房价对我国财富差距影响的作用机理

近年来,我国房地产价格不断增长,尤其是北上广为首的一些大中城市,房价居高不下,成为人们普遍关注的难题.世界上,通常运用基尼系数作为评估贫富差距的尺度,然而在某种程度上,基尼系数仅能反馈收入差距,不能笼统地代表贫富差距的实际情况.因为贫富差距通常是收入差距和财产差距两部分组成的,而收入差距是即时性的,可以用收入的基尼系数衡量,财富差距却是个积累性的量,衡量起来或多或少存在一些困难.本文将在叙述收入差距与财富差距叠加现状的基础上,进一步剖析高房价与贫富差距间的作用机制,同时提出一系列有效的对策方法.     

房价收入比与家庭消费——基于房产财富效应的视角

运用中国家庭金融调查(CHFS)2011年、2013年和2015年数据,基于调查数据构建和计算城市房价收入比,分析房价收入比对家庭消费房产财富效应的影响,并进一步考察房价收入比对拥有两套及以上住房、有房出租、拥有大小产权房和不同收入阶层家庭消费房产财富效应的影响差异。研究发现:房价收入比高时家庭消费水平也相应较高,但房价收入比高却显著降低了家庭消费的房产财富弹性;拥有两套及以上住房、有房出租家庭消费的房产财富效应受房价收入比高的弱化影响更小,拥有大产权比小产权房更能抵御房价收入比高对消费房产财富效应的弱化影响,高收入家庭的抵御能力更强。     

中国住房抵押贷款拖欠风险研究

本文使用中国某主要商业银行2004年4月至2009年5月发放的大样本房贷数据考察了房贷拖欠和违约风险决定因素及其区域差异。研究发现:(1)房价余额比(PTB)显著影响房贷拖欠风险,但债务收入比(DTI)不显著,这表明借款人通常因权益为负而非负担不起而违约。(2)房价只对1个月房贷拖欠具有显著负影响,贷款余额对所有房贷拖欠和违约风险具有显著正影响,而收入和月供无显著影响。据此,商业银行应加强对大额房贷违约风险的管理。(3)房价增长率对所有房贷拖欠和违约风险具有显著负影响,而收入增长率只对1个月拖欠风险具有显著负影响。因此,只要房价和收入保持增长,房贷拖欠和违约风险将下降。(4)房贷拖欠风险具有明显的城市差异。因此,地理位置多样化有助于降低房贷拖欠和违约风险。(5)二手房房贷比一手房房贷具有更高的拖欠和违约风险,商业银行应加强二手房房贷的拖欠和违约风险管理。     

收入差距对我国房地产财富效应的影响

该文使用1999年以来北京、上海、广州和深圳等房地产一线城市不同收入等级居民生活水平的面板数据,运用协整分析法检验收入差距因素对房地产财富效应的影响。实证结果表明,高收入家庭存在正的财富效应,中、低收入家庭表现为负的财富效应,整体表现为负的财富效应。对此,我国必须加快改变目前房地产业在国民经济中的支柱地位,真正控制房价上涨,避免房地产市场带来负面的财富效应。     

共同富裕视域下遗产税制度设计研究——基于蒙特卡洛模拟的测算

遗产税作为直接税体系的组成部分,可以有效调节社会收入和财富分配,设计合理的遗产税制度方案对推进共同富裕具有重要的理论价值和现实意义。本文基于2019年中国家庭金融调查数据,利用蒙特卡洛模型模拟了10年间的遗产继承,以及不同遗产税方案设计对财富基尼系数的影响。研究结果显示,从长期来看,遗产税可以有效缩小贫富差距,且征税时间越长,效果越明显。在共同富裕目标下,中国遗产税免征额不应低于400万元,采用超额累进税率、提高税率标准和细化税率级次也有助于降低财富基尼系数。同时,遗产税制度设计还要统筹考虑保护实体经济和中等收入群体等问题,充分思索其对促进第三次分配的作用。     

