高房价对我国全要素生产率影响的机制分析及数量测度：基于多部门资产泡沫模型的研究及政策探讨

China’s housing price has experienced rapid growth since the housing reform in 1998 with the real estate sector being regarded as the pillar industry. Meanwhile, the potential economic growth of China have slowed down as shown by Kalman filter (KF) model. The contribution of total factor productivity (TFP) to economic growth also declines. The above phenomena raise two questions? First, is there a relationship between housing bubble and total factor productivity? And if there is a relationship, then what is the influencing channel. Second, how to improve the efficiency under the background of housing bubble in China at present? This research will investigate these two questions systemically..The historical comparative analysis, empirical analysis and computer simulation are adopted in the research. First, we will analyze the relationship between housing bubble and total factor productivity in the developed country historically. The policies aiming at promoting the production efficiency and allocation efficiency will be summarized. Second, we will use principal components method to define the housing bubble. This definition is crucial for our empirical investigation. Third, we will explore the influencing mechanism of housing bubble on total factor productivity from the perspective of liquidity effect, resource reallocation effect, leverage effect as well as labor transfer effect. Fourth, we will establish a multi-sector bubble model including real estate sector, manufacture sector and research and development sector. We will calibrate the model and simulate the effect of housing bubble on total factor productivity overall. The critical condition of liquidity effect, resource reallocation effect, leverage effect and labor transfer effect will also be analyzed, which is helpful to investigate these effects on long-run economic growth in China. .Finally, the research attempts to provide the policy suggestions about the ways to improve the total factor productivity with housing bubble in China currently as well as the transition path of economic growth mode from the extensive one to the intensive one.

房改以来，房地产成为国民经济的支柱产业，房价也出现大幅增长，且中国潜在经济增速出现下滑，全要素生产率对经济增长的贡献也在下降。高房价与全要素生产率存在何种联系？高房价背景下如何促进全要素生产率提高，实现结构转型和长期经济增长目标？这是本课题研究的主要内容。.本课题采取历史比较分析、实证分析和计算机模拟相结合的研究方法。首先，分析主要国家发展历程，总结高房价背景下促进生产率提高的对策；其次，利用主成分分析法从多个角度界定高房价；再次，以流动性效应、资源再配置效应、杠杆效应和劳动力转移效应为切入点，分析高房价对全要素生产率的影响机制；最后，通过建立多部门资产泡沫模型，进行参数校准和模拟，分析高房价引致的四个效应的临界条件，以及它们对我国长期经济增长的影响。.通过研究，本课题旨在提供高房价背景下促进全要素生产率提升的政策建议，并探寻从要素驱动增长转向效率、创新驱动增长的路径。

房价问题是经济问题、社会问题，也是关乎民生的重大现实问题。金融如何来为实体经济服务？房产具有的资产属性，其价格的快速上升对实体经济又有哪些方面的影响？课题从理论上分析高房价对实体经济的影响。课题紧紧围绕着流动性效应和挤出效应全面系统的分析了高房价对实体经济的影响。在融资约束存在的情况下，企业融资需求无法得到满足，反映在行业层面便是要素配置无法实现最优，而一旦资产价格上涨产生了流动性效应，缓解了企业面临的融资约束，那么要素配置效率将会提高。高房价有提高要素错配程度的效应，其中一个可能的影响渠道是企业并没有利用高房价提高带来的流动性效应将资源用于自身的经营生产和之前由于融资约束而无法进行的项目中，从而提高要素配置效率。研究采取了宏观层面研究中常用的处理内生性问题的方法，包括将重要解释变量滞后一期，以及动态面板GMM的估计方法。.研究结果发现，流动性效应和挤出效应同时存在，政府需要对预期进行有效管理，充分发挥流动性效应，使其占据主导。具体而言，第一，高房价对行业全要素生产率产生了负面影响，房价收入比提高10%，行业全要素生产率下降2.56%，这说明高房价并没有通过流动性效应改善资源配置效率，反而导致要素配置扭曲程度加大；第二，在房价增速快、房地产投资回报率高的背景下，企业将资源配置到房地产部门，从而挤出投资风险高、回报周期长的研发投资。房价增速提高1个百分点，研发投入占总资产比重下降0.051个百分点，人均研发投入下降71.27元；第三，房价的流动性效应依然发挥着作用，房价上涨提高一个标准差，私有企业投资-现金流敏感度将下降0.0134，降幅为5.05%，并且经营时间更长或者内部资金更充裕的私有企业融资约束缓解程度越大。