Курсовая работа (т): Analysis of impact of exchange rate volatility on international trade

Analysis of impact of exchange rate volatility on international trade

Introduction

the present time globalization has becoming more significant and important phenomenon in the modern world, especially in the area of economic relations. The great example for this statement is the world economic crisis, which began in 2008. The main reason for this crisis is that the mortgage crisis happened in the USA in 2007, while it spread all over the world. The perceptible demonstration of globalization can be named the increase in the number of multinational corporations, the establishment of economic and politic unions (for instance, EAEU), etc. It is noteworthy to mention that the crucial role (even may be by the far the most important) role in international economic relations is played by exchange rates, because they have a direct impact on financial and trade flows between countries. For instance, in the case of depreciation of the national currency the country’s export will go up, given the fact that the price of export, denominated in foreign currency (US dollar) will decline for foreigners, while at the same time the country’s import will grow, because the price of import, denominated in national currency, will become higher for national consumers. It is essential to pay attention to the fact that not only the exchange rates, but also exchange rate volatility help to explain various economic situations, taking into account that the uncertainty has become a significant force, which influence crucially the economic sphere of society. This trend can help to explain the existence of a multitude of different theoretical and empirical works, devoted to the analysis of the impact of exchange rate volatility on various economic areas, including international trade.aim of this research consists in investigating the influence of exchange rate volatility RUB/USD on aggregate export of Russian Federation.into consideration the aim of this scientific work, it is possible to formulate following goals of the research:

)        Considering the various theoretical models, related to the influence of exchange rate volatility on international trade

)        Estimating the nominal exchange rate volatility RUB/USD by using ARCH model

)        Constructing autoregressive distributed lags model (ADL model) in which the export of Russian Federation serves as a dependent variable, while explanatory variables include real effective exchange rate index RUB/USD, Russian industrial production index and estimated nominal exchange rate volatility RUB/USD.scientific work is organized as follows: in the second section the literature survey of various works, related to the influence of exchange rate volatility on international trade, is represented; in the third section the data, used in this research, are described in details, the empirical methodology, which serves as a base for further empirical analysis, is considered and descriptive statistics of investigating variables are calculated and the information about the movements of nominal exchange rate volatility is visualized; in fourth section it is paid attention to the main part of this work- empirical analysis; in the fifth section some suggestions about future research, related to this topic, are made, in the last part of this work the conclusion is drawn .

