In this study, relationship between inflation and inflation uncertainty is analyzed using Granger causality tests with annual inflation series covering the time period 1923 to 2012 for Turkish Economy. Inflation uncertainty is measured by Exponential Generalized Autoregressive Conditional...

In this paper, we investigate whether the currency substitution can affect the exchange rate uncertainty for the Turkish economy. Considering the whole time period 1987M01-2006M12 as well as thesub-periods 1987M01-1999M12 and 2001M03-2006M12 for sensitivity analysis, our estimation results...

Abstract: In this study, the relationship between inflation and inflation uncertainty is analyzed using Granger causality tests with annual inflation series covering the time period 1923 to 2012 for Turkish Economy. Inflation uncertainty is measured by Exponential Generalized Autoregressive...

The purpose of this paper is to analyze the dynamics of crude oil prices of OPEC and non-OPEC countries using threshold cointegration. To capture the long run asymmetric price transmission mechanism, we develop an error correction model within a threshold cointegration and CGARCH errors...

Unanticipated shocks could lead to instability, which is reflected in statistically significant changes in distributions of random variables. Changes in the conditional moments of stationary variables are predictable. We provide a framework based on a statistic for the Sample Generalized...

Unanticipated shocks could lead to instability, which is reflected in statistically significant changes in distributions of independent Gaussian random variables. Changes in the conditional moments of stationary variables are predictable. We provide a framework based on a statistic for the...

This paper considers statistical inference for nonstationaryGaussian processes with long-range dependence and intermittency. The existence of such a process has been established by Anh et al. (J. Statist. Plann. Inference 80 (1999) 95–110). We systematically consider the case where the...

Nonparametric methods have been very popular in the last couple of decades in time series and regression, but no such development has taken place for spatial models. A rather obvious reason for this is the curse of dimensionality. For spatial data on a grid evaluating the conditional mean given...

In this paper, we consider some identification, estimation and specification problems in a class of semi-linear time series models. Existing studies for the stationary time series case have been reviewed and discussed. We also establish some new results for the integrated time series case. In...

This paper considers the problem of estimating a simultaneous spatial autoregressive model (SSAR). We propose using the quasi maximum likelihood method to estimate the model. The asymptotic properties of the maximum likelihood estimator including consistency and limiting distribution are...