The purpose of this study is to determine whether composite leading indicators are a leading indicator feature for developed and emerging stock exchange. It is also to show how it differs in developed and developing countries. For this purpose, panel cointegration and causality analyzes were applied with data from January 2002 to June 2017 for these countries. In addition, AMG method was used for long term coefficient estimations. As a result of the analysis, the long-run relationship between the variables was not significant with the Durbin-Hausman cointegration test. However, in the Westerlund Multi-Breaks LM Test results, the long-run relationship among variables was found to be significant around breaks. In the coefficient estimates, a positive significant relationship was found in both of the G7 and E7 countries, but this relationship was found to be stronger in the G7 countries. Finally, the results of the Emirmahmutoğlu-Köse causality test show that there are two-way causality among variables for both groups of countries.