变量方法

变量方法

约翰森(1988)提出了最大似然估计方法对多变量协整测试。方法可以测试co-integrating向量的线性约束,并解决测试问题的对称和均衡条件的准确性。three-variable系统相比,两变量系统使用更多协整技术。但对称和均衡条件往往拒绝;在购买力平价回归参数通常有很大的理论价值和估计的价值之间的差距。在两步协整方法这可能是由于少量样本偏差,问题仍然存在,无论使用大量的样品或Johansen的方法。认为这可能是由于样本数据的时间跨度太短,测试意味着实际汇率的恢复。这就是所谓的计量经济学的效率低下。效率低下的主要原因是一些样品和信息。弗兰克尔(1986)是第一个发现单位根测试效率低下的人,他相信当我们只使用十年或十年以上的数据来测试实际汇率是否生成由一个随机游走过程,拒绝零假设的趋势仍然很低,即使实际汇率是固定的。这种观点被许多学者证明后,果脆&罗格夫(1995),等洛锡安和泰勒(1996)等等。作为传统的单位根检验的测试值较低,研究人员增加了样品在两个办法来解决这个问题:(1)利用大跨度或长期的数据,(2)使用来自不同国家的时间序列数据,这是面板数据方法。

变量方法

Johansen (1988) proposed a maximum likelihood estimation method for multivariate co-integration test. The method can test the linear constraints of co-integrating vectors, and has solved the problem of test accuracy of symmetry and proportionality conditions. Compared to three-variable system, two-variable system uses more co-integration techniques. But the symmetry and proportionality conditions are often rejected; parameters in the PPP regression usually have a great gap between the theoretical value and the estimated value. In the two-step co-integration method this may be caused by the small amount sample bias, and the problem still exists no matter using the large amount of samples or Johansen’s method. It is argued that this may be because the time span of the sample data is too short to test mean reverting of the real exchange rate. This is called inefficient in econometric. The main reason of inefficient is few samples and information. Frankel (1986) was the first one who found the unit root test inefficient, he believed that when we use only ten or more than ten years of data to test whether the real exchange rate is generated by a random walk process, the tendency of rejecting the null hypothesis is still very low even if the real exchange rate is stationary. This view is proved by many scholars later, such as Froot & Rogoff (1995), Lothian & Taylor (1996) and so on. As the test value in traditional unit root test is low, the researchers expanded the sample in two ways to solve this problem: (1) using large-span or long-term data, (2) using cross time series data from different countries, that is panel data methods.

相关的论文代写的话题