限购背景下存准率与房价的关系研究

2010年以来,我国主要的大中城市纷纷出台了商品房的限购政策,同期法定存款准备金率也多次调整.在限购政策背景下,本文运用广义矩(GMM)方法,将限购政策作为逻辑变量加入到估计模型中,对限购背景下的存款准备金率调整与商品房价格的关系进行了定量分析.结果表明,限购政策对于抑制房价过快上涨具有显著意义,同时,政府上调存款准备金率在滞后2期和3期时对于抑制商品房价格过快上涨也具有一定的积极作用,但商品房价格不会因存款准备金率的上调而出现急速下跌,而是在存款准备金率持续上调的过程中呈现出先上涨后下跌,再上涨、再下跌的交替变化特征.研究同时发现,限购政策和存款准备金率调整对于我国东部地区城市影响显著,而对于中西部城市影响则不显著.基于此,本文提出了运用存款准备金率手段在抑制商品房价格过快上涨过程中的对策建议.     

房地产“限购令”的调控机制与政策反思*——基于单中心双环城市模型的分析

近年来中国城市住房价格快速上涨,政府推出房地产“限购令”,以期调整房地产市场,控制城市房价。本文构建了带“限购令”政策约束条件的单中心双环城市住房市场模型,利用数值模拟的方法,从理论上分析房地产“限购令”的政策效果和作用机制。结果显示,限购政策使大中小城市房价均有所下跌,中小城市房价的下降幅度大于大城市的幅度,城市的投机性住房需求越大,限购政策的效果越明显。本文认为“限购令”作为非市场调控手段,仅可作权宜之计而非长久之策,应充分考虑城市的异质性特征,对限购政策进行辨证选择。     

Effects of house-sale restrictions in China: a difference-in-difference approach

Chinese housing prices have increased rapidly in recent years. Concerned about the potential for a burst bubble, the Chinese government has been intervening in the market to rein in the rising price trend since 2010. In March 2017, a new housing policy, called house-sale restriction, was developed to curtail speculation in the Chinese housing market. This study uses a difference-in-difference model to examine the policy effect of this new restriction. By using house-sale and price data of 43 cities across 30 provinces in China, we find that house-sale restrictions could effectively reduce speculation in the market as well as decrease housing prices in the short term. This study analyses only the short-term effect of this new housing policy; the long-term effect requires further examination.     

区域房价差异、劳动力流动与产业升级

中国正在发生的大规模区域产业转移的动因是什么,区域房价差异对产业转移和产业升级产生哪些影响,是本文关注的焦点。作者引入房价因素,对新经济地理学模型进行拓展,发现区域房价差异导致劳动力流动,从而诱发产业转移。在此基础上,利用动态面板数据模型对2000-2009年中国35个大中城市进行实证检验,结果发现城市间的相对房价升高,导致相对就业人数减少,并促使产业价值链向高端攀升,实现了产业升级。对不同区域的深度分析表明,区域房价差异确实是影响东、中、西部地区产业转移和产业升级的一个重要因素。因此,制定合理的区域产业发展规划,加大对东部地区中高端产业发展的扶持力度,建立健全与产业转移相适应的住房政策和住房保障体系,是顺应产业转移趋势、避免部分区域产业空心化的必要措施。     

Modelling the housing market in OECD countries

Recent episodes of housing bubbles, which occurred in several economies after the burst of the United States housing market, suggest studying the evolution of housing prices from a global perspective. We utilise a theoretical model for the purposes of this contribution, which identifies the main drivers of housing price appreciation, such as, for example, income, residential investment, financial elements, fiscal policy and demographics. In a second stage of our analysis, we test our theoretical hypothesis by means of a sample of 18 OECD countries from 1970 to 2011. We employ the vector error correction econometric technique in terms of our empirical analysis, which permits us to model the long-run equilibrium relationship and the short-run dynamics, which also helps to account for endogeneity and reverse causality problems.     

