Neljapäeval, 20. oktoobril 2022 toimus Eesti Panga avatud seminar, kus rahvusvaheliselt tunnustatud majandusteadlane Fabio Canova tutvustas koos Evi Pappaga valminud uurimustööd „Kulukad looduskatastroofid, energiatarbimine ning eelarvepoliitika“ (Costly disasters, energy consumption, and the role of fiscal policy).

1. Costly disasters, energy consumption,
and the role of fiscal policy
Fabio Canova and Evi Pappa
BI and UC3M/Warwick
October 2022

2. Number and costs of
climate related
disruptions have
increased over the last
20 years.
UN report “The Human
Cost of Disasters 2000-
2019”

3. Distribution of reported disasters (2000-2019, UN report)

4. Estimated insurance costs (2000-2019, UN report)

5. Questions
Are disasters associated with
output recessions and
unemployment increases?
How did (fiscal) policy respond?
Were recessions shorter
(smaller) when fiscal policy was
more pro-active? Was local
debt affected?
Should budget rules be
suspended after catastrophic
events? Should there be
budget stabilization funds for
disasters?
Similarities with COVID19
(Ukraine war): potentially large
and persistent strain on local
fiscal balance.
Financial stability issues added
if insurance companies fail.

6. Contribution
of the paper

7. National Oceanic
and Atmosphere
Administration,
(NOOA) disaster
data. Billion dollar
events: costs and
frequency; all
states

8. Geography of
disasters

9. Per-Capita
insurance
costs

10. Event study
exercise I
Trace out the spatial distribution of state macro
variables (scaled by the US average, normalized by pre-
desaster level) around disaster dates. Consider:
All events
Events destroying capital stock, affecting agriculture,
hurricanes only.
Costly events: more than 2200 dollars per capita or
more than 5% of GSP (32/33 episodes).
Events occurring in years with more than 10
calamities (1998, 2008, 2011-2013, 2015-2017).

11. All events (first row) and by type (next three rows)
-1 0 1 2 3
98
100
102
All
disasters
-1 0 1 2 3
98
100
102
Destroying
K
stock
-1 0 1 2 3
98
100
102
Severe
storms
-1 0 1 2 3
GSP
97
98
99
100
101
Hurricanes
-1 0 1 2 3
90
100
110
-1 0 1 2 3
90
100
110
-1 0 1 2 3
95
100
105
110
-1 0 1 2 3
Unemployment rate
90
100
110
-1 0 1 2 3
98
100
102
104
-1 0 1 2 3
98
100
102
104
-1 0 1 2 3
98
100
102
-1 0 1 2 3
State expenditure
98
100
102
104
-1 0 1 2 3
95
100
105
-1 0 1 2 3
95
100
105
-1 0 1 2 3
95
100
105
-1 0 1 2 3
State welfare transfers
95
100
105
-1 0 1 2 3
95
100
105
-1 0 1 2 3
95
100
105
-1 0 1 2 3
95
100
105
-1 0 1 2 3
Federal state transfers
96
98
100
102
104
106
-1 0 1 2 3
95
100
105
-1 0 1 2 3
96
98
100
102
104
106
-1 0 1 2 3
96
98
100
102
104
106
-1 0 1 2 3
State debt
96
98
100
102
104
106
-1 0 1 2 3
98
100
102
104
-1 0 1 2 3
98
100
102
104
-1 0 1 2 3
98
100
102
104
-1 0 1 2 3
State revenue
98
100
102
-1 0 1 2 3
98
100
102
-1 0 1 2 3
98
100
102
-1 0 1 2 3
98
100
102
-1 0 1 2 3
Personal income
97
98
99
100
101
Median 25percent 75percent

12. Events with very large costs
-1 0 1 2 3
99
100
101
102
103
104
Per-capita
costs
-1 0 1 2 3
GSP
99
100
101
102
103
104
105
106
Per-GSP
costs
-1 0 1 2 3
90
95
100
105
-1 0 1 2 3
Unemployment rate
85
90
95
100
105
-1 0 1 2 3
98
100
102
104
106
-1 0 1 2 3
State expenditure
98
99
100
101
102
103
104
105
106
-1 0 1 2 3
94
96
98
100
102
104
106
-1 0 1 2 3
State welfare transfers
92
94
96
98
100
102
104
106
108
-1 0 1 2 3
96
98
100
102
104
106
108
110
112
-1 0 1 2 3
Federal state transfers
98
100
102
104
106
108
110
112
-1 0 1 2 3
94
96
98
100
102
104
106
108
-1 0 1 2 3
State debt
94
96
98
100
102
104
106
108
110
-1 0 1 2 3
97
98
99
100
101
102
103
104
-1 0 1 2 3
State revenue
96
97
98
99
100
101
102
103
104
-1 0 1 2 3
98
99
100
101
102
103
104
-1 0 1 2 3
Personal income
99
100
101
102
103
104
105
Median 25percent 75percent

