BlockbookFRM2015.1

Course Manual

Financial Research Methods

EBC4095

Master:

International Business Studies

Finance

School of Business and Economics (SBE)

Maastricht University

Academic Year 2014/2015

All rights reserved. ©2014 Maastricht University.

February, 2015

1

Contents

1 Introduction 3

1.1 Course Overview . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.2 Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.3 Academic Honesty . . . . . . . . . . . . . . . . . . . . . . . . 6

2 Organisation 6

2.1 Instructors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.2 Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.3 Schedule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.4 Classroom Tutorial Meetings . . . . . . . . . . . . . . . . . . . 10

2.5 Computing Classes . . . . . . . . . . . . . . . . . . . . . . . . 19

2.6 Final Research Paper . . . . . . . . . . . . . . . . . . . . . . . 20

3 Examination Requirements 22

3.1 Attendance & Participation . . . . . . . . . . . . . . . . . . . 23

3.2 Research Paper . . . . . . . . . . . . . . . . . . . . . . . . . . 24

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Block Book Financial Research Methods Period 4 Academic Year 2014/15

1 Introduction

1.1 Course Overview

The course Financial Research Methods is intended to provide students with

the necessary tools to understand, assess, and perform research for both

academic and business purposes specifically related to financial applications.

The aim of the course is to prepare students to a level where they can perform

high quality research in finance. The course gives students the skills with

which to to develop a research proposal that has the following three important

qualities: it is well motivated, properly designed, and feasible to implement.

This is particularly relevant for writing the Master’s thesis, which all students

of this program are required to do towards the end of their Master’s year.

The course structure has three parts, which run in parallel. The first

part of the course covers general research elements; both methodology and

theory are discussed during tutorial meetings. The second part focusses on

quantitative methods with an emphasise on applied quantitative analysis.

In the final part of the course students are required to produce their own

research assignment, which covers all the elements studied during the course.

In the first session, we start by discussing different research methodolo-

gies, such as interpretivism and positivism. We also cover core elements

of the research process so that you become aware of the essential elements

that are required when writing a high quality research paper. A decent re-

search paper, for instance, needs a theory and a model as a basis to derive

a testable hypothesis, or hypotheses. Moreover, a researcher has to decide

whether his/her work should be of a quantitative or qualitative nature. If it

is an empirical study would you rather rely on primary or secondary data?

What are the limitations to the research? It is important that the researcher

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is able to put the work into perspective and to understand the drawbacks

and limiting assumptions in the research. In short, there are many aspects

to the research process that need to be addressed to guarantee well executed

research.

We build on students’ knowledge from the undergraduate course Quan-

titative Methods. In conducting empirical research we focus on classical

regression analysis, one of the fundamental building blocks for conducting

empirical research. We cover how ’good’ regression analysis is conducted,

and in which cases the classical assumptions for OLS regression are violated.

The classes are practical in nature and students learn how to conduct main-

stream financial research, and to evaluate regression output. For example, is

a regression always good if it has a R2 that is close to 1? And what other

statistics are there and what do they mean? Students should become confi-

dent about the use of OLS, an important tool used in conducting financial

research.

During the course students attend a number of computer sessions, where

they use the Econometric package Eviews. The emphasis of the course is on

students learning to use and apply a number of familiar Econometric tech-

niques. The course book is geared specifically towards students who require

an introduction to Econometrics with a focus on financial applications. Ad-

ditional literature is used to investigate in greater depth the methodology

behind the chosen research method.

Students shall learn which resources the University offers in the provision

of financial data. Other online data sources are also available for downloading

financial data. Students learn how to conduct their own empirical research,

using a variety of applications to issues in finance. We use financial time series

data, which covers how a series of data changes over time, such as stock prices

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or interest rates. Cross sectional data is also used, which accesses data at a

given point in time, for example the current share price for all companies in

the market index. Finally students are introduced to the use of panel data.

