新能源汽车价格补贴政策的绩效分析和改善建议--以J新能源汽车公司为例

新能源汽车是我国汽车行业重要的发展方向,笔者通过研究我国新能源汽车的发展历程、价格补贴政策存在的问题,提出完善新能源汽车价格补贴政策的对策,以期为我国新能源产业的科学发展和我国汽车产业的转型升级提供参考。     

中国生猪价格周期性波动分析、展望及对策

2006年以来,中国生猪价格波动经历了三个半周期,呈现出价格波动周期日益延长、价格波动幅度前窄后宽、传统消费旺季作用逐渐消退等特征。其中既有生猪养殖自身规律、规模化养殖比例提升等内因的影响,也有上游行业价格变动、生猪疫情等外因的影响。综合来看,2019年非洲猪瘟疫情发展、规模化生猪养殖场补栏、气温条件变化及冬季的猪肉旺季消费等情况会对后续的生猪价格波动走势产生较大影响,至2020年春节前生猪价格持续走高。应通过加快生猪养殖产业结构升级、加强生猪市场信息服务体系建设、推进生猪产业链市场化发展等措施,有效减缓中国生猪价格周期波动的影响。     

体验型产品在线评论与消费意愿及销量的关系——以价格为调节变量

随着网络在线交易的迅猛发展,在线评论等网络口碑传播的重要性日益凸显。以体验型产品为研究对象,以信号理论和"刺激-反应"理论为指导,建立"在线评论-消费意愿-在线销量"模型分析三个要素之间的关系机理,并采用中介效应检验和调节效应检验进行验证,结果显示:在线评论作为一种信息刺激,其数量对体验型产品在线销量具有显著的正向影响,但在线评论质量效价评分对体验型产品在线销量的影响不显著,这与产品的类型有关;在线评论一是直接对在线销量产生影响,一是通过中介变量(即作为消费意愿替代变量的收藏量)传递影响,对在线销量产生作用;商品价格在在线评论和在线销量的直接和间接关系中都起到了正向调节作用,这与体验型产品交易过程中价格质量信号功能强于促销功能有关。实践中,企业可通过一些激励设计提高消费者在线评论参与度;进行更加科学化的网页设计,完善收藏功能,以方便消费者进行筛选和比较;注意防止盲目降价行为给消费者带来的负面影响,发挥好价格的信号作用。     

中美玉米期货市场功能效率比较

价格发现与套期保值是期货市场的基本功能,能够反映期货市场的运行效率。通过对比中美贸易摩擦前后期货市场的价格发现和套期保值功能,分析中美玉米期货市场效率间的差距,探究我国玉米期货市场运行效率低的原因。利用格兰杰(Granger)因果分析、协整检验、分位信息份额模型、套期保值比率及绩效分析方法,定量对中美两国2013—2019年玉米期货及现货的数据进行分析,结果表明,中国玉米期货市场存在较强的价格发现功能,但套期保值绩效不佳。使用前沿分位信息份额模型和滚动格兰杰因果法分析中美两国期现货市场动态关系的区别,发现中国仅存期货市场对现货市场的单向引导,而美国在中美贸易摩擦前表现为玉米期现货市场具有相近的引导能力,套期保值效率较高,中美贸易摩擦增强了其现货市场对期货市场的引导能力,降低了期货市场运行效率。从期现货市场双向引导关系视角来看,中国玉米期货市场效率低的原因主要是现货市场的信息不完全、发展不完善,期现货市场缺少长期稳定的双向引导关系抑制了期货市场功能发挥。中国应全面加强期货市场建设,提升期货市场定价效率,推动农产品期货市场快速健康发展。     

国有农用地基准地价评估研究——以广东省云浮市云城区为例

农用地估价,是以农用地定级为基础的农用地基准地价评估。农用地定级与基准地价评估是根据农用地的自然属性和经济属性,对农用地的质量优劣进行综合评定,划分土地质量级别并测算土地价格。以广东云城区国有农业用地为研究对象,采取"先定级后估价"的方式,通过因素因子法综合评定农用地级别,再通过样点地价法进行估价,确定了农用地的基准地价。     

Forecasting using heterogeneous panels with cross-sectional dependence

In this paper, we focus on forecasting methods that use heterogeneous panels in the presence of cross-sectional dependence in terms of both spatial error dependence and common factors. We propose two main approaches to estimating the factor structure: a residuals-based approach, and an approach that uses a panel of auxiliary variables to extract the factors. Small sample properties of the proposed methods are investigated through Monte Carlo simulations and applied to predict house price inflation in OECD countries.     

The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning

Whether investor sentiment affects stock prices is an issue of long-standing interest for economists. We conduct a comprehensive study of the predictability of investor sentiment, which is measured directly by extracting expectations from online user-generated content (UGC) on the stock message board of Eastmoney.com in the Chinese stock market. We consider the influential factors in prediction, including the selections of different text classification algorithms, price forecasting models, time horizons, and information update schemes. Using comparisons of the long short-term memory (LSTM) model, logistic regression, support vector machine, and Naïve Bayes model, the results show that daily investor sentiment contains predictive information only for open prices, while the hourly sentiment has two hours of leading predictability for closing prices. Investors do update their expectations during trading hours. Moreover, our results reveal that advanced models, such as LSTM, can provide more predictive power with investor sentiment only if the inputs of a model contain predictive information.     

Fiscal and monetary interdependence

Where classical economics integrates the quantity theory of money with the concept of Ricardian equivalence, the tendency of recent macroeconomic presentations is to focus either upon money and inflation or upon taxation and debt. That neglect of classical monetary–fiscal integration is surprising, given an initiative by the International Monetary Fund that set credit, money, and fiscal policy within a single structure. This article places those ‘credit counterparts of broad money’ in the context of the Great Depression and the recent global financial crisis. The upshot is a set of conclusions: that, to counter the prospect of deflation, quantitative easing is a weak policy response; that fiscal deficits are better; and that cuts in taxation are preferable to increased government spending.     

Credit risk pricing and the rationality of lending decision-making within dual banking systems: A parametric approach

The reduction of non-performing loans, and making correct provisions for them, plays a primary role in the management and minimization of banking credit risk. However, these actions depend primarily upon the cost at which banks may dispose of these bad loans. Hence, this study aims to perceive the price of banks’ credit risk via estimating the shadow price of non-performing loans. We assess and compare the perceived price of the credit risk of Islamic and conventional banks operating in 9 countries from the Middle East and Asia, using a quadratic directional distance function. Following this, we evaluate the impact of different settings of directional vectors on shadow prices by conducting a risk-sensitivity analysis. Applying bootstrap regression, the factors affecting NPLs’ prices are further investigated. The paper concludes that the estimation of the shadow prices of bad loans can provide important elements in favor of credit risk management and, therefore, credit risk mitigation.     

Environmental policies,national culture,and stock price crash risk: Evidence from renewable energy firms

This study investigates the impact of country‐level environmental performance and national culture on the stock price crash risk of renewable energy firms. Employing a large sample of 626 renewable energy firms across 31 countries, we find a significant nonlinear relationship between country‐level environmental performance and crash risk. National culture dimensions are found to strongly predict the crash risk of renewable energy firms, particularly after the global financial crisis. On the contrary, national culture dimensions and environmental policies are observed to not exert any significance in explaining the crash risk of fossil fuel firms. Our results are robust with respect to alternative measures of stock price crash risk and the endogeneity of national culture dimensions. Overall, the findings of this paper contribute to the environmental economics literature by providing new evidence regarding the role of societal and environmental factors in explaining the stock price crash risk of energy firms.