




































African Journal of Agricultural Marketing Vol. 1 (2), pp. 041-046, December, 2013. Available online at 
www.internationalscholarsjournals.org © International Scholars Journals 
 
 
 

Full Length Research Paper 
 

Marketing price transmission analysis in the Iranian 
rice market 

 

Mohammad Chalajour
1
 and Yaser Feizabadi

2
* 

 
1
Islamic Azad University – Roudehen Branch, Tehran, Iran,  

2
Department of Agricultural Economics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran. 

 
Accepted 28 September, 2013 

 
The goal of this paper is to test whether changes in the marketing margin between the farm and the 
retail prices can result in an asymmetric relationship between the on farm and the retail prices in the 
rice market of Iran. By separating the transaction cost variation into two regimes, this paper utilizes a 
two-type TVECM with the error correction. The empirical results show that when the marketing margin 
is lower than the threshold value, the market system operates freely and there is feedback between the 
farm and retail prices. However, when the marketing margin is higher than the threshold value, the 
government intervenes in the market and the causality between the farm and retail prices no longer 
exists. The conclusions are as follows: Changes in the marketing margin can cause the asymmetric 
price transmission between the farm and retail prices in Iran’s rice markets; therefore, ignoring the 
effect of the marketing margin could lead to errors in the models. When the marketing margin is higher 
than the threshold value, the government intervenes in the market and the causality between the two 
prices is broken. 

 
Key words: Marketing margin, price transmission, price asymmetry, threshold model. 

 
 
INTRODUCTION 
 
Rice has long been the most important staple food in  
Iran, as well as one of Iran‟s most important agricultural 
products. The Iranian government has in the past 
employed a range of measures to maintain the price 
stability for agricultural products, including the “375 Rent 
Reduction” in 1949 and the “land to the tiller” policy in  
1953. These policies were effective in stimulating large 
increases in agricultural production, which had two 
positive consequences: the policies solved problems of 
food supply and also helped achieve the policy goal of  
“developing industry through agriculture.” As Iran‟s 
economy modernized, incomes rose and standards of 
living improved; the consumption of rice gradually fell, as 
it lost its status as the pre-eminent staple. However, the 
government continued to encourage rice production out 
of food security considerations, which results in the 
phenomena that rice consumption is dropping off steeply, 
while there is currently still excess production in Iran. This 
demonstrates that with government intervention in the 
 
 

 
*Corresponding author. E-mail: yaserfeiz@yahoo.com 

 
 
 

 
agricultural sector, it is often unable to adapt to changes 
in the actual supply and demand in the market. However, 
because of the need for food security, it remains 
necessary for the government to intervene in the rice 
market. What is vital is that the government has a full 
understanding of how information is transmitted between 
the rice producers and retailers and of the effects of 
changes in the marketing margin.  

Only with such an understanding, it is possible to 
develop effective long-run policies and short-run adaptive 
measures. The two most common varieties of rice 
available on the Iranian market are A and B, there is a 
gap between the farm and market retail prices, which 
reflects the marketing margin between the farm and the 
retailer. We can also see that for both varieties of rice, the 
marketing margin reflected in the price gap appear to be 
stable, which implies that the farm price and the retail 
price may be co-integrated in the long-run. Furthermore, 
the fluctuations in the marketing margin as prices vary. 
Why might the marketing margin deviate from the long 
run equilibrium over the short term? Variation in 
production costs and changes in the weather and human 
activities are all causes of short-run asymmetric 



Chalajour and Feizabadi         041 
 
 

 
adjustments in the markets. This fluctuation may cause 
nonlinear fluctuations and limited cycles in the farm and 
the retail prices, despite their relatedness. These 
nonlinear effects may cause more short-run deviations 
from the equilibrium for the marketing margin, which can 
in turn, generate asymmetric price adjustments in the rice 
markets. Because of this, models which do not consider 
nonlinear relations between variables are certain to 
produce biased results.  

