A remark on topological robustness to bounded rationality in semialgebraic models

In this short note, we show that the compact semialgebraic class of Anderlini and Canning (2001) is topologically robust, i.e. the topological properties of the equilibrium set are preserved, deviating parameter values and introducing a small amount of bounded rationality.     

Tourism firm restructuring: Does the attention of individual investor matter?

We examine the power of individual investor attention in increasing tourism firms' restructured performance, the different effects caused by ‘attention heterogeneity’, the moderating effect of media coverage on the relationship between individual investor attention and tourism firms' restructured performance, and the robustness of the effects. The results indicate that 1) individual investor attention has a significant positive effect on tourism firms' restructured performance, 2) individual investor attention via mobile devices influences tourism firms' restructured performance more than attention via computers, 3) the moderating effect of media coverage on this relationship varies with time and media heterogeneity, and 4) the effect of individual investor attention is immediate, while time is needed for the moderating effect of media coverage to appear. The main effect of individual investor attention and the moderating effect of media coverage on tourism firm performance do not depend on the firm size or the proportion of individual shareholders.     

Coarsened Propensity Scores and Hybrid Estimators for Missing Data and Causal Inference

In the areas of missing data and causal inference, there is great interest in doubly robust (DR) estimators that involve both an outcome regression (RG) model and a propensity score (PS) model. These DR estimators are consistent and asymptotically normal if either model is correctly specified. Despite their theoretical appeal, the practical utility of DR estimators has been disputed (e.g. Kang and Schaffer, Statistical Science 2007; 22: 523–539). One of the major concerns is the possibility of erratic estimates resulting from near‐zero denominators due to extreme values of the estimated PS. In contrast, the usual RG estimator based on the RG model alone is efficient when the RG model is correct and generally more stable than the DR estimators, although it can be biased when the RG model is incorrect. In light of the unique advantages of the RG and DR estimators, we propose a class of hybrid estimators that attempt to strike a reasonable balance between the RG and DR estimators. These hybrid estimators are motivated by heuristic arguments that coarsened PS estimates are less likely to take extreme values and less sensitive to misspecification of the PS model than the original model‐based PS estimates. The proposed estimators are compared with existing estimators in simulation studies and illustrated with real data from a large observational study on obstetric labour progression and birth outcomes.     

Robust and stable multi-task manufacturing scheduling with uncertainties using a two-stage extended genetic algorithm

ABSTRACT

In cloud manufacturing (CMfg), unexpected uncertainties can occur in real-world manufacturing processes that could make the predetermined schedule infeasible. A new multi-objective proactive method is proposed in this situation to evaluate the proactive schedule. A novel two-stage extended genetic algorithm (2S-EGA) is proposed to generate proactive schedules that consider service interruptions. The experimental results confirmed that the obtained proactive schedule produces great performance when applied to multi-task scheduling problems with service interruptions. Furthermore, the results also showed that the proactive schedule obtained by the proposed approach is more robust and stable than other baseline algorithms taken from the literature.     

终极控制权、审计师行业专长与盈余稳健性

文章探讨了上市公司终极控制权和审计师行业专长对会计盈余信息稳健性的影响。研究结果表明,终极控制权与现金流权的分离程度越大,公司的盈余信息越不稳健;相对于非行业专长审计师审计的公司,专长审计师审计的公司对损失的确认更及时;更重要的是发现具有行业专长的审计师能够显著抑制由于终极控制权分离所造成的会计盈余信息不稳健的行为。国内外学者研究表明,稳健的会计盈余信息能够导致正面的经济后果,文章的研究结论暗示雇佣一个行业专长的会计师事务所对存在终极控制权分离的公司是有利的。     

Which Method Should the Central Bank Choose to Estimate the Model Economy? A Korean Monetary Policy Example

Abstract

To understand how the macro economy evolves, the central bank has two options in choosing how to estimate the economic model against actual data: one is to estimate each sector of the model piece-by-piece, and the other is to estimate the whole model altogether. This paper demonstrates the advantage for the central bank of estimating the whole model in terms of the estimation accuracy and the robustness of the resulting policy recommendations. For that aim, we construct a macro model for the monetary policy analysis of the Korean economy and estimate the model via the system approach and single-equation approach. We evaluate the data fits of the two estimation results and show that the fit of the system approach is far better than the other and comparable to other methods such as vector autoregressions. It is also shown that, if the two estimated models are equally likely, conducting the policy tailored for the model estimated by the system approach delivers better stabilization results for the Korean economy.     

