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ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)
Industrial Engineering & Management Systems Vol.18 No.2 pp.283-291
DOI : https://doi.org/10.7232/iems.2019.18.2.283

# Effectiveness of Trade and Exchange Rate Policies on Exporting Garden Products: Evidences from Iran

Department of Financial and Trading Management, Faculty of Management and Economics, University of Sistan and Baluchestan, Zahedan, Iran
Department of Economic Agriculture, Faculty of Agriculture, University of Zabol, Zabol, Iran
Corresponding Author, E-mail: at.rasoolizadeh@gmail.com
May 20, 2018 November 29, 2018 December 27, 2018

## ABSTRACT

The current research intends to study the effectiveness of trade and exchange rate policies on exporting garden products in Iran. For the policies on exchange rate, the instability of the exchange rate and the dummy variable of exchange rate unification were considered in relation to trade policies, trade diversion and economic openness. To do so, the short term and long term relation between the variables of the export supply logarithmic function was determined according to ARDL model and the error correction model. The data was collected from the international trade database, the statistics of the agriculture ministry and the central bank’s site for 1997-2015. The results showed that, for long term, such variables as trade diversion, exchange rate instability, economic openness, export value of the stone fruits during previous years and the dummy variable of exchange rate unification were positively influencing on exporting Iran’s stone fruits. The value of error correction factor was estimated as -0.42 which is significant and indicates a more highly increased adjustment for long term equilibrium. Also, when a shock or diversion from equilibrium occurs, 0.58 of the short term imbalances are adjusted to reach the long term equilibrium.

## 1. INTRODUCTION

Reaching a higher economic growth is one of the economic objectives considered by all countries. This insures application of appropriate economic policy which itself is one of the main extension of trade policies, especially the foreign trade (Azimi and Yahyazadehfar, 2013). Additionally, the agriculture sector participates in foreign trade through agriculture export and exports more than other sectors (Yufu et al., 2013). Therefore, stressing of this sector with developing export can contribute to pave the way for participating in in global market while also utilizing its benefits. Therefore, regarding the development and trade in agriculture is necessary as a precondition for economic development (Pakravan and Gilanpour, 2013).

The importance of agriculture for economic development together with effectiveness of the trade and exchange rate policies on agricultural performance contributed to consideration of these policies. One of the main policies on foreign trade in developing countries is the progress and development of exports. In terms of theory, vicariate when the export changes, the economic growth improves. Thus, export development, as a strategy for economic development, significantly determines increased production capability, employment, security and supplying revenues from exchange rate for investment in new technologies (Gilbert et al., 2013). Therefore, adoption of economic policies (money, financial, exchange rate, trade and protective) plays a vital role in plans for development of agricultural products’ export. We will review some of the investigations carried out on the effects of economic policies on non- oil export in Iran and other countries. Kouchakzadeh and Karbasi (2015) studied the factors influencing on trading Saffron. They did it using the gravity model and panel econometrics for 2001-2013. The results indicated that GDP and population of the importing countries and the exchange rate significantly influence on Saffron trade with values of 1.55, 0.015, 0.54, respectively. Azizi et al. (2015) studied the role of the protective policies in development of exporting agricultural products. According to the results from the ratio of export price, the agricultural added value and protection were influential on the pattern while positively related with export supply both in short term and long term. On the other hand, the exchange rate, consumption of the private sector and war don’t influence on export supply. The error correction factor showed that, for each period, 52% of the imbalances disappear and the long term adjustment occurs. Safari et al. (2014) studied the effects of exchange rate volatility on exporting agricultural products with respect to section two of the general agricultural policies. They used the autoregressive model with the distributed delays for 1981-2011. The results showed a reverse relationship between exchange rate volatility and exporting agricultural products.

