初次收入分配与技术进步——基于马克思主义经济学的视角

生产力概念的深化对于马克思主义的发展非常重要,考察初次收入分配与技术进步之间的关系是一个可行的切入点。在税收收入占比保持不变的情况下,劳动收入占比的下降意味着资本收入占比的上升。劳动收入占比的下降缩小了消费市场规模而抑制技术进步(消费效应),资本收入占比的提高使得企业技术投资面临更少的融资约束而促进技术进步(融资效应),初次收入分配与技术进步之间可能呈现出无关、线性或者倒U型关系,其具体关系要视消费效应和融资效应的相对强弱而定。基于中国省际面板数据的实证分析发现,中国初次收入分配与技术进步之间的关系呈现出倒U型关系,存在一个最有利于技术进步的初次收入分配格局,意味着当前需要同时保护劳动和资本的权利。     

Dynamic jump intensities and risk premiums: Evidence from S&P500 returns and options

We build a new class of discrete-time models that are relatively easy to estimate using returns and/or options. The distribution of returns is driven by two factors: dynamic volatility and dynamic jump intensity. Each factor has its own risk premium. The models significantly outperform standard models without jumps when estimated on S&P500 returns. We find very strong support for time-varying jump intensities. Compared to the risk premium on dynamic volatility, the risk premium on the dynamic jump intensity has a much larger impact on option prices. We confirm these findings using joint estimation on returns and large option samples.     

中国绿色创新指数的分布动态演进与区域差异

研究目标:编制中国绿色创新指数,考察各区域指数的分布动态、区域差异及空间收敛特征。研究方法:建立绿色创新指数评价体系、采用时空极差熵权法赋权指标,利用世界知识产权组织绿色专利清单在线检索工具和采用爬虫技术检索、匹配、汇总国家知识产权局绿色专利数据,采用社会网络分析法(Social Network Analysis, SNA)测度绿色技术创新辐射力,采用Kernel估计分析绿色创新分布动态演进,采用Dagum基尼系数分解东中西绿色创新空间差距来源,采用空间杜宾模型考察绿色创新空间β条件收敛特征。研究发现:我国整体及东中西各地区绿色创新水平均呈总体上升趋势,源于绿色技术创新能力、绿色技术创新辐射力与绿色创新制度支撑力三者“携手并进”;绿色创新水平较高的城市集中分布于经济发达地区并具有较高行政级别特征,北京、深圳、上海、广州及主要省会城市稳居前列;我国整体及东中西地区核密度图均呈现“曲线右移、峰值先升后降、宽度收窄后扩大”的特征;东中西区域内部及区域间差异均呈逐渐下降趋势;绿色创新存在空间β条件收敛效应,且俱乐部收敛特征也较为显著,但在不同空间权重矩阵、不同地区样本中收敛速度存在差异。研究创...     

Investigating the impact of demand amplification on freight transport

Despite freight transport operations being influenced by supply chain dynamics, there has been only a very limited investigation into the impact of demand amplification on this function, with almost no analytical research. This paper aims, through spreadsheet simulation of a generic production control system, to quantify the impact of demand amplification on transport performance. Performance measures evaluated include both transport cost and efficiency. The results in general find a negative relationship between transport performance and demand amplification. It is also found that the ratio of vehicle capacity to average demand affects these results.     

居民住房房地产税免税扣除方式的效应分析——基于中国家庭收入调查数据的微观模拟

对居民住房征收房地产税要考虑家庭最基本的居住需要,有必要设计合理的免税扣除方案。本文基于中国家庭收入调查数据,比较分析了"按人均面积扣除"、"按人均价值扣除"和"按套数扣除"三种免税扣除方式的公平效应、财政收入效应和供求效应。研究发现,在改善收入分配、筹集财政收入和调节房地产市场供求方面,"按套数扣除"方式最不可取,"按人均面积扣除"和"按人均价值扣除"方式各有利弊。本文建议将人均面积扣除和人均价值扣除方式相结合,采取"面积+价值"的复合扣除方式,并提出了相应的配套措施及建议。     

Performance effects of innovation in two-sided markets: The paradigmatic case of OTAs