The economic impact of reducing on-base naval housing

This article develops a methodology for estimating the impact on rents and home prices from a hypothetical reduction of on-base naval housing from 56 naval bases in the United States. Based on data from the Center for Naval Analyses and the U.S. Census of Housing, and response coefficients from housing economics literature, illustrative estimates are presented of the short-run and long-run and long-run impact of reducing naval housing.
Key factors determining the increase in rents and home prices include (1) the increase in demand for housing in the private sector resulting from the reduction of on-base naval housing, (2) the short-run and long-run elasticities of supply of private sector housing with respect to housing prices, and (3) the elasticity of demand to live in a defined housing area with respect to housing prices.
We find that the effects on rents and home prices are in most cases small in the short run and negligible in the long run. The median first-year rent increase in the 53 counties is estimated to be 0.90%, with only 9 of the counties still expected to experience rent increases of as much as 4%. In the long run, the median rent increase is estimated to be only 0.10%. Because the purchase of a home is a long-term investment, we find that the impact on home prices is negligible, similar to the long-run impact on rents.     

Housing,consumption and monetary policy: how different are the first-, second- and third-tier cities in China?

This article presents an empirical analysis of the relationship between house prices and the real economy in China’s first-, second- and third-tier cities. A Structural Vector Autoregression model is applied to study the impacts of monetary policy shocks and housing demand shocks on various housing markets across China. We also investigate the role of house prices in the transmission mechanism of monetary policy. The results reveal that in first-tier cities, raising interest rates has a stronger negative effect on house prices. Also, as house prices decrease in first-tier cities, private consumption declines sharply. There is a stronger role of housing markets in the transmission of monetary policy shocks in these cities. Our findings indicate that interest rate adjustment could effectively curb spikes in housing prices in the first-tier cities, but the impact of such adjustments on household consumption must also be considered.     

Talent introduction and housing price: a tale of Xi’an

A comprehensive competition policy for talent introduction was first implemented in Xi’an in February 2017 and has been imitated by many cities in China ever since. Although turned out to be useful in alleviating the problem of talents loss in the lower-tier cities, the policy has been criticized for its potential effect of driving up housing prices. Using the synthetic control method proposed by Abadie and Gardeazabal (2003), we explore the influence of the competition policy for talent introduction on housing prices in Xi’an. Based on the monthly data of Xi’an and 62 control cities across 30 provinces in China from January 2015 to April 2018, we find strong evidence for the positive effect of the competition policy on housing prices. Specifically, the policy increased housing prices in Xi’an by approximately 43% until April 2018.     

A national or local phenomenon? A comparison of the US and the Chinese housing markets

This article investigates the common movements of house prices across cities as well as the macroeconomic underpinnings of the comovements in the US and China. Our empirical results indicate more differences than similarities between the US and the Chinese housing markets. The results from a Bayesian dynamic latent factor model indicate that the fluctuations of house prices across cities in the US are more a national phenomenon, while the dynamics of house prices across cities in China are mainly driven by the city-specific component. We further use VAR models to compare the roles of the underlying determinants in these two housing markets. The results show that the roles of monetary policy shocks and aggregate fluctuations in driving the common movements of house prices across cities differ substantially between the US and China at both short and long horizons.     

Analysis of the impact of excess mortgages on housing prices using the cointegration test

This article attempts to explain and predict housing prices by constructing a model based on the variables that most influence demand: the theoretical purchase effort index without tax deductions as well as a new and innovative indicator that includes the excess of mortgages granted. The Johansen methodology for cointegration analysis reveals the existence of long-run equilibrium and the model’s subsequent ECM, to verify the statistical significance of the variables, confirms the validity of the model concerning this Spanish case study.     