Bahmani-Oskooee et al. (2018), that while exchange rate volatility affects trade flows of many of the countries in our sample in the short run, the long-run effects were restricted only on the exports of five countries and on the imports of only one country. The level of economic activity in the world and at home were identified to be major determinants of exports and imports, respectively. Hasanov (2012) studied the effects of real exchange rate on non-oil export in the country of Azerbaijan using asymmetric error correction model for 2000-2010. It was found that there is a significant relationship between non-oil export and non-oil trade volumes based on real exchange rate and foreign income but the adjustment process is not asymmetric when compared to balance level. Goswami and Saikia (2012) studied the relationship between trends of direct foreign investment and export at North eastern part of India. They used VECM model and found that there is a mutual causative relationship between direct foreign investment and export. Prasanna (2010) investigated the impacts of direct foreign investment on India’s export and concluded that direct foreign investment positively influenced India’s export. Fogarasi (2010), using panel data In Romania for 1999-2008, studied the effects of exchange rate instability on agricultural export. The results showed that instability of exchange rate had negative and significant impact on Romania’s agricultural exporting in such a way that a 10% increase in in stability of exchange rate led to 5% reduction of Romania’s agricultural export. Kazerooni and Feshari (2010), using Johansson’s co integration method, studied the effects of the changes in real exchange rate on Iran’s non- oil export for 1971-2007. The results showed that the real exchange rate and its changes had both positive and negative effects on non-oil export. Peng et al. (2004) studied the effects of money and trade policies on food price in China. The results indicated that, in long term, the exchange rate has negative impact on food, but it isn’t influenced by interest rate. Also, both in long and short terms, the amount of money has positive impact on food price. Therefore, the current research intended to study the effects of trade and exchange rate policies on exporting Iran’s stone fruits for 1997-2105.

## 2. METHODOLOGY

Here, in order to study the effects of trade and exchange rate policies on exporting garden products, first the criteria indicating the trade and exchange rate policies will be identified and determined. Thus, for exchange rate policies, exchange rate policy and the dummy variable of exchange rate unification will be considered. With respect to trade policies, trade diversion and economic openness will be measured while also regarding the effects of these two criteria on stone fruits.

In order to determine deviation of real exchange rate (instability of exchange rate), the equilibrium of purchasing power parity was applied. According to this theory, the equilibrium rate of real exchange rate is fixed and is considered as equal to mean real exchange rate for years when Iran was enjoying good exchange rate which means payment equilibrium and current account need to be in a good condition.

$E R E R = ∑ i = 1 n M a x . R E R i n$
(1)

ERER: equilibrium real exchange rate, n= number of years when good conditions of exchange rate dominated. Max.RER = exchange rate of those years. In order to determine incorrectness of adjustment of real exchange rate, the following equation is used:

$R E R M I S = ∑ i = 1 n M a x . R E R i n R E R i − 1 = E R E R R E R − 1$
(2)

where RER is real exchange rate and the following equation is applied:

$R E R = E . W P I ( O E C D ) C P I I r a n$
(3)

where E is the official exchange rate, WPI (OECD) is the wholesale price index for the industrialized countries, CPI is consumers’ price index for Iran. Trade balance (TB) is determined by the following equation:

$T B = P x P X ′ P I P I ′ = 1 − t x 1 + t m = R E X R E I$
(4)

where PI and PX are domestic prices for export and import goods, tx and tm are those controls and restrictions done on import and export goods. REX and REI are the real exchange rate for export and import goods, respectively.

When no control is applied on foreign trade, tx and tm will be close to zero and TB equals 1. Values less than 1 indicate supporting importing goods and those values more than 1 indicate supporting production of exporting goods in foreign markets. Trade balance includes all trade and exchange rate policies. Economic openness is obtained through dividing total amounts of export and import by GDP:

$O E P N = M + X G D P$
(5)

This criterion indicates those trade policies which help the domestic economy more open to international trade.

Having identified and determined those criteria indicating the trade and exchange rate policies, in order to study the effects of these criteria on supplying for exporting stone fruits and to estimate the short term and long term relationship between model variables, the logarithmic form of export supplying function was used according to ARDL and error correction model. The main advantage of ARDL is that , without regarding the fact that the descriptive variables should be stable (I(O)) or should be stable even when reduced (I(1)), co-integration relationship between the variables could be recognized.

