graphics for macroeconomics. principles graphing is done best when it clearly communicates ideas...
TRANSCRIPT
Graphics for Macroeconomics
Principles
• Graphing is done best when it clearly communicates ideas about data
• Focus on the main point while preventing distractions
Volatility
• Volatility makes it hard to see trends– Example from coin data
Figure 7Total Net Pay
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003
Date
Bil
lio
ns
of
coin
s
Figure 7Total Net Pay (12-month moving average)
0
0.5
1
1.5
2
2.5
1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003
Date
Bil
lio
ns
of
coin
s
Figure 7Total Net Pay
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003
Date
Bil
lio
ns
of
coin
s
Figure 3.3Annual Demand for New Coins
0
5
10
15
20
2519
59
1962
1965
1968
1971
1974
1977
1980
1983
1986
1989
1992
1995
1998
2001
Date
Bill
ion
s o
f co
ins
Scatter plots
• Scatter plots help you see the relationship between variables
• Time series plots vs. scatter plots
Consumption and Income
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
1947
1950
1953
1956
1959
1962
1965
1968
1971
1974
1977
1980
1983
1986
1989
1992
1995
1998
2001
2004
Date
Bil
lio
ns
of
20
00
do
lla
rs
Real PersonalDisposable Income
Real Consumption Expenditures
Time-series plot
Consumption & Income
0.0
1000.0
2000.0
3000.0
4000.0
5000.0
6000.0
7000.0
8000.0
9000.0
0.0 1000.0 2000.0 3000.0 4000.0 5000.0 6000.0 7000.0 8000.0 9000.0
Income (billions of 2000 dollars)
Co
nsu
mp
tio
n (
bill
ion
s o
f 20
00 d
olla
rs)
Scatter Plot
V2 & Opportunity Cost
-6
-5
-4
-3
-2
-1
0
1
2
1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001
Date
log
(V
2) &
lo
g (
OC
2MA
)
V2
Log (Opportunity Cost)
Time-series plots on same scale
V2 & Opportunity Cost
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
-6 -5.5 -5 -4.5 -4 -3.5 -3 -2.5 -2
Log (Opportunity Cost)
Lo
g (
V2)
Scatter plot
V2 & Opportunity Cost (1959Q3-1990Q4)
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
-6 -5.5 -5 -4.5 -4 -3.5 -3 -2.5 -2
Log (Opportunity Cost)
Lo
g (
V2)
V2 & Opportunity Cost (1991Q1-2002Q2)
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
-6 -5.5 -5 -4.5 -4 -3.5 -3 -2.5 -2
Log (Opportunity Cost)
Lo
g (
V2)
Elements of Graphical Style
• Know your audience & know your goals
• Show the data and appeal to the viewer– Minimize non-data ink– Avoid chart junk
• Revise and edit, again and again
Non-data ink
V2 & Opportunity Cost (1991Q1-2002Q2)
0.5757515350.5769643910.5818889660.589998097
0.5980613730.612308964
0.6215451180.634236405
0.6448874580.6519155380.655360665
0.6705993890.680683197
0.6962442740.70759967
0.7249136430.7347066670.731518180.7258282360.7294754930.730741368
0.7386243760.7383458120.7437971680.749863730.7573885620.754695620.7495421920.748614004
0.7387424840.7337964550.7262206750.7207223540.7155877490.715515828
0.7222989570.7215927150.7243511130.7148240430.707762182
0.691240894
0.66963651
0.64733339
0.6294975940.6308009330.627905563
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
-6 -5.5 -5 -4.5 -4 -3.5 -3 -2.5 -2
Log (Opportunity Cost)
Lo
g (
V2) Note that after 1990, the pattern of
velocity and opportunity cost changed significantly, with a couple of years of transition and a new pattern to the slope. The new intercept was much higher than the old one and thus the relationship changed so that it was much more difficult to use the model for forecasting.
1959
1962
1965
1968
1971
1974
1977
1980
1983
1986
1989
1992
1995
1998
2001
National Net Pay
0
5
10
15
20
25
Bill
ion
s o
f co
ins
Date
Figure 3.3Annual Demand for New Coins
Chartjunk
Chartjunk
• Don’t use 3 dimensions for a 2-dimensional object
• Don’t add decorations, cartoons, etc. that do not tell your story
Hi, I’m irrelevant!
Make graphs tell your story
• The golden ratio of height to width is 0.618
• Use scale to show variations in a variable
log(V2)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001
Date
log
(V
2)
Velocity is very stable
log(V2)
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001
Date
log
(V
2)
Or is it unstable?
