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ECON7950 Research Methods in Economics
Assessment 2 – Reverse Pitch
Instructions and Marking Criteria
Overview
Once we identify a list of useful literature for our research, the next step is to concentrate on
one (or sometimes two) “really relevant” piece of literature on which we will base our
research. Very often, new research work is done by putting a “twist” to the existing literature.
The twist can be a change in assumptions, a different stratification of data, imposing extra
restrictions, adding different dimensions, using a different methodology… etc. However, to
be able to put a meaningful twist to a piece of literature, we need to understand that piece
of literature well – inside-out well.
There are many ways to achieve this in-depth understanding. For this course, we will use the
Reverse Pitching method. Reverse Pitching refers to the reverse engineering of the research
pitch of an existing research study. It deconstructs the existing research study into its primary
elements, and in particular, its research questions and how the author(s) answer(s) them. This,
in turns, can help you pose your own research question in a more specific way, as well as
finding a feasible method to tackle the question.
As an assessment of ECON7950, this assessment also gives you an experience in research
pitching. This time, you don’t need a research plan of your own – yet. By seeing how other
researchers could have pitched their research, you can then pitch your own next time!
Your Task
Choose one research study from your Annotated Bibliography (Assessment 1)1 and make a
written reverse research pitch using the template in the same folder as this instruction.
Your reverse pitch should include:
A. The complete reference details of the research study you are reverse pitching
Give the full reference details of the research study you are reverse pitching in APA
style.
B. Basic research question
In one (1) sentence, define the key features of the research questions.
C. Key papers
Identify the three (3) keys paper which most critically underpins the topic. You can
simply give their full reference details (again, APA).
D. Motivation/Puzzle
In one (1) short paragraph (about 100 words), capture the core academic motivation
– which may include identifying a “puzzle” that the authors hope to resolve.
E. Idea
Identify the “core” idea that drives the intellectual content of this research topic.
In three (3) to six (6) bullet points (about 100—150 words):
For theory research:
1 If you have changed/updated your research question since you turned in your first assessment, you can pick a
research study that was not included in your annotated bibliography. But for your own sake, the research
study should be related to your new research question, or at the very least, be “interesting” for you.
- Note significant innovation in assumptions, if any.
- Articulate the main theorem and the main intuition/strategy of proof of
the main theorem.
For experimental research:
- Articulate the central hypothesis(es).
- Identify the key dependent (“explained”) variable(s) and describe the
control and treatment(s).
For research using secondary data:
- Identify the key dependent (“explained”) variable and the key
test/independent (“explanatory”) variable(s).
- What is the identification strategy? (E.g., natural experiment, regression
discontinuity, instrumental variables, structural estimation, etc.)
If the research study has a mix of the above, you should identify the core idea from
each part.
F. Data
Describe, if appropriate, in three (3) to six (6) bullet points (about 100—150 words):
For research with secondary data:
- What data are used? E.g., Country/setting; unit of analysis (e.g.,
individual/firms/sectors/countries, etc).; sampling period and sampling
interval (e.g., daily, monthly, quarterly, etc.).
- Sample size and sampling nature (e.g., cross-section, time-series,
balanced/unbalanced panel, etc.)
- Data sources – publicly available vs. propriety data, are they collected by
the researchers, are they novel new data?
- Possible problems with the data (e.g., missing data, database merging
issues, decisions on how to handle “irregular” cases)
For research with experimental data:
- When and where are the experiments run? Are they laboratory
experiments, field experiments or others?
- What is the subject pool?
- How are the experiments run? Computer-based? Experimenter
observations? Interviews? Are real effort tasks involved?
- Are the experiments individual or do they involve group interactions? If the
later, how are subjects matched? (E.g., do they stay in the same match
throughout the same experiment, or are they rematched every period?
How many matching groups are there?)
- Is/are the treatment(s) within-subjects or between-subjects? If a subject
experiences multiple treatments, how is the order of treatments
determined?
- Any other relevant concerns about the experiments or subjects. (E.g.,
whether certain measures are incentivised.)
For theory research (i.e., research with no “real” data):
- Simulation or calibration “data”, if any
- Motivating examples for the theory model
- Hypothetical examples to which the proposed theory/solution/model can
be applied (better than competing theories)
- Anecdotal or “stylised” observations that matches the model’s prediction
(better than competing theories)
If the research is a mixed of the above, describe the part that contains actual data.
(That is, if it is theoretical research with some actual data, describe the actual data.)
G. Tools
Describe, if appropriate, in three (3) to six (6) bullet points (about 100—150 words):
For research with secondary data:
- The basic econometric model (e.g., linear regression, two-stage least
squares, maximum likelihood, etc.)
