Graphical abstract Abstract This paper examines the relationship between financial inclusion and economic growth in Organization of Islamic Cooperation (OIC) countries. In order to draw multilateral results, we have set up the panel data for 55 OIC countries and estimated not only the dynamic panel estimation, but also the panel VAR, IRFs, and panel Granger causality tests. Based on the results of dynamic panel estimations, we find that financial inclusion has a positive effect on economic growth. The IFRs results derived from the panel VAR analysis suggest that financial inclusion has positive effects on the economic growth and financial inclusion and economic growth have mutual causalities with each other based on the panel Granger causality tests. Therefore, it seems reasonable to conclude that financial inclusion has positive effect on the economic growth in OIC countries.

Highlights • We find that sovereign CDS and bond markets are co-integrated. • The sovereign bond market mostly leads in price discovery by adjusting to new information regarding credit risk before CDS. • We find a positive correlation between financial integration and bond market information share. • Changes in sovereign credit risk and bond yields are influenced by common global factors. Abstract This study investigates the link between the price discovery dynamics in sovereign credit default swaps (CDS) and bond markets and the degree of financial integration of emerging markets. Using CDS and sovereign bond spreads, the price discovery mechanism was tested using a vector error correction model. Financial integration is measured using news-based methods. We find that sovereign CDS and bond markets are co-integrated. In five out of seven sovereigns (71%), the bond market leads in price discovery by adjusting to new information regarding credit risk before CDS. In 29% of times, CDS markets are the source of price discovery. We also find a positive correlation of 0.67 between the degree of financial integration and the bond market information share. The evidence suggests that changes in sovereign credit risk and bond yields are significantly influenced by common external (global) factors, while country-specific factors play an insignificant role.

We investigate financial integration of MENA region to facilitate a more in-depth exploration of the structure of interdependence and transmission mechanism of stock returns and volatility between MENA and world stock markets. The EGARCH-M models with a generalized error distribution are employed to consider both leverage effect of negative shocks and leptokurtosis prevalent in the MENA stock markets. The estimation results of multivariate AR-GARCH models indicate that there are large and predominantly positive volatility spillovers and volatility persistence in conditional volatility between MENA and world stock markets. Own-volatility spillovers are generally higher than cross-volatility spillovers for all the markets.

We investigate financial integration of MENA region to facilitate a more in-depth exploration of the structure of interdependence and transmission mechanism of stock returns and volatility between MENA and world stock markets. The EGARCH-M models with a generalized error distribution are employed to consider both leverage effect of negative shocks and leptokurtosis prevalent in the MENA stock markets. The estimation results of multivariate AR-GARCH models indicate that there are large and predominantly positive volatility spillovers and volatility persistence in conditional volatility between MENA and world stock markets. Own-volatility spillovers are generally higher than cross-volatility spillovers for all the markets.

This paper proposes asymmetric GARCH-Jump models that synthesize autoregressive jump intensities and volatility feedback in the jump component. Our results indicate that these models provide a better fit for the dynamics of the equity returns in the US and emerging Asian markets； irrespective whether the volatility feedback is generated through a common GARCHmultiplier or a separate measure of volatility in the jump intensity function. We also find that they can capture several distinguishing features of the return dynamics in emerging markets； such as； more volatility persistence； less leverage effects； fatter tails； and greater contribution and variability of the jump component. JEL Classification: C22； F31； G15