A conceptual design of "what and how should a proper macro-prudential policy framework be?" A globalistic approach to systemic risk and procuring the data needed

During the last half-decade, the 2007 global crisis has kept all interested parties busy and urged them to focus on the causes of this crisis, to find solutions for recovery, and to contrive to be capable of projecting potential ones that may happen in the future. As one of the precautionary tool-sets devised for the authorities among others the classical macro-prudential and systemic risk models focused on banks and sought for the systemically important ones (SIFIs). It had been argued by a handful of interest groups that this sort of approach to risk embedded in a network structure was both unbalanced condoning potential plausible sources of risk to monitor passively as well as take policy actions pro-actively and further was undue in remedying possible causes if, when and where seen indispensable. Therefore, a more macro stance towards the conventional macro-prudential paradigms considering micro elements of the system was seen as vital. This work attempts to draw an extended framework that would span all potential incumbents forming part of the Circular Flow of Income (CFI), which is treated as a network or a bijective counter-party mapping of incumbent groups of different sources that each have claims against the funds granted to other groups or to members of the same group. Availability of data would be a focal point for the operability of a model as such. Though the significance of data availability being a central question is inarguable and the necessary data is really scarce, that doesn’t abstain one from devising usable designs, nor does it from standing in a proper position in such design efforts for public welfare. In reality, the data is available for a different variety of incumbent groups at different levels of congruity, but unfortunately sparsely distributed among different collectors and users . Still, there is data that can be used for empirical analysis purposes but needs a considerable extent of effort to collect and make use of. We propose a si(This abstract was borrowed from another version of this item.)