Investigating the relationship between interest rate ...

‫اولین کنفرانس ملی مدیریت و سیستم های فازی با حضور چهره های سرشناس بین المللی‬ 9016 ‫ شهریورماه‬03 ،‫ دانشگاه علم و صنعت ایران‬،‫ تهران‬-‫ موسسه مهدپژوهش ره پویان حقیقت‬،‫دانشگاه ایوانکی‬

Investigating the relationship between interest rate and exchange rate: Application to a VAR model Habib Ansari Samani1, Majid Sheikh Ansari2* 1

Department of economics, Yazd University, Yazd, Iran

2

Department of economics, Yazd University, Yazd, Iran *

Corresponding author: [email protected]

Abstract Finance and economic literature are awash with theories and researches linking exchange rate, interest rate and inflation. This paper investigates the relationship between exchange rate and interest rate for Iran, by using time series techniques such as unit root tests, co-integration test and impulse response function. The study used data for the period 1991 to 2112. The existance of cointegration among the variables implies that the long run relationship between inflation, interest rate and exchange rate is existent. The empirical results of this study have been unable to detect a clear systematic relationship between interest rates and exchange rates. Keywords: Inflation, Interest rate, Exchange rate, VAR, Iran JEL Classification: E34, F41

1.

Introduction

The relationship between interest rates and exchange rates has long been a key focus of international economics. Most standard theoretical models of nominal exchange rates predict that exchange rates are determined by economic fundamentals. One such fundamental is the interest rate. Exchange rates fluctuations is one of the main obstacles that developing economies confront in the macroeconomic management. Especially during the economic crisis periods, this subject gains more importance in terms of cost and duration of the recovery process. Interest rate is, among other monetary policy instruments, constitutes an important part of policy variables in coping with unintended exchange rate fluctuations (Saraç and Karagöz, 2112). Even in textbook models, however, the relation between interest rates and the nominal exchange rate can differ greatly. In the simplest monetary model of the exchange rate, for example, an increase in the home interest rate will be associated with a fall in real money demand and, hence, a depreciation of the domestic currency. In contrast, in a Dornbush-type, sticky prices model, an increase in the home interest rate (in response to a reduction in the level of the money supply) will appreciate the currency. Perhaps reflecting this tension between flexible and sticky prices models, the data has not provided an unambiguous answer either. Indeed, a slew of studies that have examined the time series relationship between interest rates and the nominal exchange rate tend to either find conflicting results that depend on the sample of countries and/or the time period studied (Hnatkovska et al., 2114). The absence of a clear empirical relationship between interest rates and the exchange rate is even more problematic from the perspective of practitioners. A short-term interest rate is the typical policy instrument www.Icmfs.ir 1


