财政支出预期冲击——来自金融市场的识别Expected Impact of Fiscal Expenditure——Identification from Financial Markets
田磊,张少华,张佐敏
摘要(Abstract):
公众对财政政策的预期是否具有重要的宏观经济效应?为探究这一问题,本文首先分析了财政支出预期对宏观经济动态系统和SVAR设定的影响;接着,基于中国财政政策实践和股市运行特征,构造适合中国财政政策实践的财政政策预期变量;最后,建立SVAR模型,识别出财政支出预期冲击效应和未预期到的财政支出冲击效应。研究发现:(1)本文基于上证180基建指数季度简单超额收益率构造的财政支出预期变量,对政府投资支出和总财政支出具有良好的预测能力;财政支出预期冲击能够产生明显的宏观经济刺激效应。(2)不含财政政策预期变量的SVAR模型将不同程度地高估主要宏观经济变量的脉冲响应函数。(3)未预期到的政府投资并不拥有明显高于政府消费的支出乘数。本文最主要的边际学术贡献是构建了一个适用于中国数据的财政支出预期的代理变量。
关键词(KeyWords): 财政支出预期;季度简单超额收益率;SVAR;财政支出乘数
基金项目(Foundation): 国家自然科学基金常规面上项目“中国企业和城市规模分布异化的政策根源、形成机制与效率评估”(批准号72073038)和“中国的‘中部迷失’问题:典型事实、形成机理及宏观后果”(批准号71673253)的资助;; 广州市宣传文化人才培养专项经费资助;; 浙江省2011协同创新中心(数据科学与大数据分析协同创新中心)的资助
作者(Author): 田磊,张少华,张佐敏
DOI: 10.16513/j.cnki.cje.20220803.002
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- (1)如贾俊雪和郭庆旺(2012)、李永友(2012)等论述,增加财政支出,特别是增加生产性财政支出,是我国积极财政政策的主要内容,因此,本文将财政政策聚焦于财政支出政策,将对税收政策宏观经济效应的考察放在未来的研究中(但本文在稳健性分析部分考察了财政收入的影响)。除非有专门说明,本文不对“财政政策”和“财政支出政策”进行严格区分。
- (2)这里的“铁公基”是指铁路、公路、机场、水利等重大基础设施建设。基础设施类概念股指的是能够直接从“铁公基”投资中受益的股票,著名的股票信息平台,比如Wind、同花顺和各主要券商的交易软件都列示了基础设施类概念股。
- (3)具体的模型设定和详细推导过程请参见附录。感谢审稿专家为我们指出“考虑政府投资的必要性”。
- (4)由于政府消费不进入居民效用函数,是否包括政府消费不会对理论结果产生重要影响。为推导方便,此处我们仅考虑政府投资。
- (5)Gertler and Karadi(2015)利用资产价格变动提取货币政策冲击的做法被许多文献借鉴。
- (6)尽管都是基础设施投资概念股,但公司之间的主营业务存在比较大的差异,政府增加铁路建设投资,高速公路上市公司的股票反应就不大可能强烈,政府出台“海绵城市”计划,只会刺激地下管廊公司的股票价格,因此,利用单一公司的股票价格不具有好的代表性。
- (7)基建180指数时常受到大盘走势的影响,比如时有发生的由监管政策造成的“千股跌停”现象,另一方面,在大牛市期间主题指数的走势在很大程度上也是受到大盘走势的影响。
- (8)十四只基建类股票的名称分别为:“粤高速A”、“山东路桥”“甘肃电投”“海南高速” “赣能股份”“中南建设”“福建高速”“葛洲坝”“重庆路桥”“岷江水电” “赣粤高速”“宁沪高速”“中铁二局”和“隧道股份”,其中最晚上市日期为中铁二局的2001年5月28日。
- (9)Fisher and Peters(2010)正文的“Table 2”呈现了相关的预测能力检验结果,具体页码是424-426。
- (10)该数据集可在美联储亚特兰大分行网页https://www.frbatlanta.org/cqer/research/china-macroeconomy.aspx下载,里面有指标构建说明,更新频率等详细信息。
- (11)考虑到我国经济发展现实,负向财富效应在我国应该是很弱的。
- (12)本文也计算出了预期冲击的现值乘数,但发现这一数值并不稳健。这是因为,预期冲击本身的大小难以量化,但正向的财政支出预期冲击发生后,财政支出和实际产出均会增加,因此我们同样可以利用总产出变化的现值除以财政支出变化的现值得到现值乘数。然而,预期冲击的乘数值会受到模型设定的明显影响,比如,变化SVAR模型的滞后阶数、变化内生变量的顺序,都会引起现值乘数的明显变化。与之作对比,未预期到的财政支出的乘数值表现得非常稳健。出于严谨性考虑,此处我们就不报告预期冲击的乘数。但是,需要说明的是,我们得到的政府投资预期冲击乘数的最小值也明显大于未预期到的政府投资乘数。