Panel cointegration

Using panel data error correction models, we investigate the short- and long-run causality between financial development and economic growth in the Middle East. Three different indicators are used to measure financial developments. Generalized Least Square (GLS) method with cross-section Seemingly Unrelated Regression (SUR) and fixed effecst in cross dimension is used to estimate the models. Our estimation results suggest that there is bidirectional causality between financial development and economic growth in both the short- and long run. The result underscores the feedback between finance and growth and hence advocates the third view that emphasizes on mutual causality between financial development and economic growth. In other words, finance can promote growth and in turn output growth will enhance financial development in the Middle East. This results can have important policy implications for both policymakers and international institutions.

In this study, considering the necessity and importance of the relationship between risk and return on investment, some explanations were presented about the relationship between risk and return on the asset portfolio including gold, exchange and stocks during the period 2001: 1 - 2018: 3 using panel vector auto-regression (PVAR) method and Kao and Pedroni panel cointegration approach and pooled mean group (PMG) method and Engel-Granger time series methods. The software used in this study involves EVIEWS 10 and STATA15. In this study, multivariate GARCH (M-GARCH) approach (BEKK) was used to extract portfolio risk. The results showed a positive relationship between risk and return based on PVAR approach. And also, given the beta coefficient of the CAPM equation, gold was the best inflation cover during the period under study, with a slight difference from the exchange rate.