The Evaluation of Price Volatility of Beef and Chicken and Livestock’s Major Inputs in Iran

Introduction: In recent years, price volatility of chicken and beef, along with volatility in livestock inputs have become one of the main problems of the livestock and poultry industries in Iran. Price volatility which in fact is the fluctuations of the price variances (logarithm of price changes), increasing production risk, investment insecurity, and predicting a decline in producer profits, also endangers consumer spending behaviors and food security. This is the fact especially in countries that do not have effective price policies. One of the important issues in the production of animal and poultry protein products is the supply of needed inputs, which imports a significant portion of the country's consumer demand for livestock and poultry inputs such as corn, barley and soybean meal. According to the Customs Statistics of the Islamic Republic of Iran in 2017, imports of corn, barley and soybean meal were 7283, 2563 and 1269 thousand tons, respectively. Therefore, due to the dependence of domestic production of these products on imported inputs, price fluctuations of these inputs can also lead to price fluctuations in protein products. Therefore, evaluating the volatility and price fluctuations of protein products and the inputs needed and solutions to counter the negative effects of these fluctuations is one of the policy makers' goals in this regard. The purpose of this study was to evaluate and analyze the price volatility of chicken and beef and their inputs including corn, barley and soybean meal. By identifying price volatility behavior, we can reduce this volatility by using appropriate policy tools.
Material and methods: For this purpose, we used ARCH family techniques (both the linear and non-linear models) and monthly time series data from 2002 to 2017. To this end, the ARCH test is first used to investigate the effects of ARCH (heterogeneity variance) on the series of returns on the prices of the goods under investigation, and if these effects are confirmed, these effects are linear or nonlinear with the Engel & Neg (1993) nonlinear test. Finally, linear and nonlinear GARCH models are used to analyze price volatility. For the studied series, nine patterns of GARCH, EGARCH, GJR-GARCH, TGARCH, SAGARCH, PGARCH, NGARCH, APGARCH and NPGARCH were estimated.
Results and discussion: Statistics analysis on the probability distribution characteristics of the price return series of show that the distribution normality for the series studied with the exception of corn and chicken has been rejected and only the two aforementioned series have normal distribution. Based on the results presented, all series except for chicken have positive Skewness . This indicates that the probability density on the left is greater for the distribution of maize, soybean meal, barley and beef. This means that the negative returns in these series are likely. The kurtosis, except for corn and chicken, which is approximately equal to the kurtosis value of the normal distribution, is greater in the other series than the normal elasticity. This means that the average monthly fluctuations in corn and chicken prices are less likely to occur than barley, soybean meal, and beef. Due to the time series nature of the data used in this study, the existence of a single root in the yield series of inputs and outputs was tested. The existence of a single root for the series of returns on the prices of the inputs and products under study is rejected, in other words, the series are at static or I (0) levels. Therefore, ARCH models can be used to model the price returns of these products and inputs. Findings show that non-linear ARCH effect confirmed for all commodities except corn. According to results, the EGARCH model is the best model for barley and soybean meal price series volatility modeling and SAGARCH model is the best model to survey volatility in price series of chicken and beef. Moreover, volatility in the prices of above mentioned goods has an asymmetric response to positive and negative shocks. The volatility in the prices of these commodities also has an asymmetric reaction to positive and negative price shocks, so that the effect of positive shocks on price volatility is greater than the effect of negative shocks. Estimated patterns show a high degree of shocks stability, low price adjustment rates, and price volatility of corn, soybean meal, and beef. However, due to the high rate of price adjustment in the barley and chicken market, the shocks are not sufficiently stable. Although various policies have been implemented by the government to manage the market of inputs and products under study, the price volatility in the market for these items is noticeable and significant, according to the results. In other words, the management of market volatility and price fluctuations was not desirable despite the use of various policy tools. Given that the effect of positive and negative shocks on price volatility of inputs and products excluding corn is asymmetric, therefore, it is recommended that policy makers plan the market for these commodities based on the type of shocks ( (Positive or negative) and their sustainability, and pave the way for reducing price volatility in the commodity market. Therefore, it is suggested that policies implemented to reduce the price volatility of these commodities be reviewed and alternative policy packages in this area be designed and implemented. Since these input as a major input in the broiler industry of the country shows high volatility and volatility in this market may be transmitted to the market of products of this industry, such as chicken and also a major part of imported inputs. Imports will have a significant impact on the price of these products, so it is recommended that in the short term a sufficient amount of this input be bought and stored so that both the input market and the poultry market are more stable and in the long run the government better With appropriate supportive policies to reduce inappropriate and unmanaged dependence on imports and production Move it.