我国家庭信贷状况研究：基于CHFS微观数据的分析

文章利用中国家庭金融调查2013年发布的调查数据,分别构建非参数次序probit模型和Heckman模型检验了影响城乡家庭信贷约束状况和贷款可得性的相关因素。结果表明,户主受教育程度和家庭收入水平提高、家庭资产规模增加等都能缓解家庭的信贷约束,户主的党员身份、大学以上的受教育程度以及家庭资产规模等能提高家庭的贷款可得性,户主年龄、风险偏好等变量对家庭信贷规模的边际效应显著为负,而尽管城市家庭和东部地区家庭获得的贷款支持更多,但是城市家庭和东部地区家庭还是面临着更大信贷约束。     

应用ANSYS建立再生混凝土随机骨料模型的方法研究

通过对再生混凝土粗骨料成份的分析,初步提出将再生粗骨料大致分为以附着砂浆石子为主要成分并含有少量砂浆块和砖块杂质,并确定某批次再生粗骨料中各类骨料的百分含量。应用ANSYS的APDL参数化编程,结合蒙特卡罗方法和富勒级配理论,从细观层次上生成再生混凝土各类骨料的二维圆形与三维球形随机骨料模型,并赋予各类骨料的材料属性。然后根据选定的单元类型进行有限元网格的划分,通过判断各单元与骨料形心的位置关系来识别砂浆基质与骨料之间的界面单元,并赋予它相应的材料属性。从而建立起再生混凝土的数值模拟试件,为今后在ANSYS中直接对其进行加载求解,以此来模拟各种力学性能试验提供了必要的基础。     

Might randomization in queue discipline be useful when waiting cost is a concave function of waiting time?

This paper suggests that introducing randomization in queue discipline might be welfare enhancing in certain queues for which the cost of waiting is a concave function of waiting time. Concavity can make increased variability in waiting times good not bad for aggregate customer welfare. Such concavity may occur if the costs of waiting asymptotically approach some maximum or if the customer incurs a fixed cost if there is any wait at all. As examples, cost might asymptotically approach a maximum for patients seeking organ transplants who will not live beyond a certain threshold time, and fixed costs could pertain for knowledge workers seeking a piece of information that is required to proceed with their current task, so any delay creates a “set up charge” associated with switching tasks.     

基于随机需求的物流配送中心选址离散模型研究

针对物流需求不确定情况下的物流配送中心选址问题,对传统模型进行改进,将随机需求变量引入离散型选址模型,利用随机规划理论和遗传算法对实例模型进行求解。结果显示物流需求不确定情况下的随机规划模型的求解结果比假设已知需求情况下的结果真实可信,所需物流费用较少。     

经济全球化背景下我国外资准入困境与出路——以外商投资企业审批制度为视角

外商投资企业审批制度是我国外资准人的主要手段,从审批制开始实施至今,为我国有效吸引利用外资提供保障,也为我国经济的快速发展提供了帮助。但是经济全球化日益深入的今天,外商投资企业审批制度需要随我国经济发展的需要进行完善,笔者通过对外商投资企业审批制度的探讨,分析外资准入发展中的症结所在,并提出相应的建议,以期为我国创造更好的投资环境。     

Can Mobile Money Help Firms Mitigate the Problem of Access to Finance in Eastern sub-Saharan Africa?

ABSTRACT

Mobile money is a mobile-phone-based financial tool that can transfer money safely and quickly across a wide geographical area. Mobile money has transformed the way businesses in Eastern sub-Saharan Africa operate. Nowadays, banks team up with mobile-money-service providers and pay interest on deposits and grant loans based on financial transactions in mobile-money accounts. In this paper, these recent developments are investigated in order to determine whether the adoption of mobile money by firms can actually help them mitigate the vexing problem of access to finance. To answer this question, the World Bank’s Enterprise Surveys Program data set for the year 2013 is used, thus making the study applicable to the present time. The results obtained, after controlling for a large number of firm-level characteristics and using a newly introduced measure to identify access-to-finance status of the firms, indicate that firms which use mobile money are more likely to obtain loans or lines of credit. Further analysis shows that the firms that use mobile money are more productive than other firms in the region.     

A comparison of regret-based and utility-based discrete choice modelling – an empirical illustration with hospital bed choice

There is some concern that the unobserved preference heterogeneity in random utility maximization theory-based discrete choice experiment modelling is an important source of error variability. The randomness in utility is often interpreted as interpersonal preference heterogeneity but it can also be intrapersonal random variation in preferences. We compare utility maximization and regret minimization-based choice models’ sensitivity to individual heterogeneity, examine differences between two consecrated models and validate with empirical illustrations. We use frequency of category (public, semi-private, and private) of bed chosen from Swiss cross-sectional datasets (2007–2012) to compare two approaches – utility maximization and regret minimization by applying multinomial logit (MNL) models in regard to the variances in utility (regret) function, goodness-of-fit and predicted marginal effects (pseudo-elasticity) of additional payment. We find parameters with the same sign and estimates with almost same order of magnitude in both the approaches. The statistical significance of attribute effects is consistent in all variants of utility -based MNL models while effects of different attributes are significant only in heteroskedastic extreme value (HEV) variant of regret-based MNL models. This empirical illustration suggests that HEV variant of regret-based models perform better in capturing attribute effects in choice behaviour.     

An alternative approach for portfolio performance evaluation: enabling fund evaluation relative to peer group via Malkiel’s monkey

We propose an implementable portfolio performance evaluation procedure that compares a portfolio with respect to the portfolios constructed by an infinite number of Malkiel’s blindfolded monkeys, or equivalently the whole enumeration of all possible portfolios. We argue that this approach exhibits two main advantages. First, it does not require any benchmark portfolios because a portfolio is being compared to an infinite number of portfolios. Second, it is market condition invariant. Since the market conditions are already reflected in the portfolio performances of an infinite blindfolded monkeys, our measure of portfolio performances is invariant to volatile market conditions.     

Regional wages and market potential in the enlarged EU: an empirical investigation

This article empirically analyses the link between market potential and regional wages in the enlarged EU. We contribute to the existing literature in several ways: (1) we analyse the link between market potential and wages for the EU27 and (2) deconstruct total market potential into several geographical components and analyse their respective contributions to explaining the geographical wage structure. We correct for existing spatial autocorrelation and endogeneity by using an instrumental variable generalized spatial two-stage least squares (IV GS2SLS).     

Demystifying the Meese–Rogoff puzzle: structural breaks or measures of forecasting accuracy?

Structural breaks have been suggested by several economists as a possible explanation for the Meese–Rogoff puzzle, in the sense that an exchange rate model can outperform the random walk in terms of the out-of-sample forecasting error if the period under investigation is free of structural breaks. The results indicate that structural breaks cannot explain the inability of the flexible price monetary model to outperform the random walk. The only plausible explanation for the Meese–Rogoff puzzle is that forecasting accuracy is traditionally assessed by magnitude-only measures. When forecasting accuracy is assessed by alternative measures that do not rely exclusively on the magnitude of error, the monetary model can outperform the random walk regardless of the presence or otherwise of structural breaks.