不同人群对养老模式选择的经济分析

社会结构的变迁使传统的家庭养老失去支持系统,多元化的养老模式是社会发展的必然结果。文章探讨了不同人群对养老模式选择,并建立三元选择模型分析不同特征的影响。研究结果显示女性、受教育程度低和家庭子女数较多的人偏向于家庭养老,男性、收入较高的人较倾向于独立养老,而受教育程度较高年轻一代和低收入的人群对集体社区养老模式的接受程度较高。未来的养老趋势为经济上对后代依赖的减弱,生活照顾和精神慰藉的依赖仍很强。     

农村电网最优电压组合方案的研究

电网的经济技术指标是选择最优电压组合的重要依据。因此，如何科学地计算出不同电压组合的待建农村电网的相关经济技术指标，就成为研究此类问题的关键所在。提出一个基于统计数据，辅以《农村电力网规划设计导则》的电网模型来研究经济技术指标。该模型是出线、变电站容量和导线截面都随负荷密度变化而变化的动态模型。该方法避免了采用固定值建立适应性差的模型，使模型更加合理、更加符合实际情况。实例证明该方法是有效和可行的。     

我国食品价格对非食品价格的传导效应——基于VAR模型的实证分析

近年来,我国食品通胀率持续上涨,而非食品通胀率也呈现出不断增长的趋势,由此引发了社会的广泛关注,本文实证研究了食品通胀对非食品通胀的传导效应.结果表明：1）非食品价格和食品价格之间存在相互影响的双向因果关系;2）食品价格的上涨会对非食品价格产生正向冲击,且这种冲击有一定的时滞性,非食品价格受到食品价格冲击的影响比较明显;3）平均来看,2007年1月-2012年12月,食品价格冲击对非食品价格的变动有明显解释力,但非食品价格的变动主要由其自身冲击造成.     

PhenologyMMS: A program to simulate crop phenological responses to water stress

Crop phenology is fundamental for understanding crop growth and development, and increasingly influences many agricultural management practices. Water deficits are one environmental factor that can influence crop phenology through shortening or lengthening the developmental phase, yet the phenological responses to water deficits have rarely been quantified. The objective of this paper is to provide an overview of a decision support technology software tool, PhenologyMMS V1.2, developed to simulate the phenology of various crops for varying levels of soil water. The program is intended to be simple to use, requires minimal information for calibration, and can be incorporated into other crop simulation models. It consists of a Java interface connected to FORTRAN science modules to simulate phenological responses. The complete developmental sequence of the shoot apex correlated with phenological events, and the response to soil water availability for winter and spring wheat (Triticum aestivum L.), winter and spring barley (Hordeum vulgare L.), corn (Zea mays L.), sorghum (Sorghum bicolor L.), proso millet (Panicum milaceum L.), hay/foxtail millet [Setaria italica (L.) P. Beauv.], and sunflower (Helianthus annus L.) were created based on experimental data and the literature. Model evaluation consisted of testing algorithms using “generic” default phenology parameters for wheat (i.e., no calibration for specific cultivars was used) for a variety of field experiments to predict developmental events. Results demonstrated that the program has general applicability for predicting crop phenology and can aid in crop management.     

Improving cereal yield forecasts in Europe – The impact of weather extremes

The impact of extreme events (such as prolonged droughts, heat waves, cold shocks and frost) is poorly represented by most of the existing yield forecasting systems. Two new model-based approaches that account for the impact of extreme weather events on crop production are presented as a way to improve yield forecasts, both based on the Crop Growth Monitoring System (CGMS) of the European Commission. A first approach includes simple relations – consistent with the degree of complexity of the most generic crop simulators – to explicitly model the impact of these events on leaf development and yield formation. A second approach is a hybrid system which adds selected agro-climatic indicators (accounting for drought and cold/heat stress) to the previous one. The new proposed methods, together with the CGMS-standard approach and a system exclusively based on selected agro-climatic indicators, were evaluated in a comparative fashion for their forecasting reliability. The four systems were assessed for the main micro- and macro-thermal cereal crops grown in highly productive European countries. The workflow included the statistical post-processing of model outputs aggregated at national level with historical series (1995–2013) of official yields, followed by a cross-validation for forecasting events triggered at flowering, maturity and at an intermediate stage. With the system based on agro-climatic indicators, satisfactory performances were limited to microthermal crops grown in Mediterranean environments (i.e. crop production systems mainly driven by rainfall distribution). Compared to CGMS-standard system, the newly proposed approaches increased the forecasting reliability in 94% of the combinations crop × country × forecasting moment. In particular, the explicit simulation of the impact of extreme events explained a large part of the inter-annual variability (up to +44% for spring barley in Poland), while the addition of agro-climatic indicators to the workflow mostly added accuracy to an already satisfactory forecasting system.