Economics Research Methodolgy
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Transcript of Economics Research Methodolgy
7/31/2019 Economics Research Methodolgy
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RESEARCH METHODOLOGY
CARRYING OUT AN EMPIRICAL PROJECT;
Andrew Maredza, MSc. MCom.
Office R25 Law Building
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Introduction:
The Nature And Purpose Of Econometrics
• Econometrics is all about endeavouring to find out
“what we don't know” by “what we do”.
• “What we do know” of economics are data.
• Econometrics shows us how to use data in a sensible
and systematic manner to shed light on economic
questions.
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Types of Data and Notation
• There are 3 types of data which econometricians
might use for analysis:
1. Time series data: Subscript t is used
2. Cross-sectional data: Subscript i is used
3. Panel data: Subscript it is used
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Time Series Data
• It is data collected over a period of time.
• Subscript t is used.
• Examples of time series data
− GNP or unemployment
− Government budget deficit
− Money supply
− Inflation
• Frequency
− monthly, quarterly, annually
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Cross-sectional Data
• It is data collected at one period in time.
• Data are data that are characterised by individual units.
• These units might refer to companies, people, or
countries., e
• Examples
− Return earned on the stock of many different companies.
− Capital structure of several private firms.
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Panel Data
• Examples of Problems that Could be Tackled Using a Cross-
Sectional Regression
- The relationship between company size and the return to
investing in its shares.
- Panel Data has the dimensions of both time series and cross-
sections, e.g. the daily prices of a number of blue chip stocks
over two years.
• Primary and Secondary Data ??
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Research Methodology
• The choice of research methodology is a difficult step in
the research process.
• Many researchers struggle with how to choose an
appropriate methodology for the research question they
are attempting to investigate.
• The methodology selected should be the one that will be
the most effective to collect the data needed to answer the
research question or to test the hypothesis.
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Why Research Methodology
• The methodology is the section of the study in which you
describe the goals of the study and the methods by which
you hope to achieve those goals.
• The reliability of findings and validity of the study
depends upon how robust and rigorous the applied
methodology is and hence, research methodology takes aprominent place in a research project.
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Choice of the Methodology
• Research studies may be either quantitative or
qualitative.
• Generally, one could search the literature for ideas on
how others have tackled similar problems.
• Should be guided by economic theory
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Research Methodology
in Economics
Consider the following steps
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1. Introduction
• The methodology is the section of the study in which
you describe the main objective of the study and the
methods by which you hope to achieve those goals.
• Restate the goal of your study briefly.
• Summary of the structure or outline of the
methodology chapter.
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2. Model Specification
•Model specification is the most difficult stage yet the mostimportant because of potential specification errors.
• Model specification should be guided by theory
• Specification of the relationship between the independent
variable and the dependent variable in the form Y= f ( X )
• Choice of the functional form of the model and in this case
we determine whether the relationship between the two
variables is linear or quadratic.
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Functional Form
• When specifying your model you must make functional
form decisions
• You do not need an extensive discussion of the functional
form but it is useful to mention whether you will be
estimating elasticities or a semi-elasticity
– What variables should be included in the model?
– Should some variables appear in log form? (often yes)
– Should some variables be included in levels and
squares, to possibly capture a diminishing effect?
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Econometric Analysis:
Time series
• Time series applications require extra care
• Should the equation be estimated in levels? If levels
are used, are time trends needed?• Is differencing the data more appropriate?
• If the data are monthly or quarterly does seasonality
have to be accounted for?
• If allowing for dynamics, how many lags should be
included?
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Data Mining
• Virtually all applied researchers search over various
models before finding the “best” model.
• Minimize this data mining by “ not searching over
numerous models or estimation methods until a
significant result is found and then reporting only
that result ”; report several plausible results
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2. Model specification (Contd…)
• One should avoid the game of “data mining,”
• That is why it is essential that there be some economic
reasoning underlying the chosen model and that any
modifications in the model should have some economic
justification.
• A purely ad hoc model may be difficult to justify on
theoretical or a priori grounds.
• In short, theory should be the basis of estimation.
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3. Data Sources and Definition
of Variables
• What type of data is to be used?
