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, it is shown that this correspondence is continuous. Numerous problems in economics involve optimization over a space of …
Persistent link: https://www.econbiz.de/10014200393
of stochastic optimization problems. The results are formulated so as to highlight the tradeoffs between assumptions …
Persistent link: https://www.econbiz.de/10014046785
Decision-making and competitive strategies in major American sports have often relied on heuristics and conventional wisdom. Recently, statistics and quantitative methods have been used in the sport of baseball to help teams improve their chances of winning. However, the use of mathematical...
Persistent link: https://www.econbiz.de/10014047572
We consider a Bayesian decision problem in which an agent must draw inferences about multiple unobserved variables. This problem appears in different economic settings, for instance in the theory of agency. Assume that both observed and unobserved variables are ordered. We say that the inference...
Persistent link: https://www.econbiz.de/10013098799
Using the standard linear model as a base, a unified theory of Bayesian Analysis of Cointegration Models is constructed. This is achieved by defining (natural conjugate priors in the linear model and using the implied priors for the cointegration model
Persistent link: https://www.econbiz.de/10014069432
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This paper studies simulation-based optimization with multiple outputs. It assumes that the simulation model has one … for testing whether a specific input combination (proposed by some optimization heuristic) satisfies the Karush …
Persistent link: https://www.econbiz.de/10014049484
Monotone methods enable comparative static analysis without the restrictive assumptions of the implicit function theorem. Ease of use and flexibility in solving comparative static and game theory problems have made monotone methods popular in the economics literature and in graduate courses, but...
Persistent link: https://www.econbiz.de/10014217258
In this paper, we consider an optimal stopping problem that addresses model uncertainty. Model uncertainty is the uncertainty affecting the model assumptions, e.g., the assumed form of the probability distribution, the parameters embedded in the probability distribution. The result presented in...
Persistent link: https://www.econbiz.de/10014084327