The robustness of optimal equilibrium among overlapping generations

Summary. We combine and strengthen optimality and robustness theorems for the overlapping-generations model of money. Roughly, we find a Pareto-optimal monetary equilibrium of a generic stationary economy that is near an optimal monetary equilibrium of each nearby non-stationary economy. Since the nearby equilibria are monetary, the general problem of macroeconomic stabilization reduces to maintaining the money supply. And since the nearby equilibria are optimal, stabilization is socially desirable. Received: October 27, 1997; revised version: March 25, 1998     

Regularity and robustness in monotone Bayesian games

This paper defines regular and weakly regular equilibria for monotone Bayesian games with one-dimensional actions and types. It analyzes the robustness of equilibria with respect to perturbations. It also proves an index theorem and provides applications to uniqueness of equilibrium.     

基于预测能力的扩展极限边界分析法

本文在传统EBA方法的基础上,将其引入到时间序列中,构建以预测为导向的AEBA模型选择方法。AEBA在模型选择上更注重于模型的预测能力,在稳健性检验上细分为模型稳健性检验与参数稳健性检验两部分,提出了基于时间序列预测能力的检验方法。最后实证示例用AEBA方法对影响石油股票指数收益率的因素进行了研究,表明该方法选择的模型的预测能力,特别是短期预测能力要显著强于CAPM、三因子模型、ARMA以及VAR。     

Reducing airplane boarding time by accounting for passengers' individual properties: A simulation based on cellular automaton

The increase of air travel puts tremendous burden on airline companies. A time saving boarding strategy is required to improve the utilization of airplane boarding time and explore flexible time management strategies. Firstly, an improved boarding strategy is introduced by assigning individual passengers to seats based on the number of luggage they carry. Passengers with the most luggage board onto the plane first. To test the behavior of boarding strategies under different conditions, a sophisticated simulation environment based on cellular automata model is designed. Simulation results indicate that the improved boarding strategy shows an excellent efficiency and robustness comparing with other strategies.     

地方政府帮助地方银行改善经营绩效了吗?--基于“地方保护”和“行政干预”的视角

本文检验了地方政府行为对地方银行经营绩效的影响,发现:(1)\"地方保护\"具有\"保护之手\"作用,\"行政干预\"具有\"良性引导\"作用,二者有利于降低地方银行的盈利波动性、提升地方银行的运营稳健性。(2)对于资产规模较小的银行、未设立省外分行的银行,\"地方保护\"和\"行政干预\"的积极影响较大;对于高技术产业投资比较活跃的地区,\"地方保护\"和\"行政干预\"的积极影响较大。(3)当省内经济增长率领先于全国水平时,\"地方保护\"和\"行政干预\"依然发挥积极作用;然而,当省内经济增长率落后于全国水平时,\"地方保护\"会产生\"约束之手\"作用,\"行政干预\"会产生\"恶性引导\"作用,二者反而会加剧地方银行的盈利波动性、降低地方银行的运营稳健性。     

CHOOSING AMONG ALTERNATIVE LONG‐RUN EVENT‐STUDY TECHNIQUES

This paper reviews the long‐run event‐study debate by outlining the strengths and weakness of the most commonly used alternative techniques. The fist part of the discussion highlights that prior literature has failed to provide a single risk‐adjusted model of long‐run abnormal returns with no biases. Subsequently, the paper provides guidance on how one can choose among pertinent alternative techniques. As a conclusion, researchers ought to choose among alternative techniques after considering issues such as (i) the nature of dataset and market of interest, (ii) the event type (regulatory or corporate), (iii) returns’ time‐interval, (iv) association of the event with accounting data, (v) sample characteristics and prior evidence regarding similar events, as well as (vi) risk changes following the event. Robustness tests are essential, while the road for further research regarding the appropriate technique(s) is open.     

Small sample corrections for LTS and MCD

The least trimmed squares estimator and the minimum covariance determinant estimator [6] are frequently used robust estimators of regression and of location and scatter. Consistency factors can be computed for both methods to make the estimators consistent at the normal model. However, for small data sets these factors do not make the estimator unbiased. Based on simulation studies we therefore construct formulas which allow us to compute small sample correction factors for all sample sizes and dimensions without having to carry out any new simulations. We give some examples to illustrate the effect of the correction factor.