房地产价格、泰勒规则与宏观经济调控——基于2000-2010年我国宏观经济数据的检验

央行是否应该针对房地产价格制定货币政策进行调控,一直是学者们关注的焦点,但研究结果仍存在分歧。基于2000-2010年我国季度经济数据,对比检验了融入房地产价格的泰勒规则与标准泰勒规则对我国制定货币政策调控宏观经济的适用性。实证结果表明,依据标准泰勒规则所制定的利率政策,可以降低央行损失函数值,提高利率政策有效性。这一结果意味着,在房地产价格波动不影响物价稳定和经济增长的情况下,央行不应针对房地产价格进行调控。也就是说,央行需考虑房地产价格波动与通货膨胀和产出之间的相关关系,判断其对政策目标的潜在影响,制定利率政策对宏观经济进行调控。     

The asymmetric impacts of monetary policy on housing prices: A viewpoint of housing price rigidity

Previous studies have discovered the defensive characteristics of housing prices, which is also known as downward price rigidity. This paper discusses whether this feature would result in an asymmetric relationship between housing prices and monetary policy. This paper first uses the loss aversion behavior of traders to assess the viability of housing price rigidity in the housing market and to deduce further that if downward housing price rigidity actually existed, then the impact of monetary policy on housing prices should be asymmetric. For empirical tests, this paper uses data from the UK housing market and then uses the money supply as the proxy variable of monetary policy. The relationships between these two variables are observed. This paper performs estimation using both traditional and threshold error correction models by comparing the coefficients of both models. The results indicate that housing price is indeed asymmetrically adjusted to money supply. When housing prices increase to reflect a loose monetary policy, a modification behavior is evident. Conversely, housing prices cannot easily reflect a tight monetary policy. This result indicates that housing prices tend to overreact in upturn and underreact in downturn. The results imply that when implementing relevant policies for the housing market, the government should consider the asymmetry of housing price changes. Otherwise, the situation can easily result in the creation of a bubble or the collapse of the housing market because of incorrect policies.     

The Impact of Monetary Policy and Housing-Purchase Restrictions on Housing Prices in China

This paper examines the level and volatility effect of monetary policy on housing prices in China utilizing a novel set of housing price indices constructed by (Fang, H., QuanlinGu, W. X., & Zhou, L.-A. (2015). Demystifying the Chinese housing boom. NBER Macroeconomics Annual 2015, Volume 30. University of Chicago Press.). We find that in the long-run, average housing prices react positively to inflation, money supply and bank lending growth, and negatively to the reserve requirement ratio and benchmark lending rate. Housing prices in Tier 1 cities respond more sensitively to monetary shocks relative to Tier 2 and 3 cities, possibly due to surging demand and limited supply under housing-purchase restrictions (HPR). We further study the volatility effect of monetary shocks using the GARCH model and find that the benchmark lending rate, reserve requirement ratio and money supply growth have strong negative impact on the volatility of housing price growth. Our benchmark results remain robust after incorporating the HPR policy variable in the estimation, with a significant negative effect of HPR on housing price growth in Tier 1 and Tier 2 cities. Lastly, we conclude with recommendations on future monetary policy design and implementation, with a specific focus on the heterogeneous characteristics of China’s housing market.     

Outsiders,insiders and interventions in the housing market

In the wake of China’s “great migration,” many cities, including Beijing and Shanghai, restrict some residents from owning housing, forcing them to rent. We build a model studying motivations for and effects of ownership-restricting policies. When some agents are prohibited from purchasing housing, competitive equilibrium further punishes renters, failing to attain a “second-best” that maximizes welfare subject to the policy’s intended constraint. We then consider real estate taxation, a hotly debated topic in China, currently undergoing reform. We show that positive taxes on housing transactions can help mitigate the inefficiency caused by restricted ownership, but only by introducing a new distortion. Meanwhile, subsidizing rental transactions could, in theory, restore the second-best, but only by diverting public funds away from other uses.     

The multi-market analysis of a housing price transmission model

In this article, we examine dynamic relationships among housing prices from four first-tier cities in China from December 2000 to May 2010 and present an equilibrium model of housing price in multi-markets. By explicitly incorporating and modelling endogenous price series in competing housing markets, our empirical model is able to capture the existence of long-run equilibrium relationships and important short-run dynamics and price structures such as price leadership, price transmission lag and asymmetric price responses. Such multi-market analysis has generalized implications and can easily be applied to analyse the pricing dynamics among other real estate markets in the world. Our major contribution lies in two aspects. First, we employ an Error-Correction Model (ECM) with Directed Acyclic Graphs (DAG) to study the price dynamics in the four largest and key housing markets in China. Second, we uncover a price transmission among these housing markets in China and provide an insightful understanding of price adjustment across markets. The revealed effective price transmission and high correlation among these different markets actually is not a good thing for a stable financial system and for the defence against price bubbles in the housing market.     

