Forecasting Bordeaux wine prices using state-space methods

Generic Bordeaux red wine (basic claret) can be regarded as being similar to an agricultural commodity. Production volumes are substantial, they are traded at high frequency and the quality of the product is relatively homogeneous. Unlike other commodities and the top-end wines (which represent only 3% of the traded volume), there is no futures market for generic Bordeaux wine. Reliable forecasts of prices can to large extent replace this information deficiency and improve the functioning of the market. We use state-space methods with monthly data to obtain a univariate forecasting model for the average price. The estimates highlight the stochastic trend and the seasonality present in the evolution of the price over the period 1999 to 2016. The model predicts the path of wine prices out of sample reasonably well, suggesting that this approach is useful for making reasonably accurate forecasts of future price movements.     

玻璃纤维增强塑料夹砂管初始力学性能检测的研究

由玻璃纤维增强塑料夹砂管的环刚度、刚度等级概念分析了环刚度设计与检测的基本方法,探讨挠曲水平、轴向拉伸强力和环向拉伸强力检测方法,比较分析了各种方法的优缺点与适用范围,对理解及掌握玻璃纤维增强塑料夹砂管初始力学性能的概念及相关检测方法具有一定参考意义。     

Accounting Research: Where Now?

This paper provides a commentary on the studies of Barth (2015), Dyckman and Zeff (2015), Ohlson (2015), Sunder (2015), and Whittington (2015) as they relate to past, present, and future directions in accounting research.     

Varying Coefficient Regression Models: A Review and New Developments

Varying coefficient regression models are known to be very useful tools for analysing the relation between a response and a group of covariates. Their structure and interpretability are similar to those for the traditional linear regression model, but they are more flexible because of the infinite dimensionality of the corresponding parameter spaces. The aims of this paper are to give an overview on the existing methodological and theoretical developments for varying coefficient models and to discuss their extensions with some new developments. The new developments enable us to use different amount of smoothing for estimating different component functions in the models. They are for a flexible form of varying coefficient models that requires smoothing across different covariates' spaces and are based on the smooth backfitting technique that is admitted as a powerful technique for fitting structural regression models and is also known to free us from the curse of dimensionality.     

浅谈测量员如何更好更快地提高业务水平

测量作为服务于国民经济建设的重要行业，随着传统测绘技术向数字化测绘技术转化，它表现出复杂性及多样性，当我们面对一项新的测量任务时，除了传统学习模式之外，我们该如何更好地提高自身地业务水平呢？本文结合作者工作经验论述了上述问题，为测量同行提供一些建议及指导。     

Small Area Estimation for Disease Prevalence Mapping

Small area estimation (SAE) entails estimating characteristics of interest for domains, often geographical areas, in which there may be few or no samples available. SAE has a long history and a wide variety of methods have been suggested, from a bewildering range of philosophical standpoints. We describe design-based and model-based approaches and models that are specified at the area level and at the unit level, focusing on health applications and fully Bayesian spatial models. The use of auxiliary information is a key ingredient for successful inference when response data are sparse, and we discuss a number of approaches that allow the inclusion of covariate data. SAE for HIV prevalence, using data collected from a Demographic Health Survey in Malawi in 2015–2016, is used to illustrate a number of techniques. The potential use of SAE techniques for outcomes related to coronavirus disease 2019 is discussed.     

Effects of subject pool culture and institutional environment on corruption: Experimental evidence from Albania

This research uses experimental methods to investigate whether subject pool culture and institutional environment have an effect on participants’ corrupt behavior in the laboratory. While we find that subject pool culture does not affect the overall magnitude of corruption of laboratory participants, it does affect the likelihood of corruption and its distribution. Additionally, we find that the effect on corrupt behavior differs with the framing of the experiment’s instructions. Interestingly, in the context of a weak rule of law and high levels of corruption, loaded negative instructions positively affect corrupt behavior of firms and public officials. Previous research in the context of a country exhibiting a strong rule of law and low levels of corruption finds no framing effects. We also find that increasing the probability of detection significantly reduces corruption as measured by the amount of the bribes offered/accepted and the probability of offering/accepting a bribe. Finally, we find that individual risk preferences negatively affect the level of corrupt behavior.     

Bridging the valuescape with digital technology: A mixed methods study on customers’ value creation process in the physical retail space

This mixed methods study investigated how value is created in the physical retail space and how the customer experience is influenced by digital technology. A cross-sectional survey, with both qualitative and quantitative components, was distributed across a heterogeneous sample of 832 customers. The results revealed an overarching model comprised of three interrelated clusters: customer, service provider, and digital technology. We propose that this model can be understood as a valuescape, where customers' specific goals, needs, and desires drive them to interact and co-create value with service providers in the physical retail space, with digital technology either enhancing or disrupting this value co-creation process. The results also show that the importance of aligning digital solutions with customers’ drives increases at the same pace as reliance on technology. The findings offer guidelines on how to utilize digitalization to leverage customer experiences and thus strengthen the attractiveness of physical retail spaces.     

In CEOs we trust: When religion matters in cross-border acquisitions. The case of a multifaith country

This paper examines the emergence of trust by multifaith target-firm personnel in foreign acquirer CEOs during early post-acquisition integration, a decisive period for acquisition success, yet considerably under-researched. Combining self-categorization and similarity-attraction theories, we argue that religious similarity with the foreign acquirer’s CEO represents shared values to the personnel, from which trust in the CEO arises. Further, we scrutinize the moderating effects of the personnel’s religiosity and prior alliance success between the acquirer and target firm. We test our model using field-experimental data from 411 multifaith Malaysian personnel. The findings show that personnel-leader trust occurs more readily with religious similarity than religious dissimilarity, and that the personnel’s religiosity strengthens this relationship. However, a successful prior alliance does not weaken the religious similarity–trust relationship. Our research encourages acquisition managers to consider religion, a factor beyond the traditional acquisition playbook, as a trust antecedent during early post-acquisition integration.     

Correction to: Optimal and robust combination of forecasts via constrained optimization and shrinkage

We provide a correction to Proposition 1 in Optimal and robust combination of forecasts via constrained optimization and shrinkage, published in the International Journal of Forecasting 38(1):97-116 (2021). This correction has no impact on any other result (neither theoretical nor empirical) provided in the above paper.