中国贫富差距扩大化的演化脉络与机制分析

自改革开放以来,中国贫富差距扩大,似乎与"共同富裕"相悖。而实现全国贫富差距缩小的目标,首先有必要研究中国贫富差距扩大化的演化脉络。其次对贫富差距扩大化的发展进行机制分析,并进行模型构建,研究表明工人知识独占性以及技术变革会扩大工资差异,进而扩大收入差距,最终扩大贫富差距。最后,利用统计软件结合时间序列模型进行实证研究,选取与贫富差距相关的四个指标,即基尼系数、城镇居民人均可支配收入、农村居民消费价格指数和东部城镇居民人均可支配收入,得到了四项指标存在长期稳定的均衡关系,同时城镇居民人均可支配收入、农村居民消费价格指数和东部城镇居民人均可支配收入都存在基尼系数的格兰杰因果关系,城镇居民人均可支配收入和东部城镇居民人均可支配收入对基尼系数具有负作用,而对农村居民消费价格指数却是正作用的结论。     

房价、房价收入比对中国城镇化的影响与空间效应实证分析

利用2005—2019年我国31省面板数据,基于三种权重矩阵构建空间滞后模型和空间误差模型,分析房价、房价收入比对城镇化的影响。结果表明:(1)房价、房价收入比与三种城镇化的空间自相关和空间依赖性显著,并存在空间溢出效应和"马太效应"。(2)房价对人口城镇化、经济城镇化与土地城镇化的正向影响作用显著,房价对人口城镇化的影响呈现倒"U"型,但房价对经济城镇化和土地城镇化的影响是线性的。(3)房价收入比对人口城镇化的影响为正,房价收入比对经济城镇化与土地城镇化的影响呈倒"U"型。(4)从区域看,东部和中部房价上涨对人口城镇化的影响为正,西部为负;中部房价收入比对人口城镇化的影响不显著,西部为正,东部为负;中西部人口城镇化溢出效应最大。     

收入差距、挤出效应与高房价

本文考察了收入差距的扩大对城市房价的影响。研究表明,收入差距的扩大在微观上通过挤出效应、在宏观上通过储蓄率的上升引发过度住房投资,助长了房价。无论是用基尼系数表征的收入差距,还是用高收入阶层所占总收入的比例表征的收入差距,在经验分析上都与高房价高度正相关。这意味着改善收入分配或通过各种手段限制高收入者的住房投资需求应成为房地产调控的政策选择。     

我国经济格局与收入差距演变关系探讨

对区位基尼系数和收入基尼系数的计算方法讨论后,利用区位基尼系数考查了近年来我国大陆地区经济活动空间格局的变化状况；探讨了混合样本总体收入基尼系数的计算方法,并据此分析了2002-2010年我国收入差距的演变特征.研究发现,2006年前区位基尼系数单调上升,2006年后区位基尼系数单调下降,说明近年我国经济活动集聚与扩散的拐点出现在2006年；而在2002-2010年收入基尼系数表现出波动上升的特征.研究认为,我国经济格局变化对收入差距演变产生滞后影响,相比于区域经济差距问题,缓解收入差距扩大显得更加紧迫.     

住房价格不平衡对我国财富分布格局的影响研究

规范财富积累机制对我国分阶段推进共同富裕和实现经济高质量发展具有重要意义。通过分析房屋财富差异影响家庭财富不平等的典型事实，基于房价上涨、房屋财富升值与财富不平等程度加剧的理论逻辑并利用2011—2019年中国家庭金融调查（CHFS）数据的研究结果表明，住房价格不平衡将会加剧同类型家庭内部、不同类型家庭之间的财富不平等程度，严重恶化我国财富分布格局。家庭财富积累动机与房价水平的双重差异是造成同类型家庭内部财富不平等的核心因素，房价上涨的财富效应与房价水平的双重差异是导致不同类型家庭之间财富分化的关键成因。数值模拟显示，降低收入差距与城乡差距、缓解财富顶层集中、有效管控住房投资行为、切实降低消费性住房购买压力等措施，对我国规范收入分配秩序和财富积累机制、改善财富分布格局具有积极意义。     

