This research examines cointegration and dynamics of price transmission among domestic as well as domestic & global and domestic & major supplier's markets of high and low quality rice; and compares the magnitude of price transmission and speed of adjustment between the high and low quality rice markets. Unit root tests, the consistent momentum threshold autoregressive (M-TAR) models and vector error correction models (symmetric and asymmetric) are employed in this study. The results showed that the provincial markets of high and low quality rice are cointegrated with their respective market of Kabul, exception being Kandahar and Maimana markets of low quality rice. They are also cointegrated with their corresponding Pakistani and global markets. Evidence of short-And long-run asymmetric adjustment among the provincial markets of high and low quality rice with respect to their corresponding Kabul, Pakistani and global markets indicates the presence of persistent and temporary inefficiencies in the rice markets. The short-And long-run speed of adjustment coefficients are relatively larger for high than low quality rice markets, implying efficient and/or remunerative spatial arbitrage in the high quality rice markets. Conversely, the elasticity of price transmission is relatively greater for the majority of low than high quality rice markets pairs. A random shock in Kabul, Pakistani and global markets of high and low quality rice affect their respective provincial markets in varying degrees. In a nutshell, the dynamics of price transmission may be different between the pairs of high and low quality rice markets. This paper illuminates the dynamics of spatial price transmission among the segmented rice markets and emphasizes the need for improving the functioning of rice markets in the country using an integrated approach.
|Number of pages||20|
|Journal||Journal of the Faculty of Agriculture, Kyushu University|
|Publication status||Published - Feb 2017|
All Science Journal Classification (ASJC) codes
- Agronomy and Crop Science