This teaches students the techniques with which to do research on a cross

sectional panel of data, across a period of time. Used together students can

therefore analyse data over space and time.

Throughout the course students acquire theoretical skills and shall ac-

tively use these skills on empirical data. The course provides an excellent

basis from which students are able to conduct financial research. The tech-

niques learned and applied are the foundations for writing the final thesis,

which is a required part of the Master program. Students are encouraged

to actively prepare themselves for the final thesis by considering topics and

methods for financial research during the course.

During the tutorials students are expected to discuss and analyse a num-

ber of academic research papers. The emphasis is to critically evaluate what

makes the paper a good research paper, and relate this back to the research

methodologies and theory discussed at the beginning of the course. Whilst

also conducting empirical research, the students shall be able to assess the

potential pitfalls and problems associated with conducting research.

Finally, the course concludes with students writing their own piece of

research. This is done in pairs, or at maximum groups of three, assigned

during the first tutorial meeting.

1.2 Computing

All faculty, staff and students of the University are governed by the Accept-

able Usage Policy for the use of computers, printers and library facilities.

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1.3 Academic Honesty

Students who enrol at Maastricht University commit themselves and their

peers to a high standard of honour and integrity. Failure to comply with

this commitment can result in disciplinary action, up to and where necessary

expulsion from the University.

2 Organisation

2.1 Instructors

This block book has been compiled by Dr. Rachel A. J. Pownall who is the

course coordinator. If you have any comments, questions or suggestions con-

cerning the course, please address them to Dr. Pownall preferably by e-mail.

If questions are of general interest I shall provide feedback through the course

website on Eleum and the course tutors. The course tutors are Rogier Quaed-

vlieg and Alessandro Pollastri. Emails: [email protected]

and [email protected].

If you want to contact me in person please respect my office hours for

this course, or arrange a meeting via the department secretaries. Their email

address is: [email protected]

Course Office Hours: Wednesdays from 16.30 - 17.30

Room: B1.05b (Finance Department)

The course website can be found on Eleum. It contains announcements,

additional information, information on tutors, last-minute schedule changes

and answers to frequently asked questions. Please make sure that you check

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this site regularly.

2.2 Literature

During the course we closely follow the textbook by Chris Brooks, Intro-

ductory Econometrics for Finance, 3rd Edition, Cambridge University Press.

ISBN: 978-1-107-66145-5. Students are advised to buy a copy of the book for

the course. A number of additional academic articles are required reading for

the course and shall be available on EleUM, posted throughout the duration

of the course.

2.3 Schedule

The course consists of an opening lecture, tutor group meetings, computer

lab sessions and a research project. During the course there are two meetings

per week. During the opening session a general overview of the course shall

be given and how the course fits within the overall schedule of the Master pro-

gramme. During the second week there is a lecture devoted to data resources

available to students at the University. There are a number of different data

sources available which shall be explained in detail. Students shall be able to

download their own data for the assignments and for their research projects.

In so doing this also prepares students for the empirical part of their final

thesis as the other data resources can be born in mind for a later stage.

Below, in Table 1 we provide a general overview of the course on a week

by week basis:

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Table 1: Course Timetable

WEEK 1 OPENING & RESEARCH PHILOSOPHY

05-FEB-15 Block Opening Opening Lecture (13:30-15:30 C-1.03)

Overview of course, objectives and course structure

WEEK 2 DATA & INTRODUCTION TO EVIEWS

09-FEB-15 Classroom Tutorial 1 Research Philosophy

Methodology for financial research

12-FEB-15 Computing Lab Session 1 Running Regressions

Introduction to Eviews

Calculating returns

Basic functions

Statistical Inference & Testing Outperformance

WEEK 3 FUNDAMENTALS FOR FINANCIAL RESEARCH

23-FEB-15 Classroom Tutorial 2 Discuss Computing Class Results 1

Statistical Inference

Classical linear regression

Reading distributions tables

26-FEB-15 Lecture Data Collection (13:30-15:30 C-1.03)