Auto-regressive model with distributive delays as ARDL (p, q1, q2, …, qk) is represented as follows:

$α ( L , p ) Y t = α 0 + ∑ i = 1 k β i ( L , q i ) X i t + δ W t + u t t = 1 , 2 , ... , n$
(6)

The equation shows a dynamic relationship between the variables so that:

$a ( L , p ) = 1 − α 1 L − α 2 L 2 − ⋯ − α p L p$
(7)

$β i ( L , q i ) = 1 − β i 1 L − β i 2 L 2 − ⋯ − β i q L q i = 1 , 2 , ... , n$
(8)

Where Yt is the dependent variable, ao intercept, Xit independent variables, delay operator L, P numbers of delays applied for dependent variable (Yt), q numbers of delays applied for independent variables (Xt) and Wt including predetermined variables like virtual variables, trend and other exogenous variables with fixed delay.

The numbers of optimal delays of the individual variables should be determined by Akaike, Schwartz Bayesian and Hamman Quinn criteria. The long term relationship of ARDL model is obtained by the following equation through a simple operation and given the fact that, in long term, the current value of the individual delays of the dependent and distributive variables are equal:

$Y t = α + ∑ i = 1 k θ i X i + γ W t + v t$
(9)

where

$α = α 0 α ( 1 , p )$
(10)

$γ = δ α ( 1 , p )$
(11)

$θ i = β i ( 1 , q ) α ( 1 , p ) = ∑ j = 1 q β i j α ( 1 , p )$
(12)

$v t = v t α ( 1 , p )$
(13)

Estimation of ARDL model includes two steps for estimating long term factors. First, the long term relationship predicted by economic theory and if a long term relation existed, second, the long term and short term factors would be estimated.

In order to perform the long term co-integration test for recognizing the long term relationship in model, Banerjee, Dolado and Mastre method was applied. The test was based on t statistics which is related with the factors of the dependent variable delay. In order to perform the test, a value of one should be reduced from the factor with a dependent variable delay and be divided by SD of the variables. When the absolute value of t statistics is more than that of the critical values as suggested by Banerjee, Dolado and Mastre, null hypothesis will be rejected and long-term relationship will be supported (Tashkini, 2005):

$t = α ^ i − 1 s x ^ i$
(14)

If, in first step of ARDL model, the long term relationship is supported, long term factors will be estimated. Dynamic error correction model (ECM) is derived from ARDl model (Banerjee et al., 1993). ECM combines long term and short term dynamics without losing the long term data (Shrestha and Chowdhury, 2005;Saidane, 2017). ECM could be rewritten as follows:

$D Y t = α + ∑ i = 1 m β t D Y t − i ∑ i = 1 m Y i D X y − t + λ E C M t − 1 + ν t 1 < λ < 0$
(15)

where D is first order difference of the variables, λ, adjustment value of a period; they show the path to long term balance. According to Granger, if the current values of y are predicted using previous values of x and y with a higher correctness as compared to when values of x are not used, then y is caused by x (Granger et al., 1998). Canova (1995) contended that when the variables are instable in terms of vector autoregressive pattern (VAR), Granger’s non-causality test might provide incorrect results. In such cases, first order difference of the variables , in terms of VAR or long term co-integration patterns, should be applied. Having identified the variables, the mathematical relations and model will be defined.

where the variable dependent on value of garden products and the independent variables include: logarithm of exchange rate instability (LRER), logarithm of trade diversion (LTB), logarithm of economic openness (LOPEN), logarithm of value of export in previous years (LEXt-i), logarithm of domestic products’ price (LPF) and the dummy variable for exchange rate unification (ED). It is necessary to note that the research data was derived from UNCOMTRADE site and Iran’s central bank site for 1997-2015. The model was estimated by Eviews.

