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作 者:刘建丰 潘英丽[2] Liu Jianfeng;Pan Yingli(School of Finance,Shanghai University of International Business and Economics,Shanghai 201620,China;Antai College of Economics and Management,Shanghai Jiao Tong University,Shanghai 200030,China)
机构地区:[1]上海对外经贸大学金融管理学院,上海201620 [2]上海交通大学安泰经济与管理学院,上海200030
出 处:《财经研究》2020年第5期94-110,共17页Journal of Finance and Economics
基 金:上海市哲学社会科学规划一般项目(2019BJL005)。
摘 要:中国的土地制度、家庭购房偏好和新房生产函数都不同于欧美国家,作为从宏观视角研究中国房地产经济的起点,需要利用中国数据校准或估计出一个参数更加可信的新房总量生产函数。为此,文章基于一个包含两个生产部门的动态随机一般均衡(DSGE)模型,尝试做了此项工作。基本模型分析表明,在中国新房生产中,土地、实物资本和劳动成本分别占23%、67%和10%;而在京沪等一线城市的新房生产成本中,土地接近30%,实物资本略超50%,劳动占20%。如果模型设定基本正确,那么中国房地产部门的统计数据可能存在系统性偏差,而且全国平均水平比京沪等一线城市更加严重。基于基本模型的模拟分析,文章强调对于当前的土地供给应"分城施策",三四线城市短期内应适当减少土地供给以稳定地价和房价,而一二线城市长期应尽量增加土地供给以降低地价和房价。2020年3月12日,国务院印发《关于授权和委托用地审批权的决定》,进一步深化"放管服"改革,赋予省级人民政府更大的用地自主权,这更加有利于地方政府实施文章所提出的"分城施策"建议。China’s land supply system, household’s housing purchasing preference and new housing’s production function are totally different from those in Europe and the United States. As a starting point to study China’s real estate economy from a macro perspective, there is an urgent need to use China’s data to calibrate or estimate a new housing’s aggregate production function with more credible parameters. Therefore,based on a dynamic stochastic general equilibrium(DSGE) model with two production sectors, this paper attempts to do this work.Because we do not pay attention to the short-term fluctuations of China’s macro economy and real estate economy, it is not necessary to establish a large and complex DSGE model that takes into account the monetary and credit financial sectors and various nominal frictions when calibrating or estimating these structural parameters. To this end, this paper follows a common practice of estimating the aggregate production function at home and abroad to construct a fundamental model that does not include these financial and nominal friction factors. The small-scale model in this paper mainly includes six sectors: new housing production, general product production, households, investment products, land resellers and governments.The fundamental model’s estimation finds that in China’s new housing production costs, the shares of land, physical capital and labor are 23%, 67% and 10%, respectively. Obviously, this result is hugely different from Iacoviello and Stefano(2010) about the shares of capital, land and labor of the new housing production function in the United States at approximately 20%, 10% and 70%, respectively. Therefore, we cannot directly borrow the structural parameters in the new housing production function from those countries such as the United States and Europe. In comparison, in the new housing production costs of the first-tier cities such as Beijing and Shanghai, the land’s share is close to 30%, the physical capital’s is slightly over 50%, and the
关 键 词:新房总量生产函数 房地产部门统计数据质量 土地政策 供给侧结构性改革
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