山东省房价与居民收入关系的实证研究

根据山东现有历史统计数据,通过运用判定房地产泡沫的方法与指标,分析山东房地产经济是否存在泡沫现象,并从总体上、不同收入阶层以及地域不同来解析山东房价与居民收入之间的关系,从而发现在山东房地产经济中存在的各种问题,得出初步结论:就山东房地产经济整体而言,当前并未出现房地产泡沫现象,但该行业存在着许多亟待解决的问题,并就此提出了政策性建议。     

校园包裹营销初探

随着高校不断扩招生源,毕业生包裹市场成为兵家必争之地。为提高邮政在校园包裹市场的占有率,文章从确立营销目标、拟定营销策略、准备工作及组织实施等方面介绍了佳木斯市邮政局开发校园包裹市场的经验。     

Partisan Social Happiness

We use a new approach to study questions in political economy that relies on data on the subjective well-being of a large sample of people living in the OECD over the period 1975{1992. Controlling for the personal characteristics of the respondents, year and country fixed effects and country-specific time trends, we find that the data describe social happiness functions for left-wing and right-wing individuals where inflation and unemployment enter negatively. We use these functions to test the root assumption of partisan business cycle models. The evidence is consistent with the hypothesis that left-wing individuals care more about unemployment relative to inflation than right-wingers. Interestingly, we find that individuals declare themselves to be happier when the party they support is in power, even after controlling for macroeconomic variables. The effect of politics is large. Finally, we find that these partisan differences cannot be traced back to income differences. That is, it is misleading to assume|as it is done in the previous literature|that the poor (rich) behave similarly to the left (right). For example, inflation and unemployment do not have differential effects across rich and poor and the happiness levels of these two groups are unaffected by the identity of the party in power. Our findings are hard to explain using median voter models but are to be expected in a partisan world.     

关于旅游住宅地产的十点提示

<正> 中国房地产业在经历了一系列风风雨雨的考验后,近年来顺应国民经济快速发展和人民生活迅速提高的需要,走进了强势增长的通道,走进了城市运营和泛地产时代,其中,旅游房地产成为最为关注的开发方向之一。我们有足够的理由相信,中国的旅游房地产开发具有广阔的前景,因为这个独特的开发方向已为市场所普遍认同。正是由于市场认同,越来越多的房地产商们在旅游房地产领域抢滩屯兵,跃跃欲试;也正是由于这种跃跃欲试的大量出现,促使我宁愿在一股热浪中给业界一点理性的提示,目的是希望中国旅游房地产发展得更加健康一些、规范一些、快速一些。     

基于GA-Elman动态回归神经网络的股价预测模型研究

文章针对股价预测问题的复杂性、不确定性、时变性及动态性等特性,利用Elman神经网络具有记忆性的优点,采用遗传算法训练优化Elman神经网络的初始权值,提出了高效的GA-Elman动态回归神经网络股价预测模型。实验模拟结果表明:该模型快速稳定且具有较高的精度,将其用于股票价格预测可行且有效。该模型的提出也为股票价格预测提供了一种新的技术和方法。