## 3. RESULTS AND DISCUSSION

The current research intended to study the effects of trade and exchange rate policies on exporting stone fruits for 1997-2015 using autoregressive distributive lag (ARDL). Small size of the sample size leads to the fact that increased application of such methods as minimum normal squares due to disregarding the short term dynamic reactions existing as between variables leads to bias in estimation. Therefore, to estimate the factors, a dynamic model should be considered so that many lags could be included for the variables. Also, in addition to provide an estimation without bias from the long term parameters with valid t statistics using this model, the unit root test could be implemented. While estimating the variables of the long-term model, this method provides error correction model in order to study how short term adjustment could be turned into long term equilibrium.

Before discussing co-integration test, stationary test is implemented for all of the variables so that none of the variables are not a sum of second order I (2) so that the fake results could be avoided. When the integrated variables are in second order or higher orders, the F statistics determined by Pesaran et al. (2001). In order to determine integration order of the variables, Phillips Perron (PP) and Dickey Fuller tests were applied for which the results presented in Table 1.

The results indicated that the times series for logarithm of trade diversion, logarithm of economic openness and logarithm of domestic product prices are stable and the time series for logarithm of values for exporting stone fruits and logarithm of exchange rate instability are not stable and became stable with one time difference. It should be noted that, when estimating ARDL method for long term, the variables might be I (o) and I (1) or a combination of both of them (Pesaran and Shin, 1998).

In first step of estimating ARDL, F test is used to identify the long term relationship. F test, first, estimates OLS regression for first order difference. Next, it tests significance of the factors for lags when added to first side of the equation. Table 2 presented f statistics results when first order difference of the individual variables were considered as the dependent variable of ARDL-OLS regression.

According to Table 2, the calculated F statistics (5,4508) is more than the higher limit of critical value of F (4,124) at 99%. So, the long term or co-integration relationship between the model variables are confirmed. After the cointegration is found, the long term model and error correction model are estimated using Schwarz Bayesian criterion and ARDL maximum lags (1, 1, 0, 0, 1, 1).

According to Table 3,The results from estimating long term model showed that all of the variables have significant impact on the dependent variable in long term. However, the most influential factors on exporting Iran’s stone fruits include: logarithm of trade diversion, logarithm of real exchange rate, logarithm of economic openness, logarithm of the values of exporting garden fruits in previous years, logarithm of domestic product price and the dummy variable of exchange rate unification, respectively.

Trade diversion factor is significant with a confidence level of 99%. In addition, indicates that, with 1% increase or decrease, the probability of exporting garden product increases (decreases for 7.8% and this increases national exchange rate incomes. In other words, increased support for exporting agricultural products increases trade diversion and, in consequence, exporting stone fruits. With a confidence level of 95%, exchange rate instability is significantly influences on the value of exporting stone fruits. The sign is positive and indicates, with 1% increase (decrease) in real exchange rate, the value of exporting garden products increases (decreases) 6.5%. This could be justified given the fact that increase in volatility of exchange rate has both substitution and income effects. For this case, the income effects overweighs the substitution ones and, therefore, increased export activities.

With the exchange rate increases, the value of Iran's national money decreases against the international exchange rates. In other words, more national money is bought by one international money. Thus, the domestic products will be cheaper than the international ones and this contributes to more export and less import. Also, the economic openness is positive and significant with a confidence level of 99% which means, with a 1% increase (decrease), the value of exporting garden products increases (decreases) 6.1%. According to the classic and neo-classic theories of economy, the increased economic openness drives the economic growth and development and this contributes to encouraging countries for more economic convergence through increased export and import. Therefore, this positive relationship is supported. Domestic product price has significant impact on the value of exporting garden products with a confidence level of 90%. The sign of this factor is negative and indicates that, with 1% increase (decrease) in domestic price, the value of exporting stone fruits decreases (increases) 1.2%. In other words, with increasing domestic prices, since the domestic goods will be more expensive than the foreign ones, export level decreases. Export of stone fruits, in previous years, was significant and positive with a confidence level of 99% which means its 1% increase (decrease) probably increases (decreases) the value of exporting stone fruits for 3.3%. This is due to appropriate export conditions experienced in previous period which convinces farmers to pay more attention to production of high valued products.