1. Review of literature, devoted to analysis of impact of exchange rate volatility on international trade

spite of the fact that that topic of the influence of exchange rate volatility on international trade is relatively new for economic literature, taking into account that this area of economic thought is extremely actual for modern world economy, a multitude of different theoretical, as well as empirical, articles and scientific works has been already written. It is arduous to distinguish the common feature of these works, because of their great variety: the existence of large amount of various approaches to modeling the effect of exchange rate and different results of empirical analysis, made by scientists in this field (positive, negative effect, insignificant impact).of the first the most important works in the area of investigating the influence of exchange rate volatility on international trade is the article “The effect of exchange rate uncertainty on the prices and volume of international trade”, written by the authors P. Hooper and S.W. Kohlhagen (1976). In the model, developed in this work, the import demand and export supply are considered, taking into account that exchange rate volatility or exchange rate uncertainty is introduced in this model through the variance of importer’s and exporter’s profit. Then, maximizing the utility of importers and exporters and expressing some variables in terms of others, researchers find the equilibrium values of quantity of trade and price. During the next stage the authors find the first partial derivatives of price and volume of international trade with respect to the exchange rate variance. Having made these mathematical transformations, the authors obtain following result: in the case of risk-averse exporters and importers the increase in exchange rate volatility leads to the decline in volume of international trade, while the impact of growth of exchange rate volatility on price of international trade has an ambiguous effect on price. In the case of risk-neutral exporters and importers the exchange rate volatility does not have any impact on the price and volume of international trade. Finally, if exporters and importers are risk-loving, the effect of increase in exchange rate volatility on volume of international trade is positive. the article “Exchange rate variability and the slowdown in growth of international trade” the author Paul De Grauwe (1988) attempts to analyze the problem of influence of exchange rate volatility on international trade by the idea of modern theory of production and consumption under risk: the effect of risk is not so simple that only negative impact is possible. The individual producer, which has a choice between producing for foreign market and for home market, given the fact that both markets are perfectly competitive, lies in the foundation of the constructed model. It is assumed that labor is only one factor of production in the model. Then the profit function and production functions for foreign and home markets are defined. Paul De Grauwe maximizes the expected utility of producer’s profit, obtaining, as a result, optimal condition. Having finished transformations, described above, the author obtain the following conclusion: if producers are “sufficiently risk-averse”, the growth of exchange rate risk will lead to the increase of expected utility of export revenue and, as a result, increase in export. In the case of not “sufficiently risk-averse”, the opposite is true: the higher exchange rate volatility will make expected utility of export revenue lower, inducing producers to export less. The economic mechanism of such influence is so: “sufficiently risk-averse” producers worry about the worst outcomes and, consequently, increase in exchange rate risks stimulates them to export more in order to avoid the serous decline of their incomes. Not so “sufficiently risk-averse” producers pay less attention to the best and the worst outcomes and, therefore, the growth of exchange rate risk motivates them to decrease their export activity. In addition to this, in this article the obtained result is explained from the point of substitution and income effects. The substitution effect can be defined in this manner: in the case of rise of exchange rate risk the attractiveness of export activity, connected with risk, goes down, decreasing the export and stimulating to shift to risk-free activity (for instance, production for home market). The income effect is formulated so: the growth of uncertainty makes expected utility of export revenue lower and this decrease must be compensated by increase in export.the article “Exchange rate volatility and international trading strategy” (Franke, 1991) the problem of the influence of exchange rate volatility on international trade is investigated by using the term “cash flow”. One of the most distinctive features of the model, built by Gunter Franke, is that the entry costs of entering the foreign market and, respectively, exit costs are assumed to exist. In the model it is assumed that there are two countries; the market structure, used in this model, is monopolistic competition. The trading strategy, which firms use for exporting activity, is called “bang-bang” strategy, which implies that the firm enters the foreign market, when the log of exchange rate is higher or equals to entry costs, while it exits the foreign market, when the log of exchange rate is lower or equals exit costs. Given the fact that the firms follow this “bang-bang” trading strategy, firms, which are have a comparative disadvantage in international trade, will expand their export, if exchange rate volatility goes up, because their expected cash flows from exporting will increase by a higher rate than their entry and exit costs will. previous articles do not assume the existence of forward market, which makes possible to purchase forward contracts to buy or sell currency at a fixed rate in order to hedge exchange rate risk. It is obvious that it is arduous to overestimate the role of forward markets. A multitude of scientists deemed that the existence of forward markets made the impact of exchange rate volatility on international trade insignificant, given the fact that forward markets provide producers an opportunity to overcome exchange rate uncertainty by acquiring forward contracts. However, some researchers do not agree with this statement. For example, in the article “International trade and exchange rate volatility” the scientists J-M Viaene and C.G. de Vries (1991) consider the model, incorporating the forward market and the influence of Central Bank, which shows that the impact exchange rate volatility