我国热钱流入规模影响因素的实证分析

发布时间：2018-02-26 18:24

本文关键词： 热钱结构转变向量误差修正模型　出处：《吉林大学》2014年硕士论文　论文类型：学位论文

【摘要】：2007年2月美国次级贷款质量问题浮出水面，2007年4月4日美国次贷危机正式爆发，2007年世界股指均出现大幅下滑，2008年开始，美联储紧急大幅降息75个基点，中美利率开始出现倒挂，2008年4月8日，IMF称全球次贷亏损一万亿美元，2008年9月15日雷曼兄弟宣布破产。而与此同时，2007年，中央银行10次提高银行法定准备金率，5次提高利息率，2010年6月实行二次汇改，进一步加大了人民币弹性。在2009年以来，欧美发达国家通过向金融市场投放流动性为代价的量化宽松货币政策来使经济复苏，造成了热钱在市场上的活跃，增加了我国的热钱监控压力，对我国造成了非常不利的影响。本文旨在研究热钱规模流动趋势以及热钱影响因素，研究得出我国今后在面对危机时应针对哪些方面对热钱进行控制。本文将从（1）热钱的规模测算方式；（2）热钱规模流动趋势分解；（3）时间序列结构转变检验；（4）热钱规模长期均衡关系；（5）热钱规模短期波动效应；（6）热钱影响的主要因素这几个方面进行研究。在直接法、间接法、全口径测算方式这三种方式比较下最终选择间接法作为接下来研究的依据。而BP滤波方法将热钱规模进行趋势分解后发现，中国的热钱规模正处于大量流出的长期趋势，而短期波动幅度也有明显加大，这说明我国依然是一个很大的热钱集散地市场，并且我国热钱压力正在增大，加大了监管的难度。接着，我们选用GDP增长率、CPI增长率、中美利率差、NDF（美元兑人民币远期（一年期）汇率）、上证A股综指、国房景气指数作为具有代表性的研究变量对热钱流动进行实证分析。通过Bai-Perron结构转变检验又发现，我国的热钱系统在经历了全球性的次贷危机后并没有出现结构转变，即热钱投资的选择模式并没有改变。通过协整检验发现的五个长期均衡关系表明中美利率差、GDP增长率是推动整个系统变化的最主要因素。用向量误差修正模型继续探讨热钱的短期波动影响因素，，其中只有NDF和国房景气指数是对热钱流动短期波动产生影响的因素。另外，国房景气指数是比较重要的影响因素，不论是脉冲检验还是方差分解都体现出国房景气指数解释了大部分的影响变化。基于以上结论，本文提出了努力维持我国宏观环境的稳定；维持国内金融系统的稳定，尤其是利率和汇率；维持房地产市场的合理增长等政策建议。
[Abstract]:In February 2007, the quality of subprime loans in the United States came to the surface. In April 4th 2007, the subprime mortgage crisis officially broke out in the United States. In 2007, the world stock indexes all showed a sharp decline. Since 2007, the Federal Reserve has cut interest rates by 75 basis points in an emergency manner. Interest rates in China and the United States began to rise upside down, with the IMF saying a $1 tillion global subprime loss on April 8th 2008 and Lehman Brothers' bankruptcy on September 15th 2008. Meanwhile, in 2007, The Central Bank raised the bank's legal reserve ratio five times and the interest rate five times. In June 2010, the Central Bank implemented a second exchange rate reform, which further increased the flexibility of the renminbi. Since 2009, Developed countries in Europe and the United States have made the economic recovery by pouring liquidity into the financial market at the expense of quantitative easing monetary policy, which has caused hot money to become active in the market and increased the pressure on our country to monitor hot money. The purpose of this paper is to study the trend of hot money flow and the influencing factors of hot money, and to find out which aspects of hot money should be controlled in the future in the face of crisis. In this paper, we will analyze the scale of hot money (1) the scale of hot money (2) the trend of flow of hot money (3) the structural transformation of time series, test the long-term equilibrium relationship of scale of hot money (5) the effect of short-term fluctuation of hot money scale and the influence of hot money on the main factors. Several aspects of the study. In the direct method, The indirect method, the full caliber measurement method and the final selection of the indirect method as the basis for the next research under the comparison of the three methods, and the BP filtering method, after the trend decomposition of the scale of hot money, was found. The scale of hot money in China is in the long-term trend of a large outflow, and the short-term fluctuations have also increased significantly. This shows that China is still a large hot money distribution center market, and the pressure on hot money in our country is increasing. We then chose the GDP growth rate to match the GDP growth rate, the China-US interest rate difference, the forward (one-year) rate of the US dollar to the renminbi, and the Shanghai A-share Composite. The national housing boom index is used as a representative research variable to analyze the hot money flow. Through the Bai-Perron structural transformation test, it is found that the hot money system of our country has not experienced the structural change after the global subprime mortgage crisis. That is, the choice mode of hot money investment has not changed. The five long-term equilibrium relations found by cointegration test show that the growth rate of GDP of interest rate difference between China and the United States is the most important factor to promote the whole system change. The vector error correction model is followed by the vector error correction model. Continue to explore the factors that affect the short-term fluctuations of hot money, Among them, only NDF and the national housing boom index are the factors that affect the short-term fluctuations of hot money flows. In addition, the national housing boom index is a relatively important factor. Both pulse test and variance decomposition show that the national housing boom index explains most of the changes. Based on the above conclusions, this paper proposes to maintain the stability of the macro environment of our country; to maintain the stability of the domestic financial system. In particular, interest rates and exchange rates; to maintain reasonable growth in the real estate market and other policy recommendations.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F224;F832.6

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