Abstraction: The exchange rate is one of the most of import determiners of a state ‘s comparative degree of economic wellness. Exchange rate plays a critical function in a state ‘s degree of trade, which is critical to most free market economic systems in the universe. This paper is an effort to analyse the relationship between involvement rate, rising prices rate and exchange rate volatility in Malaysia covering the period between 1999-2009. This paper used time-series Vector Error Correction Model ( VECM ) attack of stationarity trial, cointegration trial, stableness trial and Granger causality trial. Impulse Response Function ( IRF ) has besides been generated to explicate the response to floor amongst the variables. The consequences show that the rising prices rate impacts the involvement rate as indicated by Granger-cause. Subsequently the involvement rate influences the exchange rate as shown by the Granger cause trial. Taking into history a long term relationship, involvement rate moves positively while rising prices rate goes negatively towards exchange rate volatility in Malaysia. The deduction of this survey is that increasing the involvement rate can be efficient in keeping exchange rate volatility. Future research workers should try to utilize panel informations and screen longer study continuance of above10 old ages by utilizing other variables.

Keywords: Exchange rate aˆ? Interest rate aˆ? Inflation rate aˆ? Vector Error Correction Model ( VECM ) aˆ? Impulse Response Function

## Introduction

Exchange rates play a critical function in a state ‘s degree of trade, which is critical to most every free market economic systems in the universe. For this ground, exchange rates are among the most watched analyzed and governmentally manipulated economic steps[ 1 ]and most states attempted to chair their domestic currency fluctuations by enforcing regulative limitations on exchange rate motions [ 1 ] . However, commanding the exchange rate could be really dearly-won, and even go pointless, when speculators attack a currency, even under authorities protection. High involvement rate will forestall capital escapes, hinder economic growing and, accordingly, hurt the economic system [ 2 ] .

In July 1997, fiscal crisis has gripped much of Asia. The crisis started inA ThailandA with the fiscal prostration of theA Thai bahtA caused by the determination of the Thai authorities toA floatA the tical, cutting itsA pegA to theA USD, after thorough attempts to back up it in the face of a terrible fiscal over extension that was in partA existent estateA driven [ 3 ] . Malaysia was besides under “ attacked ” by speculators within yearss of theA Thai bahtA devaluation. Then the Prime Minister, A Mahathir Mohammad imposed rigorous capital controls and introduced a MYR3.80 nog against theA US dollar.

Therefore, it would be interesting to research the factors of exchange rate volatility in Malaysia. The survey intended to look at the factors of exchange rate motions in Malaysia. In associating exchange rate alterations with alterations in involvement and rising prices rates, the International Fisher Effect theory provinces that the future topographic point rate of exchange can be determined from nominal involvement derived function. Harmonizing to [ 4 ] , the differences in awaited rising prices that are embedded in the nominal involvement rates are expected to impact the future topographic point rate of exchange.

An exchange rate has been defined by [ 5 ] as a comparative monetary value of two national monies. More specifically, it can be stated that the exchange rate is the ratio between a unit of one currency and the sum of another currency for which that unit can be exchanged at a peculiar clip. The macroeconomic analysis of exchange rate volatility starts with [ 6 ] Optimal Currency Area hypothesis. He shows that states with comparatively big bilateral trade and states with correlative economic dazes might benefits from a common currency. Harmonizing to the fitted GARCH ( Generalized Auto-Regressive Conditional Heteroscedasticity ) theoretical accounts, the exchange rate discrepancy is relentless and serially correlated [ 7, 8 ] . Thus current and past volatility of exchange rates can be used to foretell future volatility. However, flights with about indistinguishable initial conditions can differ a batch from each other [ 9 ] .

There is, so, a significant sum of research about the effects of volatility of a state ‘s ain existent exchange on certain macroeconomic variables. Higher volatility of the existent exchange rate hurt exports in a big group of developing states [ 10 ] . Recent and stronger grounds of a negative impact of exchange rate volatility on trade flows can be found in [ 11 ] and [ 12 ] . While [ 13 ] suggested that the fiscal variables such as external debt besides affect optimum exchange rate volatility.

