7SSMM603
R ESEAR CH MET H ODS
Introduction to Research Methods
Dr. Neophytos Lambertides
King’s College London
About the
Module
Objectives, logistics and
assessments
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Aims and Objectives of the Module
• This module aims to:
• foster your critical understanding of the various research methodologies and
methods in finance, accounting and/or management research
• familiarise yourselves on research design, implementation, and relevant
statistical tools
• provide you with conceptual ideas and operational tools to undertake individual
research for your MSc dissertation
• draw your attention to research ethics issues related to any research undertaken
involving human participation
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Learning Outcomes
• After completing this module, you should be able to:
• identify and explain the principal themes and issues in social sciences
research related to research in finance, accounting, accountability and
financial management
• formulate research questions and design a research project
• apply appropriate research methods and evaluate their relative
usefulness
• exercise powers of interpretation and evaluation of arguments and
evidence
• present research findings in a critical manner
• follow the necessary process for ensuring best practice in research ethics
in their project, where appropriate
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Teaching Staffs on the Module
Dr. Neophytos Lambertides
• office: Neophytos Lambertides, BH (N) 3.09, Bush House Building
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Assessment of the module
• Commentary on Selected Paper (10% of total mark): Individual work. Word count:
400
• Essay (20% of total mark): a research-based essay (no more than 1000 words
excluding numbers in analysis) on econometrics and data analysis
• Exam (70% of total mark): 2-hour exam on all material covered in this module
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Formats of module activities
• Lectures: 60 mins each week
• Tutorials: around 55 mins each week focusing on the discussion
of research papers and the practical implementation of selected
methods.
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Commentary (10%)
• Individual written commentary
• Word count: 400
• Commentary should focus on:
o Research motivation and research questions of the paper
assigned
o Contribution of the paper
o Potential improvements to the research
• Submission deadline: 5pm GMT, 8 Nov 2024
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Essay (20%)
• A problem set on empirical data analysis will be given before the
reading week. You are required to collect data and complete the
analysis using the techniques you have acquired in the module.
• Wordcount: no more than 1000 words excluding numbers in
analysis
• Submission deadline: 5pm GMT, 29 Nov 2024
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Exam (70%)
• Written exam on all topics covered in this module. Material
covered includes lectures, tutorials, and all compulsory readings.
• Sample exam will be given after reading week.
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Plagiarism
• We take plagiarism very seriously
• Refer to student handbook and guidelines on kcl.ac.uk including
but not limited to:
• Student guidance on Academic Honesty and Integrity
(https://www.kcl.ac.uk/aboutkings/orgstructure/ps/acservices/conduct/S
tudent-Guidance-on-Plagiarism.pdf)
• Academic Honesty & Integrity Policy
(https://www.kcl.ac.uk/governancezone/assets/assessment/academic-
honesty-integrity-policy.pdf)
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Readings
• Compulsory:
• Approx. 1-2 research paper per week (to be advised)
• Lecturer slides
• Tutorial questions (if applicable)
• Optional textbooks (recommended):
• Principles of Econometrics (4th or 5th editions), by R. Carter Hill et al.
• Relevant chapters: Ch. 1-9, 12, 14, 15
• Introductory Econometrics: A Modern Approach (any edition), by Jeffrey Wooldridge.
• Relevant chapters (based on 6th ed.): Ch. 1-8, 10-14
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Research
Methods
Research Methods
• Research methods are split broadly into quantitative and
qualitative methods
• Which you choose will depend on
• your research questions
• your underlying philosophy of research
• your preferences and skills
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Choosing your approach
• Your approach may be influenced by your colleagues’ views, your organisation’s approach, your
supervisor’s beliefs, and your own experience
• There is no right or wrong answer to choosing your research methods
• Whatever approach you choose for your research, you need to consider five questions:
• What is the unit of analysis? For example, country, company or individual.
• Are you relying on universal theory or local knowledge? i.e. will your results be generalisable, and
produce universally applicable results, or are there local factors that will affect your results?
• Will theory or data come first? Should you read the literature first, and then develop your theory, or will
you gather your data and develop your theory from that? (N.B. this will likely be an iterative process)
• Will your study be cross-sectional or longitudinal (time series)? Are you looking at one point in time, or
changes over time?
