Abstract

Managing disequilibrium and its consequent traverse is one of the important topics in economic theory. During such traverse, the evolving economic system faces various imbalances and coordination problems that arise within and outside the sys-tem. In order to traverse the disequilibrium, the economic system should innovate, create, and manage its resources in a viable manner. This dissertation reports stud-ies in modelling ‘disequilibrium traverse economies’, in the sense of Hicksian Neo-Austrian, Time-to-Build, theory. In the first chapter, we discuss the origins of traverse analysis and the role of ‘time-to-build’ framework in modelling macro-dynamics. We also provide a review of the literature concerning ‘time-to-build’ tradition in modelling traverse and business cycles. Then, we discuss in detail how this framework actually enters into these models and the assumptions that underpin them. In the second chapter, we provide an overview of different notions of viability, which are widely used in economic literature, and formulate viability conditions for Amendola and Gaffard’s Neo-Austrian model. We then simulate the model, with and without the viability conditions, to study the dynamics of the evolving system. The main aim of this chapter is to explore and analyse the importance of viability creating mechanisms during dynamic traverse. In chapter three, we analyse some of the classics in business cycle theory and how the ‘time-to-build’ framework plays an important role in modelling economic fluctuations. The contribution of this chapter is to provide insights on various as-sumptions and the choice of mathematical formalisms that underpin these business cycle models. In conclusion, we also suggest that the Neo-Austrian tradition should be placed as a part of the rich tradition of business cycle theory. In the fourth chapter, we take the ‘time-to-build’ model and improve the framework by endogenizing one of the main engines of growth, i.e., innovations, in a non-stochastic, non ad-hoc, manner. We model innovations using Turing Machine metaphor, so that we can encapsulate the intrinsic uncertainties of Research and Development processes in an insightful way. The enhanced ‘time-to-build’ model thus developed is then simulated for various policy parameters, such as - R&D policies, interest rates, and bankruptcy policies, and the resulting traverses are studied. In the last chapter, we provide a comprehen-sive summary of the novel contributions of the dissertation and list some of the future research paths that can be traversed.