房价对居民消费的跨空间影响*——基于中国278个城市空间面板数据的实证研究

本文首先基于住房财富效应，构建了房价变动对居民消费的跨空间影响的分析框架。该框架阐释了住房财富效应的区域差异：不同地区间房价的空间传导、居民的异地消费以及消费的示范效应，使得本地房价变动可能引起周边地区居民消费的连锁反应。其后，本文利用中国278个地级市2000—2018年数据，通过空间面板杜宾模型，实证考察了不同地区住房财富效应的差异，以及房价变动对居民消费的跨空间影响。结果显示：（1）虽然中国整体上存在住房财富效应，但西部城市财富效应并不显著，并且核心城市还存在负财富效应。（2）不同城市间房价对消费存在跨区影响。东部城市和核心城市对周边城市消费的正向影响很显著，而边缘城市则对周边城市消费有显著的负向影响。（3）不同城市间的消费也具有空间上的示范效应。最后，本文从房价和居民消费空间联动的视角，为政府扩大内需、调控房地产市场提供了相关政策建议。     

房价对居民消费的跨空间影响*——基于中国278个城市空间面板数据的实证研究

本文首先基于住房财富效应,构建了房价变动对居民消费的跨空间影响的分析框架。该框架阐释了住房财富效应的区域差异：不同地区间房价的空间传导、居民的异地消费以及消费的示范效应,使得本地房价变动可能引起周边地区居民消费的连锁反应。其后,本文利用中国278个地级市2000—2018年数据,通过空间面板杜宾模型,实证考察了不同地区住房财富效应的差异,以及房价变动对居民消费的跨空间影响。结果显示：（1）虽然中国整体上存在住房财富效应,但西部城市财富效应并不显著,并且核心城市还存在负财富效应。（2）不同城市间房价对消费存在跨区影响。东部城市和核心城市对周边城市消费的正向影响很显著,而边缘城市则对周边城市消费有显著的负向影响。（3）不同城市间的消费也具有空间上的示范效应。最后,本文从房价和居民消费空间联动的视角,为政府扩大内需、调控房地产市场提供了相关政策建议。     

Housing Prices in Urban China as Determined by Demand and Supply

This paper studies the demand for and supply of residential housing in urban China since the late 1980s when the urban housing market became commercialized. Using aggregated annual data from 1987 to 2012 in a simultaneous equations framework we show that the rapid increase in the urban residential housing price can be well explained by the forces of demand and supply, with income determining demand and cost of construction affecting supply. We find the income elasticity of demand for urban housing to be approximately 1, the price elasticity of demand to be approximately ?1.1 and the price elasticity of supply of the total housing stock to be approximately 0.5. The resulting long‐run effect of income on urban housing prices in elasticity terms is approximately 0.7, because the increase in income has shifted the demand curve outward more rapidly than the supply curve.     

TRENDS IN HOUSEHOLD WEALTH IN THE UNITED STATES, 1962–83 AND 1983–89

Using the 1983 and 1989 Surveys of Consumer Finances, I find evidence of sharply increasing house-hold wealth inequality over this period. Whereas mean wealth increased by 23 percent in real terms, median wealth grew by only 8 percent. The share of the top one-half percentile rose by five percentage points, while the wealth of the bottom two quintiles showed an absolute decline. The Gini coefficient increased from 0.80 to 0.84. Almost all the growth in real wealth accrued to the top 20 percent of wealthholders. In contrast, the degree of wealth inequality was almost identical in 1983 as in 1962, and real wealth growth was more evenly distributed across the wealth distribution. There is also evidence that the sharp increase in wealth inequality from 1983 to 1989 was due to a correspondingly sharp rise in income inequality, the increase of stock prices relative to housing prices, and relatively slow inflation.     

How large is income inequality in China: assessment on different estimates of Gini coefficient

The rising income inequality in China has attracted social attentions, especially since SWUFE published the unbelievably high Gini coefficient in December 2012. In order to answer the question how large income inequality in current China is, this paper compares existing different Gini coefficients estimated from four different household surveys, which are the NBS household survey, the CHIP survey, the CHFS of SWUFE, and the CFPS of Peking University, and then assesses these household surveys themselves. The relevant evidences indicate that the national Gini coefficient in current China is between 0.47~0.52. The sampling defects of the CHFS are significantly major and that the national Gini coefficient of 0.61 published by SWUFE is seriously overestimated.     

