H. Sherafatmand; A.A. Baghestany
Abstract
Introduction: Agricultural prices are one of the most important tools for resource allocation in an economy. Evidence suggests that, agricultural prices in comparison with other goods prices have more volatility. If these volatility leads to asymmetric price transmission, this subject will be very important. ...
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Introduction: Agricultural prices are one of the most important tools for resource allocation in an economy. Evidence suggests that, agricultural prices in comparison with other goods prices have more volatility. If these volatility leads to asymmetric price transmission, this subject will be very important. In other words, if changes in the market price are not absolutely transferred between levels, asymmetric price transmission has occurred, which is leading to increased marketing margin. Price transmission in different market levels related to the marketing efficiency, which also affected the welfare of producers and consumers. Dates, among all horticultural crops, with a share of 10% of the planted area in our country, after the pistachios and grapes were located in the third highest level, and with 6.5 percent of the total horticulture products after grapes, apples and oranges, are in the fourth highest level. Iran Dates from global production share is 14% in 2012. Despite of important Dates, Dates producers, suffer from volatility and low price of this product. Dates owners considerable expenses for crop production, including purchasing, supply of fertilizers and pesticides, irrigation (water and electricity costs) and the cost of labor in planting and harvesting spent, but in most cases they not only benefit from production, but also sell it below cost. According to the phenomena that Dates owners are not marketed through cooperatives, so farmers are the victims and intermediaries benefited. In such an environment, the marketing of dates, have a significant impact on how prices transmitted. In policy debates, asymmetric price transmission is a phenomenon that arises from imperfect competition in the market and it would be imposing additional costs to consumers. Having this information will help policy makers to adopt the correct policies.
Materials and Methods: To achieve the aims of this study which determines the mechanism of price transmission in dates market bivariate GARCH model was used. Developments of ARCH and GARCH models take into account the nature of the phenomenon Volatility in financial and prices error component regression equations. ARCH model was first introduced by Engle and augmented GARCH model was first introduced by Bollerslev. Due to Conditional variance Heteroscedasticity, ARCH and GARCH models are widely used but little attention has been to this interaction. For this purpose, bivariate GARCH models developed. This study determined the mechanism of price transmission in date's market, over the period 1361: 1-1391: 4 with Diagonal VECH Bivariate GARCH model.
Results and Discussion: With the implementation of augmented Dickey-Fuller test, it was found that the time series producer price index and the consumer price index over the period 1361:1-1391:4 are stationary in first difference. In this study, also Hegy test used for stationary of variables. In this test the unit root hypothesis tested with different periods (for the monthly data used in this study up to 12 repetitions will examined). Next, Johansen co-integration test results showed that there was a long-term relationship between the producer price index and the consumer price index. Granger causality test results indicated that there was a one-way causal relationship from consumer price index to producer price index. The results of this study indicated that the producer price index volatility with one lag has a positive and significant impact on its current volatility. As the results indicated, the covariance coefficient is statistically significant, indicating the volatility spillover between the two levels of the market. The spillover of volatility indicated uncertainty in the retail market and in producers market. The results also indicated that a one unit increase in the consumer price index cause an increase in producer price index less than unity (0.003).
Conclusions: the price transmission in Dates market is incomplete. So it is recommended to policy makers and government for reducing price risk and producers stabilize income, perform market regulation policies and protection policies like as steward devices on the market to buy dates at harvest time and, it needed structural support like appropriate and timely packaging and ware housing which Can lead to an increase in the welfare of producers and consumers as well as reforms in incomplete dates market.
JEL classification: Q1-Q23-E3
R. Moghaddasi; H. Sherafatmand; A.A. Baghestany
Abstract
AbstractComparison of food prices in different periods, indicates fluctuations and continually upward trend. Any change in agricultural sector variables, as main food supplier, will affect food price. Productivity shocks and production gap are examples of such variables. In this paper ,Hodrick Prescott ...
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AbstractComparison of food prices in different periods, indicates fluctuations and continually upward trend. Any change in agricultural sector variables, as main food supplier, will affect food price. Productivity shocks and production gap are examples of such variables. In this paper ,Hodrick Prescott and Kalman filters are used as generators of productivity shocks and production gap series. Also for analyzing the impact of these variables on food prices growth during the 1976-2007 Johansen Cointegration test and VECM Model are applied. Main results indicated that, productivity shocks have a reverse effect while production gap has a positive and significant effect on food price. Also among all surveyed variables, the effect of negative productivity shock on food price is the greatest. Therefore more attention should be paid to management of negative shocks in comparison with positive ones. Productivity promotion and bridging the gap between actual and potential production can lead to control of agricultural prices.JEL classification: C22-E2-E3