It is an explanatory variable that explained the sensitiveness of the exchange rate due to the alterations in involvement rate. The more popular intercession tool in the exchange rate is altering involvement rate [ 14 ] . Irving Fisher, an American economic expert, developed a theory associating exchange rates to involvement rates. Interest rate derived functions tend to reflect exchange rate outlooks which besides known as Fisher Effect. In a survey by [ 15 ] , The International Fisher Effect ( IFE ) theory explained the derivation of relationship of the existent return to investors in place state is the foreign involvement rate and the alteration in the foreign currency value [ 16 ] .

Most surveies have been tested and analyzed the influence of involvement rate derived functions on alteration in exchange rates based on the IFE theory and old surveies [ 4 ] hence [ 1 ] provinces that high existent involvement rate is successful in controling exchange rate volatility. Harmonizing to the diary written by [ 17 ] , The common external factors act uponing the stock return would be stock monetary values in planetary economic system, the exchange rate and the involvement rate, for case, capital influxs are non determined by domestic involvement rate merely but besides by alterations in the involvement rate by major economic systems in the universe. Therefore, the individual economic system grounds revives the more sensible hypothesis that exchange rate volatility is basically negatively correlated with involvement rate.

An empirical survey [ 18 ] by utilizing being of threshold effects in the relationship between rising prices rate and growing rate of GDP in the context of Malaya shows that below the threshold degree, there is a statistically important positive relationship between rising prices rate and growing. New grounds from a Dynamic Panel Threshold Analysis by [ 19 ] , using the dynamic panel threshold theoretical account to the analysis of thresholds in the inflation-growth nexus.They provided new grounds on the non-linear relationship between rising prices and long-run economic growing. However, the correlativity remains undistinguished.

By and large, the rising prices rate is used to mensurate the monetary value stableness in the economic system. Conceptually, [ 20 ] through his study shows the rising prices can be divided into two sides, viz. : demand side rising prices ( demand pull rising prices ) and supply side rising prices ( cost push rising prices ) . In a survey by [ 21 ] , it is shown that money growing rate and rising prices rate have a positive relationship. The alterations in exchange rates do non impact the rising prices rate in ASEAN, except Thailand [ 22 ] . On the other manus, [ 23 ] through empirical observation found the relationships between rising prices and the existent exchange rates in most states of Asia and Latin America. In the instance of Malaysia, [ 24 ] found the exchange rate is an of import determiner of rising prices in the state. However, [ 25 ] , who examine rising prices in six Asiatic states found that the growing of money stock is non the primary beginning of rising prices in these states. The impact of exchange rate besides related to the imports and exports for the state. Referred to the diary written by [ 26 ] the survey examines the important impact of exchange rate daze on monetary values of Malayan imports and exports. It is found that rising prices in a figure of industrial and developing states has remained surprisingly stable in the face of broad swings in exchange rate. A research by [ 27 ] found that the relationship between rising prices rates derived functions and exchange rates is non perfect even in the long tally, but it supports the usage of rising prices derived functions to calculate long-term motions in exchange rates.

## Methodology

Theoretical Model: The identified theoretical account is three variable theoretical accounts which hypothesize that exchange rate as a map of involvement rate and rising prices rate.

EXCt = F ( IRt, INFt )

( Equation 1 )

Where, EXC represents monthly exchange rate in Malaysia ( RM/USD ) , IR represents monthly involvement rate, INF represents rising prices rate where t-sign represents clip tendency. The sample consists of 132 monthly informations from 1999 to 2009 and was obtained from Bank Negara Malaysia ( BNM ) Statistical Report web site. The information on exchange rate is valued in rate while informations on involvement rate and rising prices rate are valued in per centum. All informations so being converted into log-log equation for clip series processing. Therefore, the coeeficient can be interpreted as an snap.

Stationarity Test: Stationarity of a series is an of import phenomenon because it can act upon its behavior. If ten and y series are non-stationary random procedures ( integrated ) , so patterning the ten and Y relationship as a simple OLS relationship as in equation 4 will merely bring forth a specious arrested development.