used by policymakers to affect currency values. If there is no clear relationship in the data, then why do policymakers persist in using the interest rate instrument to affect exchange rates? Are the typical time series empirical results camouflaging some key features of this relationship? Rest of the paper is organized as follows: In the second and third sections, the literature and theoretical aspects of the relationship between interest rates and exchange rate are reviewed. In the fourth section, details of the methodological procedure are explained. Result of the empirical analysis is given in the fifth section. The paper concludes in the sixth section. 2. Literature review The relationship between interest rates and exchange rates has long been a key focus of international economics. Most standard theoretical models of exchange rates predict that exchange rates are determined by economic fundamentals, one of which is the interest rate. Keminsky and Schumulkler (1991) examined the time series correlation between daily exchange rates and interest rates for Indonesia, Korea, Malaysia, the Philippines, Thailand, and China by using daily data during the second half of 1991. They found that the signs of these correlations were very unstable and concluded that interest rates in those countries must not be an exogenous variable. In that year, Goldfajn and Baig (1991) have studied the linkage between real interest rate and real exchange rate for the Asian countries during July 1991 to July 1991 by using Vector Autoregression (VAR) based on the impulse response function from the daily interest rates and exchange rates. They have not found any strong conclusion regarding the relationship between interest rate and exchange rate. Gould and Kamin (2111) examined the interest rate and exchange rate relationship by studying the effect of interest rate, risk premium, and default probabilities on the exchange rates for Indonesia, South Korea, Malaysia, the Philippines, Thailand, and Mexico. They found that the exchange rates in these countries were influenced by credit spreads and stock prices rather than interest rates. According to them, their results neither support Mundell-Fleming’s view nor monetarist’s views. Kwan and Kim (2113) study investigated the empirical relationship between the exchange rate and the interest rate for four Asian crisis countries – Indonesia, Korea, Philippines and Thailand. Using a bivariate VAR-GARCH model they examined the empirical relationship between exchange rates and interest rates, and investigated how the dynamics between them have changed following the post-Asia crisis. Their findings suggested these countries did not use interest rate policy more actively to stabilize exchange rates after the crisis, and provided evidence that their domestic currencies exhibited greater sensitivity to competitors’ exchange rates post-crisis. Further, the results indicate that increased exchange rate flexibility did not lead to greater stability in interest rates in these economies. They further argue that as for the interaction between exchange rate and interest rate volatility, there is no strong evidence that an increase in exchange rate variability is associated with an increase in interest rate volatility in any of the four countries. Sanchez (2112) states that there has been a special interest in the link between exchange rates and interest rates in both advanced and developing countries. The study consisted of the experience of some Asian EMEs at the time of the Asian crisis (1991-1991) and a couple of periods of financial turmoil in Brazil (1999 and 2112-2114). It makes use of the identified vector autoregressions (IVAR), given the important role these variables play in determining developments in the nominal and real sides of the economy. Further, his findings showed that, in response to an adverse risk premium shock, exchange rates and interest rates exhibit a negative correlation when depreciations are expansionary and a positive correlation when they are contractionary. Hacker et al., (2111) examined the relationship between spot exchange rate and nominal interest rate differential. Using wavelet analysis to investigate the relationship between the spot exchange rate and the interest rate differential for seven pairs of countries, with a small country, Sweden, included in each of the www.Icmfs.ir

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cases. Their key empirical results showed that there tends to be a negative relationship between the spot exchange rate (domestic-currency price of foreign currency) and the nominal interest rate differential (approximately the domestic interest rate minus the foreign interest rate) at the shortest time scales, while a positive relationship is shown at the longest time scales. This indicates that among models of exchange rate determination using the asset approach, the sticky-price models are supported in the short-run while in the long-run the flexible-price models appear to better explain the sign of the relationship. The results when using the two different data frequencies – monthly and quarterly – are consistent with each other in this finding.

4. Economic theory In this section, we present more in detail five open-macroeconomic models which include a distinctive shortrun element. These models are 1) a simple Keynesian model with an exogenous exchange rate change, 2) the floating exchange-rate version of the Mundell-Fleming model, 4) the Dornbusch (overshooting) model, 3) the portfolio-balance, and 2) Redux model. By discussing these models, we hope to illuminate some issues on causality between our variables. We also briefly discuss a couple of long-run models to round-out the discussion, and present some previous empirical research in the area. In our discussion, we will often discuss how the domestic interest rate moves and assert without explanation that the interest rate differential moves in the same direction. The reason is that in these cases we can say that the foreign interest rate is either constant (due to a small country assumption) or that the foreign interest rate is moving in the opposite direction due to a symmetrically opposite logic. In addition, it is important to recognize that our definition of the exchange rate as the domestic-currency price of foreign currency has the implication that a rise in that exchange rate is synonymous with depreciation of the home currency. First, we consider how the interest rate differential and the exchange rate could be related through an exogenous change in the exchange rate. An increase in a country’s exchange rate due to exogenous real exchange rate movement (due to changes relative supply and relative demands for the products of various countries) leads to an increase in that country’s trade balance. If one considers the standard IS-LM framework, that increase in the trade balance in turn drives up that country’s interest rate due to the increase in aggregate demand for its products. This channel is referred to as Keynesian here due to its focus on aggregate demand. This phenomenon works as presented in the sticky price world typically assumed in the short run for Keynesian models. In the long-run, assuming the country had full employment to begin with the increase in aggregate demand drives output to be above the full-employment level, which induces price increases that cause real money supply to fall and interest rates to rise further in the long run. Thus, both in the short run and in the long run, this model indicates a positive causal relationship from the exchange rate to the interest rate differential. In the Mundell-Flemming (M-F) model (as in Mundell (1922) and Fleming (1922)), the effect of an initial policy action and its sequential adjustment in this model depends on the degree of capital mobility. In case of high capital mobility, the effect of monetary expansion or fiscal contraction in the home country is a decrease of the interest rate at home, given that the home country is small and foreign variables are exogenously taken. The decrease in the interest rate of the home country leads to an incipient deficit in the balance of payments at the original exchange rate due to a potentially massive capital outflow from the home country. Therefore, there is an excess demand for foreign currency at the original exchange rate, so the exchange rate of the home country depreciates. That depreciation leads to an increase in the trade balance for the home country, which in turn means that aggregate demand in the home country increases so the homecountry interest rate increases and the capital account does not drop as much as it would otherwise. Overall, the home-country interest rate ends up lower than before the monetary expansion, and to meet the requirement that the balance of payments must be zero at all times, the exchange rate must rise sufficiently such that increase in the trade balance totally offsets the overall drop in the capital account (or financial account, in more modern terminology). In this model, we see that in the short-run a negative causal relationship from the interest rate differential to the exchange rate is apparent—the interest rate falls and www.Icmfs.ir

