趨勢周期分解理論與我國經(jīng)濟的周期
[Abstract]:The economic cycle phenomenon appearing alternately between expansion and contraction in the market economy has always been the focus of macroeconomics. Since Keynes, every macroeconomic school that has appeared successively is trying to create new theories to explain the economic cycle. How to evaluate these competing theories has become macro economics. The main content of the study. The empirical research based on the macroeconomic statistics is the main method to evaluate the economic cycle theory, and the premise of these empirical studies is to extract the periodic components in the macro-economic data. This is the focus of this article, that is, the trend cycle decomposition method in.2004 years. Research in the field has gradually increased, but it is still in the stage of application of various decomposition methods.
This paper divides the trend periodic decomposition method into the single variable decomposition method and the multivariable decomposition method according to the different methodology, and the former can also be subdivided into the method based on probability theory and the filtering method. The structure of this paper is also arranged accordingly. The main contents and innovations of this paper are summarized as follows.
In the field of univariate trend periodic decomposition, this paper has the significance of theoretical innovation. In view of the "anti sign" problem of the periodic component of BN decomposition, which has not been thoroughly solved at present, the research is carried out from the perspective of methodology, and the quantitative relationship between this phenomenon and the persistence metric is established. The persistence of the difference ratio is more than 1, which indicates that the sequence has a strong persistence, and the "anti sign" problem of the periodic component will appear, otherwise it will not appear. This result shows a relatively clear theoretical innovation. This paper also finds that the periodic component of the unobservable component model also has the "anti sign" question. The above two aspects of theoretical research are the first time in the trend cycle decomposition field.
On the basis of analyzing the methodology of single variable decomposition, this paper aims at the periodic, stability, timeliness and consistency criteria of the decomposition of the decomposition, and evaluates the various decomposition methods. The periodic concern is whether the periodic component of the decomposition is in accordance with the economic cycle that needs to be considered. After adding new observation values, the degree of the periodic component of the latest decomposition deviates from the previous periodic component. The time is concerned that the end value of the periodic component of the decomposition can accurately reflect the status of the variable. The study of the actual GDP variables in the country shows that the CF filter is relatively suitable for extracting its periodic components. From the perspective of comparative study, the standards proposed in this paper can better evaluate various decomposition methods, thus the empirical decomposition is similar to the theoretical basis of the macro data provision, which is similar to our country's GDP, thus reflecting the creation of theory and application. New meaning.
In the field of trend periodic decomposition, multivariable decomposition is the most frontier and the most difficult research direction. This paper traces the main research literature and clearly interprets and expresses its development and decomposition theory from the perspective of methodology. From the literature, so far, there is no relevant research work in this field at home. In particular, the multivariable trend periodic decomposition is based on the non stationary time series theory. After considering the interaction between the various trends and the interaction between each cycle, the multivariable decomposition method is taken into account. The theory of sequence related common feature proposed by Engle and Kozicki (1993) is used to study the interaction between multiple cycles. On this basis, the trend periodic decomposition of multivariables is realized by the VEC model containing cointegration and sequence related common characteristic constraints. On the basis of the study of the multivariable decomposition methodology, this paper is present to our country. The study of real economic problems is applied. According to the study of the monetary and economic operation and the price level, the monetary factor plays an important role in the economic cycle. The supply of money is the first indicator of the economic operation. The research on the price and inflation of agricultural products shows the phase of the price cycle of agricultural products and the CPI cycle. The large fluctuations in the price cycle of agricultural products, to a large extent, are the impact of factors such as the rise and fall of the price of pork, and the strong dependence of the monetary cycle with the CPI cycle shows that the monetary policy goal of our country is alternately converted between inflation and growth. Accordingly, the price of the agricultural product is also given in the price of agricultural products. In the rising period of the grid cycle, inflation control should be guided by the policy of restraining the prices of agricultural products from the supply side.
To sum up, the innovation of the theory and methodology of this paper can be summarized as the study of the "anti sign" problem of the periodic components of the BN decomposition and the UC model decomposition method, and the evaluation of various single variable decomposition methods through the establishment of evaluation criteria. The application innovation is embodied in the new multivariable trend periodic decomposition of this measure. The economic method, from the point of view of important but not fully paid attention to, studies the problems of economic operation and inflation in China, and draws realistic conclusions and policy suggestions with practical value.
【學(xué)位授予單位】:華中科技大學(xué)
【學(xué)位級別】:博士
【學(xué)位授予年份】:2013
【分類號】:F224;F124.8
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