The objective of this paper is to test whether changes in 
the marketing margin between the farm and the retailer, 
as measured by the price difference, can cause an 
asymmetric relationship between the farm and the retail 
price. For this objective, we establish the following three 
hypotheses. Hypothesis 1 is that there is a co-integration 
relationship between the farm and the retail prices. Under 
the null hypothesis of Hypothesis 1, the marketing margin 
exists and the long-run relationship between the two 
prices is stable. Hypothesis 2 is that given the established 
co-integration relationship, there is no threshold relation 
between the farm and the retail prices. Hypothesis 2 
could be examined by the linearity test. When hypothesis 
2 is rejected, we could construct the threshold model and 
divide the model into two regimes. Hypothesis 3 is that 
the causality between the farm and the retail prices does 
not vary with the regimes. The benefit of testing these 
three hypotheses is that we will be able to calculate a 
critical level for the marketing margin, which will provide a 
rational basis for the government to decide when to 
intervene in the market. consumers will also be able to 
judge whether the market price for rice is within 
reasonable limits.  

This will help prevent profiteering by businesses in the 
supply chain, which is against the interests of both the 
farmers and the consumers. We employ the farm and 
retail prices of the two varieties of rice mentioned before 
to conduct the empirical study. The results show that: 
 
1) There is a co-integration relationship between the farm 
and retail prices;   
2) The linearity test rejects hypothesis 2, which indicates 
that the threshold effect exists; and   
3) Under the two regimes, the causality test result shows 
that when the marketing margin is lower than the 
threshold value, the market system operates freely and 
there is feedback between the farm and the retail prices.  

 
But when the marketing margin is higher than the 
threshold value, the government intervenes in the market 
and the causal relationship between the farm and the 
retail prices no longer exists. 
 
 
LITERATURE REVIEW 
 
In recent years, empirical analyses of price transmission 
for agricultural products have attracted attentions among 

 
 
 

 
economists. Von Braun (1998) analyzes vertical. Price 
transmission between farm gate and wholesale pig prices 
in Germany using an error correction model (ECM). To 
incorporate also effects of the marketing margin into 
models of price transmission, the author develops the 
threshold error correction models (TECM). Many studies 
have been undertaken based on works by Tong (1978) 
and Balke and Fomby (1997). For example, Obstfeld and  
Taylor (1997) analyzed the „Law of one Price‟ within such 
a framework. Goodwin and Harper (2000) used a 
threshold error correction model to quantify the spatial 
integration in United States corn and soybean markets. 
Ben-Kaabia et al. (2002) and Ben-Kaabia and Gil (2007) 
estimate the price transmission between the vertically 
related stages of the Spanish lamb market using a 
threshold model. Meyer (2004) argues that a three-
regime threshold vector error correction model (TVECM) 
is most suitable for analysis of the bi-directional price 
adjustment in the presence of the to analyze the 
dynamics of the transaction cost and to detect any co-
movements with (policy induced) changes in the financial 
environment. Poghosyan and Kuper (2008) estimate a 
TVECM model for United States gasoline and crude oil 
prices and find Asymmetric price transmission seems to 
be important because the addition showing deep gap of 
economic theory can provide concepts and applications 
of economic for policy evidence for the threshold effect 
after February 1999. makers. There are two types of price 
transfer; 1) Horizontal is transferring product price from 
the market of a country (region) to market of another 
country (region); 2) Vertical is transferring product price in 
producer level, wholesale and retail within a country. It 
has been reviewed as the existing marketing margin. 
These models can account for the effects of the 
marketing margin in the price transmission analysis even 
when the transaction cost data are unavailable.  

In other applications, Frey and Manera (2007) review 
the existing empirical literature on the price asymmetries 
in commodities, providing a way to classify and compare 
different studies that are highly heterogeneous in terms of 
econometric models and type of asymmetries and 
empirical findings. Poghosyan and De Haan (2007) use 
the TVECM for a fixed rolling window empirical literature 
on the price asymmetries in commodities, providing a 
way to classify and compare different studies who are 
highly heterogeneous in terms of econometric models 
and type of asymmetries and empirical findings (Aguiar 
and Santana, 2002; Alizadeh, 2003). The degree of price 
transmission can provide at least a broad assessment of 
the extent to which markets are functioning in a 
predictable way, and price signals are passing-through 
consistently between different markets. Price's 
transmission is affected by several factors such as 
transport and transaction costs, market power, exchange 
rate, border and domestic policies, and product 
homogeneity and differentiation (Campa and Goldberg, 
2005; Frey and Manera, 2007; Ghosh and Rajan, 2006). 



