流动性约束视角下我国房价财富效应与最优利率规则研究

后危机时代中国房价的波动引起了广泛关注,如何利用以货币政策为代表的宏观调控抑制高房价透支未来经济发展的程度,成为当前管理层高度关注的焦点。本文建立了新凯恩斯模型框架分析房价波动如何通过流动性约束影响消费,从而揭示了中央银行货币政策与房价的财富效应之间的关系,得出最优利率规则中房价的最优权重随预期通胀、产出缺口、房价和名义利率而变动的结论。通过实证分析本文进而认为,利率规则比货币供应量更能迅速调控房价的增长和居民消费的扩张。中国房价上涨的财富效应虽然比较明显,但流动性约束的作用机制需要一个过程才能显现,利率调控的效果也有一个量变到质变的过程,从而在理论上为中央银行制定应对房价的利率政策提供了一定启示。     

Factors influencing the user acceptance of digital home services

Digital home services provide multimedia entertainment, communication, and healthcare services to the public in order to make their lives more convenient. Many articles predict that the digital home service market will be huge and that many will take advantage of this situation. The purpose of this paper is to identify the future market for digital home services in South Korea by exploring the existing critical information and literature. This study proposes a conceptual model for assessing the adoption of digital home services, for which survey data from 600 heads of households in Korea were collected and used to test the proposed model. This paper also examines customer characteristics and their relationship with the acceptance of digital home services. First, the findings indicate that infra-service is mainly determined by age, region, job, family type, house type, and attitude towards adoption of new products. Second, home entertainment service is also significantly affected by gender, age, region, family type, family member, house type, and attitude towards adoption of new products. Third, home healthcare service was positively affected by gender, region, job, and usage period of high-speed internet. This study may provide companies with valuable guidelines for the implementation of digital home services.     

学区房溢价的影响因素:教育质量的视角

优质教育资源可能形成于学校的教育质量,也可能来源于生源质量。房地产的市场化定价机制为探讨优质教育资源的背后形成机制提供了便利。本文利用北京市二手房成交数据,采用特征价格模型和边界固定效应法,估算了学区房溢价。在此基础上,利用学校层面的教育质量信息,探讨了教育质量对学区房溢价的解释力。实证结果表明,以学校物质资本和教师人力资本所表征的教育质量是学区房溢价,即优质教育资源的主要来源,解释了总体学区房溢价的64.71%,这种解释力在考虑了潜在的内生性问题后依旧稳健。进一步通过量化北京市的三个教育强区(西城区、东城区和海淀区)中教育质量的解释力,发现优质教育资源既可形成于优质生源集聚,也可形成于教育经费投入长期累积所带来的教育质量的提升。义务教育均衡化改革,推动优质公共投入的公平供给,是平抑高企的学区房价格的有效手段。     

Forecasting state- and MSA-level housing returns of the US: The role of mortgage default risks

We analyze the ability of an index of mortgage default risks (MDRI) for 43 states and 20 metropolitan statistical areas (MSA) of the US derived from Google search queries, in predicting (in- and out-of-sample) housing returns of the corresponding states and MSAs, based on various panel data and time-series approaches. In general, our results tend to prefer the panel data model based on common correlated effects estimation. We highlight that growth in MDRI negatively impacts housing returns within-sample, with predictive gains primarily concentrated beyond a year. These results are robust to alternative out-of-sample periods and econometric frameworks. Given the role of house prices as a leading indicators, our results are of value to policymakers, especially at the longer-run.     

房产税改革对城市房价的影响 ——以上海市为例

从2003年以来,中国许多城市的房价一直在快速上涨。近几年,中央与地方采取了一系列房价调控政策,以控制我国房价直线上涨的情况。2011年1月,房产税试点改革政策首次在上海市和重庆市颁布,在试点城市采取调整税收的方式控制房价。基于2011—2017年上海市住宅商品房平均售价与地方财政房产税的数据,设定线性回归模型,使用普通最小二乘法(OLS)估计征收房产税对城市房价的影响,提出了应扩大房产税征收范围、设置科学的房产税税率、加快政府保障性住房建设、建立健全购房机制等政策建议。     

