Investigating the causality relationship between the exchange rate and the commercial quantity of fertilizers in Iran using of Markov Switching approach

The real exchange rate is considered a key variable due to its interrelationship with other macroeconomic variables and plays an effective role in the export and import of agricultural goods and inputs. Iran's agricultural sector is one of the most dependent sectors on the exchange rate, and as a result, fluctuations in the real exchange rate can have significant effects on the export and import of agricultural inputs such as chemical fertilizers. Considering the effect of the Covid-19 crises and the Ukraine war on real exchange rate fluctuations and the importance of chemical fertilizers trade in current conditions, as well as observing the non-linear behavior of variables, the purpose of this study is to investigate the non-linear causality of real exchange rates and the value of import and export of chemical fertilizers Using monthly data from April 2015 to September 2022, using the nonlinear hybrid wavelet-Markov switching approach. The results of data denoising using wavelet transformation showed that the error rate flowed in a relatively turbulent domain and the data contained some kind of noise. The results of the Markov switching model also showed that the relationship between the real exchange rate and the value of export and import of chemical fertilizers is non-linear. Also, there is a one-way causality relationship from the real exchange rate to the export value of chemical fertilizers, and only when the import value increases, there is a one-way causality relationship from the real exchange rate to the import value of chemical fertilizers. Therefore, in order to reduce real exchange rate fluctuations, it is suggested to diversify the import sources and export destinations of chemical fertilizers, as well as create bilateral and constructive interactive relations with the target countries in order to reach a win-win agreement.