042 Afr. J. Agric. Mark. 
 
 

 
The effect of changes in import prices on domestic 

prices is central to applied trade policy analysis; however, 
it has shown that in some periods, price increases are 
more rapid and fully transmitted than price decreases and 
this is reverse in other periods and places (Aguiar and 
Santana, 2002; Goodwin and Harper, 2000). It was 
examined how to price transfer from a farm to retail for 
four dairy products butter, cheese, raw milk and ice 
cream in the United States. The results showed that the 
increase in farm prices than to reduce in farm prices is 
transferred the faster and more complete with retail level, 
and price transmission has been made asymmetric 
(Campa and Goldberg, 2005; Guillen and Franquesa, 
2007; Hansen, 1994). It showed that prices of the dairy 
products in the Brazil processing industries are 
transferred from the farm to retail faster than from retail to 
the farm (Goodwin and Harper, 2000; Hildreth and 
Jarrett, 1995). It came to the conclusion that the price 
transfer of beef and pork is asymmetric (Houck, 1997; 
Husseini and Nikokar, 2006). It reviews symmetry Price's 
test for the product of raw milk and the two percent fat 
milk in seven states of United States. Their results were 
used as evidence of price asymmetric transmission 
(Husseini and Dowrandish, 2007; Margarido and Lima, 
2009). It came to the conclusion that reducing prices over 
the on farm, is transmitted faster and more complete in 
the price transfer of fresh vegetables (Moghadasi and 
Ardekani, 2007). 
 
 
Iranian background 
 
It examines price transfer of chicken in Iran from 
producing to consuming the years 1984 until 2006. It 
came to the conclusion that any increase in the producing 
price of chicken meat is transmitted thoroughly to retail, 
while finality transfer is not complete with the retail level 
(Moghadasi and Fazeli, 2007; Mundlak and Larson, 
1992). During the third Five-Year Development Plan 
(1984 to 2006), the Iranian government undertook various 
economic initiatives, such as removing non-tariff barriers, 
in order to prepare the conditions for the country to join 
the global trade system, and to accelerate its 
development efforts to reduce the level of poverty. 
Generally speaking, the Iranian government policy 
interventions in food markets are directed toward 
ensuring domestic food security and lowering food prices 
through trade policies and rising staple imports supported 
by crude oil price climbing as well as fiscal and monetary 
policy, etc.  

Furthermore, Iran attempts to manage food price rises 
through subsidies and supplying discounted staple foods 
through a coupon system (Negassa and Myers, 2007). It 
studies the price transfer of meat and chicken market in 
Iran. Their study confirmed that the level of producer 
price fluctuation is transferred symmetrical shape to the 
retail level (Rapsomanikis et al., 2003; Staatz et al., 2008; 

 

  
 

 
Schnepf, 2008). As described by the World Bank (2009) 
report, each policy is expected to have different effects on 
various groups of households and could depress 
incentives to farmers to increase output resulting in 
further increases in food prices. On the other hand, 
policies such as export bans or high export tariffs taken 
by the exporter partners may create harmful effects on 
Iran as a net food importer (The World Bank, 2009). The 
preferred rate was applied to import of essential goods, a 
fixed or export rate (3000 Rial for $1) was applied to 
capital good imports of public enterprises and a variable 
market rate was devoted to other imports. Such a multi 
exchange rate system had generated implicit subsidies 
for state owned enterprises and revolutionary foundations 
as well as for importers of basic commodities (Alizadeh, 
2003). It was studied market price in the dates and the 
pistachios (Moghadasi and Fazeli, 2007). It was reviewed 
price transmission model of Iranian pistachio in the global 
market (Husseini and Dowrandish, 2007). 
 

