长江经济带中三角地区农业结构的分析与优化对策

[目的]从宏观、中观和微观3个层面深入分析长江经济带中三角地区湖北、湖南和江西3省的农业产业结构及其各产业差异性和相对优势及其竞争力。[方法]在宏观层面运用了传统的基尼系数分析3个省份历史发展上的地区经济水平差异,判断3个地区经济发展是否存在虹吸效应;从中观层面运用区位熵指数分析法分析区域农业产业结构,从农畜林渔等方面判断各区域产业专业化水平程度;从微观层面运用偏离—份额分析法(SSM)分离出3个地区的各部门产业的优势及其竞争力。[结果]区域内的经济差异变化呈不断增大的趋势,基尼系数不断扩大;湖北的种植业、渔业和农林牧渔服务业,湖南的种植业、林业、畜牧业和农林牧渔服务业,江西的林业、渔业都较中三角地区对应的子产业的区位熵指数高;江西木材和竹加工业和烟草业具有较大的产业竞争优势,湖北的茶叶、水产和瓜果疏菜产业优势明显,湖南地区农业产业综合优势主要在于烟草、水果、肉类以及木材和竹类加工业。[结论]通过比较地区农业产业竞争优势,提出发展地区产业特色,合理布局全域农业产业,提高农产品附加收益,稳固对结构优化的资金支持等对策建议。     

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.     

成渝经济区生态农业对区域经济影响分析

[目的]区域经济发展反映经济各个方面的综合发展状况,探讨其影响因素以确定区域未来经济的发展方向,为进一步规划发展提供科学依据。[方法]先构建生态农业评价指标体系再采用层析分析法确定权重,结合线性加权和函数计算生态农业评价指数,通过相关分析法分析生态农业各个指标与区域经济的关系,最终确定生态农业对成渝经济区经济的影响程度。[结果]生态农业指标中评价指数大于0.9是森林覆盖率,介于0.8~0.7的包括投入产出比、土地生产率、农业科技贡献率、万人拥有的科技人员、劳动生产率、化肥施用量。且生态农业中各个指标与GDP都正相关,其中森林覆盖率、人均收入增长率、农业科技贡献率和万人拥有的科技人员与GDP显著相关,对区域经济的影响最大。[结论]成渝经济区经济受生态农业的影响,进一步选取更多生态农业相关因素,对于全面促进区域经济持续发展具有十分的重要现实意义。     

Volatility dynamics under an endogenous Markov-switching framework: a cross-market approach

This study uses an endogenous Markov-switching framework to examine the interrelatedness of the volatility dynamics of the US and Korean markets. Previous literature assumes that the US market implied volatility index is exogenous to the Korean implied volatility index. Here, we allow for correlations between the US and Korean variables and suggest two types of endogeneity, namely endogeneity in the regressors and in the regime-switching probabilities. The estimation results show that both types of endogeneity are present in the US variables and that the parameter estimates are quite different when endogeneity is considered, indicating a serious endogeneity bias in the parameter estimates. The results of the endogeneity test for the regressors show that the effects of global shocks are often persistent and may last for as long as six periods. Sub-period analyses indicate that the degrees of endogeneity were especially strong during the global financial crisis.     

旅游目的地地格的理论源流、本质与测度指标

全球化背景下,在旅游目的地开发与营销过程中忽视了地方的本质特征,旅游目的地竞争走向“无地方性”与“无个性”的地方趋同陷阱。地格理论融合地理学的地方性理论、营销学的品牌个性理论、旅游学的推拉理论以及管理学的资源基础论,提出旅游目的地开发与营销成功的关键是以地格为依托,即关注目的地长期积累形成的生活方式的本质特征,避免地方趋同。本文指出具有代表力、吸引力与竞争力的旅游地格是旅游目的地的品牌基因,还从旅游目的地政府、游客和居民视角出发,运用定性与定量相结合的方法,创建了由自然环境、人文环境与群体性格组成的地格因子体系。     

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.     

南京江北新区新型城镇化发展质量评价与提升路径

文章构建了由31项指标组成的新型城镇化综合发展质量评价指标体系,运用AHP层次分析法和熵值法,选择19个国家级新区中2018年经济总量排名前十的新区进行定量对比分析,并结合民生幸福建设群众满意度问卷调查分析,对南京江北新区新型城镇化发展质量进行综合评价。研究表明:(1)南京江北新区新型城镇化整体发展处于中上游水平,与发达新区相比存在一定差距,产业结构亟需优化;(2)发展增长方式、资源利用率、环境保护类指标明显落后;(3)科教文卫、居民生活等指标具有比较优势。文章最后提出新型城镇化提升路径为加快生态环境和公共服务建设,积极提升科教和生态示范效应,做大做强主导产业,促进城乡特色均衡发展和推进以人为核心的新型城镇化。     

How Fast are Semiconductor Prices Falling?

The Producer Price Index (PPI) for the U.S. suggests that semiconductor prices have barely been falling in recent years, a dramatic contrast to the rapid declines reported from the mid‐1980s to the early 2000s. This slowdown in the rate of decline is puzzling in light of evidence that the performance of microprocessor units (MPUs) has continued to improve at a rapid pace. Over the course of the 2000s, the MPU prices posted by Intel, the dominant producer of MPUs, became much stickier over the chips' life cycle. As a result of this change, we argue that the matched‐model methodology used in the PPI for MPUs likely started to be biased after the early 2000s and that hedonic indexes can provide a more accurate measure of price change since then. MPU prices fell rapidly through 2004 on every price measure we present, with the PPI declining at an even quicker pace than the hedonic indexes. However, from 2004 to 2009, our preferred hedonic index fell faster than the PPI, and from 2009 to 2013 the gap widened further, with our preferred index falling at an average annual rate of 42 percent, while the PPI declined at only a 6 percent rate. Given that MPUs currently represent about half of U.S. shipments of semiconductors, this difference has important implications for gauging the rate of innovation in the semiconductor sector.     

An information-theoretic approach for forecasting interval-valued SP500 daily returns

We develop an iterative and efficient information-theoretic estimator for forecasting interval-valued data, and use our estimator to forecast the SP500 returns up to five days ahead using moving windows. Our forecasts are based on 13 years of data. We show that our estimator is superior to its competitors under all of the common criteria that are used to evaluate forecasts of interval data. Our approach differs from other methods that are used to forecast interval data in two major ways. First, rather than applying the more traditional methods that use only certain moments of the intervals in the estimation process, our estimator uses the complete sample information. Second, our method simultaneously selects the model (or models) and infers the model’s parameters. It is an iterative approach that imposes minimal structure and statistical assumptions.     

基于图形小波变换的遥感图像表示与去噪

离散小波变换（Discrete Wavelet Transform，DWT）通常用于图像的表示。然而，对于具有不规则形状边缘的图像，尤其是对于纹理和细节信息较多的遥感图像，DWT却很难有效表示，进而影响后续去噪效果。针对该问题，提出了一种基于图形小波变换（Graphic Wavelet Transform，GWT）的图像去噪方法。首先，将图像表示为图形信号，并通过该图形信号的谱表示构造相应的变换矩阵；然后，设计了一种改进自适应阈值的图像去噪方法，在GWT变换域内对图像去噪。实验结果表明，与常用的图像去噪方法相比，所提算法能够提供更好的图像主观质量。采用均方根误差（Root Mean Square Error，RMSE）和峰值信噪比（Peak Signal-to-Noise Ratio，PSNR）作为客观指标，结果表明，采用所提方法得到的重建图像客观质量更优。