IMBA THESIS WORKSHOP
CLASS 2
P. SCHUHMANN, SPRING 2013
LECTURE MATERIAL BASED ON THE WORK OF
STEVEN GREENLAW:
DOING ECONOMICS: A GUIDE TO UNDERSTANDING
AND CARRYING OUT ECONOMIC RESEARCH,
STEVEN A. GREENLAW, 2006.
HOUGHTON MIFFLIN CO.
AVAILABLE FOR PURCHASE HERE:
HTTP://WWW.AMAZON.COM/DOING-ECONOMICSUNDERSTANDING-CARRYING-ECONOMIC/DP/0618379835
THESIS OUTLINE
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Title
Abstract
Table of contents
Acknowledgements
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Introduction
Literature review
Theory
Data
Methods
Results
Discussion & conclusions
• References
• Appendices
SUMMARIZING RESEARCH
• What is the research topic?
• What is the research question(s)?
• Is this research question problem oriented or descriptive?
• What is the hypothesis?
• What is the basis of this hypothesis?
• What data are used?
• What methodology is used?
• What are the results?
• i.e. what are the facts associated with testing the hypothesis?
• What knowledge is created?
• Using logic, theory and intuition, what is the meaning of the
facts?
• What other interesting questions can be investigated?
• Can you suggest exploratory or confirmatory research that
might be associated with the research questions addressed in
this study?
QUESTIONS TO GUIDE YOUR A.B.
You should attempt to answer the following for each
paper you read (1-3 sentences for each):
• Who? (full citation)
• What? (what are the research questions?)
• Why? (why is this important?)
• How? (how was the research question addressed?
i.e. what data and methods were used?)
• What? (what were the main findings?)
• Why? (why is this important?)
READING AND SUMMARIZING
• What methodology is used?
• What if I don’t understand what the authors did?
• Chances are that you will encounter several papers
where you do not fully understand the
methodology. This is normal.
• If the paper is published, then it is very likely that the
authors were able to convey the purpose of their
study and some basic idea of the methods.
• Summarize what you can.
• Ask your committee members for guidance.
ARE A LIT REVIEW AND AN A.B. THE
SAME?
• No.
• An A.B. is a list of sources and summaries of those
sources that you reviewed in order to understand
your topic.
• A literature review is a summary of the work that has
been done in your topic area, written with the goal
of providing the reader with the information
needed to understand:
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The major findings in the area
The approaches (and data) employed
Any deficiencies in those studies
The importance of your topic
LIT REVIEW
• The purpose of the literature review is to provide
justification for your research.
ELEMENTS OF GOOD WRITING
Use the literature
• Seek out published confirmation of your thoughts,
ideas and assertions.
• “Facts” should always be cited, unless they are
common knowledge.
ELEMENTS OF GOOD WRITING
• Always give credit for intellectual property.
• Failure to do so is plagiarism.
• The key to avoiding plagiarism is to keep very
careful records of everything you read and
everything you write.
• When in doubt, cite it.
CITING YOUR SOURCES
• One or two authors:
• Smith (2001) notes that …
• Smith and Jones (2008) suggest …
• Empirical analysis of the relationship between
environmental quality and travel demand includes
applications in Asia (Lee and Phan, 2009), the Caribbean
(Schuhmann, 2010; Oxenford and Mahon, 2007), and the
U.S. (Dant, 2001; Ainsley and Medford, 2005).
CITING YOUR SOURCES
• More than two authors:
• Smith et al. (2001) note that …
• et al. is an abbreviation for the Latin phrase et alia,
which means “and others.”
• The period comes after “al.”
• Provide the full citation in the reference section
HOW TO CITE A SOURCE
Reference sources of factual information or opinion:
• “The protection of biological resources maintains
essential ecosystem services that, while not explicitly
represented in GDP (de Groot et al., 2002), serve to
attract foreign exchange to developing nations via
tourism (e.g. Troëng and Drews, 2004), and
significantly contribute to human health and quality
of life (McField and Kramer, 2007).”
• “Lack of formal teacher training and the ingrained
tradition of conventional methods of teaching and
assessment may also create barriers to change in
the classroom (Sunal et al, 2001).”
HOW TO CITE A SOURCE
Reference facts, positions or arguments to
help motivate your argument: :
• “Kwok (2006) and Weber (1998) suggest that
financial systems differ across countries
because of different perceptions of risk.”
• “Graham et al. (2010) show that …”
HOW TO CITE A SOURCE
Reference general methodology
• “The random utility modeling framework for
describing site-choice decisions is well
established in the literature (see, e.g.,
Bockstael et al. 1987; Bockstael et al. 1989;
Kaoru et al. 1995).”