 
RESEARCH METHODOLOGY 
 

In this paper, the retail price ( r ) has been used and on farm  
prices ( Pf ), of rice a week over a period of twenty five years. The 

statistics have been prepared from the Central Bank of Islamic 
Republic of Iran. Consumption price index (CPI) is used to remove 
inflation producer. In this paper, price transmission has been 
analyzed, elasticity of transmission prices and causality relationship 
between the two levels of wholesale prices and retail sales for two 
types of rice product (grades A and B). The unit root and the 
Dickey-Fuller tests were used for reviewing stationary of data (as 
time series), if time series' data are static, it will be used as the 
Houck model, and If time series' data are non-static, first up through 
the Johansson test is used for reviewing the relationship between 
market variables at different levels, then if it converges, it will be the 
error correction model for analysis of price transmission. The 
Granger causality test was used for the impressionability of prices. 
The Houck model is calculated by Formula 1 as follows: 
 

 M 1 
 

 M 2 
 

  
 

rt r0  ɑ 0t ɑ1 Pf 
 

ɑ2 Pf e1 

 
 

t i 


 t i  
 

 i 0   i 0   (1)  

       
 

Where:        
 

r : Logarithm of the retail price; Pf : Logarithm of the on farm 
 

prices;  
Pf

 
     

Pf 
 

 

:  Increase  in the on farm  prices; :  A 
  

reduction in the on farm prices; 

M
 
1
 , 

M
 
2
 : Length of interruption. To 

investigate symmetric or asymmetric in the positive and  
negative shocks of price transfer between two levels of market, it 
uses the equity hypothesis test of variable coefficients.  

Coefficients 

ɑ
1
 and 

ɑ
2
 are respectively increasing and decreasing 

effect farm prices on the retail prices. The null hypothesis is defined 
by Formula 2. 



Chalajour and Feizabadi         043 
 
 
 

Table 1. The basic statistics of the first-differenced price variables. 
 

Parameter FP1 FP2 RP1 RP2 
Mean 0.0007 0.0006 0.003 0.006 
Standard  deviation 0.039 0.042 0.022 0.024 
Skewness -0.2 -0.6 -0.4 -0.6 
Kurtosis 8.564 5.234 12.321 5.067 
Observations 302 302 302 302 

 
Variables are all in natural logarithms. Variable FP1 the farm price per kilo of A rice, FP2 the 
farm price per kilo of B rice, RP1 is the retail price per kilo of A rice, and RP2 is the retail price 
per kilo of B rice. 

 
 

M
 1 

M
 2  

H
 0 

:
  

ɑ
1i 


 

ɑ
2i  

i 0 i 0 (2) 
 
The above equation can be easily estimated with OLS.  

Whereas 

ɑ
1
 with 

ɑ
2
 are equal and both are positive, then price 

transfer is symmetrical and otherwise to be asymmetrical. In order 
to test rejection or acceptance of null hypothesis the Wald test is 
used. Granger and Lee, error correction models proposed as 
Formulas 3 and 4. 
 
 

     
P

1 P
2 

 

Prt   B 0  B 1 Pft   B  B 


  

B
 3 i 

P
rt i  B 

 

2 
ECT

 t 1 2 
ECT

 t 1 
 

      i 1 i 1 
 

(3)        
 

 

 
 

1) If ( 



 j  0 
) and ( 




 j  0 
 

   ), then unilateral causality will 
 

form the r to 
w

 , therefore wholesale in the retail level effects 
 

on price in the wholesale level.  
 

2) If ( 



 j  0 
) and ( 




 j  0 
 

   ), then unilateral causality will 
 

form the 
w

  to r , therefore, wholesale market creates by price 
 

changes in the retail market.  
 

3)  If  the  total  coefficients  of 
w

 and  r  in  regression  were 
 

 statistically  significant  and  non-zero,  then  they  have  two-way 
 

 causality and both markets influence each other. 
 

4 i P    v w and r in regression were not  

ft4) i If the  total coefficients of   
 

statistically significant, and both markets are independent. 

ECT t 1 


 

P
rt 1 


 

ɑ
0 


 

ɑ
1

P
ft 1 

(4)  
    

 
In the aforestated regression, it reviews change in retail prices to  
changes in wholesale prices at time 

t
 and wholesale prices in prior 

periods. 

Coefficients  
B

 
 

B 
 

 2
  and 

2
   show respectively, adjustment of the 

  
retail price to positive and negative shocks in marketing margin. 
Null hypothesis to this species is defined as Formula 5. 
 