WEEK 4 CONDUCTING EMPIRICAL FINANCIAL RESEARCH

02-MAR-15 Computing Lab Session 2 Downloading Data

Risk and Return

Capital Asset Pricing Model

05-MAR-15 Classroom Tutorial 3 Discuss Computing Class Results 2

Theoretical framework for financial research

Writing a literature review

Defining hypotheses

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WEEK 5 EXTENDING OUR RESEARCH METHODS TOOLKIT

09-MAR-15 Computing Lab Session 3 Further Issues in Regression Analysis

Stationarity

Multivariate Regression

Robust Standard Errors


Breakdowns in the assumptions for OLS

Autocorrelation

Multicollinearity

Heteroskedasticity

Omitted Variable Bias

Correct Functional Form

WEEK 6 APPLIED FINANCIAL RESEARCH

16-MAR-15 Computing Lab Session 4 Writing a Program

Applied Course Review

Class output to be printed and handed in at the end of the class

Dummy Variables


Cutting Edge Financial Research

Group Presentations of Current Research Papers

WEEK 7 APPLIED FINANCIAL RESEARCH

23-MAR-15 Meetings with Tutors Half hour Individual Group meeting with tutor on final research project

26-MAR-15 Work on own paper

EXAM WEEK ASSESSMENT

03-APR-15 Hand in on EleUM DEADLINE FOR FINAL RESEARCH PAPER Midnight!

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2.4 Classroom Tutorial Meetings

There are five PBL tutorial meetings throughout the course. In the first

week, we deal with research methods in general. In the following four tuto-

rials the material from the course book is covered along with a number of

supplementary articles. The tutorial meetings enable the theory and meth-

ods of financial research to be discussed. Sequential to each tutorial meeting

is a computing session where the material from Brooks is applied to a num-

ber of research topics in finance, allowing students to develop their applied

skills, to put the theory into practice. These computing classes are a valuable

addition to the teaching of the course material. This is further outlined in

section 2.5 on the computing classes.

During the classroom tutorials the aim is for students to critically review

and evaluate research that has been conducted by others, using the concepts

discussed during the tutorial on research philosophy, and the econometric

fundamentals from the course book. Discussing research articles highlights

how the quantitative techniques that you acquire during the course are ap-

plied in practice.

In this course the primary aim is to learn and understand about research

methods. The goal is to present the research project. This implies that you

should discuss issues such as, for example, defining the problem statement?

How are the hypotheses derived? How do the authors get to their results?

Why are they using (or not using) a particular statistical technique? Why

and how is a sample selected and what is the corresponding relevant popula-

tion? etc. In short, you are asked to show that you understand the intuition

and the motivation of the research. The approach by Whetten (1989) pro-

vides a good point of reference in providing the pointers when presenting and

discussing research papers.

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It is also important to focus on the quality of the research and the choice

of the econometric techniques used. In your analysis incorporate for instance:

Why you think that the respective articles are good or bad, where would you

expect the research to be published? How would you improve the articles,

etc.? Furthermore, also try to contrast research with other articles and how

they add to the encompassing literature. To what extent is it better in

terms of, for example, further use and application of the results, contribution,

techniques, etc.? For further guidelines on critical aspects of research paper,

please refer to the book of Brooks (2002), Chapter 1, Section 6.

Additional articles must be obtained by students themselves. This is to

ensure that students know how, and where, to find research papers them-

selves.

During the tutorial meetings learning objectives and goals are formulated.

The EViews output shall be discussed. The tutor may ask individuals at

random to present their results. Remember that it is important to the func-

tioning of the course that all individuals are well prepared for the meetings.

Remember to bring a copy of the EViews output from the computing class

preceding the tutorial meeting and be able to access your workfile. Students

should be prepared to use EViews during the tutorial meetings to discuss

their work as and when is required. At the end of each tutorial meeting

students are required to hand in the question with an asterisk (*)

to their tutor. This forms part of the participation grade for the meetings.

