What we Understand by Financial Stability: Text Analysis with Network Approach

During the last decade the financial stability became one of the key concepts in the macroeconomic and financial literature and represented one of the main concerns of monetary authorities. However, neither the financial stability definition, nor its assessment, is commonly agreed between academics and policy makers. In this context our purpose is to identify the key elements underlining the financial stability concept, using both a clustering and a networking approach. More precisely we conduct an investigation over a sample of 145 papers including in their title the concept “financial stability”, starting from financial stability related keywords advanced in the literature. We establish a network and performed a hierarchical and k-means clustering analysis which helps us to identify the clusters of keywords related to the financial stability concept. In addition, we apply a Pathfinder algorithm which helps us to identify the most important links and nodes from the network. Our results show that the interest for the “financial stability” increased exponentially after the recent financial crisis. Further, the keywords related to financial stability are grouped in four clusters which might be associated with systemic risk, banks, monetary policy and economic context. However, the clustering analysis does not lead to clear results even if the hierarchical and k-means clustering present similar findings. Finally, our network analysis identifies the banks on the one hand, and the central banks and their monetary policies on the other hand, as the most important elements for the financial stability.