3.4. Data presentation,
analysis and interpretation
The data obtained were analyzed using econometrics
methodology. Money stock constitutes the dependent variable. The study employs
an econometric technique of cointegration methodology.
To formulate a monetary reaction function for National Bank of
Rwanda, the Taylor rule equation was adopted to the context of monetary policy
in Rwanda.
The original Taylor rule can be expressed as following:
FFR=f (YG, IG) (1)
Where: FFR= the federal funds rate, YG= the output gap, IG= the
inflation gap.
Because of data availability problems for the monetary base
series of Rwanda, the monetary stock aggregate (Mt) will be used as the
instrument policy. Indeed, the monetary stock aggregate (M) plays an important
role in Rwanda monetary policy since the National Bank of Rwanda assumed its
responsibility to regulate liquidity in the economy and the data of the
monetary base are frequently referred to Mt.
In respect of goal variables, inflation and output will be
used. The former variable has emerged from many economists as the real goal of
monetary policy in order to maintain price stability and the latter is
considered as a historically objective of monetary policy in various
countries.
In the context of Rwanda, the strategy used by the Central
Bank is to ensure that liquidity expansion is consistent with target inflation
and GDP growth levels. Thus, the modified version of Taylor's rule to be
estimated can be written as:
Mt= B_{0}+ B_{1 }(IG_{t}) + B_{2
}(YG_{t}) + _{t } (2)
However, recently, with number of empirical studies related to
the Taylor rule, economists argue that the exchange rate would also be an
essential state variable that has to be included in the model in the case of a
small and open economy. On this basis, the equation (2) is extended as
follow:
Mt= B_{0}+ B_{1 }(IG_{t}) +
B_{2}(YG_{t}) + B_{3}DEX_{t} + _{t}
(3)
EX_{t} = the change in exchange rate in terms of the
Rwandan Francs per US Dollars,
B_{0} is constant term and B_{1, }B_{2,
}B_{3 }are coefficients respectively to be estimated
empirically,
_{t }= the error term that presents all other variables
which can have effects on Money stock in Rwanda.
The equation (3) can be seen as a function in which the money
stock aggregate reacts to the Inflation gap, Output gap and the change in
Exchange rate.
The version of the equation (3) to be empirically estimated can
take a dynamic form since there is the lag response of Monetary Authority. On
this basis, the equation (3) is expressed as follows:
LnMt= B_{0}+ lnM_{t1} + lnIG_{t} +
lnIG_{t1} +lnYG_{t} + lnYG_{t1} +lnDEX_{t}
+lnDEX_{t1} + _{t} (4) and finally the equation (4) become:
M_{t}= B_{0}+ B_{1}M_{t1} +
B_{2}IG_{t} + B_{3}IG_{t1} +B
_{4}YG_{t} + B_{5}YG_{t1} +B
_{6}DEX_{t} +B_{7}DEX_{t1} + _{t}
(5)
(Mukunzi, 2004: 34)
The Taylor Rule has been considered as a representation of
Central Bank behavior in various countries. It provides information about the
responsiveness of the monetary policy instrument to the monetary variables.
Therefore, estimating the policy behavior of the Rwandan Central Bank and
determining the target the Central Bank followed, is essential to the different
policy implications, especially to the implementation of an accurate and
successful monetary policy.
According to Mishkin (1997) six basic goals are continually
mentioned by Central Banks when they discuss the objective of monetary
policy:
 High employment level,  Economic growth,  Price stability,
 Interest rate stability,  Stability of financial markets,  Stability in
foreign exchange rate markets.
The primary objective is to establish a model that explains
well the relationship between the money stock and some macroeconomic variables
in Rwanda. In addition, the qualitative and quantitative impacts of each of
these variables on money stock are determined. A lot of other information is
also obtained. For instance, it will be possible to know what the different
partial elasticity that pertained by each variable is.
The augmented DuckeyFuller Unit Root Test will be used for
the purpose of data analysis throughout the research. According to Gujarati
(1999: 455467), it is this test which detects the stationary of a variable.
Many other tests will also be conducted.
According to Gujarati (1999: 377398), the DurbinWatson test,
the Runs test or the examination of the residuals are techniques that will be
used in relation the problem of serial correlation.