HOW TO CITE A SOURCE
Reference modeling particulars:
• “In a framework similar to those employed
by Bunn et. al. (1992), Mixon and Mixon
(1996), and Mixon (1996), we seek to
determine the degree to which
macroeconomic movements impact firm
investment behavior, ceteris paribus.”
• “Following Burrus et al. (2009) we also control
for differences in firm size using the log of the
number of employees.”
HOW TO CITE A SOURCE
Reference source conclusions to support your
conclusions:
• “These results are also supported by those found by
Baird (1980), Kerkvliet (1994), McCabe and Bowers
(1996), and McCabe and Trevino (1997), but stand
in contrast to the results found by Kermit et al.
(1990). Notably, we show …”
HOW TO CITE A SOURCE
Reference sources for additional information:
• “There is currently no ongoing teacher
training program in economics, and past
efforts have varied in terms of intensity of
experience and frequency. For more
information on such programs see Salemi
(2010), Goodman et al (2003) and Salemi et
al (1996).”
ELEMENTS OF GOOD WRITING
• You should rarely (if ever) use direct quotes
in your paper.
• The effort required to paraphrase someone else’s
ideas are an important part of gaining a
command over the literature.
• There is almost always an alternative way of
expressing a thought.
• You want to put the work of others into the
context of your work.
ELEMENTS OF GOOD WRITING: ACTIVE OR
PASSIVE VOICE?
Which of these styles of writing seems more
appropriate for your thesis (or professional
research article)? A or B?
A. “We measure the importance of several factors
influencing biotech valuation.”
B. “The importance of several factors influencing biotech
valuation were measured”.
-----------A. “I hypothesize that firms with greater drug approval rate
will have higher valuations.”
B. “It is hypothesized that firms with greater drug approval
rate will have higher valuations.”
ELEMENTS OF GOOD WRITING: ACTIVE OR
PASSIVE VOICE?
The active voice is clearer and more honest.
• “We collected data from…”
• “We hypothesize that …”
• “We estimated the following model …”
• “We can conclude that …”
• “ I…” instead of “We…” is perfectly fine (especially
for a thesis, which by definition has a single author),
but less common.
ELEMENTS OF GOOD WRITING
• Keep it simple.
• Avoid run-on sentences.
• Can a sentence be divided into 2 simpler
sentences?
• Avoid emotion.
• Avoid subjective language.
• Is this is a matter of opinion or a matter of
judgment?
• Avoid questions
• But how important is beach width to Caribbean tourists?
PAIR UP
• Choose a topic in finance
• What might be an interesting research question in
this topic area?
• Can you be more specific?
• How might you introduce the research question
(the inverted triangle) to a novice reader on the
subject?
• What data might you need to collect to examine
the research question?
DATA
• What is the concept or relationship in
question?
• How can the concept (or variables in the
relationship) be measured?
• What are the appropriate units of measure?
• What is an appropriate sample frame or
time frame?
DATA
• Cross-section
• Time series
• Panel/longitudinal
TIME SERIES FREQUENCIES
• Quarterly
• GDP
• Profits (Revenues, Costs)
• Productivity measures
• Monthly
• Personal income measures
• Sales measures
• Price indices (CPE, PPI)
• Weekly
• Money measures
• Daily
• Interest rates
• Stock prices
• Exchange rates
TIME SERIES FREQUENCIES
• How to combine time series collected at
different frequencies?
TIME SERIES FREQUENCIES
• Example: Suppose you have total sales data
(measured monthly) and GDP data (measured
quarterly).
• Note: GDP = total value of production
• How could you combine these time series?
• Suppose you have a measure of total output
(measured quarterly) and average price (measured
monthly).
• How could you combine these time series?
SOURCES OF DATA
• Census bureau (www.census.gov)
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Population statistics for the U.S.
Statistical abstract of the U.S.
County and City Data Book
Population census (every 10 years)
Economic census (every 5 years)
Annual survey of Manufacturers
American Housing Survey
SOURCES OF DATA
• Bureau of Economic Analysis (www.bea.gov)
• Major macro indicators for the U.S.
• National income and product accounts (components of GDP
and associated price indices)
• Bureau of Labor Statistics (www.bls.gov)
• Employment, productivity and consumption data
• The Federal Reserve
(http://www.federalreserve.gov/econresdata/)
• Interest rates, exchange rates, money, public debt, bank
assets& liabilities, corporate debt
SOURCES OF DATA
• IMF (http://www.imf.org/external/fin.htm)
• International Financial Statistics (good source of financial
data for IMF member countries)
• EuroStat
(http://epp.eurostat.ec.europa.eu/portal/page/por
tal/statistics/themes)
• Official statistical agency for the EU (fee for historic data?)