The dummy variable of exchange rate unification is significant with a confidence level of 90% and this indicates that, its 1% increase (decrease) rises (reduces) the probability of exporting garden products for 1.2%. Table 4 presented the results from short term factors together with respective error correction process.

The results from estimating the short term model is a bit different from those of the long term model. All of the variables are significant for both short and long terms. However, the most effective variables on exporting stone fruits in previous years included; exchange rate instability, trade diversion, economic openness, domestic product price and dummy variable of exchange rate unification, respectively. Here, exchange rate instability is negative and significant with confidence level of 95% which indicates that its 1% increase (decrease)of exporting stone fruits increases (decreases) exporting stone fruits 2.4%. It seems that, in this case, the substitution effect of exchange rate instability is more than its income effect and, in consequence, it decreases export. The negative effects of real exchange rate instability reduces trade level through instable conditions for benefits from international trades and mitigates movement for capital flow by reducing investment in foreign trade and value of financial portfolio and export.

Trade diversion is significant with a confidence level of 99%. Also, its 1% increase (decrease) increases (decreases) 7.1% exporting stone fruits. Economic openness, with a confidence level of 90%, indicates that, with 1% increase (decrease), reduces (rises) 4.4% exporting garden products. Additionally, exporting fruit stones in previous years was significant with a confidence level of 99% and its 1% increase (decrease) will increase (decrease) the value of exporting garden products for 2.3%. Domestic product price is significant with a confidence level of 90% and its 1% increase (decrease) the value of exporting stone fruits increases (decreases) for 2.5% and the incomes from nonoil export will increase. For short term, the dummy variable of exchange rate unification isn't significant.

Error correction factor was estimated as -0.42 which is completely significant and indicates a highly increased adjustment for long term balance. Also, it shows, when shock and balance diversion occurs, 0.58 % of short-term imbalance is adjusted in order to reach long term balance. The determination coefficient’s value is 0.85 and Durbin Watson’s value is 2.43. In addition, a number of diagnostic tests were performed on the model and the results from Ramsey test for consequential form, LM for selfcorrelation, White for heteroskedastic variance indicated that the null hypothesis was rejected.

## 4. GENERAL CONCLUSION

Given the fact that agriculture is important in Iran , especially with its capability to enter foreign exchange moneys into the country, the current research studied the effects of trade and foreign exchange rate policies on exporting Iran's garden products. As mentioned earlier, the garden products, especially including such stone fruits as cherry, apricot, peach an plum, are among those products with huge amount of productions across the world. Therefore, it is vital to regard these products for export.

According to previous results, trade diversion and increased supportive policies of exporting agricultural products, in short and long terms, are directly related with increased export of garden products. This leads to policies which increase supporting export of agricultural products. Therefore, given the fact that implementing protective policies directly contribute to development of exporting agricultural products, the governmental officials need to regard this process so that, with increasing technical knowledge and infrastructural facilities, the productive capacity will increase for both short and long terms. While contributing to development of new methods for producing and supplying different products, this reduces import level and helps increase export and improved level of trade balance. Also, with a review of the policies supporting export in different countries, it is clearly concluded that each country adopted its own version of incentive and supportive plans on export. When looking at the protective plans of these countries, it is found that many kinds of financial supports on export are provided in terms of insurance, taxation and exchange rate. One of the significant fact within the protective plans on export, across the world, is the supports and incentives provided to medium and small industries. In principle, due to limited sources, these small and medium industries face more damages in terms of the activities and competitions across the international markets. Thus, development of plans for supporting these firms, especially against the risks and threats of activities in international markets is drastically important since such plans, if implemented appropriately across the country, can assist export sector increasingly grow.

Exchange rate instability is another variable which, in long term, influences on the value of exporting garden products. Therefore, exchange rate needs to be close to real balance for exporting agricultural products and those exchange rates significantly diverted from real exchange rate must be avoided.

