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    Analysis of Real Exchange Rate in Turkey with Nonlinear Models: Band-TAR and STAR Models
    (Bilgesel Yayincilik San & Tic Ltd, 2012) Ersin, Ozgur Omer
    Analysis of Real Exchange Rate in Turkey with Nonlinear Models: Band-TAR and STAR Models In this study, we aimed to analyze the Purchasing Power Parity (PPP) relation in Turkey for the Post-February 2001 Crisis period. In order to test PPP, in addition to the traditional approach that utilizes the linear unit root tests, the methodology focuses on the nonlinear econometric real exchange rate models. According to the empirical results obtained, the real exchange rate is accepted to follow unit root both in light of linear ADF and PP tests, which suggest rejection of PPP The KSS nonlinear unit root test shows that nonlinear unit root behavior cannot be rejected. Additionally, linearity in real exchange rates is rejected by the Hansen, Tray, Mcleod-Li and Luukkonnen et.al linearity tests. As a result, the study aimed at conducting the analysis with nonlinear Obsfeld and Taylor Band-TAR, Taylor et.al. ESTAR and the LSTAR2 model which is selected by the LM type STAR model selection tests. If models to investigate PPP are compared with Diebold Mariano tests and MSE, MAE and RMSE error criteria for forecast accuracy the success increased accordingly once we moved from linear to the nonlinear models - from AR towards Band-TAR, ESTAR, and LSTAR2. The results suggest that, for the flexible exchange rate period adopted after the Feb. 2001 Crisis in Turkey, PPP holds only for the outer regimes that occur if the real exchange rate appreciation or depreciation is larger than the upper or lower thresholds.
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    ASYMMETRIC POWER AND FRACTIONALLY INTEGRATED SUPPORT VECTOR AND NEURAL NETWORK GARCH MODELS WITH AN APPLICATION TO FORECASTING FINANCIAL RETURNS IN ISE100 STOCK INDEX
    (Editura Ase, 2014) Bildirici, Melike; Ersin, Ozgur Omer
    The study aims to augment commonly applied volatility models with support vector machines and neural networks. Further, fractional integration and asymmetric powers will be introduced. The proposed modeling strategy benefits from neural network based GARCH models and SVR-GARCH models. Following these approaches, the study proposed fractional integration and asymmetric power GARCH structures to obtain SVR-FIAPGARCH and NN-FIAPGARCH models to be evaluated in terms of learning algorithms. Models are evaluated for in-sample and out-of-sample forecasting of daily returns in Istanbul ISE100 stock index. Results suggest several findings: i. fractional integration and asymmetric power structures could be modeled with learning algorithms. ii. volatility clustering, asymmetry and nonlinearity characteristics are modeled more effectively with SVR-GARCH and MLP-GARCH models compared to the GARCH models. iii. SVR-GARCH models provided the lowest error criteria levels in out-of-sample and are closely followed by the MLP-GARCH models.
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    Economic growth and CO2 emissions: an investigation with smooth transition autoregressive distributed lag models for the 1800-2014 period in the USA
    (Springer Heidelberg, 2018) Bildirici, Melike; Ersin, Ozgur Omer
    The study aims to combine the autoregressive distributed lag (ARDL) cointegration framework with smooth transition autoregressive (STAR)-type nonlinear econometric models for causal inference. Further, the proposed STAR distributed lag (STARDL) models offer new insights in terms of modeling nonlinearity in the long- and short-run relations between analyzed variables. The STARDL method allows modeling and testing nonlinearity in the short-run and long-run parameters or both in the short- and long-run relations. To this aim, the relation between CO2 emissions and economic growth rates in the USA is investigated for the 1800-2014 period, which is one of the largest data sets available. The proposed hybrid models are the logistic, exponential, and second-order logistic smooth transition autoregressive distributed lag (LSTARDL, ESTARDL, and LSTAR2DL) models combine the STAR framework with nonlinear ARDL-type cointegration to augment the linear ARDL approach with smooth transitional nonlinearity. The proposed models provide a new approach to the relevant econometrics and environmental economics literature. Our results indicated the presence of asymmetric long-run and short-run relations between the analyzed variables that are from the GDP towards CO2 emissions. By the use of newly proposed STARDL models, the results are in favor of important differences in terms of the response of CO2 emissions in regimes 1 and 2 for the estimated LSTAR2DL and LSTARDL models.
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    Economic growth and CO2 emissions: an investigation with smooth transition autoregressive distributed lag models for the 1800-2014 period in the USA (vol 25, pg 200, 2017)
    (Springer Heidelberg, 2018) Bildirici, Melike; Ersin, Ozgur Omer
    The original publication of this paper contains a mistake.
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    An Empirical Analysis of the Effects of Consanguineous Marriages on Economic Development
    (Sage Publications Inc, 2010) Bildirici, Melike; Kokdener, Meltem; Ersin, Ozgur Omer
    In this study, development experiences toward economic development are investigated to provide an alternative analysis of economic development, human capital, and genetic inheritance in the light of consanguineous marriages. The countries analyzed in the study are discussed in accordance with consanguineous marriage practices and classified by their per capita gross domestic product (GDP) growth. A broad range of countries are analyzed in the study. Arab countries that experienced high rates of growth in their gross national income during the twentieth century but failed to fulfill adequate development measures as reflected in the growth in national income, countries undergoing transition from tight government regulation to free market democracy, and African nations that have experienced complications in the process of development show important differences in the process of economic development. It is shown that the countries that have reached high average development within the context of per capita GDP have overcome problems integral to consanguineous marriage.
