An application of two-stage quantile regression to insurance ratemaking

Two-part models based on generalized linear models are widely used in insurance rate-making for predicting the expected loss. This paper explores an alternative method based on quantile regression which provides more information about the loss distribution and can be also used for insurance underwriting. Quantile regression allows estimating the aggregate claim cost quantiles of a policy given a number of covariates. To do so, a first stage is required, which involves fitting a logistic regression to estimate, for every policy, the probability of submitting at least one claim. The proposed methodology is illustrated using a portfolio of car insurance policies. This application shows that the results of the quantile regression are highly dependent on the claim probability estimates. The paper also examines an application of quantile regression to premium safety loading calculation, the so-called Quantile Premium Principle (QPP). We propose a premium calculation based on quantile regression which inherits the good properties of the quantiles. Using the same insurance portfolio data-set, we find that the QPP captures the riskiness of the policies better than the expected value premium principle.     

基于水权交易和面源污染控制的农户灌溉施肥行为模型

将水权交易和面源污染控制有机结合,以种植面积、农业用水定额、污染物浓度为约束条件,运用边际分析方法建立农户灌溉施肥行为模型,分析水权交易和排污控制对农户行为的影响。结果表明:灌溉用水量与农作物价格成正相关,与交易水价和边际灌溉成本成负相关;一定范围内肥料施用量与农作物价格成正相关,与边际施肥成本或边际环境成本成负相关。模型证明,当农业用水定额内水权可交易时,水市场的存在和水价政策将激励农户减少灌水量,节约用水。     

基于SARIMA-SVR组合模型的 空气质量指数预测

空气质量指数(AQI)在波动中既具有整体的时间序列线性特征和明显的季节性波动周期,又具有多种因素影响的不确定性,为了提高AQI的预测精度,基于Ri386 3.3.3和Matlab R2014a两种编程软件,提出了一种同时具有线性和非线性的复合特征的时间序列预测模型——SARIMA-SVR组合模型。以太原市2014年1月—2019年7月的AQI月均值数据为基础,利用SARIMA时间序列模型进行线性预测,利用SVR模型对残差进行非线性预测,加和得到组合预测模型的预测结果,分析比较SARIMA,SVR和SARIMA-SVR这3种模型的预测结果和平均绝对百分比误差。结果表明,组合预测模型发挥了2种模型各自的优势,相较于单一预测模型的预测结果而言,其预测精度更高,稳定性更好。通过此模型得到的空气质量预测结果不仅可为人们的日常生活提供指导,而且可为大气污染的防治工作提供科学依据和借鉴意义。     

Non-linear Gaussian sovereign CDS pricing models

Prior literature indicates that quadratic models and the Black–Karasinski model are very promising for CDS pricing. This paper extends these models and the Black [J. Finance 1995, 50, 1371–1376] model for pricing sovereign CDS’s. For all 10 sovereigns in the sample quadratic models best fit CDS spreads in-sample, and a four factor quadratic model can account for the joint effects on CDS spreads of default risk, default loss risk and liquidity risk with no restriction to factors correlation. Liquidity risk appears to affect sovereign CDS spreads. However, quadratic models tend to over-fit some CDS maturities at the expense of other maturities, while the BK model is particularly immune from this tendency. The Black model seems preferable because its out-of-sample performance in the time series dimension is the best.     

基于DEA模型的建筑业环境行为效率评价研究

对建筑企业进行环境行为效率评价是促进我国建筑行业健康可持续发展的重要手段。根据建筑行业特点及我国现有的企业环境信用标准,构建了建筑企业环境行为评价的投入产出指标体系,将改进的数据包络分析方法模型运用到企业环境行为效率评价领域,解决了现有企业评价研究主观性突出的问题,得出建筑企业评价分析方法。在此基础上对某代表性建筑企业2010—2017年环境行为数据进行了评价分析。分析结果表明该企业环境行为总体效率良好,但鉴于出现了奇数年和偶数年的效率波动情况,仍需提高环境行为效率。     

A Statistical Model to Investigate the Reproducibility Rate Based on Replication Experiments

The reproducibility crisis, that is, the fact that many scientific results are difficult to replicate, pointing to their unreliability or falsehood, is a hot topic in the recent scientific literature, and statistical methodologies, testing procedures and p‐values, in particular, are at the centre of the debate. Assessment of the extent of the problem–the reproducibility rate or the false discovery rate–and the role of contributing factors are still an open problem. Replication experiments, that is, systematic replications of existing results, may offer relevant information on these issues. We propose a statistical model to deal with such information, in particular to estimate the reproducibility rate and the effect of some study characteristics on its reliability. We analyse data from a recent replication experiment in psychology finding a reproducibility rate broadly coherent with other assessments from the same experiment. Our results also confirm the expected role of some contributing factor (unexpectedness of the result and room for bias) while they suggest that the similarity between original study and the replica is not so relevant, thus mitigating some criticism directed to replication experiments.     

