Abstract
Problems of optimization, both static and dynamic have occupied a central role in economic theory. The optimization behavior of economic agents, be they households or firms have provided the economists with a set of normative decision rules that can be tested against the observed behavior at the market place, which may be competitive, regulated or otherwise. The theory of economic policy, as applied to macromodels has postulated implicit normative behavior by assuming as decision maker such agents as the government, the central bank or the national planning authority. The process of optimization is thus basic to economic modeling at three levels: the specification, estimation and control. The specification, viewed as a set of equations in economic variables may or may not include a normative hypothesis. Thus, a production relationy ⩽ f(x 1,x 2) between one outputy and two inputsx 1,x 2 includes the case of a production frontier when an optimizing assumption is introduced. The estimation problem, conditional as it is on the specification, starts as soon as one makes a distinction between the parameters and the variables. The above production relation, for instance appears asy ⩽ f(x 1,x 2;θ) whereθ denotes a set of unknown parameters. If the parametersθ are unknown but observations on variables (y,x 1,x 2) are available, then in suitable casesθ may be estimated by following a suitable method of estimation e.g. least squares (LS) or, maximum likelihood (ML).
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Sengupta, J.K. (1985). Stochastic optimization: examples and applications. In: Information and Efficiency in Economic Decision. Advanced Studies in Theoretical and Applied Econometrics, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-5053-5_1
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DOI: https://doi.org/10.1007/978-94-009-5053-5_1
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