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because of that the exchange rate rises. At the time scale, we also see causality in the other direction with an opposite sign in the relationship: the rise in the exchange rate causes the trade balance to increase, resulting in a rise in the exchange rate. The Dornbusch overshooting model, originally formulated by Rudiger Dornbusch (1912), includes an explicit treatment of expectations of exchange rate changes, the lack of which is a serious problem with the Mundell-Fleming model, and, unlike the latter model, demonstrates what happens between the sticky-price short-run and the flexible price long-run. In the Dornbusch overshooting model, the two markets-the financial market and the goods market-are allowed to have different adjustment speeds. The consequence of allowing in these two markets is that financial market has to over adjust to disturbances, so that the pricestickiness in the goods market can be compensated in the short-run. In this model, monetary expansion by the home country causes the interest rate to drop, which in turn results in the exchange rate rising immediately to maintain UIP. The UIP condition is 1

(1)

where i is the domestic interest rate, i* is the foreign interest rate, E is the spot exchange rate, and Ee is the expected future exchange rate (the long-run exchange rate in this model). Keeping i* and Ee constant, a drop in i needs to be offset by a rise in E to maintain the equality. The monetary expansion also makes the expectation of the future exchange rate increase, since prices will rise which in turn put pressure on the exchange rate to be higher ultimately to maintain purchasing power parity. The consequence of the higher Ee is even more pressure for E to rise to maintain UIP, resulting in E overshooting its level in the long-run. Between the short-run and the long-run, prices rise, which results in i rising and (again to maintain UIP) E falling. As in the Mundell-Fleming model, there appears a negative causal relationship from the interest rate to the exchange rate in the short run in the Dornbusch overshooting model. However, between the short-run and the long-run, this negative causal effect of i on E continues, driven always by UIP. The portfolio balance model, brought to prominence in Branson (1914), Branson and Halttunen (1919) and Branson, Halttunen, and Masson (1919), allows for investors’ concerns about the riskiness of the assets in which they are invested and considers the slow adjustment of goods prices as in the Dornbusch model. Similar to the Mundell-Fleming model, a reduction in the return on assets in the home country (due to a monetary expansion, say) will initially result in capital flows out of that country, but unlike MundellFleming, those capital flows stop once investors have adjusted their portfolio shares to make the optimal trade-offs between risk and return. This situation again leads to an depreciation of the home country’s currency—the same reaction we saw in Mundell-Fleming and through the UIP condition in the Dornbusch model. The decrease in the interest rate in the home country due to a money supply increase, thus, leads to an excess demand for money and the excess supply of domestic bonds while it creates an excess demand for foreign denominated asset in a foreign currency. This process makes the exchange rate go up (i.e. domestic currency depreciation), which allows us to draw a negative causal relationship from the interest rate to the exchange rate in the short run, as in the Dornbush and Mundell-Fleming models. After the initial depreciation in the portfolio balance model, the home country collects foreign assets due to the depreciation-induced current account surplus (assuming it started with a current account equal to zero). Between the short-run and the long-run in this model, two adjustments are occurring. First, the homecountry’s goods prices are rising, reducing the competiveness it gained through the depreciation. Second, the home country’s exchange rate appreciates since the home-country investors value foreign assets less considering they collected a lot of them already through the short-run current account surplus. In addition, the exchange rate appreciates sufficiently to support a long-run home-country current account deficit funded by interest collected on the earlier collected foreign assets from the short-run current account surplus. As in the Dornbusch model, there is overshooting of the exchange rate, but the adjustment process does not include a change in the interest rate, so no causal relationship between the exchange rate and the interest rate is supported after the short run.