H 
   

 

0 
:
 
B

 2  B2 (5)  
    

 
Acceptance of the null hypothesis indicates symmetry of the price 
transmission and its denial represents asymmetric pric 
transmission. In this study, it reviews causality between retail and 
wholesale market, that ultimately it shows the market effect of the 
two different levels. In other words, though the causality test can 
determine which market effects on price and its changes in other 
markets. Granger's causality test is expressed as Formulas 6 and 7. 

 
w    w   

 
 r   U i , j 1,2,..., n 

(6) 
 

 t   i t i  j t  j 1t  
 

r    r     w  U i , j 1,2,..., m 
(7) 

 

t   it i   j   t  j  2t  
  

If disruption components are non-correlative, there are 4 modes in 
the following separation: 

 
RESULT ANALYSIS 

 
The variables in this model are the on farm and the retail 
prices of the, A and the B rice, the two main varieties 
grown in Iran. The data come from the council of 
agriculture, and consist of monthly price data from 
January 1981 to March 2006, a total of 302 observations. 
Table 1 reports the basic statistics of the returns of 
logarithmic farm and retail prices. The means of the two 
variables indicates that the fluctuation of the retail price is 
larger than that of the on farm price. These two 
phenomena imply that there is the marketing margin (or 
transaction cost) between the on farm and retail prices. 
The standard deviations could evaluate the risk of the rice 
prices. The numbers of Table 1 indicate that the farm 
price is riskier than the retail price is, which indicates that 
the rice market that Iranian farmers face is a low-return 
and high-risk one. The skewness coefficient indicates that 
the distribution of the on farm price is skewed on the left 
and the distribution of the retail price is skewed on the 
right. The kurtosis coefficient indicates that the 
distributions of the four time series are not comparable. 
When conducting the tests, we first applied two unit root 
tests: the augmented Dickey-Fuller and the Phillips-
Perron tests, to establish that the variables were not 
stationary. The unit root tests compare constant and time-
trend models. They indicate that the four price series are 
I(1) processes, that is the first difference of the four 

   



044 Afr. J. Agric. Mark. 
 

 

 
Table 2. Test of causality between wholesale and retail level of A rice 
(grade 1). 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
series are stationary.  

Using these results, we can test for co-integration 
between the on farm and the retail rice prices. The 
parameter value of A shows that for both varieties, there 
exists a fixed mark-up effect; the value of B shows that 
the cross-elasticity between the farm and the retail prices 
is higher than 1 for both varieties. This implies that 
variations in the retail price of both varieties of rice are 
larger than the variations in the on farm price. The cross-
elasticity is higher for the A than for the B rice, meaning 
that the retail price response to changes in the farm price 
is greater for the A than for the B rice. It is used the unit 
root test for stationary of variables. Granger causality test 
is used to examine the relationship of prices. First, the 
optimum interval is determined for each variable at any 
price based on the lowest statistic, for this purpose, the 
cost variable of each product at every level is regressed 
to their values interval separately and the optimum 
interval for the variable has been determined. Then the 
desired equation is regressed to other variables in 
different intervals, the optimum interval for the variable 
has been determined. After determining the optimal 
interval variables, the equations are examined to estimate 
and the causality test is reviewed by the Wald test and 
the results are shown in Tables 2 to 4. Table 2 shows 
results of causality test between the two levels of retail, 
and wholesale A rice (grade 1). According to the Wald 
test, null hypothesis accepts in significant level, therefore 
it is rejected causality form the wholesale to retail market 
and prices in retail level are not affected by prices on 
wholesale level. But in the second equation, the 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
null hypothesis is rejected; therefore it is accepted 
causality form the wholesale to retail market and prices in 
retail level is affected on prices in wholesale level. 
Therefore, there is causality communication from 
wholesale to retail in the A rice, the A rice (grade 1) price 
in retail market influence the wholesale level market. 
Table 3 shows results of causality test between the two 
levels of retail and wholesale of B rice (grade 2). 
According to Wald test, null hypothesis is accepted in 
both equations, therefore there is no causality relation 
between the two markets (wholesale market and retail 
market), and price in the two markets have independent 
behaviors. 
 
