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作者：Horowitz, JL
作者单位：Northwestern University
摘要：The block bootstrap is the best known bootstrap method for time-series data when the analyst does not have a parametric model that reduces the data generation process to simple random sampling. However, the errors made by the block bootstrap converge to zero only slightly faster than those made by first-order asymptotic approximations. This paper describes a bootstrap procedure for data that are generated by a Markov process or a process that can be approximated by a Markov process with suffic...
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作者：Ruszczynski, A; Vanderbei, RJ
作者单位：Rutgers University System; Rutgers University New Brunswick; Princeton University
摘要：We consider the problem of constructing a portfolio of finitely many assets whose returns are described by a discrete joint distribution. We propose mean-risk models that are solvable by linear programming and generate portfolios whose returns are nondominated in the sense of second-order stochastic dominance. Next, we develop a specialized parametric method for recovering the entire mean-risk efficient frontiers of these models and we illustrate its operation on a large data set involving tho...
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作者：Prat, A; Rustichini, A
作者单位：University of London; London School Economics & Political Science; University of London; London School Economics & Political Science; University of Minnesota System; University of Minnesota Twin Cities
摘要：We introduce a game of complete information with multiple principals and multiple common agents. Each agent makes a decision that can affect the payoffs of all principals. Each principal offers monetary transfers to each agent conditional on the action taken by the agent. We characterize pure-strategy equilibria and we provide conditions-in terms of game balancedness-for the existence of an equilibrium with an efficient outcome. Games played through agents display a type of strategic inefficie...
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作者：Geweke, J; Gowrisankaran, G; Town, RJ
作者单位：University of Iowa; University of Iowa; Harvard University; National Bureau of Economic Research; University of Minnesota System; University of Minnesota Twin Cities
摘要：This paper develops new econometric methods to infer hospital quality in a model with discrete dependent variables and nonrandom selection. Mortality rates in patient discharge records are widely used to infer hospital quality. However, hospital admission is not random and some hospitals may attract patients with greater unobserved severity of illness than others. In this situation the assumption of random admission leads to spurious inference about hospital quality. This study controls for ho...