Additionally, fixation of exchange rate, in case of price volatility for agricultural products due to inflate and increased expenses, leads to hard competitive conditions in global markets. Thus, ,before the fixation policies adopted, financial and money policies need to be implemented in order to reduce inflation rate according to the global average level. This is in accordance with investigations carried out by Khalighi and Fadaei (2017), Liefert and Westcott (2016) and Fogarasi (2010).

The empirical results suggest that, while overvaluation is harmful to exports, undervaluation of the real exchange rate boosts export supply as well as export diversification. A high rate of growth in exports is associated with periods of undervalued currencies.

With respect to the significant and negative effects of the garden products’ domestic price on exporting these products, mitigating price volatility for these products needs to be considered when formulating such trade and protective policies since volatility can negatively influence on short term and long term production planning and exporting agricultural products. Generally speaking, the vital fact is that there should be stability in terms of trade and exchange rate policies while also preventing changes in those policies for long term so that the end markets of the agricultural products could be retained and developed because, in case of lacking stability in policies, the exporters lose their planning power and competitiveness in long term. Then, the risk of their activities increases which leads to reduced export value of agricultural products.

## Table

Results from Phillips Perron (PP) and Dickey Fuller unit root tests

Source: Research results.

Results of F test model

Source: research results.

Estimation of long term factors using ARDL model

Source: Research results.

Estimation of error correction model’s factors using ARDL model

Source: Research results.

