Volume 1, Issue 1, June (2014)

Editors Introduction 1: ISSN 2148-6212


1) Nonlinearity and Smooth Breaks in Unit Root Testing

Tolga Omay            Dilem Yıldırım                                         2-9
We develop unit root tests that allow under the alternative hypothesis for a smooth transition between deterministic linear trends, around which stationary asymmetric adjustment may occur by employing exponential smooth transition auto-regressive (ESTAR) models The small sample properties of the newly developed test are briefly investigated and an application for investigating the PPP hypothesis for Argentina is provided.

Keywords: Smooth Break; Nonlinear Unit Root Test; PPP.

JEL Codes: C12; C22; O47.


2) Testing for a unit root in the presence of a nonlinear trend:

The case of Australian Reel Exchange Rate

Mübariz Hasanov                                                 10-17

In this paper, we examine stationarity of the Australian real exchange rate (RER). For this purpose, we modify the test of Kapetanios et. al. [Testing for a unit root in the nonlinear STAR framework. Journal of Econometrics 112 (2003) 359-379] to allow for a nonlinear trend function in the data generating process. Using bootstrap techniques, we show that the null hypothesis of unit root can be rejected, providing evidence in favour of PPP proposition for the Australian RER.

Keywords:   Purchasing Power Parity, Nonlinearity, Unit Root

JEL Codes: C12, C22, F31

3) A Survey about Bias Reduction in Smooth Transition Panel Data Analysis

Tolga Omay                                                                                      18-29

This study introduces a literature survey about the panel smooth transition regression models. This type of modeling emerged from two different strand of literature where the first is nonlinear time series the other is the panel data analysis. Both of these fields dealt with different type of biases in estimation process. Therefore, combining these two fields constitutes different problems in estimation. Hence, instead of giving the studies in chronological order, explanation of papers with respect to problems they have solved is preferred. Within this order, first the categories of different models are analyzed. For instance, there are several categorizations in the panel data estimation with respect to time and cross-section dimension. Therefore every category has its own biases depending on these. On the other hand the dynamic structure of the panel data is another important determinant in which classifies the biases. Hence, the static and dynamic panel smooth transition models are also discussed separately in this study. Finally, smooth transition models has its’ own categories, hence these categories under the panel categorization are given as well.

Keywords: Panel smooth transition data; Bias; Large-moderate-small panel data; static   panel data; dynamic panel data, Logistic, exponential,  time varying


4) Cross-section Dependency and the Effects of Nonlinearity in Panel Unit Testing                                                                          30-36

Furkan Emirmahmutoglu
In this study, we have analyzed the Cross Section Dependence (CSD) problem that is frequently encountered in a panel unit root setting by using the Pesaran (2004, 2008) CD tests. For this purpose we have generated cross sectionally dependent data and investigated the effects of nonlinear modeling on the cross section dependency problem inherited in panel analysis. The simulation study shows us that the nonlinear models remedy some part of this CSD.

Keywords: Panel Unit Root; Cross Section Dependency Bias; Cross Section Dependency Test.

Jel Classification: C1,C12