( Equation 2 )

Time series stationarity is the statistical features of a series such as its mean and discrepancy over clip. If both are changeless over clip, so the series is said to be a stationary procedure ( i.e. is non a random walk/has no unit root ) , otherwise, the series is described as being a non-stationary procedure ( i.e. a random walk/has unit root ) . Differencing a series utilizing differencing operations produces other sets of observations such as the first-differenced values, the second-differenced values and so on.

( Equation 3 )

If a series is stationary without any differencing it is designated as I ( 0 ) , or integrated of order 0. On the other manus, a series that has stationary first differences is designated I ( 1 ) , or integrated of order one ( 1 ) . Augmented Dickey-Fuller trial suggested by [ 28 ] and the Phillips-Perron trial recommended by [ 29 ] have been used to prove the stationarity of the variables.

Johansen and Juselius Cointegration Test: [ 30 ] processs uses two trials to find the figure of cointegration vectors: the Maximum Eigenvalue trial and the Trace trial. The Maximum Eigenvalue statistic trials the void hypothesis of R cointegrating dealingss against the option of r+1 cointegrating dealingss for R = 0, 1, 2aˆ¦n-1. This trial statistics are computed as:

( Equation 4 )

Where I» is the Maximum Eigenvalue and T is the sample size. Trace statistics investigate the void hypothesis of R cointegrating dealingss against the option of n cointegrating dealingss, where N is the figure of variables in the system for R = 0, 1, 2aˆ¦n-1. Its equation is computed harmonizing to the undermentioned expression:

( Equation 5 )

In some instances Trace and Maximum Eigenvalue statistics may give different consequences and [ 31 ] indicates that in this instance the consequences of trace trial should be preferred.

Vector Error Correction Model ( VECM )

If cointegration has been detected between series we know that there exists a long-run equilibrium relationship between them so we apply VECM in order to measure the short tally belongingss of the cointegrated series. In instance of no cointegration VECM is no longer required and we straight precede to Granger causality trials to set up causal links between variables. The arrested development equation signifier for VECM is as follows:

( Equation 6 )

In VECM the cointegration rank shows the figure of cointegrating vectors. For case a rank of two indicates that two linearly independent combinations of the non-stationary variables will be stationary. A negative and important coefficient of the ECM ( i.e. et-1 in the above equations ) indicates that any short-run fluctuations between the independent variables and the dependent variable will give rise to a stable long tally relationship between the variables

Granger-Causality

A general specification of the Granger causality trial in a bivariate ( X, Y ) context can be expressed as:

Yt = I±0 + I±1Yt-1 + aˆ¦aˆ¦+ I±iYt-i + I?1Xt-1 +aˆ¦aˆ¦..

I?iXt-i + I?

( Equation 7 )

Crosstalk = I±0 + I±1Xt-1 + aˆ¦aˆ¦+ I±iXt-i + I?1Yt-1 +aˆ¦aˆ¦..

I?iYt-i + I?

( Equation 8 )

In the theoretical account, the inferiors denote clip periods and I? is a white noise mistake. The changeless parametric quantity I±0 represents the changeless growing rate of X in the equation 11 and Y in the equation 12, and therefore the tendency in these variables can be interpreted as general motions of cointegration between X and Y that follows the unit root procedure. We can obtain two trials from this analysis: the first examines the void hypothesis that the Ten does non Granger-cause Y, and the 2nd trial examines the void hypothesis that the Y does non Granger-cause X. If we fail to reject the former nothing hypothesis and reject the latter, so we conclude that X alterations are Granger-caused by a alteration in Y [ 32 ] . Unidirectional causality will happen between two variables if either void hypothesis of equation ( 7 ) or ( 8 ) is rejected. Bidirectional causality exists if both void hypotheses are rejected and no causality exists if neither void hypothesis of equation ( 7 ) nor ( 8 ) is rejected [ 33 ] .

