基于生态-技术创新和熵理论的企业绿色创新风险度量研究

历史的考察表明,企业进程的实然状态是非生态化的,而生态觉醒之后的企业发展的应然趋势是生态化,导致二者背离的恰恰是作为推动企业发展的＂技术创新→利润＂中轴。随着绿色消费在全球的兴起,绿色企业将成为未来的新型主导企业。文章基于可持续发展的视角,将生态理论和熵理论引入技术创新风险管理领域,建立了基于生态-技术创新和熵理论的技术创新风险度量模型,并将该模型用于企业对技术创新项目进行风险度量和决策。     

Estimators for the common principal components model based on reweighting: influence functions and Monte Carlo study

The common principal components model for several groups of multivariate observations is a useful parsimonious model for the scatter structure which assumes equal principal axes but different variances along those axes for each group. Due to the lack of resistance of the classical maximum likelihood estimators for the parameters of this model, several robust estimators have been proposed in the literature: plug-in estimators and projection-pursuit (PP) type estimators. In this paper, we show that it is possible to improve the low efficiency of the projection-pursuit estimators by applying a reweighting step. More precisely, we consider plug-in estimators obtained by plugging a reweighted estimator of the scatter matrices into the maximum likelihood equations defining the principal axes. The weights considered penalize observations with large values of the influence measures defined by Boente et al. (2002). The new estimators are studied in terms of theoretical properties (influence functions and asymptotic variances) and are compared with other existing estimators in a simulation study.     

Maximum Likelihood Estimation of a General Unbalanced Spatial Random Effects Model: a Monte Carlo Study

Abstract

This paper discusses the maximum likelihood estimator of a general unbalanced spatial random effects model with normal disturbances, assuming that some observations are missing at random. Monte Carlo simulations show that the maximum likelihood estimator for unbalanced panels performs well and that missing observations affect mainly the root mean square error. As expected, these estimates are less efficient than those based on the unobserved balanced model, especially if the share of missing observations is large or spatial autocorrelation in the error terms is pronounced.

Estimation de vraisemblance maximale d'un modèle général d'effets aléatoires spatiaux déséquilibré: une étude Monte Carlo

RÉSUMÉ La présente communication se penche sur l'estimateur du maximum de vraisemblance d'un modèle général d'effets aléatoires spatiaux déséquilibré avec des perturbations normales, en supposant l'absence aléatoire de certaines observations. Des simulations de Monte Carlo montrent que des groupes déséquilibrés se comporte bien, et que les observations manquantes affectent principalement l'erreur de la moyenne quadratique. Comme prévu, ces évaluations sont moins efficaces que celles qui sont basées sur le modèle équilibré non observé, notamment si la part des observations manquantes est importantes, ou l'on déclare une autocorrélation spatiale dans les termes d'erreur.

Estimación de la probabilidad máxima de un modelo espacial general desequilibrado de efectos al azar: un estudio de Monte Carlo

RÉSUMÉN Este trabajo discute el estimador de probabilidad máxima de un modelo espacial general desequilibrado de efectos al azar con alteraciones normales, suponiendo que faltan algunas observaciones al azar. Las simulaciones de Monte Carlo muestran que el estimador de probabilidad máxima para los paneles desequilibrados funciona satisfactoriamente, y que las observaciones omisas afectan principalmente al error de la media cuadrática. Como se suponía, estas estimaciones son menos eficientes que las basadas en el modelo equilibrado inadvertido, especialmente si la cantidad de omisiones es grande/o la autocorrelación en los términos de error es pronunciada.

     

我国增值税扩围改革研究文献述评

分税制改革后,我国形成了增值税和营业税并存的局面,分别在中央和地方财政收入中占据主要地位,这对市场经济的运行造成了一定的扭曲,不利于经济结构的转型,因此增值税扩围改革势在必行。增值税扩围意味着营业税最终被取消,建立这样一个新体制对既有利益分配格局的冲击是显而易见的,在这一改革中如何兼顾各方面的利益将是增值税扩围改革能否取得成功的关键。本文主要对近年来国内学者关于增值税扩围及其相关问题的研究成果进行梳理,以期能为改革实践和有关研究提供参考。     

Biases in demand analysis due to variation in retail distribution

Aggregate demand models typically assume that consumers choose between all available products. Since consumers may be unwilling to search across every store in a given market for a particular item, this assumption is problematic when product assortments vary across stores. Using supermarket scanner data for five product categories we demonstrate that approximately one third of products have limited retail distribution, which account for one fourth of dollar sales. Monte Carlo analysis demonstrates that the level of limited product availability observed in the data can significantly bias the results of aggregate demand models that incorrectly assume all consumers in a given market face the same choice set.     

森林生态效益价值会计核算研究

森林生态效益是有价值的无形资产,这些价值不仅可以计量,而且应作为会计核算的对象。随着人们日益关注环境问题,营林企业应该将纳入企业会计核算的范围。本文着重研究了不同性质的营林企业如何进行森林生态效益价值的会计核算。     

Forecasting economic time series with unconditional time-varying variance

The classical forecasting theory of stationary time series exploits the second-order structure (variance, autocovariance, and spectral density) of an observed process in order to construct some prediction intervals. However, some economic time series show a time-varying unconditional second-order structure. This article focuses on a simple and meaningful model allowing this nonstationary behaviour. We show that this model satisfactorily explains the nonstationary behaviour of several economic data sets, among which are the U.S. stock returns and exchange rates. The question of how to forecast these processes is addressed and evaluated on the data sets.     

国家高新区技术创新效率增长空间不平衡及分布动态演进研究——基于双非参数估计方法

本文基于2014—2018年82家国家高新区的创新投入与创新产出数据,采用DEA-Malmquist指数和Kernel核密度估计方法实证研究了国家高新区技术创新效率增长的空间不平衡性及分布动态演进规律.研究发现:①在样本考察期内,国家高新区的技术创新效率呈现持续增长态势且存在空间不平衡;②国家高新区的技术进步变化由负转正,技术效率变化由正转负;③总体、东部、中部、西部及东北国家高新区的技术创新效率增长的空间差距都在明显扩大.     

Pension plan solvency and extreme market movements: a regime switching approach

We develop and test a new approach to assess defined benefit (DB) pension plan solvency risk in the presence of extreme market movements. Our method captures both the ‘fat-tailed’ nature of asset returns and their correlation with discount rate changes. We show that the standard assumption of constant discount rates leads to dramatic underestimation of future projections of pension plan solvency risk. Failing to incorporate leptokurtosis into asset returns also leads to downward biased estimates of risk, but this is less pronounced than the time-varying discount rate effect. Further modifying the model to capture the correlation between asset returns and the discount rate provides additional improvements in the projection of future pension plan solvency. This reduces the perceived future risk of underfunding because of the negative correlation between interest rate changes and asset returns. These results have important implications for those with responsibility for balancing risk against expected return when seeking to improve the current poor funding positions of DB pension schemes.     

Size,time-varying beta,and conditional heteroscedasticity in UK stock returns

The purpose of this study is to examine the relationship between firm size and time-varying betas of UK stocks. We extend the Schwert and Seguin (1990)(Journal of Finance 45, 1120–1155) methodology by explicitly modeling conditional heteroscedasticity in the market model residual returns. Our results show that the time-varying coefficient is not statistically significant for both small and large firm stock indexes. We also find that accounting for GARCH effects in the Schwert-Seguin market model yields beta estimates that are markedly differently from those when conditional heteroscedasticity is ignored. Event studies that ignore conditional heteroscedasticity may bias the abnormal returns of small and large firms, thereby leading to a different conclusion regarding the significance of an information event.