Foley's Thesis, Negishi's Method, Existence Proofs and Computation

Duncan Foleyís many-faceted and outstanding contributions to macroeconomics, microeconomics, general equilibrium theory, the theory of taxation, history of economic thought, the magnificent dynamics of classical economics, classical value theory, Bayesian statistics, formal dynamics and, most recently, fascinating forays into an interpretation of economic evolution from a variety of complexity theoretic viewpoints have all left -and continue to leave - significant marks in the development and structure of economic theory. He belongs to the grand tradition of visionaries who theorise with imaginative audacity on the dynamics, evolution and contradictions of capitalist economies - a tradition that, perhaps, begins with Marx and Mill, continues with Keynes and Schumpeter, reaching new heights with the iconoclastic brilliancies of a Tsuru and a Goodwin, a Chakravarty and a Nelson, and to which Duncan Foley adds a lustre of much value. In this contribution I return to mathematical themes broached in Foleyís brilliant and pioneering Yale doctoral dissertation (Foley, 1967) and attempt to view them as a Computable Economist would.The intention is to suggest that algorithmic indeterminacies are intrinsic to the foundations of economic theory in the mathematical modeEquilibrium existence theorems, Welfare theorems, Constructive proofs, Computability

Negishi's Theorem and Method

Takashi Negishi's remarkable youthful contribution to welfare economics, general equilibrium theory and, with the benefit of hindsight, also to one strand of computable general equilibrium theory, all within the span of six pages in one article, has become one of the modern classics of general equilibrium theory and mathematical economics. Negishi's celebrated theorem and what has been called Negishi's Method have formed one foundation for computable general equilibrium theory. In this paper I investigate the computable and constructive aspects of the theorem and the methodComputable General Equilibrium, Fundamental Theorems of Welfare Economics, Negishi's Method

The Fundamental Theorems of Welfare Economics, DSGE and the Theory of Policy - Computable & Constructive Foundations

The genesis and the path towards what has come to be called the DSGE model is traced, from its origins in the Arrow-Debreu General Equilibrium model (ADGE), via Scarf's Computable General Equilibrium model (CGE) and its applied version as Applied Computable General Equilibrium model (ACGE), to its ostensible dynamization as a Recursive Competitive Equilibrium (RCE). It is shown that these transformations of the ADGE - including the fountainhead - are computably and constructively untenable. The policy implications of these (negative) results, via the Fundamental Theorems of Welfare Economics in particular, and against the backdrop of the mathematical theory of economic policy in general, are also discussed (again from computable and constructive points of view). Suggestions for going 'beyond DSGE' are, then, outlined on the basis of a framework that is underpinned - from the outset - by computability and constructivity considerationsComputable General Equilibrium, Dynamic Stochastic General Equilibrium, Computability, Constructivity, Fundamental Theorems of Welfare Economics, Theory of Policy, Coupled Nonlinear Dynamic

Simon's Bounded Rationality. Origins and use in economic theory

The paper aims to show how Simon's notion of bounded rationality should be interpreted in the light of its connection with artificial intelligence. This connection points out that bounded rationality is a highly structured concept, and sheds light on several implications of Simon's general views on rationality. Finally, offering three paradigmatic examples, the artic1e presents the view that recent approaches, which refer to Simon's heterodox theory, only partially accept the teachings of their inspirer, splitting bounded rationality from the context of artificl al intelligence.

Computability and analysis: the legacy of Alan Turing

We discuss the legacy of Alan Turing and his impact on computability and analysis.Comment: 49 page