The concept of causality, developed by Wiener (1956) and Granger (1996), has been a cornerstone for examining the dynamic relationships between time series. Since the Granger causality relationship helps researchers to formulate a suitable model and obtain better predictions for the variables, it has attracted attention in the literature and the Granger causality test has been employed in many studies. In this study, current methods used in Granger causality tests are included. In this context, in the relevant sections, the regime-dependent causality test proposed by Krolzig (1996), the lag-augmented VAR-based causality test developed by Toda and Yamamoto (1996), the causality test in variance proposed by Hong (2001), the frequency domain test developed by Breitung and Candelon (2006), the asymmetric causality test developed by Hatemi-J (2012), and Fourier Granger causality test proposed by Enders and Jones (2016) are discussed theoretically and empirically. We would like to thank all the chapter authors who contributed to the book.