Strategic Decision in Long and Short Run for Cross-Country Commodity Market in the Post-COVID 19 Era

Accepting the price association and dependencies for agricultural products is one of the biggest challenges mainly when there is an outbreak of Covid-19. As per this issue, the present paper considers few selected food crops, i.e., corn, wheat, rice, and soy for three different countries, i.e., USA, India, and China to identify price movements and price associations in the short and long run. After understanding the nature of data, the cross-country causal effect analysis is conducted through Granger causality for all the crops that state a unidirectional relationship between countries. This output supports the evaluation of measuring the long-run and short-run association through the vector error correction model that states the soy price of the USA can be tracked from the movement of India soy price in long run with a high degree of positive relation as India is the highest producer of soy with a cheaper rate that is widely imported by the USA for its organic poultry and dairy feed. Even the price of corn China can be followed in the long run from the price of USA corn but it establishes a negative relation. Similarly, the USA price of rice can be tracked from the China price as it is the major rice producer and exporter globally. While the prediction of wheat prices for India can be well-known from the price movement of the USA in both the long run and short run with a negative effect. This outcome is well accepted as the data series has mean reverse throughout the period. This outcome is beneficial mainly to the farmers in price fixation and decision on trading at the national or international platform, and this is also useful for the investors to invest in agro sectors in post-Covid-19 eras rather than investing in an unpredictable stock market or indices.