Please refer to the examination requirements, in section 3 for further details.

The outline for the tutorial meetings is given below. All students are

expected to prepare and be able to discuss the following points for each of

the five tutorial sessions. The course material is subject to changes.

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Tutorial 1: Research Philosophy

Research methods can differ along several dimensions. We can categorise

research, for instance, by referring to it as exploratory, descriptive or causal;

research can be of a qualitative or quantitative nature. It also differs de-

pending on the standpoint of the researcher: Is he part of the phenomenon

that he is attempting to analyse? or does (s)he take an external position? in

which case it is certainly easier to provide ‘value-free’ research.

1. Discuss the steps involved in preparing a well-grounded research project

or dissertation.

2. According to Whetten (1989), a solid theoretical contribution comprises

of four elements. Discuss each of these elements within the structure

of a research proposal.

3. Discuss the roles of deduction, induction and reduction in research

philosophy.

4. Krauss (2005) introduces students to the epistemological differences

between quantitative and qualitative research paradigms. It is an in-

troduction to research methodologies, and how meaning making actu-

ally occurs through looking at qualitative data analysis. Discuss in this

context qualitative and quantitative research.

5. Discuss positivistic, realistic, and interpretivistic research, naturalism

and constructivism.

6. What type of methodology is generally used for financial research and

why?*

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Reading

• Brooks (Chapter 14), Friedman (1966), Krauss (2005) and Whetten

(1989).

• Ryan, Scapens and Theobald (Chapter 1). Research Method and

Methodology in Finance and Accounting.

Tutorial 2: Fundamentals for Financial Research

The majority of financial research is based on empirical data. There is

an enormous amount of data available, however, there are also many is-

sues with collecting data for empirical financial research. For example mis-

measurement and missing values. During the tutorial meeting we shall dis-

cuss some of these issues. Furthermore we discuss the workhorse of applied

financial research; the use of ordinary least squares (OLS) for running re-

gression models. The aim of the tutorial is to ensure students have a good

working knowledge of basic Statistical Inference and Classical Regression

beyond that taught in earlier quantitative research courses.

1. Discuss data sources for qualitative and quantitative financial research.

Do you know what is available at the UM? via the Library? Online?

2. What is classical regression and how is it helpful in financial research

methods?

3. Using an example of your choice discuss the five classical assumptions

in the classical regression model.*

4. When are the estimators used in OLS BLUE?

5. Discuss the issue of Causality and Spurious Regression.

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6. Recall how you would conduct some basic statistical inference and a

difference in means tests?

7. What is the difference between a Type I and a Type II error?

8. Discuss the EViews output and questions from the first computing

class*.

Reading

• Brooks Chapter 1, 3 & 7.1. (Prior knowledge: Brooks Chapter 2).

• Granger (2004), Krueger (2001), Zellner (2007), Hausman (2001), Drakopoulus

and Torrance (1994).

Tutorial 3: Theoretical framework for financial research

Once a research problem has been identified and justified, then the next

step is to analyse the problem by formulating a hypothesis. Hypotheses are

constructed based on abstract theory. The research method chosen depends

upon the philosophy upon which the stream of current research on the topic

is built. The process which dominates much of mainstream finance is the

positivist quantitative approach.

The notion of the ‘model’ as an abstraction of reality is a more meaningful

concept within the finance discipline than the notion of theory. Financial

research requires a clearly defined hypothesis and model from which to test;

often with empirical data. In order to produce good research it is important

to set out clearly your theory and entails the development of theoretical

models which are then tested by confronting hypotheses derived from these

models with empirical data.

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Theory development within finance is based upon neo-classical thinking.

There are a number of core terms, which are taken as non-conjectural. The

three propositions which form the basis of, at least, the initial phase of model

development within the general framework are as follows:

I. Economic agents (investors and decision makers) are, at the individual

level, formally rational

II. Financial markets are perfectly competitive

III. Information is freely available.

Other frameworks for theory development can be followed. However, the

approach here provides us with the general perspective from which most

mainstream finance has been built upon. From which modifications can be

acknowledged.

