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Article Real Interest Rate Parity in Latin American Countries: Evidence from New Panel Unit Root Tests(Wiley, 2026) Omay, Tolga; Abioglu, Vasif; Hasanli, MubarizIn this study, we test the empirical validity of the real interest rate parity hypothesis for 15 Latin American countries over the period 2005-2023. To this end, we employ a battery of panel unit root tests to examine stochastic properties of the real interest rate differentials (RIDs) of the countries under consideration. The panel unit root tests that allow for both the cross-sectional dependence and the nonlinearities in the adjustment process do not reject the null of unit root for the most of these countries, suggesting that the real interest rate parity hypothesis does not hold for these countries. On the other hand, the panel unit root test that allows for smooth structural changes produces results consistent with the real interest rate parity hypothesis for 12 out of 15 Latin American countries. These findings imply that various shocks, including political, economic, and financial upheavals, can cause significant structural shifts in the RIDs of Latin American countries.Article Citation - Scopus: 2The Refinement of a Common Correlated Effect Estimator in Panel Unit Root Testing: an Extensive Simulation Study(Mdpi, 2024) Omay, Tolga; Akdi, Yilmaz; Emirmahmutoglu, Furkan; Eryilmaz, MeltemThe Common Correlated Effect (CCE) estimator is widely used in panel data models to address cross-sectional dependence, particularly in nonstationary panels. However, existing estimators have limitations, especially in small-sample settings. This study refines the CCE estimator by introducing new proxy variables and testing them through a comprehensive set of simulations. The proposed method is simple yet effective, aiming to improve the handling of cross-sectional dependence. Simulation results show that the refined estimator eliminates cross-sectional dependence more effectively than the original CCE, with improved power properties under both weak- and strong-dependence scenarios. The refined estimator performs particularly well in small sample sizes. These findings offer a more robust framework for panel unit root testing, enhancing the reliability of CCE estimators and contributing to further developments in addressing cross-sectional dependence in panel data models.