• Others: World Bank, Organization for Economic
Cooperation & Development (OECD), UN Agencies
DATA
• What if I cannot find the variable I’m looking
for?
• Can you find or create a proxy?
• Does it measure the same behavior?
• Is it highly correlated with the variable of interest?
• If no proxy is available, can you reformulate the
hypothesis given the available data?
EXCHANGE RATES
Official exchange rates vs. PPP exchange
rates
• To properly use GDP as a measure of
economic well-being, we must consider
differences in purchasing power.
• E.g. comparing per capita GDP in the U.S. to per
capita GDP in Dominica is an inaccurate way to
compare well being, because prices are much
lower for many goods in Dominica.
OFFICIAL EXCHANGE RATES VS. PPP
EXCHANGE RATES
We need equality of purchasing power for these
comparisons to be meaningful.
• The official exchange rate between two countries
may not be an accurate measure of purchasing
power parity (PPP).
OFFICIAL EXCHANGE RATES VS. PPP
EXCHANGE RATES
• Official exchange rates are determined by the
supply and demand for currencies.
• The supply and demand for currencies comes from
the supply and demand for goods and services that
can be purchased with those currencies and
traded over international borders (“tradable
goods”).
• The prices of these “tradable goods” will eventually
equalize across nations due to the forces of supply
and demand. “The law of one price”.
OFFICIAL EXCHANGE RATES VS. PPP
EXCHANGE RATES
• True PPP depends not only on the prices of “traded
goods”, but also on the prices of goods not traded
internationally, like meals, haircuts, bus rides, land,
housekeeping services, etc…
• The prices of these “non-traded” goods are in large
part determined by unit labor costs, which of course
tend to be lower in poorer countries.
OFFICIAL EXCHANGE RATES VS. PPP
EXCHANGE RATES
• PPP exchange rate = ratio of the price of a
basket of (traded and non-traded) goods in
nation a vs. nation b
OFFICIAL EXCHANGE RATES VS. PPP
EXCHANGE RATES
• For “rich” nations like Japan, US and Germany, the
official exchange rate GDP is a reasonable
approximation to the PPP exchange rate GDP
• The difference between the PPP exchange rate
and the official exchange rate will be higher for
poorer, less developed nations.
• Using the official exchange rate means an
underestimate of living standards in poorer
countries if measured using the currency of a richer
country.
REAL VS. NOMINAL
• When dealing with price data or interest
rate data be sure to differentiate between
nominal and real:
• Real Interest Rate = Nominal Interest Rate –
Inflation rate
E.g. bond yield = 6%
inflation = 2%
Real interest rate = 4%
• Real price = nominal price / price index
• Real price = nominal price / (1 + % Increase in
prices since base year)
REAL VS. NOMINAL
E.g price in (base) year 2000 = $50 (CPI = 100)
• Price in 2001 = $60
• Did you earn 20%?
• Inflation = 2% => (CPI = 102)
• Real price in 2001 is 60/1.02= 58.82
• Change in real price is $8.82 (17.84%)
WHAT BELONGS IN THE DATA SECTION
OF YOUR THESIS?
• An explanation of what data you are using
• Where did the data came from?
• What variables are measured? (this could be shown in a
Table of variable names and definitions)
• What time period is covered? Or, when was the data
collected?
WHAT BELONGS IN THE DATA SECTION
OF YOUR THESIS?
1. An explanation of what data you are using:
“The data in this study include daily closing price indices of
Shanghai A share (SHA), Shenzhen A share (SZA), Shanghai B
share (SHB), Shenzhen B share (SZB) and Hong Kong Hang
Seng China Enterprises Index H- Shares from the first quarter of
1992 through the fourth quarter of 2012.”
AN EXPLANATION OF THE DATA
YOU ARE USING:
“In order to test the hypotheses noted above, we use
measures of monetary aggregates, price levels and real GDP
from 23 European nations for the period 1998-2011. All data
are quarterly, except personal income, which was converted
to a quarterly average from monthly data. Variable names,
definitions and sources are reported in Table 1.”
“Data on mergers and acquisitions between U.S. corporations
were collected from Bloomberg using the following criteria:
…”
WHAT BELONGS IN THE DATA SECTION
OF YOUR THESIS?
2. A description of how you treated or modified the
data.
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Are there missing observations?
Are there outliers? How were they treated?
