Download An Overview of Research Process

AN OVERVIEW OF RESEARCH
PROCESS
FINA262
Financial Data Analysis
1. WHAT IS RESEARCH METHODOLOGY?
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The process of collecting information and data for
the purpose of decision making and policy
implications.
“Without data you’re just another person with an
opinion” W. Edwards Deming
1. WHAT IS RESEARCH METHODOLOGY?
(CONTINUED)
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The scientific method in social science developed
from the key methodological approaches of
positivism and empiricism.
Fundamental to the positivist approach is the
idea that the study of the social world can use the
tools of science in order to create understandings
which are verifiable.
Empiricism gives primacy to the observable
world and relies on observable data from which
to deduce patterns which may form the basis of
research questions, hypotheses and problems.
2. STEPS IN RESEARCH METHODOLOGY
STEP 1: DEFINE THE PROBLEM OR OPPORTUNITY
STEP 2: REVIEW THE LITERATURE
STEP 3: FORMULATE YOUR HYPOTHESIS
STEP 4: CHOOSE A RESEARCH METHOD
STEP 5: COLLECT YOUR DATA
STEP 6: ANALYZE YOUR DATA
STEP 7: RESEARCH AND POLICY IMPLICATIONS
STEP 1: DEFINE THE PROBLEM OR
OPPORTUNITY
The initial step in research methodology is to define
the problem or opportunity.
 If the definition is not carefully tought through and
precisely formulated, resources will be wasted trying
to solve the wrong problem.
 To define a problem or opportunity effectively,
researchers must consider several concerns;
1. The reasons for pursuing information
2. The decision maker’s objectives
3. What is already known about the issue
4. The risks associated with the problem
5. Resources available for the research activity
6. How the information will help the decision maker
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STEP 2: REVIEW THE LITERATURE
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A literature search is “a systematic and through
search of all types of published literature in order
to identify as many items as possible that are
relevant to a particular topic” (Gash, 2000).
Reviewing literature provides context of the
study and clarifies the relationship between the
proposed research and previous research.
Literature review shows how the proposed study
is unique from previous research.
STEP 3: FORMULATE YOUR HYPOTHESIS
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After choosing a research question, the next step is to
formulate a research hypothesis.
A research hypothesis is a tentative answer to the
research question. That is, after reading previous
research studies, researchers predict in advance what
they think the outcome of a research study will be.
The concepts addressed by the hypothesis must be
clearly defined and measurable.
Research hypotheses must refer to concepts that can
be studied scientifically. To say that a company’s
aggressive strategies are caused by the devil isn't a
testable hypothesis because this hypothesis refers to a
concept (the devil) that isn't in the province of science.
Science deals with what can be observed; this is the
basis for empirical observation.
STEP 4: CHOOSE A RESEARCH METHOD
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Let the literature be your guide!
A through literature review is the best starting
point for choosing your methods because
evaluating previous researchers' efforts can
suggest a path to answer your own research
question.
"You might find out that people have used certain
designs and that they've worked well or that
there have been problems."
STEP 5: COLLECT YOUR DATA
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Researcher should ask “Where will I get the
information?”
The data may already exist as secondary datadata that has already been collected for a purpose
other than the current study or it may have to be
primary data-original data gatehered to satisfy
the purpose of the current study.
Secondary data is used whenever possible,
because it tends to be much less expensive than
primary data, and such data is also available in a
timely manner.
STEP 6: ANALYZE YOUR DATA
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Once data collection is complete, the next step is to
analyze the information.
Analysis makes sense of the data so that decision
makers can draw conclusions about the variables.
No matter which analytical procedure is used, the
results must provide, in a timely manner, the
information that the decision maker seeks.
It is no longer necessary to analyze data using
manual methods. High-speed computers use
statistical software to perform all sorts of calculations
like E-views and SPSS.
STEP 7: RESEARCH AND POLICY
IMPLICATIONS
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After the data has been collected and properly
analyzed, research and policy implications should
be reported.
All results should be explained in details.
According to the results of the study, researcher
should suggest policy implications to decision
makers.
CRITERIA OF GOOD RESEARCH
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1. The purpose of the research should be clearly
defined and common concepts be used.
2. The research procedure used should be
described in sufficient detail to permit another
researcher to repeat the research for further
advancement, keeping the continuity of what has
already been attained.
3. The procedural design of the research should
be carefully planned to yield results that are
as objective as possible.
4. The researcher should report with complete
frankness, flaws in procedural design and
estimate their effects upon the findings.
CRITERIA OF GOOD RESEARCH (CONTINUED)
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5. The analysis of data should be sufficiently
adequate to reveal its significance and the
methods of analysis used should be appropriate.
The validity and reliability of the data
should be checked carefully.
6. Conclusions should be confined to those
justified by the data of the research and limited
to those for which the data provide an adequate
basis.
7. Greater confidence in research is warranted if
the researcher is experienced, has a good
reputation in research and is a person of
integrity.
TYPES OF RESEARCH
Descriptive vs. Analytical:
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Descriptive research includes surveys and fact-finding
enquiries of different kinds.
In social science and business research we quite often use the
term Ex post facto research for descriptive research studies.
The main characteristic of this method is that the researcher
has no control over the variables; he can only report what has
happened or what is happening.
Most ex post facto research projects are used for descriptive
studies in which the researcher seeks to measure such items
as, for example, frequency of shopping, preferences of people,
or similar data.