## RESULTS AND DISCUSSION

Stationarity Test

It is clear from Table 1 that the void hypothesis of no unit roots for all the clip series are rejected at their first differences since the ADF and PP test statistic values are less than the critical values at 1 % degrees of significances. Therefore, the variables are stationary and integrated of same order, i.e. , I ( 1 ) . However, the application of the ADF and PP trials for IR revealed that this variable is stationary in both its degrees and its first differences. In this instance, IR does non necessitate no differencing, merely the log transmutation. In short, all the variables became stationary and do non incorporate unit root in first difference.

Table 1: ADF and PP unit root trials

Seriess

ADF

PP

Degree

First Difference

Degree

EXC

-0.840

-9.710***

-1.078

Iridium

-3.805***

-7.043***

-3.785***

INF

-2.823

-6.012***

-3.106

Notes: *** denote important at 1 % utilizing t-stat attack

Determination of slowdowns

As proposed by [ 34 ] , he used lowest SBIC value as primary concern. Table 2 studies lag-order choice statistics. The consequence shows lags order at two. So, we precede farther trials with slowdowns ( 2 ) .

Table 2: Lag-order choice standard

Note: * indicates the optimum slowdown choice.

Cointegration Trial

Cointegration rank ( rank of matrix I ) is estimated utilizing Johansen methodological analysis. Johansen ‘s attack derives two likeliness calculators for the CI rank: a hint trial and a maximal Eigen value trial. The CI rank ( R ) can be officially tested with the hint and the maximal Eigen value statistics. The consequences are presented in Table 3. The hint statistic either rejects the void hypothesis of no co-integration among the variables or does non reject the void hypothesis that there is one co-integration relation between the variables. Start by proving H0: R = 0. If it rejects, repetition for H0: R = 1. When a trial is non rejected, halt proving at that place, and that value of R is the commonly-used estimation of the figure of cointegrating dealingss. In this trial, H0: R = 1 is non rejected at the 5 % degree ( 13.66 & lt ; 15.41 ) . In other words, this hint trial consequence does non reject the void hypothesis that these three variables are non cointegrated. The concluding figure of cointegrated vectors with two slowdowns is equal to one, i.e. rank ( Iˆ ) =1. Since, the rank is equal to 1 which is more than zero and less than the figure of variables ; the series are cointegrating among the variables. However, we will continue to gauge the VECM theoretical account.

Table 3: Consequences of co-integration trials

Note: Trace is likelihood ratio statistic for the figure of co-integration vectors.

* indicates the optimum slowdown choice.

Vector Error Correction Model

The presence of cointegration between variables suggests a long term relationship among the variables under consideration. Then, the VEC theoretical account can be applied. The long tally relationship between exchange rate, involvement rate and rising prices for one cointegrating vector for the Malaysia in the period 1999-2009 is displayed below ( standard mistakes are displayed in parenthesis ) .

EXC = 0.7983 IR – 0.1075 INF – 2.1382

( 0.0888 ) ( 0.0349 )

( Equation 9 )

Table 4: Vector Error Correction Model

In Table 4, all the coefficients were important at 1 % degree of significance. Harmonizing to[ 2 ]when the variables are in logarithms and one cointegrating vector is estimated, the coefficients can be interpreted as long tally snaps. The grasps of the exchange rate are related to increasing involvement rate, therefore, the estimated theoretical account was able to bring forth a consistent consequence. Thus, 1 % grasp of the involvement rate is likely to increase exchange rate by 0.7983 % , and this estimation was important. Normally believed ; in the long tally, rising prices found to be damaging to interchange rate alterations. For 1 % addition in rising prices, exchange rate is reduced by.1075 % , this coefficient was important at 1 % degree of significance. By and large, the consequence of the EXC equation as shown above is found to be satisfactory in footings of right marks. It is seen that involvement rate has right positive mark with the exchange rate relationship.