• What is the frequency of the data?
• Is it from a reliable source? Is the data of “good
quality”?
• Is the size of the sample sufficiently large?
• A section to discuss each of the specified variable is
necessary.
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Data: Sources of Data
• Some government agencies and international agencies
provide data on their websites e.g.
– http://www.dti.gov.za/;
– http://www.reservebank.co.za/;
– http://www.statssa.gov.za/
– http://unstats.un.org/unsd/databases.htm
– http://www.worldbank.org/
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Data: Sources of Data
• You should always have a section that carefully describes
the data used in the empirical analysis
– It is also informative to present a table of summary
statistics, such as minimum and maximum values,means, and standard deviations for each variable
• Enough information should be presented so that the
reader could in principle obtain the data and redo your
analysis.
• If you use your own survey to collect the data, a copy of
the questionnaire should be presented in the appendix.
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Definition of Variables
• A section to discuss each of the specified variable is
necessary.
• LOPEN: This is a measure of the degree of openness.
It is defined as the logarithm of the ratio of the sum of
imports and exports of goods and services to GDP. An
increase in openness through trade liberalisation –
tariff reduction or removal of quotas – increase importsand worsens the current account balance of payments,
thus causing the real exchange rate to depreciate. A
negative sign is, therefore, expected
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Data Inspection & Cleaning
• It is extremely important to become familiar with any data
set you will use in an empirical analysis.
• Summary statistics.
– Are there outliers or incorrect entries? – It is always useful to find minimums, maximums, means and
standard deviations of all or at least the most important variables
in the analysis
− What do you conclude if you find that the minimum value of
education in your sample is “-250 000 000”?
• If it is time series one could test for the problem of unit
root in the data set.
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4. Estimation Of The Model:
• After specifying the model(s), it is appropriate to
discuss estimation methods
– OLS, WLS, 2SLS, MLE, etc
• You should explain why the method you are choosing
is appropriate.
• If you use more advanced estimation methods such as
the 2SLS techniques, you must provide a careful
discussion.
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4. Estimation Of The Model:
• This involves obtaining the numerical estimates of the
coefficients and this stage involves the following steps:
• Choosing appropriate econometric technique is critical
• We choose from single equation technique or simultaneous
equation technique
• This will depend on the nature of relationship between
variable.
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Choosing Appropriate Econometric
Technique
• Choice between single equation techniques or simultaneous equation techniques.
• This depends on the nature of relationship between
variables.
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Single Equation Techniques:
CLRM (OLS) Technique
• Given a model of the form:
• when we specify the equation as shown we estimate our
equation using the classical linear regression model.
• The traditional and the workhorse of all econometric
techniques is the Classical Linear Regression Model.
• According to Gauss Markov, given the assumptions
of the classical linear regression model are satisfied,
OLS estimators are BLUE.
iiiu X Y
21
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Simultaneous Equation Techniques
• It is common in economics to have models where
some variables are not only explanatory variables for
a given dependent variable, but they are also
explained by the variables that they are used to
determine.
• In these cases, we have models of simultaneous
equations, in which it is necessary to clearly identify
which are the endogenous and which are the
exogenous or predetermined variables.
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Simultaneous Equation Techniques
• Sims (198 )argues:
“If there is simultaneity among a number of variables, then
all these variables should be treated in the same way.”
• This argument implies there should be no distinction
between endogenous and exogenous variables, all variables
are treated as endogenous variables.
• This each equation has the same set of regressors which
leads to the development of:
• VAR MODELS
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5. Diagnostic Checks
− Have the techniques been validly applied? Have
diagnostic tests for violations of been conducted for any
assumptions made in the estimation of the model?
− It involves checking whether assumptions of the
econometric models are observed, if the assumptions are
not observed we must re specify the model.
− We also check for unexpected signs and sizes of
parameters and this could be as a result of deficiencies in
the data or poor model choice.
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5. Diagnostic Checks (Contd...)
• Diagnostic checks test the stochastic properties of
the model, such as residual autocorrelation,
heteroskedasticity and normality, among others.
1. Autocorrelation LM Test
2. White heteroskedasticity test
3. Residual Normality Test
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