Plausible versus implausible tensile price claim: Selective accessibility model approach

Retailers frequently use exaggerated price discount advertisements with a tensile price claim (TPC; e.g., “Save up to 70%”) to attract consumers because they expect that once consumers enter a store, they will purchase low‐ or medium‐discounted products. Drawing on the selective accessibility model, this study investigated the way in which an implausibly high maximum level of savings stated in a TPC influences consumers’ expected price discount (EPD) and perceptions of actual price discounts across different types of TPCs (i.e., TPC stating a maximum level and TPC stating a range of savings). This study also investigated two situations in which consumers have previous knowledge of a product’s price discount versus when they have less or no knowledge of the discount. For both conditions, a single‐anchor TPC (i.e., “Save up to Y%”) that stated an implausible maximum level of savings led to a higher EPD and lower perceptions of the deal (i.e., perceived savings, price fairness, and perceived value) with respect to the actual price discount than did a TPC with a plausible maximum level of savings. In contrast, when the TPC stated two anchors (i.e., “Save X–Y%”) and consumers had knowledge of the price discount, their EPDs assimilated only toward the plausible anchor (X), and ignored the implausibly high maximum price discount (Y), resulting in a lower EPD and higher perceptions of the deal of the actual price discounts than a TPC that stated a plausibly high maximum level of savings. In contrast, when consumers had no knowledge of the price discount, their EPDs only adjusted toward the more plausible anchor (X), regardless of whether they perceived the maximum anchor as plausible or implausible. Thus, there was no difference in consumers’ perceptions of “Save X–Y%” between implausibly and plausibly high Y%.     

Trade-threshold Effect on Inflation in Tunisia: New Evidence Resulting from a Nonlinear Approach

Trade openness is an important determinant of the inflation process. The effect of trade openness on inflation, however, is still an issue of debate at both theoretical and empirical levels. This study tried to provide a contribution to the literature by examining the relationship between inflation and trade openness in Tunisia over the period 1975Q1-2015Q4 using a nonlinear model. The originality of this study stems from the fact that it is the first investigation considering both the Residual-Based Tests for Cointegration in Models with the Regime Shifts and Threshold Regression model. The linear model confirms the existence of a positive relationship between inflation and trade in Tunisia. Yet, considering the nonlinear model, trade openness growth and Consumer Price Index (CPI) inflation growth show a statistically significant negative link as long as the trade openness evolution does not exceed the threshold. Nevertheless, if the trade openness growth is higher than the threshold, integrating the trade positively affects CPI inflation. Furthermore, a positive influence of Money supply growth on this type of inflation was noticed in Tunisia in all the considered regimes proving the effect of monetary factors on inflation level. Consequently, trade openness could be used to control inflation in Tunisia.     

The Impact of Public Expenditure and International Trade on Agricultural Productivity in China

The “industry nurturing agriculture” reforms and World Trade Organization accession led to dramatic growth in public expenditure and international trade in China’s agricultural sector. This article aims to estimate the effects of public expenditure and trade on agricultural productivity in China for 2004–2015. A semi-parametric production function with shape constraints is introduced to derive more accurate productivity before the productivity determinants are analyzed with an emphasis on public expenditure and trade. The empirical result shows that public expenditure and exports can effectively improve agricultural productivity, while imports have no significant effects. Policy implications are discussed in the context of supply-side reforms.     

利用信道状态信息的室内定位技术

多径效应导致基于信号接收强度（RSSI）的室内定位方法精度不高，采用更细粒度的物理层信道状态信息（CSI）可以区分不同路径，提高定位精度。在已有基于CSI室内定位方法的基础上，通过改进对数距离路径损耗模型，得到CSI与传输距离的关系，并结合目标位置所测得的CSI值回归出目标与发射端的距离，最后通过三边定位法预测出目标的位置坐标。实验表明，相比基于RSSI的定位方法以及已有的基于CSI的定位方法，所提方法2 m以内的误差概率提高了将近40%和20%，有效提高了定位精度。