| A common saying goes,“hog prevails and grain matters”.In other words,pigs have been playing an important role in the national economy and people’s livelihood since ancient times.As the world’s largest pork producer and marketing country,the importance of maintaining pork price stability for China is self-evident.However,the relatively extensive consumption of pork in China and the regional imbalance in hog breeding have led to unbalanced supply and demand in the market,and the "trans-regional" transmission of pork,thus the prices of pigs and pork in China enter a strange circle of periodic fluctuations.Therefore,by clarifying the spatial correlation and dynamic evolution of hog price fluctuation in China and identifying the factors that affect hog price correlation in different provinces,We can get a comprehensive understanding of the interactive relationship between hog prices in different provinces under the background of continuously updating industry status in China and government departments make forward-looking policy of price stability and regional readjustment,which is of great practical significance to promote the safe and healthy development of hog industry in China.The main research contents and empirical conclusions of this paper are as follows:(1)Analysis on the fluctuation and characteristics of hog Price.Through sorting out the scale and consumption of hog industry in different provinces,it is found that there is indeed an imbalance between hog breeding and pork consumption in China.By using the Census X12 seasonal adjustment method and HP filtering method,we found that the number of wavelet peaks in the period of hog price fluctuation in China becomes more and more with the obvious higher frequency and more complicated trends.Hog prices in different provinces of China interdependent and interrelate with the existence of spatial price heterogeneity.(2)Static Analysis on Spatial correlation of hog Price fluctuation in different provinces.Based on the daily data of hog prices in 22 provinces(autonomous regions and cities)of China from March 4,2010 to March 11,2019,we applied the Relational degree Measurement Framework based on Generalized Predictive error Variance decomposition proposed by Diebold and Yilmaz(2014),and found out that the overall correlation levelof pig prices in different provinces of China is as high as 87.98% from the point of view of the total correlation degree.From the view of the overall directional correlation degree,there are differences in the influence degree of hog price fluctuation in different provinces on other provinces,among which Jilin and Henan have the largest positive net correlation degree and they are the price leader of hog price system in different provinces of our country.And Chongqing and Shanghai have the largest negative net correlation degree,and they are price recipients in the price system of hog in different provinces.In terms of pairwise directional correlation degree,the price correlation degree of hog in the province of main hog producing area and geographical location is generally higher,among which Jilin Province and Heilongjiang Province,as the main producing areas of hog,have the highest correlation degree of the hog price.(3)Dynamic Analysis on Spatial correlation of hog Price fluctuation in different provinces.In this paper,the time-varying characteristics of the correlation degree are analyzed by combining the rolling window regression and the network topology diagram on the basis of the measurement framework of the correlation degree.The empirical results show that it is time-varying,affected by epidemic situation,related policies and "pig cycle" transformation,thus it can be divided into three stages.From the point of view of the total directional correlation degree,the overall trend of the directional correlation map affected by the other provinces is more stable and the fluctuation range is smaller than that of the directional correlation map which affects the pig price in other provinces.Most of the main hog production areas have a positive net correlation with the prices of hog in other provinces of the system,and the degree of impact is greater except for individual periods.While the net price correlation between Chongqing and Sichuan provinces and other provinces was negative because of consumption,distance and the degree of large-scale breeding.From the point of view of pairwise directional correlation degree,the correlation degree of pig price between different provinces in different stages of our country is dynamic,and the whole correlation degree in the system has the trend of enhancement.At the same time,the reliability of the results is further ensured by changing the prediction step size and rolling window width to test the robustness.(4)Spatial correlation Analysis of Swine Price fluctuation in different provinces.In this paper,the QAP method was used to quantitatively identify the factors affecting spatial association.It was found that geographical location,the influence of main pig producing areas and the extent of large-scale pig breeding could explain that the net directional relationship between pig prices in different provinces and regions in China is 76%.All of them had a significant positive effect on the spatial correlation of hog price fluctuation in different provinces.The innovations of this paper are as follows:(1)the research framework is new.Based on the correlation degree measurement framework of generalized predictive error variance decomposition,this paper integrates the three dimensions of price between different provinces,one province and the whole system,and the whole system into an analysis system and empirically tests the spatial correlation level and direction of hog price fluctuation.(2)the angle of study is novel.Using the rolling window regression method and the network topology diagram,this paper analyzes the spatial correlation degree of pig price fluctuation in different provinces from a dynamic point of view,which makes up for the limitation that only full sample static analysis may cause deviated result because of the breaking point of the data.(3)the research content is more thorough.At present,the factors that affect the spatial transmission or market integration of pig price fluctuation are mostly on the theoretical level.In this paper,the QAP method is used to quantitatively analyze the factors affecting the spatial correlation of pig price fluctuation in China through the "relational data".In a word,This paper makes an effective supplement to the relevant empirical tests. |