on international trade exists. In this work the behavior of importers, exporters, speculators and Central Bank is investigated. As a result of conducted research, several conclusions are obtained. First of all, taking into account the absence of forward market, the growth of mathematical expectation of exchange rate results in increase in export and decrease in import, which corresponds to the traditional considerations about international trade. If exchange rate volatility goes up, both import and export will decline. On the hand, if we assume the existence of forward market, taking into account the risk- aversion of the majority of participants of forward market and the absence of official intervention of Central Bank, the growth of mathematical expectation of exchange rate leads to the growth of import and export, and the increase in exchange rate volatility causes the decline (increase) in export and growth (decrease) in import if the observed country faces the positive (negative) trade balance. However, if the condition of risk-aversion of the majority of participants of forward market is not complied, i.e. the majority of participants of forward market are speculators, who are risk-loving agents, the result becomes unclear. the article “Exchange rate volatility and international trade” the scientists Udo Broll and Bernhard Eckwert (1999) consider the influence of exchange rate volatility on international trade using “real option approach”: export strategy is rather similar to option, because the revenue from home sales is fixed, while the revenue from foreign sales is random, depending on fluctuations of exchange rates. The model, which is described in this work, is built for the firms, which have a choice to sell their goods in home or foreign market, given the fact they make decisions based on the exchange rates (the flexibility of sales). In this case the price of home market should be considered as a strike-price of the export option. The firm decides to export or not, taking into account the value of exchange rate. The minimum that the firm can obtain is the price of its goods in home market. According to this approach, the impact of exchange rate volatility may be positive or negative. Taking into consideration that the firm is risk-averse, the growth of exchange rate volatility causes decline in expected utility of revenue, leading to decrease in production and international trade. At the same time, the larger fluctuations of exchange rate make the export option more profitable (Higher exchange rate volatility makes possible to get higher revenue), stimulating the growth of production and export, because of the increase in exchange rate volatility. Depending on the degree of risk-aversion of the firm, it is defined which effect dominates. If relative risk-aversion is less than one, the increase in exchange rate volatility causes the rise in export. In other case of high relative risk-averse (it is higher than one) the opposite is true. the article “Elasticity of risk-aversion and international trade” (Broll, Wahl & Wong, 2006) it is considered that that the elasticity of risk-aversion with respect to the standard deviation of profit is the factor, which influences the direction of the effect of exchange rate volatility on international trade. The degree of risk-aversion is formulated as a marginal rate of substitution between mathematical expectations of exchange rate and standard deviation of exchange rate. According to the obtained results, it can be inferred that in the case of the rise of exchange rate volatility the export of the firm goes down, if the elasticity, the parameter, which is described above, is less than one, or, in other word, if the risk-aversion is inelastic with respect to standard deviation of profit. If the investigated elasticity equals to one, the increase in exchange rate volatility will have no effect on international trade. However, if the standard deviation elasticity of risk-aversion is higher than one, the volume of international trade will go up in the case of growth of exchange rate volatility. importance of considering the forward market for understanding the influence of exchange rate volatility on international trade is raised in the article “Currency hedging and goods trade” (Wei, 1999). In this work the “hedging hypothesis” is investigated. The main idea of the “hedging hypothesis” constitutes that if hedging instruments can be acquired without costs, output and export of the firms cannot be influenced by the exchange rate volatility. The rapid development of forward market and, as a result, easy access to hedging instruments leads to the fact that the “hedging hypothesis” can be named fair for current economic conditions and answers the question: why does not a great amount of empirical researches find a significant negative impact of exchange rate volatility on international trade? At the same time, despite the fact that the high level of development of forward markets is achieved in many countries, the statement about applicability of this hypothesis is far from the reality. Firstly, the use of hedging instruments is costly. In addition to this, the exchange rate volatility has a positive effect on the costs of use of hedging instruments. Thirdly, the hedging instruments are available only for the short period of time (from month to year), which may be shorter than the planning horizon of the vast majority of exporters and importers. As a result of conducted empirical analysis, Shang-Jin Wei makes following conclusion: the conception of the “hedging hypothesis” is really wrong.the article “Exchange rate volatility and international trade: A general - equilibrium analysis” (Sercu & Uppal, 2003) both the volume of international trade and the exchange rate volatility as an endogenous variables, i.e. those variables that are generated within the model. The base of this model is a model of two countries is the existence of transportation costs, which follows the Samuelson’s iceberg form. The authors Piet Sercu and Raman Uppal come to the idea that the sign of relation between exchange rate volatility and international trade depends on the source of changes of exchange rate volatility. The growth of output volatility leads increase in both exchange rate volatility and volume of international trade, i.e. these two variables change in the same direction. However, in the case of decrease in transportation costs, the exchange rate volatility goes down, while the volume of international trade goes up. In this way, it can be obtained that both positive and negative relation between exchange rate volatility and volume of international trade is possible.