13. Events at special times and special location
-1 0 1 2 3
100
102
104
106
108
Years
with
at
least
10
disasters
-1 0 1 2 3
GSP
98
98.5
99
99.5
100
100.5
101
101.5
102
South-east
states
-1 0 1 2 3
90
95
100
105
110
115
120
125
130
-1 0 1 2 3
Unemployment rate
90
95
100
105
110
-1 0 1 2 3
98
100
102
104
106
108
110
-1 0 1 2 3
State expenditure
98
99
100
101
102
103
104
105
-1 0 1 2 3
95
100
105
110
115
-1 0 1 2 3
State welfare transfers
95
100
105
110
-1 0 1 2 3
100
105
110
115
-1 0 1 2 3
Federal state transfers
98
100
102
104
106
108
-1 0 1 2 3
95
100
105
110
115
120
-1 0 1 2 3
State debt
96
98
100
102
104
106
108
-1 0 1 2 3
100
102
104
106
108
110
-1 0 1 2 3
State revenue
98
99
100
101
102
103
104
-1 0 1 2 3
100
101
102
103
104
105
106
-1 0 1 2 3
Personal income
99
100
101
102
103

14. Quarterly data

15. Punchline:
Large cross-state
dynamic
heterogeneity
following
disasters.
Unrelated to:

17. IV-Local
projection
exercise
Measure state macro variables responses (scaled by the US
average) to a disaster cost shock:
All events, state by state.
Conditional regression of y(t+h), h=-1,0,1,2,3 on the costs
(instrumented by a cost shock), rather than a dummy.
State conttols included.
Disaster cost shock proxy for an unexpected disruption
of the capital stock. Computed using a lag of costs and a
regional and a US factor

18. Responses to disaster cost shocks, per-capita costs
0 1 2 3 4
GSP
-6
-4
-2
0
2
4
6
10
-3
0 1 2 3 4
Urate
-0.015
-0.01
-0.005
0
0.005
0.01
0.015
0 1 2 3 4
State G
-5
0
5
10
-3
0 1 2 3 4
State Welfare
-0.015
-0.01
-0.005
0
0.005
0.01
0 1 2 3 4
Federal Tansfer
-0.01
-0.005
0
0.005
0.01
0.015
0 1 2 3 4
State Debt
-0.01
-0.005
0
0.005
0.01
0 1 2 3 4
State Revenue
-5
0
5
10
-3
0 1 2 3 4
Personal Income
-6
-4
-2
0
2
4
10
-3
zero mean lower range upper range

19. Punchline:
Still a large
heterogeneity
in response to
the disaster.

20. Responses to disaster costs shocks, per-capita costs, conditional on energy
0 2 4
GSP
-6
-4
-2
0
10
-3
0 2 4
Urate
0
0.01
0.02
0.03
0 2 4
State G
0
5
10
15
10
-3
0 2 4
State Welfare
-4
-2
0
2
10
-3
0 2 4
Federal Tansfer
0
0.02
0.04
0 2 4
State Debt
0
5
10
15
10
-3
0 2 4
State Revenue
0
5
10
10
-3
0 2 4
Personal Income
-4
-2
0
10
-3
0 2 4
e-consumption
-0.02
-0.015
-0.01
-0.005
0
0 2 4
e-residential
-10
-5
0
10
-3
0 2 4
e-commercial
-0.02
-0.01
0
0.01
0.02
0 2 4
e-industrial
-0.04
-0.03
-0.02
-0.01
0
0 2 4
e-transport
-8
-6
-4
-2
0
2
4
10
-3
zero
mean
Lower range
Upper range

21. Which are the states with negative energy responses?

22. Why is energy
consumption
falling in some
states but not in
others?
Investigate three
hypotheses:
• Vulnerability and poor
maintenance of power
facilities.
• Home ownership vs. rental.
• National Flood Insurance
Policy (NFIP) and special state
insurance programs.

24. Power grid modernization rankings

26. Flood cost
not included
in home
insurance.
Earthquake
damages
either.

27. State and
Federal
government
insurance
programs

28. What state
characteristics
explain the
differences in
energy response to
disaster shocks ?

29. Characteristics that
DO NOT explain
differences in
energy response to
disaster shocks?

30. Does the the
fiscal framework
matter for the
way the state
economy respond
to disasters?
• Tight vs. loose budget (debt)
restrictions states.
• Existence of budget stabilization
(rainy days funds) or not.

