摘要
本文建立了一个中等规模的动态随机一般均衡(DSGE)模型。利用中国的数据,对模型参数进行了校准、估计,并利用贝叶斯方法和冲击响应方法对模型性质进行了评估。在通过评估对模型建立信心的基础上,利用模型对主要宏观经济变量进行预测,并讨论了货币政策和预期外生需求冲击的影响。最后基于模型性质讨论了金融市场、货币政策和经济波动三者之间的关系。
本文的主要贡献是建立了一个可以反复使用的、分析中国经济的基准模型。模型基于新凯恩斯主义宏观经济学的最新发展,其核心是第四代宏观计量模型的基准CEE/SW模型,其中包含了大量的真实和名义摩擦,这使得模型对于宏观经济时间序列有良好的拟合能力;由于模型与世界各国央行使用的模型保持一致,这使得本文的结论可以更好的与国外的同类研究进行比较;模型在核心的CEE/SW模型之外,还包含了新古典的银行部门和金融加速器机制,这使得模型可以探讨不同口径的货币流通速度、外部融资成本与企业信贷、资产价格和货币政策关系等问题。
第4章对控制模型稳态的参数进行了比较详细的校准。对稳态的初步分析发现模型对于银行部门的资产负债表和不同口径的货币流通速度拟合较好。模型预测的稳态存款利率高于实际数据,除了政府控制利率的因素,另外两个重要原因是稳态的高增长率以及名义利率中包含了通货膨胀的风险溢价。
第5章利用贝叶斯方法对核心模型的动态参数进行了估计。与国外的估计结果相比,中国的投资调整成本较低,而资本利用率调整成本和价格粘性程度较高。历史分解的结果表明影响中国经济最重要的冲击是外生需求冲击、投资效率冲击和货币政策冲击。
第6章对核心模型的评估表明对数据解释力最强的因素是价格粘性,而资本利用率调整成本、工资粘性、价格和工资的指数化因素则并不重要。使用去掉这三种因素的模型进行样本外预测,结果表明:模型对于消费和GDP的预测能力较强,DSGE模型在长期预测中表现优于向量自回归(VAR)模型。
第7章将核心模型与金融部门结合,考察了货币政策冲击和预期外生需求冲击的影响,表明正向货币冲击可以降低外部融资溢价,预期需求冲击可以对当期经济产生重要影响。基于冲击响应分析,作者研究了金融市场和资产价格波动的关系。证明来自金融市场的资产价格泡沫冲击和企业家风险冲击对于实体经济有重要影响,不同的融资结构会影响货币冲击的传播方式,而不同的货币政策也会影响金融冲击的传播。模拟结果表明:在货币增长规则中引入通胀目标和资产价格可以降低产出、通胀和资产价格的波动,有助于宏观经济稳定。
This paper constructs a medium-scale structural model of the Chinese economy. After the usual calibration and estimation, this paper evaluates the core model numerically, and uses it to forecast the key macroeconomic variables. Finally, the author analyzes the impulse response from monetary policy and expected exogenous demand shock, explores the relationship between asset price and monetary policy based on the complete model.
The main contribution of this paper is building a usable, standard model for analyzing the Chinese economy. This model is rooted in the current development of New Keynesian Macroeconomics and includes numerous nominal and real frictions to make a good match of the main time series. The core CEE/SW model is the workhorse of the fourth generation macro-econometric models. Since the model specification is in accordance with other models used in the major central banks in the world, it is convenient to compare our conclusions with those in other countries. Like the complete CMR model, this paper incorporates a neoclassical bank sector and financial accelerator, which makes it convenient to analyze issues relating to money aggregates, firm credit, asset prices, and etc.
Chapter 4 carefully calibrates the parameters governing the steady state based on yearly data. Then the ahe author match steady state to the main ratios, money aggregates and various interest rates in China. Preliminary analyses show that the discrepancy between model predicted and actual interest rate can be explaind by inflation risk premium, habit formation liquidity constraint, precautionary deposits and liquidity constraint.
Chapter 5 estimates the dynamic parameters of the core CEE/SW model based on quarterly observations and Bayesian methods. The results show the investment adjustment cost is low, while the capital utilization rate adjustment is costly compared with extant research. Historical decomposition finds that the most important driving forces of the Chinese economy are exogenous demand (including fiscal expenditure and net export), monetary shock and investment efficiency.
Chapter 6 evaluates the core model and finds the most important friction for the model performance is price stickiness, while wage stickiness, variable capital utilization, price and wage indexation are of minor importance. Removing these frictions from the model, the author compares its out-of-sample forecasts performance with VAR model and the judgemental Langruen Forecasting. The RMSE statistics show DSGE model outperforms VAR model in the long run; In case of one-step-ahead forecasts, it competes well with the judgemental Langruen Forecasts.
Chapter 7 combines the core model with financial sector, and evaluates the complete model based on impulse responses from monetary policy and expected demand shock. The author proves that expected demand expansion may elevate the expectation of the agents, thus expands demand and production in the current period.
Finally this paper explores the relationship between monetary policy and asset price fluctuation. Based on impulse response analysis, the author proves that financial shocks contribute to business cycle fluctuations, financial structure plays an important role in the propagation of monetary shocks, and different monetary rules may influence the propagation of financial shocks. The simulation results support introducing inflation and asset price targeting into money growth rule, which may reduce macroeconomic fluctuation. While targeting output gap may reduce output and asset price fluctuations, at the same time amplify the inflation fluctuation.
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