 
DISCUSSION 
 
The summary of the empirical results presented in Table 
2 shows causality communication from wholesale to retail 
in the A rice (grade 1), Table 3 shows the same for the B 
rice (grade 2), the A rice price in retail market influences 
the wholesale level market, therefore there is not any 
causality relation between the two markets (wholesale 
market and retail market), and price in the two markets 
has independent behaviors. Considering all the variables 
to be static, so the Houck model for reviewing symmetry 
of price transmission at two levels of retail and wholesale. 
For this purpose, the first optimum interval of variables is 
determined in this model and then it estimated the model, 
estimation results shown in Table 4. The short-term 
coefficients show increase or decrease of price in 



          Chalajour and Feizabadi         045 
 

 
Table 3. Causality test between wholesale and retail market in B rice product 
(grade 2). 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
Table 4. Results of Houck model and Wald test to review symmetry of price transmission 
 
 Short term coefficients of  Long term coefficients of   

Symmetry of price  

Variable price changes  price changes Wald test Null hypothesis  

 

transmission  

 

Increase Reduce 
 

Increase Reduce 
  

 

     
 

Price of rice      F = 16.32 
Reject Asymmetric  

Grade 1 0.76 0.12 - 0.65 Probability = 0.002  

  
 

Price of rice      F = 21.88 Reject Asymmetric 
 

 
 

 
wholesale on price changes in the retail level in the same 
period, and the long-term coefficients show price transfer 
with interval between these two levels of market. 
According to Table 4, in any grade of rice, the 
transmission speed of price increase or positive shock of 
price is faster than the transmission speed of price 
reduce or negative shock of price in wholesale market to 
the retail market.  

So a positive shock of price in wholesale is transferred 
immediately and in the same period to the retail level for 
grade 1 of rice, while reducing cost is transferred with a 
delay and after a transition period. The reason is that 
retailers seek to make more profit and wholesale reacts 

 
 

 
to price reduction at the retail level. Thus, it concludes 
that transmission of positive and negative shocks from 
wholesale to retail are asymmetric and these results are 
confirmed by Wald test. According to Table 4, it rejects 
null hypothesis in equity at total coefficients of price 
increase in different intervals with total coefficients of 
price reduction for each product with regards to the 
significance of the F statistics. Therefore, price 
transmission in the rice market is asymmetric.  

Finally, the difference in the threshold values suggests 
that there is a difference in the timing of government 
interventions in the markets for the A (threshold 0.081) 
and the B (threshold 0.054) rice. This may be because 



046 Afr. J. Agric. Mark. 
 
 

 
the long-run cross elasticity for the A rice is greater than 
that of the B rice. This means that a higher transaction 
cost threshold for the intervention is acceptable for the A 
rice, when the objective is to avoid excessive movements 
in the retail price of rice. 
 
 
Conclusions 
 
The purpose of this study is to examine the relationship 
between the on farm and the retail prices in the Iranian 
rice market. We established three hypotheses and 
obtained several important empirical findings. Firstly, 
there is a long-run co-integration relationship between the 
on farm and the retail prices. Secondly, the marketing 
margin resulting from this long-run relationship may 
cause short-run dynamic adjustments between the on 
farm and the retail prices, which results in the asymmetric 
causality. This implies that the marketing margin is an 
important factor when analyzing the causality in the on 
farm and the retail markets. Because of this, we 
constructed a nonlinear threshold model to fully 
understand the effect of the marketing margin. Thirdly, 
when the marketing margin is low, the market operates 
freely; when the marketing margin is high, the 
government makes necessary interventions in the market 
to prevent excessive rises in the rice prices.  

When intervention occurs, the market system no longer 
operates. The main advantage of our model is that it is 
able to analyze the asymmetric price transmission 
between the price series without the addition of the 
transaction cost data (for example, operating costs for 
intermediary companies). Additionally, the new findings of 
this paper can allow the government to make appropriate 
decisions on market interventions and can be used by 
consumers to determine a reasonable price range for 
rice, which serves the interests of both farmers and 
consumers. Finally, employing different empirical models, 
adopting various rice prices, or including government 
policies in the model could serve as the possible future 
research directions for us. 
 
