Application of nonlinear unit root tests and threshold autoregressive models

Download

index.pdf

Date

2012

Author

Uysal, Ela

Metadata

Show full item record

Item Usage Stats

210
views

80
downloads

Popularity of nonlinear threshold models and unit root tests has increased after the recent empirical studies concerning the effects of business cycles on macroeconomic data. These studies have shown that an economic variable may react differently in response to downturns and recoveries in a business cycle. Inspiring from empirical results, this thesis investigates dynamics of Turkish key macroeconomic data, namely capacity utilization rate, growth of import and export volume indices, growth of gross domestic product, interest rate for cash loans in Turkish Liras and growth of industrial production index. Estimation results imply that capacity utilization rate and growth of industrial production index show M-TAR type nonlinear stationary behavior according to the unit root test proposed by Enders and Granger (1998).

Subject Keywords

Nonlinear pricing, Macroeconomics, Macroeconomics

URI

http://etd.lib.metu.edu.tr/upload/12614878/index.pdf
https://hdl.handle.net/11511/21843

Collections

Graduate School of Social Sciences, Thesis

Suggestions

OpenMETU
Core

Nonlinear Decentralized Data Fusion with Generalized Inverse Covariance Intersection Noack, Benjamin; Orguner, Umut; Hanebeck, Uwe D. (2019-01-01) Decentralized data fusion is a challenging task even for linear estimation problems. Nonlinear estimation renders data fusion even more difficult as dependencies among the nonlinear estimates require complicated parameterizations. It is nearly impossible to reconstruct or keep track of dependencies. Therefore, conservative approaches have become a popular solution to nonlinear data fusion. As a generalization of Covariance Intersection, exponential mixture densities have been widely applied for nonlinear fu...
Advanced mathematical and statistical tools in the dynamic modelling and simulation of gene-environment networks Purutçuoğlu Gazi, Vilda (Springer, 2014-01-01) In this study, some methodologies and a review of the recently obtained new results are presented for the problem of modeling, anticipation and forecasting of genetic regulatory systems, as complex systems. In this respect, such kind of complex systems are modeled in the dynamical sense into the two different ways, namely, by a system of ordinary differential equations (ODEs) and Gaussian graphical methods (GGM). An artificial time-course microarray dataset of a gene-network is modeled as an example by usin...
Modeling and implementation of local volatility surfaces in Bayesian framework Animoku, Abdulwahab; Uğur, Ömür; Yolcu-Okur, Yeliz (2018-06-01) In this study, we focus on the reconstruction of volatility surfaces via a Bayesian framework. Apart from classical methods, such as, parametric and non-parametric models, we study the Bayesian analysis of the (stochastically) parametrized volatility structure in Dupire local volatility model. We systematically develop and implement novel mathematical tools for handling the classical methods of constructing local volatility surfaces. The most critical limitation of the classical methods is obtaining negativ...
Integrability of Kersten-Krasil'shchik coupled KdV-mKdV equations: singularity analysis and Lax pair Karasu, Emine Ayşe; Yurdusen, I (AIP Publishing, 2003-04-01) The integrability of a coupled KdV-mKdV system is tested by means of singularity analysis. The true Lax pair associated with this system is obtained by the use of prolongation technique. (C) 2003 American Institute of Physics.
Comparison of iterative algorithms for parameter estimation in nonlinear regression Musluoğlu, Gamze; Akkaya, Ayşen; Department of Statistics (2018) Nonlinear regression models are more common as compared to linear ones for real life cases e.g. climatology, biology, earthquake engineering, economics etc. However, nonlinear regression models are much more complex to fit and to interpret. Classical parameter estimation methods such as least squares and maximum likelihood can also be adopted to fit the model in nonlinear regression as well, but explicit solutions can not be achieved unlike linear models. At this point, iterative algorithms are utilized to ...

Citation Formats

E. Uysal, “Application of nonlinear unit root tests and threshold autoregressive models,” M.S. - Master of Science, Middle East Technical University, 2012.