A new perspective on the exporter productivity premium: online trade

We use a unique firm-level data set including 9000 companies from 26 European Union countries covering four different sectors to take a close look at the relationship between online exports and productivity. The online exporter productivity premium is estimated using different techniques (ordinary least squares, quantile regressions and robust estimation). Results consistently indicate that the estimated online exporter productivity premium is statistically different from zero, positive and significant from an economic point of view. European online exporters, according to these results, are approximately 2% more productive than non-online exporters. Productivity differences between firms could be related to variables that are not included in the empirical model. More research would be needed to address this issue in the future.     

改进高阶容积粒子滤波的系统状态估计算法

传统粒子滤波（PF）直接采用状态转移先验分布作为重要性密度函数来近似后验概率密度函数，使得后验概率密度函数未包含量测信息。针对此问题，提出了一种改进高阶容积粒子滤波(CPF)的系统状态估计算法。算法采用七阶正交容积卡尔曼滤波（7th-CQKF）对PF的粒子进行传递，使得先验分布更新阶段融入最新量测信息；通过7th-CQKF设计重要性密度函数，提高对状态后验概率密度的逼近程度；通过反比例函数计算粒子权重，突出大噪声粒子与小噪声粒子权重差别，提高粒子有效性。仿真结果表明，改进高阶容积粒子滤波的估计精度高于容积粒子滤波（CPF）。     

Corrigendum to “Characterization of the asymptotic distribution of semiparametric M-estimators” [J. Econometrics 159 (2) (2010) 252–266]

This note provides correction to Ichimura and Lee (2010).     

组织支持感与员工创造力——相对组织支持感和情感承诺的影响

从自我提升视角出发，基于社会比较理论与社会交换理论，分析组织支持感影响员工创造力的过程机制，相对组织支持感的调节作用以及情感承诺与创造力之间的曲线关系。基于458份企业员工与主管的配对样本，研究结果表明：相对组织支持感显著正向调节了组织支持感与情感承诺之间的关系，情感承诺与员工创造力呈显著的倒U型关系，情感承诺在组织支持感与创造力关系之间起到了瞬时中介作用。研究结果拓展了对组织支持感的影响机制及其边界条件的分析，深化了情感承诺与员工创造力关系的检验。     

Krazy Kimmy's: A Case in Fraud Examination

This two‐part case allows for maximum student engagement through preparation, in‐class discussion, and through a Part B case that is part of the Teaching Note. Through this case, students work to identify possible fraud schemes, plan an investigation, and perform horizontal analysis calculations. Students will learn about the concept of ethical hacking, red flag identification, internal control weaknesses, and investigation considerations for fraud schemes. Further, in‐class planning for next steps and investigation can occur, providing an opportunity for group work and in‐depth learning. This case offers flexibility for instructors in that it can be covered over one class or multiple classes, or can be assigned as an independent or group assignment. This teaching note provides an overview of the case along with guidance for teaching this case.     

The Local Whittle Estimator of Long-Memory Stochastic Volatility

We propose a new semiparametric estimator of the degree of persistencein volatility for long memory stochastic volatility (LMSV) models.The estimator uses the periodogram of the log squared returnsin a local Whittle criterion which explicitly accounts for thenoise term in the LMSV model. Finite-sample and asymptotic standarderrors for the estimator are provided. An extensive simulationstudy reveals that the local Whittle estimator is much lessbiased and that the finite-sample standard errors yield moreaccurate confidence intervals than the widely-used GPH estimator.The estimator is also found to be robust against possible leverageeffects. In an empirical analysis of the daily Deutsche Mark/USDollar exchange rate, the new estimator indicates stronger persistencein volatility than the GPH estimator, provided that a largenumber of frequencies is used.     

Time Inhomogeneous Multiple Volatility Modeling

Price variations at speculative markets exhibit positive autocorrelationand cross correlation. Due to large parameter spaces necessaryfor joint modeling of variances and covariances, multivariateparametric volatility models become easily intractable in practice.We propose an adaptive procedure that identifies periods ofsecond-order homogeneity for each moment in time. To overcomethe high dimensionality of the problem we transform the multivariateseries into a set of univariate processes. We discuss thoroughlythe implementation of the adaptive technique. Theoretical andMonte Carlo results are given. We provide two applications ofthe new method. For a bivariate exchange rate series we comparethe multivariate GARCH approach with our method and find thelatter to be more in line with the underlying assumption ofindependently distributed innovations. Analyzing a 23-dimensionalvector of asset returns we underscore the case for adaptivemodeling in high-dimensional systems.     

Beyond Single-Factor Affine Term Structure Models

This article proposes a new approach to testing for the hypothesisof a single priced risk factor driving the term structure ofinterest rates. The method does not rely on any parametric specificationof the state variable dynamics or the market price of risk.It simply exploits the constraint imposed by the no-arbitragecondition on instantaneous expected bond returns. In order toachieve our goal, we develop a Kolmogorov-Smirnov test and applyit to data on Treasury bills and bonds for both the United Statesand Spain. We find that the single risk factor hypothesis cannotbe rejected for either dataset.     

Relative risk aversion, relative prudence and comparative statics under uncertainty: The case of (μ, σ)‐preferences

From the expected‐utility approach, relative risk aversion being smaller than one and relative prudence being smaller than two emerge as preference restrictions that fully determine the optimal responses of decisions under uncertainty to certain shifts in probability distributions. We characterize the magnitudes of relative risk aversion and relative prudence in terms of the two‐parameter, mean‐standard deviation approach. We demonstrate that this characterization is instrumental in obtaining comparative static results in the two‐parameter setting. We further relate our findings to the results in the expected‐utility framework.