Innovation and productivity: insights from Malaysia's logistics industry

Efficient logistics is critical to a country's trade competitiveness. This paper uses the Data Envelopment Analysis Malmquist Index that includes an innovation component comprising three dimensions (input, process, and output), to assess the impact of innovation by third-party logistics (3PL). We treat the panel data of asset-based 3PL in Malaysia from 2007 to 2012. Three findings hold. First, innovation is not always accompanied by productivity gains. Second, innovation is still lacking in the logistics industry in Malaysia. Third, 3PL need to invest more in technology and stay financially healthy to accelerate the diffusion of innovation under a more competitive cost structure. This paper has two contributions. First, we offer an enhanced methodology for total factor productivity by including an innovation component and apply it for the first time to the logistics industry. Second, we augment the performance measurement literature specific to the logistics industry and our research suggests that the antecedents of productivity in logistics companies are investment and financial strength. These productivity–innovation findings provide insights into Malaysia's logistics industry and may be helpful for economies similar to Malaysia.     

Bootstrap J-Test for Panel Data Models with Spatially Dependent Error Components,a Spatial Lag and Additional Endogenous Variables

We develop a bootstrap J-test method for testing a panel model against one non-nested alternative when the competing specifications are estimated by Feasible Generalised Spatial Two Stage Least Squares/Generalised Method of Moments (FGS2SLS/GMM). Both models incorporate spatially correlated error components, thus accounting for spatial heterogeneity via random effects, and accommodate endogenous regressors other than the spatially lagged dependent variable. The proposed scheme is applied to a testing problem involving non-nested wage equations as motivated by the Wage Curve literature and the New Economic Geography theory. Results show that our bootstrap test is a reliable and effective procedure for correcting asymptotic reference critical values and distinguishing between the two rival hypotheses.     

我国经济增长与大气污染物排放的关系——基于分省面板数据的经验研究

本文应用1998-2004年期间我国30个省(市、自治区)的面板数据,通过综合简化型模型,研究了3种大气污染物和经济增长之间的关系.实证研究发现在3种大气污染物与经济增长之间不存在倒U型环境库兹涅茨曲线.二氧化硫排放与经济增长之间呈倒N型曲线,与多数研究结果不相符;同时,第二产业比重、经济增长速度、单位GDP能耗和环境政策强度四个解释变量总体上对3个大气污染物的排放具有显著影响,并包含明确的政策含义.     

Software for Learning and for Doing Statistics

The community of statisticians and statistics educators should take responsibility for the evaluation and improvement of software quality from the perspective of education. The paper will develop a perspective, an ideal system of requirements to critically evaluate existing software and to produce future software more adequate both for learning and doing statistics in introductory courses. Different kinds of tools and microworlds are needed. After discussing general requirements for such programs, a prototypical ideal software system will be presented in detail. It will be illustrated how such a system could be used to construct learning environments and to support elementary data analysis with exploratory working style.     

采用消息方式处理串口与主程序间的通讯

主要针对采用消息方式处理串口与主程序间的数据通讯进行介绍 ,另外 ,对在串口通讯中 ,端口在巡回监控处理方式与消息处理方式进行了简要对比说明 ,并且对串口数据接收是非确定性问题做一说明     

Prediction of the next hypercalcemia free period: application of random effect models with selection on first event

The length of repeated hypercalcemia free periods of patients with bone metastasis of breast cancer with at least one hypercalcemic event was modelled according to a generalized linear mixed model formulated in terms of transition probabilities and according to a latent variable model. In the former case the periods were assumed to be lognormally distributed with two variance components (patients and residue). In the latter case the conditional intensity given a patient was assumed to be the intensity of the Weibull distribution, while the random patient effect (frailty) was assumed to be drawn from a gamma distribution. In both cases the selection of only patients with at least one hypercalcemic event was taken into consideration. In both models the variance of the patient effect turned out to be negligible. For the second and later periods the Weibull appeared to fit better than the lognormal model. For the first period there was almost no information available.     

Trades and Quotes: A Bivariate Point Process

This article formulates a bivariate point process to jointlyanalyze trade and quote arrivals. In microstructure models,trades may reveal private information that is then incorporatedinto new price quotes. This article examines the speed of thisinformation flow and the circumstances that govern it. A jointlikelihood function for trade and quote arrivals is specifiedin a way that recognizes that an intervening trade sometimescensors the time between a trade and the subsequent quote. Modelsof trades and quotes are estimated for eight stocks using Tradeand Quote database (TAQ) data. The essential finding for thearrival of price quotes is that information flow variables,such as high trade arrival rates, large volume per trade, andwide bid–ask spreads, all predict more rapid price revisions.This means prices respond more quickly to trades when informationis flowing so that the price impacts of trades and ultimatelythe volatility of prices are high in such circumstances.     

A Partially Observed Model for Micromovement of Asset Prices with Bayes Estimation via Filtering

A general micromovement model that describes transactional price behavior is proposed. The model ties the sample characteristics of micromovement and macromovement in a consistent manner. An important feature of the model is that it can be transformed to a filtering problem with counting process observations. Consequently, the complete information of price and trading time is captured and then utilized in Bayes estimation via filtering for the parameters. The filtering equations are derived. A theorem on the convergence of conditional expectation of the model is proved. A consistent recursive algorithm is constructed via the Markov chain approximation method to compute the approximate posterior and then the Bayes estimates. A simplified model and its recursive algorithm are presented in detail. Simulations show that the computed Bayes estimates converge to their true values. The algorithm is applied to one month of intraday transaction prices for Microsoft and the Bayes estimates are obtained.     

Multiple Imputation in Multivariate Problems When the Imputation and Analysis Models Differ

Bayesian multiple imputation (MI) has become a highly useful paradigm for handling missing values in many settings. In this paper, I compare Bayesian MI with other methods – maximum likelihood, in particular—and point out some of its unique features. One key aspect of MI, the separation of the imputation phase from the analysis phase, can be advantageous in settings where the models underlying the two phases do not agree.