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    ANALYSIS OF RELATIONSHIP BETWEEN GOVERMENT DOMESTIC DEBTS AND BASIC MACROECONOMIC INDICATORS IN TURKEY
    (Mehmet Akif Ersoy Univ, 2022) Gov, Abdullah; Yilanci, Veli
    Most of the algorithms used in the literature for the Granger (1969) causality test are based on a statistical significance test. The fact that the number of variables included in the model is sufficiently large may lead to some problems in the estimating of Granger causality test equations. Lozano et al. (2009) emphasizes that it is very important for Granger causality methods to formulate the group structure appropriately among lagged values of any time series. Bahadori and Liu (2013) stated that the Granger causality approach may not provide consistent results for a high-dimensional data set within sufficient number observations. In order to solve such problems in Granger causality tests, Granger causality approaches based on various penalized estimators are developed. The applications of Granger causality approaches based on various penalized estimators in the context of economic variables are very few in the literature. In this study, the causality relationship between goverment domestic debts and some basic macroeconomic indicators in Turkey is analyzed with Granger causality approaches based on various penalized estimators. According to the results of LASSO GN, elastic net GN and elastic net CGN tests, it was determined that there are bidirectional causal relationships between government debt, inflation, exchange rate, money supply, interest rate, industrial production index, and primary balance.
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    Testing the Convergence Hypothesis for OECD Countries: RALS Panel Fourier SURADF Unit Root Test
    (Sosyoekonomi Soc, 2020) Yilanci, Veli; Canpolat-Gokce, Esra
    The main aim of this study is to improve the SURADF panel unit root test of Breur et al. (2001) by considering structural breaks and the knowledge of non-normal distrubited residuals. Chang et al. (2012) introduce a new panel unit root test by allowing smooth structural breaks in SURADF test process. In this study, we also take into account of the information of the residuals that are nonnormally distrubited. We test the validity of stochastic convergence among 18 OECD countries using this newly suggested test and find supportive evidence of convergence for only seven countries.