Did you convert nominal to real?
Did you convert monthly to quarterly (etc)?
Did you create new variables? (e.g indicator variables,
indices)
DESCRIBING HOW DATA WERE
TREATED
• “Firms in our sample have Standard Industrial Classification
(SIC) codes between 2830 and 2836. These firms discover,
develop, produce, and sell drugs for the treatment or
diagnosis of human diseases; 199 firms meeting this criterion
were initially identified; 29 firms were omitted due to
incomplete or inaccessible financial data and seven firms
were excluded due to incomplete or inaccessible clinical trial
data.”
DESCRIBING HOW DATA WERE TREATED
“Monthly returns of international equity indices were averaged
for the ten-year period 2000- 2010, and closing prices expressed
in local currency were used to compute returns.
For countries with more than one equity index, we select the
capitalization-weight index that best represents the country’s
overall stock market. We estimate volatility as the standard
deviation of the monthly stock index returns over the 2000-2010
sample period. We estimate the risk-adjusted return using the
Sharpe ratio calculated as:
Average return Index − Average Risk free rate
Sharpe Ratio =
σ
The numerator of the Sharpe ratio is the average excess return
over a risk-free benchmark. We use the average risk-free rate per
country from 2000 to 2009 which we retrieved from the United
Nations database. Homogeneous data were difficult to gather,
so for some countries, the money market rate was chosen as the
risk-free rate while for others we use the three month government
borrowing rate.”
WHAT BELONGS IN THE DATA SECTION
OF YOUR THESIS?
3. A description of the distribution of important
variables, including descriptive statistics.
• Be sure to note measures of central tendency, dispersion
and spread for key variables.
• Refer back to theory/hypotheses to justify the measurement
or inclusion of variables.
• Include a table of descriptive statistics
• Consider a histogram or (smoothed) series plot for your key
variable(s) of interest
DESCRIBING THE DISTRIBUTION
• “The typical size of boards of directors in our sample
is approximately eight individuals, with an average
of 3.45 business experts, 1.47 financiers and 1.3
medical doctors per board. There is an average of
nearly seven males in each group and roughly 42
percent of the boards in our sample are chaired by
the CEO. On average, boards contain
approximately 1.5 members who are current or
previous employees of the company.”
• “Our sample of divers contains 195 persons from
Tobago and 165 persons from Barbados.
Descriptive statistics are shown in Table 1. Divers in
the sample are predominantly male and highly
educated, mostly from the UK or the US.
Approximately 60 percent of the sample had visited
the island where they were diving on a prior
occasion, or had traveled to the Caribbean
previously. …
• … Divers reported encountering an average of less
than four other divers at the dive site and
approximately one-third of the sample reported
viewing no other divers at the site. Only 23 divers
(6.4 percent) reported viewing more than 11 other
divers at the site and only 4 divers (1 percent)
reported viewing more than 15 other divers.
IMPORTANT TABLES AND FIGURES
• Table: Variable Names and definitions (and sources?)
• Table: Descriptive statistics
• Table: Correlation coefficients
• Figure: Histogram for key variable(s)
• Figure: Smoothed time series plot for key variable(s)
• With more than 7.5 years of diving experience on
average, our sample contains many experienced
divers. Yet, 10 percent of the sample claimed zero
years of diving experience and 32 percent
indicated having no formal scuba certification. …
• … Following the approach of Dearden et al. (2006),
we construct a diver specialization index that
ranges from 0-10 a priori using responses to 7
questions in our survey. Scoring for the index is
shown in Table 2 and the frequency distribution of
index values is shown in Table 3.”
The Theory / Hypotheses Section
• The purpose of this section is to present a
theoretical analysis (the logical argument) of the
problem you are investigating.
• Explain how your problem can be viewed as an application
of relevant theory (econ theory?) or results from the
literature.
• Describe your theoretical model.
The Theory / Hypotheses Section
• Why is this section important?
• The purpose of any empirical investigation is to attempt to
validate a particular hypothesis (or set of hypotheses).
• It is therefore important that you communicate this
hypothesis to the reader so that they can put the results in
context.
EXAMPLE
Within the revealed preference literature, while there has
been considerable research investigating various
representations of expected catch (McConnell et al.
1995), there has been considerably less attention given to
expected congestion. Furthermore, the effects of
accounting for congestion on compensating variation
measures for changes in site quality or access price within
this framework have yet to be explored. To further illustrate
some of these important issues within the RUM framework,
consider the following explicit linear representation of the
conditional indirect utility function
Vij t + εij t = βtcij + δce jt + λqe jt + εij
(3)
where V is the conditional indirect utility for individual i, ce
and qe are the expected catch and congestion,
respectively, of visiting site j at time t, and the other
variables are defined above.