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The Redux model is a general equilibrium exchange-rate determination model dealing with two countries with the characteristics of monopolistically competitive industries, sticky prices, and an intertemporal approach to the current account balance, which was developed by the initial work of Obstfeld and Rogoff (1992). There is no causal relationship between the exchange rate and the interest rate is supported in its earlier form where uncovered interest rate parity is holding but monetary shocks simply cause nominal interest rates to change by the same amount in both countries so no expected depreciation or appreciation after that change is created. However, within the appendix of Obstfeld and Rogoff (1992) paper, an alternative small open economy model with nontraded consumption goods is presented, and that model does have the possibility that a money-supply increase Granger causes an exchange-rate to overshoot. Lane (2111) notes that that overshooting is associated with a lowered short-run nominal interest rate. An extension of the Redux model is made by Betts and Devereux (2111) by including pricing to market through local currency pricing, and found that under such circumstances a monetary expansion could lead to the interest rate differential decreasing along with exchange rate overshooting. Table 1 summarizes the above discussion with both the short-run and long-run models. Table 1: Causal relationships suggested by various exchange rate determination models Adjustment Process Short run to Adjustment Long run Short‐run Monetarist: Money Demand Effect Monetarist: Fisher Effect positively related Keynesian: Exogenous Exchange Rate Change Mundell‐Fleming Dornbusch Portfolio Balance

E reverses direction of movement found in the short‐run No causal relationship

Redux model

Note: Each arrow indicates the direction of the causal relationship while the sign above the arrow represents the sign of the causal relationship.

4. Methodology 4.1 Econometric framework and model specification This paper adopts the model specification used by Hacker et al., (2111) but modified so as to suit the study objectives and follows a vector autoregressive (VAR) approach. The VAR is a general dynamic specification because each variable is a function of lagged values of all the variables. Each equation has many lags of each variable, the set of variables must not be too large. A vector autoregressive (VAR) approach which can be represented as follows: 1

1

1

2

2

(1)

Where A is an invertible matrix (n*n) describing contemporaneous relations among the variables; is an ( 1 2 ) 1 is a vector of constants; (n*1) vector of endogenous variables such that is an (n*n) matrix of coefficients of lagged endogenous variables; is an (n*n) matrix whose non-zero off– diagonal elements allow for direct effects of some shocks on more than one endogenous variable in the system; are uncorrelated or orthogonal white-noise structural disturbances i.e. the covariance matrix ( ) 1 of is an identity matrix

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Unrestricted versions of the VAR model (and the error-correction model) are estimated by ordinary least squares (OLS) because Zellner (1922) proved that OLS estimates of such a system are consistent and efficient if each equation has precisely the same set of explanatory variables. If the underlying structural model provides a set of over-identifying restrictions on the reduced form, however, OLS is no longer optimal. The simultaneous equations system in a contemporaneous structural VAR, however, generally does not impose restrictions on the reduced form. The standard, linear, simultaneous equations model is a useful starting point for understanding the structural VAR approach. A simultaneous equations system models the dynamic relationship between endogenous and exogenous variables. If some shocks have temporary effects while others have permanent effects, the empirical model must account for this. Sims, Stock and Watson (1991) show that this reduced form is consistently estimated by OLS, but hypothesis tests may have non-standard distributions because the series have unit roots, their existence is controversial. 4.2 Unit roots tests Testing for the presence of unit root in the series is a primary step before attempting to estimating economic relationships. Furthermore, the test also helps in finding the order of integration at which the variables become stationary. These tests are necessary to avoid spurious regression (Gujarati, 2113). Hence, the whole idea for unit root test is to search for data generating process (DGP) namely: (a) Pure random walk meaning no intercept and no time trend items: (2) 1