• Will you verify or falsify a theory? You cannot conclusively prove any theory; the best that you can do is
find nothing that disproves it. It is therefore easier to formulate a theory that you can try to disprove,
because you only need one ‘wrong’ answer to do so.
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Quantitative Approaches
• Attempts to explain phenomena by collecting and analysing numerical data
• Tells you if there is a “difference” but not necessarily why
• Data collected are always numerical and analysed using statistical methods
• Variables are controlled as much as possible to eliminate interference and measure the
effect of any change
• Randomisation to reduce subjective bias
• If there are no numbers involved, its not quantitative
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Quantitative Data
• Data sources include:
• Surveys where there are a
large number of respondents
• Observations (counts of
numbers and/or coding data
into numbers) – i.e. no
respondents
• Secondary data (economic /
financial market data)
• Analysis techniques include
hypothesis testing,
correlation, regression
analysis, etc
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Falsifiability
Are they different????
• Falsifiability or refutability
of a statement, hypothesis,
or theory is the inherent
possibility that it can be
proven false
• Hypothesis testing
• Start with null hypothesis
i.e. H0 – that there will be no
difference
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Analysing Quantitative Data
• Always good to group and/or visualise the data initially ->
outliers/cleaning data
• What quantity are you looking for?
Mean, median or mode?
• Spread of data:
• skewness/distribution
• range, variance and standard deviation
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What are you looking for?
• Trying to find the signal from the noise
• Generally, either a difference (between/within groups) or a
correlation
• Choosing the right test to use:
parametric vs non-parametric (depends what sort of data you
have – interval/ratio vs nominal/ordinal and how it is distributed)
• Correlation does not imply causation!
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Does correlation always tell the truth?
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Identification Strategy
• We want to tell more about a relationship than merely:
• x is associated with y
• a is related to b
• To establish a plausible causality (i.e. x caused y)
• More to be covered in Lectures 6 and 7
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Theoretical Research
• Normative theory
• A type of theory that focuses on what should be or what ought to be, rather than what is. It's about setting standards, values, or
goals.
• Descriptive statement: "People in Italy generally eat a Mediterranean diet.“ This is fact
• Normative statement: "People in Italy should eat a Mediterranean diet because it is healthier.“ This expresses an opinion about what people ought to do
• Theories about how economies should be managed to achieve certain goals, such as economic growth or social justice.
• Positive theory
• A type of theory that focuses on what is or what exists in the real world. It's about describing, explaining, and predicting
phenomena without making judgments about whether they are good or bad.
• Descriptive statement (also Positive statement): "People in Italy generally eat a Mediterranean diet.“
• Positive statement: "People who eat a Mediterranean diet tend to have lower rates of heart disease."
• Other examples include MM irrelevance theorems, capital asset pricing model (CAPM), accounting valuation models, option
pricing theory, agency theory
• Interpretive/critical theory
• Primarily concerned with developing understanding through observing aspects of behaviour, practices and technologies
• This leads to interpretive frameworks for understanding how accounting and finance function in organisations and society
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Empirical Research
• Empirical research builds our understanding through empirical evidence
• Empirical research largely builds on positive and interpretive/critical
theoretical perspectives
• Positive approach is most prevalent in empirical research in financial
reporting and financial management where researchers test hypotheses
related to theoretical models
• Interpretive / critical approach is more prevalent in management accounting
where researchers are concerned with the organisational functioning of
accounting practices
• Research on governance and accountability includes different approaches,
some studies adopt more positivist approach, others are more interpretive /
contextual
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Issues in Finance and Accounting
• Our focus in this module is on questions and issues addressed in the empirical research
literature
• A wide variety of research questions or issues are addressed in this literature
• Some questions / issues may be closely related to predictions of particular positive theories
or models
• Other questions may be more open-ended and seek to understand how techniques and
information are used by capital market and organizational participants
• Note also an increasing tendency for research questions to be related to issues of current
economic, social and regulatory importance
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Examples of research questions
• Does the capital market make use of accounting information to value shares and has
the introduction of IFRS improved the quality of accounting information?
• What is the relative usefulness of different types of accounting information (e.g.,
earnings v cash flow information) to investors?
• Are fund managers able to generate abnormal stock returns (i.e. returns above the
‘required’ rate of return)?
• How important is corporate governance information to the analysis and
recommendations of financial analysts?
• What is the relationship between ESG performance and firm value? To what extent
does ESG performance influence firm valuation?
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