2. Data, empirical methodology and descriptive statistics

2.1 Data

this research the following indicators are used: export of Russian Federation, industrial production index in RF, nominal exchange rate RUB/USD, real effective exchange rate index RUB/USD. All data was obtained from the official site of Federal Reserve Bank of St. Louis.this research quarterly data is used.list of variables, used in this research, is:

Table 1

description of variables in the statistical software Stata is:- aggregate export of Russian Federation_rate - nominal exchange rate RUB/USD_production - index of industrial production in RF _effective_exchange_rate - real effective exchange rate index RUB/USD

2.2 Empirical methodology

order to estimate the impact of nominal exchange rate volatility RUB/USD on Russian export it is essential to make two steps: estimating the nominal exchange rate volatility, obtained from ARCH model and building autoregressive models with distributed lags, based on available data and estimated nominal exchange rate volatility.

.        As it is mentioned above, first of all, it is important to estimate nominal exchange rate volatility RUB/USD by using ARCH model, which makes possible to investigate time-varying volatility (the volatility, which changes over time) :

>0, 0<  <1

ARCH model the conditional variation (time-varying volatility)  depends on the squares of the errors in the previous periods (). It is crucial to mention that all coefficients before ARCH parameter in this model must be positive and not be more than one (0<  <1) Moreover, the constant term must be also positive. ARCH model was proposed by R.F. Engle in his article “Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation” (1982). Nowadays ARCH model is widely used for various purposes of investigations of different financial time series, including the estimating exchange rate volatility. The main attractive feature of this model is that it does not neglect “news”. What is more, ARCH model pays to attention to the clustering of volatility, when high volatility follows high volatility and low volatility follows low volatility, which is rather common for real economies.

2.      The next step, according our empirical methodology, is constructing autoregressive models with distributed lags (ADL models) in order to analyze the direction of influence of nominal exchange rate volatility RUB/USD, estimated by the method, described above, on export of Russian Federation. Apart from nominal exchange rate volatility, following variables are used as a explanatory variables in the ADL models: Russian industrial production and real effective exchange rate RUB/USD. It is expected that the industrial production has a positive impact on export, because the growth of industrial production means that the competition in the domestic market becomes tougher, encouraging the producers to expand export activity. According to expectations, real effective exchange rate RUB/USD has also a positive effect on Russian export, because, taking into account the conception of traditional international trade theory, depreciation of the national currency or growth of relative foreign price level (the ratio of foreign price level and domestic price level) (growth of real effective exchange rate RUB/USD) leads to the increase in export due to its reduction in price for foreign consumers, and the decrease in import due to its rise in price for domestic consumers. In the model current value of nominal exchange rate RUB/USD volatility is not considered, given the fact that the exporters cannot react to current volatility of nominal exchange rate, only to lags of this variable. The empirical model, which is tested in this research, looks like:

 - the value of Russian export at the period t

 - the value of Russian industrial production at the period t

 - the value of real effective exchange rate RUB/USD at the period t

 - nominal exchange rate volatility RUB/USD at the period t-1 optimal structure should be defined by using information criteria.

3.      The final step, which should be made, if we want to finish empirical analysis, is considering the effect of reverse causality between values of export and nominal exchange rate volatility. In order to overcome this difficulty, the method, which is suggested in the article “Chickens, eggs, and causality, or which came first?”(1988), is used. The core idea of this method is that, initially, it is essential to build two regressions. In the first regression the current value of export serves as a dependent variable, while the independent variables are the lags of export and nominal exchange rate volatility. In the second regression the opposite situation is observed: the dependent variable is the current value of nominal exchange rate volatility and independent variables are the same as for the first regression.

If the null hypothesis that all coefficients before the lags of nominal exchange rate volatility equals to null ( is accepted, it is possible to say that the nominal exchange rate volatility does not cause changes in export. , we define the causality from export to exchange rate volatility.

If the null hypothesis that all coefficients before the lags of export equals to null ( is accepted, it is possible to say that the export does not cause changes in exchange rate volatility.

2.3 Descriptive statistics

graphic of nominal exchange rate, shown below, helps to demonstrate visually the existence and the magnitude of exchange rate volatility from the first quarter of 2000 to the third quarter of 2014. this graph we can see that high volatility is near high volatility and the low volatility is near low volatility. As a consequent, it is possible to make following conclusion about clustering of volatility - visual information provides us with the opportunity to use ARCH model for estimating nominal exchange rate volatility RUB/USD.graph of other observed variables can be found in Appendix B.

 1

descriptive statistics of values of economic parameters, used in the research, with the time span from the first quarter of 2000 to the third quarter of 2014, are demonstrated below:

Table 2

It is possible to prove the expectations about direction of impact of real effective exchange rate RUB/USD and Russian industrial production on Russian export, described in empirical methodology, by using correlation analysis:

Table 3

As it is seen from the preliminary results, export and real effective exchange rate and export and industrial production are positively linked.

3. Empirical analysis

3.1 Stationarity of variables

, it is really crucial to test time series of logarithmic values of nominal exchange rate, real effective exchange rate, industrial production and export for stationarity. Using non-stationary time series may lead to “spurious regressions”. values of export:

Logarithmic values of real effective exchange rate:

Logarithmic values of industrial production:

Logarithmic values of nominal exchange rate:

As it is seen from the obtained results, none of the variables is stationary time-series, because the null hypothesis that the time series contains the unit root is accepted at the significance level of 1 % (The real effective exchange rate is a stationary time series at the significance level of 5 %). In order to overcome the problem of non-stationary time series, it is high time to shift to the analysis of the first difference of investigated variables.first difference of logarithmic values of export:

The first difference of logarithmic values of real effective exchange rate:

The first difference of logarithmic values of industrial production:

All in all, according to results of tests, the problem of non-stationary time series is resolved for export, real effective exchange rate, industrial production, nominal exchange rate, because the first differences of these variables are stationary time series at the significance level of 1 % (The null hypothesis that these new obtained time series contain the unit root is rejected at the significance level of 1 %).

