This paper connects variance–covariance estimation methods, Gaussian graphical models, and the growing literature on economic and financial networks. We construct the network using the concept of partial correlations which captures direct linear dependence between any two entities, conditional on dependence between all other entities. We relate the centrality measures of this network to shock propagation. The methodology is applied to construct the perceived network of publicly traded Australian banks and their connections to domestic economic sectors and international markets. We find strong links between the big four Australian banks, real estate and other sectors of the economy, and determine which entities play a central role in transmitting and absorbing the shocks.

We investigate the extent to which emerging stock market integration affects the joint behavior of stock and bond returns using a two-stage semi-parametric approach. Using a sample of 18 emerging markets, we find an unambiguous and robust link between emerging stock market integration and stock–bond return decoupling. We explain this with a decline in the segmentation risk premia in equities modeled by De Jong and De Roon [De Jong, F., De Roon, F.A., 2005. Time-varying market integration and expected returns in emerging markets. Journal of Financial Economics 78, 583–613] that leads to increased demand for stocks and reduced or unchanged demand for bonds. Our findings deliver new insights into the financial liberalization and stock–bond comovement literatures.