31. Responses to disaster shocks, negative energy responses
0 2 4
-0.015
-0.01
-0.005
0
Budget
restrictions
0 2 4
GSP
-10
-5
0
5
RDF
10
-3
0 2 4
-0.01
0
0.01
0.02
0.03
0.04
0 2 4
U rate
0
0.01
0.02
0.03
0.04
0.05
0.06
0 2 4
0
2
4
6
8
10
12
14
16
10
-3
0 2 4
State G
-5
0
5
10
15
10
-3
0 2 4
-20
-15
-10
-5
0
5
10
-3
0 2 4
State Welfare
-6
-4
-2
0
2
4
6
8
10
10
-3
0 2 4
-0.01
-0.005
0
0.005
0.01
0.015
0.02
0.025
0 2 4
Federal Tansfer
-0.01
-0.005
0
0.005
0.01
0.015
0.02
0.025
0.03
0 2 4
-2
0
2
4
6
8
10
12
14
10
-3
0 2 4
State Debt
0
5
10
10
-3
0 2 4
-5
0
5
10
15
20
25
10
-3
0 2 4
State Revenue
-15
-10
-5
0
5
10
-3
0 2 4
-10
-5
0
5
10
-3
zero
LowBB-u
LowBB
LowBB-l
HighBB-u
HighBB
HighBB-l
0 2 4
Personal Income
-0.01
-0.005
0
0.005
0.01
0.015
zero
noRDF-u
noRDF
noRDF-l
RDF-u
RDF
RDF-l

32. Does the way
fiscal policy
reacts to the
disasters
matters?
• High vs. low state expenditure
reaction.
• High vs. low federal transfers
reaction.

33. Responses to disaster cost shocks, negative energy responses. High vs low
state expenditure
0 1 2 3 4
GSP
-0.01
-0.005
0
0.005
0.01
0 1 2 3 4
Urate
-0.01
0
0.01
0.02
0.03
0.04
0 1 2 3 4
State G
0
5
10
15
20
10
-3
0 1 2 3 4
State Welfare
-10
-5
0
10
-3
0 1 2 3 4
Federal Tansfer
0
0.02
0.04
0.06
0 1 2 3 4
State Debt
0
0.01
0.02
0.03
0 1 2 3 4
State Revenue
-5
0
5
10
15
20
25
10
-3
0 1 2 3 4
Personal Income
-5
-4
-3
-2
-1
0
1
10
-3
zero R-Small G R-Small G-l R-Small G-u R-Large G R-Large G-l R-Large G-u

34. Responses to disaster cost shocks, negative energy responses. High vs low
federal transfers
0 1 2 3 4
GSP
-20
-15
-10
-5
0
5
10
-3
0 1 2 3 4
Urate 1
0
0.01
0.02
0.03
0 1 2 3 4
State G
0
0.005
0.01
0.015
0 1 2 3 4
State Welfare
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
0 1 2 3 4
Federal Tansfer
0
0.02
0.04
0.06
0.08
0 1 2 3 4
State Debt
-0.005
0
0.005
0.01
0.015
0.02
0.025
0 1 2 3 4
State Revenue
0
5
10
15
10
-3
0 1 2 3 4
Personal Income
-10
-5
0
10
-3
zero R-Small F R-Small F-l R-Small F-u R-Large F R-Large F-l R-Large F-u

35. Conclusions

36. APPENDIX

37. Estimated costs for 2021

38. 8 out of 10
most expensive
natural
disasters are
hurricanes

39. Disasters
costs and
frequency,
Gulf States

40. Disasters
costs and
frequency;
Tornado
Alley

41. Costs and
frequency by
state: Illinois

42. Costs and
frequency
by state:
California

44. State
macroeconomic
data
Unemployment rate

45. State and local
government
data 1980-2017
U.S. CENSUS
BUREAU
PUBLICATIONS
ON
GOVERNMENT
FINANCES

46. Event study econometric model
𝑦𝑦𝑖𝑖,𝑡𝑡+ℎ = 𝑎𝑎𝑖𝑖,ℎ𝑥𝑥𝑖𝑖,𝑡𝑡 + 𝑒𝑒𝑖𝑖,𝑡𝑡+ℎ
𝑖𝑖 = state, 𝑡𝑡 =time, ℎ =horizon; 𝑦𝑦𝑖𝑖,𝑡𝑡+ℎ, variables of
interest (scaled relative US average, normalized at t-1
level); 𝑥𝑥𝑖𝑖,𝑡𝑡 is the disaster per-capita (per-gsp) dummy
at time t for state i.

47. Event study
exercise II
Equivalent to running a regression of y(t+h) h=-
1,0,1,2,3 on a dummy for the year that there
is an event, state by state, without constant or
controls.
Why not use diff-in-diff? Units may be treated
or controlled at different time. There is a spatial
and temporal pattern in the treatment (it is
not random).
Post-treatment average dynamics messed
around. (Sun and Abraham, 2021).