 
REFERENCES 
 
Aguiar DRD, Santana JA (2002). Asymmetry in farm to retail price 

transmission: evidence from Brazil. Agribusiness, 18(1): 37-48.  
Alizadeh P (2003). Iran‟s quandary: economic reforms and the 

„„structural trap”. The Brown J. World Affairs IX 2: 266-281.  
Campa JM, Goldberg LS (2005). Exchange rate pass-through into 

import prices. Rev. Econ. Stat., 87: 660-679.  
Frey G, Manera M (2007). Econometric models of asymmetric price 

transmission". J. Econom. Surv., 21(2).  
Ghosh, A., Rajan, R. (2006). How High is Exchange Rate Pass-through 

in India? Has it changed over time? Department of Economics and 
Business, Colorado College, pp. 42-50 

 

  
 

 
Goodwin BK, Harper DC (2000). Price transmission, Threshold 

behavior, and Asymmetric adjustment in the U.S. pork sector, J. 
Agric. Appl. Econ., pp. 3-32.  

Guillen J, Franquesa R (2007). Analysis of the price transmission along 
the Spanish market chain for different seafood products, www.eafe-
fish.eu.`, 1-15.  

Hansen B (1994). Determinants of the farm-retail milk price spread, 
Agricultural Information Bulletin, P. 693.  

Hildreth C, Jarrett FG (1995). A statistical study of livestock production 
and marketing, Cowles Commission Monograph, No: 5 , New York., 
10,11  

Houck JP (1997). An approach to specifying and estimating 
nonreversible function, Am. J. Agric. Econ., 59: 21-30.  

Husseini S, Nikokar A (2006).asymetric price transmission and effects 
on market margin. J. Agric. Sci., pp. 2-37.  

Husseini S, Dowrandish A (2007). Price transmission of Iranian 
Pistachio in global market. J. Agric. Sci., PP 2-37.  

Margarido MA, Lima LA (2009). Transmission of External and Domestic 
Prices to Farm Prices in Brazil: a Aimulation". Mimeo, pp. 25-26.  

Moghadasi R, Ardekani R (2007). Reviewing of price transmission in 
meat and chicken markets. J. Agric. Sci., pp. 2: 37.  

Moghadasi R, Fazeli F (2007). Reviewing of price transmission of 
Pistachio, the 6 conference on agricultural economics, Mashhad, Iran 
no pp. 5.  

Mundlak Y, Larson D (1992). On the transmission of world agricultural 
prices. The World Bank Econom. Rev., 6(3): 399-422.  

Negassa A, Myers R (2007). Estimating policy effects on spatial market 
efficiency: An extension to the bounds model. Am. J. Agric. Econ., 89: 
338-352.  

Poghosyan T, de Haan J (2007).Interest Rate Linkages in 
EMUCountries: A Rolling Threshold Vector Error-Correction  
Approach”. CESifo Working Paper Series 2060, CESifo GmbH.  

Poghosyan T, Kuper GH (2008). Non-Linear Price Transmission 
between Gasoline Prices and Crude Oil Prices (September 9, 2008), 
Available at SSRN: http://ssrn.com/abstract=1265569  

Rapsomanikis G, Hallam D, Conforti P (2003). Market Integration and 
Price Transmission in Selected Food and Cash Crop Markets of 
Developing Countries: Review and Applications", in Commodity 
Market Review 2003-2004, FAO, Rome, 7-11.  

Staatz J, Dembélé N, Kelly V, Adjao R (2008). Agricultural Globalization 
in Reverse: The Impact of the Food Crisis in West Africa, Department 
of Agricultural, Food and Resource Economics Michigan State 
University. Background paper for the Geneva, PP. 1-15.  

Schnepf R (2008). High Agricultural Commodity Prices: What Are the 
Issues? Report RL34474. Congressional Research Service. 
Washington, DC.  
(http://assets.opencrs.com/rpts/RL34474_20080529.pdf). Price 
transmission and welfare impact in Africa p.50.  

The World Bank (2009). Islamic Republic of Iran, an Agricultural Policy 
Note, Water, Environment, Social and Rural Development 
Department, Middle East and North Africa Region. pp. 1-10.  

Von Braun J (2008). High Food Prices: The What, Who, and How of 
Proposed Policy Actions, Policy Brief. International Food Policy 
Research Institute. Washington, DC.  
(http://www.ifpri.org/PUBS/ib/foodprices.asp). Pp. 1-10. 
 