∑

1

1

(b) Random walk with drift meaning intercept and no time trend item: (4) 1

∑

1

1

(c) Random walk with drift and time trend meaning intercept and time trend item: (3) 1

∑

1

1

There are various methods for testing unit roots such as Augmented-Dickey Test (ADF), extension to the dickey fuller test for example Pantula tests, Phillips Peron tests, Kwaitowski- Phillips-Schmidt-shin (KPS), Elliot-Rothenberg-stock point optimal (ERS) as Ng-Perron tests. This study will use ADF test for unit root.

4.4 Cointegration tests Cointegration gives an indication as to whether the variables will converge in the long-run to some sort of equilibrium. To ascertain whether such a relationship exist, this study employs the Johansen cointegration test in order to determine if there are any cointegrated equations. Since this will be done in the vector autoregressive (VAR) framework, the first step uses first difference as shown below: 1

whereas

1

2

2

(2)

is lag length n(p1) vector endogenous variable, then first difference changes below:

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‫اولین کنفرانس ملی مدیریت و سیستم های فازی با حضور چهره های سرشناس بین المللی‬ 9016 ‫ شهریورماه‬03 ،‫ دانشگاه علم و صنعت ایران‬،‫ تهران‬-‫ موسسه مهدپژوهش ره پویان حقیقت‬،‫دانشگاه ایوانکی‬ 1

(2)

∑ 1

1

Whereas is a short term adjusting coefficient to explain short-term relationship, is long term shock vector that includes long-term information that tips off on the existence long term equilibrium relationship. Moreover rank of decides the number of cointegrated vector. has three hybrids: (a) rank () n, then is full rank, meaning all the variables are stationary series in the regression ( ) (b) rank () 1, then is null rank, meaning variables do not exhibit cointegrated relationship. (c) 1 rank () r n , then some of variables exist r cointegrated vector. The Johansen cointegration approach uses rank of to distinguish the number of cointegrated vector and examine rank of vector in testing how many of non-zero of characteristic roots exist in the vector. There are two statistic processes for cointegration. (i)

Trace test:

1

( )

(

1

( )

(

( )

) )

1

∑

̂)

(1 1

T is sample size, is estimated of characteristic root. If test statistic rejects least r+1 long term cointegrated relationship. (ii)

1

that means variables exist at

Maximum eigenvalue test:

1

( )

(

1

( )

(

(

) 1 (1

1)

)

̂1 )

If test statistics accepts 1 that means variables have r cointegrated vector. This method starts testing from variables that do not have any cointegrative relationship which is r=1. Then test has added the number of cointegrative item to a point of no rejecting 1 that means variables have r cointegrated vector. 4.4 Impulse response function Impulse responses trace out the response of current and future values of each of the variables to a unit increase in the current value of one of the VAR errors, assuming that this error returns to zero in subsequent periods and that all other errors are equal to zero. More generally, an impulse refers to the reaction of any dynamic system in response to some external changes. According to Hamilton (1993), a VAR can be written in vector moving average (MA) as follows: 1

Thus, the matrix

1

1

2

has the interpretation

consequences of one unit increase in the variable at time t + s (

(

) ),

(1)

2

that is, the row i, column j element of variable’s innovation at the t (

identifies the

) for the value of the

holding all the other innovations at all dates constant. A plot of

function of s is called the impulse response function. It describes the response of impulse in with all other variables dated t or earlier held constant (Girma, 2112).