Based on [ 6 ] , the higher involvement derived function would pull capital influxs and consequence in exchange rate grasp. Higher involvement rates offer loaners in an economic system a higher return relative to other states. Therefore, higher involvement rates attract foreign capital and do the exchange rate to lift. The impact of higher involvement rates is mitigated, nevertheless, if rising prices in the state is much higher than in others, or if extra factors serve to drive the currency down. Inflation besides gives right mark between the relationships with exchange rate, which is negative relationship. As a general regulation, a state with a systematically lower rising prices rate exhibits a lifting currency value, as its buying power additions relative to other currencies. During the last half of theA 20th century, the states with low rising prices included Japan, Germany and Switzerland, while the U.S. and Canada achieved low rising prices merely subsequently. States with higher rising prices typically see depreciation in their currency in relation to the currencies of theirA trading spouses [ 36 ] .

Granger Causality Trials

Recall that although co-integration between two variables does non stipulate the way of a causal relation, if any, between the variables. Economic theory warrants that there is ever Granger Causality in at least one way [ 37 ] . Researchers verify the way of Granger Causality between EXC, IR and INF. Appraisal consequences for granger causality between the really variables are presented in Table 5. The survey by [ 32 ] used chi-square statistics and chance to mensurate causality between the variables. Chi-Square statistics and chance values constructed under the void hypothesis of non causality show that there is a causal relationship between those variables.

Table 5: Granger Causality Test

Null Hypothesis

I‡2

Probability

Decision

EXC does non Granger-cause IR

0.09

0.7646

Do non reject

IR does non Granger-cause EXC

1.24

0.2647

Do non reject

EXC does non Granger-cause INF

0.00

0.9856

Do non reject

INF does non Granger-cause EXC

6.71

0.0096***

Cull

IR does non Granger-cause INF

8.19

0.0042***

Cull

INF does non Granger-cause IR

1.19

0.2748

Do non reject

Notes: *** denote important at 1 %

Table 6 provides the consequences of pair wise analyses. Significant chance values denote rejection of the void hypothesis. This survey reject the void hypothesis if the chance value is more than 1 % otherwise do non reject the void hypothesis if the chance value is less than 1 % . It is found that INF “ Granger cause ” EXC unidirectional at the 1 % significance degree. It means that EXC follow its mature opposite numbers in the short-run that there exists a lead-lag relationship between them. The causality trial besides tested between two independent variables. There is unidirectional causality running from IR to INF, connoting that past values of involvement rate have a prognostic ability in finding the present values of rising prices. This consequences besides supported by many investors and economic experts in Turkey. They believe that any alterations in nominal involvement rate will do a alteration in rising prices. Research by [ 32 ] besides shows involvement rate Granger cause rising prices. On the other manus, there is no causality in either way between these series and between IR and EXC. This determination can be explained by the alterations in the short term involvement rate and it can non reflect on the alterations of exchange rate motion and frailty versa.

Impulse Response Function ( IRF )

The survey uses impulse response map as an extra cheque of the Cointegration trial ‘s findings. Followed by [ 37 ] , Cholesktype of contemporary identifying limitations are employed to pull a meaningful reading. The recursive construction assumes that variables looking foremost contemporaneously act upon the latter variables but non frailty versa. It is of import to name the most exogenic looking variables earlier than the most endogenous looking variables. Impulse response maps are shown in Figure 1.

Figure 1: Impulse-Response Functions

In the initial response of exchange rate to a unit daze in rising prices is negative and dies out. In the response of rising prices to a daze in exchange rate is impersonal, i.e. , irresponsive. It is proven that rising prices Granger-cause exchange rate. The initial response of rising prices to a unit daze in involvement rate is negative for the short period and can be consider as important after that. A panel shows that the response of involvement rate to an exchange rate daze is negative and dies out. Finally, the initial response of involvement rate to a daze in rising prices is positive and besides can be considered as important. Overall, from Figure 1 we see that the short-term equilibrium accommodation procedure is rather fast.

## Decision

It can be concluded that increasing the involvement rate can be efficient in keeping exchange rate volatility. Besides, information contained in the INF besides refering the future way of the EXC. This implies that there is information contained in the IR refering the future way of the INF. For hereafters surveies, it is recommended that