Socially optimal replacement of conventional with electric vehicles for the US household fleet

In this study, a framework is proposed for minimizing the societal cost of replacing gas-powered household passenger cars with battery electric ones (BEVs). The societal cost consists of operational costs of heterogeneous driving patterns' cars, government investments for charging deployment, and monetized environmental externalities. The optimization framework determines the timeframe needed for conventional vehicles to be replaced with BEVs. It also determines the BEVs driving range during the planning timeframe, as well as the density of public chargers deployed on a linear transportation network over time. We leverage data sets that represent US household driving patterns, as well as the automobile and the energy markets, to apply the model. Results indicate that it takes 8 years for 80% of our conventional vehicle sample to be replaced with electric vehicles, under the base case scenario. The socially optimal all-electric driving range is 204 miles, with chargers placed every 172 miles on a linear corridor. All public chargers should be deployed at the beginning of the planning horizon to achieve greater savings over the years. Sensitivity analysis reveals that the timeframe for the socially optimal conversion of 80% of the sample varies from 6 to 12 years. The optimal decision variables are sensitive to battery pack and vehicle body cost, gasoline cost, the discount rate, and conventional vehicles' fuel economy. Faster conventional vehicle replacement is achieved when the gasoline cost increases, electricity cost decreases, and battery packs become cheaper over the years.     

高密度电法在地基塌陷区勘察中的应用

通过高密度电法快速采集地电断面结构信息，准确反映不良地质体的二维分布情况。为查明地基塌陷的诱发原因和地基处理提供了依据。通过实例证明该方法工作效率高、信息量大及在实际应用中的良好效果。     

环境心理感受与个人空间

通过拥挤、密度、个人空间与空间气泡、私密性四个方面简要地说明了人对环境特点的感情和姿态反应,对各种环境场所的接近或回避,以及如何适应环境等。     

ASYMPTOTIC BEHAVIOR OF DISTRIBUTION DENSITIES IN MODELS WITH STOCHASTIC VOLATILITY. I

We study the asymptotic behavior of distribution densities arising in stock price models with stochastic volatility. The main objects of our interest in the present paper are the density of time averages of a geometric Brownian motion and the density of the stock price process in the Hull–White model. We find explicit formulas for leading terms in asymptotic expansions of these densities and give error estimates. As an application of our results, sharp asymptotic formulas for the price of an Asian option are obtained.     

Do subjective expectations explain asset pricing puzzles?

The structural uncertainty model with Bayesian learning, advanced by Weitzman (AER 2007), provides a framework for gauging the effect of structural uncertainty on asset prices and risk premiums. This paper provides an operational version of this approach that incorporates realistic priors about consumption growth volatility, while guaranteeing finite asset pricing quantities. In contrast to the extant literature, the resulting asset pricing model with subjective expectations yields well-defined expected utility, finite moment generating function of the predictive distribution of consumption growth, and tractable expressions for equity premium and risk-free return. Our quantitative analysis reveals that explaining the historical equity premium and risk-free return, in the context of subjective expectations, requires implausible levels of structural uncertainty. Furthermore, these implausible prior beliefs result in consumption disaster probabilities that virtually coincide with those implied by more realistic priors. At the same time, the two sets of prior beliefs have diametrically opposite asset pricing implications.     

An analysis of snow options for ski resort establishments

This study proposes a pricing method for put options on snow level for tourism establishments operating in Palandoken ski resort in the east of Turkey. In the calculation of put prices historical densities and Edgeworth adjusted densities methods together with Alaton, Djehiche, and Stillberger (2002) method have been applied. The findings show that there may be significant differences in the prices calculated by the three different methods, hence enabling both parties, i.e. buyers and sellers, with bases in the negotiation process. As the study is primarily aimed at providing a framework for pricing put options on snow levels in general, it is expected that it would be of use not only for this particular ski resort but also for various ski resorts in the world.     

中国城乡有效经济增长的差异性分析

本文提出了有效经济增长的概念,构建了有效经济增长动态模型,利用该模型建立了超额人均收入等相关变量的测定方法。在此基础上分别测算我国城镇部门与农村部门有效经济增长的相关指标,并进行比较分析。结果发现,改革开放以来我国城镇部门有效经济增长无论从绝对量上还是增长速度上都明显高于、快于农村部门;城镇部门有效经济增长的减损量大于农村部门;而农村部门对有效经济增长的减损强度却大于城镇部门。因此,推动城市化且合理控制城市化进程的速度,是降低我国有效经济增长的减损强度,实现有效经济增长可持续性的有力途径。     

小麦粉中阿拉伯木聚糖含量与小麦籽粒之间的关系

本文研究了面粉中阿拉伯木聚糖（简写AX）含量与小麦籽粒特性之间的关系,研究结果表明：AX含量与硬度（r=0.049）、水分（r=0.048）呈微弱正相关;与容重呈显著负相关（r=-0.215）,因为AX主要存在于小麦籽粒面筋蛋白和淀粉之间,当它们之间的AX多时,面筋蛋白和淀粉的量就会减少,容重就会减少;面粉中的AX与不完善粒（r=0.146）、出粉率（r=0.155）呈正相关,因为在小麦籽粒中,麸皮中AX含量占小麦籽粒的30%左右,当出粉率增加,会使一小部分的麸星进入面粉,从而使面粉中的AX增加。     

我国寿险市场区域差异的空间经济计量分析

近年来,我国保险业呈现出显著的地区差异,本文以我国寿险市场的地区差异作为考察重点。基于2009年我国各省区寿险市场的截面数据,从空间计量经济学角度,采用Moran I指数以及Moran散点图考察我国寿险市场区域差异的空间特性。在此基础上,利用空间滞后模型结合空间误差模型实证分析导致空间格局差异的成因。     

Markov regime-switching Beta-t-EGARCH

We suggest a Markov regime-switching (MS) Beta-t-EGARCH (exponential generalized autoregressive conditional heteroscedasticity) model for U.S. stock returns. We compare the in-sample statistical performance of the MS Beta-t-EGARCH model with that of the single-regime Beta-t-EGARCH model. For both models we consider leverage effects for conditional volatility. We use data from the Standard Poor’s 500 (S&P 500) index and also a random sample that includes 50 components of the S&P 500. We study the outlier-discounting property of the single-regime Beta-t-EGARCH and MS Beta-t-EGARCH models. For the S&P 500, we show that for the MS Beta-t-EGARCH model extreme observations are discounted more for the low-volatility regime than for the high-volatility regime. The conditions of consistency and asymptotic normality of the maximum likelihood estimator are satisfied for both the single-regime and MS Beta-t-EGARCH models. All likelihood-based in-sample statistical performance metrics suggest that the MS Beta-t-EGARCH model is superior to the single-regime Beta-t-EGARCH model. We present an application to the out-of-sample density forecast performance of both models. The results show that the density forecast performance of the MS Beta-t-EGARCH model is superior to that of the single-regime Beta-t-EGARCH model.