(

)

(

)

as a

to a one-time

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5. Empirical results 5.1 Unit root test The Augmented Dickey-Fuller (ADF) test is applied. The results of the unit root test are presented in Table 2. The table shows that the series were found to be non-stationary and after differencing them, the entire test statistic shows that all the series became stationary. Table 2: Results of ADF unit root test ADF Critical values Variables

I(1)

11 critical values

12 critical values

111 critical values

Exchange rate

-35922 (15114)

-45121

-25132

-25221

Interest rate

-15422 (15111)

-45132

-25242

-25429

Inflation

-25122 (15111)

-45112

-45321

-25122

Source: Own calculation * The optimal lag structure is determined by Schwartz Bayesian Criterion ** The p-values are in parentheses

Reduced form VAR model is estimated based on the information criteria. The convergence lag length suggested is two. 5.2 Testing for cointegration Table 4: Johansen Cointegration Hypothesized No. of CE(s)

Trace Statistic

21 Critical Value

Prob

R=1 R 1

19252* 93522*

91524 11511

151111 151114

R 2

21529

32542

151124

Hypothesized No. of CE(s)

Max-Eigen Statistic

21 Critical Value

Prob

R=1 R 1

11511* 32593*

34511 41592

151111 151292

R 2

23532

21511

151912

As can be seen, both tests (trace and max-eigenvalue) indicate that two cointegrations exist among the variables included in the system at 2 percent level of significance. The existance of cointegration among the variables implies that the long run relationship between inflation, interest rate and exchange rate is existent

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5.4 Impulse response function Figure1: Impulse response of exchange rate, interest rate and inflation rate Response of exchange rate to exchange rate

Response of exchange rate to interest rate

Response of exchange rate to inflation

Response of interest rate to exchange rate

Response of interest rate to interest rate

Response of interest rate to inflation

Response of inflation rate to exchange rate

Response of inflation rate to interest rate

Response of inflation rate to inflation rate

Figure 1 above, presents the responses of the exchange rate to changes in the level of interest rate. In contrast to theoretical expectations such as that by Hacker et al., (2111), the response of exchange rate to interest rate in the short-run is observed to be a stable increase in the exchange rate, the effects of the shock are seen to be brief and pass on only for about a year. Thereafter, there is convergence toward the steady state although slightly above the baseline. However, the effects remained permanent even after 23 quarters. The response of interest rate to exchange rate is negative in the transitory period but die off in the 4 period followed by a permanent effect from the 12 period which is above the steady state. A transitory negative effect in the year 1 which is short-lived is observed in the response of exchange rate to inflation, followed by a gradual positive effect in the years 4-1 succeeded by a permanent effect along the steady state through to the year 23. However, in the response of interest rate to inflation, a shock on inflation results in positive temporary effect through to the year 4 which dies off as seen by a negative drop in the interest rate until the year 19 at which it converges toward the steady state along the baseline

6. Conclusion The study examined the relationship between inflation, interest rate and exchange rate. Economic theory postulates that there exists a negative relationship between interest rates and exchange rates. This therefore formed the basis for this study so as to examine whether this holds for Iran and whether interest rate policy does really lead to exchange rate stability. The study employed considerable amount of secondary data from 1991-2112. It introduced the model specification and econometric procedures to be carried out which included the unit root test, cointegration test, and impulse response functions.

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The VAR procedure designates that both the interest rate and the exchange rate are affected by their respective previous lagged values. In light of the above results, it can be recommended that policy makers consider the inflation rate for forecasting and policy planning. From the backdrop of economic theory, it is well documented that interest rate does affect macroeconomic policy. This study showed that for Iran, there is long run relationship between variables, however, a uni-causal relationship exists between the exchange rate and inflation rate. This does not necessarily imply that monetary authorities should not exercise restraint when regulating interest rate, but rather the interest rate should be monitored regardless of this result. Interest rate should be monitored and adjusted accordingly because it is a contributing factor in macroeconomic policy making. The interest rate is affected by many components such as economic stability, monetary policy etc., for which exchange rate is one of those macroeconomic variables. Future research should adopt a different methodological approach and possibly, to add more additional variables in the estimations to determine whether similar results would be obtained. Quarterly frequencies maybe more appropriate due to the fact that sometime monthly rate remains constant over a period.

