Asymmetric Effects of Local and Global Variables on Domestic Food Prices in China: An Evidence from Quantile on Quantile Regression Technique

The existing research investigates the impact of global and national variables on local food prices. This study adds to the current research by examining such impact at various quantiles, frequencies, and time periods. Utilizing data from January 2004 to June 2021, our research incorporates six global factors and three domestic factors as explanatory variables. Furthermore, this study employs cutting-edge econometric techniques such as Quantile-on-Quantile Regression (QQR), Wavelet Coherence (WC), and Granger Causality in Quantiles (GCQ). Similarly, this research utilizes the Quantile Regression (QR) method to assess the robustness of the results. Results based on the GCQ technique indicate that the association between the variables exists at most quantiles, except for the lowest, and middle quantiles for all variables. Moreover, the WC findings demonstrate a strong correlation between the determinants of local food prices and their occurrences at various moments and intervals. Likewise, QQR results indicate that the impact of independent variables on local food prices varies across quantiles. The QR technique also supports these results. Finally, our research suggests policy recommendations based on the findings of this study.