1. Discuss each of these three propositions above in the context of devel-

opments in the literature in financial research.

2. Which steps should be followed in forming a model and outline for your

research? Use as an example the CAPM: *

• How would you set up a research paper to test the CAPM?

• What assumptions does the CAPM require?

• Is there a joint hypothesis problem (Roll critique) and would this

influence your results?

• Is OLS appropriate for testing the CAPM? i.e. How can you be

sure that your estimate for Beta (coefficient in the regression) is

BLUE?

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• In what ways could you extend the methodology to the CAPM?

• How would you test how good your multiple regression model is?

3. Discuss the EViews output and questions from the second computing

class*.

Reading

• Ryan, Scapens and Theobald (Chapter 3). Research Method and

Methodology in Finance and Accounting.

• Brooks (Chapter 4) and Jagannathan and McGrattan (1995).

Tutorial 4: Running Good Regressions

The vast majority of research in applied financial used simple parametric

approaches such as OLS regression. However, when the assumptions under-

lying the OLS approach break-down then problems arise. For example when

the relationship between the variable is not linear, when the regressors are

correlated with the error term, when the error term is heteroskedastic or

autocorrelated, or when the variables are mis-measured (See Krueger, 2001).

How we deal with these issues is the subject of today’s tutorial.

1. Discuss the consequences of autocorrelation?

2. How do we test for autocorrelation?

3. What type of model could you use to overcome any limitations from

autocorrelation, so that you use the autocorrelation to your advantage?

4. Discuss correlation, causality and multicollinearity.

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5. What is heteroskedasticity and how can we detect it in financial time

series?

6. Which criteria should be satisfied, and which methodology followed, in

your choice for a final acceptable model? (Think also about functional

form, choice of variables, parameter stability, non-normality).*

7. Hand in and discuss the results from the third computing session.*

Reading

• Brooks (Chapter 5), Granger (2004), DiNardo and Tobias (2001), Hansen

(2001).

Tutorial 5: Cutting Edge Finance Research

During the tutorial meeting each group shall present a current research paper

from the finance literature. The focus is on how good research is conducted.

When presenting the research bare in mind the following points.

1. What question are the authors trying to answer?

2. Is the research well motivated and the objective clear?

3. Do they formulate a hypothesis to answer the question?

4. How do they text their conjecture/hypothesis/research question?

5. Are the tests significant/robust to the model specification?

Reading

• A choice of articles for discussion and presentation will be made avail-

able on Eleum during the course.

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2.5 Computing Classes

Starting in the second week we have four computing classes, which take

place in the University Library Computing rooms. There is one computer

session per week. Students are introduced to the statistical software Eviews

which can be accessed during the classes. This gives students a hands on

chance to learn some useful econometric tools for the analysis of financial

data sets and statistical inference. The sessions are backed up by the tutorial

group meetings which alternate between the computing sessions. Providing a

focus on both theory and practise for financial research. The software is also

available via the UB anywhere link. www.maastrichtuniversity.nl/anywhere.

At the beginning of each computing class the tutor shall introduce the

topic and explain what is required during the class. Students shall be given a

task to prepare, which needs to be completed during the class. It is expected

that students work independently, each at an individual computer. The tu-

tor shall be able to assist students in the classroom. In some cases students

shall need to download data beforehand, which will be used in class. When

this is the case this shall be discussed in detail during the tutorial meeting

proceeding the computing class. At the end of the session students are re-

quired to hand in a copy of their output for the class. For each class an

individual grade is given to each student. This comprises 32% of

the final grade. It is therefore important that students read the relevant

chapter of the course book (and any other additional material required) in

preparation for the class.