Reference Betts, Caroline and Devereux, Michael B. (2111) Exchange rate dynamics in a model of pricing-to-market, Journal of International Economics, 22(1), pp. 212-233. Branson, W. H. (1914) Macroeconomic determinants of real exchange risk. In Herrin R. J. (ed.) Managing Foreign Exchange Risk. Cambridge: Cambridge University Press. Branson, W. H. and Halttunen H. (1919) Asset market determination of exchange rates: initial empirical and policy results. In Martin J. P. and Smith A. (eds) Trade and Payments Under Flexible Exchange Rates. London: Macmillan Branson, W. H., Halttunen H. and Masson (1919) Exchange rates in the short-run: the dollar-Deutschmark rate. European Economic Review. 11, pp 414-423. Dornbusch, R. (1912) Expectations and Exchange Rate Dynamics. Journal of Political Economy, 13(2), pp.1121-1112. Fleming J. M. (1922) Domestic financial policies under fixed and floating exchange rates. IMF Staff Papers, 9(4),pp 429 – 411. Lane, Philip R. (2111) The New Open Economy Macroeconomics: a Survey. Journal of International Economics, 23(2) pp. 242-222. Mundell, R. A. (1922) The appropriate use of monetary and fiscal policy under fixed exchange rates. IMF Staff Papers, 9(1),pp 11-11. Obstfeld, M. and Rogoff, K. (1992) Exchange Rate Dynamics Redux. The Journal of Political Economy, 114(4), pp.223-221. Saraç, T.B., and Karagöz, K. (2112). Impact of Short-term Interest Rate on Exchange Rate: The Case of Turkey. Procedia Economics and Finance 41 , pp192 – 212. Zellner, A.(1962).‘An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias,’ Journal of the American Statistical Association,pp 348-68. Sims, C.A., Stock,J., and Watson, M.(1991)., ‘Inference in Linear Time Series Models with Some Unit Roots,’ Econometrica, pp 114-33 Gujarati, D.N. (2113) .Basic Econometrics. Fourth Edition. New York: Mc-Graw Hill Hamilton, J. (1993). Time Series Analysis. Princeton University Press:Princeton Girma, F.K.(2112).Relationship between Inflation and Economic Growth in Ethiopia: An Empirical Analysis, 19112111. Unpublished thesis (MPED, University of Oslo)

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‫اولین کنفرانس ملی مدیریت و سیستم های فازی با حضور چهره های سرشناس بین المللی‬ 9016 ‫ شهریورماه‬03 ،‫ دانشگاه علم و صنعت ایران‬،‫ تهران‬-‫ موسسه مهدپژوهش ره پویان حقیقت‬،‫دانشگاه ایوانکی‬ Kwan, H., and Kim, Y.(2113). The Empirical Relationship between Exchange Rates and Interest Rates in Post-Crisis Asia. Singapore Management University Press: Singapore Goldfajn, I. and Baig, T. (1991). ‘Monetary Policy in the Aftermath of Currency Crises:The Case of Asia’, International Monetary Fund Working Paper, WP/911111, Washington D.C. Sanchez, M.(2112). The Link Between Interest Rate and Exchange Rates: Do Contractionary Depreciations Make A Difference. Kaiserstrass: European Central Bank Keminsky, G. and Schumulkler, S. (1991), “The Relationship Between Interest Rates and Exchange Rates in Six Asian Countries” World Bank, Development Economics and Office of the Chief Economist, Washington, D.C. Gould, D. M. and Kamin, S. B. (2111), “The Impact of Monetary Policy on Exchange Rates During Financial Crisis”, International Finance Discussion Paper 229, Board of Governers of the Federal Reserve System, Washington D.C. Hnatkovska et al., Interest Rate and the Exchange Rate: A Non-Monotonic Tale Hacker, R.S., Kim, H., and Månsson, K. (2111). An Investigation of the Causal Relations between Exchange Rates and Interest Rates Differentials using Wavelets. CESIS Electronic Working Paper Series, Paper No. 212

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