EXAMPLE
Real estate investor sentiment surrounding periods of recurring hurricane landfalls is
an attractive topic for research, especially in the area around Wilmington, NC, where
four hurricanes made landfall between 1996 and 1999. Adjacent to discoveries of a
real estate market “recovery” in this area of southeastern North Carolina since the
unprecedented series of hurricane landfalls in the late 1990’s, we test a series of
empirical expectations. First, we affirm the findings of Graham, Hall, and Schuhmann
(2007) where home prices rebound in the years following Hurricane Floyd, the last
major storm to hit the region in 1999. Second, we assemble metrics to proxy for
investor sentiment, and use those metrics to illustrate the market’s improving
sentiment since early this century.
The first metric we consider is the spread between listing and selling prices. Our
premise is that spreads between listing and selling prices increase as home-buyer
sentiment changes with perceptions of increased exposure to hurricanes and
catastrophic risk. This expanding spread is affirmed by Graham and Hall (2002).
Extending those findings, we expect the spread to narrow in the years following
Floyd. Home buyers become less willing to purchase at current prices, ceteris
paribus, due to expectations of increasing future hurricane losses. As a result, sellers
are forced to provide some price concession to compensate buyers for the
assumption of additional risk.
EXAMPLE
Based on results in the literature and economic theory of
demand, we hypothesize that tourism demand is a
function of the explicit and implicit costs of travel,
individual demographics and destination quality.
More formally, travel demand can be estimated as:
Log (vi/pi) = β0 + β1 TCi + β2 Qi + ∑ (βk∙Xk + … + βj∙Xj)
(1)
Where vi = total visits from zone i,
pi = population of zone i,
TCi = round trip travel cost from zone i (explicit + time
cost)
Qi = measure of coatal quality for respondents from
zone i (response or instrument), and
Xk … Xj = demographic characteristics of
respondents from zone i.
EXAMPLE
In order to examine the relationship between student
characteristics and economic knowledge
acquisition, scores on the economics portion of the
survey serve as the dependent variable. Note that
the pre and post survey results can be examined
individually or together by calculating the difference
in correct answers between the pre- and post-course
surveys. In the former case, the variable we wish to
explain is constrained to be zero or a positive integer,
hence a count data model will be appropriate for
estimation. In the latter, the variable of interest
(change in score) can be positive or negative; hence
more traditional regression methods will suffice for
estimation.
EXAMPLE CONT’D
Poisson regression models provide a standard framework for the analysis of count data when a
majority of the data falls in the lower end of the distribution (ie 0,1,2,..). The Poisson distribution
determines the probability of a count.
(1)
P(yi) = Prob[yi = j] = exp(-i) -ij / j!
, j = 0, 1, 2, …
Where the standard formulation for i is:
(2)
i = exp( ΄xi )
In order to examine the relationship between student characteristics and pre- and post-course
scores on the economics questions in our survey, we estimate the following equations using a
Poisson specification for both the pre-course survey results and the post-course results (variable
definitions are provided in Table 1):
(Model 1) Yi = 0 + 1(RSURVEYi)+ 2(BUSINESSi) + 3(OTHERi) + 4(HS ECONi) + 5(MACROi) + 6(MAC
HAD MICi) + 7 (MIC HAD MACi) + 8(MIC HAD SURVEYi) + 9(MAC HAD MIC AND SURVEYi) +
10(TMATHPREi or TMATHPOSTi) + 11(MWCi) + 12(UNCWi) + 13 (UNi)
and
(Model 2)
Yi = 0 + 1(RSURVEYi)+ 2(BUSINESSi) + 3(OTHERi) + 4(HSECONi) + 5(MACROi)
+ 6(MAC HAD MICi) + 7 (MIC HAD MACi) + 8(MIC HAD SURVEYi) + 9(MAC HAD MIC AND
SURVEYi) + 10(Q1i) + 11(Q2i) + 12(Q3i) + 13 (Q4i) + 14(Q5i) + 15(Q6i) + 16(Q7i) + 17(Q8i) +
18(MWCi) + 19(UNCWi) + 20(UNi).
METHODS
• The methods section may be combined with the
theory section or it may be combined with the data
section.
• “Theory and methods”
• “Materials and methods”
• In this section you specify the exact model that you
are going to estimate.
• E.g. “Using OLS regression, we estimate the following
version of equation (2):”
The Introduction
• The introduction is often one of the last things you
write (abstract will probably be the very last thing).