOI:
https://doi.org/10.5902/2179460X40466Keywords:
Smooth transition, Structural Break, Nonlinearity, Time SeriesAbstract
This tutorial aims to analyze nonlinear models of Smooth Transition Regression with JMulTi and contribute to the understanding of STR specification, from the estimation until the evaluation cycle of these models. It provides pedagogical explanations, combining theoretical concepts and empirical results coherently. Especially in economic relationships, where an asymmetric behaviour with distinct effects is often found on contractions and expansions. As economic series generally present asymmetric/nonlinear behaviour, Smooth Transition Regression (STR) models provide a flexible empirical strategy that allows capturing the impacts of possible types of asymmetry in the data, Souza (2016).An overview of theory and applications in software is described. These nonlinear models describe in-sample movements of the stock returns series better than the corresponding linear model. The data used in this study consist of daily prices index from January 02, 1995 to March 29, 2013, a total of 4761 observations, from Germany (DAX30). The data was collected from the DataStream database considering 5 days a week. The data (price index) is converted to base 100 and the yields are then calculated based on the first differences in the log price series. 10-year interest rates treasury bond regarding the same markets identified has also been collected for the same period.
Downloads
References
AMSLER C, LEE J. An LM test for a unit root in the presence of a structural change. Econometric Theory [internet]. 1995;11(2), 359-368. Available from: https://www.cambridge.org/core/journals/econometric-theory/article/an-lm-test-for-a-unit-root-in-the-presence-of-a-structural-change/120C11ADC073BCD02D49C347FD7417AF
BANERJEE A, LUMSDAINE RL, STOCK JH. Stock Recursive and sequential tests of the unit-root and trend-break hypothesis: theory and international evidence. Journal of Business and Economic Statistics. 1992;10(3), 271-287.
CAVALIERE G, GEORGIEV I. A note on unit root testing in the presence of level shifts. Statistica. 2005;66(1), 3-17.
CAVALIERE G, GEORGIEV I. Testing for unit roots in autoregressions with multiple level shifts. Working Paper. 2005 ;
CHANG T, SU CW, LIU YS. Purchasing power parity with nonlinear threshold unit root test. Applied Economics Letters. 2012;19, 839–842.
EITRHEIM O, TERASVIRTA T. Testing the adequacy of smooth transition autoregressive models. Journal of Econometrics. 1996;74, 59-75.
FERRER AG. On Granger’s predictability of financial markets in theory and practice. International Journal of Forecasting. 2012;28, 121–127.
GLYNN J, PERERA N, VERMA R. Unit root tests and structural breaks: a survey with applications. Journal of Quantitative Methods for Economics and Business Administration. 2007;3(1), 63-79.
KWIATKOWSKI D, PHILLIPS PCB, SCHMIDT P, SHIN Y. Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics. 1992;54, 159-178.
JARQUE CM, BERA AK. Efficient tests for normality, homoskedasticity and serial independence of regression residuals. Economic Letters 1980;6, 255-259.
LOMNICKI ZA. Tests from departure from normality in the case of linear stochastic processes. Metrika. 1961;4, 27-62.
LANNE M, LUTKEPOHL H, SAIKKONEN P. Test Procedures for Unit Roots in Time Series with Level Shifts at Unknown Time. Humboldt University of Berlin Discussion Paper. 2001;(39).
LANNE M, LUTKEPOHL, SAIKKONEN P. Comparison of unit root tests for time series with level shifts. Journal of Time Series Analysis. 2002;23, 667-685.
LEE J, STRAZICICH MC. Break Point Estimation and Spurious Rejections with Endogenous Unit Root Tests. Oxford Bulletin of Economics and Statistics. 2001;63, 535-558.
LEE J, STRAZICICH MC. Minimum Lagrange Multiplier unit root test with two structural breaks. Review of Economics and Statistics. 2003;85(4), 1082-1089.
LEE J, STRAZICICH MC. Minimum LM unit root test with one structural break. Working Paper. Department of Economics. Appalachian: Appalachian State University; 2004.
LEE CF, TSONG CC. A revisit on real interest rate parity hypothesis - simulation evidence from efficient unit root tests. Applied Economics. 2012;44, 3089–3099.
LI XM. The Great Leap Forward, economic reforms and the unit root hypothesis: Testing for breaking trend functions in China’s GDP data. Journal of Comparative Economics. 2000; 28, 814– 827.
LUMSDAINE RL, PAPELL DH. Multiple trend breaks and the unit root hypothesis. Review of Economics and Statistics. 1997;79(2), 212-218.
LUTKEPOHL H, MULLER C, SAIKKONEN P. Unit root tests for time series with a structural break when the break point is known, in Hsiao, C., K. Morimune e J. Powell (Eds.), Nonlinear Statistical Inference: Essays in Honor of Takeshi Amemiya, Cambridge: Cambridge University Press. 2001;327-348.
NELSON C, PLOSSER C.Trends and random walks in macroeconomic time series. Journal of Monetary Economics. 1982;10, 139– 162.
NUNES L, NEWBOLD P, KUAN C. Testing for Unit Roots with Breaks Evidence on the Great Crash and the Unit Root Hypothesis Reconsidered. Oxford Bulletin of Economics and Statistics. 1997;59, 435-448.
PERRON P. The great crash. the oil price shock and the unit root hypothesis. Econometrica. 1989;57, 1361– 1401.
PERRON P. Testing for a unit root in a time series with a changing mean. Journal of Business and Economic Statistics. 1990;8(2), 153-162.
Published
How to Cite
Issue
Section
License
To access the DECLARATION AND TRANSFER OF COPYRIGHT AUTHOR’S DECLARATION AND COPYRIGHT LICENSE click here.
Ethical Guidelines for Journal Publication
The Ciência e Natura journal is committed to ensuring ethics in publication and quality of articles.
Conformance to standards of ethical behavior is therefore expected of all parties involved: Authors, Editors, Reviewers, and the Publisher.
In particular,
Authors: Authors should present an objective discussion of the significance of research work as well as sufficient detail and references to permit others to replicate the experiments. Fraudulent or knowingly inaccurate statements constitute unethical behavior and are unacceptable. Review Articles should also be objective, comprehensive, and accurate accounts of the state of the art. The Authors should ensure that their work is entirely original works, and if the work and/or words of others have been used, this has been appropriately acknowledged. Plagiarism in all its forms constitutes unethical publishing behavior and is unacceptable. Submitting the same manuscript to more than one journal concurrently constitutes unethical publishing behavior and is unacceptable. Authors should not submit articles describing essentially the same research to more than one journal. The corresponding Author should ensure that there is a full consensus of all Co-authors in approving the final version of the paper and its submission for publication.
Editors: Editors should evaluate manuscripts exclusively on the basis of their academic merit. An Editor must not use unpublished information in the editor's own research without the express written consent of the Author. Editors should take reasonable responsive measures when ethical complaints have been presented concerning a submitted manuscript or published paper.
Reviewers: Any manuscripts received for review must be treated as confidential documents. Privileged information or ideas obtained through peer review must be kept confidential and not used for personal advantage. Reviewers should be conducted objectively, and observations should be formulated clearly with supporting arguments, so that Authors can use them for improving the paper. Any selected Reviewer who feels unqualified to review the research reported in a manuscript or knows that its prompt review will be impossible should notify the Editor and excuse himself from the review process. Reviewers should not consider manuscripts in which they have conflicts of interest resulting from competitive, collaborative, or other relationships or connections with any of the authors, companies, or institutions connected to the papers.