48. Events in high debt states

49. Events in states with mainly democratic governor

50. Events in states voting democratic president

51. Texas

52. Zooming in on selected states

53. LP exercise: the econometric model
-
𝑦𝑦𝑖𝑖,𝑡𝑡+ℎ = 𝑎𝑎𝑖𝑖,ℎ + 𝑐𝑐𝑖𝑖,ℎ𝑤𝑤𝑖𝑖,𝑡𝑡−1 +𝑏𝑏𝑖𝑖,ℎ𝑦𝑦𝑖𝑖,𝑡𝑡−1 + 𝑑𝑑𝑖𝑖,ℎ𝑥𝑥𝑖𝑖,𝑡𝑡 + 𝑒𝑒𝑖𝑖,𝑡𝑡+ℎ
𝑖𝑖 = state, 𝑡𝑡 =time, ℎ =horizon; 𝑦𝑦𝑖𝑖,𝑡𝑡+ℎ, variables of interest (scaled relative US average); 𝑥𝑥𝑖𝑖,𝑡𝑡 is
the disaster per-capita cost at time t for state i; 𝑤𝑤𝑖𝑖,𝑡𝑡−1 are controls (at least, scaled state
output, scaled state unemployment).
- Instruments: 𝑧𝑧𝑖𝑖,𝑡𝑡=(1, 𝑤𝑤𝑖𝑖,𝑡𝑡−1,ℎ, 𝑦𝑦𝑖𝑖,𝑡𝑡−1, 𝑢𝑢𝑖𝑖,𝑡𝑡).
- 𝑢𝑢𝑖𝑖,𝑡𝑡 obtained from (𝑓𝑓𝑡𝑡 = spatial factor):
𝑥𝑥𝑖𝑖,𝑡𝑡 = 𝛼𝛼𝑖𝑖 + 𝛽𝛽1𝑖𝑖𝑥𝑥𝑖𝑖𝑖𝑖−1 + 𝛽𝛽2𝑖𝑖𝑓𝑓𝑡𝑡 + 𝑢𝑢𝑖𝑖,𝑡𝑡
- Normal prior on (ai,h, bi,h, , ci,h, di,h) with zero mean and fixed variance (IV ridge estimator).
- Use a diffuse prior on (𝛼𝛼𝑖𝑖, 𝛽𝛽𝑖𝑖).
- Unit by unit estimation (no pooling because of heterogeneity), see Canova (2021).

59. Home ownership US
64.1%
65.1%
67.5%
68%
68.3%
68.6%
69.2%
69% 68.9%
67.8%
67.5%
67.2%
66.5%
66%
65.4%
65.2%
64%
63.8% 63.7%
64.2%
64.8%
65.1%
65.8%
65.5%
63.0%
64.0%
65.0%
66.0%
67.0%
68.0%
69.0%
70.0%
1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Homeownership
rate

61. Home insurance industry
41.11
35.49
39.92
41.24
44.39
56.48 56.25
54.08
63.85
0
10
20
30
40
50
60
70
2012 2013 2014 2015 2016 2017 2018 2019 2020
Loss
in
billion
U.S.
dollars
Note(s): United States; 2012 to 2020
Further information regarding this statistic can be found on page 39.
Source(s): Insurance Information Institute; SNL Financial; ID 428998
11
Incurred losses for homeowner insurance in the United States from 2012 to 2020 (in billion U.S.
dollars)
Incurred losses for homeowner insurance in the U.S. 2012-2020

64. Home ownership by ethnicity
75.4%
76% 75.8% 75.8%
75.2% 75% 74.8% 74.4%
73.8% 73.5% 73.3%
72.6%
71.9% 71.9% 72.3%
73% 73.3%
75%
46.7%
48.1%
49.5% 49.7% 49.7%
49.1%
48.4%
47.5%
46.9%
46.1% 46.1%
45.4% 45.6% 46% 46.2%
47.1% 47.5%
50.1%
48.8%
49.7%
48.8% 48.4%
47.8% 47.9%
46.6%
45.9% 45.4%
44.6%
43.8% 43.8%
43%
42.2%
43.1% 42.9% 42.8%
45.9%
56.7%
59.6%
60.4%
61.1%
60.3% 59.8% 59.7%
58.8%
58%
56.9%
57.6% 57.8%
56.5%
55.5%
57%
58.3%
57.5%
60.7%
58%
60.4%
59.8% 59.9%
59%
57.8%
56% 55.6%
54.9%
55.7%
53.5%
51.7%
50.8%
49.2%
50.3%
51%
52.2%
53.2%
35%
40%
45%
50%
55%
60%
65%
70%
75%
80%
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Homeownership
rate
White Hispanic Black Other race Two or more races

69. Policy frontiers