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    Forecasting oil prices: Smooth transition and neural network augmented GARCH family models
    (Elsevier Science Bv, 2013) Bildirici, Melike; Ersin, Ozgur Omer
    The study focuses on a new class of nonlinear volatility models based on neural networks and STAR type nonlinearity. Accordingly, LSTAR-LST-GARCH family and LSTAR-LST-GARCH-NN family of models will be evaluated to analyze petrol prices with economic applications. The nonlinear behavior and leptokurtic distribution are discussed in many studies. The study aims proposing augmentation of linear GARCH, fractionally integrated FI-GARCH and Asymmetric Power APGARCH models with LSTAR type nonlinearity modeling. Further, the proposed models will be augmented with neural networks to benefit from well known learning and forecasting capabilities. The multilayer perceptron (MLP) neural network model and LSTAR model have significant similarities in terms of their architecture. The proposed LSTAR-LST-GARCH family and ANN augmented LSTAR-LST-GARCH-MLP models are evaluated for modeling petrol prices. Empirical findings of the study are: (1) Fractionally integrated and asymmetric power improvements among the GARCH family models provide better forecasting capability for petrol prices; better captured long memory and high volatility characteristics of petrol prices. (2). LSTAR-LST-GARCH model family results in even better gains in out-of-sample forecasting. (3) Donaldson and Kamstra (1997) based MLP-GARCH family provided similar results with the LSTAR-LST-GARCH family models. One exception is for MLP-FIGARCH and MLP-FIAPGARCH models; FI and AP augmented models proposed in this study. (4) Volatility clustering, asymmetry and nonlinearity characteristics of petrol prices are best captured with the LSTAR-LST-GARCH-MLP model family. Forecasting capabilities of neural network techniques are promising. Among the evaluated models, the LSTAR-LST-APGARCH-MLP model provided the best performance overall. With a political perspective, in addition to the highly volatile structure, the long memory characteristics of petrol prices requires that the economic policy interventions should be kept at the modest levels to avoid persistent impacts of shocks. (C) 2013 Elsevier B.V. All rights reserved.
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    Genetic structure, consanguineous marriages and economic development: Panel cointegration and panel cointegration neural network analyses
    (Pergamon-Elsevier Science Ltd, 2011) Bildirici, Melike; Ersin, Ozgur Omer; Kokdener, Meltem
    Consanguineous marriages and their effects on human beings in light of biological effects of genetic sicknesses are discussed in many studies. Among many, the likelihood of sicknesses such as phenylketonuria, thalassemia, Landsteiner-Fanconi-Anderson's syndrome, hemophilia and many neuro system anomalies increase drastically in countries with consanguineous marriage practices resulting in increasing economic costs. In the study, we aimed to analyze the effects of consanguineous marriage and its effect on economic growth and development. We also analyzed infant mortality in these countries in light of consanguineous marriages and economic development. In the study, Panel Cointegration specifications are integrated into Neural Network models known with their strong generalization properties. The study focuses the econometric analyses, where the Panel Cointegration Neural Network Model is investigated and compared to the Panel Cointegration Model. According to MSE, MAE and RMSE error criteria and Die-bold Mariano tests of equal forecast accuracy, the results suggest strong advantages of Panel Cointegration MLP models compared to Panel Cointegration models used in regression analysis. (C) 2010 Elsevier Ltd. All rights reserved.
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    NONLINEARITY, VOLATILITY AND FRACTIONAL INTEGRATION IN DAILY OIL PRICES: SMOOTH TRANSITION AUTOREGRESSIVE ST-FI(AP)GARCH MODELS
    (Inst Economic Forecasting, 2014) Bildirici, Melike; Ersin, Ozgur Omer
    The study aims to extend the GARCH type volatility models to their nonlinear TAR (Tong, 1990) and STAR-based (Terasvirta, 1994) counter parts where both the conditional mean and the conditional variance processes follow TAR and STAR nonlinearity. The paper further investigates the models under their fractional integration and asymmetric power variants. The STAR-based models are LSTAR-LST-GARCH, LSTAR-LST-FIGARCH, LSTAR-LST-FIPGARCH and LSTAR-LST-FIAPGARCH models, which may be easily applied to model and forecast various financial time series. In the empirical section, an application is provided to model the daily returns in WTI crude oil prices considering the regime shifts the crude oil prices were subject to during history. Models are evaluated in terms of their out-of-sample forecasting capabilities with equal forecast accuracy tests and also in terms of various error criteria. The results suggest that volatility clustering, asymmetry and nonlinearity characteristics are modeled more efficiently as compared to their single regime variants, such as the GARCH, FIGARCH and FIAPGARCH models. Further, the out-of-sample results suggest that the LSTAR-LST-FIAPGARCH model provides the best forecasting accuracy in terms of RMSE and MSE error criteria.
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    PSYCHOLOGICAL DOMINANCE, MARKET DOMINANCE AND THEIR IMPACTS IN TURKEY
    (Editura Ase, 2015) Bildirici, Melike; Parasiz, Ilker; Ersin, Ozgur Omer; Aykac-Alp, Elcin
    The study focuses on analyzing an economy that applies an inflation-targeting rule in which the policy interest rate is determined actively by the Taylor rule, and the policy maker involuntarily becomes the affirmant of inflation. In an economy that applies inflation-targeting policy where interest rates are determined in light of the Taylor rule, as the Central Bank tries to establish price stability and financial stability by determining policy interest rates, the Central Bank might fall into a position to do nothing but to assent inflation. In the empirical section, two new indices, the psychological dominance (pdi) and market dominance indices (mdi) are developed based on the difference between the policy rates. The band within which the indices follow random walk processes are determined with Band-TAR models. The CB policy is additionally modeled with a nonlinear Taylor rule with TVEC models. The most significant point of the process is its inflation-creating effect. By moving from the Turkey example, the main problem in the policies of Central Bank of Turkey is the difference between the borrowing and lending rates and its inflationary effect.