房价预期与城镇居民家庭股市参与——理论探讨与微观经验证据

本文基于中国家庭金融调查数据,通过构建理论模型和实证检验分析了房价预期与家庭股市参与的关系,考察了行为金融偏差在房价预期影响股市参与过程中的作用,并根据背景风险、社会网络和户主特征进行异质性分析。结果表明:(1)房价上涨预期通过降低居民家庭的股票收益率预期和增加住房资产,进而降低居民家庭的股市参与概率和参与程度;(2)“心理账户”以及“有限关注”的存在显著弱化了房价上涨预期对家庭股市参与的负向作用;(3)房价上涨预期对股市参与概率和参与程度的负向作用在收入风险更高、健康状况更差、社会网络水平较低以及受教育程度偏低的家庭中更大。因此,稳定房价预期能够通过提升家庭股市参与,进而从需求角度促进股票市场的健康发展。     

资产财富和居民消费——来自中国省际面板数据的经验证据

随着"双循环"发展战略的提出，如何提升我国居民消费成为研究热点。与已有研究不同，文章首先从省际视角研究了居民消费行为的影响因素，证实了金融资产和住房资产分别对消费产生的促进作用和抑制作用，且金融资产的促进作用大于住房资产的抑制作用。其次，文章探讨了两种资产对不同种类消费品的影响，金融资产增加主要促进教育娱乐医疗等改善性消费，住房资产增加则主要抑制基本品消费。最后，文章对不同省份居民消费的影响因素进行异质性分析，发现金融资产对消费的促进作用随收入、资产增加先上升后下降，而住房资产对消费的抑制作用随收入、资产增加先上升后下降，金融资产和住房资产在东部地区影响小于西部地区，且受区域教育、人口和收入结构影响。综上来看，提升居民收入水平，改善居民收入结构，控制房价过度上涨，改善资本市场在资产分配中的作用，加大政府在教育、医疗、养老等公共服务方面的投入能够有效改善家庭资产结构，提升居民消费水平。     

Housing prices and macroprudential policies: Evidence from microdata

This paper examines the efficacy of macroprudential policies in addressing housing prices in a developing country like India, utilizing two novel databases on city-level house prices in India. Though the empirical models provide evidence of a sizable effect of the fundamental factors in influencing house price dynamics, they also reveal strong countercyclical properties of macroprudential tools i.e., loan-to-value (LTV) limit, risk weights, and provisioning requirements, in influencing housing price movements. Among the macroprudential policy tools, the LTV limit emerges as the most potent one in influencing the price dynamics. A granular investigation of the effectiveness of macroprudential tools suggests that the countercyclical effect of the regulatory ratios for large-sized mortgages is much stronger as compared with those for the small-sized mortgages, attributed mainly to investment motives associated with the large-sized loans. We also find the presence of asymmetry in the impact of loosening versus the tightening of the LTV limit, which can be attributed to the procyclical behavior of the house prices.     

Yield curve and the macroeconomy: Evidence from a DSGE model with housing

The slope of the yield curve has long been found to be a useful predictor of future economic activities, but the relationship is unstable. One change we have identified in this paper is that, between the early 1990s and the collapse of the housing market in 2007, movements at the long end of the yield curve have an increase in predictive power. We use a medium-scale DSGE model with a housing sector and a yield curve as a guide to find out the sources of such change. The model implies that an increase in the short-term interest rate and a decrease in the long-term interest rate have different impacts on the economy, and to use the slope as a predictor one needs to distinguish movements at the two ends of the yield curve. Based on simulated data from the model, we find that nominal wage rigidities and the capital adjustment costs are closely related to the predictive power of the yield curve. This result is further confirmed with actual data.     

A re-examination of housing bubbles: Evidence from European countries

This study uses data from six Eurozone countries and the United Kingdom between 1980Q1 and 2018Q4 to examine whether these countries had housing bubbles during the observed period. Whereas typical studies make strictly limited assumptions regarding interest rates, we make an unconventional argument for the necessity of testing the integration relationship between the price–rent ratio and the interest rate reciprocal to determine the existence of housing bubbles. To verify this study’s proposition, two housing bubble indicators were adopted to dynamically examine periods of housing bubbles in European countries by using a series of individual countries and panel data from Eurozone countries. According to the empirical results for individual countries, although the price–rent ratio indicates the occurrence of housing booms in the targeted countries, the evidence for housing bubbles is unclear. The dynamic bubble indicator revealed that housing bubbles occurred in France and Ireland within a short period in 1993Q3 and 2000Q2, respectively. Spain experienced two short-term housing bubbles in 1990Q1 and 2015Q1. The short-term bubbles signify that the housing markets were efficient. Once the price–rent ratio failed to converge toward the nominal interest rate, market traders’ rational behavior can immediately correct the short-term market divergence. The panel data of the Eurozone countries also reveals that simply using the price–rent ratio for examination may underestimate the correction of the housing markets. In conclusion, the results of this study demonstrate the importance of the interest rate in controlling the housing market.