山西省乡村休闲旅游地空间分布特征及影响因素研究

［目的］通过对山西省乡村休闲旅游地的空间分布特征及影响因素进行研究，旨在为山西省的乡村旅游发展提供合理的参考建议。［方法］选取山西省213处国家级和省级乡村旅游示范点为研究对象，运用最临近点指数对其空间分布类型进行判别，并运用地理集中指数和地理联系率对其分布均衡程度和地理联系程度进行考量，通过核密度图进一步分析其空间分布指向，在此基础上对影响因素进行分析。［结果］山西省乡村休闲旅游地空间分布呈集聚分布的特点，且与经济规模和人口密度在空间上的均衡、配合程度较高。［结论］（1）山西省乡村休闲旅游地包括以太原和晋中为主的中部密集区和以临汾、运城、晋城为主的南部密集区，且都以各地级市为中心向周边扩展，大多数示范点分布于城郊地区； （2）经济发展、人口密度、资源禀赋、区位因素和社会因素是影响山西省乡村休闲旅游地分布的主要因素，其中农业科技类、农事体验类和特色村镇类多分布于经济和人口密度较高的地区。     

区域制造业空间效应及生产性服务业发展模式选择

通过空间计量模型考察生产性服务业发展模式与制造业集聚的空间溢出效应后发现:生产性服务业专业化水平及多样化水平与制造业集聚呈倒U型关系,同时城市化水平会对服务业发展模式与制造业集聚关系产生影响。分区域模型研究发现,生产性服务业对制造业全要素生产率影响因区域经济发展水平、产业层次、要素禀赋等因素有所差异,东部地区制造业全要素生产率与生产性服务业呈线性关系,适合选择多样化发展模式;中部地区呈倒U型关系,现阶段中部地区生产性服务业更适合选择多样化发展模式;西部地区生产性服务业发展水平与制造业全要素生产率呈正U型关系,生产性服务业专业化和多样化发展都将促进制造业全要素生产率提升。     

How does leverage in stock market influence the margin of stock index futures?

In this article, we propose a margin-setting model under the assumption of extreme stock price changes. Specifically, extreme stock price changes are caused by the positive feedback effect of leverage and market impact. By introducing these factors into the futures price changes through a cost-of-carry model for setting the margin of stock index futures, we find that leverage and market impact in stock market are positively correlated with the margin.     

Cost analysis of plasma-derived factor VIII/von Willebrand factor versus recombinant factor VIII for treatment of previously untreated patients with severe hemophilia A in the United States

Background: Inhibitor development to factor VIII (FVIII) hemophilia therapy results in increased complications and substantial economic costs. The SIPPET study, the first randomized controlled trial to compare the immunogenicity of plasma-derived FVIII (pdFVIII)/von Willebrand factor (VWF) and recombinant-DNA-derived FVIII (rFVIII), demonstrated higher inhibitor rates in previously untreated patients (PUPs) treated with rFVIII than in PUPs treated with pdFVIII/VWF.

Objective: To quantify the economic impact of treating PUPs with pdFVIII/VWF vs rFVIII.

Methods: An Excel-based clinical and economic model was developed from a US healthcare payer perspective and run over a 5-year period. The analysis utilized a cohort approach to model patient treatment and outcomes over a monthly cycle to quantify differences in costs of FVIII, bypassing agents, and hospitalizations for serious bleeds. Rates of high-titer inhibitor development were obtained from the SIPPET study. Patients developing high-titer inhibitors were treated with immune tolerance induction (ITI). Patients who developed low-titer inhibitors and those who did not develop inhibitors continued their usual FVIII treatment. Patients who were successfully treated with ITI returned to FVIII treatment, while unsuccessfully treated patients received bypassing agents. Total costs per treated patient were estimated and a one-way sensitivity analysis was conducted to quantify the impact of parameter uncertainty on the model outcomes.

Results: Total cumulative costs per patient over 5 years were $834,621 for pdFVIII/VWF patients and $1,237,163 for rFVIII patients, representing a total saving of $402,542 per patient over the 5-year period, for an average annual saving of $80,508 per patient.

Conclusions: Based on data from the SIPPET study, this analysis found that initiating FVIII treatment in severe hemophilia A PUPs with pdFVIII/VWF has the potential to offer substantial cost savings to healthcare payers, amounting to a one-third reduction in costs.     