The content and the order of the course closely follows the book of Brooks

(2014), which is the compulsory literature for this course. We strongly recom-

mend, that you also consider additional literature, especially when preparing

for teaching your fellow students. Wooldridge (2000) is particularly useful.

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http://www.maastrichtuniversity.nl/anywhere


2.6 Final Research Paper

As a final task, you are expected to carry out your own small-scale research

project and to write a short empirical paper. This has several purposes.

Firstly, students are expected to show that they are able to implement the

concepts of research methodology to a real-life project. Secondly, this gives

students the opportunity to prove that they have understood the quantita-

tive techniques that have been taught and can apply the tools to real data.

Thirdly, the use of EViews will become easier once applied to a chosen empir-

ical investigation. Finally, students have the opportunity to show that they

can write in a scientific manner and are able to write in an understandable,

condensed and sophisticated manner. These are all attributes which are use-

ful in preparing you for writing your final thesis at the end of the Master

program.

While working on your paper, there are no tutorial meetings scheduled. You

are expected to work on the paper mainly by yourselves within your sub-

group. If you get stuck or need to back-up your progress, please send your

tutor an email and/or we can arrange an appointment. In any case I strongly

recommend that you consult at least once with the respective supervisor of

your topic, to make sure that your research is going in the right direction.

In addition, you can refer to Wooldridge (2002), Chapter 19 for guidelines in

writing your paper.

Towards the end of the course we will distribute the topics for your em-

pirical project. In case the number of groups are not more or less evenly

distributed across the subjects, we reserve the right to assign you to topics.

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Independent of your topic, we expect you to include an introduction, a decent

literature review, methodology, analysis, and a conclusion in your paper. It is

important to focus on the research methodology, and the philosophy behind

the research method in order to obtain a sufficient grade.

The grade for the research paper depends on the following five, equally

weighted elements:

- Justification of your research methodology

- Reviewing the relevant literature

- Formulation of a research hypothesis and a testable framework

- Empirical Analysis

- Interpretation of results and discussion

The deadline of your max. 12 page (without graphs and tables) paper

is midnight on Friday April 3rd, 2015! As usual, you are expected to write

in “Times New Roman” font, 12 pt, 1.5 line spacing.

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3 Examination Requirements

The evaluation of students’ performance in this course is made up from the

three components of the course. Participation during classroom tutorials,

computing class assignments and the final research paper. Each component

carries roughly one third of the overall course grade. The exact weighting is

given below: the grade from your individual participation during the 5 class-

room tutorial meetings (each meeting accounts for 7%), the 4 assignments

during the computing sessions (each assignments carries an 8% allocation),

and the final research paper (33%). The weighting therefore follows the sim-

ple rule:

Final grade out of 10

+ 0.35 × Classroom Tutorial Participation

+0.32 × Computing Lab Assignments

+0.33 × Final Paper Group Grade

The emphasis is on your individual scores to encourage all students to

understand and cover the material over the duration of the course. Therefore

2/3 of the final grade is obtained during the tutorial and computing class

participation and assignments. These are graded on an individual basis.

The final third is assessed as a group grade, and requires the group to act

in a coherent manner together. The tutors shall grade all aspects of your

participation during the course, so it is important to attend and be active

during all meetings. In order to pass this course two requirements must be

fulfilled

21


1. Each of the separate grades mentioned above have to be a minimum of

a ≥ 5.0.

2. To pass the course, the final grade has to be a ≥ 5.5 or above. Where

scores below 5.5 shall not be rounded up.

In case you fail either of your individual partial performance grades you will

have to follow the entire course again. This also implies that even if you

passed your final paper, but failed one or several of the other requirements,

you will have to complete and pass all parts in a second attempt of the course

again.

In case you fail only the final paper, you will have the possibility to reg-

ister for a re-sit in the corresponding re-sit period. You will be asked to

complete another final research paper. This will be of a similar form and

scope as the original task. Paper topics will be assigned to you by one the

course coordinator beforehand, such that you will have a comparable period

to work on the paper as students had in the first attempt. Note however

that opposed to the original paper project, you will be working individually

on your re-sit paper.

