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   بررسی محرک‌های قیمت انواع گوشت در ایران با استفاده از مدل خودتوضیح‌ برداری ساختاری پانلی (panel-svar)  
   
نویسنده حیدری رضا
منبع اقتصاد و توسعه كشاورزي - 1401 - دوره : 36 - شماره : 3 - صفحه:265 -286
چکیده    در سال‌های اخیر، نوسانات قیمت گوشت همواره از چالش‌های اساسی بازار گوشت ایران بوده و هر ساله عدم تعادل در بازار آن باعث کاهش رفاه مصرف‌کنندگان و بروز خسارت برای تولیدکنندگان می‌شود. در شرایط کنونی که منابع ارزی کشور محدود و قیمت در بازار گوشت دارای روند افزایشی است، بررسی محرک‌های قیمت انواع گوشت در ایران از منظر اقتصاد خرد و به ویژه زنجیره انتقال عمودی قیمت‌ها می‌تواند راهنمای مناسبی برای سیاست‌گذران و برنامه‌ریزان در اتخاذ سیاست‌های مناسب برای کنترل قیمت و مصرف داخلی این محصولات باشد. هدف از انجام این مطالعه شناسایی محرک‌های قیمت انواع گوشت در ایران با استفاده از مدل panel-svar در 30 استان کشور طی سال‌های 98-1385 است. نتایج حاصل از تابع عکس‌العمل آنی نشان داد که اثر شوک‌های متغیر ارزش افزوده بخش کشاورزی بر شاخص قیمت گوشت، قیمت گوشت گوسفند و قیمت گوشت گاو منفی و روی قیمت گوشت مرغ مثبت است. در حالی‌که اثر تکانه‌های سه متغیر شاخص قیمت نهاده‌های وارداتی دام و طیور (ذرت، کنجاله سویا و جو)، قیمت دام زنده و خود قیمت گوشت روی تغییرات قیمت انواع گوشت (مرغ، گوسفند و گاو) مثبت است. نتایج حاصل از تجزیه واریانس و تجزیه تاریخی نیز نشان داد که تکانه‌های مربوط به متغیر ارزش افزوده بخش کشاورزی کمترین اثر و تکانه‌های خود متغیر قیمت گوشت بیشترین اثر را بر تغییرات قیمت انواع گوشت در ایران دارد. در این راستا برای مهار شوک‌های قیمتی وارد بر قیمت انواع گوشت، مدیریت انتظارات تورمی و استفاده از سیاست‌های حمایتی مناسب در کل زنجیره تولید گوشت از قبیل نظارت بر مراحل تولید و توزیع و مصرف، اصلاح ساختار بازار به جای کنترل قیمت، تامین به موقع نهاده‌های تولید برای تولیدکنندگان، توسعه کشت نهاده‌های دامی در داخل کشور و نیز توزیع کافی و در زمان مناسب برای مصرف‌کنندگان پیشنهاد می‌شود.
کلیدواژه ارزش افزوده بخش کشاورزی، قیمت گوشت، مدل panel-svar
آدرس موسسه پژوهش های برنامه ریزی، اقتصاد کشاورزی و توسعه روستایی, ایران
پست الکترونیکی rezaheidari3631@gmail.com
 
