In this paper, we provide a model of monetary economy with differences in liquidity across assets. Our purpose is to understand how aggregate production and asset prices fluctuate with recurrent shocks to productivity and liquidity. In so doing, we want to find out what role government policy might have through open market operations that change the mix of assets held by the private sector. The present paper takes fiat money to be one of the assets under consideration. We investigate under what circumstances money is essential to a better allocation of resources. We show that certain apparent anomalies of the non monetary economy are in fact normal features of an economy where money is essential. Among the well known puzzles we have in mind are: the low risk free rate puzzle; the excess volatility of asset prices; the anomalous savings behaviour of certain households, and their low participation in asset markets. Before describing our monetary economy, we should start with some remarks about modeling strategy.
In broad terms, there are two ways of getting fiat money into a competitive macroeconomic model. One approach is to endow money with some special function for example, cash in advance or sticky nominal prices. The other approach is to starve agents of alternatives to money pas in an overlapping generations framework where money is the sole means of saving. Although the first approach, in particular the cash in advance model and the dynamic sticky price model, has proved important to monetary economics and policy analysis, it is not well suited to answering larger questions to do with liquidity. By endowing money with a special function in the otherwise frictionless economy with complete Arrow Debreu security market, one is imposing rather than explaining the use of money, which precludes the possibility that other assets or media of denomination may substitute for money. And the second approach rules out any general discussion of liquidity if there are no alternative assets to money.
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There are two key areas under constant pressure as the information revolution accelerates that must be addressed; knowledge and knowledge management, or in other words, collection and production. In relation to security matters, the question is how to find the best information to produce relevant and useful intelligence, and then what is the best method to understand that information and develop the appropriate responses. This task has traditionally been the domain of the varying intelligence agencies, who have cultivated an air of mystery and secrecy that is ill fitted to meet the demands of modern counter-terrorism, or even the level of information sharing that is required in the network-centric warfare championed by many in the Pentagon. As the information revolution continues and more individuals have more access to more and more information, it becomes clear that attempting to restrict and control information flows becomes an exercise in futility. It also is apparent that while society at large, and particularly the business community, have begun to embrace the potential offered by information technology advances, the intelligence community lags behind. This research paper will introduce two constructs for dealing with information flows that take full advantage of technological gains, while challenging traditional methods and assumptions about knowledge and knowledge management. For collection, open source intelligence; for production, open source development.
Intelligence is defined as the product resulting from the collection, processing, integration, analysis, evaluation, and interpretation of available information concerning foreign countries or areas, also information and knowledge about an adversary obtained through observation, investigation, analysis, or understanding. The crucial component of this definition is that intelligence is a product that must be created, it is not simply enough to know something; if it is not packaged, analyzed, and filtered, than it has no value to policy makers. The role of the intelligence product itself is to give decision makers relevant information about the outside world so that informed choices can be made, or put succinctly, "intelligence defines reality for those whose actions could alter it".1 Increasingly, the focus of intelligence agencies has been to move away from strategic intelligence towards an emphasis on tactical information, or in the words of the Tim Weiner in the New York Times; "The big picture has been bumped by spot news. Strategic intelligence in the power to know your enemies intentions, spot news is what happened last night in Waziristan"
