What makes a good presentation?
1. Structure
2. The slides
3. The talk
4. Miscellaneous
1
1. Structure
1. Presentation  paper
 motivation is most important!!!
(see Economic History presentations)
 present as few equations as possible
BM 
b0
(  3  )
a0


df (  ) 
b 
c1
  
0
bX  ( X X )
1
 df
( )
?
 emphasize the economic intuition
2
1. Structure
1. Presentation  paper
2. Rule of thumb:
Put yourself into the shoes of someone who
doesn’t know much about your topic, literature, details
Best example:
Recall how you felt during the most recent seminars
 implement what you liked
 avoid what put you to sleep
3
1. Structure
1. Presentation  paper
2. Rule of thumb
3. Outline of a good presentation:
1. “What is the point of being here?” (Motivation of your topic)
2. “When can I ask what question?” (Brief outline of your talk)
3. “What is new?”
(Very briefly relate your work to the existing
literature)
4. “What do I need to know to understand your results?”
(Describe the essential parts of your economic/econometric model)
5. “What should I learn from your talk?”
(Present, explain, and discuss your results)
4
2. The Slides
12 point font won’t do!
 ( Ip )  v 0  v ( Ip )  v 0   f ( Ip )  Ip
 v(I p )  f (I p )  I p ,
 p ( I p )  (1  p ) v ( I p )  f ( I p )  I p  pC T ( I p ).
dv ( I p )
dI
(1  p ) 
df ( I p )
dI
p
d ( I p )
dI
p
dC T ( I p )
dI
p
d ( I p )
dI
1 p
 0.
(1)
(2)
(3)
p
(4)
 0.
p
 p
dv ( I p )
dI
 0.
(5)
p
5
2. The Slides
12 point font won’t do!
The 4 most important rules
20 point font is the absolute minimum
28 point font is even better
Don’t do fancy things with
Don’t have too many slides
 10 – 12 slides maximum for a 40 minute presentation
Don’t overload your slides
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2. The Slides
If you need to show equations: make them simple!
mean loglikelihood ratio
Kernel of the
multinomial distribution
 3!
N re
mean LLR 
ln   ( p re )

913 e 1  r 1
1
913
3!

r 1
N re 
( q re )


observed shares
Elections
Rankings
Number of voters
predicted shares
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Don’t reproduce tables from your paper
Table 3. Assessment of six models of voter behavior
Analysis of observed
election data
Analysis of simulated data
(“impartial anonymous culture
assumption”)
Degrees of
freedom
Mean
LLR
Mean
WSSR
AIC
BIC
Mean
LLR
Mean
WSSR
(1)
(2)
(3)
(4)
(5)
(6)
(7)
Equally likely
rankings
0
-196.80
(4.26)
207.28
(4.42)
359,357
359,357
-535.12
(0.31)
581.00
(0.41)
Unequally likely
rankings
5
-31.15
(0.97)
32.45
(0.88)
56,890
56,922
-161.00
(0.15)
160.22
(0.17)
Borda model
913
-116.79
(2.72)
121.00
(2.78)
215,085
220,951
-367.14
(0.23)
363.84
(0.24)
Condorcet model
913
-84.99
(2.00)
88.36
(2.25)
157,018
162,885
-297.27
(0.20)
283.20
(0.20)
3,652
-0.87
(0.05)
0.97
(0.06)
8,893
32,360
-73.15
(0.11)
65.13
(0.09)
Spatial model
Notes:
1. Standard errors of estimate of the estimated means are shown in parentheses.
2. To facilitate comparisons, we have multiplied the statistics reported in Columns (3) and (7) by 1,000,000.
3. We calculated the AIC and BIC in Columns (4) and (5) using the LLRs in Column (2), which share the same denominator. Thus
the two measures of fit differ from the conventional measures by an additive constant.
4. To determine the BIC in Column (5), note that there are 5  913 – 1 = 4,564 degrees of freedom in the data.
8
Assessment of six models of voter behavior
Analysis of observed
election data
Analysis of simulated data
(“impartial anonymous culture”)
mean LLR
mean LLR
Equally likely
rankings (IC)
-196.80
(4.26)
-535.12
(0.31)
Unequally likely
rankings
-31.15
(0.97)
-161.00
(0.15)
Borda model
-116.79
(2.72)
-367.14
(0.23)
Condorcet model
-84.99
(2.00)
-297.27
(0.20)
Spatial model
-0.87
(0.05)
-73.15
(0.11)
Note: Standard errors of estimate of the estimated means in parentheses.
9
Assessment of six models of voter behavior
Analysis of observed
election data
mean LLR
Equally likely
rankings (IC)
-196.80
(4.26)
Unequally likely
rankings
-31.15
(0.97)
Borda model
-116.79
(2.72)
Condorcet model
-84.99
(2.00)
Spatial model
-0.87
(0.05)
Note: Standard errors of estimate of the estimated means in parentheses.
10
Assessment of six models of voter behavior
Analysis of observed
election data
Analysis of simulated data
(“impartial anonymous culture”)
mean LLR
mean LLR
Equally likely
rankings (IC)
-196.80
(4.26)
-535.12
(0.31)
Unequally likely
rankings
-31.15
(0.97)
-161.00
(0.15)
Borda model
-116.79
(2.72)
-367.14
(0.23)
Condorcet model
-84.99
(2.00)
-297.27
(0.20)
Spatial model
-0.87
(0.05)
-73.15
(0.11)
Note: Standard errors of estimate of the estimated means in parentheses.
11
2. The Slides
Don’t show anything on a slide that you
do not plan to discuss in your presentation
Don’t write out text in long paragraphs with
detailed definitions that your audience
cannot possibly digest at a single glance
because your explanation is too longwinded
and tedious.
 use short bullet points
 add verbal explanations
 use graphics when possible
12
3. The talk
Don’t read your slides!
Don’t read your slides!
Don’t read your slides!
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3. The talk
 the slides are for your audience, not for you
 slides should have only short bullet points
 write everything you plan to say on paper
… but don’t read your presentation from that paper
 practice your talk, with all your slides,
- in front of a mirror
- with your friends
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3. The talk
 only make things appear and disappear on
your slides if you know your presentation cold
 otherwise: show the entire slide
 don’t be afraid of questions
 If you cannot answer the question, say
“That is a good question. I haven’t thought about it yet.”
 Write the question down
and work on it when you are back in your office
15
3. The talk
 if you describe an equation, use the variable
names and not their symbols
C    Y
This is not “beta”
but “the marginal propensity to consume”
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3. The talk
 your audience is your friend, not your enemy
 speak loudly enough
 look at your audience, not at your shoes
 smile
 if you get nervous, imagine that everyone
in the audience is naked
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4. Miscellaneous
 arrive at least 15 minutes early to set up your
equipment
 have a backup plan in case something does
not work
 email your presentation to yourself
(in case the flash drive fails)
 bring a printout of your presentation
(to make transparencies if the computer fails)
 be prepared to talk even without your slides
(in case the projector fails)
18
Thank your audience
for coming!
It is bad if your presentation ends with “that’s it!”
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