The identification of outliers in exponential samples

In this paper, the task of identifying outliers in exponential samples is treated conceptionally in the sense of DAVIES and GATHER (1989, 1993) by means of a so-called outlier region. In case of an exponential distribution, an empirical version of such a region – also called an outlier identifier – is mainly dependent on some estimator of the unknown scale parameter. The worst-case behaviour of several reasonable outlier identifiers is investigated thoroughly and it is shown that only robust estimators of scale should be used to construct reliable identifiers. These findings lead to the recommendation of an outlier identifier that is based on a standardized version of the sample median.     

HEDGING WITH ENERGY

In the setting of diffusion models for price evolution, we suggest an easily implementable approximate evaluation formula for measuring the errors in option pricing and hedging due to volatility misspecification. The main tool we use in this paper is a (suitably modified) classical inequality for the L ² norm of the solution, and the derivatives of the solution, of a partial differential equation (the so-called "energy" inequality). This result allows us to give bounds on the errors implied by the use of approximate models for option valuation and hedging and can be used to justify formally some "folk" belief about the robustness of the Black and Scholes model. Surprisingly enough, the result can also be applied to improve pricing and hedging with an approximate model. When statistical or a priori information is available on the "true" volatility, the error measure given by the energy inequality can be minimized w.r.t. the parameters of the approximating model. The method suggested in this paper can help in conjugating statistical estimation of the volatility function derived from flexible but computationally cumbersome statistical models, with the use of analytically tractable approximate models calibrated using error estimates.     

On Tests for a Normal Mean with Known Coefficient of Variation

Hinkley (1977) derived two tests for testing the mean of a normal distribution with known coefficient of variation (c.v.) for right alternatives. They are the locally most powerful (LMP) and the conditional tests based on the ancillary statistic for μ. In this paper, the likelihood ratio (LR) and Wald tests are derived for the one‐ and two‐sided alternatives, as well as the two‐sided version of the LMP test. The performances of these tests are compared with those of the classical t, sign and Wilcoxon signed rank tests. The latter three tests do not use the information on c.v. Normal approximation is used to approximate the null distribution of the test statistics except for the t test. Simulation results indicate that all the tests maintain the type‐I error rates, that is, the attained level is close to the nominal level of significance of the tests. The power functions of the tests are estimated through simulation. The power comparison indicates that for one‐sided alternatives the LMP test is the best test whereas for the two‐sided alternatives the LR or the Wald test is the best test. The t, sign and Wilcoxon signed rank tests have lower power than the LMP, LR and Wald tests at various alternative values of μ. The power difference is quite large in several simulation configurations. Further, it is observed that the t, sign and Wilcoxon signed rank tests have considerably lower power even for the alternatives which are far away from the null hypothesis when the c.v. is large. To study the sensitivity of the tests for the violation of the normality assumption, the type I error rates are estimated on the observations of lognormal, gamma and uniform distributions. The newly derived tests maintain the type I error rates for moderate values of c.v.     

Robust cyclical growth

The stability of cyclical growth within the context of a model in "Growing through cycles" in Econometrica by Matsuyama (1999) is examined. It is shown that but for an extreme situation, the two-period cycles (two-cycles) are unique and a range of parameter values that imply the stability of such cyclical growth is derived. The growth enhancing property of two-cycles are shown to be retained by any cycle; the results of simulation exercises carried out are reported to show that for a very wide range of parameter values, such cyclical growth paths are stable and, therefore, robustness of the conclusions is established.