Analysis Of Influencing Factors And Trend Prediction Of China’s Macro Economy Under The Impact Of COVID-19

In January 2020,the Novel Coronavirus outbreak broke out in Wuhan,Hubei Province of China,and then spread rapidly to various regions of China due to its strong infectivity,which not only seriously threatened people’s lives and health safety,but also brought social operation to a standstill and economic development suffered a heavy blow with the implementation of domestic epidemic prevention measures.As the biggest risk to the world economy since the 2008 international financial crisis,COVID-19 has had a significant and far-reaching impact on China’s economy and even the world economy.In the post-epidemic era,how to analyze the changes of the influencing factors of China’s macroeconomic structure and predict its future trend is still an important issue for macroeconomic researchers.According to certain principles of index selection chosen 51 macroeconomic indicators,build a macroeconomic indicators system,according to the characteristics of the thick tail of macroeconomic data,the innovation in the higher dimensional ellipsoid approximation factor model robust two-step estimation method(RTS)application in China’s macroeconomic structure factors influencing the change and trend prediction research,the concrete from the following three aspects.Firstly,MKER(Multivariate Kendall’s tau Eigenvalue Ratio)method and MKTCR(Multivariate Kendall’s tau Transformed Contribution Ratio)method are used to estimate the number of common factors potentially affecting macroeconomic structure from a dynamic perspective,and the relationship between the impact of sudden major economic events and the number of common factors is explored.The study found that the number of potential common factors changes significantly when the macro economy faces a shock like COVID-19.Then this article will high-dimensional ellipsoid approximation factor model is applied to the macroeconomic panel data we collected,the RTS method is utilized to extract the first four common factors and according to the actual load matrix gives each public factor,the study found that the first four common factor score after new crown outbreak in 2020 also made corresponding change,Studying the variation trend of each factor score with the epidemic situation is of great significance to ensure the normal operation of all areas of macro economy during the response to COVID-19.At the same time,we find that the first common factor can be interpreted as the factor that best represents national economic development within the statistical interval,and the main variable it contains represents the main melody leading economic development at present.Next we do key research of the first public factor,to the point of view of dynamic,based on the rolling window method,analysis with the passage of time,the effects of the first public what kind of changes have taken place in the main economic variables,obtained during various periods,especially the new champions of the main factors influencing the macro economic structure change tendency.Finally,this thesis applies the ellipsoid approximation factor model to the rolling prediction of macroeconomic variables,and the results show that compared with the traditional factor model,the ellipsoid approximation factor model can extract the common components of macroeconomic variables more robustly,and has a better prediction effect when the macro economy is faced with the impact of COVID-19.