Descriptive vs. Analytical:
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Ex post facto studies also include attempts by
researchers to discover causes even when they cannot
control the variables.
The methods of research utilized in descriptive
research are survey methods of all kinds, including
comparative and correlational methods.
In analytical research, on the other hand, the
researcher has to use facts or information already
available, and analyze these to make a critical
evaluation of the material.
Applied vs. Fundamental:
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Research can either be applied (or action) research or
fundamental (to basic or pure) research.
Applied research aims at finding a solution for an
immediate problem facing a society or an
industrial/business organisation, whereas fundamental
research is mainly concerned with generalisations and with
the formulation of a theory.
“Gathering knowledge for knowledge’s sake is termed ‘pure’
or ‘basic’ research.” Research concerning some natural
phenomenon or relating to pure mathematics are examples
of fundamental research.
Research to identify social, economic or political trends that
may affect a particular institution or the marketing
research or evaluation research are examples of applied
research.
Applied vs. Fundamental:
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Thus, the central aim of applied research is to
discover a solution for some pressing practical
problem, whereas basic research is directed towards
finding information that has a broad base of
applications and thus, adds to the already existing
organized body of scientific knowledge.
Quantitative vs. Qualitative:
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Quantitative research is based on the
measurement of quantity or amount. It is
applicable to phenomena that can be expressed in
terms of quantity.
Qualitative research, on the other hand, is
concerned with qualitative phenomenon,
i.e.,phenomena relating to or involving quality or
kind. For instance, when we are interested in
investigating the reasons for human behaviour
(i.e., why people think or do certain things), we
quite often talk of ‘Motivation Research’, an
important type of qualitative research.
Conceptual vs. Empirical:
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Conceptual research is that related to some abstract
idea(s) or theory. It is generally used by philosophers
and thinkers to develop new concepts or to reinterpret
existing ones.
On the other hand, empirical research relies on
experience or observation alone, often without due
regard for system and theory. It is data-based
research, coming up with conclusions which are
capable of being verified by observation or
experiment.
In empirical research, the researcher must first
provide himself with a working hypothesis or guess as
to the probable results. He then works to get enough
facts (data) to prove or disprove his hypothesis.
Conceptual vs. Empirical:
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Empirical research is appropriate when proof is
sought that certain variables affect other
variables in some way.
Evidence gathered through experiments or
empirical studies is today considered to be the
most powerful support possible for a given
hypothesis.
TYPES OF DATA
Time Series Data
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Macroeconomic data measures phenomena such as real
gross domestic product(denoted GDP), interest rates, the
money supply, etc. This data is collected at specific points
in time (e.g. yearly).
Financial data, on the other hand, measures phenomena
such as changes in the price of stocks. This type of data is
collected more frequently than the above, for instance,
daily or even hourly.
In all of these examples, the data are ordered by time and
are referred to as time series data.
Time series data can be observed at many frequencies.
Commonly used frequencies are: annual (i.e. a variable is
observed every year), quarterly (i.e. four times a year),
monthly, weekly or daily.
Years
GDP (m.$)
DC /GDP
2007
225,2
0.75
2008
226,4
0.66
2009
227,8
0.45
2010
225,4
0.60
2011
229,5
0.70
2012
240,0
0.31
2013
234,1
0.40
2014
285,9
0.62
2015
262,4
0.94
Cross-sectional data
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Data that is characterized by individual units are
called cross-sectional data.
These units might refer to people, companies or
countries. A common example is data pertaining to
many different people within a group, such as the
wage of all people in a certain company or industry.
With such cross-sectional data, the ordering of the
data typically does not matter (unlike time
series data).
For example, a labor economist might wish to survey
N = 1,000 workers in the steel industry, asking each
individual questions such as how much they make or
whether they belong to a union.
Country
GDP (m.$)
(Year: 2015)
DC /GDP
(Year: 2015)
Nigeria
315,2
0.65
Cyprus
306,4
0.86
Turkey
417,8
0.75
Azerbaijan
515,4
0.60
Tajikistan
219,5
0.90
Kazakhstan
220,0
0.81
Jordan
324,1
0.66
Iran
650,9
0.68
Chad
432,4
0.78
Panel Data
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Some data sets will have both a time series and a
cross-sectional component. This data is referred to as
panel data.
For example, GDP for many countries from1950 to
the present is available. A panel data set on Y= GDP
for 12 European countries would contain the GDP
value for each country in 1950 (N = 12 observations),
followed by the GDP for each country in 1951
(another N = 12 observations), and so on. Over a
period of T years, there would be T times N
observations on Y.
Country
Years
GDP (m.$)
DC /GDP
Nigeria
2002
315,2
0.65
2003
406,4
0.66
2004
517,8
0.75
2002
115,4
0.70
2003
219,5
0.75
2004
320,0
0.79
2002
424,1
0.80
2003
550,9
0.82
2004
632,4
0.84
Cyprus
Turkey
THE DISTINCTION BETWEEN
QUANTITATIVE AND QUALITATIVE DATA
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The microeconomist’s data on sales will have a
number corresponding to each firm surveyed (e.g. last
month’s sales in the first company surveyed were
£20,000). This is referred to as quantitative data.
The labor economist, when asking whether or not
each surveyed employee belongs to a union, receives
either a Yes or a No answer. These answers are
referred to as qualitative data. Such data arise often
in economics when choices are involved(e.g. the choice
to buy or not buy a product, to take public transport
or a private car, to join or not to join a club).