Use colors to split data
Figure 18.18The Shifting Short-Run Phillips Curve
-4
-2
0
2
4
6
8
10
12
14
16
0 2 4 6 8 10 12
Unemployment Rate
Infl
atio
n R
ate
PC(1948-1965, 1997-2003)
PC(1984-1996)
PC(1974-1983)
Beware of Outliers
• Measurement outliers– Data errors
• Innovation outliers– A shock or innovation
Figure 18.6Unemployment Rate
0
2
4
6
8
10
12
19
60
19
61
19
62
19
63
19
64
19
65
19
66
19
67
19
68
19
69
19
70
19
71
19
72
19
73
19
74
19
75
19
76
19
77
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78
19
79
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80
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81
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82
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83
19
84
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85
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86
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87
19
88
19
89
19
90
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91
19
92
19
93
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94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
Date
Un
em
plo
ym
ent
rate
(p
erc
en
t)
Figure 18.19Expectations-Augmented Phillips Curve from 1960 to 2003
-4
-2
0
2
4
6
8
-4 -3 -2 -1 0 1 2 3 4
Unemployment Gap
Infl
atio
n S
urp
rise
1973
1974
1979
Excess Reserves
0
2
4
6
8
10
12
14
16
18
20
Jan-90
Jan-91
Jan-92
Jan-93
Jan-94
Jan-95
Jan-96
Jan-97
Jan-98
Jan-99
Jan-00
Jan-01
Jan-02
Jan-03
Jan-04
Date (monthly data)
$ b
illio
ns
Adding recession bars
• See instruction sheet; useful to keep around
Figure 10.10Output Growth and the Unemployment Rate
Quarterly, 1949:Q3 to 2003:Q4
-4
-2
0
2
4
6
8
10
12
14
194
91
950
195
11
952
195
31
954
195
51
956
195
71
958
195
91
960
196
11
962
196
31
964
196
51
966
196
71
968
196
91
970
197
11
972
197
31
974
197
51
976
197
71
978
197
91
980
198
11
982
198
31
984
198
51
986
198
71
988
198
91
990
199
11
992
199
31
994
199
51
996
199
71
998
199
92
000
200
12
002
200
3
Date
Rea
l GD
P G
row
th R
ate
(per
cen
t)
0
2
4
6
8
10
12
Un
emp
loym
ent
Rat
e (p
erce
nt)
Economic Liftoff Reorganization Long Boom
Unemployment Rateright scale
Real GDP Growth Rate left scale
Figure 10.10Output Growth and the Unemployment Rate
Quarterly, 1949:Q3 to 2003:Q4
-4
-2
0
2
4
6
8
10
12
14
194
91
950
195
11
952
195
31
954
195
51
956
195
71
958
195
91
960
196
11
962
196
31
964
196
51
966
196
71
968
196
91
970
197
11
972
197
31
974
197
51
976
197
71
978
197
91
980
198
11
982
198
31
984
198
51
986
198
71
988
198
91
990
199
11
992
199
31
994
199
51
996
199
71
998
199
92
000
200
12
002
200
3
Date
Rea
l GD
P G
row
th R
ate
(per
cen
t)
0
2
4
6
8
10
12
Un
emp
loym
ent
Rat
e (p
erce
nt)
Economic Liftoff Reorganization Long Boom
Unemployment Rateright scale
Real GDP Growth Rate left scale
Graphs as diagnostics for regressions
• Plot actual and fitted values; residuals over time
• Plot residuals squared or absolute values of residuals over time (solutions: interactive data analysis)
• Do a scatter plot of residual vs. explanatory variable
Example: consumption & income
• We can save residuals and do plots of residuals themselves, actual & predicted, residuals vs. explanatory variables
• Later, using saved residuals, we can plot squares and absolute values
• Note that non-random residuals suggests that a non-linear model may be better
Plotting from FRED
• FRED graphs are nice
Plotting from FRED
• Sometimes you need to make your own graphs
• Download FRED data to make graph
• What’s wrong with this graph?
Critique this graph
• No title
• Bad dates
• Trailing zeroes on y axis
• Legend takes up too much space
Time-Series Graphs
• Choose a scale to make the graph informative– Especially levels vs. growth rates– Which is best depends on purpose
• Sometimes best to show level for long-term issues• Other times best to show growth rate for cyclical
issues
Nominal or Real?
• Nominal variables of economic activity should never be plotted– You don’t know what is real activity and what
is caused by higher prices– Only plot nominal variables for which it makes
sense to do so: money supply, price level– Example: plot real GDP, not nominal GDP– Example: plot ratios of nominal variables,
such as government debt/GDP
