基于计算机信息集成技术的房产管理信息系统

基于计算机信息集成技术的房产管理信息系统是房管部门实现房产管理现代化的一种重要途径。这种系统不但具有房产信息管理的输入、查询、检索、修改、计算、统计等一般功能，而且在信息集成技术的支持下还可以实现信息的数据集中、网络共享、并行处理、数据完整等优点。本详细探讨了这种基于计算机信息集成技术的房产信息管理系统系统分析、系统设计以及系统实施等几个重要开发过程的设计思想和作业内容，对计算机信息集成技术的相关内容也进行了一定介绍。     

Quantitative easing and the loan to collateral value ratio

We study optimal monetary policy in a New Keynesian model at the zero bound interest rate where households use cash alongside house equity borrowing to conduct transactions. The amount of borrowing is limited by a collateral constraint. When either the loan to value ratio declines or house prices fall, we observe a decrease in the money multiplier. We argue that the central bank should respond to the fall in the money multiplier and therefore to the reduction in house prices or the loan to collateral value ratio. We also find that optimal monetary policy generates a large and persistent fall in the money multiplier in response to the drop in the loan to collateral value ratio.     

Free-play impact by customer segment

Little is known about the effectiveness of casino free-play campaigns, despite hundreds of millions of dollars in annual redemptions. These costly play incentives are awarded to individual players, based largely on management’s evaluation of their historical play. Extant campaign-level research suggests these incentives may not be effective in driving spend per visit, but there has been no attempt to examine efficacy across player tiers (e.g., light, medium, and heavy users). Analysis of 365 days of performance data from a Las Vegas Strip casino produced varied results across tiers, but all tier-level findings indicated a failure to recover the face value of the free-play incentives. While no support was garnered for the house money effect, the results were consistent with the notion of loss aversion. The methodological approach outlined herein provides the means to critically evaluate free-play offers at the tier level, fast-tracking campaign optimization via more targeted revisions.     

Forecasting using heterogeneous panels with cross-sectional dependence

In this paper, we focus on forecasting methods that use heterogeneous panels in the presence of cross-sectional dependence in terms of both spatial error dependence and common factors. We propose two main approaches to estimating the factor structure: a residuals-based approach, and an approach that uses a panel of auxiliary variables to extract the factors. Small sample properties of the proposed methods are investigated through Monte Carlo simulations and applied to predict house price inflation in OECD countries.     

Random mechanisms for house allocation with existing tenants

We study the house allocation problem with existing tenants: $n$ houses (stand for “indivisible objects”) are to be allocated to $n$ agents; each agent needs exactly one house and has strict preferences; $k$ houses are initially unowned; $k$ agents initially do not own houses; the remaining $n-k$ agents (the so-called “existing tenants”) initially own the remaining $n-k$ houses (each owns one). In this setting, we consider various randomized allocation rules under which voluntary participation of existing tenants is assured and the randomization procedure either treats agents equally or discriminates against some (or all) of the existing tenants. We obtain two equivalence results, which generalize the equivalence results in Abdulkadiroğlu and Sönmez (1999) and Sönmez and Ünver (2005).     

Business cycle implications of mortgage spreads

How do aggregate quantities at the business cycle frequency respond to shocks to the spread between residential mortgage rates and government bonds? Using a structural VAR approach, we find that mortgage spread shocks impact the real economy by both economically and statistically significant magnitudes: a 100 basis point decline in the spread causes a peak increase in consumption, residential investment and GDP by 1.6 percent, 6.2 percent and 1.9 percent, respectively. Presumably, these effects are magnified when the policy rate is held fixed, as was the case in the US during the recent implementation of unconventional monetary policy.     

关系型借贷视角下购房融资方式与家庭创业行为——基于2017年中国家庭金融调查的实证研究

本文利用2017年中国家庭金融调查数据深入考察购房融资方式对家庭创业行为的影响。研究结果显示,相较于民间借贷购房的家庭,按揭贷款购房的家庭参与创业活动的可能性更高,且更倾向于主动创业。进一步机制分析发现,相较于民间借贷购房,按揭贷款购房能够降低家庭的流动性约束,缓解家庭的资金压力,从而促进创业。同时,按揭贷款购房能使家庭获得充足的贷款额度与较长的贷款期限,进而有助于家庭创业。而且在偿还按揭贷款的过程中,家庭能与银行建立长期良好的信贷关系,从而有助于提高家庭获得正规信贷的可能性,促进家庭创业。为了积极推进创业创新的战略部署,应进一步健全银行信贷体系,发展和完善住房金融制度,从而有利于缓解小微企业融资难、融资贵的问题,释放和激发家庭创业活力。     

普惠保险发展的路径选择及其优化——基于小额保险的国际经验

保险“十三五”规划要求大力发展小额保险等普惠保险,但我国小额保险发展相对滞后,制约着普惠保险的全面发展。本文基于对印度等五国经营小额保险的经验研究,比照我国普惠保险发展实际情况,期望借此破解我国普惠保险发展困局,优化普惠保险发展路径。研究发现:我国普惠保险发展在政府推动力度、法律法规完善程度、政策支持力度及发展模式上均可进一步强化改善。结合国际经验和中国实践,我国普惠保险发展应重视法律法规等正式制度建设,顺应各地风俗文化等非正式制度,出台“小额保险条例”作为普惠保险的配套支持政策,利用合作代理销售模式和科技创新手段,控制普惠保险交易成本,开发符合消费者实际利益的普惠保险险种。     

城市居民住房承受能力测度研究——剩余收入视角

借鉴扩展线性支出系统模型确定家庭食品、衣着、家庭设备用品及服务等非住房基本消费支出的基础上,运用剩余收入法测度了2003—2008年武汉市七种不同类型家庭的住房承受能力。剩余收入法测度结果能反映出不同类型家庭住房承受能力的具体差距,显示出武汉市中等偏下收入及以下收入家庭面临住房承受能力问题,并且收入越低住房承受能力问题越突出,结果比传统比率法更具有说服力。而比率法测度显示中等偏上户及以下家庭面临住房承受能力问题,扩大了存在住房承受能力问题的家庭范围。运用剩余收入法可以定量地测度各类家庭住房承受能力的大小和绝对差距,有助于确定城市中低收入家庭住房补贴的对象及标准,制定我国公共住房销售、租赁政府指导价格,促进完善住房保障政策。     

The house price determination process: Rational expectations with a spatial context

Applying the rational expectations hypothesis, this essay models the current value of a house as the conditional expectation of the discounted stream of housing services accruing to the owner of the house. The value of housing services is determined by neighborhood effects as well as the physical attributes of the property itself. In the existing hedonic literature, future transactions have not been utilized to describe neighborhood effects. The rational expectations asset pricing model in this study accounts for expected future neighborhood effects as well as observed current neighborhood effects. The reduced form of the rational expectations model is a spatial autoregressive (SAR) model with two spatial lags. After employing the generalized method of moments (GMM) in estimating the spatial asset pricing model, I find that both expected future transactions and prior transactions in the neighborhood are significant. The inclusion of expected future transaction prices in the neighborhood takes into account the influence of expected changes in the community and factors these potential changes into the current house price. This is consistent with forward-looking households. The forward-looking model generates superior out-of-sample prediction performance relative to both the conventional hedonic model without considering neighborhood effects or the standard spatial hedonic model including only past transactions.