Fuel poverty in residential housing: providing financial support versus combatting substandard housing

Between 50 and 125 million Europeans are unable to afford the energy needed for adequate heating, cooking, light and use of appliances in the home. Tackling fuel poverty has thus become a public policy challenge. In this article, we assess the effectiveness of social energy subsidies and social housing to reduce fuel poverty. The literature reports that rising fuel prices, low incomes and energy-inefficient housing are the main causes of fuel poverty. Existing public policies focus mainly on price- and income-based measures to reduce fuel poverty, such as social energy subsidies. This type of policy is palliative as it does not permit to sustainably eradicate fuel poverty. Other policies aim to encourage renovation in order to improve energy efficiency. Those policies are curative as they sustainably reduce one cause of fuel poverty: energy inefficiency. In this article, we focus on another public policy to tackle fuel poverty: social housing. We believe that this policy could be preventive, as the literature reports the better energy efficiency of social housing. We use matching methods and find that living in social housing decreases fuel poverty by 5.4% to 9.1%. On the contrary, social energy subsidies have no effect on fuel poverty.     

北京市房地产价格影响因素分析及限购政策绩效评估

随着经济的高速发展,城市的房价也呈现出急剧攀升的态势,脱离了正常的价格波动轨道,大大增加了城市居民的生活成本。以首都北京为例,房价的上升幅度远远超过预期。在经济理论的基础上,运用近几年北京房地产行业的统计数据建立回归模型,可以对影响北京房价的因素进行分析,并且可以对北京市政府2011年2月出台的＂京八条＂限购政策进行绩效评估。     

Housing prices and son preference: Evidence from China’s housing reform

Do high housing prices reduce the demand for sons? As Chinese parents need to acquire houses for their sons’ marriage, high housing prices increase the cost of sons relative to daughters. We exploit China's housing reform in the 1990s as a natural experiment to identify the effect of housing prices on demand for sons. We find that housing prices have no effect on the probability of having a son at the first birth. High housing prices reduce the probability of having a son at the second birth, especially when the first-born is a daughter. A 10% increase in housing prices reduces the probability of having a son at the second birth by 0.78 percentage points. The findings remain robust when using aggregate prefecture-cohort data for the post-reform period.     

Do regional house prices converge or diverge in China?

This paper aims to test whether the regional house prices are convergent or divergent in China using a monthly panel data set of China’s 70 large and medium-sized cities from July 2005 to December 2010. This issue is closely related to understanding the efficiency of the country-level housing policies made by China’s central government. The test results suggest that the regional house prices in China are generally divergent, and thereby the country-level policies may be inefficient since they do not explicitly take the strong heterogeneity of China’s regional housing markets into consideration. As a consequence, it may be better for China’s central government to further decentralize and devolve its governance toward the housing market to the local governments.     

Housing investment in urban China

What explains the rapidly increasing housing investment demand in China? To address this question, we develop an analytical framework featuring how expected capital gains impact households' housing investment decisions when subject to financial constraints. Housing demand in China takes place not only through households' owning multiple houses, but also through their owning a larger primary living residence if they are constrained from buying multiple houses. We show that households are more likely to own multiple houses when expecting higher capital gains. As expected capital gain increases, the primary housing demand of those households who are constrained from owning multiple houses increases, while those owing multiple housing units invest in extra ones instead of improving primary housing. Our empirical findings, based on 2010 and 2011 household survey data, are consistent with our theoretical predictions. We also find that the marginal effect of expected capital gains is higher for wealthier households. This links the booming housing market to widening income inequality which is a typical growth pain in a developing country like China. As an extension, we apply the analysis to derive implications of the institutional features (such as purchasing restriction policy and the existence of subsidized housing) for China’s housing markets.