Financial Market Frictions, Beliefs, and the Macroeconomy; An Application to the Case of China

项目1：“有限的承诺和货币政策的影响”在这个项目中，我们将研究市场参与者的信念对金融摩擦的影响，以及对货币政策的影响(例如利率变化对生产率和增长的影响)。2011年后，中国的扩张性货币政策(更高的货币供应量增长或更宽松的贷款条件)对通胀和产出的扩张作用并不像前几年那样大。我们将研究一种特定类型的摩擦--有限承诺--的存在如何显著影响货币政策的影响，并解释近年来观察到的不同影响。项目二：“金融市场流动性与政府政策的寻找匹配”根据世界银行的数据，2000年至2013年，中国的货币供应量(M2)年增长率为16.2%：同期，年均通货膨胀率为2.4%，年均实际国内生产总值增长率为8.7%。这意味着，即使考虑到国内生产总值的高实际增长，中国的通货膨胀率也已经系统性地低于人们根据货币供应量增长率的预期。中国的金融市场还不够发达，许多私募资产流动性不强。因此，除了交易动机外，经济主体持有货币也是出于流动性需求。本项目的目的是研究当有关流动性的信念影响市场参与时，较高的流动性需求(由于金融市场的低流动性)如何影响货币政策、通胀和经济增长之间的关系。我们将运用这项研究来理解前面提到的中国实践，并讨论它是否可持续。我们将通过在其他标准的宏观经济框架中引入资产流动性摩擦来研究这些问题。与外生资产流动性不同的是，内生资产流动性是微观的，适合于政策分析。项目3：“金融市场中的长期羊群行为和波动性集聚”在第三个项目中，我们转向另一种形式的金融摩擦--信息不对称。金融市场对于良好的投资决策至关重要。价格聚合分散信息的能力是资源有效配置的基础。我们将通过使用新的金融市场模型来研究中国金融市场的信息效率，重点是学习和羊群效应。我们还将研究为什么资产价格表现出时变的波动性，以及这与羊群行为的关系程度。然后，我们将使用从万得资讯获得的中国证券交易所的交易数据来估计模型。结构性估计将使我们能够量化羊群效应和资产价格时变波动的驱动因素及其对市场效率的影响。

Project 1: "Limited Commitment and the Effects of Monetary Policy"In this project, we will study how financial frictions affected by beliefs of market participants, and the implication for monetary policy (such as a change in interest rates on productivity and growth). The expansionary monetary policy (higher money supply growth or easier lending conditions) in China after 2011 did not have the same expansionary effects on inflation and output as in the previous years. We will study how the presence of a particular type of frictions, limited commitment, significantly affects the impact of monetary policy and can explain the different effects observed in recent years. This study could shed light on the conduct of monetary policy, which will depend on the beliefs in the credit market and the firm size-productivity distribution.Project 2: "Search-and-matching for Liquidity in Financial Markets and Government Policies"According to World Bank data, between 2000 and 2013 in China, the quantity of money (M2) grew at a yearly rate of 16.2%: in the same period, the average yearly inflation rate was 2.4%, and the average yearly real GDP growth rate 8.7%. This means that, even after taking into account the high real GDP growth, the inflation rate in China has been systematically lower than what one would expect on the basis of the money supply growth rate.Chinese financial markets are still not fully developed, and many privately issued assets are not very liquid. As a result, besides the transaction motive, economic agents' hold money also because of liquidity needs. The purpose of this project is to study how the higher liquidity needs (due to the low liquidity of the financial markets) affect the relations between monetary policy, inflation and economic growth, when beliefs about liquidity affect market participations. We will apply the study to understand the Chinese practice mentioned in the beginning, and discuss whether it is sustainable. We will study these issues by introducing asset liquidity frictions in an otherwise standard macroeconomic framework. In contrast to exogenous asset liquidity, expressed by a fixed fraction of assets sellable in a given period, endogenous asset liquidity is micro-founded and suitable for policy analysis. Project 3: "Long Run Herd Behaviour and Volatility Clustering in Financial Markets"In the third project, we turn to another form of financial frictions, asymmetric information. Financial markets are crucial for good investment decisions. The ability of prices to aggregate dispersed information is fundamental for an efficient allocation of resources. We will study the informational efficiency of the Chinese financial markets through the use of novel financial markets models, with a specific focus on learning and herding. We will also study why asset prices exhibit time-varying volatility and the extent to which this is related to herd behaviour. We will then estimate the models using transactions data for the Chinese stock exchanges obtained from Wind Info. The structural estimation will allow us to quantify the drivers of herding and asset prices' time-varying volatility and their effect on market efficiency.