## REFERENCES

1. Alijani, F. , Homayouni, M. , Karbasi, A. , and Mozaffari, M. (2010), Effectiveness of economic policies on exporting agricultural and industrial products in Iran, Journal of Economic Research, 4, 1-17.
2. Asgarpour, H. , Mohammadpour, S. , Rezazadeh, A. , and Jahangiri, K. H. (2012), Impact of exchange rate instability on exporting agricultural products in Iran, Research on Agricultural Economy, 4 (1), 121-137.
3. Azimi, H. and Yahyazadehfar, M. (2013), The effect of incentive programs and export supports on the trade of agricultural products, Economic Modeling, 7(2), 121-135.
4. Azizi, V. , Mehregan, V. , and Yavari, G. H. (2015), Role of protective policies on development of agricultural products’ export in Iran, Economic Research and Agriculture Development in Iran, 46 (l1), 107-119.
5. Bahmani-Oskooee, M. , Halicioglu, F , and Mohammadian, A. (2018) On the symmetric effects of changes on domestic production in Turkey, Economic Change and Restructuring, 51(2), 97-112.
6. Banerjee, A. , Dolado, J. , Galbraith, W. , and Hendry, F. (1993) Cointegration, Error-Correction and the Econometric Analysis of None-Stationary Data, Advanced Text in Econometrics, Oxford University Press, Oxford.
7. Canova, F. (1995), VAR models: Specification, estimation, inference and forecasting, In H. Pesaran and M. Wickens (eds.), Handbook of Applied Econometrics, Chapter 2, Blackwell, Oxford, UK.
8. Dadras Moghaddam, A. and Zibaei, M. (2009), Relationship between grand economy variables and agriculture sector in Iran (stressing on money policies), Iran’s Economic Researches Journal, 39, 95-112.
9. Daei, K. S. , Emamverdi, G. H. , and Shayesteh, A. (2014), The effect of real exchange rate on non-oil exports to Iran, Journal of Financial Economics (Financial Economics and Development), 8(29), 151-168.
10. Dehghan, H. , Mehrabi, B. H. , and Rahbar, D. A. (2014), Impacts of financial and taxation policies on agricultural trade in Iran, Research and Scientific Journal of Budgeting and Planning, 19(1), 111-128.
11. Ferro, E. , Otsuki, T. , and Wilson, J. S. (2015), The effect of product standards on agriculture exports, Food Policy, 50, 68-79.
12. Fogarasi, J. (2010), The effect of exchange rate volatility upon foreign trade of Romanian agricultural products, Global Development Network Regional Research Competition, Project RRC8+39, https://www.researchgate.net/publication/228546513.
13. Gilbert, N. A. , Linyong, S. G. , and Divine, G. M. (2013), Impact of agricultural export on economic growth in cameroon: Case of Banana, Coffee and Cocoa, International Journal of Business and Management Review, 1(1), 44-71.
14. Goswami, C. and Saikia, K. K. (2012), FDI and its Relation with Export in India, status and prospect in North East Region, Procedia: Social and Behavioral Sciences, 37, 123-132.
15. Granger, C. W. J. , Huang, B. N. , and Yang, C. W. (1998), A bicariate causality between stock prices and exchange rates: Evidence from recent Asianflu, The Quarterly Review of Economics and Finance, 40(3), 337- 354.
16. Hasanov, F. (2012), The impact of the real exchange rate on non-oil exports. Is there an asymmetric adjustment towards the equilibrium?, In: The George Washington University, RPF Working Paper, 1-24.
17. Karami, A. and Zibaei, M. (2008), Impacts of exchange rate volatility on exporting agricultural products in different countries, Journal of Economic Research, 8(13), 59-71.
18. Kazerooni, A. R. and Feshari, M. (2010), The impact of the real exchange rate volatility on non-oil exports: The case of Iran, International Economic Studies, 36(1), 9-18.
19. Khalighi, L. and Fadaei, M. S. (2017), A study on the effect of exchange rate and foreign policies on Iranians dates export, Journal of the Saudi Society of Agriculture Sciences, 16(2), 112-118.
20. Kouchakzadeh, S. and Karbasi, A. (2015), Factors influencing on trading saffron in Iran, Publication of Saffron Culture and Technology, 3(3), 217-227.
21. Liefert, W. M. and Westcott, P. C. (2016), Modifying agriculture export taxes to make them less marketdistorting, Food Policy, 62, 65-77.
22. Pakravan, M. and Gilanpour, A. (2013), A study of the perspective for export potentials and competitiveness of Iran’s agricultural products in Middle East and Northern Africa, Economy and Agriculture Development (Agricultural Sciences and Industries, 1(127), 51-63.
23. Peng, X. , Marchant, M. A. , and Reed, M. R. (2004), Identifying monetary impacts on food prices in china: A vec model approach, Paper prepared for presentation at the American Agricultural Economics Association Annual Meeting in Denver, Colorado, August 1-4.
24. Pesaran, M. H. and Shin, Y. (1998), An Autoregressive Distributed Lag Modeling Approach to Cointegration Analysis, Centennial Volume of Rangar Frisch, Cambridge University Press, Cambridge.
25. Pesaran, M. H. , Shin, Y. , and Smith, R. J. (2001), Bounds testing approaches to the analysis of level relationships, Journal of Applied Econometrics, 16(3), 289-326.
26. Prasanna, N. (2010), Impact of foreign direct investment on export performance in India, Journal of Social Sciences, 24(1), 65-71.
27. Safari, S. , Rahmani, M. , and Ahmadi, H. (2014), Impacts of exchange rate volatility on exporting agricultural products according with section two of general agriculture policies, Journal of Grand and Strategic Policies, 5, 97-109.
28. Saidane, M. (2017), A Monte-Carlo-based latent factor modeling approach with time-varying volatility for value-at-risk estimation: Case of the Tunisian foreign exchange market, Industrial Engineering & Management Systems, 16(3), 400-414.
29. Shrestha, M. B and Chowdhury, K. (2005), ARDL Modelling Approach to Testing the Financial Hypothesis, Department of Economics, University of Wollongong, New South Wales, Australia.
30. Sonaglio, C. M. , Campos, A. C. , and Braga, M. J. (2016), Effect of interest and exchange rate policies on Brazilian export, EconomiA, 17(1), 77-95.
31. Tashkini, A. (2005), Applied Econometrics with Microfit. Artistic andCultural Institute of Dibagaran, Tehran.
32. Yufu, N. , Lixia, R. , and Jianjun, L. (2013), Inventory models for fresh agriculture products with time-varying deterioration rate, Industrial Engineering & Management Systems, 12(1), 23-29.
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