- Any econometric techniques in over-coming data obstacles
- Econometric techniques considered for robustness check (but be brief!)
For research with experimental data:
- Tools for eliciting certain information (e.g., Holt-Laury for risk preference)
- Any experimental design that is specific to the type of experiments run
- Statistical tools used for analysing the data
For theory research (i.e., research with no “real” data):
- The type of model (e.g., static, dynamic, network, etc.)
- The type of the proof, if any (e.g., induction, construction, by contradiction)
- Notable mathematical/statistical theorems used
If the research study has a mix of the above, you should identify the core idea from
each part.
H. What’s New
In two (2) to four (4) sentences (about 50—100 words), indicate the novelty of the
research. Is the novelty in the idea/data/tools? Which is the main “driver” of the
novelty? Is it being limited by some other elements?
I. So what?
In two (2) to four (4) sentences (about 50—100 words), state the “policy implications”
of the research. Why is it important to know the answer? How will major
decisions/behaviour/activity etc be influenced by the outcome of this research?
J. Contribution
In two (2) to four (4) sentences (about 50—100 words), describe the main contribution
of the research work to the relevant literature.
K. Three key findings
In three sentences (or bullet points), briefly list the three key findings or takeaways
for the paper. Briefly indicate whether these come directly from what the authors
claim or alternatively that they, to some degree, come from your perspective framed
on your research potential plans/interests.
Resources
You can find a self-paced learning module (or simply powerpoint slides) on reverse pitching,
as well as examples of reverse pitches on https://pitchingresearch.com/resources/ (module
3).
Since there are some good examples there, I will not provide examples in this instruction
sheet. (Plus, that will be too long.)
See also the FAQ’s on Blackboard (in the same folder as this instructions).
Format
You should use the Template for Reverse Pitching (downloadable from the course Blackboard
site, in the same folder as this instruction) for this assessment. The Reverse Pitching template
is similar to the Pitching Research template (introduced in Lecture 4), but with some
differences – so please use the correct template! There is a cued template (which includes
prompts for you) and an empty template (which you can directly type your pitch in). If you
are using a cued template, please delete the cues before submission.
You have a word limit of 1000 words (plus or minus 20%). Marks will not be deducted for
pitches below 800 words per se (conciseness is a virtue), however, if the lack of words means
little information is conveyed, you will likely be hurt on some marking criteria. On the other
hand, marks can be deducted for extraneous pitches.
The following guide provides a rough “words budget” for each item. This is just a guide – the
words count for each part may vary depending on the research study you are reverse pitching
(e.g., theory papers should get less on “data”).
Item Suggested words budget
A. Full Reference 20—25 words
B. Basic Research Question 20—30 words (1—2 sentences)
C. Key papers 60—70 words (3 full references)
D. Motivation/Puzzle 150—200 words (4—6 sentences or bullet points)
E. Idea 100—150 words (3—6 bullet points)
F. Data 100—150 words (3—6 bullet points)
G. Tool 100—150 words (3—6 bullet points)
H. What’s new 50—100 words (2—4 sentences)
I. So what? 50—100 words (2—4 sentences)
J. Contribution 50—100 words (2—4 sentences)
K. Three key findings 50—100 words (3 sentences or bullet points)
Submission
Submit your completed annotated bibliography electronically to Turnitin through the link on
the course Blackboard site before Thursday, 5th October 2023 4:00pm Brisbane time.
Requests for the granting of extensions must be made online
Extensions cannot exceed the number of days you suffered from a medical condition, as
stated on the medical certificate.
Where an extension has not been previously approved, a penalty of 10% of the maximum
possible mark allocated for the assessment item will be deducted per day for up to 7 calendar
days, at which point any submission will not receive any marks unless an extension has been
approved. Each 24-hour block is recorded from the time the submission is due.
Marking Criteria
Criteria Maximum possible marks
Language and style
• Accuracy and consistency in referencing
• Clarity and quality of written expression
5
Focus and coherence
• Clarity of focus and inter-connectedness of entri
- 经济Economics
- 金融Finance
- 会计Accounting
- 工商管理Business Management
- 计算机computer science
- 商业分析business analysis
- 法律Law
- 管理Management
- 市场营销Marketing
- 哲学Philosophy
- 心理学Psychology
- 物理Physical
- 统计学statistics
- 电气工程electric engineering
- 化学chemistry
- 生物biology
- 数学mathematics
- 语言学linguistics
- 土木工程civil engineering
- 工程力学engineering mechanics
- 艺术art
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