Online Travel Agents (OTAs) play an important intermediary role in the two-sided travel distribution market. A critical factor that enhances a firm's competitive advantage is innovation. Yet, the analysis of innovation in the OTA context is scarce. The main objective of this article is to fill this gap and examine the effect of OTA innovations on firm performance. We analyze the effect of two-sided market specific innovations (same-side and cross-side) on performance and contribute to the literature by expanding the theoretical understanding of innovations. We find that producer-to-consumer innovations have a greater effect on OTA performance than producer-to-producer and consumer-to-consumer innovations. A fundamental managerial implication is that exchange management is an area to be enhanced when innovating in travel market distribution.     

M5 competition uncertainty: Overdispersion,distributional forecasting,GAMLSS, and beyond

The M5 competition uncertainty track aims for probabilistic forecasting of sales of thousands of Walmart retail goods. We show that the M5 competition data face strong overdispersion and sporadic demand, especially zero demand. We discuss modeling issues concerning adequate probabilistic forecasting of such count data processes. Unfortunately, the majority of popular prediction methods used in the M5 competition (e.g. lightgbm and xgboost GBMs) fail to address the data characteristics, due to the considered objective functions. Distributional forecasting provides a suitable modeling approach to overcome those problems. The GAMLSS framework allows for flexible probabilistic forecasting using low-dimensional distributions. We illustrate how the GAMLSS approach can be applied to M5 competition data by modeling the location and scale parameters of various distributions, e.g. the negative binomial distribution. Finally, we discuss software packages for distributional modeling and their drawbacks, like the R package gamlss with its package extensions, and (deep) distributional forecasting libraries such as TensorFlow Probability.     

Out-of-stock justifications and consumers’ behavioral outcomes– exploring the role of product type and sales level information in out-of-stock situations

The present study extends prior research on stockouts by examining how product-related attributes interact with OOS justifications to influence consumer responses to stockouts. Drawing from Out-of-stock (OOS) literature, this study investigates how perceived popularity, perceived uniqueness, negative affect, and behavioral outcomes are influenced by out-of-stock justifications, product type, and sales level. Two scenario-based experiments and two field studies are conducted in which the cause of the stockout, product type, and sales level are manipulated at different levels. The results of the studies provide the following primary insights- 1) Consumers infer popularity of the product when the product is OOS due to high demand or when the sales level is high 2) Consumers infer uniqueness of the product when the product is OOS due to short supply but not when sales level is low 3) As the perceived popularity of utilitarian products or the perceived uniqueness of hedonic products increases, consumers' propensity to switch stores to purchase the OOS products increases 4) Consumers’ intention to spread negative word of mouth decreases when the cause of OOS or a high sales level is specified. Retailers can influence behavioral outcomes by specifying the cause of stockout tailored according to the type of product, or by providing sales level information.     

Logistics optimization through a social approach for food distribution

The management of supply chains is becoming more important in economic and social environments. Currently, the social sustainability is a factor that must be considered to design governmental strategies and policies. The objective of this research paper was to show, with a case study an approach to optimize distribution and delivery logistics of food in a social assistance program of school breakfast using mathematical models that include transportation distance, optimal locations, and vehicle routing through different clusters. By using qualitative variables like poverty levels, food insecurity and social exclusion, different clustering methods are proposed with the purpose of identifying the common characteristics in the studied population; and at the same time, reducing the distribution complexity. The results show an efficient approach to design a supply chain that includes economic and social factors. The new model developed in this paper can be used to plan social assistance governmental programs, to identify the specific needs and characteristics of the beneficiaries, minimizing the total cost of the distribution network logistics when delivering food for school meals.     

Modelling distribution of aggregate expenditure on tourism

The aim of this article is to obtain a statistical distribution that describes the aggregate expenditure of tourists related to their length of stay at a given location. This distribution enables us to estimate two parameters simultaneously; one controls the length of stay and the other, the expense incurred. We propose two distribution models, for which closed-form expressions are obtained. Covariates are introduced in order to study the factors that affect the aggregate expenditure. The results obtained indicate that the models achieve a reasonably good fit, with and without covariates.