Evolution of wealth inequality in China

Household wealth is a key indicator that reflects national economic competiveness and individual income levels. The distribution of wealth is central for evaluating social justice in a country. This article uses a data set composed of the 2002 China Household Income Project and the 2010 Chinese Family Panel Survey to analyze the level of wealth and wealth inequality in China during 2002 and 2010. The analysis decomposes the evolution of wealth inequality during that period in terms of the structure and composition of wealth. The findings show that there was a large increase in the quantity of wealth and wealth inequality between 2002 and 2010. The level of wealth in 2010 was four times that of 2002, and housing assets were the greatest component of overall wealth in 2010. Wealth inequality also rose dramatically after 2002, with the Gini coefficient of the distribution of wealth increasing from 0.538 in 2002 to 0.739 in 2010. The rapidly escalating price of housing has been the main contributor to increasing wealth inequality in recent years.     

Distributional national accounts for the Netherlands and a comparison with 12 other countries

Most inequality studies rely on micro data that do not capture a substantial share of income identified in the national accounts. In the Netherlands, almost one fifth of household disposable income is missed by current inequality statistics. In this paper, we present inequality statistics for the Netherlands that capture all of household income, so-called distributional national accounts. Compared to the current inequality statistics, the Gini coefficient for disposable income increases substantially from 0.289 to 0.337. Cross-country comparisons show that such a change between Gini coefficients based on micro-data versus Gini coefficients based on distributional national accounts does not apply to all countries. The difference between both Gini coefficients varies not only between countries in the size, but also in the sign of the difference.     

The effects of transition on the distribution of income in China

Using two large samples for 1988 and 1995 we decompose the Gini coefficient of household income according to type of income with the purpose of analyzing reasons for the rapid increase of inequality. The results show that the change in relative size of money income and its changed profile are found to be the major processes behind the rapid increase of income inequality in rural China. Changes in housing allocation and an increased number of retirees in combination with higher benefits have made inequality increase in urban China and in China as a whole. JEL classification: D31, P27.     

影响我国农村居民收入差距的主要因素:从收入构成角度的分解分析

This paper attempts to explore the causes behind the change of the inequality in China rural areas at the very beginning of this century by decomposing the inequality of the total per capita income into the contributions from different income components. Furthermore, we develop the decomposition method of Gini coefficients from the income components and use it not only in the static analysis but also in comparative static analysis. Namely it can be used to explore the change of the overall inequality by decomposing the change of Gini Coefficient from income components. The empirical results show that the wage from local employment, the income from agricultural household business and the incomes from non-agricultural household business are the three income components that made the largest contributions to the inequality of the total per capita income. The total contribution to the overall inequality of non-agricultural incomes was much more than that of agricultural incomes. The incomes from agricultural household business, the incomes from non-agricultural household business and the wages from migration made the positive impact on the increase of the overall inequality. The incomes donated by relatives and friends made the most important negative impact on the increase of the overall inequality.     

财富不平等会抑制金融素养对家庭借贷行为的作用效果吗*——基于CHFS数据的经验分析

本文基于2013年中国家庭金融调查（CHFS）数据,选用工具变量法,考察了金融素养对城乡家庭借贷行为影响的差异性,并验证了财富不平等扩大会抑制金融素养对家庭借贷行为的影响。研究发现：（1）金融素养是影响家庭借贷行为的重要因素。户主金融素养水平的改善显著提高了家庭发生借贷的概率与家庭借贷规模。（2）金融素养对城乡家庭借贷行为的影响存在明显差异,金融素养的提高对信贷约束较为严重的农村家庭借贷行为的促进作用更大。（3）财富不平等对家庭借贷行为存在明显的抑制作用,财富不平等的扩大减少了家庭借贷需求,降低了家庭发生借贷的概率和家庭负债规模。（4）随着家庭财富不平等程度的扩大,金融素养对家庭借贷行为的促进作用受到抑制。基于以上结论,政府应该大力开展消费者金融素养教育,注重家庭收入分配合理性,从而推动我国消费金融市场的健康发展。