   investigating drivers of the price of meat types in iran using panel-svar model  
   
Authors heydari r.
Abstract    introductionmeat is one of the most important sources of animal protein and plays an important role in human nutrition. in addition, meat is one of the main commodities in the basket of iranian households, so that it included about 20% of food costs in iran. in recent years, fluctuations in meat prices have always been one of the main challenges of the meat market of iran and every year the imbalance in its market reduces the welfare of consumers and causes damage to producers. in the current situation where the iran foreign exchange resources are limited and prices of the meat market has many fluctuations, examining the price drivers of meat price in iran from the perspective of microeconomics and especially the chain of vertical price transmission can be a good guide for policymakers and planners in adopting appropriate policies to control prices and domestic consumption of these products. the purpose of this study is to identify the drivers of the price of meat different types in iran using the panel-svar model in 30 provinces of the country during the years 2006-2019. materials and methodswe use the panel svar methodology developed by pedroni (2013) to analyze the implications of shocks on the price of meat types. defining z𝑖t ≡ (y𝑖𝑡, x𝑖𝑡, s𝑖𝑡, m𝑖𝑡)′, the heterogeneous panel svar model can be formulated as:𝐵𝑖 z𝑖𝑡 = 𝐴𝑖 (𝐿) z𝑖𝑡−1 +   , 𝑖 = 1,…,, 𝑡 = 1, … , 𝑇  and  𝑢it ∼ (0,σ𝑖)where 𝐵𝑖 is the matrix of structural parameters, reflecting the instantaneous relations among model variables, 𝑧𝑖𝑡 is the vector of endogenous variables, (𝐿) is a polynomial of lagged coefficients for ith province. 𝑢𝑖𝑡 ≡ (𝑢𝑦𝑖𝑡, 𝑢x𝑖𝑡, 𝑢s𝑖𝑡, 𝑢m𝑖𝑡)′ is the vector of the structural shocks or innovations in 𝑧𝑖𝑡, the variance-covariance matrix σ𝑖 is diagonal. assuming 𝐵𝑖 be an invertible matrix, pre-multiply both sides of equation (1) by , we get the reduced form var model:𝑧it = π𝑖 (𝐿) 𝑧it−1 + 𝜀it    where π𝑖 (𝐿) = 𝐴𝑖 (𝐿), 𝜀𝑖𝑡 =  𝑢𝑖𝑡 and 𝜀it ∼ (0,ω𝑖)moreover, the variance-covariance matrix ω𝑖 of the reduced form error 𝜀𝑖𝑡 = (𝜀𝑦𝑖𝑡, 𝜀x𝑖𝑡, 𝜀s𝑖𝑡, 𝜀m𝑖𝑡)′  is full rank and no diagonal. the reason is that the errors are correlated between equations, implying that the innovations are not orthogonal. traditionally, when this happens, innovations are correlated with each other and the matrix ω𝑖 can be orthogonal zed by structural cholesky decompositions. this method imposes an economic structure and allows the specific ordering of the panel svar variables. finally, the contemporary matrix 𝐵𝑖 is of the following form:bi = results and discussionthe results of pedroni and cao co-integration test showed that the hypothesis of no co-integration among the variables could not be rejected. the optimal lags length for the panel-var model, using the criterion of schwartz-bayesian, was determined as 2. the unit root test of the circle also showed that the estimated panel-var model provides the stability condition. the results of panel-var granger causality test also showed that there is a direct or indirect causal relationship between all the studied variables. the results of estimating the &matrix of long-term response function in the panel-svar model showed that all estimated coefficients are significant. the results of the impulse response functions (irfs) showed that the effect of shocks of the value added of the agricultural sector in the agricultural sector on meat price index, mutton price and beef price is negative and on chicken price is positive, while the shocks effect of the price index of imported inputs (corn, soybean meal and barley), livestock prices and meat prices are positive on meat price changes (chicken, sheep and beef). the maximum and minimum effect of these variables occurred between the first to the fifth period and their effect pattern is sinusoidal, afterwards shocks continue to be almost constant (or with low amplitude). this result shows that the effect of shocks of meat price stimuli in iran is continuous and stable. the results of analysis of variance and historical decompositions also showed that the shocks related to the value added of the agricultural sector have the least effect and the shocks of the meat price variable have the greatest effect on meat price changes in iran. the results of analysis of variance and historical analysis also showed that the shocks related to the value added variable of the agricultural sector have the least effect and the shocks of the meat price variable itself have the greatest effect on variation of meat prices in iran. this result indicates that the impact of agricultural shocks on the meat price of is relatively weak, in contrast, the impact of shocks of the price transmission especially in the short term (beginning of periods) play a vital role.conclusionin this study, impulses effect of four variables of the value added of agricultural sector, price index of imported inputs (corn, barley and soybean meal) and livestock price (live chicken, live sheep, live calf) was examined in four channels (equation) of price including meat price index (total meat market), chicken, mutton and beef using the panel-svar model in 30 provinces during the years 2006-2019. the findings of this study showed that the most important cause of price fluctuations in the iran meat market is due to shocks to the vertical price transmission channel, especially in the short term. therefore, preventing from price shocks in the iran meat market will be one of the most important tools to create efficiency in the market of this product. managing inflation expectations is a good way to reduce the price of meat in iran. in addition, the use of appropriate protectionist policies throughout the meat production, distribution and consumption chain, such as monitoring the production, distribution and consumption stages; modify market structure instead of price control; timely provision of production inputs for producers; development of livestock inputs in the country; providing the supply of meat in the stock market; adequate and timely distribution to consumers; cash payments are offered to households and meat producers in the event of price shocks and explosions, is suggested.
Keywords meat price ,panel-svar model ,the value added of agricultural sector
 
 

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