3.1 Attendance & Participation

Generally, you are expected to be present at all group meetings and lectures

throughout the first five weeks of the block. If you do miss a tutorial meeting

or one of the computing sessions you will get a zero grade for the participa-

tion and the assignment. In exceptional circumstances please discuss your

situation with your tutors. Not actively participating in the tutorial meetings

shall also result in a zero grade.

22


3.2 Research Paper

Note that you will have approximately two weeks to work on your own final

project. This is sufficient time to complete the task. Hence, please make sure

that you strictly stick to the deadlines that will be announced in the course

of the block.

23


References

[1] Brooks, Chris (2014) “Introductory Econometrics for Finance ” Cam-

bridge University Press, 3rd Edition.

[2] Drakopoulos, Stavros. A., and Thomas S. Torrance (1994) “Causality

and Determinism in Economics ” Scottish Journal of Political Economy,

Vol 41(2) pp. 176-193.

[3] DiNardo, John and Justin L. Tobias (2001) “Nonparametric Density and

Regression Estimation. ” Journal of Economic Perspectives. Vol. 15(4),

pp. 11-28.

[4] Engle, Robert (2001) “GARCH 101: The Use of ARCH/GARCH Models

in Applied Econometrics. ” Journal of Economic Perspectives. Vol. 15(4),

pp. 157-168.

[5] Engle, Robert (2004) “Risk and Volatility: Econometric Models and

Financial Practice. ” The American Economic Review. Vol. 94(3) pp.

405-531.

[6] Friedman, Milton (1966) “The Methodology of Positive Economics ”

in Essays in Positive Economics. University of Chicago Press. pp. 3-16,

30-43.

[7] Granger, Clive W. (2004) “Time Series Analysis, Cointegration, and

Applications. ” The American Economic Review. Vol. 94(3) pp. 421-

425.

[8] Hansen, Bruce E. (2001) “The New Econometrics of Structural Change:

Dating Breaks in U.S. Labor Productivity. ” Journal of Economic Per-

spectives. Vol. 15(4), pp. 117-128.

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[9] Hausman, Jerry (2001) “Mismeasured Variables in Econometric Analy-

sis: Problems from the Right and Problems from the Left. ” Journal of

Economic Perspectives. Vol. 15(4), pp. 57-67.

[10] Horowitz Joel L., and N. E. Savin (2001) “Binary Response Models:

Logits, Probits and Semiparametrics. ” Journal of Economic Perspec-

tives. Vol. 15(4) pp. 43-56.

[11] Jagannathan, Ravi and Ellen R. McGrattan (1995) “The CAPM debate.

” Federal Reserve Bank of Minneapolis Quarterly Review. Vol 19(4) pp.

2-17.

[12] Krauss, Steven E. (2005) “Research Paradigms and Meaning Making:

A Primer. ” The Qualitative Report, Vol 10(4) pp. 758-770.

[13] Krueger, Alan B. (2001) “Symposium on Econometric Tools. ” Journal

of Economic Perspectives. Vol. 15(4) pp. 3-10.

[14] Ryan, Bob., Robert W. Scapens, and Michael Theobald. (2002) “Re-

search Method and Methodology in Finance and Accounting. ” South-

Western Cengage Learning.

[15] Whetten, David A. (1989) “What Constitutes a Theoretical Contribu-

tion? ” The Academy of Management Review, Vol. 14(4), pp. 490-495.

[16] Wooldridge, J. M. (2002) “Econometric Analysis of Cross-Section and

Panel Data. ” MIT Press, Massachusetts.

[17] Zellner, Arnold (2007) “Philosophy and Objectives of Econometrics. ”

Journal of Econometrics 136, pp. 331-339.

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BlockbookFRM2015.1

Documents

research process

research paper242block

research proposal

conductingempirical

course students

final research paper

general research elements

performhigh quality