.2 Estimating nominal exchange rate volatility by using ARCH model

, ARCH model is constructed for further estimation of nominal exchange rate volatility RUB/USD, it is essential to test the existence of ARCH effects for the nominal exchange rate RUB/USD. In order to achieve this aim, LM test is conducted.

The obtained results show that the null hypothesis that there are no ARCH effects for the nominal exchange rate RUB/USD is rejected at the significance level of 1 %. Consequently, ARCH effects are observed for the nominal exchange rate RUB/USD. Now it is possible to build ARCH model.

The coefficient before ARCH parameter is significant at the significance level of 1 %, while it is also positive. This intermediate result allows to explain continue estimation of exchange rate volatility.’s test the obtained by using ARCH model time series of estimates of nominal exchange rate volatility RUB/USD for stationarity:

The null hypothesis that this time series contains the unit root is rejected at the significance levelof 1 %. Respectively, the estimated exchange rate volatility is a stationary rime series and it is possible to continue empirical analysis.graphic of nominal exchange rate volatility RUB/USD, obtained by using ARCH model, during the period from the first quarter of 2000 to the third quarter of 2014, looks:

2

3.3 Constructing ADL regressions

of all, it is essential to build regression, which incorporates following independent variables: the first lags of export, industrial production, real effective exchange rate and volatility, as well as the current values of industrial production and real effective exchange rate (In the model only the first lags are used, because the optimal structure of the lags involves only the first lags, according to information criteria (Appendix A)). As a result, we obtain the following model:

From this table it can be inferred that the coefficient before the current values of industrial production, as well as the coefficient before the first lag volatility are significant, because the null hypothesis that coefficients before these variables equal to null. On the other hand, other coefficients are insignificant. Now it would be an excellent idea to construct regression, incorporating the first lags of export and volatility and the current values of real effective exchange rate and industrial production

In the obtained model all coefficients are significant. The impact of industrial production and real effective exchange rate turns to be positive, as it has been expected. The growth of industrial production leads to increase in export, while the rise of real effective exchange rate causes the increase in export. The value of export in the previous period (the first lag of export) positively affects the current value of export, which seems rather evident. The positive sign of the coefficient before the first lag of nominal exchange rate volatility means that the obtained result is not intuitive: if the nominal exchange rate volatility RUB/USD goes up, the growth of export will happen.

.4 Determination of causality between export and volatility

spite of the fact that the positive impact of exchange rate volatility in the previous period on current value of export is obtained, this finding does not withdraw the question causality between exchange rate volatility and export: not only exchange rate volatility causes changes in export, but also export causes changes in exchange rate volatility. In order to find an answer to this question it is essential to method, described above: construction of two regressions with export and exchange rate volatility as dependent variables and the first lags of exchange rate volatility and export as independent variables.first regression with export as a dependent variable:

The second regression with exchange rate volatility as a dependent variable:

Taking into account the second regression with the exchange rate volatility as a dependent variable, it is remarkable that he first lag of values of export have a negative impact on current exchange rate volatility. This interesting result can be explained so: more closed economies required larger changes in exchange rates in order to achieve the adjustments of balance of payments (The ratio export and GDP (export/GDP) can be considered as a measure of openness of the economy) (Canales-Kriljenko & Habermeier, 2004). What is more, other explanations are also possible.these two regressions it can be concluded that not only the exchange rate volatility in the previous period has an impact on export in the current period, but also the export in previous period has an influence on exchange rate volatility in the current period. Therefore, it is impossible to make an inference about the unambiguous direction of the effect of exchange rate volatility on export, because the both influence of the first lag of exchange rate volatility on current export and impact of the first lag of export on current exchange rate volatility.

