Application of Quantile Regression in the Analysis of the Fluctuations in the Price of Chicken meat in Iran

Short-term chicken supply (for example, over a year) lacks the flexibility to respond to demand fluctuations, which can negatively impact the welfare of consumers and producers. Thus, using various methods to identify these fluctuations can be useful in lowering or adjusting the market's price and equilibrium.

Using quantile regression and monthly data (April 2002 to March 2015), this study examined how short-term chicken price fluctuations in the Iranian market responded to related cost factors.

The results demonstrated that the confidence intervals generated by the quantile regression between quantiles 0.5th and 0.95th can indicate the range of possible price fluctuations. The economic values forecasted by this model not only help to analyze cost-effective factors and improve forecasting accuracy, but they also benefit from risk management in the agricultural market.

Among the cost factors influencing chicken prices, day-old chick (DOC) and consumer price index (CPI) had the greatest influence on price fluctuations. Coherent hatching planning based on seasonal needs, as well as price insurance for day-old chicks and a reduction in government interventions at certain times of the year, can all help to reduce price fluctuations.