Measuring And Analyzing Provincial Coincident Index With Mixed-Frequency Data

Economic coincident index is usually used to monitor and track business cycle.As a key area of macroeconomic research,accurate measurement of the economic cycle is undoubtedly an important prerequisite for policy regulation.Scholars have made a lot of achievements and consensus on the construction of coincident index or the monitoring of economic cycle,but there is still room for improvement in the following aspects.Firstly,most of the existing literatures describe the economic cycle by single variable or the same frequency economic indicators,and there are few literatures on the measurement of economic prosperity coincident index based on mixed-frequency data.Secondly,empirical studies on different regional economic cycles focus more on synchronization validation between regional economic cycles and national economic cycle,or on explaining the influence and the contribution of different variables to economic fluctuations.There is hardly any way to monitor the economic operation of different regions by constructing a coincident index of regional economic cycle.Thirdly,the existing literature more likely investigates the synergistic characteristics of different regions,but the description of stage characteristics is insufficient.It is difficult to objectively capture the economic cycle state switching of each region,which is unproductive to policy makers to formulate policies efficiently.Based on the previous research,this paper will mainly use the mixed-frequency data Markov regime-switching model to construct the provincial economic prosperity coincident index,explain and compare the economic cycle characteristics of each province.This paper monitors the economic operation of each province through the Markov Regime-Switching Mixed-Frequency Dynamic Factor Model,and deeply depicts the co-movement and stage characteristics of the provincial economic cycle,which is conducive to understanding the regional differences of each province on the basis of the overall rapid economic development of China,and also makes up for the blank of the construction of the economic prosperity coincident index at the provincial level,and the provincial economic monitoring is of great significance in the context of policy adjustment and control.Based on the dynamic factor model and its extension,this paper implements three provincial economic coincident index measurement methods and makes an empirical comparison.The synergistic change of macroeconomic variables can be described by an implicit factor.For this reason,this paper first establishes a dynamic factor model to capture the co-movement of economic variables.In order to comprehensively utilize the most important macroeconomic index of GDP,this paper makes use of the mixed-frequency data based on the dynamic factor model,and obtains more accurate measurement results about the economic cycle.In view of the stage and asymmetry in the economic cycle,this paper introduces the Markov regime switching model to identify the stage characteristics of the economic cycle of each province.This paper realizes the construction of the provincial economic coincident index and sucessfully captures the characterization of the synergy and stage characteristics of the provincial economic cycle.It not only truly reflects the specific and common characteristics of each province,but also accurately grasps the economic operation situation of each province,which provides an important basis for macroeconomic control and policy analysis of each province.