CHAPTER THREE: RESEARCH
METHODOLOGY
The research intends to follow quantitative patterns. For it
to be systematic and intensive process of carrying out data collection, it will
involve some sort of procedures in collecting and analyzing data.
The methodology will follow procedures of quantitative
research because it is based on measurements of quantitative indicators. It is
applicable to the phenomena that can be expressed in terms of quantity that is
easily empirically measured.
3.1 DATA
COLLECTION
3.1.1 Techniques
A technique is defined as all resources and processes that
enable researchers to gather data and information on the research topic (WELMAN
J. C and KRUGER S.J., 2001:34)
Thus, we preferred the documentary techniques which is a
systematic search of all that is written related with the research area such as
books, pamphlets, monographs, unpublished documents, reports, budgets, public
records etc. the documentary technical allows us to choice among the books
available what are useful for our research and help to use the best
resources.
3.1.2 Types and sources of
data
The success of any econometric analysis ultimately depends on
the availability of the appropriate data. It is therefore essential that we
spend some time discussing the nature, sources, and limitations of the data
that one may encounter in empirical analysis.
Time Series Data will be used in our research. A time series
is a set of observations on the values that a variable takes at different
times. Such data may be collected at regular time intervals, such as daily
(example stock prices, weather reports), weekly (money supply figures), monthly
[the unemployment rate, the Consumer Price Index (CPI)], quarterly (GDP),
annually (government budgets), every 5 years (the census of manufactures), or
decennially (the census of population).
Time series data are used heavily in econometric studies but
they present special problems for econometricians; most empirical work based on
time series data assumes that the underlying time series is stationary.
Although it is too early to introduce the precise technical meaning of
stationarity at this juncture, loosely speaking a time series is stationary if
its mean and variance do not vary systematically over time GUJARATI
(2006:26).
Different visits to libraries, internet exploration, and use
of documents provided by National Bank of Rwanda, National Institute of
Statistic of Rwanda, Ministry of finance has been considered useful.
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