财政压力、技术创新与绿色全要素生产率

经济社会转型期典型的中国式"压力型"财政，对地方创新活动和绿色可持续发展具有重要影响。运用2004~2017年中国256个地级市面板数据，实证考察了财政压力对绿色全要素生产率的影响以及传导机制。基准检验结果显示，财政压力显著抑制了绿色全要素生产率的提升，技术创新对绿色全要素生产率具有显著的促进作用；中介效应检验发现，财政压力通过抑制技术创新进而阻碍绿色全要素生产率的提升，即验证了财政压力→技术创新→绿色全要素生产率的传导机制；进一步门槛效应检验表明，技术创新对绿色全要素生产率的影响存在基于财政压力的双门槛效应，在财政压力的不同门槛值区间，技术创新对绿色全要素生产率的促进效应呈现出明显的阶梯性降低趋势。未来需综合完善中国式"压力型"财政激励制度，合理控制财政压力的区间范围，助力技术创新以提升城市绿色全要素生产率。     

Migration,population aging,and income inequality in China

In this study, we examine the effects of four demographic factors, namely, birth, death, natural aging, and net migration, on population aging and income inequality in China. We use the official Chinese data and the China Household Income Project Survey data for the 2007–2013 period and apply a decomposition model based on the Shapley method. Unlike previous studies, we include migration in our decomposition model and find that natural aging is the primary factor contributing to population aging in both urban and rural areas. Further, migration may accelerate population aging in rural areas. Moreover, migration contributes to reducing income inequality in urban areas, while widening income inequality in rural areas. The effect of migration is larger than those of birth, death, and natural aging on income inequality. The robustness checks confirm these conclusions.     

Factor extraction using Kalman filter and smoothing: This is not just another survey

Dynamic factor models have been the main “big data” tool used by empirical macroeconomists during the last 30 years. In this context, Kalman filter and smoothing (KFS) procedures can cope with missing data, mixed frequency data, time-varying parameters, non-linearities, non-stationarity, and many other characteristics often observed in real systems of economic variables. The main contribution of this paper is to provide a comprehensive updated summary of the literature on latent common factors extracted using KFS procedures in the context of dynamic factor models, pointing out their potential limitations. Signal extraction and parameter estimation issues are separately analyzed. Identification issues are also tackled in both stationary and non-stationary models. Finally, empirical applications are surveyed in both cases. This survey is relevant to researchers and practitioners interested not only in the theory of KFS procedures for factor extraction in dynamic factor models but also in their empirical application in macroeconomics and finance.     

Factors influencing consumers' purchase decision-making in O2O business model: Evidence from consumers' overall evaluation

Online-to-offline (O2O) has become a rapidly growing e-commerce model worldwide, but the factors influencing consumers' purchase decision-making have not been examined well. After exploring the working mechanism of the O2O model, we extract eleven indexes of consumers' overall evaluation in the O2O model with Crawlzilla and R techniques. Social network analysis (SNA) is adopted to build social networks reflecting consumers' overall evaluation in the O2O model. Based on the modified social network and the extracted subgraph, this study (N = 768) reveals consumers' overall evaluation behavior patterns in the O2O model by calculating network density, central potential, edge betweenness. The results show that shoppers overall evaluate the eleven indexes, especially perceived product quality, online product price, promotion intensity, business reputation, and product brand, which reflects the significant associations between the indexes. Among all the eleven evaluation indexes, perceived product quality, online product price, and business reputation dominate consumers’ decision-making behavior. When making purchase decisions, consumers not only overall consider online product price, perceived product quality, and business reputation but also balance perceived product quality, business reputation, and promotion intensity. Finally, we make some suggestions on marketing strategy for e-commerce companies.     

Analysis of Bitcoin prices using market and sentiment variables

This paper proposes an empirical model for analysing the dynamics of Bitcoin prices. To do this, we consider a vector error correction model over two overlapping periods: 2010–17 and 2010–19. Price discovery is achieved through the Gonzalo–Granger permanent‐transitory decomposition. The pricing factors are endogenous linear combinations of the S&P 500 index, gold price, a Google search variable associated to Bitcoin and a fear index proxied by the FED Financial Stress Index. Our empirical analysis shows that during the first period, a linear combination of four pricing factors describes the efficient Bitcoin price. The S&P 500 index and Google searches have a positive effect whereas gold prices and the fear index have a negative effect. In contrast, during the second period, the efficient price behaves idiosyncratically and can be only rationalised by individuals' search for information on the cryptocurrency. These findings provide empirical evidence on the presence of a correction in Bitcoin prices during the period 2018–19 uncorrelated to market fundamentals. We also show that standard empirical asset pricing models perform poorly for explaining Bitcoin prices.     

Agricultural productivity growth in Latin America and the Caribbean: an analysis of climatic effects,catch‐up and convergence*

This paper investigates whether climatic adjusted total factor productivity (CATFP) in Latin America and the Caribbean (LAC) is converging, converging to different steady states or exhibit absolute convergence, that is the process does not require (government) interventions to reach its equilibrium path. We use data from the University of East Anglia’s Climatic Research Unit and from the Food and Agriculture Organization for 28 LAC countries over a 54‐year period (1961–2014) to estimate random parameters stochastic production frontier models to calculate CATFP and then use cross‐sectional regressions and an error correction model to analyse CATFP convergence across countries in the region. The results show that technological progress is the main driver of CATFP growth in the region and there is no absolute convergence, that is CATFP gaps across countries will not decrease over time and least performing countries will not grow faster than better performing ones without targeted policies. However, CATFP across LAC exhibits conditional convergence towards different steady states. Technological progress plays a critical role in raising the steady state level of CATFP with an overall average of 2.22 per cent per annum.