4. Future research

the fact that the result is obtained, it is essential to note what might be done in this area in the future. First of all, it would be a good idea to investigate disaggregated data of various branches of the national economy of Russian Federation (agriculture, food industry, light industry etc). In this case the influence of each variable, investigated in this research, for every sector. It is rather plausible that the influence of exchange rate volatility is different for different branches or is significant for some sectors and insignificant for others.is more, the obtained model can be improved by adding the determinants of export that are not used in this work. For instance, investigating the role of variables, related to government influence on export: subsidies to companies, exporting goods.into consideration that Russian government shifted from fixed to floating exchange rate system at the end of 2014, it would be interesting to conduct analogical research, but using future data in order to answer the question: does the influence of exchange rate volatility change, in the light of the larger exchange rate fluctuations.

Conclusion

work represents an empirical research of the impact of nominal exchange rate volatility RUB/USD on export of Russian export by using the time series of real effective exchange rate RUB/USD, nominal exchange rate RUB/USD, expot of Russian Federation and Russian industrial production during approximately fourteen years: from the first quarter of 2000 to the third quarter of 2014. In order to estimate nominal exchange rate volatility, ARCH model is applied. The obtained autoregressive model with distributed lags tells us that the value of estimated nominal exchange rate volatility in the previous period positively influence the export in the current period, as well as other variables: current values of real effective rate and industrial production and the first lag of export have an expected positive effect on current export. On the other hand, it is defined that the first lag of export affects the current exchange rate volatility. Consequently, the mutual influence of export and exchange rate volatility is observed. This fact can explain, in addition to other interpretations, the positive impact of the nominal exchange rate volatility RUB/USD on export of Russian Federation. Nevertheless, it would be a good idea for our Central Bank not to spend great efforts on stabilization of the exchange rate RUB/USD, but concentrate on stimulating economic growth in our country by reducing interest rates in order to increase private investments. However, it is clear that it is essential to conduct further research in order to find the most effective policy of Central Bank for achieving maximal economic result for Russian Federation.

References

1.   Broll U., & Eckwert B. (1999). Exchange rate volatility and international trade. Southern Economic Journal, 178-185.

2.      Broll U., Wahl J.E., & Wong W.K. (2006). Elasticity of risk aversion and international trade. Economics Letters,92(1), 126-130.

.        Canales-Kriljenko J.I., & Habermeier K. (2004). Structural factors affecting exchange rate volatility: A cross-section study.

.        Clark P., Tamirisa N., Wei S.J., Sadikov A., & Zeng L. (2004). Exchange rate volatility and trade flows-some new evidence. IMF Occasional Paper,235.

5.      Côté A. (1994). Exchange rate volatility and trade.Bank of Canada Work. Pap, 94-5.

.        De Grauwe P. (1988). Exchange rate variability and the slowdown in growth of international trade.Staff Papers-International Monetary Fund, 63-84.

.        Engle R.F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the Econometric Society, 987-1007.

.        Franke G. (1991). Exchange rate volatility and international trading strategy.Journal of International Money and Finance,10(2), 292-307.

.        Hill R.C., Griffiths W.E., & Lim G.C. (2008).Principles of econometrics (Vol. 5). Hoboken, NJ: Wiley.

.        Hooper P., & Kohlhagen S.W. (1978). The effect of exchange rate uncertainty on the prices and volume of international trade. Journal of International Economics, 8(4), 483-511.

.        Ozturk I. (2006). Exchange rate volatility and trade: a literature survey. International Journal of Applied Econometrics and Quantitative Studies, 3(1).

.        Sercu P., & Uppal R. (2003). Exchange rate volatility and international trade: A general-equilibrium analysis. European Economic Review,47(3), 429-441.

.        Thurman W.N., & Fisher M.E. (1988). Chickens, eggs, and causality, or which came first. American Journal of Agricultural Economics,70(2), 237-238.

.        Viaene J.M., & De Vries C.G. (1992). International trade and exchange rate volatility.European Economic Review, 36(6), 1311-1321.

.        Wang K.L., & Barrett C.B. (2007). Estimating the effects of exchange rate volatility on export volumes. Journal of Agricultural and Resource Economics, 225-255.

.        Wei S.J. (1999). Currency hedging and goods trade. European Economic Review, 43(7), 1371-1394.

.        Economic Data Federal Reserve Bank of St. Louis

rate volatility autoregressive export

Appendix A

criteria for the model, incorporating only the first lags

Information criteria for the model, incorporating the first two lags

Information criteria for the model, incorporating the first three lags

Appendix B

of export during the observed period

of real effective exchange rate RUB/USD during the observed period

Graph of industrial production RUB/USD during the observed period